CN115221611B - Whole vehicle matching parameter optimization method and device, medium and electronic equipment - Google Patents

Abstract

The invention relates to the field of vehicle development, and discloses a method, a device, a medium and electronic equipment for optimizing matching parameters of a whole vehicle. The method comprises the following steps: respectively establishing a whole vehicle dynamics model, a basic test working condition model and a plurality of system related models of a vehicle, and carrying out parameter configuration on the whole vehicle dynamics model and each system related model; respectively executing a matching parameter optimization step aiming at each test working condition; determining an optimal index of the whole vehicle performance according to the test result and the whole vehicle performance target corresponding to each test working condition model; and if the vehicle performance index values of the vehicle under all the test working conditions meet the vehicle performance optimal index, the optimization of the adjustable matching parameters is completed. The method not only improves the efficiency and accuracy of the parameter optimization process, but also improves the robustness of the control system, and can realize the performance optimization of the whole vehicle level.

Description

Matching parameter optimization methods, devices, media and electronic equipment for the entire vehicle

Technical field

The present disclosure relates to the technical field of vehicle development, and in particular to a matching parameter optimization method, device, medium and electronic equipment for a complete vehicle.

Background technique

In vehicle development, each system matches actual vehicle parameters based on its own development indicators. For the interaction between various systems, relatively simple interaction instructions are formulated to meet the correct response to interactive signals such as torque, speed, gear, etc. However, there is a lack of comprehensive The vehicle-level matching parameter boundary concept, interaction requirement formulation and parameter matching lack the consideration of vehicle performance optimization, and lack of vehicle simulation results to guide parameter optimization. The parameter matching process is relatively inefficient and independent.

Contents of the invention

In the field of vehicle development technology, in order to solve the above technical problems, the purpose of this disclosure is to provide a matching parameter optimization method, device, medium and electronic equipment for a complete vehicle.

According to one aspect of the present disclosure, a matching parameter optimization method for a complete vehicle is provided. The method includes:

Establish a vehicle dynamics model, a basic test condition model and multiple system-related models respectively, and configure parameters for the vehicle dynamics model and each of the system-related models. The parameters include adjustable matching parameters. ;

The matching parameter optimization steps are performed separately for each test condition. The matching parameter optimization steps include:

Configure test working condition parameters for the basic test working condition model to obtain a test working condition model;

Obtain the vehicle performance target set for the test working condition model, where the vehicle performance target corresponds to multiple performance indicators;

Repeat the simulation steps, parameter adjustment steps and actual vehicle test steps until the test results meet the vehicle performance goals corresponding to the test working condition model, and end the matching parameter optimization step. The simulation steps include: based on the entire vehicle performance The vehicle dynamics model, the test condition model and the system-related model are simulated to obtain simulation results; the parameter adjustment step includes: adjusting the adjustable matching parameters according to the simulation results and the vehicle performance target. ; The actual vehicle testing step includes: performing an actual vehicle test based on the adjusted adjustable matching parameters, obtaining test results, and adjusting the adjustable matching parameters again based on the data analysis results of the test results;

Determine the optimal vehicle performance index according to the test results corresponding to each test working condition model and the vehicle performance target;

If the vehicle performance index values of the vehicle under each test condition all meet the optimal vehicle performance index, the optimization of the adjustable matching parameters is completed.

According to another aspect of the present disclosure, a matching parameter optimization device for a complete vehicle is provided, and the device includes:

The model building module is configured to respectively establish a vehicle dynamics model, a basic test condition model and multiple system-related models of the vehicle, and configure parameters for the vehicle dynamics model and each of the system-related models, so The above parameters include adjustable matching parameters;

The parameter optimization module is configured to perform a matching parameter optimization step for each test condition. The matching parameter optimization step includes: configuring test condition parameters for the basic test condition model to obtain a test condition model; obtaining a test condition model for each test condition. The vehicle performance target set by the test working condition model is set, and the vehicle performance target corresponds to multiple performance indicators; the simulation steps, parameter adjustment steps and real vehicle testing steps are repeatedly performed until the test results meet the test working conditions. The vehicle performance target corresponding to the model, and ends the matching parameter optimization step. The simulation step includes: performing simulation based on the vehicle dynamics model, the test condition model and the system-related model, and obtaining simulation results. ; The parameter adjustment step includes: adjusting the adjustable matching parameters according to the simulation results and the vehicle performance target; the actual vehicle testing step includes: performing an actual vehicle test based on the adjusted adjustable matching parameters, and obtains test results, and adjust the adjustable matching parameters again according to the data analysis results of the test results;

An index determination module configured to determine the optimal vehicle performance index based on the test results corresponding to each test working condition model and the vehicle performance target;

The judgment module is configured to complete the optimization of the adjustable matching parameters if the vehicle performance index values of the vehicle under each test condition meet the optimal vehicle performance index.

