Methods, apparatus, electronic devices, and readable storage media for calibrating control parameters

Abstract

This application relates to the field of vehicle calibration technology, and provides a method, apparatus, electronic device, and readable storage medium for calibrating control parameters. The method includes: acquiring a calibration strategy; establishing a simulation model of a real vehicle under calibration background conditions; determining several optional values ​​based on the parameter to be calibrated; for each optional value, assigning the optional value to the parameter to be calibrated and then conducting a simulation test on the simulation model to obtain the corresponding simulation test results; determining the optional values ​​corresponding to the simulation test results that meet the desired result characteristics as the values ​​to be measured; for each value to be measured, assigning the value to the parameter to be calibrated and then conducting a real vehicle test to obtain the corresponding real vehicle test results; determining the optimal test result from the real vehicle test results, and determining the value to be measured corresponding to the optimal test result as the target calibration value of the parameter to be calibrated. This application eliminates reliance on the subjective experience and ability of calibration personnel, achieving efficient and low-cost calibration.

Description

Technical Field

[0001] This application relates to the field of vehicle calibration technology, and in particular to a method, apparatus, electronic device and readable storage medium for calibrating control parameters. Background Technology

[0002] A vehicle's control system consists of two parts: control strategy and control parameters. The process of determining these control parameters so that the control strategy operates optimally according to them is called calibration. Currently, parameter calibration involves calibration personnel defining the calibration range of the calibration data based on their experience, then comparing the calibration effects of different calibration data through real-vehicle testing to finally obtain the calibration data.

[0003] Because real-vehicle testing is costly, requiring significant time, manpower, and vehicle resources, and posing safety hazards, the number of tests is limited, and the control parameters defined by calibration personnel are also limited. Under these limited control parameters, the ability of calibration personnel to accurately define the test data range determines whether optimal calibration data can be obtained. This places extremely high demands on calibration personnel and cannot guarantee complete reliability. If the optimal calibration data falls outside the calibration range subjectively defined by the calibration personnel, the optimal calibration data will not be provided in subsequent real-vehicle tests, resulting in suboptimal performance and ultimately impacting the user experience.

[0004] Therefore, how to provide a solution to the above-mentioned technical problems is a problem that needs to be solved by those skilled in the art. Summary of the Invention

[0005] In view of this, embodiments of this application provide a method, apparatus, electronic device, and readable storage medium for calibrating control parameters, in order to address the potential problem of incomplete calibration data caused by limitations in the capabilities of calibration personnel and the cost of testing in the prior art.

[0006] A first aspect of this application provides a method for calibrating control parameters, comprising:

[0007] Obtain the calibration strategy, which includes the calibration background conditions, the parameters to be calibrated, and the expected result characteristics of the parameters to be calibrated;

[0008] Based on the calibration background conditions, a simulation model corresponding to the real vehicle under the calibration background conditions is established;

[0009] Several optional values ​​are determined based on the parameters to be calibrated. For each optional value, the optional value is assigned to the parameters to be calibrated, and then a simulation experiment is performed on the simulation model to obtain the corresponding simulation experiment results.

[0010] The optional values ​​corresponding to the simulation test results that meet the expected results characteristics are determined as the values ​​to be measured.

[0011] For each value to be measured, the value is assigned to the parameter to be calibrated, and then a real vehicle test is conducted to obtain the corresponding real vehicle test results.

[0012] The optimal test result is determined from the actual vehicle test results, and the measured value corresponding to the optimal test result is determined as the target calibration value of the parameter to be calibrated.

[0013] A second aspect of this application provides a calibration device for control parameters, comprising:

[0014] The acquisition module is used to acquire the calibration strategy, which includes the calibration background conditions, the parameters to be calibrated, and the expected result characteristics of the parameters to be calibrated.

[0015] A model building module is used to build a simulation model of the actual vehicle under the calibration background conditions.

[0016] The numerical processing module is used to determine several optional values ​​based on the parameters to be calibrated.

[0017] The simulation test module is used to perform simulation tests on the simulation model for each optional value, assign the optional value to the parameter to be calibrated, and obtain the corresponding simulation test results.

