Vehicle crosswind stability virtual test method based on driving simulator

Abstract

The invention relates to the technical field of vehicle tests, in particular to a vehicle crosswind stability virtual test method based on a driving simulator. The method comprises the following steps: firstly, constructing a virtual test scene according to a preset crosswind test working condition standard, and constructing a gust model of a fan array; and performing a vehicle crosswind stability test according to the virtual test scene, and applying lateral wind power to the test vehicle based on the gust model. Lateral wind power is applied to the vehicle multi-body dynamics model, and vehicle operation data of the vehicle multi-body dynamics model are determined. And synchronously feeding back the vehicle operation data to the driving simulator, so that a driver determines the operation condition after receiving the lateral wind power. According to the scheme, the blank of crosswind stability test virtualization is filled, a virtual crosswind test in the early stage of vehicle design and development is formed, crosswind stability verification and optimization can be carried out on the vehicle dynamics model in the early stage of research and development, the development period is shortened, and the later modification cost is reduced.

Description

Technical Field

[0001] This specification relates to the field of vehicle testing technology, and in particular to a virtual test method for vehicle crosswind stability based on a driving simulator. Background Technology

[0002] As the automotive industry continues to advance towards higher speeds, lighter weight, and greater intelligence, the aerodynamic stability of vehicles, especially their dynamic response and safety performance under sudden crosswind conditions, has become one of the key indicators for evaluating the design level of modern automobiles. Crosswind stability not only directly affects ride comfort but also relates to driving safety in high-speed driving scenarios. Currently, research on vehicle crosswind stability mainly relies on methods such as road tests and wind tunnel tests.

[0003] Currently, the mainstream research method for vehicle crosswind stability is road testing. Road testing, based on national standards, uses a fixed wind turbine array in a test track to simulate lateral wind loads, and sensors collect vehicle motion data to assess its resistance to crosswind interference. However, this method is significantly affected by natural environmental factors (such as atmospheric turbulence, temperature and humidity changes), road conditions, and driver operation in practical applications, resulting in limited test condition coverage and low data repeatability and consistency. Furthermore, in the traditional "V"-shaped development process, subjective evaluation heavily relies on physical prototypes and can often only be conducted in the later stages of development. The inability to incorporate real driver feedback in the early stages of development causes a significant delay in the subjective evaluation process, leading to a series of problems such as extended development feedback cycles, increased design change costs, and a disconnect between objective indicators and subjective experience, severely restricting the optimization depth and development efficiency of vehicle crosswind stability design. Therefore, this specification provides a virtual testing method for vehicle crosswind stability based on a driving simulator. Summary of the Invention

[0004] This specification provides a virtual test method for vehicle crosswind stability based on a driving simulator, in order to partially solve the aforementioned problems existing in the prior art.

[0005] The following technical solution is adopted in this specification: This specification provides a virtual test method for vehicle crosswind stability based on a driving simulator, including: S1. Based on the preset crosswind test condition standards, a virtual test scenario including a wind turbine array and a test vehicle is constructed in the first simulation software; and a gust model of the wind turbine array is constructed. S2. Based on the virtual test scenario, conduct a vehicle crosswind stability test on the test vehicle. When the test vehicle enters the crosswind area caused by the wind turbine array, determine the lateral wind force applied to the test vehicle in the crosswind area based on the gust model. S3. In the second simulation software, the lateral wind force is applied to the pre-built vehicle multibody dynamics model to determine the vehicle operation data of the vehicle multibody dynamics model; S4. The vehicle operation data is synchronously fed back to the driving simulator so that the driver in the driving simulator can determine the operating status of the vehicle multibody dynamics model after being subjected to the lateral wind force; wherein, the vehicle multibody dynamics model is communicatively connected to the driving simulator, and the vehicle multibody dynamics model is a simulation model controlled by the driving simulator.

