• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
  • 同族专利
  • 引用文献
  • 法律状态
  • 优先权
    • 专利摘要:
    The subject of the present invention is a method for estimating the angular position of a rotor with respect to a stator in a rotary electric machine (M), such as an electric machine of an electric or hybrid motorization system, comprising the estimation of the angular position and / or the rotational speed of the rotor (θHF, QHF) by a high frequency signal injection method as long as the absolute value of the rotational speed of the rotor derived from said rotor angular position, is less than a first predefined threshold (V1); the estimation of the angular position and / or the speed of rotation of the rotor (θML, ΩML) by a model resulting from a learning method as long as the absolute value of the rotational speed of the rotor, derived from said angular position, is greater than a second predefined threshold (V2).
    公开号:FR3062762A1
    申请号:FR1751047
    申请日:2017-02-08
    公开日:2018-08-10
    发明作者:Keyu Chen；Wided Zine；Lengfei Yu；Zaatar MAKNI
    申请人:Valeo Siemens eAutomotive France SAS；
    IPC主号:
    专利说明:

    TECHNICAL FIELD AND OBJECT OF THE INVENTION In general, the invention relates to the control of a rotary electric machine, in particular with a permanent magnet, of an electric drive system, such as for example an electric motorization system. electric or hybrid vehicle.
    In particular, the present invention relates to a method for estimating the angular position and the speed of the rotor of such electric drive systems.
    In fact, in a rotary electrical machine, in particular with a permanent magnet, the information on the angular position of the rotor is essential for controlling the production of the required drive torque.
    In general, a rotary electrical machine comprises a stator corresponding to the fixed part of the machine, and a rotor, corresponding to the rotary part of the machine. In particular in the context of an electric or hybrid vehicle motorization system, the rotor is integral with the motor shaft. To control the production of the rotor drive torque, and therefore the speed of rotation of the motor shaft driven in rotation by the rotary electric machine, it is essential to know at all times, with precision, the angular position of the engine shaft.
    In the prior art, a physical position sensor is placed in the electric machine. Such a sensor comprises a fixed part and a part arranged on the rotating part (rotor or motor shaft), making it possible to directly measure the angular position of the rotor. From this measurement derives the speed of rotation of the shaft, the torque to be produced by the electric machine driving said motor shaft being determined from these values. When the data from such a sensor is lost, for example because the said sensor is out of service, it is essential to obtain the angular position of the rotor by another means.
    STATE OF THE ART An immediate solution consists in ensuring redundancy by integrating at least one second physical sensor. However, physical sensor redundancy has a high cost, in particular not compatible with cost requirements in the automotive world.
    [0007] Alternatively, as is known, when the angular position sensor of the rotor is lost, the angular position of the rotor can be estimated by numerical methods. It can even be envisaged to replace the physical sensor (s) with one or more sufficiently precise digital estimators.
    Today, it is essentially the use of such degraded mode estimators, also called "limp-home" in English, which is envisaged in particular in the case of the electric vehicle. The principle of such a limp-home application lies in the implementation of a degraded mode of use of the motorization system which allows, in the automotive context, the vehicle to continue driving, in degraded conditions in terms of performance, so as to “go home” safely, despite the loss of the sensor giving direct information on the angular position of the motor shaft.
    [0009] Thus, the document Ehsan Dehgan-Azad et al., "Sensorless Control of IM for limp-home Mode EV Applications", in IEEE Transactions on Power Electronics describes a limp-home application, relating to an asynchronous electric motor, the method described being based on the modeling of the behavior of the electric machine of the motorization system. From this model derives the estimate of the angular position of the motor shaft. However, the frozen model described in this document does not work correctly at low speed. In addition, it cannot be transposed without adapting the model and its performance has only been proven for the case of an asynchronous electric machine in the context of this publication.
    In document US 20110028975 in particular, another technique for estimating the angular position of a rotor in a rotary electric machine is described. The estimation method described in this document implements a well-known technique based on the injection of high-frequency signals superimposed on the fundamental of the excitation voltage of the electric machine. In this case, the high frequency voltage injected is added to the voltage from the controller responsible for controlling the electric currents supplying the electric machine. At the output of the electric machine, the current comprises a high frequency component which, after treatment, makes it possible to estimate the angular position of the rotor.
