A multi-disciplinary linkage-based electric vehicle virtual simulation system and testing method

Abstract

The application discloses a kind of based on multidisciplinary linkage electric vehicle virtual simulation system and test method, wherein the method comprises: constructing multidisciplinary joint simulation environment;The closed loop simulation of the automatic driving algorithm to be measured is executed;Vehicle dynamics response simulation;Vehicle subsystem simulation and feedback;Scene construction and test execution;Test result output and evaluation.The application integrates multidisciplinary commercial simulation software, constructs the multidisciplinary joint simulation platform of scene generation, sensor simulation, vehicle control system and electromechanical system, to realize key test scene construction, multi-class sensor data simulation, core control module modeling and high-fidelity simulation of key components such as battery, motor and thermal management, to provide complete solution for the research and development of electric vehicle and intelligent driving technology, meet the comprehensive demand of multidisciplinary fine simulation for new energy vehicles and intelligent driving system.

Description

Technical Field

[0001] This invention relates to the field of vehicle virtual simulation technology, and more specifically to a virtual simulation system and testing method for electric vehicles based on multidisciplinary collaboration. Background Technology

[0002] Vehicle virtual simulation refers to the process of simulating and testing vehicle performance, behavior, and systems in a virtual environment using computer technology and mathematical modeling. By establishing digital models and combining them with physical laws, environmental factors, and control algorithms, it is possible to analyze a vehicle's dynamic response, handling stability, energy consumption, and safety performance under different operating conditions.

[0003] At the functional level, a complete vehicle virtual simulation should at least include several core modules such as traffic scene generation and sensor simulation, vehicle dynamics modeling, vehicle control logic modeling, and electromechanical component modeling. Existing software typically excels in one aspect while lagging behind in others. To compensate for the shortcomings of single software, the industry has gradually developed simulation architectures that combine multiple software programs.

[0004] Currently, common co-simulation architectures include MATLAB / Simulink, Ansys Simplorer (TwinBuilder), CANoe, Ansys Maxwell, PanoSIM, and IPG CarMaker. Among them: MATLAB / Simulink can achieve interdisciplinary collaboration to a certain extent, but still relies on third-party integration for dynamics and traffic scenarios; Simplorer mainly focuses on modeling electric drive and electrical systems, and lacks functionality in traffic environment and autonomous driving verification; CANoe has long been used for in-vehicle network communication and ECU functional testing, and although it can couple with other platforms, it is not suitable for dynamics and electromechanical simulation tasks; Maxwell has high accuracy in electromagnetic performance simulation, but is limited to the component level and lacks system-level integration capabilities; PanoSIM is one of the earliest multi-software co-simulation platforms proposed in China, capable of integration at the traffic scenario and vehicle dynamics levels, but it is insufficient in high-fidelity modeling of key components and complex control systems of electric vehicles, relying on external interface expansion; CarMaker is an internationally widely used vehicle-level simulation platform with a rich scene library and sensor models, especially suitable for autonomous driving and ADAS verification, but it is still weak in high-precision modeling of key new energy components such as batteries, motors, and thermal management, and the modeling of control logic also relies on tools such as Simulink. Therefore, existing software or joint platforms are insufficient in terms of functional coverage, interface compatibility, and joint simulation stability, making it difficult to simultaneously meet the comprehensive needs of new energy vehicles and intelligent driving systems for multidisciplinary and refined simulation. Summary of the Invention

[0005] The present invention provides a high-precision, scalable virtual simulation system and testing method for electric vehicles based on multidisciplinary collaboration, which can solve at least one of the above-mentioned technical problems.

[0006] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:

[0007] A virtual simulation system for electric vehicles based on multidisciplinary collaboration includes:

[0008] The scenario construction and simulation model is used to generate simulation scenarios based on preset test requirements, adapt to different test requirements, and receive simulation scenario element editing signals to modify the simulation scenario according to test requirements. The vehicle performs real-time response and control simulation in the simulation scenario.

[0009] The vehicle dynamics simulation model is used to simulate the longitudinal, lateral and vertical dynamic responses of a vehicle. The input of the vehicle dynamics simulation model is historical and current vehicle position information, vehicle attitude information and vehicle dynamic information, and the output is the vehicle position information, vehicle attitude information and vehicle dynamic information at the next moment.

[0010] The vehicle dynamics parameter analysis model is used to analyze, transform, and visualize the data output by the vehicle dynamics simulation model in order to extract key dynamic parameters. The analysis process includes data format decoding, unit conversion, and time synchronization processing.

[0011] The vehicle controller simulation model is used to receive and process the data output by the vehicle dynamics parameter analysis model, including the driver model, the vehicle control unit (VCU) model, the electronic stability program (ESP) model, and the battery management system (BMS) model.

[0012] Vehicle component simulation models are used to perform joint simulations of motors, batteries, and thermal systems to support high-precision modeling of the energy flow and thermal behavior of the entire vehicle, including motor models, battery models, and thermal management models.

[0013] The data transmission interface model is used to realize communication and data interaction between systems.

[0014] Furthermore, the scenario construction and simulation model includes multiple sub-modules, which are used to automatically generate different road types and environmental conditions to support the construction of various related typical test environments such as urban roads, highways and test fields.

[0015] Furthermore, in the vehicle controller simulation model:

[0016] The driver model is used to generate a feasible driving trajectory for the vehicle based on a preset trajectory reference point.

[0017] The vehicle control unit (VCU) model is used to coordinate the overall operation of the motor, braking and energy management system.

[0018] The ESP model is used to achieve vehicle attitude stability and anti-skid control based on the vehicle's position and posture information.

[0019] The battery management system (BMS) model is used to calculate battery heating / cooling requests based on battery temperature, and to calculate battery output power based on battery temperature, current, and state of charge.

[0020] Furthermore, in the data transmission interface model, communication interaction is used to realize data transmission and synchronization between computers with different addresses, and interface interaction is used to construct functional simulation unit (FMU) and other types of interfaces.

[0021] Furthermore, the scenario construction and simulation model, the vehicle dynamics simulation model, the vehicle dynamics parameter analysis model, the vehicle controller simulation model, and the vehicle component simulation model interact with each other through the data transmission interface model. The data transmission adopts the functional simulation unit (FMU) standard interface and UDP / TCP communication protocol for structured encapsulation and real-time transmission.