[0006] Based on the aforementioned technical means, this solution fills the gap in virtual crosswind stability testing, enabling virtual crosswind testing in the early stages of vehicle design and development. This allows for the verification and optimization of vehicle dynamics models (such as suspension, steering, and ESP system parameters) for crosswind stability during the early R&D phase, shortening the development cycle and reducing later modification costs. By constructing a gust model using preset standards, wind speed, direction, duration, and spatial distribution can be precisely controlled, achieving high consistency and repeatability of test conditions. The unsteady aerodynamic forces generated by the wind turbine array are simulated using a first simulation software (possibly CFD or dedicated wind field software) and applied as input to a high-precision vehicle multibody dynamics model in a second simulation software, achieving high-fidelity coupling between aerodynamics and vehicle dynamics. Vehicle operating data (such as yaw rate, lateral velocity, lateral acceleration, steering wheel angle, longitudinal speed, lateral offset, roll angle, and slip angle) are fed back to the driving simulator in real time, providing the driver with realistic force, vision, and motion perception, forming a closed-loop testing system of "driver-vehicle-wind environment."

[0007] Furthermore, the expression for the gust model described in S1 is:

[0008] in, The crosswind speed caused by the aforementioned wind turbine array. The time for conducting the crosswind stability test on the test vehicle; The time it takes for the test vehicle to enter the crosswind area created by the wind turbine array; The time it takes for the test vehicle to leave the crosswind area caused by the wind turbine array; The time required for the crosswind speed to increase from zero to its maximum value (or decrease from its maximum value to zero); This is the preset maximum crosswind speed.

[0009] Furthermore, the vehicle multibody dynamics model described in S3 includes a body model, a suspension model, a steering model, and a tire model.

[0010] Based on the above technical means, the vehicle multibody dynamics model is composed of multiple high-fidelity subsystem models, including the body model (representing the vehicle mass, moment of inertia and center of gravity position), the suspension model (describing the kinematic and elastodynamic characteristics of each suspension assembly), the steering model (reflecting the transmission and clearance characteristics of the steering system), and the tire model (characterizing the complex force and torque characteristics between the tire and the road surface).

[0011] Furthermore, the suspension model is a high-frequency bushing model.

[0012] Based on the above technical means, the high-frequency bushing model can accurately characterize the nonlinear stiffness and damping characteristics of the rubber bushing in the crosswind excitation frequency range.

[0013] Furthermore, the tire model is a magic formula model.

[0014] Based on the aforementioned technical means, the magic formula model can continuously express the longitudinal force, lateral force, and self-aligning torque of the tire using a unified mathematical form, making it suitable for dynamic simulation under a wide range of working conditions.

[0015] Furthermore, it also includes step S5: obtaining the driver's evaluation results of the vehicle crosswind stability test in the driving simulator, the evaluation results including lateral stability score and driving confidence score; Based on the evaluation results and the vehicle operation data, the subjective and objective consistency correlation results of the vehicle crosswind stability test are determined.

[0016] Based on the aforementioned technical means, vehicle operating data (such as yaw rate, lateral velocity, lateral acceleration, steering wheel angle, longitudinal speed, lateral offset, roll angle, and slip angle) can determine whether a vehicle is "stable," but cannot evaluate whether the driver feels "safe" or "controlled." The S5 quantifies the driver's perception of the vehicle's ability to resist crosswind interference and their subjective control over the vehicle through lateral stability and driver confidence scores, directly quantifying the driver's subjective sense of security and operational burden, revealing the true experience of human-machine interaction. Establishing a scientific correlation between "physical response" and "subjective feeling," identifying which vehicle operating data most significantly influence the driver's stability and confidence scores, provides engineers with clear optimization directions. This shifts the development goal from simply optimizing objective indicators to simultaneously optimizing key dynamic parameters strongly correlated with a positive subjective experience, thereby achieving truly driver-centric performance design.

[0017] Furthermore, S3 specifically includes: In the first simulation software, after applying the lateral wind force to the test vehicle, the drag, lateral force, lift, pitching moment, roll moment, and yaw moment experienced by the test vehicle are determined. In the second simulation software, the drag, the lateral force, the lift, the pitch moment, the roll moment, and the yaw moment are applied to the pre-built vehicle multibody dynamics model to determine the vehicle operation data of the vehicle multibody dynamics model. The vehicle operation data includes yaw rate, lateral velocity, lateral acceleration, steering wheel angle, longitudinal speed, lateral offset, roll angle, and sideslip angle.