    However, this known technique based on the injection of high frequency signals does not give satisfactory results, in particular at high speed, since the injected voltage generates increasing losses, ie of detrimental electrical consumption, in particular in a electric vehicle. In addition, this technique generates torque oscillations that can affect the operation of the electric drive.
    There is therefore a need for a method for estimating the angular position of a motor shaft of an electric or hybrid motorization system which operates in a reliable, stable and precise manner, both at rotational speed of the rotor. reduced or even zero only at medium or high rotor speed.
    To this end, the present invention provides in particular the combination of an estimation technique by injection of high frequency signals, at low speed of rotation of the shaft, and an estimation technique by means of '' a learned model, in particular based on a neural network, with medium or high rotational speed of the rotor.
    GENERAL PRESENTATION OF THE INVENTION More specifically, the subject of the present invention is a method for estimating the angular position of a rotor relative to a stator in a rotary electric machine, such as an electric machine an electric or hybrid motorization system, comprising:
    the estimation of the angular position and / or of the speed of rotation of the rotor by a method of injecting high frequency signals as long as the absolute value of the speed of rotation of the rotor, derived from said angular position, is less than a first predefined threshold;
    the estimate of the angular position and / or of the speed of rotation of the rotor by a model resulting from a learning method as long as the absolute value of the speed of rotation of the rotor, derived from said angular position, is greater at a second predefined threshold.
    Thanks to the present invention, in particular in the event of a defect in a physical sensor which is supposed to supply the torque control module generated by a rotary electric machine, for example integrated into an electric or hybrid motorization system, in particular of a vehicle. , a reliable estimate of the angular position and / or the speed of the rotor is available, precise and stable, whatever the speed of rotation of the rotor.
    In particular, the model is formed by a learning process which establishes a correspondence between the currents and the phase voltages on one side and the position of the rotor on the other. The estimation of the angular position by the model resulting from the learning method is precise at medium and high speed. However, at low speed and especially around a zero speed, the estimate operating by means of a learned model is imprecise. Estimation by an injection method overcomes inaccuracy at low speed.
    Advantageously, the model includes a neural network whose weights and / or internal connections are taken from the learning method.
    According to one embodiment, the method of injecting high frequency signals is a pulsating method.
    According to one embodiment, the method of injecting high frequency signals is a rotary method.
    In addition, the invention relates to a method for controlling an electric machine, in particular the torque it produces, its speed or its currents.
    According to one embodiment, such a method relates to a method for controlling the torque produced by a rotary electric machine, in particular with permanent magnets, said electric machine comprising a rotor and a stator, a physical sensor measuring the angular position and / or the speed of rotation of the rotor, said method comprising controlling the torque to be produced by the electric machine as a function of the angular position and / or of the speed of rotation of the rotor measured by the physical sensor as long as said physical sensor is available and , if said physical sensor is faulty, the control of the torque to be produced by the electric machine as a function of the angular position and / or of the estimated speed of rotation of the rotor, according to the method as briefly described above.
    In practice, a specific process can then provide information relating to the fact that the physical sensor is faulty.
    Advantageously, according to one embodiment, the torque generated by the electric machine has a maximum value corresponding to a maximum achievable current or to a maximum available voltage, and, in the event of a fault in the physical sensor, the maximum value of the torque generated by the electric machine is reduced to correspond to a degraded maximum torque.
    Furthermore, the present invention relates to a device for controlling an inverter supplying the phases of a stator of a rotary electric machine further comprising a rotor, said control device comprising a module for estimating the position. estimated angular and / or said rotational speed derived from said angular position of the rotor configured to implement the method briefly presented above, said estimated angular position and / or said rotational speed derived from said angular position of the rotor being taken into account account for the control of said inverter.