According to another aspect of the present disclosure, a computer-readable program medium is provided, which stores computer program instructions. When the computer program instructions are executed by a computer, they cause the computer to perform the method as described above.

According to another aspect of the present disclosure, an electronic device is provided, the electronic device including:

processor;

A memory has computer-readable instructions stored in the memory. When the computer-readable instructions are executed by the processor, the method as described above is implemented.

The technical solutions provided by the embodiments of the present disclosure may include the following beneficial effects:

For the matching parameter optimization method, device, medium and electronic equipment of the vehicle provided by the present disclosure, the method includes the following steps: establishing a vehicle dynamics model, a basic test condition model and multiple system-related models of the vehicle, and Parameter configuration is performed on the vehicle dynamics model and each of the system-related models, and the parameters include adjustable matching parameters; a matching parameter optimization step is performed for each test condition, and the matching parameter optimization step includes: Configure the test condition parameters in the basic test condition model to obtain the test condition model; obtain the vehicle performance target set for the test condition model, and the vehicle performance target corresponds to multiple performance indicators; repeat the execution The simulation step, the parameter adjustment step and the actual vehicle test step are carried out until the test results meet the vehicle performance target corresponding to the test working condition model, and the matching parameter optimization step is ended. The simulation step includes: based on the vehicle power The learning model, the test working condition model and the system-related model are simulated to obtain simulation results; the parameter adjustment step includes: adjusting the adjustable matching parameters according to the simulation results and the vehicle performance target; The real vehicle testing steps include: performing a real vehicle test based on the adjusted adjustable matching parameters, obtaining test results, and adjusting the adjustable matching parameters again based on the data analysis results of the test results; according to each test working condition model Corresponding to the test results and the vehicle performance target, determine the optimal vehicle performance index; if the vehicle performance index values of the vehicle under each test condition meet the vehicle performance optimal index, then Complete the optimization of the adjustable matching parameters.

Under this method, by setting the optimal vehicle performance index and performing matching parameter optimization steps under different working conditions, the vehicle's adjustable matching parameters are optimized from the perspective of optimal vehicle performance, and during optimization During the process, the adjustable matching parameters are adjusted based on the simulation results, that is, the simulation results are used to guide parameter boundary positioning and parameter optimization, and are combined with actual vehicle testing, which not only improves the efficiency and accuracy of the parameter optimization process, but also improves This improves the robustness of the control system and enables performance optimization at the vehicle level.

It should be understood that the above general description and the following detailed description are only exemplary and do not limit the present invention.

Description of the drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description serve to explain the principles of the invention.

Figure 1 is a flow chart of a matching parameter optimization method for a complete vehicle according to an exemplary embodiment;

Figure 2 is a flowchart of matching parameter optimization steps according to an exemplary embodiment;

Figure 3 is a specific flow diagram of a matching parameter optimization method for a complete vehicle according to an exemplary embodiment;

Figure 4 is a block diagram of a vehicle matching parameter optimization device according to an exemplary embodiment;

Figure 5 is an example block diagram of an electronic device that implements the above matching parameter optimization method for a complete vehicle according to an exemplary embodiment;

Figure 6 is a program product that implements the above matching parameter optimization method for a complete vehicle according to an exemplary embodiment.

Detailed ways

Exemplary embodiments will be described in detail herein, examples of which are illustrated in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the invention. Rather, they are merely examples of apparatus and methods consistent with aspects of the invention as detailed in the appended claims.

Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings represent the same or similar parts, and thus their repeated description will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities.