[0022] A virtual simulation testing method for electric vehicles based on multidisciplinary collaboration, employing the aforementioned virtual simulation system for electric vehicles, includes the following steps:

[0023] S1. Construct a multidisciplinary joint simulation environment: Based on VTD, construct and simulate scenarios to generate dynamic virtual test scenarios; based on CarSim, construct a high-precision electric vehicle dynamics model to realize the real motion response simulation of electric vehicles under control commands; based on AMESim, construct vehicle subsystems to realize high-precision state simulation of vehicles under different working conditions; based on Simulink as an algorithm development and system integration platform, integrate autonomous driving decision-making algorithms, vehicle control models and communication interface modules.

[0024] S2. Closed-loop simulation of the autonomous driving algorithm under test: Simulink receives environmental perception data and sensor information output by VTD and inputs them into the autonomous driving algorithm under test. The algorithm outputs longitudinal and lateral control commands for the vehicle.

[0025] S3. Vehicle Dynamics Response Simulation: The control commands of the autonomous driving algorithm are parsed by Simulink and transmitted to CarSim. CarSim simulates the vehicle dynamics state at the current moment based on the vehicle attitude, environmental information and vehicle subsystem parameters of the previous moment, and outputs the vehicle dynamics parameters.

[0026] S4. Vehicle Subsystem Simulation and Feedback: An electric vehicle controller module is integrated into Simulink to analyze the vehicle dynamics parameters output by CarSim and the battery / motor / thermal management parameters output by AMESim. The vehicle system control commands and subsystem state parameters are calculated. Simultaneously, Simulink encodes the updated vehicle state and vehicle controller output according to a preset communication protocol and sends them to CarSim, AMESim and VTD to influence the environmental update, vehicle dynamics and vehicle subsystem response in the next time step.

[0027] S5. Scenario Construction and Test Execution: Based on the test requirements, construct test scenarios in VTD, set boundary conditions according to the test requirements, configure initial vehicle parameters, road conditions, interference events and traffic information, and execute closed-loop tests.

[0028] S6. Test Result Output and Evaluation: Based on the vehicle attitude, dynamic response and subsystem state information output by CarSim, AMESim and Simulink, evaluate the performance of the electric vehicle and determine whether the vehicle system performance meets the preset standards based on the simulation data.

[0029] Furthermore, in S1, the simulation system and simulation testing method support joint simulation on multiple platforms including MATLAB, Simulink, CarSim, VTD and AMESim, and the platforms achieve time synchronization and signal consistency through data transmission interfaces.

[0030] Furthermore, in S2, the VTD and the Simulink interact with each other via Real-Time Industrial Communication (RTI) or Socket Communication (Socket). The VTD outputs environmental perception data and sensor information to the Simulink, including at least lane line position, obstacle information, camera image, LiDAR point cloud, and vehicle Z-axis attitude.

[0031] Furthermore, in S3, CarSim supports the customization of the parameters of the vehicle dynamics of electric vehicles to adapt to the simulation needs of different vehicle types, suspension structures, tire models and vehicle operating conditions.

[0032] In S4, AMESim supports the customization of related subsystems of electric vehicles, such as batteries, motors, and thermal management, to meet the simulation requirements of different vehicle types, battery models, motor models, and vehicle operating conditions.

[0033] Furthermore, in S3, during the Simulink vehicle subsystem simulation, the following control strategy is adopted:

[0034] The vehicle control unit (VCU) model calculates the driving torque in the forward state by looking up the corresponding value in a two-dimensional interpolation table based on the current vehicle speed and accelerator pedal opening.

[0035] By combining battery torque limits and motor torque limits, the output torque is constrained, and the target torque required by the motor is finally generated. Then, the motor's limiting torque is obtained by looking up a table using the positive voltage and motor speed.

[0036] Based on the positive electrode voltage, battery output power and load current, calculate the peak discharge power and load power. The difference between the two is used to determine the motor's limiting power. Then, by combining the motor speed and the limiting power, look up the table to obtain the battery's limiting torque, and then calculate the vehicle's drive command.

[0037] The Electronic Stability Program (ESP) model performs stability control and outputs braking correction signals based on vehicle dynamic parameters.

[0038] The Battery Management System (BMS) model outputs battery state of charge, battery health status, and thermal management parameters based on the vehicle battery's voltage, current, and temperature parameters.

[0039] The beneficial effects of this invention are reflected in:

[0040] 1. Construct a multi-disciplinary integrated joint simulation platform with more comprehensive disciplinary coverage.

[0041] This invention integrates multiple professional software such as VTD, Simulink, CarSim, and Amesim to achieve full-chain coverage from traffic scene generation, sensor simulation, vehicle dynamics modeling to control system and electromechanical component modeling, and establishes a unified simulation platform for multidisciplinary collaboration, which is used for the full-process verification of electric vehicles and intelligent driving systems.

[0042] 2. Improve interface compatibility and data interaction capabilities.

[0043] This invention designs a universal interface and an efficient data mapping method to solve the differences in data format, coordinate system transformation and communication between different software, ensuring that the data of sensors, dynamic parameters, control logic and electromechanical component models can interact smoothly, and improving the openness and scalability of the system.

[0044] 3. Ensure the accuracy and stability of joint simulation to serve new energy and intelligent driving applications.

[0045] This invention proposes a joint simulation solution method based on delay decoupling and optimized scheduling, which eliminates instability caused by algebraic loops and ensures convergence of multidisciplinary coupled computation and simulation efficiency. At the same time, it integrates key models such as BMS, VCU, ESP, motor, and thermal management system, which not only supports traffic scenario and multi-sensor simulation, but also deeply couples with vehicle control system and electromechanical component models to achieve high-fidelity simulation results, providing an overall solution for new energy vehicles and intelligent driving applications. Attached Figure Description

[0046] The accompanying drawings, which are provided to further illustrate this application and form part of this application, illustrate exemplary embodiments of this application and are used to explain this application, but do not constitute an undue limitation of this application.

[0047] Figure 1 This is a schematic diagram of the overall structure of an embodiment of the present invention.

[0048] Figure 2 This is a schematic diagram of the vehicle handling stability test operation process according to an embodiment of the present invention.