    According to one embodiment, such a device for controlling an inverter comprises a first estimator for estimating the angular position and / or the speed of rotation of the rotor by a high signal injection method frequency, a second estimator for estimating the angular position and / or the rotational speed of the rotor by a model from a learning method and a decision module for making the selection, as a function of the speed derived from the angular position of the rotor from the first estimator or from the second estimator, from the first or from the second estimator as the source of the estimated angular position and / or of the rotational speed taken into account for the control of said inverter.
    The present invention also relates to an electric or hybrid motorization system for a vehicle, comprising a motor shaft driven by a rotor of a rotary electric machine further comprising a stator supplied by an inverter, as well as a device for controlling the inverter as briefly presented above.
    The present invention also relates to a motor vehicle comprising an electric or hybrid motorization system as briefly described above.
    DESCRIPTION OF THE FIGURES The invention will be better understood on reading the description which follows, given solely by way of example, and referring to the attached drawings which represent:
    Figure 1, the block diagram of an electric motor system implementing the method according to the invention;
    FIG. 2, the block diagram representing the steps of the method according to the invention;
    - Figure 3, the logic diagram representing the operation of the decision module.
    DETAILED DESCRIPTION OF THE INVENTION It is recalled that the present invention is described below using various nonlimiting embodiments and is capable of being implemented in variants within the scope of skilled in the art, also referred to by the present invention.
    In particular, if the present invention preferably relates to an application to an operating mode of the “limp-home” type in a motor vehicle, any implementation of the invention for the estimation of the angular position of a rotor of a rotating electrical machine, in any electrical drive system, is also targeted. More generally, the present invention thus provides a method for estimating the angular position of a rotor relative to a stator, in particular in an electric motor with permanent magnets. In addition to the electric machine of an electric or hybrid motorization system of a vehicle, it can for example be the determination of the angular position and the speed of the rotor of an electric machine of a cooling system for example.
    Figure 1 shows the diagram of an electric drive system using the invention, in particular to allow the implementation of a limp-home application in a vehicle.
    The electric drive system shown diagrammatically in FIG. 1 comprises: a DC battery ensuring the supply of direct voltage; an INV inverter;
    an electric machine M;
    a control module C, in this case presenting a limp-home operating mode.
    The power stage, comprising the DC battery and the INV inverter, supplying the electric machine M, is here three-phase, but it might as well have a different number of phases.
    The control module C comprises a control module TCV of the torque requested on the power stage. The input data supplied to said TCV torque control module are the angular position θ of the rotor and the rotation speed Ω of the rotor derived therefrom, as well as the phase currents of the electric machine M. These angular position data and speed, as appropriate, from the physical sensor
    S, the first HF estimator based on the injection of high frequency signals or the second ML estimator based on a learning method.
    According to one embodiment, for use in limp-home mode for the control of a degraded operating mode of an electric or hybrid vehicle engine system, the control module C also has a limp-home module LH capable of acquiring information F D of a fault with the physical sensor S or of detecting such a fault, by suitable means, to control, if necessary, a power limitation of the electric drive system by adapted means PL, and to make the choice, by means of the decision module D, between the information coming from the first HF estimator based on the injection of high frequency signals and that coming from the second estimator ML based on a learning method, in order to provide the best estimates 0 tr , Q tr of angular position and speed of the rotor to the torque control module TCV in the event of a fault in the physical sensor S.
    In practice, in the event of a fault in the physical sensor, a specific method determines whether the physical sensor is in default and if necessary communicates the information F d relating to the fact that said physical sensor is in default in the decision module D Module D selects the estimated position and speed 0 tr , Q tr intended for use in the TCV module. According to the preferred embodiment, the first HF estimator and the second ML estimator operate continuously, in the sense that they estimate the angular position and the speed of the rotor at all times, whether the physical sensor S is functioning correctly or is faulty, and whatever the rotational speed of the rotor.
    In practice, if no fault of the physical sensor S is detected, the angular position and speed information of the shaft 0S, QS are supplied to the torque control module TCV by said physical sensor S.
