Joint simulation method, device and equipment of vehicle electronic control system and vehicle

Abstract

The invention provides a joint simulation method, device and equipment for a vehicle electronic control system and a vehicle, and relates to the technical field of vehicle chassis electronic control, and the method comprises the steps: firstly obtaining basic data of an electronic control system model and a vehicle dynamics model, and a simulation test working condition; then, an interface mapping relation between an electric control system model and a vehicle dynamics model is established, and the electric control system model and the vehicle dynamics model are integrated by means of a multidisciplinary collaborative tool chain to generate an interactive dynamic link library file, so that efficient and stable joint simulation of the electric control system and the Adams whole vehicle model is achieved. According to the method, key parameters are uniformly packaged into an external system library, direct debugging of an electronic control model and flexible configuration of control parameters in a single Adams environment are supported, so that the problems of multi-software switching, solver conflict and interface immobilization in traditional master-slave joint simulation are avoided, the simulation stability, the execution efficiency and the system expansibility are effectively improved, and the method is suitable for large-scale popularization and application. And the control effect of the electronic control system on the dynamic performance of the vehicle can be verified more accurately.

Description

Technical Field

[0001] The present invention relates to the field of vehicle chassis electronic control technology, and in particular to a joint simulation method, device, equipment and vehicle for a vehicle electronic control system. Background Art

[0002] In the field of vehicle chassis design, to accurately evaluate vehicle dynamics and optimize overall vehicle design, it is often necessary to integrate and simulate electronic control systems (such as ESP and ABS) with a multibody dynamics-based Adams vehicle model to verify the synergy between the electronic-mechanical coupled system. This makes joint simulation of electronic control systems and Adams a critical step in the R&D process. Currently, most existing solutions encapsulate and embed the Adams model within the Simulink environment, with Simulink leading the entire simulation process. While this approach is simple to implement and easy to debug, it suffers from numerous shortcomings in practical applications. The need to operate multiple software platforms simultaneously leads to cumbersome parameter modifications and iterations, significantly impacting simulation efficiency. Furthermore, this approach's rigid integration structure means that replacing or upgrading the electronic control system often requires reconfiguring interfaces and even rebuilding the model, resulting in limited system scalability and flexibility. These shortcomings limit the applicability and efficiency of existing technologies in the development of complex electronic control systems. Summary of the Invention

[0003] The purpose of the present invention is to provide a joint simulation method, device, equipment and vehicle for a vehicle electronic control system to solve one or more technical problems existing in the prior art and at least provide a beneficial option or create conditions.

[0004] The present invention solves the technical problem as follows: On the one hand, the present invention provides a joint simulation method of a vehicle electronic control system, comprising the following steps: Obtain basic data of the electronic control system model and the vehicle dynamics model, as well as simulation test conditions; wherein the electronic control system model is a control model built in the Simulink environment, and the vehicle dynamics model is a full vehicle model built in the Adams environment; Based on the basic data, an interface mapping relationship of the joint simulation is established; wherein the interface mapping relationship includes an input interface of the vehicle state signal in the vehicle dynamics model and an output interface of the output signal of the electronic control system model; Integrating the electronic control system model with the vehicle dynamics model through a multidisciplinary collaborative tool chain to generate an interactive dynamic link library file; wherein the dynamic link library file is used to achieve real-time interaction between the vehicle dynamics model and the electronic control system model; Encapsulating the dynamic link library file into an external system library and configuring editable key parameters; wherein the key parameters include control algorithm parameters of the electronic control system model and physical characteristic parameters of the vehicle dynamics model; According to the simulation test conditions, the Adams simulation driven by the external system library is run, and the control effect of the vehicle electronic control system on the vehicle dynamic performance is verified based on the simulation results to complete the joint simulation.

[0005] Furthermore, the obtaining of basic data of the electronic control system model includes the following steps: Based on the target electronic control system type, the electronic control system model is constructed using the Simulink simulation environment, and the control algorithm parameters in the electronic control system model are represented by independent editable modules to form parameterizable data. The electronic control system model includes a calculation module, an adjustment module, and a distribution module. The calculation module is used to calculate the ideal vehicle motion parameters; the adjustment module is used to optimize the control output; and the distribution module is used to distribute actuator signals. The constructed electric control system model is saved as a standard format file supporting Adams integration as basic data of the electric control system model.

[0006] Furthermore, the acquisition of basic data of the vehicle dynamics model includes the following steps: Determine the basic subsystems of the vehicle dynamics model based on the target vehicle type using the Adams simulation environment; wherein the basic subsystems include the suspension system, steering system, powertrain system, body system, and tire system; An interactive interface is configured in the basic subsystem, an execution interface for braking torque is set in the braking system, and a sensor signal interface is set in the steering system and the body system; the execution interface is used to receive the braking torque output by the electronic control system; and the sensor signal interface is used to obtain the vehicle status signal; The configured basic subsystems are integrated into a complete Adams vehicle dynamics model as the basic data of the vehicle dynamics model.

[0007] Furthermore, the electronic control system model and the vehicle dynamics model are integrated through a multidisciplinary collaborative tool chain to generate an interactive dynamic link library file, including the following steps: Exporting the control strategy parameters of the vehicle dynamics model through the Adams collaborative tool and loading them into the compilation environment; wherein the control strategy parameters include signal type and unit information of the input and output interfaces; Connecting the input and output interfaces of the electronic control system model and the vehicle dynamics model in a Simulink environment so that the vehicle state signal of the vehicle dynamics model is input to the electronic control system model and the braking torque command of the electronic control system model is output to the actuator interface of the vehicle dynamics model; The integrated electronic control system model and the vehicle dynamics model are compiled into the dynamic link library file that can be called by Adams using a multidisciplinary collaborative code generation tool.

[0008] Furthermore, after the dynamic link library is integrated, the simulation process is dominated by Adams' GStiff solver.

[0009] Furthermore, the encapsulation of the dynamic link library file into an external system library and configuring editable key parameters includes the following steps: Encapsulating the dynamic link library file into the external system library file using the Adams Mechatronics collaborative tool; wherein the external system library file includes interactive interface information between the electronic control system model and the vehicle dynamics model; Use a text editor to open the external system library file and configure the key parameters; the key parameters are represented by independent fields and support direct modification of values; Verify the compatibility of the configured key parameters with the simulation environment, so that the parameter format of the key parameters meets the Adams simulation requirements and can be correctly identified and called.

