self-learning control system and method for optimizing a consumable input variable

专利摘要:
self-learning control system and method for optimizing a consumable input variable control system for an operable system such as a flow control system or temperature control system. The system operates on a control circuit to constantly update a model against at least one optimizable input variable based on the detected variables. The model provides a prediction of the use of input variables in all possible paths or operating points of system variables that obtain an output setpoint. In some examples of configurations, the control circuit is performed during the initial configuration and subsequent operation of one or more operable elements in the operable system. The control system is self-learning in the sense that at least some of the initial and subsequent system parameters are automatically determined at runtime.
公开号:BR112015013494A2
申请号:R112015013494
申请日:2013-11-13
公开日:2019-12-24
发明作者:Javier Acosta Gonzalez Marcelo
申请人:S A Armstrong Ltd；
IPC主号:

专利说明:

SELF-LEARNING CONTROL SYSTEM AND METHOD FOR OPTIMIZING A VARIABLE INPUT OF CONSUMABLES
CROSS REFERENCE TO RELATED APPLICATIONS [0001] This application claims the priority benefit of United States Provisional Patent Application No. 61 / 736,051 filed on December 12, 2012, entitled COORDINATED CONTROL SYSTEM WITHOUT SENSOR, and the Provisional Patent Application of the United States No. 61 / 753,549 filed on January 17, 2013, entitled SYSTEM GIVE CONTROL OF SELF-LEARNING AND METHOD TO OPTIMIZE A CONSUMABLE INPUT VARIABLE *, which are incorporated herein by reference in their entirety.
TECHNICAL FIELD [0002] Some example configurations are related to control systems and others are specifically related to flow control systems or temperature control systems.
BACKGROUND OF THE INVENTION [0003] Systems with more degrees of freedom than restrictions, in which goals can be operated in different ways, while still achieving the same defined goals. A typical example is a car that can be driven between two points through different tracks, at different speeds, at different gears and using the brakes differently.
[0004] Normally, if the way these systems work and undefined goals is analyzed, there is room for improvement. For example, most vehicles do not operate either with the minimum possible amount of gas, nor using them as little as possible, nor reaching the minimum transit time legally or safely as possible.
[0005] Often, when an optimization system is designed for a given environment, the environment itself changes and the
2/47 the system fails to optimize its originally designated function.
[0006] Additional difficulties with existing systems can be seen in the description below.
BRIEF DESCRIPTION OF THE INVENTION [0007] According to some aspects, a control system is provided for temperature control systems and circulation devices such as pumps, propellers and fans, centrifugal machines and related systems.
[0008] In one aspect, a control system is provided to control an operable system, which comprises: one or more operable elements resulting in output variables, in which there is more than one path or point of operation of the system's system variables. operable system that asks to provide a certain output setpoint, in which at least one system variable in one path or point of operation restricts the operation of another system variable in the path or point of operation; and one or more controllers configured to operate on a control circuit to: detect input variables, including one or more optimizable input variables that are required to determine output variables, detect system variables, update a model with respect to at least one optimizable input variable based on the detected input variables and the detected system variables, with the model providing a prediction of the use of the input variables in all possible paths or operating points of the system variables that obtain a point adjustment, and operate based on one or more of the detected input variables and the detected system variables, upara to provide a path or operating point of the system variables that obtains an output adjustment point that optimizes the use of at least least one optimizable variable.
[0009] In another aspect, a flow control system is provided to control a flow system, which comprises: a
3/47 circulation with a variably controllable motor resulting in output variables, including pressure and flow, for the flow system; and one or more controllers configured to operate in a control circuit to: detect input variables, including one or more optimizable input variables, which are necessary to determine the output variables, detect the output variables and update a model with relation to at least one optimizable input variable based on the detected input variables and the detected output variables, with the model providing a prediction of the use of the input variables in all possible paths or operating points of the output variables that obtain an output setpoint, optimize a control curve according to the model with respect to at least one optimizable input variable based on the detected input variables and the detected output variables, with the control curve providing the coordination of the pressure and flow operating point to obtain an outlet set point and operate, based on one or more detected variables, the motor is variably controllable according to the optimized control curve to provide the operating point of pressure and flow to obtain the output set point.
[0010] In another aspect, a system of methods is provided to control an operable system, which comprises: one or more operable elements resulting in output variables, in which there is more than one path or point of operation of the system's variables. operable system that asks to provide a certain output setpoint, where at least one system variable in one path or point of operation restricts the operation of another system variable in the path or point of operation, with the method being executed as a control circuit and comprising: detection of input variables, including one or more optimizable input variables that are necessary to determine the output variables, detection of system variables.
4/47 updating a model in relation to at least one input variable that can be made based on the detected input variables and the detected system variables, with the model providing a prediction of the use of the input variables in all possible paths or points operating system variables that obtain a setpoint, and operate based on one or more of the detected input variables and the detected system variables, one or more elements operable according to the model optimized to provide a path or point of operation of the system variables that obtain an output set point that optimizes the use of at least one optimizable variable [0011] In another aspect, a non-transient, computer-readable medium is provided that includes instructions that, when executed by one or more controllers, cause the controllers to control an operating system in a control circuit, which comprises: one or m more operable elements resulting in output variables, where there is more than one path- or operating point of the operating system system variables that can provide a given output setpoint, where at least one system variable is in a path or point of operation restricts the operation of another system variable in the path or point of operation, with instructions comprising: instructions for detecting input variables, including one or more optimizable input variables that are required to determine the output variables , instructions for detecting system variables, instructions for updating a model in relation to at least one input variable that can be made based on at least one of the detected input variables and the system variables detected, with the model providing a prediction of use of input variables in all possible paths or points of operation the system variables that obtain one; set point, and instructions for operation based on one or more of the detected input variables and the
5/47 detected system, one or more elements operable according to the optimized model to provide a path or point of operation of the system variables that obtains an output set point that optimizes the use of at least one optimizable variable.
BRIEF DESCRIPTION OF THE DRAWINGS [0012] The configurations will now be described., By way of example only, with reference to the attached Figures, in which:
[0013] Fk ^ ura 1 illustrates an example of a block diagram of a circulation system with intelligent variable speed control pumps, to which examples of configurations can be applied;
[0014] Figure 2 illustrates an example of an operation graph of a variable speed control pump;
[001.5] Figure 3 shows a diagram illustrating the internal detection control of a variable speed control pump;
[0016] Figure 4 illustrates an example of the load profile for a system such as a building:
[0017] Figure 5 illustrates an example of a detailed block diagram of a control device, according to a configuration example.
[0018] Figure 6 illustrates a control system to coordinate the control of devices, according to a configuration example;
[0019] Figure 7 illustrates another control system to coordinate the control of devices, according to another example of configuration;
[0020] Figure 8 illustrates a flowchart of an example method to coordinate the control of devices, according to an example of configuration.
[0021] Figure 9 illustrates an example of a graph of operation of a variable speed control pump, with an adjustable control curve that uses the hydraulic resistance of the system detected for the optimization of energy consumption, according to an example of
6/47 configuration;
[0022] Figures 10A, 10B and 10C illustrate an example of flowcharts to adjust the operation graph of Figure 9, according to examples of configurations;
[0023] Figure 11. illustrates an example of an adjustable load profile for a system, which can be used to adjust a control curve of Figure 2, according to another example of configuration;
[0024] Figure 12 illustrates an example of a block diagram of a circulation system with external sensors, according to an example of configuration; and [0025] Figure 13 illustrates an example of a flow control system for a flow system, according to a configuration example;
[0026] Similar reference numerals can be used throughout the Figures to denote similar elements and characteristics.
DETAILED DESCRIPTION OF THE INVENTION [0027] At least some examples of configurations generally offer an automatic control system for temperature control systems and circulation devices such as pumps, thrusters and fans, centrifugal machines and related systems.
[0028] In some example configurations, a control system for an opposing system such as a flow control system or temperature control system is provided. The examples of configurations are related to processes '' in the industrial sense, which means that a process that produces products (eg hot water, air) with the use of and inlets (eg cold water, fuel, air etc.). The system operates in a control circuit to constantly optimize a model in relation to at least one optimizable input variable based on the detected variables. The model offers a prediction of the use of the input variables in all possible paths or points of operation of the
7/47 system variables that obtain an output setpoint. In some configuration examples, the control circuit is carried out during the initial configuration and in the subsequent operation of one or more operable elements in the operable system. The control system is self-learning in the sense that at least some of the initial and subsequent parameters of the system are determined automatically during run time, that is, it does not require manual configuration [0029] In pumping systems, where the flow requires changes over time, there are several conventional procedures to adapt the operation of the pump (s) in order to satisfy such demand without exceeding the nominal pressure of the system, burning seals or creating vibration., and you can also try to optimize energy use .