In related technologies, when developing a complete vehicle, it is necessary to separately match the vehicle's braking system, engine control system, gearbox control system, etc., and conduct offline analysis of some parameters based on a large number of real vehicle calibration tests and combined with partial control models. Calibration completes the matching of parameters of each system, formulates interaction requirements to meet the normal response of signals, and formulates a series of test conditions for each system to verify parameters. The acceptance criteria focus on optimizing the performance of each system itself. Parameter matching here is the process of finding optimal parameters.

However, the shortcomings of this related technology are: on the one hand, the parameter matching process of each system is relatively independent, which makes it difficult to optimize the vehicle performance under certain working conditions; on the other hand, the parameter matching results lack simulation performance at the vehicle level, and the matching process Relying on a large number of actual tests, the matching process is relatively inefficient.

To this end, this disclosure first provides a matching parameter optimization method for the entire vehicle. The above shortcomings can be overcome through this vehicle matching parameter optimization method, which not only makes the parameter optimization process more efficient, but also enables performance optimization at the vehicle level.

The implementation terminal of the present disclosure can be any device with computing, processing and communication functions. The device can be connected to an external device for receiving or sending data. Specifically, it can be a portable mobile device, such as a smart phone, a tablet computer, a notebook computer, PDA (Personal Digital Assistant), etc., can also be fixed equipment, such as computer equipment, field terminals, desktop computers, servers, workstations, etc., or can be a collection of multiple devices, such as the physical infrastructure of cloud computing or a server cluster. .

Optionally, the implementation terminal of the present disclosure may be a desktop computer or a server.

Figure 1 is a flow chart of a vehicle matching parameter optimization method according to an exemplary embodiment. The vehicle matching parameter optimization method can be executed by various devices with computing and processing functions such as personal computers and servers. As shown in Figure 1, it includes the following steps:

Step 110: Establish a vehicle dynamics model, a basic test condition model and multiple system-related models of the vehicle, and configure parameters for the vehicle dynamics model and each system-related model.

Parameters include adjustable matching parameters.

In one embodiment of the present disclosure, the plurality of system-related models include an engine torque model, a transmission dynamics model, a transmission shift control logic model, and a brake system control model.

Engine torque model, transmission dynamics model, transmission shift control logic model, braking system control model, vehicle dynamics model and basic test condition model can all be established by using Simulink.

Specifically, the engine torque model, transmission dynamics model, transmission shift control logic model, braking system control model and vehicle dynamics model may include system hardware parameters and/or control parameters, and the control parameters may be in the electronic control unit of the vehicle. Configure in . The system hardware parameters in the engine torque model may include: engine displacement and number of cylinders, and engine inertia; the control parameters in the engine torque model may include: engine speed, accelerator pedal opening, expected torque based on accelerator pedal opening, charge Quantity coefficient map, throttle flow characteristics, charging delay map based on actual measurement, target air-fuel ratio, target ignition angle, engine ignition efficiency map, engine thermodynamic efficiency map, engine accessory working status and torque loss map, reserve Torque, engine fuel-cut speed and fuel-cut exit control delay, engine speed PID control gain value, torque demand from the transmission control unit and ESP; the system hardware parameters in the transmission dynamics model can include: the number of transmission gears and their speeds ratio, the torque converter K coefficient and torque ratio characteristic map of the AT transmission, the lock-up clutch size and friction coefficient, the clutch size and friction coefficient of the DCT transmission; the control parameters in the transmission dynamics model can include: hydraulic Torque converter turbine speed, torque converter lock-up clutch control pressure; control parameters in the transmission shift control logic model can include: clutch control pressure of the DCT transmission, based on vehicle speed, accelerator pedal opening and engine speed change rate, etc. The parameter shift line, the torque demand of the transmission control unit to the engine control unit; the system hardware parameters in the vehicle dynamics model can include: vehicle test mass, wheelbase and center of mass height, tire size, transmission output shaft to wheel Equivalent moment of inertia, main reducer speed ratio, adhesion coefficient between the test road surface and the wheel; system hardware parameters in the brake system control model can include: brake fluid pipes that affect the transient characteristics of the brake master cylinder pressure and wheel cylinder pressure Road size and layout; the control parameters in the brake system control model can include: brake master cylinder pressure, target wheel slip rate, slip rate PID control parameters, and the torque demand of the brake control unit to the engine control unit.

The above system hardware parameters and control parameters can be configured according to the actual vehicle model.