[0049] Figure 3 This is a schematic diagram of the vehicle dynamics test operation process according to an embodiment of the present invention.

[0050] Figure 4 This is a rendering of a serpentine test road scene according to an embodiment of the present invention.

[0051] Figure 5 This is a test result diagram of the simulation test platform according to an embodiment of the present invention.

[0052] Figure 6 This is a graph showing the snake-like test index values ​​output by the simulation test platform in this embodiment of the invention.

[0053] Figure 7 This is a schematic diagram of a road scene with serpentine test markers placed according to an embodiment of the present invention.

[0054] Figure 8 This is a schematic diagram of a road scene with double lane shift test markers according to an embodiment of the present invention.

[0055] Figure 9 This is a schematic diagram of a circular test track road scene according to an embodiment of the present invention.

[0056] Figure 10 This is a structural block diagram of a computer device according to an embodiment of the present invention. Detailed Implementation

[0057] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Unless otherwise specified, the embodiments and features in the embodiments of this application can be combined with each other. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0058] The main technical terms used in this invention are explained below:

[0059] VTD: Virtual Test Drive, is an autonomous driving and intelligent driving simulation testing platform developed by the German company VIRES and now part of Hexagon's industrial software ecosystem. This software focuses on modeling and simulating complex traffic environments, covering the entire process from road network design and dynamic scenario configuration to multi-sensor simulation. It supports testing and verification of autonomous driving systems across all stages of the V-process, including Model-in-the-Loop (MiL), Software-in-the-Loop (SiL), Hardware-in-the-Loop (HiL), Driver-in-the-Loop (DiL), and Vehicle-in-the-Loop (ViL).

[0060] Simulink is a visual simulation tool within MATLAB, developed by MathWorks. This software provides a modular environment for multi-domain simulation and model-based design, supporting system design, simulation, automatic code generation, and continuous testing and verification of embedded systems.

[0061] AMESim: Originally developed by the French company Imagine, it aims to control complex dynamic systems by coupling hydraulic servo actuators with finite element mechanical structures. This software is an advanced modeling and simulation platform for engineering systems. Its modeling method is based on power bond graphs, which, compared to bond graphs, offer an intuitive graphical interface, enabling schematic-oriented modeling. Throughout the simulation process, the simulation system is presented through this intuitive graphical interface.

[0062] CarSim is a professional vehicle dynamics simulation software primarily used to simulate and analyze vehicle motion and control. It is widely applied in automotive R&D, control system development, and performance evaluation. This software can simulate a vehicle's response to driver, road surface, and aerodynamic inputs, mainly used to predict and simulate the vehicle's handling stability, braking performance, ride comfort, power, and fuel economy. It is also widely used in the development of modern automotive control systems.

[0063] This invention provides a virtual simulation system for electric vehicles based on multidisciplinary collaboration, used for rapid verification of electric vehicle control strategies, energy management optimization, and safety verification experiments. Specifically, this simulation system includes:

[0064] The scenario construction and simulation model can be implemented based on the VTD platform. It is used to generate simulation scenarios according to preset test requirements, adapt to different test requirements, receive scenario element editing signals, modify the scenario according to test requirements, and the vehicle performs real-time response and control simulation in the simulation scenario.

[0065] The vehicle dynamics simulation model, which can be implemented based on the CarSim platform, is used to simulate the longitudinal, lateral and vertical dynamic responses of a vehicle. The input of the vehicle dynamics simulation model is historical and current vehicle position information, vehicle attitude information and vehicle dynamic information, and the output is the vehicle position information, vehicle attitude information and vehicle dynamic information at the next moment.

[0066] The vehicle dynamics parameter analysis model is used to analyze, transform, and visualize the data output by the vehicle dynamics simulation model in order to extract key dynamic parameters. The analysis process includes data format decoding, unit conversion, and time synchronization processing.

[0067] The vehicle controller simulation model, which can be implemented based on the Simulink platform, is used to receive and process the data output by the vehicle dynamics parameter analysis model, including the driver model, the vehicle control unit (VCU) model, the electronic stability program (ESP) model, and the battery management system (BMS) model.

[0068] The vehicle component simulation model, which can be implemented based on the AMESim platform, is used to perform joint simulation of the motor, battery and thermal system to support high-precision modeling of the energy flow and thermal behavior of the whole vehicle, including motor model, battery model and thermal management model;

[0069] The data transmission interface model is used to realize communication and data interaction between systems.

[0070] This simulation system architecture is a simulation environment built on multiple commercial simulation software. It constructs and integrates model resources such as general motor model, general battery model, general thermal management model, VCU model, ESP model and BMS model. It can carry out joint simulation based on commercial simulation software including VTD, CarSim, AMESim and Simulink to support point tool joint simulation verification based on handling stability and dynamics.

[0071] In this embodiment, the scenario construction and simulation model provides road information for the vehicle dynamics simulation model and the driver model. It includes multiple sub-modules, which automatically generate different road types and environmental conditions to support the construction of various typical test environments, including urban roads, highways, and test tracks. The core task of the scenario construction and simulation model (or VTD platform) is to construct the scenarios required for simulation testing, including road alignment, scene environment, weather conditions, traffic facilities and equipment, and to visualize vehicle pose information. The scenario construction and simulation model supports the construction of test scenarios conforming to national standards through slalom or other operational methods, such as:

[0072] (1) Serpentine test: A three-lane test road with a width of 3.75 meters is set up, and cone markers are set up in accordance with the specifications. The markers are placed as follows: Figure 7 As shown. Note that the markers in this scene are automatically placed by the "Stake Placement Module" in Simulink, but the corresponding markers need to be pre-placed in the scene file, and their initial positions can be set on the outside of the lane.

[0073] (2) Double lane change test: A three-lane test road with a width of 3.5 meters is set up. Conical markers are set up in the test area according to the specifications. The markers are placed as follows: Figure 8 As shown. Unlike the serpentine test scenario, the marker positions in this scenario are fixed and can be directly stored in the scenario file.

[0074] (3) 30-minute maximum speed test: A circular test track will be used, with a one-way loop lane layout. There will be no less than four graded test lanes. The speed limit of each lane will increase from the inside to the outside. The lane height in the curve area will also increase from the inside to the outside. The specific track structure is as follows: Figure 9 As shown.