[0030] Traditional systems have used one or more pumps of constant speed and tried to keep the discharge pressure (local or remote) constant, when the flow demand changed, changing the number of pumps in operation and / or reduction valves. , deviation and discharge of operating pressure.
[0031] A popular system in use today has several pumps; each equipped with an electronic variable speed drive and operates them to control one or more pressures remotely in the system, measured by remote sensors (usually installed in the most distant location served or 2/3 below the line). At the location (s) of the remote sensor, a minimum pressure must be maintained so that the deviation of the pressure (s) measured (s) from the target (s) calculated. The speed of the pumps in operation is then adjusted (up or down) to the lowest that maintains all the pressures measured at or above their targets. When the speed of the pumps in operation exceeds a certain value (normally 95% of the maximum speed), another pump is started. When the speed falls below a certain value (50% or more and sometimes, depending on the number of
8/47 pumps running), one pump is stopped. This sequencing method was designed to minimize the number of pumps used to provide the required amount of flow.
[0032] An alternative for this type of system measures the flow and pressure in the pump (s) and estimates the remote pressure by calculating the pressure drop in the intermediate tubes. The pump (s) are then controlled according to the procedure described above, however using the estimated remote pressure instead of direct measurements. This alternative saves the cost of the remote ($) sensor (s), in addition to wiring and installation, but requires a local pressure sensor and a flow meter.
[0033] A type of pump device estimates the local flow and / or pressure of the electrical variables provided by the electronic variable speed drive. This technology is usually called, in the literature, without a ¹ 'sensor. Examples- of single pump implementations are described in PCT Patent Application Publication No. WO 2005/064167 to Witzel et al., U.S. Patent No. 7,945,411 to Kernan et al „US Patent No. 6,592,340 to Horo et al. and DE Patent No. 19618462 to Foley. The single device can then be controlled, however using the estimated local pressure and flow to then infer the remote pressure instead of direct fluid measurements. This method saves the cost of the sensors, as well as their wiring and installation, however these references may be limited to the use of a single pump.
[0034] In a configuration example, a control system for supplying a load is provided, which comprises: several circulation devices without a sensor, each containing an operable circulation element for arranged to supply the load, with each device configured to auto-detect power and speed of the respective device and one or more controllers configured to: correlate, for each device, the power and speed detected for one or more output properties, including pressure and flow, and coordinate the
9/47 control of each of the devices to operate at least the respective operable circulation element to coordinate one or more output properties for the combined output to obtain the pressure set point at the load.
[0035] Reference is first made to Figure 1 which shows in the form of a block diagram a circulation system 100 with intelligent variable speed circulation devices such as control pumps 102a, 102b (each or individually called 102 ), to which example configurations apply. Circulation system 100 may be related to a building 104 (as indicated), a campus (several buildings), vehicle, plant, generator, heat exchanger or other suitable infrastructure or load. Each control pump 102 may include one or more respective pump devices 106a, 106b (each or individually indicated as 106) and a control device 108a, 108b (each or individually indicated as 182) to control the operation of each device of pump 106. The particular circulation medium may vary depending on the particular application and may, for example, include glycol, water, air, fuel, and the like.
[0036] As shown in Figure 1, circulation system 100 can include one or more loads 110a, 110b, 110c, 1 lOd, in which each load can be a variant requirement of use based on HVaC, plumbing etc. Each 2-way valve 112a, 112b, 1 Izc, 112d can be used to manage the flow for each respective load 110a, 110b, 110c, 110d. As the differential pressure in the load decreases, the control device 108 responds to this change by increasing the pump speed of the pump device 106 to maintain or obtain the pressure set point. As the differential pressure in the load increases, the control device 108 responds to this change by slowing the pump speed of the pump device 106 to maintain or obtain the pressure adjustment bridge. In some example configurations, the
10/47 control valves 112 a, 112b, 112c, 112d may include taps or taps to control the flow to the plumbing systems. In some example configurations, the pressure setpoint can be fixed, continuously or periodically calculated, externally determined or otherwise specified.
[0037] The control device 108 for each control pump 102 can include an internal sensor or detector, usually called, in the literature, a control pump without sensor because an external sensor is not necessary. The internal detector can be configured to auto-select, for example, device properties such as the power and speed of the pump device 106. Other input variables can be detected. The pump speed of the pump device 106 can be varied to obtain the pressure and flow set point of the pump device 106 depending on the internal detector. A program map can be used by control device 108 to map a detected power and speed to the resulting output properties, such as column output and flow output (H, F).
[0038] Still in relation to Figure 1, the output properties of each control device 102 are controlled to, for example, obtain a pressure set point on the combined output properties 114, shown at a load point of the building 104. The output properties 114 represent the aggregate or total of the individual output properties of all the aornbas and control 102 in the load, in this case, flow and pressure. In typical conventional systems, an external sensor (not shown) would be placed at the location of output properties 114 and associated controls (not shown) would be used to control or vary the speed of the device to pump 106 to obtain the pressure adjustment comb. depending on the flow detected by the external sensor. In contrast, in the example configurations, the output properties 114 are, on the contrary, inferred from the properties of the self-detecting devices, such as the power and speed of the pump devices 106 and / or other input variables. As shown, solid properties 114 are located at the most extreme position of the load at the height of building 104 (or at the end of the line), and in other example configurations, they can be located in other positions such as the middle of building 104, 2 / 3 from the top of building 104 or along the line or the furthest building on a campus, [0039] One or more controllers 116 (eg, processors) can be used to coordinate the outflow of control pumps 102, As shown, control pumps 102 can be arranged parallel to shared loads 110a, 110b, 110c, 110-d. For example, the individual output properties of each of the control pumps 102. can be inferred and controlled by controller 116 to obtain aggregate output properties 114. This feature is described in more detail below, [0040] In some examples ., circulation system 100 can be a cooled circulation system (“refrigeration plant”). The refrigeration plant can include an interface 118 in thermal communication with a secondary circulation system. The control valves 112a, 112b, 112c, 112d manage the flow to the cooling coils (eg load 110a, 110b, 110c, 1 ld). Each two-way valve 112a, 112b, 112c, 112d can be used to manage the flow for each respective load 110a, 110b, 110c, HOd. As a valve 112a, 112b, 112c, 112d opens, the differential pressure of the valve decreases. The control device 108 responds to this change by increasing the pump speed of the pump device 106 to obtain a specified output set point. If a control valve 112a, 112b, 112c, 112d closes, the differential pressure of the valve increases, and the control devices 108 respond to this change by slowing down the pump device 106 to obtain an outlet setpoint. specified.
12/47 [0041] In some- other examples, circulation system 100 can be a circulation heating system (heating plant ”). The heating plant may include an interface 118 in thermal communication with a secondary circulation system. In these examples, the H 2a, 112b, 112c, 112d control valves deliver the flow to the heating elements (eg load 110a, 110b, 110 c, 1 10d). The control devices 108 respond to changes in the heating elements by increasing or decreasing the pump speed of the pump device 106 to obtain the specified output set point.
[0042] Still in relation to Figure 1, the pump device 106 can take various forms of pumps that have variable speed control. In some example configurations, the pump device 106 includes at least one sealed housing that houses the pump device 106, which at least defines an input element for receiving a circulation medium and an exit element for producing the circulation medium . The pump device 106 includes one or more operable elements, including a variable motor which can be variably controlled from the control device 108 'to rotate at variable speeds. The pump device 106 also includes an impeller that is operable coupled to the motor rotates based on the speed of the motor, to circulate the circulation medium. The pump device 106 further includes other features or suitable operable elements, depending on the type of pump device 106. The device properties of the pump device 106, including the speed and power of the motor, can be auto-detected by the control device 108.
[0043] Now, a reference is made to Figure 2, which illustrates a graph 200 showing an example of suitable operating range 202 for a variable speed device, in this example the control pump 102. Operating range 202 is illustrated as a region in
13/47 polygon shape or area in graph 200, in which the region bounded by an edge represents a suitable operating range. For example, a design point may be a maximum expected load from the system as at point A (210) as required by a system such as a building 104 on exit properties 114 (Figure 1).
[0044] The point of the project ,. Point A (210) can be estimated by the system designer based on the flow that will be required by a system for effective operation and the pressure / column loss required to pump the project flow through the system's piping and connections. Note that as pump column estimates can be overestimated, most systems will never reach the design pressure and exceed the design power and flow · .. Other systems, where designers underestimate the required column, operate at a pressure higher than the design point. For these circumstances, a characteristic of properly selecting one or more intelligent variable speed pumps is that they require to be properly adjusted to provide more flow and column in the system than the designer has specified.
(0045] The design point can also be estimated for operation with multiple control pumps 102, with the resulting flow requirements allocated between controlled pumps 102. For example, for controlled pumps of type or equivalent performance, the total properties of estimated required output 114 (eg maximum flow to maintain a required design point of pressure at the load site) from a system or building 104 can be divided equally between each controlled pump 102 to determine individual design points and to account for losses or any combined nonlinear flow output. In other example configurations, the fatal output properties (eg weight less flow) can be unevenly divided, depending on the specific flow capacities of each control pump 102, as well as to respond loss or any non-bnear flow output