The adjustable matching parameters may include at least one system hardware parameter and at least one control parameter mentioned above. Each of the above models may include adjustable matching parameters. For example, the adjustable matching parameters in the engine torque model can include: target air-fuel ratio, target ignition angle, engine accessory control status, reserve torque, fuel cut exit control delay, engine speed PID control gain value; in the transmission dynamics model Adjustable matching parameters may include: lock-up clutch control pressure; adjustable matching parameters in the transmission shift control logic model may include: clutch control pressure of the DCT transmission, vehicle speed, engine speed change rate threshold in the shift logic, etc., transmission The torque demand of the control unit for the engine control unit; the adjustable matching parameters in the vehicle dynamics model can include: tire size and the adhesion coefficient between the test road surface and the wheel. The adhesion coefficient between the test road surface and the wheel can be selected through the tire pattern. to change; the adjustable matching parameters in the brake system control model can include: brake fluid pipeline size and layout, wheel target slip rate, slip rate PID control parameters, and the torque demand of the brake control unit on the engine control unit .

Step 120: Perform matching parameter optimization steps for each test condition.

For each test condition, corresponding matching parameter optimization steps need to be performed.

Figure 2 is a flowchart illustrating matching parameter optimization steps according to an exemplary embodiment. As shown in Figure 2, the matching parameter optimization steps may include the following steps:

Step 210: configure the test condition parameters for the basic test condition model to obtain the test condition model.

The basic test condition model is a model that has not been configured with test condition parameters; for each test condition, corresponding test condition parameters need to be configured. Therefore, different test conditions are achieved by adjusting the test condition parameters. The test working condition parameters may specifically include throttle signal and brake signal.

Step 220: Obtain the vehicle performance target set for the test working condition model.

The vehicle performance target corresponds to multiple performance indicators. Each test condition corresponds to a vehicle performance target.

In one embodiment of the present disclosure, the performance indicators corresponding to the vehicle performance target may include but are not limited to: the minimum allowable engine speed under test conditions, the braking distance under test conditions, and the target under test conditions. Gear changes, etc.

The vehicle performance target may include performance index values corresponding to each performance index.

Step 230: Repeat the simulation steps, parameter adjustment steps and actual vehicle testing steps until the test results meet the vehicle performance target corresponding to the test working condition model.

If the test results do not meet the vehicle performance target corresponding to the test working condition model, the simulation steps, parameter adjustment steps and real vehicle test steps are repeated in sequence. When the test results meet the vehicle performance target corresponding to the test working condition model, the matching parameter optimization step ends.

The simulation steps may include: simulating based on the vehicle dynamics model, the test condition model and the system-related model to obtain the simulation results.

The engine torque model, transmission dynamics model, transmission shift control logic model and braking system control model are all simulation models used to simulate the vehicle, so corresponding simulation results can be obtained.

The parameter adjustment step may include: adjusting the adjustable matching parameters according to the simulation results and the vehicle performance target.

By adjusting the corresponding adjustable matching parameters, the vehicle performance can reach or be close to the vehicle performance target corresponding to the test conditions.

By adjusting the adjustable matching parameters based on the simulation results, the parameter boundary positioning can be guided by the simulation results.

The actual vehicle testing step may include: performing an actual vehicle test based on the adjusted adjustable matching parameters, obtaining test results, and adjusting the adjustable matching parameters again based on the data analysis results of the test results.

Conducting actual vehicle testing is equivalent to the process of actual vehicle verification of the adjusted adjustable matching parameters. If it is determined through the data analysis results that the test results do not meet the corresponding vehicle performance goals, the adjustable matching parameters need to be adjusted again, and the simulation is performed again based on the model configured with the adjusted adjustable matching parameters. Parameter optimization can be further achieved by adjusting adjustable matching parameters based on test results of real vehicles.

When the test results meet the vehicle performance target corresponding to the test working condition model, the matching parameter optimization step ends.

Step 130: Determine the optimal vehicle performance index based on the test results corresponding to each test condition model and the vehicle performance target.

The test results based on which the optimal vehicle performance indicators are determined can be the last test results. The optimal vehicle performance index can be defined by weighing and compromising the vehicle performance targets corresponding to each test condition model based on the test results corresponding to each test condition model.

Step 140: If the vehicle performance index values under each test condition meet the optimal vehicle performance index, the optimization of the adjustable matching parameters is completed.