[0010] Furthermore, the Adams simulation driven by the external system library is run according to the simulation test conditions, and the control effect of the vehicle electronic control system on the vehicle dynamic performance is verified according to the simulation results to complete the joint simulation, which includes the following steps: According to the simulation test conditions, running the Adams simulation driven by the external system library to collect vehicle dynamic performance indicators; wherein the dynamic performance indicators include actual yaw rate, center of mass sideslip angle, and braking torque output of each wheel; analyzing a performance deviation between the vehicle dynamic performance index and an ideal index generated by a calculation module of the electronic control system model; verifying the control effect of the vehicle electronic control system based on the performance deviation: if the performance deviation is less than a preset threshold, determining that the control effect of the vehicle electronic control system on the vehicle dynamic performance meets the standard; if the performance deviation exceeds the threshold, feedback optimization of key parameters in the external system library; Repeat the above simulation and verification steps until the control effect meets the requirements and the joint simulation is completed.

[0011] In another aspect, the present application provides a joint simulation device for a vehicle electronic control system, comprising: A basic data acquisition module is used to obtain basic data of the electronic control system model and the vehicle dynamics model, as well as simulation test conditions; wherein the electronic control system model is a control model built in the Simulink environment, and the vehicle dynamics model is a full vehicle model built in the Adams environment; An interface mapping module, configured to establish an interface mapping relationship for the joint simulation based on the basic data; wherein the interface mapping relationship includes an input interface for a vehicle state signal in the vehicle dynamics model and an output interface for an output signal of the electronic control system model; a model integration module, configured to integrate the electronic control system model with the vehicle dynamics model through a multidisciplinary collaborative tool chain to generate an interactive dynamic link library file; wherein the dynamic link library file is configured to enable real-time interaction between the vehicle dynamics model and the electronic control system model; an external packaging module, configured to connect the input and output interfaces of the electronic control system model and the vehicle dynamics model in a Simulink environment, such that the vehicle state signal of the vehicle dynamics model is input to the electronic control system model, and the braking torque command of the electronic control system model is output to the actuator interface of the vehicle dynamics model; The joint simulation module is used to run the Adams simulation driven by the external system library according to the simulation test conditions, verify the control effect of the vehicle electronic control system on the vehicle dynamic performance according to the simulation results, and complete the joint simulation.

[0012] On the other hand, the present application provides an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the aforementioned joint simulation method of the vehicle electronic control system when executing the computer program.

[0013] On the other hand, the present application provides a vehicle, which performs co-simulation on parameters of a vehicle chassis electronic control system through the aforementioned co-simulation method of a vehicle electronic control system.

[0014] The beneficial effects of the present invention are as follows: the joint simulation method of the vehicle electronic control system provided in the present application first obtains the basic data of the electronic control system model and the vehicle dynamics model, as well as the simulation test conditions; then, by establishing an interface mapping relationship between the electronic control system model and the vehicle dynamics model, and integrating them with a multidisciplinary collaborative tool chain to generate an interactive dynamic link library file, an efficient and stable joint simulation of the electronic control system and the Adams vehicle model is achieved. The method uniformly encapsulates key parameters into an external system library, supports direct calling of the electronic control model and flexible configuration of control parameters in a single Adams environment, thereby avoiding the problems of multi-software switching, solver conflicts and interface fixation in traditional master-slave joint simulation, effectively improving simulation stability, execution efficiency and system scalability, and being able to more accurately verify the control effect of the electronic control system on the vehicle's dynamic performance. The present application also provides corresponding devices, equipment and vehicles. The beneficial effects of the devices, equipment and vehicles are similar to those of the method and will not be elaborated here.

[0015] Other features and advantages of the present application will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present application. The purposes and other advantages of the present application can be achieved and obtained through the structures particularly pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings are used to provide a further understanding of the technical solution of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the technical solution of the present invention and do not constitute a limitation to the technical solution of the present invention.

[0017] Figure 1 is a flow chart of the joint simulation method of the vehicle electronic control system provided by this application; Figure 2 This is a structural diagram of the joint simulation device for the vehicle electronic control system provided by this application; Figure 3 This is a structural diagram of the joint simulation electronic equipment of the vehicle electronic control system provided in this application. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0019] The present application is further described below in conjunction with the accompanying drawings and specific embodiments. The described embodiments should not be considered as limiting the present application. All other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0020] In the following description, reference is made to “some embodiments”, which describes a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application pertains. The terms used herein are for the purpose of describing the embodiments of this application only and are not intended to limit this application.

[0022] In modern vehicle design, especially chassis design, engineers rely on multibody dynamics simulation software such as Adams to predict vehicle dynamic performance. With the advancement of electronic control systems, these systems have become an integral part of the vehicle, necessitating the integration of electronic control algorithms or models into Adams simulations. This helps engineers better evaluate and optimize vehicle dynamic performance, particularly by identifying potential issues and implementing improvements during the development phase.

[0023] First, the traditional co-simulation method imports the Adams model as an S-Function into Simulink for co-simulation, and uses Simulink's solvers (such as the ode45 solver) for computation. However, this approach suffers from significant solver compatibility issues: Simulink's ode45 solver differs from Adams' GStiff solver, and model instability can occur at the start of the simulation. This reduces the reliability of the simulation results and affects the accurate assessment of vehicle dynamics performance.

[0024] Secondly, each simulation requires running both Adams and Simulink simultaneously, which not only increases system complexity but also reduces simulation efficiency. Furthermore, during parameter adjustment and calibration, each parameter modification must be performed within Simulink, significantly impacting work efficiency and making the entire process cumbersome. The need to frequently switch between multiple software programs creates additional time and technical challenges for engineers when adjusting and verifying parameters.

[0025] Furthermore, the existing parameter adjustment and optimization process is inflexible and cannot be quickly adjusted directly through simple text editing tools, making the entire process complicated and time-consuming. Parameter modifications often require access to a specific software environment, which not only limits flexibility but also slows down the R&D cycle. To improve efficiency, it is necessary to provide a more convenient way to modify key parameters to quickly respond to changing design requirements.