Combined 14/47. The individual setpoint of the project, as in point A (210), is thus determined for each individual control pump 102.
[0046] Graph 200 includes axes that include correlated parameters. For example, the flow squared is approximately proportional to the column and the flow is approximately proportional to the speed. In the example shown, the abscissa, or x-axis, 204 illustrates the flow in American gallons (GPM) and in the ordinate, or y-axis, 206 illustrates the column (H) in pounds per square inch (psi) (alternatively in feet). The operating range 202 is a superimposed representation of the control pump 102 with respect to these parameters in graph 200.
[0047] The reaction between the parameters can be approximated by specific affinity laws., Which can be affected by volume., Pressure and brake power (BHP). For example, for variations in the impeller diameter at a constant speed: D1 / D2 ~ Q.1 / Q2; Η1 / Ή2 ~ DP / D2 ² ; BHP1 / BHP2 ~ Dl '/ D2 ³ . For example, for speed variations, with constant impeller diameter: SI / S2 = Q1 / Q2; H1 / H2 = SV- / S2 ² : BHP1 / BHP2 - SFVS23. Where: □ - Impulse Diameter (Ins / mm); H = Pump Column (Feet / m); Q - Pump Capacity (gprn / lps); S = Speed (rpm / rps); BHP - Brake Power (Axis Power - hp / kW).
[0048] A curve of the best efficiency point (BEP) 220 of the control pump 102 is also illustrated. Partial efficiency curves are also illustrated, for example, the 77% efficiency curve 238. In some example configurations, an upper limit of operating range 202 can also be better defined by a 236 motor power curve (eg . maximum power). In alternate configurations, the operating range limit 202 may also depend on a pump speed curve 234 (shown in Hz) instead of a strict maximum power curve for motor 236.
[0049] As shown in Figure 2 .. one or more curves of
15/47 control 208 (one shown) can be defined and programmed for an intelligent variable speed device, such as a 102 control pump. Depending on changes in the detected parameters (eg internal detection or inferred changes in flow / load), the operation of the pump device 106 can be maintained to operate on the control curve 208 on the basis of instructions from the control device 108 (e.g. at a greater or lesser flow point). This control mode can also be called quadratic pressure control (QPC), as control curve 208 is a quadratic curve between two operational points (eg point A (210): maximum column and point C (214): column minimum). The reference to smart devices' here includes control pump 102 being capable of self-adjusting operation of pump device 106 along control curve 208, depending on the specific load required or detected.
[0050] Other examples of control curves, other than quadratic curves, include constant pressure control and proportional pressure control (sometimes called relative line control). The selection can also be made for another specified control curve (not shown), which can be predetermined or calculated in real time, depending on the specific application.
[0051] Now, reference is made to Figure 3, which shows a diagram 300 illustrating the internal detection control (sometimes called sensorless control) of control pump 102 in operating range 202 according to the examples of settings. For example, an external or approximate sensor would not be needed in these example configurations. An internal detector 304 or sensor can be used to auto-detect device properties with the amount of power and speed (P, Si of a motor associated with the pump device 106. A program map 302 stored in a memory of control device 108 is used by control device 108 to map or
16/47 correlate c detected power and speed (P, S), for resulting output properties, such as column and flow (H, F) of device 102, for a specific building or system 104. During operation, the Control 108 monitors the power and speed of the pump device 106 using the internal detector 304 and establishes the associated column-flow condition relative to the system requirements. The associated column-flow condition IH, F) of device 102 can be used to calculate the individual contribution of device 102 to the total sound properties 114 (Figure 1) in the load. Program map 302 can be used to map the power and speed to control the operation of the pump device 106 on the control curve 208, in which a point on the control curve is used as the desired device setpoint. For example, with reference to Figure 1, as control valves 112a, 112b, 112c, 112d open and close to regulate the cooling coils (eg load 110a, 110b, 110c, 110d), control device 108 adjusts the pump speed automatically to meet the pressure requirement of the system in the current flow.
[0050] Note that the internal detector 304 for self-detecting device properties contrasts with some existing conventional systems that can use a flow meter and local pressure sensor that merely directly measures the pressure and flow in the 102 control pump. These variables (flow meter and local pressure sensor) may not be considered device properties in example configurations.
[0053] Another example of configuring a variable speed device without a sensor is a compressor that estimates the refrigerant flow and elevation from electrical variables provided by the variable speed electronic drive. In a configuration example, a “sensorless” control system can be used for one or more refrigeration devices in a controlled system, for example, as part of a refrigeration plant or other refrigeration system.
17/47 refrigeration. For example, the variable speed device may be a cooling device that contains a controllable variable speed compressor. In some example configurations, the device's self-detecting properties of the cooling device may include, for example, compressor power and / or speed. The resulting output properties may include, for example, variables such as temperature, humidity, flow, elevation and / or pressure.
[0054] Another example of configuring a variable speed device without a sensor is a fan that estimates the flow of or and the pressure it produces from electrical variables provided by the electronic variable speed drive.
[0055] Another example of configuring a device without a sensor is a conveyor belt that estimates its speed and the mass it loads from electrical variables provided by the variable speed electronic drive.
[0056] Figure 4 illustrates an example of the load profile • ^ 0'0 for a corna system, for example, a building 104, for a measured or scheduled project day. The load profile 400 illustrates the percentage of hours of operation versus the percentage of the heating / reorganization load. For example, as shown, many examples of systems may require operation of only 0% to 60% of the load capacity 90% of the time or more. In some examples, a control pump 102 can be selected to obtain the best operating efficiency with partial load, for example, at approximately or exactly 50% of the peak load. Note that the ASHRÁE 90.1 standard for energy saving requires device control which results in the nadd pump motor requiring more than 30% of the project wahagem to 50% of the project water flow (eg 70% energy savings) 50% of peak load). It is understood that the project day may not be limited to 24 hours, but can be determined by
18/47 shorter or longer periods of the systems, such as a month, a year or several years.
[0057] With reference, again, to Figure 2, several points of the control curve 208 can be selected or identified or calculated based on the load profile 400 (Figure 4), shown as point A (210), point B (212 ) and point C (214). For example, the control curve points 208 can be optimized for partial load instead of 100% load. For example, with respect to point B (212), at a flow of 50%, efficiency meets the ASHRAE 90.1 standard (more than 70% energy savings). Point B (2.12) can be called the ideal set point on the control curve 208, which has maximum efficiency on the control curve 208 for 50% at the load or the most frequent partial load. Point A (210) represents a point in the project that can be used for selection purposes for a specific system and may represent a maximum expected load requirement for a given system. Note that, in some configuration examples, there may be actually increased efficiency in part of the load for point B versus point A. Point C (214) represents a minimum column and flow (Hmin), based on 40% of the column project lotai, as standard, for example. Other examples may use a different value, depending on the requirements of the system. Control curve 208 may also include a thicker illustrated part 216 that represents the expected range of typical load (eg approximately or exactly 90% 95% of the projected load range for a scheduled design day). Likewise, operating range 202 can be optimized for partial load operation. In some examples of configurations, control curve 208 can be recalculated or redefined based on changes in the load profile 400 (Figure 4) of the system, either automatically or manually. The thicker part of curve 216 can also be modified with control curve 208 based on changes in the load profile 400 (Figure 4).
19/47 [0058] Figure 5 illustrates an example of a detailed block diagram of the first control device 108a, to control the first control pump 102a (Figure I), according to a configuration example. The first control device 108a can include one or more controllers 506a as a processor or microprocessor that controls the general operation of the control pump 102a. Control device 108a can communicate with other external controllers 116 or other control devices (one shown, called the second control device 108b) to coordinate the controlled aggregate output properties 114 of control pumps 102 (Figure 1). Controller 506a interacts with other device components such as memory 508a, system software 512a stored in memory 508a to run applications, subsist from input 522a, output subsystems 520a, and a communications subsystem 516a. A power source 518a powers control device 108 a. The second control device 108b may have the same, more or less blocks or modules as the first control device 108a, as appropriate. The second control device 108b is associated with a second device such as a second control pump 102b (Figure 1).
[0059] The communications subsystem 51.6a is configured to communicate with the other controller 116, either directly or indirectly, and / or with the second control device 108b. The communications subsystem 516a can also be configured for wireless communication, The communications subsystem 516a can be configured to communicate over a network such as a local area network (LAN), a wireless network (WiFi) and / or the Internet . These communications can be used to coordinate the operation of the 102 control pumps (Figure 1).
[0060] Input subsystems 522a can receive input variables. Input variables can include, for example, detector 304 (Figure 3) to detect device properties such as power and
20/47 speed (P, Si of the motor. Other examples of inputs can also be used. Output subsystems 520a can control output variables, for example, one or more operable elements of the 102o control pump. For example, Output subsystems 520a can be configured to control at least the speed of the control pump motor 102a to obtain a resulting desired output setpoint for column and flow (H, F |, for example to operate control nozzle 102 at control curve 208 (Figure 2) Other examples of output variables, operable elements and device properties can also be controlled.
