Vehicle dynamics model construction method, electronic device, computer-readable storage medium and computer program product

Abstract

This disclosure provides a method for constructing a vehicle dynamics model, an electronic device, a computer-readable storage medium, and a computer program product, relating to the field of vehicle dynamics model construction technology. The method includes: controlling the non-test axle of a heavy-duty vehicle to travel at a constant speed on a real road, and controlling the symmetrical steering of the wheels on both sides of the test axle of the heavy-duty vehicle; collecting lateral working condition data corresponding to each wheel on the test axle of the heavy-duty vehicle during vehicle testing; determining the wheel's self-aligning torque based on the measured lateral force, measured longitudinal force, and measured roll moment in the lateral working condition data; determining the wheel's longitudinal slip ratio and lateral slip ratio through the wheel speed, vehicle longitudinal speed, and tire slip angle in the lateral working condition data; and identifying the relationship between various parameters in the tire lateral dynamics model based on the above. Embodiments of this disclosure can improve the modeling accuracy of vehicle dynamics models.

Description

Technical Field

[0001] This disclosure relates to the field of vehicle dynamics model construction technology, and in particular to a method for constructing a vehicle dynamics model, an electronic device, a computer-readable storage medium, and a computer program product. Background Technology

[0002] This section is intended to provide background or context for the embodiments of this disclosure as set forth in the claims. The description herein is not intended to be a prior art simply because it is included in this section.

[0003] Intelligent driving decision-making, planning, and motion control rely heavily on high-fidelity, high-precision vehicle dynamics models, which need to accurately represent the dynamic response characteristics of real vehicles.

[0004] Current mainstream modeling methods are unable to fully characterize the complex nonlinear and coupled dynamic behavior of vehicles, resulting in large deviations between the model and the actual vehicle dynamics, insufficient accuracy, low model building efficiency, and poor practicality, which seriously restricts the performance of intelligent driving control. Summary of the Invention

[0005] The purpose of this disclosure is to provide a method for constructing vehicle dynamics models, an electronic device, a computer-readable storage medium, and a computer program product, which can improve the modeling accuracy and practicality of vehicle dynamics models.

[0006] Other features and advantages of this disclosure will become apparent from the following detailed description, or may be learned in part from practice of this disclosure.

[0007] This disclosure provides a method for constructing a vehicle dynamics model, including: controlling the non-test axle of a heavy-duty vehicle to travel at a constant speed on a real road; decoupling the control of the test axle from the non-test axle and controlling the symmetrical steering of the wheels on both sides of the test axle; collecting the tire rotation angle, wheel speed, and vehicle longitudinal speed of each wheel on the test axle, wherein the tire slip angle of the wheels on the test axle is equal to the tire rotation angle; and obtaining the measured lateral force of the wheels on the test axle through force sensors installed at the wheels of the test axle. Measured longitudinal force Measured roll moment The lateral force of the wheel on the tested axle is equal to the measured lateral force; this is achieved through the formula... Determine the wheel's return torque. ;in The offset of the main pin inclination. The kingpin caster trail is determined; the longitudinal slip ratio and lateral slip ratio of the tested axle are determined by wheel speed, vehicle longitudinal speed and tire slip angle; a pre-set dimensionless tire lateral force fitting model is used, with wheel lateral force, self-aligning torque, longitudinal slip ratio, lateral slip ratio and tire slip angle as inputs, to identify the wheel lateral adhesion coefficient, tire shape factor, tire trail and lateral slip stiffness in the tire lateral dynamics model, and to obtain the relationship between self-aligning torque and tire slip angle, and the relationship between wheel lateral force and tire slip angle in the tire lateral dynamics model, where the vehicle dynamics model includes the tire lateral dynamics model.