[0026] To address the above-mentioned issues, the present invention proposes a joint simulation method, device, equipment, and vehicle for a vehicle electronic control system. This method is a new code compilation-based method designed to improve the stability of the simulation and the efficiency of parameter adjustment and calibration. The method includes establishing a control model in Simulink, processing the entire vehicle model in AdamsCar and adding a control subsystem, outputting it through the Mechatronics module and connecting it to the Simulink model, compiling and generating a dynamic link library file, and encapsulating it as an external system library for Adams to call. This method simplifies the simulation process, improves the stability of the solution link, and improves the efficiency of the parameter adjustment and calibration links, helping to more efficiently evaluate and optimize the dynamic response of the vehicle.

[0027] First, the joint simulation method of the vehicle electronic control system provided by the embodiment of the present application will be described in detail with reference to the accompanying drawings.

[0028] Reference Figure 1 The implementation process of the joint simulation method of the vehicle electronic control system provided in the embodiment of the present application includes but is not limited to the following steps.

[0029] Step S110 , obtaining basic data of the electronic control system model and the vehicle dynamics model, as well as simulation test conditions.

[0030] Among them, the electronic control system model is a control model built in the Simulink environment, and the vehicle dynamics model is a full vehicle model in the Adams environment.

[0031] Step S110 is the starting point of the entire co-simulation process, primarily to ensure accurate and complete initial data. The electronic control system model is a control model built in the Simulink environment, containing the algorithms and logic required to implement specific control functions. The vehicle dynamics model, on the other hand, is a full-vehicle model built in the Adams environment, used to simulate the vehicle's dynamic behavior under various conditions. Furthermore, specific simulation test conditions must be determined, including but not limited to different driving scenarios and environmental conditions, to ensure the comprehensiveness and accuracy of the simulation. This phase of work lays a solid data foundation for subsequent model integration and simulation.

[0032] Step S120: establishing an interface mapping relationship for joint simulation based on basic data.

[0033] The interface mapping relationship includes the input interface of the vehicle state signal in the vehicle dynamics model and the output interface of the output signal of the electronic control system model.

[0034] In step S120, based on the acquired basic data, an interface mapping relationship is established between the electronic control system model and the vehicle dynamics model. These interfaces primarily include the vehicle state signal input interface (such as vehicle speed and sideslip angle) in the vehicle dynamics model, and the electronic control system model output interface (such as braking torque command). Establishing this interface mapping relationship is key to ensuring effective interaction between the two independent models. It enables the electronic control system's control output to directly act on the vehicle dynamics model and receive state feedback from the vehicle, thereby achieving closed-loop control. This process is crucial to ensuring the authenticity and effectiveness of the simulation.

[0035] Step S130 : Integrate the electronic control system model with the vehicle dynamics model through a multidisciplinary collaborative tool chain to generate an interactive dynamic link library file.

[0036] Among them, the dynamic link library file is used to realize the real-time interaction between the vehicle dynamics model and the electronic control system model.

[0037] In step S130, the two models are deeply integrated using a multidisciplinary collaborative toolchain, generating a dynamic link library (DLL) file that enables real-time interaction. This DLL not only integrates the functionality of the electronic control system model and the vehicle dynamics model but also ensures seamless communication between them. This approach avoids the instability issues inherent in traditional methods due to solver differences, while streamlining the simulation process and improving efficiency. This DLL acts as a bridge between the electronic control system and vehicle dynamics models, enabling real-time data exchange and providing strong support for subsequent simulations.

[0038] Step S140: Encapsulate the dynamic link library file into an external system library and configure editable key parameters.

[0039] Among them, the key parameters include the control algorithm parameters of the electronic control system model and the physical characteristic parameters of the vehicle dynamics model.

[0040] In step S140, the generated dynamic link library file is further encapsulated into an external system library, enabling direct access within the Adams environment. Furthermore, to enhance flexibility and adaptability, key parameters (including control algorithm parameters for the electronic control system model and physical characteristic parameters for the vehicle dynamics model) are designed to be editable. This allows engineers to quickly adjust parameter values ​​based on actual needs without having to recompile the entire model. This approach not only accelerates the debugging process but also facilitates simulation verification of different operating conditions, significantly improving work efficiency.

[0041] Step S150 , running an Adams simulation driven by an external system library according to the simulation test conditions, verifying the control effect of the vehicle electronic control system on the vehicle dynamic performance according to the simulation results, and completing the joint simulation.

[0042] In step S150, based on the previously defined simulation test conditions, an external system library is used to drive Adams simulation and evaluate the vehicle's electronic control system's control over vehicle dynamic performance. Through the simulation, vehicle dynamic performance indicators (such as actual yaw rate, sideslip angle, and wheel braking torque output) are collected and analyzed and compared with ideal indicators to verify the electronic control system's control effectiveness. If the performance deviation exceeds a preset threshold, key parameters are optimized until the expected performance is achieved. This process not only verifies the effectiveness of the co-simulation method but also provides an important reference for actual vehicle design.

[0043] It should be noted that Adams plays a core role in the joint simulation of vehicle electronic control systems. It not only provides a high-precision multi-body dynamics simulation environment that can realistically simulate the dynamic response of the entire vehicle under various working conditions, but also ensures the stability and computational efficiency of the simulation through its built-in GStiff solver. Using Adams, engineers can integrate the electronic control system model with the vehicle dynamics model to achieve "electronic-mechanical" closed-loop control, thereby accurately evaluating and optimizing the vehicle's dynamic performance. In addition, Adams supports the encapsulation of complex control systems as external system libraries, making parameter adjustment more flexible and convenient, and providing a unified and efficient simulation platform, effectively improving development efficiency and design quality, and providing strong support for the development of modern vehicles, especially chassis electronic control systems.

[0044] Simulink plays a key role in the co-simulation of vehicle electronic control systems. It provides a powerful control algorithm design and verification environment, enabling engineers to easily build and test complex electronic control system models such as ESP and ABS. With Simulink, users can leverage a rich library of modules and tools for system modeling, simulation, and analysis, enabling full-process development from conceptual design to detailed parameter tuning. Its seamless integration with Adams allows for deep interaction between electronic control system models and vehicle dynamics models, ensuring that control strategies can be effectively verified and optimized in a real vehicle dynamic environment. In addition, Simulink's automated code generation further simplifies the conversion process from models to actual applications, greatly improving R&D efficiency and flexibility. This comprehensive capability makes Simulink an indispensable tool for modern vehicle control system development.