[0018] The numerical processing module is also used to determine the optional values ​​corresponding to the simulation test results that meet the expected result characteristics as the values ​​to be measured.

[0019] The real vehicle test module is used to assign the measured value to the calibration parameter for each value to be measured and then conduct a real vehicle test on the real vehicle to obtain the corresponding real vehicle test results.

[0020] The numerical processing module is also used to determine the optimal test result from the actual vehicle test results, and to determine the measured value corresponding to the optimal test result as the target calibration value of the parameter to be calibrated.

[0021] A third aspect of this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described method.

[0022] A fourth aspect of this application provides a readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described method.

[0023] The beneficial effects of this application embodiment compared with the prior art include at least the following: This application embodiment reduces the test cost by establishing a simulation model and conducting simulation tests in the simulation model first. The selectable numerical range of the parameter to be calibrated is not limited by cost. It can efficiently and cost-effectively determine the measured value from a wide range of selectable numerical values ​​before conducting real vehicle tests to obtain a more accurate target calibration value. It no longer relies on the subjective experience and ability of calibration personnel, thus achieving efficient and low-cost calibration. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a schematic diagram illustrating one application scenario of this application.

[0026] Figure 2 This is a schematic flowchart of a control parameter calibration method provided in an embodiment of this application;

[0027] Figure 3 This is a schematic diagram of the structure of a control parameter calibration device provided in an embodiment of this application;

[0028] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0029] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0030] The following detailed description, in conjunction with the accompanying drawings, describes a method, apparatus, electronic device, and readable storage medium for calibrating control parameters according to embodiments of this application.

[0031] Figure 1 This is a schematic diagram illustrating an application scenario according to an embodiment of this application. The application scenario may include a physical vehicle 100, a first terminal device 101, a second terminal device 102, a third terminal device 103, a server 104, and a network 105.

[0032] The "Real Vehicle 100" can be a vehicle with actual operational capabilities. It is equipped with a vehicle control system that controls the operation process and collects various sensor values ​​during operation. The architecture of the vehicle control system varies depending on the type of vehicle. For example, the vehicle control system of a traditional gasoline-powered vehicle includes at least a powertrain electronic control system, a chassis electronic control system, and a body electronic control system. The powertrain electronic control system mainly includes engine electronic control (including gasoline and diesel engines), automatic transmission control, and integrated electronic control of the powertrain. The chassis electronic control system includes at least a brake slip and dynamic body control system, a traction control system, a suspension and vehicle height control system, a tire monitoring system, a cruise control system, a steering control system, and a drive control system. The body electronic control system mainly includes airbags, automatic seats, automatic air conditioning control, interior noise control, central locking, visibility lighting control, automatic wipers, automatic windows, an automatic collision avoidance system, and a power management system to meet the needs of various electrical devices. The vehicle control system of new energy vehicles can be broadly categorized into body comfort system, vehicle safety system, and new energy power system. Each system is further divided into several subsystems, which use their own electronic control units to perform their respective functions and objectives. These subsystems collaborate and optimize their matching to achieve the goals of overall vehicle performance, economy, safety, and comfort. The body comfort system includes a gateway, adaptive headlights, intelligent instrument system, domain controller, anti-pinch power window control module, power seat adjustment system, intelligent power distribution box, body control unit, engineering machinery controller, remote terminal equipment, car remote key, and door control module. The vehicle safety system includes advanced driver assistance systems, electronic stability systems, electric power steering systems, sensor fusion, anti-lock braking systems, steering wheel angle sensors, tire pressure monitoring systems, electronic suspension systems, autonomous parking systems, electronic parking brake systems, and electro-hydraulic steering control systems. The new energy power system includes electronic brake assist, range extender control system, battery management system, electric vehicle controller, electric vehicle charger, new energy power motor drive control system, electric vehicle integrated power control unit, brushless DC motor controller, electric vehicle remote monitoring and data service system, and electric water pump. In addition to the above description, other functional modules or systems may be installed on the actual vehicle. The specific configuration can be determined according to the actual working conditions or requirements, and no restrictions are imposed here.

