• 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:
    A method for optimizing internal combustion engines, in particular for optimizing emissions and / or consumption, in which optionally at least one of the secondary influencing variables is set via correction functions in their control units at each operating point in such a way that the emission limit values are maintained in a defined cycle of operating points, is thus improved will be able to automatically automate as many steps as possible, from measuring on the engine test bench to modeling and calibrating ECU parameters. For this purpose, it is provided that in a first step, a test plan for the main influencing variables and secondary factors using mathematical models of the control unit functions and the internal combustion engine is created with respect to the size to be optimized and driven on the test bench, based on these models, the optimal values of the side influence variables Compliance with the emission limit values determined and these values are used for Erstbedatung the correction functions in the control unit.
    公开号:AT510912A2
    申请号:T50060/2012
    申请日:2012-03-06
    公开日:2012-07-15
    发明作者:Harald Dipl Ing Dr Altenstrasser；Adnand Dipl Ing Dragoti；Nikolaus Dipl Ing Dr Keuth
    申请人:Avl List Gmbh；
    IPC主号:
    专利说明:

    Pripted: 07-03-2012 E014.1 10 2012/50060
    AV-3467 AT
    Method for optimizing the emission of internal combustion engines
    The invention relates to a method for optimizing internal combustion engines, in particular for emission and / or consumption optimization, in which optionally at least one of the secondary factors is adjusted via correction functions in their control units at each operating point such that the emission limit values are met in a defined cycle of operating points.
    In order to be able to comply with emissions standards for emissions, it is necessary to tune an internal combustion engine so that the emission limit values are met both in warm and in warm-up mode. For this reason, there are correction functions in engine control units that adjust the basic parameters, such as start of injection, intake manifold pressure, injection duration, etc., depending on the cooling water temperature, load and speed. The parameters of these functions are designed as characteristic maps or characteristic curves. The calibration engineer has the task of adapting these parameters to a specific engine in a vehicle in order to comply with the emission limit values. This previously manual vote is very time consuming.
    It was therefore the object of the present invention to carry out the described process largely automatically, starting with the measurement on the engine test bench, via modeling to the calibration of the control unit parameters.
    To solve this problem, the invention is characterized in that in a first step, an experimental plan for the main influencing variables and secondary factors using mathematical models of the control unit functions and the internal combustion engine is created with respect to the size to be optimized and driven off the test bench, based on these models the optimal values of the secondary factors are determined in compliance with the emission limit values and these values are used for the initial evaluation of the correction functions in the control unit.
    According to a first embodiment variant, it is provided that dynamic models are evaluated under stationary conditions and used in the optimization.
    Preferably, the operating points are given by the parameters temperature, load and speed. n «_nc * _orHo 1
    Prjfited: 07-03-2012 E014.1 102012/50060
    AV-3467 AT
    It is vorteithafterweise provided that at least three different temperature levels are specified for the parameter temperature.
    A further embodiment variant of the method according to the invention is characterized in that the operating range of the internal combustion engine is divided into several areas, wherein separate test plans are created and plausibilized on the test bench for each subarea, and partial global models are created from the measured data for each subarea.
    The experimental plans in each subarea are preferably created by a two-stage global experimental design.
    It can also be provided that create partial global models for each sub-area.
    Another variant of the method provides that dynamic models of the variable to be optimized over the entire operating range of the internal combustion engine are created on the basis of a dynamic test plan. Typically, online trial planning methods are based on an initial design plan that is calculated off-line and then adjusted during measurement to the process to be measured (i.e., the engine here) using a mathematical model. After the measurement of the specimen then not only measurement data has been generated, which can be used for modeling, but is also a finished model, for example, the internal combustion engine, based on the main factors such as load, speed and according to the invention also temperature, and the secondary factors (ECU sizes ) to disposal. This model can be used directly for the definition of the temperature correction functions. The method for online and offline modeling, for example, based on neuro-fuzzy approaches. The determination of the submodels can be based, for example, on a decisiontree method in which the division of the input space is determined by hyperplanes. The overall process model can also be divided into several submodels, whereby between dynamic and stationary processes is separated and outputs of the individual stages are used as inputs for each next modeling stage. The training of the individual model stages is preferably performed by the method as described above (online and offline modeling). 2
    Pri, nted: 07-03-2012 E014.1 10 2012/50060
    AV-3467 AT
    In all of the variants described above, the correction functions can advantageously consist of a basic map for a reference temperature of the internal combustion engine and at least one correction map for the internal combustion engine at a further reference temperature, which correction map is added to the output of the basic map by means of a factor map as a function of the current temperature of the internal combustion engine ,
    It is preferably provided that a model-based function optimization is carried out for the characteristic maps, wherein the values are optimized on the nodes of the corresponding maps.