    Referring to Figure 2, in the event of detection of a defect in the physical sensor S (step E1), the information Qtr, Qtr of estimated angular position and rotor speed are transmitted to the torque control module TCV . The angular positions and rotational speeds of the rotor estimated by the first HF, QHF, QHF estimator, and by the second ML, QML, QML estimator, are decided according to the estimated rotational speed of the rotor (step E2).
    The information Qtr, Qtr transmitted to the torque control module TCV are therefore either the angular position and rotational speed of the rotor QHF, QHF estimated by the first HF estimator, or those QML, QML estimated by the second estimator ML, according to the estimator selected by the decision module D.
    Thus, if the estimated speed of the tree at the previous sampling instant is less than a predetermined threshold, the first HF estimator is selected and the 0HF, QHF estimates which result therefrom are supplied to the module of TCV torque control (step E3); otherwise, if the estimated speed of the rotor at the previous sampling instant is greater than the predetermined threshold, the 0ML, QML estimates from the second ML estimator are supplied to the torque control module TCV (step E4).
    Step E4 also comprises, according to one embodiment, a substep for sending a signal F H Fau torque control module TCV configured so that the latter controls the activation or deactivation of the high frequency voltage injection. Said signal consists for example of a boolean allowing the activation by the control module of the TCV torque of the high frequency voltage injection if the estimated speed of the rotor implies that the estimates coming from the first HF estimator are those which will be processed by said TCV torque control module and, conversely, deactivation by the TCV torque control module of high frequency voltage injection when the estimated speed of the rotor implies that the estimates from the second ML estimator are those which will be processed by said TCV torque control module.
    In parallel, according to the embodiment relating to the implementation of a limp-home type operation of an electric or hybrid vehicle, the TCV torque control module is informed of a power limitation maximum authorized, so as to determine a torque requested from the power chain which is compatible with this power limitation (step E10).
    It should be noted that the first HF estimator as the second ML estimator carry out their 0HF, QHF, 0ML, QML estimates relating to the angular position and the speed of the rotor from current measurements i a bc and references. of voltage v abc of each phase of the electric machine.
    The determination of the speed threshold depends on the characteristics of the electric machine and the actual performance of the first and second HF, ML estimators.
    Referring to Figure 3, according to a preferred embodiment, there is provided a hysteresis H around the predetermined threshold speed to avoid any oscillation between one estimator and another in the case where the rotor speed is close to the value of the predetermined threshold chosen. Thus, the first HF estimator is selected by the decision module D as long as the estimated rotation speed of the rotor is less than a first predetermined threshold V1 beyond which the second estimator ML is selected. The switch from the second estimator ML to the first estimator HF is carried out by the decision module D when the estimated rotation speed of the rotor becomes less than a second predetermined threshold V2, less than the first threshold.
    In practice, said predetermined threshold and in particular the hysteresis are preferably chosen at a value where the first and second HF, ML estimators are stable. In addition, there is an advantage, since the second ML estimator gives precise and stable results, in stopping the injection of high frequency signals, in order to avoid any electrical overconsumption and any oscillation of the torque. With the exception of the above-mentioned hysteresis, the threshold can therefore be determined as being the minimum speed of the rotor from which the second estimator ML is able to estimate the angular position of the rotor in a stable and precise manner.
    For example, in the context of an electric or hybrid motor vehicle system, the predetermined threshold of rotor rotation speed is set at 1500 rpm for a maximum speed of the machine around 15000 rpm min (about 10% of the maximum speed). In this case, in the event of a defect in the physical sensor S, the first HF estimator is chosen to supply the angular position and speed of the rotor 0 tr , Q tr to the torque control module TCV as long as the rotation speed of the rotor is less than 1500 rpm. Beyond 1500 revolutions / min, it is the second ML estimator which provides the 0 tr , Q tr estimates of angular position and speed of the rotor to the TCV torque control module in the event of a fault in the physical sensor S. De preferably, the permutation between the first HF estimator and the second ML estimator, and vice versa, occurs according to a hysteresis based on the value of the predetermined threshold of 1500 revolutions / min. In this case, for example, the first HF estimator is selected by the decision module D as long as the estimated rotation speed of the rotor is less than 1500 revolutions / min; beyond this speed, the second estimator ML is selected by the decision module D. Consequently, the switch to the first estimator is carried out when the estimated rotation speed of the rotor becomes less than 500 rpm.