[0033] The first terminal device 101 can be either hardware or software. When the first terminal device 101 is hardware, it can be various electronic devices with a display screen that support communication with the server 104, including but not limited to smartphones, tablets, laptops, and desktop computers. When the first terminal device 101 is software, it can be installed in the aforementioned electronic devices. The first terminal device 101 can be implemented as multiple software programs or software modules, or as a single software program or software module; this application embodiment does not impose any limitations on this. Furthermore, various applications can be installed on the first terminal device 101, such as data processing applications, instant messaging tools, social platform software, search applications, shopping applications, etc.

[0034] The second terminal device 102 can be hardware or software. When the second terminal device 102 is hardware, it can be various electronic devices with a display screen that support communication with the server 104, including but not limited to smartphones, tablets, laptops, and desktop computers; when the second terminal device 102 is software, it can be installed in the aforementioned electronic devices. The second terminal device 102 can be implemented as multiple software programs or software modules, or as a single software program or software module; this application embodiment does not impose any limitations on this. Furthermore, various applications can be installed on the second terminal device 102, such as data processing applications, instant messaging tools, social platform software, search applications, shopping applications, etc.

[0035] The third terminal device 103 can be either hardware or software. When the third terminal device 103 is hardware, it can be various electronic devices with a display screen that support communication with the server 104, including but not limited to smartphones, tablets, laptops, and desktop computers. When the third terminal device 103 is software, it can be installed in the aforementioned electronic devices. The third terminal device 103 can be implemented as multiple software programs or software modules, or as a single software program or software module; this application embodiment does not impose any limitations on this. Furthermore, various applications can be installed on the third terminal device 103, such as data processing applications, instant messaging tools, social platform software, search applications, shopping applications, etc.

[0036] Server 104 can be a server that provides various services, such as a backend server that receives requests sent by terminal devices with which it has established communication connections. This backend server can receive and analyze the requests sent by the terminal devices and generate processing results. Server 104 can be a single server, a server cluster consisting of several servers, or a cloud computing service center. This application embodiment does not limit this.

[0037] It should be noted that the server 104 can be either hardware or software. When the server 104 is hardware, it can be various electronic devices that provide various services to the first terminal device 101, the second terminal device 102, and the third terminal device 103. When the server 104 is software, it can be multiple software programs or software modules that provide various services to the first terminal device 101, the second terminal device 102, and the third terminal device 103, or it can be a single software program or software module that provides various services to the first terminal device 101, the second terminal device 102, and the third terminal device 103. This application embodiment does not impose any limitations on this.

[0038] Network 105 can be a wired network using coaxial cable, twisted pair, and fiber optic connection, or it can be a wireless network that enables interconnection of various communication devices without wiring, such as Bluetooth, Near Field Communication (NFC), and Infrared. This application embodiment does not limit this.

[0039] It should be noted that the specific types, quantities and combinations of the first terminal device 101, the second terminal device 102, the third terminal device 103, the server 104 and the network 105 can be adjusted according to the actual needs of the application scenario, and this application embodiment does not impose any restrictions on this.

[0040] It should be noted that the specific types, quantities and combinations of the first terminal device 101, the second terminal device 102, the third terminal device 103, the server 104 and the network 105 can be adjusted according to the actual needs of the application scenario, and this application embodiment does not impose any restrictions on this.

[0041] Figure 2 This is a schematic flowchart illustrating a control parameter calibration method provided in an embodiment of this application. Figure 2 As shown, the calibration method includes:

[0042] S201: Obtain the calibration strategy, which includes the calibration background conditions, the parameters to be calibrated, and the expected result characteristics of the parameters to be calibrated;

[0043] S202: Based on the calibration background conditions, establish a simulation model of the actual vehicle under the calibration background conditions;

[0044] S203: Determine several selectable values ​​based on the parameters to be calibrated;

[0045] S204: For each optional value, assign the optional value to the parameter to be calibrated and then conduct a simulation test on the simulation model to obtain the corresponding simulation test results;

[0046] S205: The optional values ​​corresponding to the simulation test results that meet the characteristics of the expected results are determined as the values ​​to be measured.