[0018] This specification provides a virtual testing device for vehicle crosswind stability based on a driving simulator, including: The construction module is used to construct a virtual test scenario including a wind turbine array and a test vehicle in the first simulation software according to a preset crosswind test condition standard; and to construct a gust model of the wind turbine array. The first test module is used to conduct a vehicle crosswind stability test on the test vehicle according to the virtual test scenario. When the test vehicle enters the crosswind area caused by the wind turbine array, the module determines the lateral wind force applied to the test vehicle in the crosswind area based on the gust model. The second test module is used to apply the lateral wind force to a pre-built vehicle multibody dynamics model in the second simulation software and determine the vehicle operation data of the vehicle multibody dynamics model. The feedback module is used to synchronously feed back the vehicle operation data to the driving simulator, so that the driver in the driving simulator can determine the operating status of the vehicle multibody dynamics model after being subjected to the lateral wind force; wherein, the vehicle multibody dynamics model is communicatively connected to the driving simulator, and the vehicle multibody dynamics model is a simulation model controlled by the driving simulator.

[0019] This specification provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned virtual test method for vehicle crosswind stability based on a driving simulator.

[0020] This specification provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement a virtual test method for vehicle crosswind stability based on a driving simulator.

[0021] The above-mentioned technical solutions adopted in this specification can achieve the following beneficial effects: This solution fills the gap in virtual crosswind stability testing, enabling virtual crosswind testing in the early stages of vehicle design and development. It allows for the verification and optimization of vehicle dynamics models (such as suspension, steering, and ESP system parameters) for crosswind stability during the early R&D phase, shortening the development cycle and reducing later modification costs. By constructing a gust model using preset standards, wind speed, direction, duration, and spatial distribution can be precisely controlled, achieving high consistency and repeatability of test conditions. The unsteady aerodynamic forces generated by the wind turbine array are simulated using a first simulation software (possibly CFD or dedicated wind field software) and applied as input to a high-precision vehicle multibody dynamics model in a second simulation software, achieving high-fidelity coupling between aerodynamics and vehicle dynamics. Vehicle operating data (such as yaw rate, lateral velocity, lateral acceleration, steering wheel angle, longitudinal speed, lateral offset, roll angle, and slip angle) are fed back to the driving simulator in real time, providing the driver with realistic force, vision, and motion perception, forming a closed-loop testing system of "driver-vehicle-wind environment." Attached Figure Description

[0022] The accompanying drawings, which are included to provide a further understanding of this specification and form part of this specification, illustrate exemplary embodiments and are used to explain this specification, but do not constitute an undue limitation thereof. In the drawings: Figure 1 A flowchart illustrating a virtual test method for vehicle crosswind stability based on a driving simulator, provided as an embodiment of this specification; Figure 2 This is a schematic diagram of a virtual test scenario provided in this specification; Figure 3 A schematic diagram of a driving simulator provided in this specification; Figure 4 A schematic diagram of a virtual test device for vehicle crosswind stability based on a driving simulator, provided for this specification; Figure 5 This specification provides a corresponding Figure 1 A schematic diagram of the structure of an electronic device. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this specification clearer, the technical solutions of this specification will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments in this specification without creative effort are within the scope of protection of this application.

[0024] In embodiments of this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0025] The technical solutions provided in the various embodiments of this specification are described in detail below with reference to the accompanying drawings.

[0026] Figure 1 A flowchart illustrating a virtual test method for vehicle crosswind stability based on a driving simulator, provided in this specification, includes the following steps: S1: Based on the preset crosswind test condition standards, a virtual test scenario including a wind turbine array and a test vehicle is constructed in the first simulation software; and a gust model of the wind turbine array is constructed.

[0027] This specification describes the process of conducting a virtual test of vehicle crosswind stability based on a driving simulator. In the embodiments described herein, this virtual test can be executed by a server. However, this specification does not limit the type of device or platform used to perform the virtual test; for example, a personal computer, mobile terminal, or other similar devices or platforms can also be used. For ease of description, the following description uses a server as the executing entity.