In one embodiment of the present disclosure, after determining the optimal vehicle performance index based on the test results corresponding to each test working condition model and the vehicle performance target, the matching parameter optimization method of the vehicle also includes:

If the vehicle's vehicle performance index value under any test condition does not meet the vehicle's optimal performance index, continue to adjust the adjustable matching parameters until the vehicle's vehicle performance index value under each test condition meets the vehicle performance optimal index.

Only when the vehicle performance index values under each test condition meet the optimal vehicle performance index, it means that the adjustable matching parameters have reached a reasonable state. Otherwise, the adjustable matching parameters need to continue to be adjusted and optimized.

In one embodiment of the present disclosure, after determining the optimal vehicle performance index based on the test results corresponding to each test working condition model and the vehicle performance target, the matching parameter optimization method of the vehicle also includes:

If the vehicle's vehicle performance index value under the target test conditions does not meet the optimal vehicle performance index, the vehicle performance target corresponding to the target test condition will be adjusted until the vehicle's vehicle performance index value under each test condition is All meet the optimal vehicle performance indicators.

When the vehicle performance index value under a certain test condition does not meet the optimal vehicle performance index, it may be because the vehicle performance target corresponding to the test condition is too limited. At this time, the test can also be adjusted The vehicle performance target corresponding to the working condition is used to further determine the optimal parameters.

In one embodiment of the present disclosure, the test results include performance index values corresponding to multiple performance indicators. If the vehicle performance index values under each test condition all meet the optimal vehicle performance index, the comparison is completed. Optimization of adjustable matching parameters, including:

For each test condition, based on the weight corresponding to each performance index, determine the weighted result of each performance index value in the test results of the test condition as the vehicle performance index value;

If the vehicle performance index value reaches the optimal vehicle performance index, it is determined that the vehicle performance index value under the test conditions meets the optimal vehicle performance index.

For example, the optimal vehicle performance index is 1, and there can be two performance indexes. The first performance index value is 1.2, and the second performance index value is 0.8. However, since the weight of the first performance index is 0.75, the weight of the second performance index is 0.75. The weight is 0.25, so the vehicle performance index value is 1.2×0.75+0.8×0.25=1.1>1, so even if the second performance index value does not exceed 1, the vehicle performance can be optimal.

The solution in the embodiment of the present disclosure is not oriented to achieve the optimal value of each performance index, but on the basis that each performance index value reaches the standard, based on the vehicle performance index value calculated with different weights, the solution reaches the optimal value of the entire vehicle. The optimal performance index is used to determine that the vehicle meets the optimal performance index of the entire vehicle, so that the optimized parameters can reach the optimal level of the entire vehicle.

Figure 3 is a specific flow chart of a matching parameter optimization method for a complete vehicle according to an exemplary embodiment. The following is a further introduction to the solution of the embodiment of the present disclosure with reference to Figure 3: After the matching is started, the engine torque model is first established, and then the transmission dynamics model and the shift control logic model are established. Next, the vehicle dynamics model is established, and Braking system control model; then, establish the test working condition model; then, set the vehicle performance indicators, such as the minimum engine speed and braking distance; then, adjust the matching parameters based on the simulation results, and verify the matching parameters with the actual vehicle; then, Determine whether the test results meet the target. If not, re-adjust the matching parameters based on the simulation results and verify the matching parameters with the actual vehicle again. If yes, then determine whether the matching is established under all working conditions; if not, return to the establishment of the test process again. In the step of condition model, continue to match other test working conditions. If all working conditions are matched, the optimal vehicle performance index will be defined based on the performance of all working conditions; then, determine whether the optimal vehicle performance index is established; if not , then reset the vehicle performance index and perform subsequent steps; if the vehicle performance reaches the optimal index, the matching is completed.

The solutions of the embodiments of the present disclosure can be applied to parameter matching and optimization of vehicle driving systems such as engine control systems and transmission control systems, as well as braking systems containing ABS/ESP control units under different working conditions.