[0047] S206: For each value to be measured, after assigning the value to the parameter to be calibrated, conduct a real vehicle test on the actual vehicle to obtain the corresponding real vehicle test results;

[0048] S207: Determine the optimal test result from the actual vehicle test results, and determine the measured value corresponding to the optimal test result as the target calibration value of the parameter to be calibrated.

[0049] Figure 2 The calibration method can be derived from Figure 1 The first terminal device, second terminal device, third terminal device, or server executes the steps, and the actual vehicle involved in steps S202 and S206 is... Figure 1 The actual vehicle.

[0050] The calibration strategy targets any system or functional module on the actual vehicle and can be formulated based on the vehicle's design requirements, reference to the performance of other vehicles, or actual conditions. In some specific embodiments, when the calibration background condition is that the vehicle accelerates to the target speed and receives a chassis torque reduction request, and the expected result is that the torque curve does not change abruptly during the torque reduction process, the parameters to be calibrated include torque filtering parameters. For example, a calibration background condition is that the vehicle accelerates to 80 km / h and receives a chassis torque reduction request. At this time, the target speed is 80 km / h, the parameter to be calibrated is the torque filtering parameter, and the expected result of the parameter to be calibrated is that the torque decreases smoothly during the torque reduction process. The entire calibration strategy aims to determine a value of the torque filtering parameter as the target calibration value. When the vehicle accelerates to 80 km / h and receives a chassis torque reduction request, the response to the chassis torque reduction request is based on the target calibration value. During the response process, i.e., during the torque reduction process, the torque exhibits a smooth downward trend.

[0051] The purpose of step S202 is to establish a simulation model that is completely consistent with the actual vehicle's response under the calibration background conditions. Therefore, the process of establishing a simulation model corresponding to the actual vehicle under the calibration background conditions includes: establishing a simulation model corresponding to the actual vehicle based on the calibration background conditions; obtaining the background parameters of the actual vehicle under the calibration background conditions; and adjusting the simulation model corresponding to the actual vehicle until the background parameters of the simulation model are consistent with the background parameters of the actual vehicle. The process of establishing the simulation model corresponding to the actual vehicle includes: building a simulation test environment using MATLAB software and dynamics simulation software, and establishing the simulation model corresponding to the actual vehicle within the simulation test environment. Here, the dynamics simulation software includes CARSIM or DYNA4, etc. After establishing the simulation model in the simulation test environment, the simulation model is further adjusted until the background parameters of the simulation model are completely consistent with the background parameters of the actual vehicle. For example, the background parameters of the actual vehicle include vehicle speed and requested torque. When the actual vehicle speed is 80 km / h, the requested torque is 100 N·m. Therefore, the simulation model is required to have the same requested torque of 100 N·m when the vehicle speed is 80 km / h. Furthermore, to ensure that the simulation model matches the background parameters of the real vehicle, the adjustments made to the simulation model here include adjustments to various vehicle parameters in the simulation model, such as vehicle weight, drag coefficient, motor, and battery performance parameters. Specific adjustments can be made according to actual working conditions and requirements, and there are no restrictions here.