[0061] In some example configurations, the control device 108a can store data in memory 508a, as correlation data 510a. Correlation data 510a can include correlation information, for example, to correlate or infer between input variables and the resulting output properties. Correlation data 510a can include, for example, program map 302 (Figure 3), which can map the resulting column and flow power and speed at pump 102, resulting in the desired pressure setpoint in the outlet of the load, In other example configurations, the 510a correlation data can be in the form of a table, model, equation, calculation, inference algorithm or other suitable forms.
[0062] Memory 508a can also store other data such as load profile 400 (Figure 4) for the measured 'project day' or average annual load. Memory 503a can also store other information pertaining to system or building 104 (Figure 1).
[0063] In some configuration examples, correlation data 510a stores correlation information for some or all of the other devices 102, such as the second control nozzle 102b (Figure 1).
[0064] Still in relation to Figure 5, the control device 108a includes one or more applications of the program. In some examples of
21/47 configurations, c> control device 108a includes a 514o correlation application or inference application that receives the input variables (eg, power and speed) and determines and infers, based on the 510a correlation data, the properties outputs (eg flow and column) at pump 102a. In some configuration examples, control device 108a includes a coordination module 515a, which can be configured to receive the individual output properties determined from the second control device 108b, and configured to coordinate, logically, each of the control devices 108o _f 108b, and provide commands or instructions to control each of the output subsystems 520a, 520b and resulting output properties in a coordinated manner to obtain a specified output setpoint of the output properties 114 .
[0045] In some configuration examples, some or all of the 514a correlation applications and / or the 515a coordination module may alternatively be part of the external controller 116, [0064] In some configuration examples, in an operating mode example , control device 108a is configured to receive input variables from input subsystem 522a, and send this information as detected data (eg unrelated measured data) on communications subsystem 516a to the other controller 116 or to the second control device 108b, for processing the device, which then corrects the detection data to the corresponding output properties. Processing outside the device can also determine the aggregate output properties of all control devices 108a, 108b, for example, the output properties 114 of a common load. Control device 108a can then receive instructions or commands via communications system 516a on how to control output subsystems 520a, for example, to control local device properties or
22/47 operable elements, [0067] In some example configurations, in another example of operating mode, the control device 108a is configured to receive input variables from the second control device 108b, either from the second control device 108b or other controller 116, as detection data (e.g., unrelated measured data) via communications system 516a. Control device 108a can also auto-detect its own input variables from input subsystem 522a. The correlation application 514a can then be used to correlate the detection data of all control devices 108a, 108b with their corresponding output properties. In some configuration examples, the coordination module 515a can determine the aggregate output properties of all control devices 108a, 108b, for example, the output properties 114 of a common load. The control device 108a can then send instructions or commands via communications subsystem 516a to another controller 116 or to the second control device 108b, about how the second control device 108b is to control its output subsystems, for example example, to control your local device-specific properties. Control device 108a can also control its own subsystems 520a, for example, to control its own properties to first control pump 102a (Hgura 1).
[0068] In some other example configurations, control device 108a first maps the detection data to the output properties and sends the data as correlated data (eg inferred data). Similarly, control device 108a can be configured to receive data as correlated data (eg inferred data), which were mapped to the output properties by the second control device 108b, instead of just receiving the data.
23/47 detection data. The correlated data can then be coordinated to control each of the control devices 108a, 108b.
[0049] In a new reference to Figure 1 <the speed of each of the control pumps 102 can be controlled to achieve or maintain the constant inferred remote pressure by reaching or maintaining HI + (HD Hl) * (Q / QD)> ^A <2 (hereinafter Equation 1), where H is the inferred local pressure, HI is the remote pressure set point, HD is the local pressure under the project conditions, Q is the inferred total flow and QD is the total flow in the project conditions. In some configuration examples, the number of pumps in operation (N) is increased when H <HD * (Q / QD) ^A 2 * (N -r 0.5 + k) (hereinafter Equation 2), and decreased when H> HD * (Q / QD) ^A 2 * (N - 0.5 - k2) (hereinafter Equation 3), where k and k2 are constant to guarantee a dead band around the sequencing limit.
[0070] Now, a reference is made to Figure 8. which illustrates a flow chart of an example of method 800 to coordinate the control of two or more control devices, according to a configuration example. Each device includes a communication subsystem and is configured to auto-detect one or more device properties, with device properties resulting in outputs with one or more output properties. In event 802, method 800 includes detecting entries, including one or mac device properties for each device. In event 804, method 800 includes correlating, for each device, one or more device properties to one or more output properties, on each respective device. These one or more respective output properties can then be calculated to determine their individual contributions to a system load point. In event 806, method 800 includes determining the aggregated output pfopnedades for the garbage from one or more properties a and
24/47 individual output .; In event 808, method 800 includes comparing aggregate output properties 114 with a setpoint, such as a load pressure setpoint. For example, it can determine that one or more given aggregate output properties are greater, smaller or suitably maintained at the set point. For example, this control can be performed using Equation 1, as detailed above. In event 810, the method includes coordinating the control of one of the devices to operate one or more respective device properties to coordinate that one or more respective properties for obtaining the setpoint. This can increase, decrease or maintain that one or more respective device properties in response, for example, to a point on the control curve 208 (Figure 2). Method 800 can be repeated, for example, as indicated by response circuit 812. Method 800 can be automated, manual control not required.
[0071] In another example of configuration, method 800 includes a decision to turn one or more control pumps 102 on and off, based on predetermined criteria. For example, the decision can be made using Equation 2 and Equation 3, as detailed aorna.
[0072] While method 800 illustrated in Figure 8 is represented as a response circuit 812, in some other example configurations, each event may represent operations or modules based on the state instead of a chronological flow.
[0073] For example, with respect to Figure 1, the various events of method 800 of Figure 8 can be performed by the first control device 108a, by the second control device 108b and / or by the controller 114, either alone or in combination.
[0074] Now, reference is made to Figure 6, which illustrates an example of configuring a control system 600 to coordinate two or more control devices without a sensor (two shown), illustrated
25/47 as first control device 108a and second control device 108b. Similar reference numbers are used for convenience of reference. As shown, each control device 108a, 108b can each, respectively, include controller 506a, 506b, subsystem 522a, 522b and output subsystem 520a, 520b, for example, to control at least one or more operable members device (not shown).
[0075] A coordination module 602 is shown, which can be part of at least one of the control devices 108a. 108b, or from an external device such as controller 116 (Figure 1). Similarly, the application of inference 514a, 514b can be part of at least one of the control devices 108a, 108b, or part of a separate device such as controller 116 (Figure 1).
[0076] In operation, the coordination module 602 coordinates the control devices 108a .. 108b to produce coordinated outputs. In the configuration example shown, control devices 108a, 108b work in parallel to satisfy a certain demand or shared load 114, and which infer the value of one or more device output properties by indirectly inferring them from other variables. measured input and / or device properties. This coordination is achieved using the inference application 514a, 514b, which receives measured inputs, to calculate or infer the individual output properties on each device 102 (eg column and flow on each device). From these individual output properties, the individual contribution of each device 102 to the load (individually for output properties 114) can be calculated based on the system / building configuration. From these individual contributions, the .602 coordination module estimates one or more properties of the aggregate or combined output properties 114 in the system load of all control devices 108a, 108b. The 602 coordination module
26/47 compares a setpoint with the combined output properties (usually a pressure variable) and then determines how the operable elements of each control device 108a, 108 b are to be controlled and with what intensity.
[0077] It would be ideal if the aggregate or combined output properties 114 could be calculated as a linear combination or a non-linear combination of the individual output properties, depending on the specific property being calculated and to account for the losses in the system, as the case may be.
[0078] In some configuration examples, when the 602 coordination module is part of the first control device 108a, this can be considered a master-slave configuration, in which the first control device 108a is the master device and the second device control device 108b is the slave device. In another configuration example, the coordination module 602 is massively integrated into one of the control devices 108a, 108b than is really necessary, for safe fault redundancy.
[0079] Still in relation to Figure 6, some specific examples of control distributions for output subsystems 520a, 520b will now be described in more detail. In a configuration example, for example, when output subsystems 520a, 520b are associated with control device properties of type or equivalent performance, the device properties of each control pump 102 can be controlled to read the same device properties to distribute the load requirements of the flow. And other examples of configurations, there may be uneven distribution, for example, the first control pump 102a may have a greater flow capacity than the second control pump 102b (Figure 1). In another configuration example, each control pump 102 can be controlled to maximize the efficiency of the respective control pumps 102
27/47 with sparrow position, for example, to maintain the respective control curves 208 (Figure 2) or the best point B (212) of approach in the respective control curve 208.