To sum up, according to the vehicle matching parameter optimization method provided by the embodiment of the present disclosure, a model of the engine, transmission, vehicle, and braking system is established with the help of Simulink tools. The model includes hardware parameters and control logic parameters. After given certain working condition parameters, the performance of the driving system and braking system under this working condition can be simulated. Compare the simulation results with the set goals. If the simulation results deviate from the set goals, adjust the parameters in the model for optimization. Since the simulation model cannot fully represent the actual vehicle, the parameter matching based on the model needs to be further verified on the entire vehicle. After verification, it can provide guidance for parameter adjustment in the model. By first simulating, then verifying the actual vehicle and then simulating, a cross-iterative optimization process is formed, and finally the optimal parameter settings can be obtained, enabling more efficient and accurate parameter matching.

The optimization of vehicle performance achieved according to the solutions of the embodiments of the present disclosure is reflected in the fact that the engine does not stall, the transmission clutch does not have the risk of overheating and burning, and the braking distance and vehicle stability during the braking process are guaranteed.

The present disclosure also provides a matching parameter optimization device for a complete vehicle. The following are device embodiments of the present disclosure.

Figure 4 is a block diagram of a matching parameter optimization device for a complete vehicle according to an exemplary embodiment. As shown in Figure 4, device 400 includes:

The model building module 410 is configured to respectively establish the vehicle dynamics model, the basic test condition model and multiple system-related models of the vehicle, and configure parameters for the vehicle dynamics model and each of the system-related models, The parameters include adjustable matching parameters;

The parameter optimization module 420 is configured to perform a matching parameter optimization step for each test condition. The matching parameter optimization step includes: configuring test condition parameters for the basic test condition model to obtain a test condition model; obtaining the corresponding The vehicle performance target set by the test working condition model, the vehicle performance target corresponds to multiple performance indicators; the simulation steps, parameter adjustment steps and real vehicle test steps are repeatedly executed until the test results meet the test conditions. vehicle performance target corresponding to the condition model, and ends the matching parameter optimization step. The simulation step includes: performing simulation based on the vehicle dynamics model, the test condition model and the system-related model to obtain a simulation Result; the parameter adjustment step includes: adjusting the adjustable matching parameters according to the simulation results and the vehicle performance target; the actual vehicle testing step includes: performing an actual vehicle test based on the adjusted adjustable matching parameters, Obtain the test results, and adjust the adjustable matching parameters again according to the data analysis results of the test results;

The indicator determination module 430 is configured to determine the optimal vehicle performance indicator based on the test results corresponding to each test working condition model and the vehicle performance target;

The judgment module 440 is configured to complete the optimization of the adjustable matching parameters if the vehicle performance index values of the vehicle under each test condition meet the optimal vehicle performance index.

According to a third aspect of the present disclosure, an electronic device capable of implementing the above method is also provided.

Those skilled in the art will understand that various aspects of the present invention may be implemented as systems, methods or program products. Therefore, various aspects of the present invention can be implemented in the following forms, namely: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software implementations, which may be collectively referred to herein as "Circuits", "modules" or "systems".

An electronic device 500 according to this embodiment of the invention is described below with reference to FIG. 5 . The electronic device 500 shown in FIG. 5 is only an example and should not impose any limitations on the functions and scope of use of the embodiments of the present invention.

As shown in Figure 5, electronic device 500 is embodied in the form of a general computing device. The components of the electronic device 500 may include, but are not limited to: the above-mentioned at least one processing unit 510, the above-mentioned at least one storage unit 520, and a bus 530 connecting different system components (including the storage unit 520 and the processing unit 510).

Wherein, the storage unit stores program code, and the program code can be executed by the processing unit 510, so that the processing unit 510 executes various exemplary methods according to the present invention described in the "Embodiment Methods" section of this specification. Implementation steps.

The storage unit 520 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 521 and/or a cache storage unit 522, and may further include a read-only storage unit (ROM) 523.

Storage unit 520 may also include a program/utility 524 having a set of (at least one) program modules 525 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, Each of these examples, or some combination, may include the implementation of a network environment.

Bus 530 may be a local area representing one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, a graphics acceleration port, a processing unit, or using any of a variety of bus structures. bus.