[0075] (4) Maximum speed and acceleration test: A 10km straight test road with no elevation change is used, and no markers are required.

[0076] In this embodiment, the core task of the vehicle dynamics simulation model (or CarSim platform) is to simulate and analyze the dynamic response of the vehicle under different operating conditions, including acceleration, braking, steering, and suspension behavior. Specifically, when Simulink and CarSim are used for joint simulation, CarSim, as the dynamics model, requires inputs regarding vehicle handling (steering wheel, accelerator, brakes, etc.), vehicle state (four-wheel z-axis information), and road condition-related information (friction coefficient). Through mathematical model calculations, it can output vehicle state information (vehicle coordinates, pose, acceleration, engine speed, etc.).

[0077] In this embodiment, in the vehicle controller simulation model:

[0078] (1) The driver model is used to generate a feasible driving trajectory of the vehicle based on a preset trajectory reference point, and to provide driving control strategies for the vehicle dynamics simulation model and the vehicle control unit (VCU) model.

[0079] The driver model mainly consists of two modules: lateral control and longitudinal control. These two modules are independent of each other and do not interfere with each other.

[0080] (1.1) Horizontal control module

[0081] The standard lateral control module consists of three main parts: the FMU component, the Stanley lateral control subsystem, and the vehicle orientation change function. The functions of each component are described below:

[0082] FMU Component: This component is associated with an external FMU file. Its main function is to calculate the positional and heading errors between the vehicle and the expected trajectory based on the vehicle's current position, speed, and yaw angle. In handling stability tests, the expected trajectory is dynamically generated based on the road centerline and stake positions; in dynamic tests, the expected trajectory is embedded in the FMU as a static trajectory. To change the expected trajectory, use a decompression tool such as 7-Zip to open the corresponding FMU file and replace the data.txt file in the resources folder. Furthermore, double-clicking the FMU component in Simulink allows you to view its control parameters. Taking the serpentine test as an example, the parameters include simulation step size, delta, and k; the latter two parameters are used to adjust the vehicle's slalom amplitude.

[0083] Stanley's lateral control subsystem calculates the corresponding steering wheel angle based on the pose error output by the FMU, combined with the vehicle's current speed and attitude. This subsystem requires external parameters, primarily for heading control-related calculations. Internally, the subsystem contains several adjustable gain parameters used to adjust the vehicle's steering sensitivity.

[0084] Lane change control component: Based on the vehicle's current lane and speed, it controls whether the vehicle changes lanes to the outer lane with a higher speed limit according to the set logic.

[0085] Vehicle orientation conversion: Since the heading angle in CarSim is defined as 0 degrees due east and counterclockwise as the positive direction, while the lateral control algorithm uses 0 degrees due north and clockwise as the positive direction, it is necessary to convert the vehicle yaw angle output by CarSim to ensure coordinate system consistency.

[0086] (1.2) Longitudinal control module

[0087] The main function of the longitudinal control module is to control the accelerator pedal opening to make the current vehicle speed as close as possible to the desired speed. The core of this module is the LonFeedforwardPI longitudinal control subsystem. Based on the current vehicle speed, acceleration, and expected speed, the LonFeedforwardPI subsystem comprehensively considers driving resistance and feedback control mechanisms to output the accelerator pedal opening, achieving the desired acceleration effect. This subsystem requires external parameters, including vehicle mass, aerodynamic / rolling drag coefficient, and controller parameters.

[0088] (2) The vehicle control unit (VCU) model is used to coordinate the overall operation of the motor, braking and energy management system, provide control strategies for the thermal management model, and provide battery information for the motor model. The vehicle control unit (VCU) model includes functions such as motor demand drive torque, motor limit torque and fan speed, motor temperature status and cooling control calculation.

[0089] Furthermore, in the dynamic performance tests (including a 30-minute maximum speed test, a maximum speed test, and an acceleration test), the vehicle control unit (VCU) module mainly undertakes three core functions: torque calculation, energy management, and cooling management, among which:

[0090] (2.1) Torque calculation: Based on the current vehicle speed and accelerator pedal opening, the corresponding value is looked up in the two-dimensional interpolation table to calculate the driving torque in the forward state. On this basis, combined with the battery torque limit and the motor torque limit, the output torque is constrained, and finally the target torque required by the motor is generated.

[0091] (2.2) Energy management: The limiting torque of the motor is obtained by looking up the table by the positive voltage and the motor speed. At the same time, the peak discharge power and the load power are calculated based on the positive voltage, the battery output power and the load current. The difference between the two is used to determine the limiting power of the motor. Then, the limiting torque of the battery is obtained by looking up the table by combining the motor speed and the limiting power.

[0092] (2.3) Cooling management: Calculate the fan output duty cycle based on the battery and motor temperatures and map it to the corresponding fan speed. Take the maximum value between the battery and motor temperatures and determine the water pump speed through a one-dimensional interpolation table. Determine the cooling status of the motor based on the motor temperature and output the PTC power by looking up the temperature table. Determine the valve opening based on the temperature interpolation result.

[0093] (3) The vehicle electronic stability system ESP model is used to provide four-wheel braking torque correction information to the vehicle control unit (VCU) model based on the vehicle's position and posture information, so as to realize vehicle posture stability and anti-skid control. The vehicle electronic stability system ESP model uses fuzzy PID control to achieve stability adjustment.

[0094] The ESP model of the vehicle body is used only in handling stability tests and mainly includes a vehicle dynamics subsystem, a fuzzy PID control system, and a torque distribution subsystem, among which:

[0095] (3.1) Vehicle dynamics subsystem: The two-degree-of-freedom model in the vehicle reference model is selected as the ideal model to reflect the linear relationship between the driver's steering input and the vehicle's lateral acceleration, center of gravity sideslip angle and yaw rate;

[0096] (3.2) Fuzzy PID control system: Based on the analysis of the characteristics of the ESP system, the difference between the actual yaw rate and the ideal value and the difference between the actual centroid sideslip angle and the ideal value are selected as input variables. The fuzzy controller outputs the yaw torque adjustment amount M, which is further processed by the PID controller to output the final yaw torque compensation value ΔM.