[0080] Still with respect to Figure 6. in an ideal operating condition of the system, each of the control devices 108a, 108b is controlled by the coordination module 602 to operate on their respective control curves 208 (Figure 2) to maintain the pressure setpoint at outlet properties 114. This also allows each pump 102 to be optimized for partial load operation. For example, as an initial allocation, each of the control pumps 102 can receive a percentage of the flow allocation (eg 50% can be divided between each control device 108a, 108b of this example) to determine or calculate the initial setpoint necessary (eg Point A (210). Figure 2). The percentage of flow responsibility required for each control pump 102 can then be determined by dividing the flow allocation percentage of the total inferred output properties 114. Each of the control pumps 102 can then be controlled along its control curves 208 to increase or decrease the operation of the engine or other operable element, to obtain the percentage of responsibility for flow required.
[0081] However, if one of the control pumps (eg first control pump 102a) is determined to have negative performance or to be outside its control curve 208, the coordination module 602 may first try to control the first control pump 102a to operate on your control curve 208. However, if this is not possible (eg damage, negative performance would take you out of operating range 202, otherwise outside the control curve 208 etc.), the other control pumps (eg 102b) can be controlled to increase their device properties in their respective control curves 208 to obtain the pressure set point in the flow required in
28/47 output properties 114 to compensate for at least some of the deficiencies of the control pump 102a. Similarly, one of the control pumps 102. can be intentionally deactivated (eg maintenance, inspection, saving operating costs, night maintenance etc.), with the other control pumps 102 being controlled in the same way.
[0082] For other example configurations, the distribution between the output subsystems 520a, 520b can be dynamically adjusted over time to properly track and distribute the wear between the control pumps 102, [0083] Now, a reference to Figure 7, which illustrates another example of configuring a control system 700 to coordinate two or more control devices without a sensor (two shown), illustrated as first control device 108a and second control device 108b. Similar reference numbers are used for convenience of reference. This can be called a peer-topeer system. in some example configurations. An external controller 116 may not be required in these example configurations. In the example shown, the first control device 108a and the second control device 108b each can control their own output subsystems 520a, 520b to obtain a combined coordinate output from the '114 system. As shown, each coordination module 515a, 515b is configured to take into account the inferred and / or measured values from the input subsystems 522a. 522b, For example, as shown, the first coordination module 515a can estimate one or more output properties of the combined output properties i 14 from the inferred and / or measured individual values.
[0084] As shown, the first coordination module 515a receives the inferred and / or measured values and calculates the individual output properties of each device 102 (eg column and flow). From these
29/47 health properties. individual, the individual contribution of each device 102 to the load (individually in the output properties 114) can be calculated based on the system / building configuration. The first coordination module 515a can then calculate or infer the aggregate output properties 114 in the load.
[0085] Next, the first coordination module 515a compares the aggregate output properties 114 with an output properties setpoint (usually a pressure variable setpoint) and then determines the individual allocation contribution required by the first exit subsystem 520a (eg calculating 50% of the total contribution required in this example). The first output subsystem 520a is then controlled and at a controlled intensity (eg increases, decreases or maintains engine speed or other device properties) with the resulting coordinate output properties being again inferred by other measurements in the output subsystem. entry 522a, 522b.
[0086] As shown in Figure 7, the second coordination module 515b can be similarly configured with the first coordination module 515a to account for both input subsystems 522a, 522b to control the second output subsystem 520b. For example, each of the control pumps 102 can initially receive a percentage of flow allocation. Each of the control pumps 102 can then be controlled along its control curves 208 to increase or decrease the operation of the motor or other operable element, based on the output properties of the aggregate load. The aggregate output properties of load 114 can be used by control pump 102, the required flow and corresponding motor speed (eg to maintain the flow percentage, eg 50% for each subsystem 520a. 520b in this example). Likewise, both 515a coordination modules. 515b operate together to coordinate
Their respective output subsystems 520a; 520b for obtaining the output setpoint selected in the output properties of load 114.
[0087] As shown in Figure .7, note that, in some configuration examples, each of the 515a .. 515b coordination modules is not necessarily in communication with the others for the functionality to operate in coordination. In other example configurations, not shown, the coordination modules 515a, 515b are in communication with each other for further coordination between them.
[0088] Although the examples of configurations were first described in relation to the control devices arranged in parallel, it would be ideal if other provisions could be implemented. For example, in some examples of configurations, the controlled devices can be arranged in series, for example, a pipe, a propellant or other similar application. The resulting output properties are still coordinated in these example configurations. For example, the output setpoint and the output properties of the load may be located at the end of the series. The control of the output subsystems, device properties and operable elements are still carried out in a coordinated manner in these example configurations. In some examples of configurations, the control devices can be arranged in combination of series and parallel »[0089] Now, reference is made to Figure 9, which illustrates an example of a 900 column operation versus flow graph for a variable speed control pump 102 (Figure 1), according to a configuration example. Generally, operation graph 900 illustrates an adjustable control curve 902 which is used to optimize a hydraulic resistance of the system (K ~ H / Q ² ), such as that of the circulation system 100 in Figure 1. The hydraulic resistance of the system
31/47 is also called hydraulic conductivity.
(0090] Referring, therefore, to Figure 1, one or more controllers, such as control device 108, and / or external controller 116 can be used to determine dynamically calculate or determine control curve 902 (Figure 9) in real time during operation during run time of circulation system 100. Generally, the controller automatically adjusts or updates the control pump model or parameters 102 to adjust the control curve 902 (Figure 9) to compensate for the loss flow rate or other changes that may occur in the conditions of system 100. The controller is self-learning in the sense that at least some of the Initial and subsequent parameters of system 100 are determined, or even, do not require manual configuration. and controlled using data collected during run time. Control pump 102 is controlled to reduce pump energy consumption without compromise have the stability of the system or super-cool the load (s) 110a, 110b, 110c, 1 10d.
[0091] In some configuration examples, control pumps 102 can be sensorless in the sense that they can be used to determine or calculate the resistance of the system without an external sensor. This is done by letting the control pump 102 self-detect its own device properties, such as power and speed, as well as Inferring or correlating the resulting column and flow, as described in detail above with respect to Figure 3. The present system resistance can, then, be calculated as K - H / Q ² .
[0092] Still in relation to Figure 1, the control pump 102 can distribute a hot or cooled fluid to one or more loads 110a, 110b, 110 c, 110d, which control the flow that they transport with the use of H2a modulating valves, 112b, 112c, 112d, or. in some configuration examples, there are sufficient loads with ilgo / off valves that the
32/47 system 100 can treat as modulators. As shown in Figure 9, the pump speed can be set to any value between a minimum speed 904 and a maximum speed 906, which depends on the pump-motor-drive assembly. In the example shown in Figure 9, the design point of the 9081 system represents the column and flow of the 10.0 · .. system design, which may be initially unknown and may change over time. The design point of the 908 system is assumed to be less than or equal to the best efficiency point of the pump, 8EP 910. for flow and column, based on the selection of the proper pump. In operation, the pump speed is adjusted using a flow loss compensation algorithm with a quadratic control curve: Column - A + B x Flow ² , as shown. Higher-burn polynomials can also be used in other example configurations. In some example configurations, it can be assumed that the system load has no asymmetry greater than 40%. that is, at any moment, the maximum percentage flow requirement of a load cannot be more than 40% higher than that of the least demanding load, with some examples of configurations, it can also be assumed that valves 112a, 112b. 112c, 112d have approximately equal percentage curves.
[0093] In a new reference to Figure 9 an operation that uses a single control pump 102 will be described to facilitate the illustration, although it is possible to observe that more than one control pump 102 can be operated in system 100. Generally, the example of The configuration of Figure 9 operates to keep valves 112o, 112b, 112c, 112d as open as possible in d mode. minimize the kinetic energy (pump) dissipated by them. This is done in a controlled manner to prevent the system from being able to provide sufficient flow when valves 112a, 112b. 112c .. 112d are open.
[0094] For example, control pump 102. can be controlled
33/47 to slowly adjust the control curve 902 so that the valves operate, most of the time, 60% and 90% open and, half the time, 75% open on each side, The average opening of the valves is detected calculating the resistance, system average K = H / Q ² . An invalid zone 918 represents a right limit outside the operating range of the control nozzle 102. Other limits can be provided or set for the operating range of the control pump 102.
[0095] The following relationship was established by analyzing the curves of different valve brands (KFO is the resistance when the valve is fully open):
Position (%) K / KFO 40 44 6075............................. 90 ............... 15 r —-; - ç ......- H2nd, 5 2 í 100 ]
[0096] The K seal is monitored and the following four situations cause the control curve parameters (A and B) to be adjusted: 1) valves too open (K <2 KFO).:. the right side of the curve is elevated; 2) valves too closed (K> 15KFO): the right side of the curve is lowered; 3) most of the time, the valves are open less than 75%: the curve is lowered; 4) most of the time, the valves are open more than 75%: the curve is high. For Items 3) or 4), other appropriate percentage values can vary from 50% to 100%.
[0097] Now, a reference is made to Figures 10A, 10B and 10C, which illustrate examples of flowcharts to adjust the control curve 902 of Figure 9, according to examples of configurations. As shown, these algorithms are called the valve distribution process 1000 (Figures 10A), valve position process 1002 [Figures 10B) and resistance review process 1004 (Figures 10C),