[0052] Step S203 determines several optional values ​​based on the parameter to be calibrated, including: obtaining the target value range and precision of the parameter to be calibrated; and calculating several optional values ​​based on the target value range and precision. The target value range is determined based on the objectively achievable range of the actual vehicle or the simulation achievable range of the simulation model based on the simulation conditions in the simulation test environment. The precision is determined similarly. For example, if the torque filter parameter is used as the parameter to be calibrated, its target value range is 1-10000, and its precision is 1. Then, the multiple optional values ​​obtained include 1, 2, 3, ..., 9999, 10000. Based on 10000 optional values, repeated simulation tests are performed on each optional value. Each simulation test, as described in step 204, sets the parameter to be calibrated in the simulation model to an optional value, and then performs a simulation test on the simulation model with the corresponding calibration strategy to obtain the simulation test result for that optional value. Further optional values ​​should include the endpoints of the target value range. When determining each optional value by accumulating precision starting from the minimum endpoint, there may be cases where the maximum endpoint value is not an optional value. For example, if the target value range is 1-99.5, and the precision is 1, the conventionally determined multiple optional values ​​include 1, 2, 3, ..., 99, excluding the maximum endpoint value of 99.5. In this case, the maximum endpoint value needs to be additionally set as an optional value and corresponding simulation experiments need to be conducted. It is understood that the target value range here is not necessarily a continuous and complete value interval. The target value range may include multiple value intervals and may also include discrete value points so that the value points corresponding to special values ​​can also be used as optional values ​​for simulation experiments. The specific target value range can be selected according to the actual working conditions, and will not be elaborated here.

[0053] In addition to the optional values ​​for calibration parameters, some special parameter values ​​can be set for simulation experiments. By comparing the simulation results with actual conditions, the accuracy of the simulation model can be verified simultaneously. For example, a parameter of 4 may theoretically lead to data overflow and a large abrupt change in the torque curve. If the torque curve of the simulation experiment with this parameter of 4 shows a large abrupt change, then the accuracy of the simulation model can be confirmed to meet the requirements.

[0054] Step S204 involves assigning each selectable value to the parameter to be calibrated and then conducting a simulation experiment on the simulation model. If there are multiple parameters to be calibrated, repeated combined full-scale simulations can be performed to obtain a set of simulation results corresponding to each combined full-scale simulation.

[0055] It is understandable that simulation results can be used to adjust the accuracy of the parameters to be calibrated. If the accuracy of the parameters to be calibrated is too high, the simulation results based on the selectable values ​​obtained from the high accuracy will deviate too much from the expected results, failing to yield the optimal parameters. If the accuracy is too low, the number of selectable values ​​will be too large, resulting in wasted simulation resources and low processing efficiency. Furthermore, adjusting the schedule based on the simulation results involves assigning selectable values ​​to the parameters to be calibrated, conducting simulation tests on the simulation model, and obtaining the corresponding simulation results, which also includes:

[0056] Based on the expected result characteristics and simulation test results, the target simulation result is obtained, where the target simulation result is the simulation test result that is closest to the expected result characteristics;

[0057] Obtain the absolute value of the difference between the expected result feature and the target simulation test result. If the absolute value of the difference is greater than the preset difference threshold, obtain the difference between the absolute value of the difference and the preset difference threshold, adjust the precision according to the difference, and then execute the step of calculating several selectable values ​​according to the target value range and precision.

[0058] In some specific embodiments, under calibration background conditions, the expected result characteristics of the parameter to be calibrated change with the parameter to be calibrated.

[0059] After obtaining the simulation test results of all possible values, the possible values ​​that meet the characteristics of the expected results are determined as the values ​​to be measured. Further, real vehicle tests are conducted on real vehicles to obtain the real vehicle test results for each value to be measured. Finally, the real vehicle test result with the most ideal effect is selected from all the real vehicle test results as the optimal test result, and its corresponding value to be measured is used as the target calibration value.

[0060] It is understandable that simulation tests and real-vehicle tests involve simulation models and real vehicles, respectively. The simulation model simulates the real vehicle, and simulation tests can, to a certain extent, represent the test results of real-vehicle tests. The results of simulation tests and real-vehicle tests should correspond to the same format, the same numerical representation method, and the same expected result characteristics. Typically, both simulation test results and real-vehicle test results include a set of test result values, and the expected result characteristics are the numerical variation characteristics of the test result values. Furthermore, these numerical variation characteristics can be features specific to each set of test result values, including one or more of the mean, median, rate of change, and variance of each set of test result values. These numerical variation characteristics can also be features of the image obtained after visualizing each set of test result values. For example, both simulation test results and real-vehicle test results include a set of test result values ​​that can be fitted into a curve, and the expected result characteristics are the image data characteristics of the curve. Taking the calibration process of torque filtering parameters as an example, the expected result is that the torque decreases smoothly during the torque reduction process. The image data characteristics converted into curves should be the smoothness or smoothness of the curve obtained from the experimental results. If the curve has no obvious spikes and no obvious abrupt changes in values, it can be regarded as relatively smooth torque. Specifically, it can be described by the specific characteristic parameters of the curve.