[0097] (3.3) Torque distribution subsystem: The braking side is determined based on the difference between the actual value and the ideal value of the yaw rate. When the difference is greater than zero, the right wheel is controlled to brake, and when the difference is less than zero, the left wheel is controlled to brake, thereby achieving effective compensation for the vehicle's yaw moment.

[0098] In addition, the ESP model of the vehicle body involves several key vehicle parameters imported from the outside, including the vehicle mass m, the distance from the center of gravity to the front axle a, the distance from the center of gravity to the rear axle b, the front axle lateral stiffness k1, the rear axle lateral stiffness k2, the distance between the front and rear axles L, the front wheel track Bf, the rear wheel track Br, and the road adhesion coefficient μ.

[0099] (4) The battery management system (BMS) model provides a thermal management control strategy for the thermal management model, which is used to calculate the battery heating / cooling request based on the battery temperature, and to calculate the battery output power based on the battery temperature, current and charge status.

[0100] In this embodiment, in the vehicle component simulation model, the thermal management model provides battery information to the motor model and temperature information to the vehicle control unit (VCU) model. The battery model provides battery information to the battery management system (BMS) model and the motor model. The motor model provides motor torque to the vehicle dynamics simulation model. Specifically:

[0101] (1) Battery model. Input parameters include battery temperature, motor output current, and motor output voltage. Output parameters include battery heat flux, positive electrode voltage, positive electrode current, load current, residual current, and single-cell voltage. This battery model mainly undertakes the following core functions:

[0102] System collaborative management: Serving as the interaction hub between the Battery Management System (BMS) model and the thermal management model, it realizes the coordinated control of the battery system;

[0103] Real-time status monitoring: Dynamically feeds back battery remaining current and temperature data, providing key parameters for system decision-making;

[0104] Load current transmission: Accurately transmits real-time load current data to the vehicle control unit (VCU) model, supporting the optimization of vehicle control strategies.

[0105] (2) Motor model. The input ports include input voltage, input current, motor input speed, motor temperature, and motor required torque. The output ports include output voltage, output current, motor output speed, motor heat flow, and motor output torque. The core functions of this motor model include the following two aspects:

[0106] Torque Calculation and Transmission: Calculates the required torque of the motor in real time and transmits the result to the CarSim system;

[0107] Temperature monitoring and feedback: Dynamically monitor motor temperature changes to provide real-time data for the thermal management model to optimize temperature control strategies.

[0108] (3) Thermal management model, with input ports including motor heat flow, battery heat flow, battery heating / cooling request, fan speed, motor cooling status, PTC switch status, valve opening, and water pump required speed; and output ports including battery temperature and motor temperature. The core functions of this thermal management model include the following:

[0109] Temperature monitoring and decision-making: Real-time collection of battery and motor temperature data, combined with built-in threshold table for thermal status assessment, and determination of whether to trigger cooling strategy based on preset logic to ensure that the system operates within a safe temperature range;

[0110] Multi-level cooling control: The cooling system is controlled in stages (such as prioritizing the start of the fan and linking the water cooling system when the temperature is high), optimizing energy consumption and heat dissipation efficiency, and dynamically adjusting the water valve opening and fan speed to achieve precise temperature control;

[0111] System protection and optimization: Prevents performance degradation or thermal runaway risks caused by battery overheating, reduces efficiency loss of motor due to high temperature, and extends component life.

[0112] In this embodiment, the data transmission interface model includes:

[0113] The communication interaction is used to realize the data transmission and synchronization between computers with different addresses, and to complete the real-time exchange of different types of vehicle simulation data and scene setting data through various communication protocols such as UDP / TCP.

[0114] Interface interaction is used to build functional simulation units (FMUs) and other types of interfaces. Importing from the AMESim platform involves building a unique co-simulation interface in AMESim to export independent AME files to connect AMESim and MATLAB, enabling data interaction between the two. A functional module for reading AME files is built, modules are created and the corresponding files are selected and placed into them. The AMESim module is then embedded into Simulink to achieve co-simulation with other software. The CarSim FMU interface uses a common simulation interface protocol to ensure model interoperability.

[0115] In this embodiment, the scenario construction and simulation model, the vehicle dynamics simulation model, the vehicle dynamics parameter analysis model, the vehicle controller simulation model, and the vehicle component simulation model interact with each other through the data transmission interface model. The data transmission adopts the functional simulation unit (FMU) standard interface and UDP / TCP communication protocol for structured encapsulation and real-time transmission.

[0116] In this embodiment, the simulation system also includes a data visualization and recording module, which is used to display and analyze the vehicle state parameters generated during the simulation process in real time.

[0117] See Figure 1 This invention also provides a virtual simulation testing method for electric vehicles based on multidisciplinary collaboration, employing the aforementioned virtual simulation system for electric vehicles, and including the following steps:

[0118] S1. Constructing a multidisciplinary joint simulation environment:

[0119] Based on VTD, scene construction and perception simulation are performed to generate dynamic virtual test scenarios. These dynamic virtual test scenarios include at least complex urban roads, highways, different road surfaces, diverse traffic participants, weather and lighting conditions, and also provide sensor models such as cameras, millimeter-wave radar, and lidar.

[0120] A high-precision electric vehicle dynamics model is built based on CarSim to realize the simulation of the real motion response of electric vehicles under control commands.

[0121] The vehicle subsystem is built based on AMESim, including at least the battery, motor, and thermal management subsystems, to achieve high-precision state simulation of the vehicle under different operating conditions.

[0122] Based on Simulink as an algorithm development and system integration platform, it integrates autonomous driving decision-making algorithms, vehicle control models and communication interface modules.

[0123] S2. Perform closed-loop simulation of the autonomous driving algorithm under test:

[0124] Simulink receives environmental perception data and sensor information from VTD and inputs them into the autonomous driving algorithm under test (such as existing mature reinforcement learning algorithms, model predictive control algorithms, etc.). The algorithm outputs longitudinal and lateral control commands for the vehicle, including at least control commands for throttle, braking and steering angle.

[0125] S3, Vehicle Dynamics Response Simulation:

[0126] The control commands of the autonomous driving algorithm are parsed by Simulink and transmitted to CarSim. CarSim simulates the vehicle dynamics state at the current moment based on the vehicle attitude, environmental information and vehicle subsystem parameters of the previous moment, and outputs vehicle dynamic parameters. These vehicle dynamic parameters include at least vehicle position, attitude, speed, acceleration, heading angle, wheel speed and suspension load.