[0028] In one or more embodiments of this specification, the server can set the crosswind test condition standard according to a preset crosswind test condition standard, such as the national standard ISO 12021:2010 "Road vehicles—Crosswind sensitivity—Open-loop test method for wind turbine input". Then, in a preset first simulation software (usually computational fluid dynamics software), a virtual test scenario including a wind turbine array and a test vehicle is constructed. This scenario mainly includes a wind turbine array model and a test vehicle CFD numerical model; wherein, the wind turbine array model mainly establishes the geometric model and flow field domain of the wind turbines (groups) on one or both sides of the virtual road to simulate natural crosswinds, according to the test layout requirements in the standard; the test vehicle CFD numerical model is used to accurately reflect the external aerodynamic shape of the actual vehicle to ensure the reliability of the aerodynamic simulation results.

[0029] While constructing the virtual scenario, it is necessary to define a gust model generated by the wind turbine array. This model is used to control the change of crosswind speed over time in the simulation, to simulate the situation of encountering a sudden crosswind in the real world. The gust model of the wind turbine array, defining the crosswind speed amplitude, incoming flow angle, and timing characteristics in the virtual environment, is expressed as follows:

[0030] in, The crosswind speed caused by the wind turbine array. The time allotted for testing the crosswind stability of the test vehicle. The time it takes for the test vehicle to enter the crosswind zone created by the wind turbine array. The time it takes for the test vehicle to leave the crosswind zone created by the wind turbine array. The time required for the crosswind speed to increase from zero to its maximum value (or decrease from its maximum value to zero) is 0.1 s in this invention, and the time required for the increase is the same as the time required for the decrease. This is the preset maximum crosswind speed.

[0031] This gust model describes the complete crosswind road test wind load process: Before action ( The test vehicle did not enter the crosswind zone, and the wind speed was 0. Establishment period ( The vehicle is about to enter the crosswind zone, where the wind speed follows a cosine function. Increasing from zero to [amount] within a time period .

[0032] Stable period ( The vehicle is completely in the crosswind zone and is subjected to a stable maximum wind speed. .

[0033] Regression period ( As the vehicle moves out of the crosswind zone, the wind speed follows a cosine function law. From within a time period Reduce to 0.

[0034] After action ( ): The crosswind effect has ended.

[0035] In the first simulation software, when constructing the CFD numerical model of the test vehicle, the original three-dimensional shape model of the test vehicle is first imported into the preprocessing environment, and the model is standardized to ensure its geometric compatibility. The vehicle model is then placed in the computational fluid dynamics software environment to systematically check and repair geometric defects such as small gaps and overlapping surfaces in the original model. The computational domain and the surface of the target vehicle body are meshed, and triangular elements are used to adapt to the curvature changes of complex surfaces. The PID (Property Identifier) ​​partitioning of the computational domain and various parts of the vehicle body is completed, and physical properties and solver identification labels are assigned to each geometric boundary.

[0036] The computational domain was set up entirely according to the national standard crosswind road test section. The distance from the computational domain entrance to the crosswind zone was 100 m, the crosswind section was 21 m, the distance from the crosswind zone to the computational domain exit was 100 m, the vehicle was 7 m from the crosswind entrance, and the crosswind exit was 30 m from the leeward side of the test vehicle. During the calculation, the test vehicle entered and left the crosswind zone at a constant speed. The crosswind entrance boundary conditions were applied using the aforementioned gust model. The computational domain exit and crosswind exit used pressure exit boundary conditions, with the gauge pressure set to 0 Pa. The ground and vehicle surface used no-slip wall boundary conditions. The top of the computational domain used symmetrical boundary conditions.

[0037] The motion of the test vehicle in the virtual test scenario is achieved through overlapping mesh technology. The main region (i.e., the background region) mesh is stationary, while the sub-region (i.e., the region where the test vehicle moves) mesh moves relatively. Interpolation calculations are performed between the main region mesh and the sub-region mesh to repeatedly transmit the flow field information at their respective boundaries. An overlapping mesh interface is established between the background mesh and the sub-region mesh. An automatic hole-punching algorithm is used to mark the corresponding background mesh cells inside the solid wall of the sub-region as hole cells, which do not participate in the flow field solution. The interface interpolation uses the least squares method to achieve the conservation and transfer of velocity, pressure, and turbulent flow between the two sets of meshes. The sub-region volume mesh region is set as a rigid body; a local coordinate system is established with the origin located at the center of mass of the test vehicle; the vehicle's speed is defined by a user-defined function, and the motion vector is described based on the local coordinate system. The sub-region mesh translates or rotates as a whole with the rigid body motion, while the background mesh remains stationary. The spatial position of the sub-region is updated at each physical time step, and the overlapping interface interpolation weights are recalculated until the preset calculation termination time.