Electronic device 500 may also communicate with one or more external devices 700 (e.g., keyboard, pointing device, Bluetooth device, etc.), may also communicate with one or more devices that enable a user to interact with electronic device 500, and/or with Any device that enables the electronic device 500 to communicate with one or more other computing devices (eg, router, modem, etc.). Such communication may occur through an input/output (I/O) interface 550, such as with display unit 540. Furthermore, the electronic device 500 may also communicate with one or more networks (eg, a local area network (LAN), a wide area network (WAN), and/or a public network, such as the Internet) through the network adapter 560. As shown, network adapter 560 communicates with other modules of electronic device 500 via bus 530. It should be understood that, although not shown in the figures, other hardware and/or software modules may be used in conjunction with electronic device 500, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives And data backup storage system, etc.

Through the above description of the embodiments, those skilled in the art can easily understand that the example embodiments described here can be implemented by software, or can be implemented by software combined with necessary hardware. Therefore, the technical solution according to the embodiment of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, U disk, mobile hard disk, etc.) or on the network , including several instructions to cause a computing device (which may be a personal computer, a server, a terminal device, a network device, etc.) to execute a method according to an embodiment of the present disclosure.

According to a fourth aspect of the present disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the above method in this specification is stored. In some possible implementations, various aspects of the present invention can also be implemented in the form of a program product, which includes program code. When the program product is run on a terminal device, the program code is used to cause the The terminal device performs the steps according to various exemplary embodiments of the present invention described in the "Exemplary Method" section above in this specification.

Referring to Figure 6, a program product 600 for implementing the above method according to an embodiment of the present invention is described, which can adopt a portable compact disk read-only memory (CD-ROM) and include program code, and can be used on a terminal device, For example, run on a personal computer. However, the program product of the present invention is not limited thereto. In this document, a readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus or device.

The program product may take the form of any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: electrical connection with one or more conductors, portable disk, hard disk, random access memory (RAM), read only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above.

A computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave carrying readable program code therein. Such propagated data signals may take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A readable signal medium may also be any readable medium other than a readable storage medium that can send, propagate, or transport the program for use by or in connection with an instruction execution system, apparatus, or device.

Program code embodied on a readable medium may be transmitted using any suitable medium, including but not limited to wireless, wireline, optical cable, RF, etc., or any suitable combination of the foregoing.

Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages such as Java, C++, etc., as well as conventional procedural Programming language—such as "C" or a similar programming language. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server execute on. In situations involving remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device, such as provided by an Internet service. (business comes via Internet connection).

Furthermore, the above-mentioned drawings are only schematic illustrations of processes included in methods according to exemplary embodiments of the present invention, and are not intended to be limiting. It is readily understood that the processes shown in the above figures do not indicate or limit the temporal sequence of these processes. In addition, it is also easy to understand that these processes may be executed synchronously or asynchronously in multiple modules, for example.

It is to be understood that the present invention is not limited to the precise construction described above and illustrated in the accompanying drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the invention is limited only by the appended claims.

Claims (7)

1. The method for optimizing the matching parameters of the whole vehicle is characterized by comprising the following steps of:

respectively establishing a whole vehicle dynamics model, a basic test working condition model and a plurality of system related models of a vehicle, and carrying out parameter configuration on the whole vehicle dynamics model and each system related model, wherein the parameters comprise adjustable matching parameters;

and respectively executing a matching parameter optimization step aiming at each test working condition, wherein the matching parameter optimization step comprises the following steps:

configuring test working condition parameters for the basic test working condition model to obtain a test working condition model, wherein the basic test working condition model is a model not provided with the test working condition parameters, and the test working condition parameters comprise an accelerator signal and a brake signal;

the method comprises the steps of obtaining a whole vehicle performance target set for the test working condition model, wherein the whole vehicle performance target corresponds to a plurality of performance indexes, each test working condition corresponds to one whole vehicle performance target, and the performance indexes corresponding to the whole vehicle performance target comprise: the minimum value of the engine speed allowed under the test working condition, the braking distance in the test working condition and the target gear change in the test working condition;

repeating the simulation step, the parameter adjustment step and the real vehicle test step until the test result meets the whole vehicle performance target corresponding to the test working condition model, and ending the matching parameter optimization step, wherein the simulation step comprises the following steps: simulating based on the whole vehicle dynamics model, the test working condition model and the system related model to obtain a simulation result; the parameter adjustment step comprises the following steps: adjusting the adjustable matching parameters according to the simulation result and the whole vehicle performance target; the real vehicle testing steps comprise: performing real vehicle testing based on the adjusted adjustable matching parameters to obtain a testing result, and adjusting the adjustable matching parameters again according to a data analysis result of the testing result, wherein the testing result comprises performance index values respectively corresponding to the performance indexes;

determining an optimal index of the whole vehicle performance according to the test result and the whole vehicle performance target corresponding to each test working condition model;

aiming at each test working condition, determining a weighted result of each performance index value in test results of the test working condition based on the weight corresponding to each performance index value, and taking the weighted result as a whole vehicle performance index value;

and if the whole vehicle performance index value reaches the whole vehicle performance optimal index, determining that the whole vehicle performance index value of the vehicle under the test working condition meets the whole vehicle performance optimal index.