[0127] S4. Vehicle Subsystem Simulation and Feedback:

[0128] An electric vehicle controller module is integrated into Simulink. This electric vehicle controller module includes at least a vehicle control unit (VCU) model, an electronic stability program (ESP) model, a battery management system (BMS) model, a battery model, a motor model, a thermal management model, and other vehicle functional modules. It analyzes the vehicle dynamics parameters output by CarSim and the battery / motor / thermal management parameters output by AMESim, calculates vehicle system control commands and subsystem state parameters, and Simulink sends the updated vehicle state and vehicle controller output to CarSim, AMESim, and VTD after encoding according to a preset communication protocol. This is used to influence the environmental update, vehicle dynamics, and vehicle subsystem response at the next time step.

[0129] S5, Scenario Construction and Test Execution:

[0130] Based on the testing requirements, construct test scenarios (such as handling stability test scenarios and power performance test scenarios) in VTD, set boundary conditions according to the test requirements, configure initial vehicle parameters, road conditions, interference events and traffic information, and execute closed-loop tests.

[0131] S6. Test Result Output and Evaluation:

[0132] Based on the vehicle attitude, dynamic response, and subsystem state information output by CarSim, AMESim, and Simulink, the performance of electric vehicles (such as dynamics, handling stability, and control performance) is evaluated, and the vehicle system performance is judged to meet the preset standards based on simulation data. The test indicators include at least the vehicle body slip angle, longitudinal acceleration, lateral acceleration, yaw rate, vehicle body roll angle, pitch angle, steering wheel angle, steering wheel torque, maximum speed, acceleration time, and energy consumption.

[0133] It should be noted that in the above-mentioned virtual simulation test method for electric vehicles based on multidisciplinary collaboration, the multidisciplinary joint simulation process is a discrete-time recursive update method, and the time step is set by Simulink, which is selectable and is generally set to 0.1s-0.001s.

[0134] In this embodiment, in step S1, the simulation system and simulation testing method support joint simulation on multiple platforms including Simulink, CarSim, VTD and AMESim, and the platforms achieve time synchronization and signal consistency through data transmission interfaces.

[0135] In this embodiment, in step S2, the VTD and the Simulink communicate via RTI or Socket. The VTD outputs environmental perception data and sensor information to the Simulink, including at least lane line position, obstacle information, camera image, LiDAR point cloud and vehicle Z-axis attitude.

[0136] In this embodiment, in S3, CarSim supports the customization of the parameters of the vehicle dynamics of electric vehicles to adapt to the simulation needs of different vehicle types, suspension structures, tire models and vehicle operating conditions.

[0137] In S4, AMESim supports the customization of relevant subsystems of electric vehicles, including batteries, motors, and thermal management, to adapt to the simulation requirements of different vehicle types, battery models, motor models, and vehicle operating conditions. Specifically, during the testing process:

[0138] The input parameters of the AMESim-based battery model include battery temperature, motor output current and motor output voltage, while the output parameters cover battery heat flux, positive electrode voltage, positive electrode current, load current, residual current and single cell voltage.

[0139] The input ports of the AMESim-based motor model include input voltage, input current, motor input speed, motor temperature, and motor required torque, while the output ports cover output voltage, output current, motor output speed, motor heat flux, and motor output torque.

[0140] The AMESim-based thermal management model has the following input ports: motor heat flow, battery heat flow, battery heating and cooling request, fan speed, motor cooling status, PTC switch status, valve opening, and water pump required speed. The output ports are battery temperature and motor temperature.

[0141] In this embodiment, during the vehicle subsystem simulation process in Simulink in step S3, the following control strategy is adopted:

[0142] The vehicle control unit (VCU) model calculates the driving torque in the forward state by looking up the corresponding value in a two-dimensional interpolation table based on the current vehicle speed and accelerator pedal opening.

[0143] By combining battery torque limits and motor torque limits, the output torque is constrained, and the target torque required by the motor is finally generated. Then, the motor's limiting torque is obtained by looking up a table using the positive voltage and motor speed.

[0144] Based on the positive electrode voltage, battery output power and load current, calculate the peak discharge power and load power. The difference between the two is used to determine the motor's limiting power. Then, by combining the motor speed and the limiting power, look up the table to obtain the battery's limiting torque, and then calculate the vehicle's drive command.

[0145] The Electronic Stability Program (ESP) model performs stability control and outputs braking correction signals based on vehicle dynamic parameters, which include at least vehicle yaw rate, lateral acceleration, and tire slip angle.

[0146] The Battery Management System (BMS) model outputs battery state of charge, battery health status, and thermal management parameters based on the vehicle battery's voltage, current, and temperature parameters.

[0147] In this embodiment, the simulation testing method can automatically change the simulation scene and its parameters according to the vehicle testing requirements. The modification process includes the following steps: automatically switching the road type, obstacle density, vehicle interaction behavior, or lighting and weather conditions in the VTD scene according to the test triggering conditions to meet the scene coverage requirements of autonomous driving function testing. The parameters of the test scene include at least adjustable variables such as initial vehicle speed, road curvature, adhesion coefficient, traffic flow density, weather and lighting conditions, and sensor noise level.

[0148] In this embodiment, after the simulation test is completed, the simulation test method can generate a simulation record file based on vehicle dynamics data, subsystem state data and environmental data, which can be used for further performance playback, parameter analysis and algorithm optimization.

[0149] To further verify the feasibility and superiority of this method, this invention will use handling stability and dynamic performance tests as examples to describe the operational steps of vehicle performance testing based on this simulation testing method. The operation flowcharts for vehicle handling stability tests and vehicle dynamic performance tests using the co-simulation model are shown below. Figure 2 and Figure 3 As shown.

[0150] For handling stability testing:

[0151] First, start VTD and confirm the settings, select and load the scenario required for the test; then start CarSim, select the vehicle dynamics simulation model parameter settings, initial pose and input / output corresponding to the simulation test, and send the model to Simulink; finally, click the run button in Simulink to run the simulation test.