[0038] Large eddy simulation (LES) was used to calculate and solve the external flow field of the test vehicle. The time discretization employed a second-order bounded implicit scheme; the momentum convection term used a bounded central difference scheme, which suppresses non-physical oscillations while maintaining low numerical dissipation; the pressure term used a second-order discretization scheme; and the pressure-velocity coupling was achieved using a semi-implicit method for pressure-linked equations, namely the SIMPLE series of algorithms. The time step was estimated based on the minimum grid size and the maximum characteristic velocity, ensuring the Courant number was no greater than 1. First, a steady-state Reynolds-averaged Navier-Stokes (SST) solution was performed using the SST k-ω turbulence model. After iterative convergence, an initial field including the boundary layer distribution and wake morphology was obtained. The steady-state calculation results were saved, and the LES model and unsteady solver were switched to initiate transient calculations using the steady-state results as the initial field.

[0039] Figure 2 This is a schematic diagram of a virtual test scenario provided in this specification. Figure 2 As shown, the area within the two dark horizontal bars represents the road. Before the crosswind stability test, the test vehicle is positioned on the left side of the road. In this virtual test scenario, the maximum speed of the test vehicle is limited to a constant speed of less than 160 km / h. The steering wheel is fixed before the test vehicle starts, and the test is conducted with the steering wheel fixed. The driving direction is from left to right, and the vehicle will pass through a pre-set wind turbine area, which includes a pre-set wind turbine array, consisting of individual wind turbines. In the virtual test scenario, the origin X=0 meters is taken as the starting point of the test vehicle entering the wind turbine area, and the initial position of the test vehicle is 100 meters away from the wind turbine array.

[0040] The steering wheel is fixed at a point X = -40 meters before the start of the crosswind zone and 2 seconds after leaving the wind turbine area (i.e., the wind zone). The point where the steering wheel is released is represented by point Xd in the virtual test scenario. The test vehicle will exhibit lateral drift after being exposed to the crosswind, and this drift is represented by the solid lines connecting the test vehicles in the virtual test scenario.

[0041] S2: Based on the virtual test scenario, conduct a vehicle crosswind stability test on the test vehicle. When the test vehicle enters the crosswind area caused by the wind turbine array, determine the lateral wind force applied to the test vehicle in the crosswind area based on the gust model.

[0042] S3: In the second simulation software, the lateral wind force is applied to the pre-built vehicle multibody dynamics model to determine the vehicle operation data of the vehicle multibody dynamics model.

[0043] In one or more embodiments of this specification, the server can conduct a vehicle crosswind stability test on the test vehicle according to a virtual test scenario. When the test vehicle enters the crosswind area caused by the wind turbine array, the server determines the lateral wind force applied to the test vehicle in the crosswind area based on the gust model. Then, the wind speed calculated according to the gust model in the virtual test scenario is used to simulate the lateral wind force through the wind turbine array.

[0044] Subsequently, in the pre-set second simulation software, lateral wind force is applied to the pre-built vehicle multibody dynamics model to determine the vehicle operation data of the vehicle multibody dynamics model under the influence of lateral wind, such as yaw rate, lateral velocity, lateral acceleration, steering wheel angle, longitudinal speed, lateral offset, roll angle, and sideslip angle.

[0045] To achieve realistic vehicle motion response under crosswind conditions, a multibody dynamics model was established based on pre-set vehicle geometry, mass, and suspension layout parameters. This model included a vehicle body model, suspension model, steering model, and tire model. The tire model could employ a Magic Formula (MF) model, such as the MF-Tyre model, which considers tire lateral stiffness, longitudinal slip, road adhesion coefficient, and nonlinear saturation characteristics. The suspension model could use a high-frequency bushing model to accurately reflect the flexibility of the force transmission path and frequency response characteristics. The steering model could use a steer-by-wire model that completely decouples the existing steering wheel assembly from the steering actuator (motor-driven rack), or an existing rack and pinion steering system model including a power steering mechanism. The aerodynamic forces acting on the test vehicle in the first simulation software were coupled with the multibody dynamics model to form an aerodynamic-structural dynamic response closed loop.