[0045] In some embodiments of the present application, in step S110 , the implementation process of obtaining basic data of the electronic control system model includes but is not limited to the following steps.

[0046] In step S210 , an electronic control system model is constructed through the Simulink simulation environment according to the target electronic control system type, and control algorithm parameters in the electronic control system model are represented by independent editable modules to form parameterizable data.

[0047] The electronic control system model includes a calculation module, an adjustment module, and a distribution module. The calculation module is used to calculate the ideal vehicle motion parameters. The adjustment module is used to optimize the control output. The distribution module is used to distribute actuator signals.

[0048] Step S210 is the key initial step in electronic control system modeling. It aims to build a fully functional electronic control system model within the Simulink environment, based on the requirements of actual vehicle control systems (such as ESP and ABS). This model typically consists of a calculation module, an adjustment module, and a distribution module. The calculation module calculates the ideal vehicle motion state based on sensor input signals (such as vehicle speed and acceleration); the adjustment module optimizes the control output to ensure smooth and effective control commands; and the distribution module is responsible for properly distributing control signals to various actuators (such as brakes and motors). Furthermore, to enhance the flexibility and configurability of subsequent co-simulation, key parameters of the control algorithm (such as PID coefficients and threshold conditions) are extracted and encapsulated as independent, editable modules. This design allows for rapid parameter adjustments without modifying the model structure, significantly improving the model's adaptability and reusability.

[0049] In step S220 , the constructed electric control system model is saved as a standard format file supporting Adams integration as basic data of the electric control system model.

[0050] In step S220, after the electronic control system model is constructed and parameterized, it is converted into a standard format file that can be recognized and called by the Adams environment. This standard format is typically a common interface format supported by multidisciplinary collaborative simulation tool chains, such as FMU (Functional Mock-up Unit) or DLL (Dynamic Link Library). This format conversion not only ensures that the electronic control system model can be correctly loaded and run in Adams, but also preserves the functional logic and editable parameters of each module within the model. The processed model file becomes the foundational data for subsequent co-simulation processes, providing technical support for the efficient integration of the electronic control system and the vehicle dynamics model, while also laying a solid foundation for parameter configuration and system verification within a unified platform.

[0051] In some embodiments of the present application, in step S110 , the implementation process of obtaining basic data of the vehicle dynamics model includes but is not limited to the following steps.

[0052] Step S310 : Determine the basic subsystem of the vehicle dynamics model based on the target vehicle type through the Adams simulation environment.

[0053] Among them, the basic subsystems include suspension system, steering system, powertrain system, body system and tire system.

[0054] In step S310, key mechanical subsystems are selected and configured within the Adams simulation environment based on the specific structural and functional requirements of the target vehicle. These fundamental subsystems typically include the suspension, steering, powertrain, body, and tire systems, which together determine the vehicle's dynamic response characteristics under complex operating conditions. By modeling and integrating these subsystems, the vehicle's mechanical structure and kinematic behavior can be faithfully reproduced, providing a high-precision dynamics foundation for subsequent co-simulation with the electronic control system. The core purpose of this step is to establish a structurally complete, physically accurate, and scalable vehicle dynamics platform.

[0055] Step S320 , configuring an interactive interface in the basic subsystem, setting a braking torque execution interface in the braking system, and setting a sensor signal interface in the steering system and the body system.

[0056] The execution interface is used to receive the braking torque output by the electronic control system, and the sensor signal interface is used to obtain the vehicle status signal.

[0057] In step S320, an interaction mechanism with the electronic control system is introduced into the existing dynamics subsystem. This involves two specific aspects: first, a braking torque execution interface is configured in the braking system to receive control commands from the electronic control system (such as the braking force distribution signal output by the ESP controller); second, sensor signal interfaces are deployed in the steering and body systems to collect vehicle status information (such as speed, yaw rate, lateral acceleration, etc.) and feed it back to the electronic control system for real-time control. This bidirectional interactive interface design implements closed-loop control logic between the electronic control and the mechanical system, enabling the electronic control strategy to respond to real-world vehicle conditions and drive the corresponding actuators, thereby improving simulation realism and system interoperability.

[0058] Step S330 : Integrate the configured basic subsystems into a complete Adams vehicle dynamics model as basic data of the vehicle dynamics model.

[0059] In step S330, after completing the modeling and interface configuration of each subsystem, all subsystems are integrated in the Adams environment according to the actual vehicle assembly and connection methods to form a fully functional vehicle dynamics model. This model not only preserves the physical characteristics and interactive interfaces of each subsystem, but also reflects the comprehensive response of the entire vehicle under various driving conditions during the simulation process. As a core component of subsequent co-simulation, this model provides high-fidelity mechanical system support, ensuring that the behavior of the electronic control system in closed-loop control can be accurately evaluated. At the same time, this model also provides a unified simulation platform for parameter adjustment, test verification, and performance optimization, and is a key foundation for achieving efficient and stable co-simulation.

[0060] In some embodiments of the present application, in step S130, the electronic control system model and the vehicle dynamics model are integrated through a multidisciplinary collaborative tool chain to generate an interactive dynamic link library file, and the implementation process includes but is not limited to the following steps.

[0061] Step S410: Export the control strategy parameters of the vehicle dynamics model through the Adams collaborative tool and load them into the compilation environment.

[0062] The control strategy parameters include the signal type and unit information of the input and output interfaces.

[0063] In step S410, the control interaction information associated with the vehicle dynamics model established in Adams is extracted to prepare for subsequent integration with the electronic control system. Using the co-simulation tools provided by Adams, the model's input and output interface information, including key control strategy parameters such as signal type (e.g., analog, Boolean), units (e.g., m / s², rad), and so on, is exported. These parameters are loaded into a unified compilation environment and serve as the data foundation for interfacing with the electronic control system model. This step ensures signal consistency and compatibility between the two models, preventing integration failures due to mismatched data formats or communication protocols.

[0064] Step S420: Connect the input and output interfaces of the electronic control system model and the vehicle dynamics model in the Simulink environment so that the vehicle state signal of the vehicle dynamics model is input to the electronic control system model, and the braking torque command of the electronic control system model is output to the actuator interface of the vehicle dynamics model.