[0008] This disclosure provides a vehicle dynamics model construction device, including: a constant speed control module, which controls the non-tested axle of a heavy-duty vehicle to make the heavy-duty vehicle travel at a constant speed on a real road, decoupling the control of the tested axle from the non-tested axle and controlling the symmetrical steering of the wheels on both sides of the tested axle; a lateral working condition data acquisition module, which can be used to acquire the tire rotation angle, wheel speed, and vehicle longitudinal speed of each wheel on the tested axle, wherein the tire slip angle of the wheels on the tested axle is equal to the tire rotation angle; and a force sensor installed at the wheel of the tested axle to obtain the measured lateral force of the wheel on the tested axle. Measured longitudinal force Measured roll moment The lateral force of the wheel on the tested axle is equal to the measured lateral force; the lateral parameter force determination module can be used to determine the lateral force using the formula... Determine the wheel's return torque. ;in The offset of the main pin inclination. The module includes a caster trailing distance and a lateral dynamics model calibration module. This module uses a pre-defined dimensionless tire lateral force fitting model, taking wheel lateral force, self-aligning torque, longitudinal slip ratio, lateral slip ratio, and tire slip angle as inputs, to identify the wheel lateral adhesion coefficient, tire shape factor, tire trailing distance, and lateral slip stiffness in the tire lateral dynamics model. The module obtains the relationship between the self-aligning torque and tire slip angle, and the relationship between the wheel lateral force and tire slip angle in the tire lateral dynamics model. The vehicle dynamics model includes the tire lateral dynamics model.

[0009] This disclosure provides an electronic device comprising: a memory and a processor; the memory for storing computer program instructions; and the processor for calling the computer program instructions stored in the memory to implement the vehicle dynamics model construction method described above.

[0010] This disclosure provides a computer-readable storage medium storing computer program instructions to implement the vehicle dynamics model construction method as described in any of the preceding embodiments.

[0011] This disclosure provides a computer program product or computer program that includes computer program instructions stored in a computer-readable storage medium. The computer program instructions are read from the computer-readable storage medium, and the processor executes the computer program instructions to implement the aforementioned vehicle dynamics model construction method.

[0012] The vehicle dynamics model construction method, electronic device, computer-readable storage medium, and computer program product provided in this disclosure rely on a test scheme of uniform speed driving on a real road and decoupled symmetrical steering of the tested axle. By using wheel-side force sensors to accurately collect multi-dimensional force and motion parameters of the wheels, and after eliminating the additional torque of the kingpin structure, the true self-aligning torque of the tire is calculated. Combined with slip ratio and sideslip angle data, key parameters of the dimensionless tire lateral force model are identified. Without the need for a dedicated large chassis test bench, the mapping relationship between tire lateral force, self-aligning torque, and sideslip angle can be accurately calibrated under real driving conditions. This significantly improves the modeling accuracy and parameter calibration efficiency of the tire dynamics model of heavy-duty vehicles, and finally obtains a whole vehicle dynamics model that fits the dynamic characteristics of the real vehicle, effectively supporting the simulation development of decision planning and motion control algorithms for intelligent driving vehicles.

[0013] It should be understood that the above general description and the following detailed description are merely exemplary and do not limit this disclosure. Attached Figure Description

[0014] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure. It is obvious that the drawings described below are merely some embodiments of this disclosure, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0015] Figure 1 A schematic diagram of a scenario that can be applied to the vehicle dynamics model construction method or vehicle dynamics model construction apparatus in the embodiments of this disclosure is shown.

[0016] Figure 2 This is a flowchart illustrating a method for constructing a vehicle dynamics model according to an exemplary embodiment.

[0017] Figure 3 This is a flowchart illustrating a method for constructing a longitudinal dynamics model of a tire according to an exemplary embodiment.

[0018] Figure 4 This is a flowchart illustrating a method for determining suspension dynamic parameters according to an exemplary embodiment.

[0019] Figure 5 This is a flowchart illustrating yet another method for determining suspension dynamic parameters according to an exemplary embodiment.

[0020] Figure 6 This is a flowchart illustrating a method for determining tire lateral stiffness according to an exemplary embodiment.

[0021] Figure 7 This is a flowchart illustrating a method for determining the basic parameters of a wheel under test, according to an exemplary embodiment.

[0022] Figure 8 This is a flowchart illustrating a method for determining hydraulic characteristics according to an exemplary embodiment.

[0023] Figure 9 This is yet another method for constructing a vehicle dynamics model, as illustrated in an exemplary embodiment.

[0024] Figure 10 This is a schematic diagram of an oil-gas suspension test platform according to an exemplary embodiment.

[0025] Figure 11 This is a flowchart illustrating a bench testing method according to an exemplary embodiment.