[0046] S4: Synchronously feed back the vehicle operation data to the driving simulator so that the driver in the driving simulator can determine the operating status of the vehicle multibody dynamics model after being subjected to the lateral wind force; wherein, the vehicle multibody dynamics model is communicatively connected to the driving simulator, and the vehicle multibody dynamics model is a simulation model controlled by the driving simulator.

[0047] In one or more embodiments of this specification, the server can convert a vehicle multibody dynamics model into a pre-defined real-time vehicle model that can run on a driving simulator through model reduction and real-time solution algorithms. Communication and signal exchange are achieved through software-in-the-loop (SiL) and hardware-in-the-loop (HiL) interfaces. Thus, the server can synchronously feed back the vehicle operation data of the vehicle multibody dynamics model to the driving simulator, enabling the driver in the driving simulator to determine the operating status of the vehicle multibody dynamics model after being subjected to lateral wind forces. The vehicle multibody dynamics model is communicatively connected to the driving simulator, and is a simulation model controlled by the driving simulator.

[0048] Subsequently, in one or more embodiments of this specification, through visual, motion, and force feedback in the driving simulator, the driver can perceive the dynamic changes of the vehicle caused by crosswind interference in real time and perform subjective scoring evaluation. The server can obtain the driver's evaluation results of the vehicle crosswind stability test in the driving simulator, including lateral stability score and driving confidence score. Then, based on the evaluation results and vehicle operation data from the vehicle multibody dynamics model, the subjective-objective consistency correlation results of the vehicle crosswind stability test are determined, achieving subjective-objective consistency calibration.

[0049] In one or more embodiments of this specification, in the first simulation software, after applying crosswind force to the test vehicle, the server can also determine the drag (i.e., aerodynamic drag, which is the aerodynamic force component generated by the air on the test vehicle in the opposite direction to the vehicle's forward direction), lateral force, lift, pitch moment, roll moment, yaw moment, and other data experienced by the test vehicle. Then, in the second simulation software, the server can apply the corresponding drag, lateral force, lift, pitch moment, roll moment, and yaw moment to the pre-built vehicle multibody dynamics model to determine the vehicle's operating data. It is worth noting that the vehicle operating data also includes the lateral displacement and other trajectory data experienced by the vehicle multibody dynamics model in the second simulation software, which is finally fed back into the driving simulator, allowing the driver to experience the vehicle's displacement changes after experiencing crosswinds.

[0050] Figure 3 This is a schematic diagram of a driving simulator provided in this specification. Figure 3 As shown, the room features a large curved screen displaying road conditions. In front of this screen, a car-like driving simulator responds to the vehicle's multibody dynamics model's trajectory data, including lateral displacement, experienced in the second simulation software. It can also move along a lateral track to simulate lateral displacement caused by crosswinds.

[0051] This specification provides a virtual test method for road vehicle crosswind sensitivity based on a driving simulator. First, a virtual test scenario for road vehicle crosswind sensitivity is preset according to crosswind test condition standards, and a gust model of a wind turbine array is constructed. Based on the gust model, computational fluid dynamics (CFD) simulation analysis is performed on the test vehicle to obtain dynamic data of the six aerodynamic components of the vehicle. A multibody dynamics model of the vehicle is constructed, and the six aerodynamic components are dynamically loaded onto the vehicle's center of mass position in the multibody dynamics model using the Simulink platform, establishing an aerodynamic load-vehicle dynamics coupling model. By solving differential algebraic equations, real-time operating state data of the vehicle under crosswind conditions is obtained. Simultaneously, the vehicle motion state information from the multibody dynamics model is synchronously fed back to the driving simulator, allowing the driver in the cockpit to perceive the vehicle's driving response under crosswind disturbances in an immersive virtual environment, thereby achieving virtual testing of vehicle crosswind stability. This solution organically integrates crosswind aerodynamic load simulation, multibody dynamic response calculation, and driving simulator-based in-the-loop testing, filling the technological gap in virtualization of vehicle crosswind sensitivity testing. It enables crosswind stability verification and parameter optimization of vehicle dynamics models in the early stages of vehicle design and development, effectively shortening the overall vehicle development cycle and reducing the costs of later real-vehicle testing and structural modifications. Based on the virtual test method for vehicle crosswind stability based on a driving simulator provided in one or more embodiments of this specification, following the same idea, this specification also provides a corresponding virtual test device for vehicle crosswind stability based on a driving simulator, such as... Figure 4 As shown.