    In the following description, the invention will be described using the example of the emission optimization of an internal combustion engine, a temperature correction function and with reference to the drawing figures.
    1 shows an example of the assignment of individual models to the associated regions of the test cycle, FIG. 2 is a schematic block diagram for determining the overall cycle result, and FIG. 3 shows a diagram of the evaluation results for a simulated cycle result.
    When driving through, for example, the NEDC cycle, as prescribed for the certification of vehicles, in addition to different load-speed ranges, different temperature ranges, from the cold engine to the warm engine, are traversed.
    In order to be able to calibrate the control unit functions semi-automatically and thus time-effectively, it is necessary to have mathematical models of the control unit functions as well as the engine with regard to emissions.
    The experimental design, surveying and modeling can be done in two different ways. A first method is a stationary procedure. In order to be able to create the emission models - or models for each variable to be optimized, in particular the fuel consumption - the operating range of the engine is divided into several areas. In each subarea, test plans for load, speed, cooling water temperature and all other variation parameters are created using the method of two-stage modeling, as described, for example, in EP 2088486 A. The partial ranges differ due to different operating strategies of the motor control in the number of variation parameters. The test plans created in this way are automatically run on the engine test bench 3
    Printed: 07-03-2012 E014.1 10 2012/50060
    AV-3467 AT and plausibility. From the measured data, partial global models are compiled for each subregion, as disclosed, for example, in the AT 7710 U.
    Another method is based on a dynamic modeling method, in which the time behavior of the engine can be mapped. On the basis of a dynamic design based on, for example, the method described in "Analytic Model Based Design of Experiments", M. Stadlbauer et al., Design of Experiments in Engine Development, 2010, Expert-Verlag, also extended to variations for the water temperature, Dynamic emission models are created over the entire operating range of the engine, as exemplified in "Dynamic Modeling using local model networks", C. Hametner et al., Design of Experiments in Engine Development, 2010, Expert Publishing or "Global Dynamic Modeling: A consistent Approach for both diesel and gasoline engines ", K. Shimojo et al., Design of Experiments in Engine Development, 2010, Expert Publishing.
    Based on these models, gradient-based optimization or genetic algorithms at several temperatures and at several load / speed points will determine the optimal values for the variation parameters while respecting the emission limits set out in the exhaust emission standard. The dynamic models are evaluated under stationary conditions and used in the optimization. The results from the optimization will be used in the next step for the initial evaluation of the maps and characteristic curves in the ECU function. When selecting the temperatures for which the optimization is to be performed, it is important that at least three temperature levels be selected. The highest level is often 85 ° C for a base rating and the lowest level is often 40 ° for the correction of the cold engine timing correction map ,
    The correction functions usually consist of a basic map which contains the settings for the warm engine. Furthermore, there is at least one correction map which applies to the cold engine. By means of a factor map, this correction map is added to the output of the basic map, depending on the current engine temperature.
    The generated optimization results contain optimal settings for all parameters and all temperatures. By means of a grouping, the data for the respective temperatures can be separated. Decisive here is the determination of a "base temperature". 4
    Printed: 07-03-2012 E014.1 10 2012/50060
    AV-3467 AT and a "correction temperature". All other temperatures are called "intermediate temperatures". designated.
    By means of the data of the base temperature, the basic map can be calculated. Subsequently, the correction map can be calculated by means of the output from the basic map and the data from the correction temperature. Finally, the factor map is calculated by means of the data of all intermediate temperatures and the outputs from the basic and correction map. The following applies: Correction map = OptimizationData_correction temperature - Basic map and: Interim map = (OptimizationData_AllTemperatures - Basic map) / Correction map.