[0061] Since simulation tests only run in the program space and do not affect the actual vehicle, there are no safety hazards associated with the actual vehicle. Furthermore, simulation tests are less time-consuming and can be performed on a large number of optional values. This allows for efficient and low-cost initial screening of a wider range of optional values, reducing vehicle usage frequency, operating costs, and the probability of safety issues. For example, with 1000 optional values ​​mentioned above, 10,000 simulation test results are obtained by performing simulation tests on each optional value. Optional values ​​that meet the desired result characteristics are then selected. For instance, the torque filtering parameters that meet the desired result are selected as the following four optional values: 498 / 501 / 512 / 513. These four optional values ​​are then assigned to the values ​​to be calibrated and tested on the actual vehicle, resulting in four sets of actual vehicle test results. The optimal test result is then selected. Based on the desired result characteristics set in this example, the optimal test result should be the set of actual vehicle test results with the smoothest torque decrease curve. For example, among the four sets of real vehicle test results, the real vehicle test results with a filter parameter value of 512 showed the best performance. Therefore, the target calibration value is determined to be 512. That is, among the selectable values ​​of 1-10000, when the parameter to be calibrated is 512, the calibration background condition is that the vehicle accelerates to 80km / h and receives a chassis torque reduction request. Responding to the chassis torque reduction request can yield a more ideal expected result: the torque reduction process is smooth.

[0062] This application embodiment reduces testing costs by establishing a simulation model and conducting simulation experiments within the model. The range of selectable values ​​for the parameters to be calibrated is not limited by cost, enabling efficient and low-cost preliminary determination of the values ​​to be measured from a wide range of selectable values. Then, real vehicle testing is conducted to obtain more accurate target calibration values. This eliminates reliance on the subjective experience and ability of calibration personnel, achieving efficient and low-cost calibration.

[0063] All the above-mentioned optional technical solutions can be combined in any way to form the optional embodiments of this application, and will not be described in detail here. It should be understood that the sequence number of each step in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0064] The following are embodiments of the apparatus described in this application, which can be used to execute the embodiments of the method described in this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method described in this application.

[0065] Figure 3 This is a schematic diagram of a control parameter calibration device provided in an embodiment of this application. Figure 3 As shown, the calibration device includes:

[0066] The acquisition module 301 is used to acquire the calibration strategy, which includes the calibration background conditions, the parameters to be calibrated, and the expected result characteristics of the parameters to be calibrated.

[0067] Model module 302 is used to establish a simulation model of the actual vehicle under the calibration background conditions based on the calibration background conditions.

[0068] The numerical processing module 303 is used to determine several selectable values ​​based on the parameters to be calibrated;

[0069] The simulation test module 304 is used to perform simulation tests on the simulation model after assigning the optional values ​​to the parameters to be calibrated for each optional value, and to obtain the corresponding simulation test results.

[0070] The numerical processing module 305 is also used to determine the optional numerical values ​​corresponding to the simulation test results that meet the characteristics of the expected results as the values ​​to be measured.

[0071] The real vehicle test module 306 is used to assign the measured value to the calibration parameter for each value to be measured and then conduct a real vehicle test on the real vehicle to obtain the corresponding real vehicle test results.

[0072] The numerical processing module 307 is also used to determine the optimal test result from the actual vehicle test results, and to determine the measured value corresponding to the optimal test result as the target calibration value of the parameter to be calibrated.

[0073] This application embodiment reduces testing costs by establishing a simulation model and conducting simulation experiments within the model. The range of selectable values ​​for the parameters to be calibrated is not limited by cost, enabling efficient and low-cost preliminary determination of the values ​​to be measured from a wide range of selectable values. Then, real vehicle testing is conducted to obtain more accurate target calibration values. This eliminates reliance on the subjective experience and ability of calibration personnel, achieving efficient and low-cost calibration.