[0065] In step S420, a logical closed-loop connection is established between the electronic control system model and the vehicle dynamics model. Specifically, within the Simulink environment, vehicle state signals (such as vehicle speed and yaw rate) output by the vehicle dynamics model are transmitted as inputs to the electronic control system model. Simultaneously, control signals such as braking torque commands calculated by the electronic control system model are output to actuator interfaces (such as the brake module) within the vehicle dynamics model. This bidirectional connection establishes a complete "perception-decision-execution" control chain, enabling the co-simulation to truly reflect the electronic control system's regulatory impact on the vehicle's dynamic performance and providing a complete system topology for the subsequent generation of a dynamic link library.

[0066] Step S430 : Using a multidisciplinary collaborative code generation tool, the integrated electronic control system model and vehicle dynamics model are compiled into a dynamic link library file that can be called by Adams.

[0067] In step S430, the interfaced electronic control system and vehicle dynamics model are compiled into a dynamic link library (DLL) file that can be directly called from the Adams environment using multidisciplinary collaborative automatic code generation tools (such as Simulink Coder and Adams Mechatronics). This DLL encapsulates the complete system behavior logic and real-time interaction capabilities, allowing Adams to drive the entire co-simulation process within a single environment. Compared to traditional master-slave co-simulation methods, this approach significantly improves simulation stability, execution efficiency, and parameter configuration flexibility, achieving a truly integrated, platform-based co-simulation process.

[0068] In some embodiments of the present application, after the dynamic link library is integrated, the simulation process is dominated by Adams' GStiff solver.

[0069] After the dynamic link library integration is complete, the entire co-simulation process is led by the GStiff solver built into Adams. This design is significant: the GStiff solver is an algorithm developed by Adams specifically for optimizing multibody dynamics systems. It is particularly well-suited for handling highly nonlinear, multi-degree-of-freedom coupled dynamic models such as vehicles. Compared to traditional simulation methods that rely on general-purpose solvers like Simulink's ode45, using the GStiff solver more accurately captures the dynamic response of the vehicle system, improving simulation stability and computational efficiency.

[0070] Furthermore, because the electronic control system model has been encapsulated as a dynamic link library and implements interface mapping and data exchange with the Adams vehicle model, the electronic control system's control instructions can be applied to the dynamics subsystem in real time under the guidance of the GStiff solver, while simultaneously receiving feedback signals from the vehicle's status sensors to form a closed-loop control system. This integrated simulation architecture avoids numerical oscillations or divergence caused by inconsistent algorithms between different solvers, improving the reliability of the co-simulation.

[0071] More importantly, the entire simulation process runs entirely within the Adams environment, eliminating the need to switch to Simulink or other platforms. This significantly simplifies the workflow and improves engineers' work efficiency. This also provides a unified, efficient, and stable simulation platform for subsequent parameter adjustments, operating condition testing, and performance optimization, enabling faster and more accurate evaluation of the electronic control system's impact on vehicle dynamic performance.

[0072] In some embodiments of the present application, in step S140, the implementation process of encapsulating the dynamic link library file into an external system library and configuring editable key parameters includes but is not limited to the following steps.

[0073] Step S510 : Encapsulating the dynamic link library file into an external system library file through the Adams Mechatronics collaborative tool.

[0074] Among them, the external system library file includes the interactive interface information between the electronic control system model and the vehicle dynamics model.

[0075] In step S510, the dynamic link library (DLL) file generated in the previous stage is further encapsulated as an "external system library file" recognizable and callable within the Adams environment. Using the encapsulation tools provided by the Adams Mechatronics module, the interactive interface information, control logic, and data communication mechanisms between the electronic control system model and the vehicle dynamics model are integrated into this library file. This process embeds the electronic control system into the Adams simulation environment as a standalone functional module, maintaining its original control functionality while achieving seamless integration with the vehicle model, providing a unified technical platform for subsequent parameter configuration and co-simulation.

[0076] Step S520: Use a text editor to open the external system library file and configure key parameters.

[0077] Among them, key parameters are represented by independent fields, and direct modification of values ​​is supported.

[0078] In step S520, after the external system library is packaged, the flexibility and configurability of the library file are enhanced. Specifically, key control parameters in the electronic control system model (such as PID gains and control thresholds) and physical characteristic parameters in the vehicle dynamics model (such as mass, inertia, and tire stiffness) are defined as clearly structured, field-independent parameter items and stored in text format within the external system library file. This allows users to modify these parameters directly using a simple text editor (such as Notepad or XML editor) without entering a complex graphical modeling environment, enabling rapid iteration and optimization, effectively improving the convenience and efficiency of parameter adjustment.

[0079] Step S530 , verifying the compatibility of the configured key parameters with the simulation environment, so that the parameter format of the key parameters meets the Adams simulation requirements and can be correctly identified and called.

[0080] In step S530, after completing the textual configuration of key parameters, they need to be formatted and tested for compatibility to ensure that the units, data types, value ranges, etc. of all parameters comply with the technical specifications of Adams simulation and can be correctly parsed and called by the software. This step is usually completed automatically through Adams' built-in model checking tools or scripts. Only verified parameter configurations can ensure the stability and accuracy of subsequent simulation runs, avoiding model loading failures or abnormal simulation terminations due to parameter errors. This process provides a solid guarantee for the smooth execution of the entire joint simulation process.

[0081] In some embodiments of the present application, in step S150, an Adams simulation driven by an external system library is run according to the simulation test conditions, and the control effect of the vehicle electronic control system on the vehicle dynamic performance is verified according to the simulation results. The implementation process of completing the joint simulation includes but is not limited to the following steps.

[0082] Step S610 , running Adams simulation driven by an external system library according to the simulation test conditions, and collecting vehicle dynamic performance indicators.

[0083] Among them, the dynamic performance indicators include actual yaw rate, sideslip angle of the center of mass and braking torque output of each wheel.

[0084] In step S610, a full-vehicle dynamics simulation driven by an external system library is initiated within the Adams environment based on pre-defined test conditions (such as emergency lane changes and braking on low-adhesion surfaces). This external system library integrates the control logic and interactive interfaces of the electronic control system, enabling real-time response to vehicle state changes and output of control commands. During the simulation, the system collects key dynamic performance indicators, including actual yaw rate, sideslip angle, and braking torque output at each wheel. This data provides a foundation for subsequent evaluation of the electronic control system's control effectiveness.