    The maps calculated in this way are described below as "start values". used for a model-based function optimization. In this case, the parameters of variation are no longer directly optimized but the values on the interpolation points of the corresponding characteristic diagrams. It starts with the optimization of the basic maps with a warm engine. Based on the result of this optimization, in the next step, the correction maps are optimized when the engine is cold. Finally, based on the already calculated base and correction maps, the factor maps are optimized. While the calculation of the base and correction maps usually uses any (weighted) point grid (load, speed) at a fixed temperature (e.g., 85 ° warm engine, 40 ° cold engine), optimization of the factor maps will provide an already "continuous". Cycle measurement used (load, speed and temperature). As a result, the entire temperature range is covered and, in addition, an automatic weighting, with respect to operating ranges driven several times in the cycle, is carried out.
    In the following, a model-based cycle high calculation or simulation is usually performed. For this, again the global models are used, which were already used in the optimization. The applicator must assign the individual models to the corresponding areas of the test cycle. An example of such an assignment is shown in FIG.
    The input for the simulation is a cycle measurement, which, like the function optimization, contains the data for speed, load and temperature. These data serve as inputs to the functions that compute the temperature-dependent input values for the model parameters. Finally, the global models are evaluated to become a total ΛΑ-ΩΑ-9Μ9 5
    AV-3467 AT
    Cycle result brought together, as shown in Fig. 2. The applicator has the option here of manually setting or correcting the calculated maps of all radio zones and of directly monitoring the effects in the simulated cycle result. FIG. 3 shows a diagram for such a comparison.
    Finally, all calculated maps are written back to the engine control and verified on the test bench by means of a cycle measurement. 6
    权利要求:
    Claims (10)
    [1]
    Printed: 07-03-2012 E014.1 10 2012/50060 AV-3467 AT Claims: 1. A method for optimizing internal combustion engines, in particular for emission optimization and / or consumption optimization, in which, where appropriate, via correction functions in their control devices in each operating point at least one of the secondary factors is set such that the emission limit values are met in a defined cycle of operating points, characterized in that in a first step, an experimental plan for the main influencing variables and secondary factors using mathematical models of the control unit functions and the internal combustion engine with respect to the Size is generated and run on the test bench, based on these models determines the optimal values of the side-effects in compliance with the emission levels and these values are used for Erstbedatung the correction functions in the control unit.
    [2]
    2. The method according to claim 1, characterized in that dynamic models are evaluated under steady state conditions and used in the optimization.
    [3]
    3. The method according to claim 1 or 2, characterized in that the operating points are given by the parameters temperature, load and speed.
    [4]
    4. The method according to claim 3, characterized in that for the parameter temperature at least three different temperature levels are specified.
    [5]
    5. The method according to any one of claims 1 to 4, characterized in that the operating range of the internal combustion engine is divided into several areas, being created for each sub-area separate experimental plans and traced on the test bench and plausibility, and that from the measured data for each sub-part Models are created. 7 Printed: 07-03-2012 E014.1 10 2012/50060 AV-3467 AT
    [6]
    6. The method according to claim 5, characterized in that the experimental plans are created in each sub-area by two-stage global experimental design.
    [7]
    7. The method according to claim 5 or 6, characterized in that partial global models are created for each subarea,
    [8]
    8. The method according to any one of claims 1 to 4, characterized in that based on a dynamic test plan dynamic models for the size to be optimized over the entire operating range of the internal combustion engine are created.
    [9]
    9. The method according to any one of claims 1 to 8, characterized in that the correction functions consists of a basic map for a reference temperature of the internal combustion engine and at least one correction map for the internal combustion engine at a further reference temperature, which correction map by means of a factor map as a function of the current temperature Combustion engine is added to the output of the basic map.
    [10]
    10. The method according to any one of claims 1 to 9, characterized in that a model-based function optimization is performed for the maps, wherein the values are optimized on the nodes of the corresponding maps, nA_rv * _omi > 8th
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    引用文献:
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    法律状态:
    2020-11-15| MM01| Lapse because of not paying annual fees|Effective date: 20200306 |
    优先权:
    申请号 | 申请日 | 专利标题
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