[0074] In some specific embodiments, the numerical processing module 303 is specifically used for:

[0075] Obtain the target value range and accuracy of the parameter to be calibrated;

[0076] Several selectable values ​​are calculated based on the target value range and precision.

[0077] In some specific embodiments, the numerical processing module 303 is also used for:

[0078] Based on the expected result characteristics and simulation test results, the target simulation result is obtained, where the target simulation result is the simulation test result that is closest to the expected result characteristics;

[0079] Obtain the absolute value of the difference between the expected result feature and the target simulation test result. If the absolute value of the difference is greater than the preset difference threshold, obtain the difference between the absolute value of the difference and the preset difference threshold, adjust the precision according to the difference, and then execute the step of calculating several selectable values ​​according to the target value range and precision.

[0080] In some specific embodiments, under calibration background conditions, the expected result characteristics of the parameter to be calibrated change with the parameter to be calibrated.

[0081] In some specific embodiments, when the calibration background condition is that the chassis torque reduction request is received when the vehicle accelerates to the target speed, and the expected result is that the torque curve does not change abruptly during the torque reduction process, the parameters to be calibrated include torque filtering parameters.

[0082] In some specific embodiments, both the simulation test results and the real vehicle test results include a set of test result values, and the expected result characteristics are the numerical variation characteristics of the test result values.

[0083] In some specific embodiments, the process of establishing a simulation model of the actual vehicle under the calibration background conditions includes:

[0084] Based on the calibrated background conditions, a simulation model corresponding to the real vehicle is established.

[0085] Obtain the background parameters of the actual vehicle under the calibration background conditions;

[0086] Adjust the simulation model corresponding to the real vehicle until the background parameters of the simulation model are consistent with the background parameters of the real vehicle.

[0087] Figure 4 This is a schematic diagram of the electronic device 4 provided in an embodiment of this application. Figure 4 As shown, the electronic device 4 of this embodiment includes: a processor 401, a memory 402, and a computer program 403 stored in the memory 402 and executable on the processor 401. When the processor 401 executes the computer program 403, it implements the steps in the various method embodiments described above. Alternatively, when the processor 401 executes the computer program 403, it implements the functions of each module / unit in the various device embodiments described above.

[0088] Electronic device 4 can be a desktop computer, laptop, handheld computer, cloud server, or other electronic device. Electronic device 4 may include, but is not limited to, processor 401 and memory 402. Those skilled in the art will understand that... Figure 4 This is merely an example of electronic device 4 and does not constitute a limitation on electronic device 4. It may include more or fewer components than shown, or different components.

[0089] The processor 401 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0090] The memory 402 can be an internal storage unit of the electronic device 4, such as a hard disk or RAM of the electronic device 4. The memory 402 can also be an external storage device of the electronic device 4, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, Flash Card, etc., equipped on the electronic device 4. The memory 402 can also include both internal and external storage units of the electronic device 4. The memory 402 is used to store computer programs and other programs and data required by the electronic device.

[0091] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0092] If an integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program may include computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. A readable storage medium may include: any entity or device capable of carrying computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in a readable storage medium can be appropriately added to or subtracted according to the requirements of legislation and patent practice in a jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, a readable storage medium may not include electrical carrier signals and telecommunication signals.