[0052] Figure 4 This specification provides a schematic diagram of a virtual test device for vehicle crosswind stability based on a driving simulator, which specifically includes: The construction module 400 is used to construct a virtual test scenario including a wind turbine array and a test vehicle in the first simulation software according to a preset crosswind test condition standard; and to construct a gust model of the wind turbine array. The first test module 402 is used to conduct a vehicle crosswind stability test on the test vehicle according to the virtual test scenario. When the test vehicle enters the crosswind area caused by the wind turbine array, the gust model is used to determine the lateral wind force applied to the test vehicle in the crosswind area. The second test module 404 is used to apply the lateral wind force to a pre-built vehicle multibody dynamics model in the second simulation software and determine the vehicle operation data of the vehicle multibody dynamics model. Feedback module 406 is used to synchronously feed back the vehicle operation data to the driving simulator, so that the driver in the driving simulator can determine the operation status of the vehicle multibody dynamics model after being subjected to the lateral wind force; wherein, the vehicle multibody dynamics model is communicatively connected to the driving simulator, and the vehicle multibody dynamics model is a simulation model controlled by the driving simulator.

[0053] This specification also provides a computer-readable storage medium storing a computer program that can be used to execute the above-described... Figure 1 A virtual test method for vehicle crosswind stability based on a driving simulator is provided.

[0054] This instruction manual also provides Figure 5 The diagram shows a schematic structural representation of the electronic device. Figure 5 As shown, at the hardware level, this electronic device includes a processor, internal bus, network interface, memory, and non-volatile memory, and may also include other hardware required for business operations. The processor reads the corresponding computer program from the non-volatile memory into memory and then runs it to achieve the above. Figure 1 A virtual test method for vehicle crosswind stability based on a driving simulator is provided.

[0055] Of course, in addition to software implementation, this specification does not exclude other implementation methods, such as logic devices or a combination of hardware and software. In other words, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0056] In the 1990s, improvements to a technology could be clearly distinguished as either hardware improvements (e.g., improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the methodology). However, with technological advancements, many methodological improvements today can be considered direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved methodology into the hardware circuit. Therefore, it cannot be said that a methodological improvement cannot be implemented using hardware physical modules. For example, a Programmable Logic Device (PLD) (such as a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by the user programming the device. Designers can program and "integrate" a digital system onto a PLD themselves, without needing chip manufacturers to design and manufacture dedicated integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing integrated circuit chips, this programming is mostly implemented using "logic compiler" software. Similar to the software compiler used in program development, the original code before compilation must also be written in a specific programming language, called a Hardware Description Language (HDL). There are many HDLs, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, and RHDL (Ruby Hardware Description Language). Currently, the most commonly used are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also understand that by simply performing some logic programming on the method flow using one of these hardware description languages ​​and programming it into an integrated circuit, the hardware circuit implementing the logical method flow can be easily obtained.

[0057] The controller can be implemented in any suitable manner. For example, it can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicon Labs C8051F320. A memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also recognize that, in addition to implementing the controller in purely computer-readable program code form, the same functionality can be achieved by logically programming the method steps to make the controller take the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the means included therein for implementing various functions can also be considered as structures within the hardware component. Alternatively, the means for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0058] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or any combination of these devices.

[0059] For ease of description, the above devices are described in terms of function, divided into various units. Of course, in implementing this specification, the functions of each unit can be implemented in one or more software and / or hardware components.

[0060] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0061] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0062] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0063] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0064] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0065] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0066] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic or disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0067] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0068] Those skilled in the art will understand that the embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, this specification may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this specification may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0069] This specification can be described in the general context of computer-executable instructions that are executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This specification can also be practiced in distributed computing environments, where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0070] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0071] The above description is merely an embodiment of this specification and is not intended to limit this specification. Various modifications and variations can be made to this specification by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this specification should be included within the scope of the claims of this specification.