34/47 respectively. In example configurations, some ου all processes 1000, 1002, 1004 can be performed simultaneously in operation during the run time of control pump 102 in system 100. In some example configurations, processes 1000, 1002, 1004 can be during the initial configuration of system 100, as well as during operation.
[0098] Initially, with respect to the control curve 902 of Figure 9, the following parameters can be initialized, which initially refers to 8EP 910 for the initial resistance of the system (fully open valves):
A - Z x BEF. Column, (Z = 0-10);
B = (BEP. Column - A) / BEP_Flow ² ; and
C = BEP_Column / BEP_Flow ² (when all valves are fully open).
[0099] The various resistance curves of the system are shown in graph 900, for example, K = 1.5C (912), K = 6.5C (914) and K = 2C (916). The design point of the 908 system and the 902 control curve can be dynamically determined in real time, without having any special knowledge of the system resistance. The system resistance can change due to flow losses and other factors. As mentioned, some or all processes 1000. 1002, 1004 can be performed simultaneously to adjust the control curve 902.
[00100] With respect to Figure 10A, the valve 1000 distribution process determines whether the valves are, for the most part, open less than 75%, and the curve is lowered in response. The valve delivery process 1000 also determines whether the valves are open more than 75% most of the time, and the curve is high in response.
[00101] In event 1010, calculate or infer K = H / Q ² and count when time K. is greater than 6.5C (Count J) and when time K is less
35/47 than 6.5C (Count_2). As in the table above, remember that 6.5C corresponds to an opening of 75% of the valves.
[00102] In event 1012, it is determined whether 24 hours have passed to count the K times; for example, if CountJ + Count. ,, 2> 24 hours (the pump has been running for more than 24 hours since the last check). If 24 hours have passed, in event 1014: if ContagemJ> Contagem_2 + 4hs, decrease A by 1%; if ContagemJ + 4hs <Contágem_2, increase A by 1%. Otherwise, A must be maintained. In event 1014, reset CountJ to 0 and Count. ,, 2 to 0. Then, method 1000 is repeated until step 1010 for the next 24-hour interval.
[00103] With reference now to Figure 10B, the process of positioning the valves 1002 determines whether the valves are too open (K <2 KFO) and the right side of the curve is raised in response. The valve positioning process 1002 determines whether the valves are too open (K> 1.5KF0) and the left side of the curve is lowered in response.
[00104] In event 1020, calculate K ~ H / Q ² . In event 1022, when K remains above 15C, decrease A by 5% and increase B by 5% every 30 minutes. In event 1024, when K remains below 2C, decrease A by 5% and increase B by 5% every 30 minutes. Then, method 1002 is repeated until event 1020.
[00105] With respect to Figure 10C, the 1004 resistance review process is used to periodically determine or review the minimum resistance of the system, when the valves are fully open. In event 1034, the average of the minimum K value over the 1 minute reached (D) is determined and stored. In event 1036, at any time, if D <C <replace C with D.
[00106] In event 1038, after the first 2 days of operation (eg after the initial configuration), C is replaced by D (event 1040). In event 1042, D is reset to zero. In event 1044, after the
36/47 initial configuration, revision intervals can be used. For example, the review intervals can be given by the following: 1} the first interval is 2 days after the initial 2 days of operation: 2) the second interval is 4 days thereafter; 3) the third interval is 8 days thereafter; 4) the fourth interval is 16 days thereafter; each subsequent interval is 15 days thereafter for the defined duration of the system execution time. Other suitable intervals can vary from 1 to 30 days.
[00107] After the completion of each review interval (event 1044) .. in event 1046, if K <3C, reduce the speed to the minimum velocity of the drum (eg standard 30%) for 15 minutes. This essentially forces the valves to be fully open. Note that event 1036 will be triggered if D <C at this stage, with C being replaced by D. In event 1048, reset D to zero and <then restart to start a new review interval at event 1044.
[00108] Note that the examples of configurations 1QA to 1ÔC can also be limited by the operating range of the operation graph 900 (Figure 9). For example, the control curve 902 cannot be justified using these methods to stay out of the operating range. Any values or ranges provided must be for illustration purposes and can be in those values; or ranges, or close to them, or other suitable values or ranges, [00109] Now, a reference is made to Figure 11, in the context of Figure 2, which illustrates the optimization of pump efficiency according to an example of configuration. With reference to Figure 2, control curve 202 can be adjusted or controlled in real time, depending on a detected load (measured or inferred) from system 100. Normally, the load flow of system 100 is tracked in real time to update dynamically load profile 1100.
[00110] As an initial conceptual issue, the load profile 1100 of
37/47
Figure 11 can be implemented as a GUI graphical user interface screen 1100 to configure load profile 1102 of building 104. Load profile 1102 is normalized for one (100%) in this example representation. Load profile 1102 represents a projected or measured percentage flow 1104 for specific time periods 1106. The percentage flow is on a project day, for example. The interface screen 1100 is initially presented with a standard load profile 1102, as shown. A building designer (user) may wish to configure the load profile for the particular building 104 as something other than the standard load profile. As shown, in some examples and configurations, the user can select specific sampling points 1108 from the load profile 1102 on the interface screen 1100, and drag these points 1108 to different flows 1104 and time periods 1106, to adjust the load profile standard such as the specific projected or measured flow profile of the actual building or system 104. In other example configurations, the building designer can enter flows 1104 and term periods 1106 specific to certain pans 1108 by inserting into a field-based interface ( not shown) or loading a properly configured file that provides these values. And other examples of configurations, the axes of the load profile 1102, in contrast, can be equivalent to those shown in Figure 4.
[00111] An automated system to update the load profile 1102 will now be described, instead of the newly described manual user interface. The load profile 1102 can be a standard Initial load profile. Referring, therefore, to Figures 1 and 2, one or more controllers, such as control device 108, and / or external controller 116 can be used to determine dynamically calculate or determine control curve 208 in real time during operation. Generally, the controller automatically adjusts the control pump model or parameters 102 to fit the control curve
38/47
208 so as to compensate for changes on the day of the project or load profile 1102. Control pump 102 is controlled using data collected during run time. Control pump 102 is controlled to optimize the nozzle efficiency without compromising system stability and to maintain compliance with ASHRAE 90.1.
[00112] For the control curve 208, with respect, again, to Figure 2, the thicker illustrated part 216 can be dynamically adjusted in relation to the updated load profile 1102 (Figure 11). The 2081 control curve can also be dynamically updated, depending on the updated load profile 1102. The intelligent variable speed device would work along the dynamic changing control curve 208, which was updated in real time during the run time.
[00113] For example, point A (210), point B (212) and point C (214) would be updated in the same way, depending on the detected or inferred load profile 1102. For example, the control curve 208 can be updated so that the average or most frequent load represented as point B (212) is as close as possible to the BEP 220 curve. Although point B (212) can initially be 50% of the peak load, it can be determined (measure or inferred) dynamically that the load profile 1102 is asymmetric or has some other peak load. In response, control curve 208 may involve adjusting or recalculating point A (210) and / or point C (214), as, for example, from the initial default settings. In a configuration example, if point B (212) is determined to be to the left of the BEP 220 curve. In response, panto A (210) is moved to the right by a certain value (eg 1-10%) every specified lex interval. 1 to 365 days). If it is determined that point B (212) is to the right of the BEP curve 220, in response, point A (210) is moved pure to the left by a certain value (eg 1-10%) at each specified interval.
39/47
In a configuration example, if point B (212) is determined to be at the top of the BEP 220 curve in response. Point A (21: 0) and / or point C (214) are moved down a certain value (eg 1-10%) at each specified interval. If it is determined that point δ (212) is below the curve BEP 220, in response, point A (210) and / or point C (214) are moved up a certain value (eg 1-10%) at each specified interval.
[00114] In some example configurations, control pumps 102 are sensorless in the sense that they can be used to determine or calculate the required flow load without an external sensor. This is done by letting the control pump 102 autodetect the device properties, such as power and speed, as well as inferring or correlating the resulting column and flow, as described in detail above with respect to Figure 3.
[00115] Figure 12 illustrates an example of a block diagram of a circulation system 1200 with external sensors, according to another example in the configuration. Reference numerals similar to those in Figure 1 are used for reference purposes. Although the configuration examples above from Figures 9, 10A, 108, 10C and 11 were first described in the context of sensorless devices, in some other configuration examples, it may be appropriate to use external sensors. The 1200 system includes an external sensor 1,202 that can be used to detect, for example, pressure and flow. Another sensor 1204 can be used to detect, for example, the column and flow output of device 102. A controller 1206 can be in communication with one or both sensors 1202. 1204 to receive and track sensor measurements and control the operation of the control pump ($) 102. Likewise, any calculation in the configurations described with respect to Figures 9 to 11 that require the correlation or inference of a pressure or device properties column may otherwise be
40/47 determined using information measured by one or both sensors 1202 ,. 1204. For example, the configurations illustrated in Figures 9, 10A, 10B, 10C and 11 can be configured with external sensors, depending on the specific application.
[00116] Figure 13 illustrates an example of a control system 1300 to control an operable system 1302, according to an example of configuration. Generally, in the 1300 control system ,. outputs 1310 and inputs, including optimizable inputs 1304, are measured and an estimation method 1306 or algorithm is updated or adjusted for system 1302. In some example configurations, control system 1300 includes response circuit (s) that operate during the initial configuration, as well as the indefinite runtime of the 1302 system (continuously or at different times). In some configuration examples, little or no prior knowledge of the 1302 system is required. Instead, the 1300 control system controls and adapts its performance and control models based on the self-learning system 1302. In some example configurations, the 1302 system can be, for example, the circulation system 100 illustrated in Hgura 1 or the circulation system 1200 illustrated in Figure 12.