    As already mentioned, a main application of the present invention lies in the implementation of a degraded mode of control of the torque generated by the electric machine in the event of a fault in the physical sensor S.
    In this case, the angular position and rotor speed data measured directly OS, QS by the physical sensor S are used by the torque control module TCV as long as said physical sensor S is available. As soon as a fault with the physical sensor S is detected, the torque control module TCV receives the estimates relating to the angular position and the speed of the rotor from either the first HF estimator or the second ML estimator, in accordance with the method previously described.
    In this degraded mode, preferably, the power of the machine is limited, which consequently limits the maximum authorized torque that can be generated by the electric machine M, the aim being to allow a “return home” from the vehicle in good safety conditions, that is to say in particular by avoiding any exceptional measure of the "emergency stop" type, it being understood that the estimates of the angular position and of the speed of the rotor, these data being necessary upon precise control of the torque requested from the electric machine M, are considered a priori less reliable than those from the physical sensor S.
    However, other applications of the invention, independent of the limphoma mode, are also envisaged. In particular, the values estimated by the first HF estimator and / or the second ML estimator, as the case may be, can be compared with the data coming from the physical sensor S for a consistency check, or even to detect a possible defect of said physical sensor S in the part of a safety application.
    For example, the angular position obtained by the present method can be used to calculate an estimate of the torque. By comparing the estimated torque with the torque reference, we can then check for the presence of a fault.
    In addition, a use of the double estimate of the angular position and the speed of the rotor is envisaged for an application "without sensor" allowing the control of an electric machine, in particular of the torque generated by such an electric machine. an electric or hybrid motorization system.
    In the following description, several references are associated respectively with the stator and the rotor of the rotary electric machine M.
    First, a three-axis fixed reference frame is linked to the stator. This three-phase landmark is often noted, in the state of the art, (u, v, w) or (a, b, c).
    The reference (α, β) is obtained via a transformation of "Clarke" (amplitude conservation) or of "Concordia" (power conservation) of the fixed three-phase reference presented above, linked to the stator of the machine electric.
    The reference (d, q) corresponds to a common coordinate system making it possible to represent the stator windings as well as the rotor winding of the electric machine on a single reference frame with two axes (d, q). It is obtained by applying a rotation of an angle θ, Θ being the current angular position of the rotor, at the two-phase frame (α, β), or by applying the "Park" transform to the three-phase stator frame (u, v, w).
    Example of an estimation method using the first HF estimator The first HF estimator is based on the injection of high frequency signals superimposed on the control voltages of the torque of the electric machine M. Preferably, the first HF estimator implements a pulsating method, considered to be simpler and therefore lighter in view of its implementation on an on-board microcontroller, since the latter is limited in terms of computing capacities. However, provision may be made for the implementation of a rotary method.
    According to the pulsating method, the voltage Vh of frequency fh is injected on the estimated axis d of the rotor and superimposed on the reference voltage from the control module in order to control the inverter INV in turn supplying the machine electric M.
    In the estimated coordinate system (d, q), the expression of the high frequency component of the current is such that:
    Where hip _ (Ld + LqMji | Ihn _ (^ d '2.Wj l L ( iLq 2' 2.Wj l L ( iLq
    L d and L q are the inductances of the electric machine expressed in the reference (d, q). Their values are sensitive to the level of the current. Ldet Lq are here considered as average values over the whole range of the variation of the current, w h = 2nf h ,
    0 err is the error between the estimated value of the angular position of the rotor and its actual position, there results therefrom, after processing, the error 0 err on the angular position estimated by the first HF estimator. From this error, thanks to an integral proportional observer, the speed of the rotor is calculated, as well as the angular position of the rotor by integration of said speed.
    Example of an estimation method using the second ML estimator The second estimator determines the angular position and the speed of the rotor using a model obtained from learning. According to the preferred embodiment, the model comprises a neural network whose weights and / or connections are derived from said learning.