[0085] Step S620 , analyzing the performance deviation between the vehicle dynamic performance index and the ideal index generated by the calculation module of the electronic control system model.

[0086] In step S620, after obtaining the actual simulation results, the collected vehicle dynamic performance indicators are compared item by item with the ideal target values ​​generated by the calculation module in the electronic control system model through comparative analysis. For example, the electronic control system may calculate the ideal yaw rate based on the current driving state and generate corresponding control instructions accordingly. Whether the actual vehicle response in the actual simulation is close to the ideal value is a key criterion for measuring control effectiveness. The purpose of this step is to quantify the actual performance of control behavior and identify problems such as response lag, insufficient control, or overshoot in the system, providing guidance for subsequent optimization.

[0087] Step S630, verifying the control effect of the vehicle electronic control system based on the performance deviation: if the performance deviation is less than the preset threshold, it is determined that the control effect of the vehicle electronic control system on the vehicle dynamic performance meets the standard; if the performance deviation exceeds the threshold, feedback is provided to optimize the key parameters in the external system library.

[0088] In step S630, by setting a reasonable performance deviation threshold (e.g., yaw rate error not exceeding ±5%), it is possible to determine whether the electronic control system meets design expectations under the current parameter configuration. If the deviations for each indicator are within the allowable range, the electronic control system is considered to have met the control requirements, and the joint simulation verification is complete. Conversely, if significant deviations exist, the issue is fed back to the parameter configuration stage, and key control parameters in the external system library (such as PID coefficients, control gains, and response time constants) are adjusted and optimized to improve control accuracy and system stability.

[0089] Step S640, repeat the above simulation and verification steps until the control effect meets the requirements and the joint simulation is completed.

[0090] In step S640, because the control performance of the electronic control system is often influenced by the synergy of multiple parameters, a single simulation cannot achieve optimal results. Therefore, multiple iterations of simulation and parameter optimization are required to approximate the ideal control state. This step continuously improves key parameters in the external system library by looping through steps S610 to S630 until all dynamic performance indicators meet preset requirements. This closed-loop optimization mechanism not only improves the design quality of the electronic control system but also ensures the integrity and practicality of the joint simulation process, ultimately achieving comprehensive verification and effective evaluation of the control capabilities of the vehicle's electronic control system.

[0091] In some embodiments of this application, taking the joint simulation verification of the electronic stability system (ESP) as an example, the specific steps for integrating the ESP electronic control model into the Adams vehicle model are as follows. However, it should be understood that this method is applicable to any type of electronic control system.

[0092] First, an ESP control model was built in the Simulink environment. It consists of three core modules: a reference value module for calculating the ideal yaw rate and sideslip angle, an adjustment module that uses a fuzzy PID algorithm to optimize braking torque output, and an actuator allocation module that distributes the total braking torque to each wheel. To improve the efficiency of subsequent parameter tuning, key model parameters (such as the membership function parameters of the fuzzy rules and PID gains) are individually encapsulated using "Constant" or "Gain" modules, forming a flexible parameterized data structure. Finally, the constructed control model is saved as a ".slx" file (e.g., ESP_Control_Model.slx), which serves as the basis for subsequent integration with the Adams model.

[0093] Secondly, the vehicle dynamics model was customized within the Adams / Car environment to support interaction with the ESP control system. The basic vehicle model consists of multiple subsystems, including the front and rear suspension systems, steering system, powertrain system, body system, tire system, braking system, and control system. To meet control requirements, a PointTorque excitation was added to the braking system template to serve as the braking torque execution interface for the ESP controller output. Transducer Signal sensor interfaces were also set up in the steering and body systems to collect vehicle status information such as steering wheel angle, vehicle speed, yaw rate, and sideslip angle.

[0094] Furthermore, using the "Control System – New" function in the Adams Mechatronics module, a control strategy template with four inputs (corresponding to the four sensor signals) and four outputs (corresponding to the four wheel braking torques) was created. The signal units were correctly matched (for example, degrees for angle and N·m for torque), achieving a one-to-one mapping between sensor signals and input interfaces, and between excitation signals and output interfaces. Finally, the control system was packaged as a subsystem and integrated with other subsystems to form a complete Adams vehicle assembly (for example, Vehicle_for_ESP_Control).

[0095] Furthermore, using the multidisciplinary collaborative toolchain of Adams and Simulink, the ESP control model was integrated with the Adams vehicle control system and compiled into a dynamic link library file. First, in Adams, the control strategy of the control system template was exported as a .m file using the "Tools - Export Plant" function. This script was then run to load the required system variables (such as input and output interface definitions) into the MATLAB workspace.

[0096] Then, execute the "setup_rtw_for_adams" command in the MATLAB command line to load the Adams compiler and the "setio" command to launch the Simulink interface. Simulink automatically generates input and output modules corresponding to the Adams model. These modules are then connected to the corresponding interfaces of the ESP control model (.slx file) to complete the embedding of the control logic. Next, use the Simulink Coder tool, select "rsim.tlc" as the target file (for generating real-time simulation code), and compile the entire integrated model into a dynamic link library file with the suffix ".dll" (e.g., ESP_Adams_Interface.dll), achieving deep integration and efficient interaction between the electronic control system and the vehicle dynamics model.

[0097] The generated dynamic link library file is then further packaged into an external system library recognizable by Adams, allowing for co-simulation and verification. Using the "Tools - ESL PropertyFile" function in the Adams Mechatronics module, the ".dll" file is packaged into an external system library file in ".esl" format (e.g., ESP_External_System.esl), which contains complete interface information and editable key parameter fields. This external system library can be directly called from the Adams environment. Users can also open the .esl file in a text editor such as Notepad to easily modify key parameters such as fuzzy control rules, PID gains, and vehicle mass, enabling rapid iteration without remodeling.

[0098] After packaging, the external system library is loaded into Adams and simulation tests are run (e.g., double lane change conditions and emergency braking on low-adhesion surfaces). The ESP system's control effectiveness is evaluated by comparing the deviations between actual response metrics such as yaw rate and sideslip angle and ideal target values. If the performance deviation exceeds a preset threshold, the parameters in the .esl file are adjusted and the simulation process is repeated until all performance metrics meet design requirements, thus completing the comprehensive verification and optimization of the electronic control system's control capabilities.