[0026] Figure 12 This is a block diagram illustrating a vehicle dynamics model building apparatus according to an exemplary embodiment.

[0027] Figure 13 A schematic diagram of the structure of an electronic device suitable for implementing embodiments of the present disclosure is shown.

[0028] The reference numerals in the attached figures are explained below.

[0029] 100: System architecture for implementing the vehicle dynamics model construction method; 101: First terminal device; 102: Second terminal device; 103: Third terminal device; 104: Network; 105: Server; 1200: Vehicle dynamics model building device; 1201: Uniform speed control module; 1202: Symmetrical steering control module; 1203: Lateral working condition data acquisition module; 1204: Wheel lateral force determination module; 1205: Lateral dynamics model calibration module; 1300: Electronic device for building vehicle dynamics model; 1301: CPU; 1302: ROM; 1303: RAM; 1304: Bus; 1305: I / O interface; 1306: Input section; 1307: Output section; 1308: Storage section; 1309: Communication section; 1310: Driver; 1311: Removable medium. Detailed Implementation

[0030] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the embodiments set forth herein; rather, they are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted.

[0031] To better understand the above-mentioned objectives, features and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of the present disclosure can be combined with each other.

[0032] The technical solution provided in this application can be used for the development and testing of a new type of driving unit (corner module) for intelligent electric vehicle drive-by-wire chassis. Specifically, it involves a systematic and hierarchical dynamics test and parameter calibration method for a three-axle corner module heavy-duty vehicle with highly integrated and independently controlled drive / braking / steering / suspension wheel ends, which is used to construct a high-fidelity unified vehicle dynamics model.

[0033] In recent years, the development of advanced intelligent driving systems has placed higher demands on the underlying execution architecture of vehicles. Traditional mechanically connected chassis architectures are no longer sufficient to meet the needs of intelligent driving systems for precise vehicle status perception and millisecond-level execution. Against this backdrop, the X-by-Wire Chassis is considered a core development direction for the future of intelligent vehicles. By integrating and modularizing functions such as driving, braking, steering, and suspension, the X-by-Wire Chassis eliminates most mechanical connections, enabling independent, rapid, and precise control of each execution unit, thus providing powerful underlying execution capabilities for intelligent driving algorithms.

[0034] The new Corner Module is the culmination of the steer-by-wire chassis concept. It highly integrates hub motors (drive), steer-by-wire actuators (steering), brake-by-wire actuators (braking), and active / semi-active suspension (suspension) into a modular assembly near the wheels, forming a new generation chassis architecture of "modular design + independent full-range control." For multi-axle heavy-duty vehicles, the Corner Module technology not only significantly improves their maneuverability in complex scenarios (such as ports, mines, and large equipment transportation), but also provides intelligent driving systems with control freedom and performance reach far exceeding that of traditional vehicles. It is a key technological path to solving the problem of adaptability to extreme working conditions in heavy-duty vehicles.

[0035] The complexity of corner module heavy-duty vehicles also presents challenges to the establishment of dynamic models. The decision planning and motion control algorithms of intelligent driving rely heavily on a high-fidelity, high-precision unified vehicle dynamics model. This model must be able to accurately characterize the dynamic characteristics, nonlinear behaviors (such as tire nonlinear dynamic characteristics, actuator saturation and delay) of each subsystem (drive, steering, braking, suspension) within each corner module, as well as the complex force-motion coupling relationships between modules.

[0036] Existing dynamics modeling methods for distributed drive and independently steering vehicles are mostly based on simplified single-track models, pure geometric Ackerman steering, and rigid body assumptions. These methods fail to fully characterize the unique multi-degree-of-freedom, highly nonlinear, and rapidly time-varying intrinsic mechanisms of angular modules. In particular, they lack refined modeling of the dynamic response characteristics of actuators (such as hub motors and steering motors), the nonlinear characteristics of hydropneumatic suspensions, and the mechanical properties of tires under real heavy-load conditions. This deficiency prevents the models from accurately reflecting the behavior of real vehicles under actual inputs, severely limiting the performance limits and safety boundaries of intelligent driving cooperative control strategies (such as torque vectoring, trajectory tracking, and stability control).