2. The method of claim 1, wherein after determining the overall vehicle performance optimal index according to the test result and the overall vehicle performance target corresponding to each test condition model, the method further comprises:

if the vehicle performance index value of the vehicle under any test working condition does not meet the vehicle performance optimal index, continuously adjusting the adjustable matching parameters until the vehicle performance index value of the vehicle under each test working condition meets the vehicle performance optimal index.

3. The method of claim 1, wherein after determining the overall vehicle performance optimal index according to the test result and the overall vehicle performance target corresponding to each test condition model, the method further comprises:

and if the vehicle performance index value of the vehicle under the target test working condition does not meet the vehicle performance optimal index, adjusting the vehicle performance target corresponding to the target test working condition until the vehicle performance index value of the vehicle under each test working condition meets the vehicle performance optimal index.

4. The method of any of claims 1-3, wherein the plurality of system-related models includes an engine torque model, a transmission dynamics model, a transmission shift control logic model, and a brake system control model.

5. The utility model provides a matching parameter optimizing device of whole car, its characterized in that, the device includes:

the system comprises a model building module, a model analysis module and a model analysis module, wherein the model building module is configured to respectively build a whole vehicle dynamics model, a basic test working condition model and a plurality of system related models of a vehicle, and perform parameter configuration on the whole vehicle dynamics model and each system related model, wherein the parameters comprise adjustable matching parameters;

the parameter optimization module is configured to respectively execute a matching parameter optimization step aiming at each test working condition, and the matching parameter optimization step comprises the following steps: configuring test working condition parameters for the basic test working condition model to obtain a test working condition model, wherein the basic test working condition model is a model not provided with the test working condition parameters, and the test working condition parameters comprise an accelerator signal and a brake signal; the method comprises the steps of obtaining a whole vehicle performance target set for the test working condition model, wherein the whole vehicle performance target corresponds to a plurality of performance indexes, each test working condition corresponds to one whole vehicle performance target, and the performance indexes corresponding to the whole vehicle performance target comprise: the minimum value of the engine speed allowed under the test working condition, the braking distance in the test working condition and the target gear change in the test working condition; repeating the simulation step, the parameter adjustment step and the real vehicle test step until the test result meets the whole vehicle performance target corresponding to the test working condition model, and ending the matching parameter optimization step, wherein the simulation step comprises the following steps: simulating based on the whole vehicle dynamics model, the test working condition model and the system related model to obtain a simulation result; the parameter adjustment step comprises the following steps: adjusting the adjustable matching parameters according to the simulation result and the whole vehicle performance target; the real vehicle testing steps comprise: performing real vehicle testing based on the adjusted adjustable matching parameters to obtain a testing result, and adjusting the adjustable matching parameters again according to a data analysis result of the testing result, wherein the testing result comprises performance index values respectively corresponding to the performance indexes;

the index determining module is configured to determine an optimal index of the whole vehicle performance according to the test result and the whole vehicle performance target corresponding to each test working condition model;

the judging module is configured to determine the weighted result of each performance index value in the test results of the test working conditions based on the weight corresponding to each performance index for each test working condition, and the weighted result is used as the performance index value of the whole vehicle; and if the whole vehicle performance index value reaches the whole vehicle performance optimal index, determining that the whole vehicle performance index value of the vehicle under the test working condition meets the whole vehicle performance optimal index.

6. A computer readable program medium, characterized in that it stores computer program instructions, which when executed by a computer, cause the computer to perform the method according to any one of claims 1 to 4.

7. An electronic device, the electronic device comprising:

a processor;

a memory having stored thereon computer readable instructions which, when executed by the processor, implement the method of any of claims 1 to 4.