[0099] In summary, the joint simulation method of the vehicle electronic control system provided in the embodiment of the present application has the following technical effects.

[0100] This method integrates the electronic control system model in Simulink with the vehicle dynamics model in Adams and utilizes the built-in GStiff solver in Adams for simulation, avoiding model instability issues often encountered in traditional methods due to incompatibility between different solvers (such as Simulink's ode45). Dynamic link library files are generated and encapsulated as external system libraries, allowing the entire simulation process to be completed within a single Adams environment, eliminating the need for frequent switching between multiple software platforms. Furthermore, key parameters are designed to be independently editable, allowing users to quickly adjust parameter values ​​based on actual needs without recompiling the entire model, significantly simplifying the process and improving efficiency. This method also implements "electronic-mechanical" closed-loop control. By establishing detailed interface mappings, the electronic control system can respond to real-world vehicle conditions and drive the corresponding actuators, thereby enhancing simulation realism and system interoperability.

[0101] Furthermore, this method supports multidisciplinary collaborative simulation, leveraging a multidisciplinary collaborative toolchain to deeply integrate the electronic control system model with the vehicle dynamics model. This approach is suitable for seamlessly integrating various types of electronic control systems (such as ESP, ABS, etc.) with the entire vehicle model. Through multiple iterations of simulation and parameter optimization, the ideal control state is approached, ensuring that the electronic control system effectively controls the vehicle's dynamic performance. Simulation results not only verify the rationality of the control strategy but also provide an important reference for actual vehicle design, helping engineers identify potential issues and implement improvements. The entire co-simulation process is completed on a unified platform, reducing the complexity and uncertainty associated with the coordinated operation of multiple software programs. Furthermore, by setting reasonable performance deviation thresholds, it is possible to accurately determine whether the electronic control system's control performance meets the requirements, further enhancing the practicality and reliability of the simulation platform. This innovative approach provides strong support for modern vehicle design, especially the development of chassis electronic control systems.

[0102] Secondly, refer to Figure 2 The present invention provides a joint simulation device for a vehicle electronic control system, including: The basic data acquisition module 710 is used to acquire basic data of the electronic control system model and the vehicle dynamics model, as well as simulation test conditions. The electronic control system model is a control model built in the Simulink environment, and the vehicle dynamics model is a full vehicle model built in the Adams environment.

[0103] The interface mapping module 720 is used to establish an interface mapping relationship for the joint simulation based on the basic data, wherein the interface mapping relationship includes the input interface of the vehicle state signal in the vehicle dynamics model and the output interface of the output signal of the electronic control system model.

[0104] The model integration module 730 is used to integrate the electronic control system model with the vehicle dynamics model through a multidisciplinary collaborative tool chain to generate an interactive dynamic link library file. The dynamic link library file is used to achieve real-time interaction between the vehicle dynamics model and the electronic control system model.

[0105] The external encapsulation module 740 is used to connect the input and output interfaces of the electronic control system model and the vehicle dynamics model in the Simulink environment, so that the vehicle state signal of the vehicle dynamics model is input to the electronic control system model, and the braking torque command of the electronic control system model is output to the actuator interface of the vehicle dynamics model.

[0106] The joint simulation module 750 is used to run the Adams simulation driven by the external system library according to the simulation test conditions, verify the control effect of the vehicle electronic control system on the vehicle dynamic performance according to the simulation results, and complete the joint simulation.

[0107] Furthermore, refer to Figure 3An embodiment of the present application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the aforementioned joint simulation method of the vehicle electronic control system.

[0108] In addition, an embodiment of the present application provides a vehicle, which performs co-simulation on parameters of a vehicle chassis electronic control system through the aforementioned co-simulation method of a vehicle electronic control system.

[0109] Similarly, the contents of the above method embodiments are applicable to device embodiments, equipment embodiments and vehicle embodiments. The functions specifically implemented by the device embodiments, equipment embodiments and vehicle embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0110] In some optional embodiments, the functions / operations mentioned in the block diagram may not occur in the order mentioned in the operation schematic diagram. For example, depending on the functions / operations involved, the two boxes shown in succession may actually be executed substantially simultaneously or the boxes can sometimes be executed in reverse order. In addition, the embodiments presented and described in the flow chart of the present application are provided in an exemplary manner for the purpose of providing a more comprehensive understanding of the technology. The disclosed method is not limited to the operations and logical flows presented herein. Optional embodiments are contemplated in which the order of the various operations is changed and the sub-operations described as a part of a larger operation are performed independently.

[0111] In addition, although the present application is described in the context of functional modules, it should be understood that, unless otherwise stated, one or more of the functions and / or features may be integrated into a single physical device and / or software module, or one or more functions and / or features may be implemented in separate physical devices or software modules. It is also understood that a detailed discussion of the actual implementation of each module is not necessary for understanding the present application. More specifically, given the properties, functions, and internal relationships of the various functional modules in the devices disclosed herein, the actual implementation of the module will be understood within the routine skills of an engineer. Therefore, a person skilled in the art will be able to implement the present application as set forth in the claims using ordinary techniques. It is also understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present application, which is determined by the full scope of the appended claims and their equivalents.

[0112] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or the portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several programs that enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the various embodiments of the method of the present invention. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0113] The logic and / or steps represented in a flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable programs for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, a program execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can retrieve and execute a program from a program execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, a program execution system, apparatus, or device.

[0114] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting, or processing it in a suitable manner as necessary, and then storing it in a computer memory.

[0115] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable program execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having logic gate circuits for implementing logic functions on data signals, an application-specific integrated circuit having suitable combinational logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0116] In the above description of this specification, reference to the terms "one embodiment / implementation," "another embodiment / implementation," or "certain embodiments / implementations" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in the embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0117] Although the embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the claims and their equivalents.

[0118] The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the embodiments. Those skilled in the art can make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of the present invention.