[00117] System 1302 produces certain outputs 1310 characterized by one or more variables (eg flow, temperature, viscosity, thickness, speed, thermal energy, items per minute, distance etc.), composed of several parts whose points of operation / paths can be characterized by a finite number of continuous variables or dysstinias (eg speed, temperature, power, running status, rpm, mode of operation, running, brake position, etc.).
[00118] These continuous or distinct variables work together to produce output 1310 (s) of system 1302, as well as to interact so that the operating point / path of an output variable determines or restricts the operating points other output variables.
41/47
There may also be restrictions on the operation of each part, ου ie, limited range (s) for the values that its operating point that characterizes one or more variables can assume. These continuous or discrete variables can include device properties of one or more controllable operable elements, such as a pump motor.
[00119] System 1302 includes one or more input variables, which may include one or more uncontrollable variables 1314 that are externally determined and cannot be controlled (eg external temperature, commodity prices, output demand, etc.). ) and that affect the operation of parts of the system or should be taken into account when deciding how to operate the 1302 system efficiently. · The 1302 system includes input variables such as one or more optimizable 1304 inputs that can be optimized. Examples of feasible input (s) 1304 can be consumable inputs such as energy, chemicals, water, money or time. Other input variables 1324 can also be entered in the .system 1302. As shown, input variables can be measured using measurement 1308 to adjust a parameter or determine or calculate the appropriate model using the 1320 adjustment module model. Input variables can include consumable inputs (energy, chemicals, etc.) or other inputs (external temperature, demand, speed, supply voltage, etc.).
[00120] In system 1302. there is more than one path or point of operation that can provide the desired output 1310, The control system 1300 is configured to produce the required output 1310 (to satisfy the demand for output) optimizing the use of a or more optimizable inputs 1304 needed to produce that output 1310.
[00121] In some examples of configurations, a method or model is provided for each part of the 1302 system, such as, for example, formula (s), table (s) and algorithm, to predict the number of entries
42/47 optimisables 1304 that system 1302 uses, for all operating points in this permitted range. An ideal path / point 1312 is then determined and updated by the estimation method 1306.
[00122] The point of operation of the system or system status 1322 is given by all the variables that can be characterized by the parts of the system, reduced by the restrictions imposed by the interaction or interconnection of the variables, and with a limited range by the operational restrictions of the parts.
[00123] For each operation point allowed by the system, the number of optimizable inputs 1304 that the system 1302 consumes can be calculated as the sum of the quantities consumed by each of its parts. The system's controllable variables are its characterization variables minus the externally determined non-controllable variable (s) 1314.
[00124] As shown in Figure 13, in some examples of configurations, due to the non-contractable (s) 1314 (the conditions under which the system has to work), the 1316 optimization module uses the method estimate 1306 to find an ideal path or tip 1312 that is compatible with the given conditions and then system 1302 is controlled by controller module 1318 to operate at that point or follow that path.
[00125] The use of input variables, including the ($) optimizable input (s) 13C4 is measured and the estimation method 1306 is updated using the adjustment module model 1320 to approximate its forecast for the reported status of the user's system 1322 or consumption measurement 1308 of optimizable inputs 1304.
[00126] Note that the optimization module 1316, controller 1318 and measurement module 1308 can reside in one or more devices, or be integrated in a 1302 system, which leads to different examples of configurations. In some configuration examples, the 1316 optimization method can be performed first by a device
43/47 microprocessor. A specific method or model can then be subsequently selected <5 from a set of predetermined methods or models that best optimize the path / optimal point 1312.
[00127] Dc the same way .. the control system 1300 controls the system 1302 to produce the desired output (s) 1310 while optimizing the use of one or more optimizable inputs. 1304 by dynamically determining an optimization method 1316 to predict the amount of optimizable input (s) 1304 used in each possible path or point of operation (eg trajectory of operation over time) that produces the output (s) ( s) necessary 1310 and then finding the path / optimum point 1312 and, finally, commanding the controllable variables 1304 to obtain this trajectory or optimum point 13'12.
[00128] In some examples of configurations, the use of optimizable inputs is estimated using explicit analytical formulas instead of 1308 measurements. In some example configurations, the use of optimizable system inputs is estimated using numeric tables .
[00129] Ern some examples of configurations, the module of estimation of the optimizable inputs 1306 or formulas is simple enough to allow the analytical resolution of the optimization and to obtain explicit, parametric formulas in the output (s) 1310 and non-variable controllable variables 1314, to control controllable variables 1304.
[00130] In some configuration examples, the 1316 optimization module is numerically solved first, thus resulting in one or more numerical tables and / or ern explicit formulas to command the 1304 controllable variables.
[00131] Ern some examples of configurations, the 1316 optimization module is performed by a microprocessor based on device execution software while the system is being
44/47 is executed and for the specific non-controllable conditions that the 1316 optimization module is encountering.
[00132] And some examples of configurations, the estimation module 1306 or the formulas have adjustment parameters and these and / or the values in the table (s) are periodically adjusted based on the actual use of the optimized measured inputs. A system test can be implemented at specific times to eliminate some variables to increase the accuracy of the 1306 estimation module.
[00133] Variations can be made in the example configurations of this disclosure. Some example configurations can be applied to any variable speed device and are not limited to variable speed control pumps. For example, some additional configurations may use different parameters or variables, in addition to being able to use more than two parameters (eg three parameters in a three-dimensional graph). For example, the speed (rpm) is also shown in the described control curves. In addition, the temperature (Fahrenheit) versus the load and temperature (BfU / hr) can be parameters or variables considered for control curves, for example, for the variable temperature control which can be controlled by a circulation fan. variable speed. Some example configurations can be applied to any devices that depend on two or more correlated parameters. Some example configurations may include parameter-dependent variables or variables such as liquid, temperature, viscosity, suction pressure, elevation of the site and number of pumps in operation.
[00134] In some configuration examples, as the case may be, each illustrated block or module may represent software, hardware or a combination of hardware and software. In addition, some blocks or modules can be combined in other example configurations and a greater or lesser number of blocks or modules may be
45/47 present in other example configurations. In addition, some blocks or modules can be separated into a number of sub-blocks or submodules in other configurations.
[00135] While some of the present configurations are described in terms of methods, a person with common capabilities in this matter will understand that the present configurations are also directed to various devices, such as servers, including components to perform at least some aspects and characteristics of the described methods , whether through hardware components, software or any combination of the two, or in any other way. In addition, an article of manufacture for use with the equipment, such as a pre-recorded storage device or other similar computer-readable non-transitory medium, including program instructions written on it or instructions for a data signal transport computer program computer readable, it can direct a device to facilitate the practice of the described methods. It is understood that such equipment, manufacturing articles and computer data signals are also within the scope of these example configurations.
[00136] While some of the examples above have been described as having occurred in a specific order, it will be ideal for people with skills in the subject that some of the messages or steps or processes can be carried out in a different order, provided that the result of the changed order of any specific step does not prevent or prevent subsequent steps from occurring. In addition, some of the messages or steps described above, can be removed or combined into other configurations, as well as can be separated into a number of sub-messages or substeps in other configurations. In addition, some or all of the conversation steps can be repeated as needed. The elements described as methods or steps apply in the same way to systems or subcomponents and vice versa.
46/47 [00137] The term computer-readable medium as used herein includes any medium that can store Instructions., Program steps or others, for use or execution by a computer or other computing device, including, among others: media magnetic disks, such as floppy disks, disk drives, magnetic drums, magneto-optical disks, magnetic tapes, magnetic core or other memories, electronic storage, such as random access memory (RAM) of any type, including static RAM, dynamic RAM, RAM synchronous dynamics (SDRAM), read-only memory (ROM), programmable read-only memory of any type, including PROM, EPROM, EEPROM. FLASH, EAROM, the so-called solid state disk, other electronic storage of any type, including a charge-coupled device (CCD), or magnetic bubble memory, portable electronic data transport card of any type, including COMPACT FLASH, SECURE DIGITAL (SD CARD), MEMORY STICK, and others: and optical media such as Compact Disc (CD), Versatile Digital Disc (DVD) or BLU-RAY Disc.
[00138] Variations can be made in some example configurations, which may include combinations and subcombination of any of the items above. The various configurations presented above are mere examples and are in no way intended to limit the scope of this disclosure. The variations of the innovations described here will be apparent to people with common skills in this matter with the benefit of this disclosure, and these variations are within the intended scope of this disclosure. In particular, the characteristics of one or more of the configurations described above can be selected to create alternative configurations that comprise a subcombination of characteristics that may not have been specifically described above. In addition, the characteristics of one or more of the configurations described above can be selected and combined to
47/47 create alternative configurations that comprise a combination of characteristics that may not have been explicitly described above. The characteristics suitable for such combinations and sub-combinations would be immediately apparent to persons with skills in this matter during a review of the present disclosure as a whole.
The object described here is intended to cover and include all appropriate changes in technology.