    Such a second ML estimator, based on a neural network, is typically constructed using the Matlab Neuronal Network Toolbox software, using statistical and technical data notably obtained from Μ. B. Howard Demuth et al., Neural Network Toolbox: For Use with MATLAB, MathWorks, 2009.
    The behavior of the neural network is defined by the connection of individual elements and the weight given to each. The weights of the individual elements are adjusted according to a specific training, called learning.
    It is therefore necessary to meticulously acquire precise data dedicated to learning, that is to say the currents Ι α , Ιβ, and the voltages ν α , ν β described below, and the corresponding angular position. The learning process of the second estimator ML then makes it possible to generate a function for estimating the angular position of the rotor, in the application considered. Said estimation function is written:
    θ = ί (Ι α , Ι β , ν α , ν β ) where Ι α , Ιβ, ν α , ν β are the currents and voltages in the fixed frame of reference (α, β) respectively. Said currents expressed in the frame of reference (α, β) are obtained, after a "Concordia" transform, from measurements of three-phase currents. The voltages expressed in the reference (α, β) are digital measurements from the TCV control module; more precisely, it is, according to one embodiment, the components of the reference voltage coming from the control module TCV, expressed in the reference frame (α, β).
    A homogeneous mesh is produced in a range of engine speeds covering the entire range of implementation of the second ML estimator, making it possible to establish a correspondence between said currents and said voltages Ι α , Ιβ, V a , Vp. el the angular position of the rotor, thanks to a panel of verified data.
    From then on, the learning function makes it possible to obtain a neural network configured to autonomously estimate the angular position and the speed of the rotor from the currents and voltages I a , Ip, V a , Vp, in particular from the currents Ι α , Ι β obtained from current measurements and voltages ν α , ν β corresponding to reference voltages.
    权利要求:
    Claims (10)
    [1" id="c-fr-0001]
    1. A method for estimating the angular position of a rotor relative to a stator of a rotary electric machine, such as an electric machine of an electric or hybrid motorization system, comprising:
    - the estimate (E3) of the angular position and / or the speed of rotation of the rotor (OHF, QHF) by a method of injecting high frequency signals as long as the absolute value of the speed of rotation of the rotor, derived of said angular position, is less than a first predefined threshold (V1);
    - the estimate (E4) of the angular position and / or of the speed of rotation of the rotor (0ML, QML) by a model resulting from a learning method as long as the absolute value of the speed of rotation of the rotor, derived from said angular position, is greater than a second predefined threshold (V2).
    [2" id="c-fr-0002]
    2. Method according to claim 1, in which the model comprises a neural network whose weights and / or internal connections result from the learning method.
    [3" id="c-fr-0003]
    3. Method according to one of the preceding claims, wherein the method of injecting high frequency signals is a pulsating method.
    [4" id="c-fr-0004]
    4. Method according to one of claims 1 or 2, wherein the method of injecting high frequency signals is a rotary method.
    [5" id="c-fr-0005]
    5. Method for controlling the torque produced by a rotary electric machine (M), in particular with permanent magnets, said electric machine (M) comprising a rotor and a stator, a physical sensor measuring the angular position and / or the speed of rotation of the rotor, said method comprising controlling the torque to be produced by the electric machine as a function of the angular position and / or of the speed of rotation of the rotor measured (0S, QS) by the physical sensor (S) as long as said physical sensor is available and, if said physical sensor (S) is faulty, control of the torque to be produced by the electric machine as a function of the estimated angular position and / or rotation speed of the rotor, according to the method according to one of the preceding claims.
    [6" id="c-fr-0006]
    6. Method according to the preceding claim, the torque generated by the electric machine (M) having a maximum value corresponding to a maximum attainable current or to a maximum available voltage, in which, in the event of a fault in the physical sensor (S), the maximum value of the torque generated by the electric machine is reduced to correspond to a degraded maximum torque.