Claims

1. A joint simulation method for a vehicle electronic control system, characterized in that: The following steps are involved: Obtain basic data of the electronic control system model and the vehicle dynamics model, as well as simulation test conditions; wherein the electronic control system model is a control model built in the Simulink environment, and the vehicle dynamics model is a full vehicle model built in the Adams environment; Based on the basic data, an interface mapping relationship of the joint simulation is established; wherein the interface mapping relationship includes an input interface of the vehicle state signal in the vehicle dynamics model and an output interface of the output signal of the electronic control system model; Integrating the electronic control system model with the vehicle dynamics model through a multidisciplinary collaborative tool chain to generate an interactive dynamic link library file; wherein the dynamic link library file is used to achieve real-time interaction between the vehicle dynamics model and the electronic control system model; Encapsulating the dynamic link library file into an external system library and configuring editable key parameters; wherein the key parameters include control algorithm parameters of the electronic control system model and physical characteristic parameters of the vehicle dynamics model; According to the simulation test conditions, the Adams simulation driven by the external system library is run, and the control effect of the vehicle electronic control system on the vehicle dynamic performance is verified based on the simulation results to complete the joint simulation.

2. The joint simulation method of the vehicle electronic control system according to claim 1, characterized in that: The method of obtaining basic data of the electronic control system model includes the following steps: Based on the target electronic control system type, the electronic control system model is constructed using the Simulink simulation environment, and the control algorithm parameters in the electronic control system model are represented by independent editable modules to form parameterizable data. The electronic control system model includes a calculation module, an adjustment module, and a distribution module. The calculation module is used to calculate the ideal vehicle motion parameters; the adjustment module is used to optimize the control output; and the distribution module is used to distribute actuator signals. The constructed electric control system model is saved as a standard format file supporting Adams integration as basic data of the electric control system model.

3. The joint simulation method of the vehicle electronic control system according to claim 1, characterized in that: The method of obtaining basic data of the vehicle dynamics model includes the following steps: Determine the basic subsystems of the vehicle dynamics model based on the target vehicle type using the Adams simulation environment; wherein the basic subsystems include the suspension system, steering system, powertrain system, body system, and tire system; An interactive interface is configured in the basic subsystem, an execution interface for braking torque is set in the braking system, and a sensor signal interface is set in the steering system and the body system; the execution interface is used to receive the braking torque output by the electronic control system; and the sensor signal interface is used to obtain the vehicle status signal; The configured basic subsystems are integrated into a complete Adams vehicle dynamics model as the basic data of the vehicle dynamics model.

4. The joint simulation method of the vehicle electronic control system according to claim 1, characterized in that: The step of integrating the electronic control system model with the vehicle dynamics model through a multidisciplinary collaborative tool chain to generate an interactive dynamic link library file includes the following steps: Exporting the control strategy parameters of the vehicle dynamics model through the Adams collaborative tool and loading them into the compilation environment; wherein the control strategy parameters include signal type and unit information of the input and output interfaces; Connecting the input and output interfaces of the electronic control system model and the vehicle dynamics model in a Simulink environment so that the vehicle state signal of the vehicle dynamics model is input to the electronic control system model and the braking torque command of the electronic control system model is output to the actuator interface of the vehicle dynamics model; The integrated electronic control system model and the vehicle dynamics model are compiled into the dynamic link library file that can be called by Adams using a multidisciplinary collaborative code generation tool.

5. The joint simulation method of the vehicle electronic control system according to claim 4, characterized in that: After the dynamic link library is integrated, the simulation process is dominated by Adams' GStiff solver.

6. The joint simulation method of the vehicle electronic control system according to claim 1, characterized in that: The method of encapsulating the dynamic link library file into an external system library and configuring editable key parameters includes the following steps: Encapsulating the dynamic link library file into the external system library file using the Adams Mechatronics collaborative tool; wherein the external system library file includes interactive interface information between the electronic control system model and the vehicle dynamics model; Use a text editor to open the external system library file and configure the key parameters; the key parameters are represented by independent fields and support direct modification of values; Verify the compatibility of the configured key parameters with the simulation environment, so that the parameter format of the key parameters meets the Adams simulation requirements and can be correctly identified and called.

7. The joint simulation method of the vehicle electronic control system according to claim 1, characterized in that: According to the simulation test conditions, running the Adams simulation driven by the external system library, verifying the control effect of the vehicle electronic control system on the vehicle dynamic performance according to the simulation results, and completing the joint simulation, including the following steps: According to the simulation test conditions, running the Adams simulation driven by the external system library to collect vehicle dynamic performance indicators; wherein the dynamic performance indicators include actual yaw rate, center of mass sideslip angle, and braking torque output of each wheel; analyzing a performance deviation between the vehicle dynamic performance index and an ideal index generated by a calculation module of the electronic control system model; verifying the control effect of the vehicle electronic control system based on the performance deviation: if the performance deviation is less than a preset threshold, determining that the control effect of the vehicle electronic control system on the vehicle dynamic performance meets the standard; if the performance deviation exceeds the threshold, feedback optimization of key parameters in the external system library; Repeat the above simulation and verification steps until the control effect meets the requirements and the joint simulation is completed.

8. A joint simulation device for a vehicle electronic control system, characterized in that: include: A basic data acquisition module is used to obtain basic data of the electronic control system model and the vehicle dynamics model, as well as simulation test conditions; wherein the electronic control system model is a control model built in the Simulink environment, and the vehicle dynamics model is a full vehicle model built in the Adams environment; An interface mapping module, configured to establish an interface mapping relationship for the joint simulation based on the basic data; wherein the interface mapping relationship includes an input interface for a vehicle state signal in the vehicle dynamics model and an output interface for an output signal of the electronic control system model; a model integration module, configured to integrate the electronic control system model with the vehicle dynamics model through a multidisciplinary collaborative tool chain to generate an interactive dynamic link library file; wherein the dynamic link library file is configured to enable real-time interaction between the vehicle dynamics model and the electronic control system model; an external packaging module, configured to connect the input and output interfaces of the electronic control system model and the vehicle dynamics model in a Simulink environment, such that the vehicle state signal of the vehicle dynamics model is input to the electronic control system model, and the braking torque command of the electronic control system model is output to the actuator interface of the vehicle dynamics model; The joint simulation module is used to run the Adams simulation driven by the external system library according to the simulation test conditions, verify the control effect of the vehicle electronic control system on the vehicle dynamic performance according to the simulation results, and complete the joint simulation.

9. An electronic device, characterized in that: The electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the joint simulation method of the vehicle electronic control system according to any one of claims 1 to 7 when executing the computer program.

10. A vehicle, characterized in that: The vehicle performs joint simulation on parameters of the vehicle chassis electronic control system through the joint simulation method of the vehicle electronic control system according to any one of claims 1 to 7.

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