权利要求:
Claims (40)
[1]
CLAIMS:
1. CONTROL SYSTEM to control an operable flow system characterized by the photo comprising: one or more operator elements that result and output variables., At least one of the operable elements, Including a respective variably controllable motor, in which there is more of a path or operating point of the operating system system variables that can provide a given output set point, in which at least one system variable in one path or operating point restricts the operation of another system variable in the path or operating point; and one or more controllers configured to operate on a control circuit to:
detect input variables, with input variables including non-controllable variables and controllable system variables, with non-controllable variables including output demand, and the system's controllable variables include a speed of at least one of the variably controllable motors and at least minus one optimizable input variable, with at least one optimizable input variable including the consumed power, detect system variables, including pressure and flow of the operable flow system, update a model with respect to at least one optimizable input variable with based on the detected input variables and the system variables detected by applying a model fit to the model, with the updated model providing, based on the relationships established between the variables, a prediction of the use of the input variables in all possible paths or points of operation of system variables q u and obtain an exit setpoint; and operate, based on one or more input variables detected and system variables detected, one or more operable elements of /] 2 according to the updated model to provide an ideal operating path or point of system variables that obtain the output set point that optimizes the consumption of at least one optimizable input variable.
[2]
2. CONTROL SYSTEM, according to claim 1, characterized by the fact that the control circuit is performed during the initial configuration and in the subsequent operation of one or more operable elements in the operable system.
[3]
3. CONTROL SYSTEM, according to claim 1, characterized by the fact that an uncontrollable input variable includes a hydraulic resistance of the variable system of the operable flow system.
[4]
4. CONTROL SYSTEM, according to claim 1, characterized by the fact that one or more controllers are again configured to perform a system review through the specified operation of the output variables to calibrate at least one optimizable input variable.
[5]
5. CONTROL SYSTEM, according to claim 1, characterized by the fact that this update includes updating the model of subsequent iterations of the control circuit.
[6]
6. CONTROL SYSTEM, according to claim 1, characterized by the fact that the optimizable input variable comprises a power efficiency variable of one or more operable elements.
[7]
7. CONTROL SYSTEM, according to claim 1, characterized by the fact that this detection of the output variables comprises detecting device properties of the operable element and correlating the output variables.
[8]
8. CONTROL SYSTEM, according to claim 1, characterized by the fact that this update includes maintaining a value
Specified 3/12 average of at least one optimizable input variable
[9]
9. CONTROL SYSTEM, according to claim 1, characterized by the fact that this update includes maintaining a specified operating range of at least one optimizable input variable,
[10]
10. CONTROL SYSTEM, according to claim 1, characterized by the fact that this update includes maintaining a specified distribution, detected during a specified operating time of at least one optimizable input variable,
[11]
11. CONTROL SYSTEM, according to claim 1, characterized by the fact that at least one optimizable input variable is a consumable input variable
[12]
12. CONTROL SYSTEM, in accordance with claim 1, characterized by the fact that detecting system variables also includes correlating at least one of the system variables from at least one device property that is self-detected from one or more elements operable.
[13]
13. FLOW CONTROL SYSTEM to control a flow system characterized by the fact that it comprises:
one or more circulation pumps, with each having a variably controllable motor, resulting in output variables, including pressure and flow to the flow system; and one or more controllers configured to operate on a control circuit to:
detect input variables, with input variables including non-controllable variables and system-controllable variables, with non-controllable variables including output demand, and the system's controllable variables include a speed of at least one of the variably controllable motors and at least one optimizable input variable, with at least one optimizable input variable including the power consumed,
4/12 detect the a and output variables .. Including pressure and flow from the flow system, update a model in relation to at least one optimizable input variable earn base on at least one of the detected input variables and the detected output variables applying a model fit to the model, with the model providing, based on the relationships established between the variables, prediction of use of the input variables in all possible paths or operation points of the output variables that obtain an output set point, optimize a control curve according to the model in relation to at least one input variable that can be optimized based on the detected input variables and the detected output variables, with the control curve providing a path coordination or pressure operating point and the flow to obtain the exit set point; and operate, based on one or more variables detected by at least one of the variably controllable motors of one or more circulation shafts according to the control curve optimized to provide the path or point of operation of pressure and flow to obtain the output set point, which optimizes the consumption of at least one optimizable input variable.
[14]
14. FLOW CONTROL SYSTEM, according to claim 13. characterized by the fact that the control circuit is carried out during the initial configuration and in the subsequent operation of the variably controllable motors.
[15]
15. FLOW CONTROL SYSTEM, according to claim 13, characterized by the fact that one or more controllers are again configured to perform a system review through the specified operation of the output variables to calibrate at least one input variable optimizable.
[16]
16. FLOW CONTROL SYSTEM, according to
5/12 claim 13 .. characterized by the fact that this optimization includes updating the control curve parameters for subsequent iterations of the control circuit.
[17]
17. FLOW CONTROL SYSTEM, according to claim 13, characterized by the fact that an optimizable input variable comprises a power efficiency variable of at least one of the variably controllable motors.
[18]
18. FLOW CONTROL SYSTEM, according to claim 13, characterized by the fact that a power efficiency variable is a power efficiency curve of at least one of the variably controllable motors.
[19]
19. FLOW CONTROL SYSTEM, according to claim 13 .. characterized by the fact that this detection of the output variables comprises the correlation of the self-sensing device properties of at least one of the variably controllable motors with the output variables.
[20]
20. FLOW CONTROL SYSTEM, according to claim 13, characterized by the fact that an uncontrollable input variable includes a hydraulic resistance variable of the flow system.
[21]
21. FLOW CONTROL SYSTEM, according to claim 20, characterized by the fact that this optimization includes maintaining a specified average value of the system's hydraulic resistance variable,
[22]
22. FLOW CONTROL SYSTEM, according to claim 20, characterized by the fact that this optimization includes maintaining a specified operating range of the system's hydraulic resistance variable.
[23]
23. FLOW CONTROL SYSTEM, according to claim 20, characterized by the fact that this optimization includes
6/12 maintain a specified distribution detected during a specified operating time of the system's hydraulic resistance variable.
'
[24]
24. FLOW CONTROL SYSTEM, according to claim 13, characterized by the feeling that at least one of the optimizable input variables is a consumable input variable.
[25]
25. METHOD TO CONTROL AN OPERABLE FLOW SYSTEM, characterized by the fact that the operable system includes one or more operable elements that result and output variables, at least one of the operable elements, including a respective variably controllable motor, in which there is more of a path or operating point of the operating system system variables that can provide a given output set point, in which at least one system variable in one path or operating point restricts the operation of another system variable in the path or operating point, with the method being performed as a control circuit and comprising:
detect input variables, with input variables including non-controllable variables and controllable system variables, with non-controllable variables including output demand, and the system's controllable variables include a speed of at least one of the variably controllable motors and at least minus one optimizable input variable, with at least one optimizable input variable including power consumed:
detect system variables, including pressure and flow from the operable flow system, update a model with respect to at least one optimizable input variable based on detected input variables and detected system variables by applying a model fit to the model, with the updated model providing, based on the relationships established between the variables, a prediction of the use of the input variables in stumps the possible paths or points of operation of the
7/12 system variables that obtain an output setpoint; and operate, based on one or more detected input variables and detected system variables, one or more elements operable according to the updated model to provide an ideal operating path or point of system variables that obtain the setpoint of output and that optimizes the consumption of at least one optimizable input variable.
[26]
26. MEIQ NON-TRANSITIONAL LEGIBLE BY COMPUTER characterized by the fact that it comprises instructions that, when executed by one or more controllers, cause the controllers to control a flow system operable in a control circuit, in which the operable system includes a or more operable elements that result in output variables, with at least one of the operable elements including a respective variably controllable motor, in which there is more than one operating point or point of the operating system system variables that can provide a given output adjustment, in which at least one system variable in one operating path or point restricts the operation of another system variable in the operating path or point, with instructions comprising:
instructions for detecting input variables, with input variables including non-controllable variables and controllable system variables, with non-controllable variables including output demand, and the controllable system variables include a speed of at least one of the variably controllable motors and at least one optimizable input variable, with at least one optimizable input variable including the consumed power; instructions for detecting system variables, including pressure and flow from the operable flow system;
instructions to update a model with respect to at least one optimizable input variable based on the detected input variables and the detected system variables by applying an adjustment of
8/12 model to model, with the updated model providing, based on the relationships established between the variables, a prediction of the use of the input variables in all possible paths or points of operation of the system variables that obtain a setpoint of output; and instructions for operating, based on one or more detected input variables and detected system variables, one or more elements operable according to the updated model to provide an ideal operating path or point of system variables that obtain the output adjustment and that optimizes the consumption of at least one input variable input.
[27]
27. FLOW CONTROL SYSTEM to control a refrigerated circulation system that has a refrigerant characterized by the fact that it comprises:
one or more compressors, each with one or more variable controllable operable elements, including a respective engine, resulting in output variables, including elevation and flow to the refrigerant of the refrigerated circulation system; and one or more controllers configured to operate on a paro control circuit:
detect input variables, with input variables including non-controllable variables and controllable system variables, with non-controllable variables including output demand, and the system's controllable variables, including a speed of at least one of the motors and at least an optimizable input variable, with at least one optimizable input variable including the consumed power, detect the output variables, including elevation and flow, update a model with respect to at least one optimizable input variable based on at least one of the input variables detected and output variables detected by applying an adjustment of
9/12 model to model, with the model providing, based on the relationships established between the variables, a prediction of the use of the input variables in stumps the possible paths or points of operation of the output variables that obtain an output set point .
optimize the models in relation to at least one optimizable input variable based on the detected input variables and the detected output variables, with the model providing a coordination of the path or operating point of the outputs to obtain the output set point ; and operate, based on one or more variables detected by one or more of the variably controllable operable elements of one or more circulation pumps according to the model optimized to provide the way or point of operation of the outputs to obtain the set point output, which optimizes the consumption of at least one optimizable input variable including the power consumed.
[28]
28. FLOW CONTROL SYSTEM, according to claim 27, characterized by the fact that a refrigerated circulation system includes an interface in thermal communication with a secondary circulation system.
[29]
29. FLOW CONTROL SYSTEM, according to claim 27, characterized by the fact that the non-controllable variables include the external temperature.
[30]
30. FLOW CONTROL SYSTEM, according to claim 27, characterized by the fact that the output variables include a temperature variable to obtain the output set point.
[31]
31. CONTROL SYSTEM, according to claim 1, characterized by the fact that the operable flow system comprises a refrigerated circulation system that includes:
a refrigerant and in which one or more operable elements include
10/12 a compressor that has its respective variably controllable engine to control the refrigerant circulation, resulting in the output variables, including elevation and flow to the refrigerant.
[32]
32. CONTROL SYSTEM, according to claim 1, characterized by the fact that the output variables include a temperature variable to obtain the output set point.
[33]
33. CONTROL SYSTEM, according to claim 1, characterized by the fact that the non-controllable variables include the external temperature.
[34]
34. FLOW CONTROL SYSTEM, according to claim 13, characterized by the fact that the output variables include a temperature variable to obtain the output set point.
[35]
35. FLOW CONTROL SYSTEM, according to claim 13, characterized by the fact that the uncontrollable variables include the external temperature.
[36]
36. TEMPERATURE CONTROL SYSTEM to control a circulation system, characterized by the fact that the circulation system includes a circulation medium and an interface in thermal communication with a secondary circulation system, which comprises:
one or more operable elements that result and output variables, at least one of the operable elements, including a respective variably controllable motor, in which there is more than one operating point or point of the operating system system variables that can provide a given point output adjustment, in which at least one system variable in one operating path or point restricts the operation of another system variable in the operating path or point: and one or more controllers configured to operate in a control circuit for:
detect input variables, with input variables including
11/12 non-controllable variables and controllable system variables, with non-controllable variables including output demand, and the controllable variables of the system include a speed of at least one of the variably controllable motors and at least one optimizable input variable, with at least one optimizable input variable including the consumed power, detect the system variables, including the temperature of the circulation system.
update a model with respect to at least one optimizable input variable based on the detected input variables and detected system variables by applying a model fit to the model, with an updated model providing, based on the relationships established between the variables, a prediction of the use of the input variables in crooked the possible paths or points of operation of the system variables that obtain an output adjustment point; and operate, based on one or more detected input variables and detected system variables, one or more elements operable according to the updated model to provide an ideal operating path or point of system variables that obtain the setpoint of output and that optimizes the consumption of at least one optimizable input variable.
[37]
37. TEMPERATURE CONTROL SYSTEM, according to claim 36, characterized by the fact that the circulation system also comprises a refrigerated circulation system with one or more refrigeration coils, in which one or more operable elements include a variable compressor and in which the output demand includes the demand defined by the cooling coils and in which the circulation medium includes a refrigerant.
[38]
38. TEMPERATURE CONTROL SYSTEM, according to claim 36. characterized by the fact that the circulation system
12/12 further comprises a heating circulation system with one or more heating elements at the interface, in which one or more operable elements include a variable pump and in which the output demand includes the demand defined by the heating elements,
[39]
39. TEMPERATURE CONTROL SYSTEM, according to claim 36, characterized by the fact that the output variables include a temperature variable to obtain the output set point.
[40]
40. TEMPERATURE CONTROL SYSTEM, according to claim 36, characterized by the beech that non-controllable variables include the external temperature.

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法律状态:
2018-11-21| B06F| Objections, documents and/or translations needed after an examination request according [chapter 6.6 patent gazette]|

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2020-02-11| B06U| Preliminary requirement: requests with searches performed by other patent offices: procedure suspended [chapter 6.21 patent gazette]|

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2021-10-05| B07A| Application suspended after technical examination (opinion) [chapter 7.1 patent gazette]|

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2021-10-13| B350| Update of information on the portal [chapter 15.35 patent gazette]|

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2022-02-08| B06A| Patent application procedure suspended [chapter 6.1 patent gazette]|

优先权:

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申请号 | 申请日 | 专利标题

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US201261736051P| true| 2012-12-12|2012-12-12|

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US201361753549P| true| 2013-01-17|2013-01-17|

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PCT/CA2013/050868|WO2014089694A1|2012-12-12|2013-11-13|Self learning control system and method for optimizing a consumable input variable|

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