[0152] For dynamic testing:

[0153] First, start VTD and confirm the settings, select and load the scenario required for the test; then start CarSim, select the vehicle dynamics simulation model parameter settings, initial pose, and input / output corresponding to the simulation test, and send the model to Simulink; then load the necessary model parameters and boundary conditions in Simulink; after loading, open AMESim, set the internal parameters of the model and establish the interface for the battery / motor / thermal management model, export the corresponding files and update them in the Simulink model; finally, complete the VTD run configuration and click the run button in Simulink to start the simulation test.

[0154] Furthermore, this invention will take the serpentine test simulation test constructed based on the vehicle handling stability test method as an example to explain in detail the excellent effects that this technical solution can achieve.

[0155] (1) In accordance with national standards, construct the scenarios required for the serpentine test in the scenario construction and simulation model (or VTD platform). (Among them, the handling stability test should be based on national standard GB / T 6323-2014, and the dynamic performance test should be based on national standard GB / T18385-2005). The completed scenario is as follows: Figure 4 As shown.

[0156] (2) Based on the testing requirements, integrate the scenario construction and simulation model, the vehicle dynamics simulation model, and the vehicle controller simulation model, and improve the data output and conversion module accordingly.

[0157] (3) According to the national standard requirements, set the boundary conditions for the snake-like test simulation, as follows:

[0158] Based on the coordinates of the center points of the front and rear axles and the vehicle's dimensions (length and width), the vehicle's outline position is calculated in real time. Based on the marker layout parameters (including the horizontal coordinate of the first marker, marker spacing, and the total number of markers, including the four markers marking the boundary of the test area), the following judgments are made:

[0159] a. When the vehicle outline collides with any marker, set the current frame's output_collision=1 (this will not directly terminate the simulation); the core idea of ​​this collision detection algorithm is to calculate the vertical distance (dist_long) from the marker to the vehicle's longitudinal axis and the vertical distance (dist_lat) to the transverse axis. A collision is determined to have occurred when dist_lat < half the vehicle's width and dist_long < half the vehicle's length.

[0160] b. When the vehicle is within the test area, set the current frame's output_inrange=1;

[0161] c. The simulation process is terminated once the vehicle leaves the test area.

[0162] (4) Run the simulation test according to the operation procedures of the vehicle handling stability test and vehicle dynamics test described above. The simulation test results are shown in the figure below. Figure 5 As shown.

[0163] (5) After the simulation test is completed, the test output data is extracted, processed and analyzed, and the final vehicle performance index results required by the national standard are obtained as follows: Figure 6 As shown, according to Figure 6 Analysis of the serpentine test results shows that the proposed technical solution can achieve high-precision simulation of vehicle status and basically achieve the expected simulation test effect.

[0164] This invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of the above-described method for virtual simulation testing of electric vehicles based on multidisciplinary collaboration.

[0165] See Figure 10 The present invention also provides a computer device, including a memory and a processor. The memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the above-described method for virtual simulation testing of electric vehicles based on multidisciplinary collaboration.

[0166] This invention also provides a computer program product containing instructions that, when run on a computer, causes the computer to perform the steps of the above-described method for virtual simulation testing of electric vehicles based on multidisciplinary collaboration.

[0167] It is understood that the systems, devices and storage media provided in the embodiments of the present invention correspond to the methods provided in the embodiments of the present invention, and the explanations, examples and beneficial effects of the relevant content can be referred to the corresponding parts of the above-mentioned virtual simulation test method for electric vehicles based on multidisciplinary linkage.

[0168] It should be noted that those skilled in the art will understand that all or part of the steps implemented in the embodiments of the present invention can be implemented entirely or partially by software, hardware, firmware, or any combination thereof. When implemented in hardware, it can be implemented entirely or partially by purchasing standard parts or modifications. When implemented in software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid state disks (SSDs)).

[0169] It should also be noted that the meaning of "and / or" throughout the text includes three parallel solutions. Taking "A and / or B" as an example, it includes solution A, solution B, or a solution that satisfies both A and B. Furthermore, "multiple" refers to two or more. Additionally, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0170] In summary, this invention addresses the shortcomings of existing vehicle systems in multi-scenario, multi-disciplinary, and refined simulations, particularly in terms of functional coverage, interface compatibility, and co-simulation stability. It proposes a multi-disciplinary collaborative virtual simulation system and testing method for electric vehicles. Specifically, this invention integrates multi-disciplinary commercial simulation software, encompassing high-precision scene generation, vehicle dynamics modeling, and simulation of control systems and electromechanical components. It proposes a unified data interface and spatial coordinate transformation method, and introduces an algebraic loop processing mechanism to effectively resolve instability issues during multi-software coupling. This results in high-precision, scalable vehicle virtual simulation results, meeting the comprehensive needs of new energy vehicles and intelligent driving systems for multi-disciplinary refined simulation.

[0171] It should be understood that the examples and embodiments described herein are for illustrative purposes only and are not intended to limit the invention. Those skilled in the art can make various modifications or changes based on them. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the invention should be included within the protection scope of the invention.

Claims

1. A virtual simulation testing method for electric vehicles based on multidisciplinary collaboration, characterized in that, Includes the following steps: S1. Construct a multidisciplinary joint simulation environment: Based on VTD, construct and simulate scenarios to generate dynamic virtual test scenarios; based on CarSim, construct a dynamic model of the electric vehicle to realize the real motion response simulation of the electric vehicle under control commands; based on AMESim, construct a vehicle subsystem to realize the state simulation of the vehicle under different working conditions; based on Simulink as an algorithm development and system integration platform, integrate autonomous driving decision-making algorithms, vehicle control models and communication interface modules. S2. Closed-loop simulation of the autonomous driving algorithm under test: Simulink receives environmental perception data and sensor information output by VTD and inputs them into the autonomous driving algorithm under test. The autonomous driving algorithm under test outputs longitudinal and lateral control commands for the vehicle. S3. Vehicle Dynamics Response Simulation: The control commands of the autonomous driving algorithm are parsed by Simulink and transmitted to CarSim. CarSim simulates the vehicle dynamics state at the current moment based on the vehicle attitude, environmental information and vehicle subsystem parameters of the previous moment, and outputs the vehicle dynamics parameters. S4. Vehicle Subsystem Simulation and Feedback: An electric vehicle controller module is integrated into Simulink to analyze the vehicle dynamics parameters output by CarSim and the battery / motor / thermal management parameters output by AMESim. The vehicle system control commands and subsystem state parameters are calculated. Simultaneously, Simulink encodes the updated vehicle state and vehicle controller output according to a preset communication protocol and sends them to CarSim, AMESim and VTD to influence the environmental update, vehicle dynamics and vehicle subsystem response in the next time step. S5. Scenario Construction and Test Execution: Based on the test requirements, construct test scenarios in VTD, set boundary conditions according to the test requirements, configure initial vehicle parameters, road conditions, interference events and traffic information, and execute closed-loop tests. S6. Test Result Output and Evaluation: Based on the vehicle attitude, dynamic response and subsystem state information output by CarSim, AMESim and Simulink, evaluate the performance of the electric vehicle and determine whether the vehicle system performance meets the preset standards based on the simulation data.