Claims

1. A virtual test method for vehicle crosswind stability based on a driving simulator, characterized in that, include: S1. Based on the preset crosswind test condition standards, a virtual test scenario including a wind turbine array and a test vehicle is constructed in the first simulation software; And constructing a gust model for the wind turbine array; S2. Based on the virtual test scenario, conduct a vehicle crosswind stability test on the test vehicle. When the test vehicle enters the crosswind area caused by the wind turbine array, determine the lateral wind force applied to the test vehicle in the crosswind area based on the gust model. S3. In the second simulation software, the lateral wind force is applied to the pre-built vehicle multibody dynamics model to determine the vehicle operation data of the vehicle multibody dynamics model; S4. The vehicle operation data is synchronously fed back to the driving simulator so that the driver in the driving simulator can determine the operating status of the vehicle multibody dynamics model after being subjected to the lateral wind force; wherein, the vehicle multibody dynamics model is communicatively connected to the driving simulator, and the vehicle multibody dynamics model is a simulation model controlled by the driving simulator.

2. The virtual test method for vehicle crosswind stability based on a driving simulator as described in claim 1, characterized in that, The expression for the gust model described in S1 is: in, The crosswind speed caused by the aforementioned wind turbine array. The time for conducting the crosswind stability test on the test vehicle; The time it takes for the test vehicle to enter the crosswind area created by the wind turbine array; The time it takes for the test vehicle to leave the crosswind area caused by the wind turbine array; The time required for the preset crosswind speed to increase from zero to its maximum value (or decrease from its maximum value to zero); This is the preset maximum crosswind speed.

3. The virtual test method for vehicle crosswind stability based on a driving simulator as described in claim 2, characterized in that, The vehicle multibody dynamics model described in S3 includes a body model, a suspension model, a steering model, and a tire model.

4. The virtual test method for vehicle crosswind stability based on a driving simulator as described in claim 3, characterized in that, The suspension model is a high-frequency bushing model.

5. The virtual test method for vehicle crosswind stability based on a driving simulator as described in claim 3, characterized in that, The tire model is a magic formula model.

6. The virtual test method for vehicle crosswind stability based on a driving simulator as described in claim 1, characterized in that, It also includes step S5: Obtain the driver's evaluation results of the vehicle's crosswind stability test in the driving simulator, the evaluation results including lateral stability score and driving confidence score; Based on the evaluation results and the vehicle operation data, the subjective and objective consistency correlation results of the vehicle crosswind stability test are determined.

7. A virtual test method for vehicle crosswind stability based on a driving simulator as described in claim 2 or 3, characterized in that, S3 specifically includes: In the first simulation software, after applying the lateral wind force to the test vehicle, the drag, lateral force, lift, pitching moment, roll moment, and yaw moment experienced by the test vehicle are determined. In the second simulation software, the drag, the lateral force, the lift, the pitch moment, the roll moment, and the yaw moment are applied to the pre-built vehicle multibody dynamics model to determine the vehicle operation data of the vehicle multibody dynamics model. The vehicle operation data includes yaw rate, lateral velocity, lateral acceleration, steering wheel angle, longitudinal speed, lateral offset, roll angle, and sideslip angle.

8. A virtual test device for vehicle crosswind stability based on a driving simulator, characterized in that, include: The construction module is used to construct a virtual test scenario, including a wind turbine array and a test vehicle, in the first simulation software according to the preset crosswind test condition standards. And constructing a gust model for the wind turbine array; The first test module is used to conduct a vehicle crosswind stability test on the test vehicle according to the virtual test scenario. When the test vehicle enters the crosswind area caused by the wind turbine array, the module determines the lateral wind force applied to the test vehicle in the crosswind area based on the gust model. The second test module is used to apply the lateral wind force to a pre-built vehicle multibody dynamics model in the second simulation software and determine the vehicle operation data of the vehicle multibody dynamics model. The feedback module is used to synchronously feed back the vehicle operation data to the driving simulator, so that the driver in the driving simulator can determine the operating status of the vehicle multibody dynamics model after being subjected to the lateral wind force; wherein, the vehicle multibody dynamics model is communicatively connected to the driving simulator, and the vehicle multibody dynamics model is a simulation model controlled by the driving simulator.

9. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the method described in any one of claims 1 to 7.

10. An electronic device, characterized in that, The method includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method described in any one of claims 1 to 7.

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