[0093] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for calibrating control parameters, characterized in that, include: Obtain a calibration strategy, which includes calibration background conditions, parameters to be calibrated, and expected result characteristics of the parameters to be calibrated; Based on the calibration background conditions, a simulation model corresponding to the real vehicle under the calibration background conditions is established. Based on the parameter to be calibrated, several optional values ​​are determined. For each optional value, the optional value is assigned to the parameter to be calibrated, and then a simulation experiment is performed on the simulation model to obtain the corresponding simulation experiment results. The optional values ​​corresponding to the simulation test results that meet the expected result characteristics are determined as the values ​​to be measured. For each of the measured values, the measured value is assigned to the calibration parameter, and then a real vehicle test is performed on the real vehicle to obtain the corresponding real vehicle test results. The optimal test result is determined from the actual vehicle test results, and the measured value corresponding to the optimal test result is determined as the target calibration value of the parameter to be calibrated. The step of determining several selectable values ​​based on the parameter to be calibrated includes: Obtain the target value range and the accuracy of the parameter to be calibrated; the target value range includes several value intervals and / or discrete numerical points selected according to the calibration background conditions; Several selectable values ​​are calculated based on the target value range and the precision. After assigning the optional numerical values ​​to the parameters to be calibrated and performing simulation experiments on the simulation model to obtain the corresponding simulation results, the process further includes: Based on the expected result characteristics and the simulation test results, a target simulation result is obtained, wherein the target simulation result is the simulation test result that is closest to the expected result characteristics; Obtain the absolute value of the difference between the expected result feature and the target simulation test result. If the absolute value of the difference is greater than a preset difference threshold, obtain the difference between the absolute value of the difference and the preset difference threshold, adjust the precision according to the difference, and then execute the step of calculating several selectable values ​​based on the target value range and the precision.

2. The method according to claim 1, characterized in that, Under the calibration background conditions, the expected result characteristics of the parameter to be calibrated change with the parameter to be calibrated.

3. The method according to claim 2, characterized in that, When the calibration background condition is that the chassis torque reduction request is received when the vehicle accelerates to the target speed, and the expected result is that the torque curve does not change abruptly during the torque reduction process, the parameters to be calibrated include torque filtering parameters.

4. The method according to claim 1, characterized in that, Both the simulation test results and the actual vehicle test results include a set of test result values, and the expected result characteristics are the numerical variation characteristics of the test result values.

5. The method according to any one of claims 1 to 4, characterized in that, The process of establishing a simulation model of the actual vehicle under the calibration background conditions includes: Based on the calibration background conditions, a simulation model corresponding to the actual vehicle is established. Obtain the background parameters of the actual vehicle under the specified calibration background conditions; Adjust the simulation model corresponding to the actual vehicle until the background parameters of the simulation model are consistent with the background parameters of the actual vehicle.

6. A calibration device for control parameters, characterized in that, include: The acquisition module is used to acquire the calibration strategy, which includes the calibration background conditions, the parameter to be calibrated, and the expected result characteristics of the parameter to be calibrated. A model building module is used to build a simulation model of the actual vehicle under the calibration background conditions based on the calibration background conditions. The numerical processing module is used to determine several selectable values ​​based on the parameters to be calibrated; This includes: obtaining the target value range and the precision of the parameter to be calibrated; the target value range includes several value intervals and / or discrete numerical points selected according to the calibration background working conditions; and calculating several selectable values ​​based on the target value range and the precision. The simulation test module is used to assign the optional value to the parameter to be calibrated for each of the optional values ​​and then conduct a simulation test on the simulation model to obtain the corresponding simulation test results. The numerical processing module is further configured to determine the optional numerical values ​​corresponding to the simulation test results that conform to the expected result characteristics as the measured values; The real vehicle test module is used to assign the measured value to the calibration parameter for each measured value and then conduct a real vehicle test on the real vehicle to obtain the corresponding real vehicle test results. The numerical processing module is also used to determine the optimal test result from the actual vehicle test results, and to determine the measured value corresponding to the optimal test result as the target calibration value of the parameter to be calibrated; The numerical processing module is further configured to: after assigning the optional numerical values ​​to the parameters to be calibrated, perform a simulation experiment on the simulation model to obtain the corresponding simulation experiment results, and then obtain a target simulation result based on the expected result characteristics and the simulation experiment results, wherein the target simulation result is the simulation experiment result that is closest to the expected result characteristics; obtain the absolute value of the difference between the expected result characteristics and the target simulation experiment result; if the absolute value of the difference is greater than a preset difference threshold, obtain the difference between the absolute value of the difference and the preset difference threshold, adjust the precision based on the difference, and then execute the step of calculating several optional numerical values ​​based on the target value range and the precision.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 5.

8. A readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 5.

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