2. The virtual simulation testing method for electric vehicles based on multidisciplinary collaboration as described in claim 1, characterized in that, In S1, the simulation system and simulation testing method support joint simulation on multiple platforms including Simulink, CarSim, VTD and AMESim, and the platforms achieve time synchronization and signal consistency through data transmission interfaces.

3. The virtual simulation testing method for electric vehicles based on multidisciplinary collaboration as described in claim 1, characterized in that, In step S2, the VTD and Simulink interact with each other via Real-Time Industrial Communication (RTI) or Socket Communication. The VTD outputs environmental perception data and sensor information to Simulink, including lane line position, obstacle information, camera images, LiDAR point cloud, and vehicle Z-axis attitude.

4. The virtual simulation testing method for electric vehicles based on multidisciplinary collaboration as described in claim 1, characterized in that, In S3, CarSim supports the customization of the parameters of the vehicle dynamics of electric vehicles to adapt to the simulation needs of different vehicle types, suspension structures, tire models and vehicle operating conditions. In S4, AMESim supports the customization of related subsystems of electric vehicles, such as batteries, motors, and thermal management, to meet the simulation requirements of different vehicle types, battery models, motor models, and vehicle operating conditions.

5. The virtual simulation testing method for electric vehicles based on multidisciplinary collaboration as described in claim 1, characterized in that, In S3, the Simulink system employs the following control strategy during the vehicle subsystem simulation: The vehicle control unit (VCU) model calculates the driving torque in the forward state by looking up the corresponding value in a two-dimensional interpolation table based on the current vehicle speed and accelerator pedal opening. By combining battery torque limits and motor torque limits, the output torque is constrained, and the target torque required by the motor is finally generated. Then, the motor's limiting torque is obtained by looking up a table using the positive voltage and motor speed. Based on the positive electrode voltage, battery output power and load current, calculate the peak discharge power and load power. The difference between the two is used to determine the motor's limiting power. Then, by combining the motor speed and the limiting power, look up the table to obtain the battery's limiting torque, and then calculate the vehicle's drive command. The Electronic Stability Program (ESP) model performs stability control and outputs braking correction signals based on vehicle dynamic parameters. The Battery Management System (BMS) model outputs battery state of charge, battery health status, and thermal management parameters based on the vehicle battery's voltage, current, and temperature parameters.

6. A virtual simulation system for electric vehicles based on multidisciplinary collaboration, applicable to the virtual simulation testing method for electric vehicles based on multidisciplinary collaboration as described in claim 1, characterized in that, include: The scenario construction and simulation model is used to generate simulation scenarios based on preset test requirements, adapt to different test requirements, and receive simulation scenario element editing signals to modify the simulation scenario according to test requirements. The vehicle performs real-time response and control simulation in the simulation scenario. The vehicle dynamics simulation model is used to simulate the longitudinal, lateral and vertical dynamic responses of a vehicle. The input of the vehicle dynamics simulation model is historical and current vehicle position information, vehicle attitude information and vehicle dynamic information, and the output is the vehicle position information, vehicle attitude information and vehicle dynamic information at the next moment. The vehicle dynamics parameter analysis model is used to analyze, transform, and visualize the data output by the vehicle dynamics simulation model in order to extract key dynamic parameters. The analysis process includes data format decoding, unit conversion, and time synchronization processing. The vehicle controller simulation model is used to receive and process the data output by the vehicle dynamics parameter analysis model, including the driver model, the vehicle control unit (VCU) model, the electronic stability program (ESP) model, and the battery management system (BMS) model. Vehicle component simulation models are used to perform joint simulations of motors, batteries, and thermal systems to support the modeling of the energy flow and thermal behavior of the entire vehicle, including motor models, battery models, and thermal management models. The data transmission interface model is used to realize communication and data interaction between systems.

7. The electric vehicle virtual simulation system based on multidisciplinary collaboration as described in claim 6, characterized in that, The scenario construction and simulation model includes multiple sub-modules, which are used to automatically generate different road types and environmental conditions to support the construction of various typical test environments related to urban roads, highways and test fields.

8. The electric vehicle virtual simulation system based on multidisciplinary collaboration as described in claim 6, characterized in that, In the vehicle controller simulation model: The driver model is used to generate a feasible driving trajectory for the vehicle based on a preset trajectory reference point. The vehicle control unit (VCU) model is used to coordinate the overall operation of the motor, braking, and energy management systems. The ESP model is used to achieve vehicle attitude stability and anti-skid control based on the vehicle's position and posture information. The battery management system (BMS) model is used to calculate battery heating / cooling requests based on battery temperature, and to calculate battery output power based on battery temperature, current, and state of charge.

9. The electric vehicle virtual simulation system based on multidisciplinary collaboration as described in claim 6, characterized in that, In the data transmission interface model, communication interaction is used to realize data transmission and synchronization between computers with different addresses, and interface interaction is used to construct functional simulation unit (FMU) and other types of interfaces.

10. The electric vehicle virtual simulation system based on multidisciplinary collaboration as described in claim 6, characterized in that, The scenario construction and simulation model, the vehicle dynamics simulation model, the vehicle dynamics parameter analysis model, the vehicle controller simulation model, and the vehicle component simulation model interact with each other through the data transmission interface model. The data transmission adopts the functional simulation unit (FMU) standard interface and UDP / TCP communication protocol for structured encapsulation and real-time transmission.

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