    [7" id="c-fr-0007]
    7. Inverter control device (INV) supplying the phases of a stator of a rotary electrical machine (M) further comprising a rotor, said control device comprising a module for estimating the angular position and / or of the speed of rotation of the rotor configured to implement the method according to one of claims 1 to 4, said estimated angular position and / or said speed of rotation derived from said angular position of the rotor being taken into account for the control of said inverter (INV).
    [8" id="c-fr-0008]
    8. Device according to the preceding claim, comprising a first estimator (HF) for estimating the angular position and / or the speed of rotation of the rotor by a method of injecting high frequency signals, a second estimator (ML ) to estimate the angular position and / or the rotational speed of the rotor by the model from a learning method and a decision module (D) to make the selection, depending on the speed of the rotor derived from the angular position from the first estimator or the second estimator, from the first (HF) or from the second (ML) estimator as source of the estimated angular position and / or of the rotational speed of the rotor taken into account for the control of said inverter (INV).
    [9" id="c-fr-0009]
    9. Electric or hybrid motorization system for a vehicle, comprising a motor shaft driven by a rotor of a rotary electric machine (M) further comprising a stator supplied by an inverter (INV), as well as a device for controlling the inverter according to claim 7 or 8.
    [10" id="c-fr-0010]
    10. Motor vehicle comprising an electric or hybrid motorization system according to the preceding claim.
    1/2
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    同族专利:
    公开号 | 公开日
    CN108400740A|2018-08-14|
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    FR3062762B1|2020-08-07|
    引用文献:
    公开号 | 申请日 | 公开日 | 申请人 | 专利标题
    US20090039810A1|2007-08-06|2009-02-12|Baumuller Nurnberg Gmbh|System for seamless estimation of speed and/or position, including standstill of a permanent magnet rotor of an electric motor|
    US20160329849A1|2014-04-29|2016-11-10|Mitsubishi Electric Corporation|Ac rotating machine control device and electric power steering device equipped with same|
    US9325263B1|2014-11-05|2016-04-26|Stmicroelectronics S.R.L.|Sensorless rotor angle detection circuit and method for a permanent magnet synchronous machine|
    FR3028690A1|2014-11-18|2016-05-20|Renault Sa|METHOD FOR CONTROLLING A SYNCHRONOUS ROTOR COIL ELECTRIC MACHINE|
    US8269445B2|2009-10-20|2012-09-18|GM Global Technology Operations LLC|Limp home operational mode for an electric vehicle|CN109560735B|2018-12-03|2020-08-21|中冶南方（武汉）自动化有限公司|Rotation failure limping control method for main driving permanent magnet synchronous motor for vehicle|
    WO2020223329A1|2019-04-30|2020-11-05|Brookhaven Science Associates, Llc|Method and device for detection of condition of brushless motors and generators|
    CN110707967A|2019-09-10|2020-01-17|上海航天控制技术研究所|Self-adaptive control method of brushless direct current motor|
    CN111173681B|2020-01-09|2021-06-22|曲阜师范大学|Magnetic suspension vertical axis wind turbine generator suspension control method based on sliding mode neural network|
    CN111677853B|2020-05-09|2021-11-19|联合轲麟新能源科技有限公司|Transmission control system for low-speed region of vehicle, automobile and control method|
    CN112271974A|2020-10-10|2021-01-26|南京理工大学|Motor rotating speed estimation method based on basal ganglia|
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    优先权:
    申请号 | 申请日 | 专利标题
    FR1751047A|FR3062762B1|2017-02-08|2017-02-08|METHOD FOR ESTIMATING THE ANGULAR POSITION OF A ROTOR OF AN ELECTRICAL DRIVE SYSTEM|
    FR1751047|2017-02-08|FR1751047A| FR3062762B1|2017-02-08|2017-02-08|METHOD FOR ESTIMATING THE ANGULAR POSITION OF A ROTOR OF AN ELECTRICAL DRIVE SYSTEM|
    CN201710247243.9A| CN108400740A|2017-02-08|2017-04-14|Evaluation method, Torque Control method, control device, dynamical system, vehicle|
    US15/890,479| US10193477B2|2017-02-08|2018-02-07|Method for estimating the angular position of a rotor of an electric drive system|
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