[0037] Building a high-fidelity model requires obtaining accurate model parameters. Existing parameter calibration methods mainly include single-component bench testing and whole-vehicle road testing, which have at least the following limitations.

[0038] Bench testing, while capable of isolating and testing individual components (such as motors and shock absorbers), cannot reproduce the real dynamic load transfer process during vehicle operation, nor can it reflect the complex interaction characteristics between tires and real road surfaces. For large-sized, high-cost heavy-duty vehicle-specific tires and components, the existence of matching benches, as well as the cost and feasibility of bench testing, become major obstacles.

[0039] Traditional vehicle road tests, while conducted in real-world environments, involve highly coupled longitudinal and lateral forces across axles and wheels, compounded by random road surface disturbances and driver input noise. This makes it difficult to effectively decouple and separate the dynamic contributions of specific corner modules or subsystems. Consequently, accurately identifying the parameters of individual modules from massive amounts of mixed data becomes extremely challenging.

[0040] Therefore, the industry currently lacks a systematic and operable comprehensive calibration process and testing system specifically for corner module configuration heavy-duty vehicles, which has become a key technical obstacle restricting the construction of high-precision vehicle models and the implementation of intelligent driving collaborative control strategies.

[0041] In the process of acquiring and analyzing tire force data in related technologies, the failure of the force analysis basis is often caused by the lack of pure working condition and coupling data. The specific reasons can include at least the following.

[0042] 1. In the road test of multi-axle heavy-duty vehicles, the longitudinal force and lateral force of each axle are strongly coupled. Steering action will inevitably cause the whole vehicle to yaw. Acceleration and deceleration action will inevitably be accompanied by the influence of wheel rotational inertia. Moreover, the load transfer effect is prominent. It is impossible to separate the pure tire force generated by tire lateral / longitudinal slip. The force analysis data is mixed with coupling interference and road noise.

[0043] 2. Bench tests are separated from real vehicle heavy loads and real road surface adhesion conditions. The tire force values ​​have systematic deviations from the actual vehicle operating conditions and cannot be used as effective input for numerical modeling.

[0044] 3. The lack of numerical decoupling methods for inter-axle motion and tire force makes it impossible to separate the pure lateral force, pure longitudinal force, and self-aligning torque of a single axle and a single tire from the vehicle's composite motion data, resulting in distorted force analysis results.

[0045] In related technologies, the accuracy of numerical modeling and force analysis models is insufficient to support intelligent driving.

[0046] In the force analysis of related technologies, without pure tire force data to support it, the fitting error of the mechanical characteristics of lateral force-slip angle, longitudinal force-slip ratio, and self-aligning torque-slip angle is large, and it is impossible to accurately characterize the nonlinear force characteristics of heavy-duty tires. In the numerical modeling of related technologies, the tire dynamics numerical model based on coupled data fitting is not adapted to heavy-load variable load conditions. The numerical calculation results deviate greatly from the actual vehicle dynamic response, which cannot meet the modeling requirements of intelligent driving control algorithms.

[0047] For multi-axle heavy-duty vehicles with distributed drive, independent steering, electro-hydraulic braking, and hydropneumatic suspension, whose core functional units are integrated corner modules, the characteristics under complex working conditions are not yet clear. Existing technologies lack a set of high-precision dynamic parameter testing schemes and calibration methods, making it difficult to establish a unified dynamic model. This application provides a method and apparatus for calibrating the dynamic characteristics and parameters of corner module heavy-duty vehicles, addressing the problem that existing technologies cannot efficiently, systematically, and with high precision calibrate the dynamic parameters of this novel vehicle configuration. It constructs a unified high-fidelity dynamic model, providing fundamental support for the development of collaborative control strategies for three-axle corner module vehicles under intelligent driving and for their related major transportation tasks.

[0048] Below, this application will describe the method for constructing a vehicle dynamics model in conjunction with specific embodiments.

[0049] The exemplary embodiments of this disclosure will now be described in detail with reference to the accompanying drawings.

[0050] Figure 1 A schematic diagram of a scenario that can be applied to the vehicle dynamics model construction method or vehicle dynamics model construction apparatus in the embodiments of this disclosure is shown.

[0051] Please refer to Figure 1 The diagram illustrates an implementation environment provided by an exemplary embodiment of this disclosure.

[0052] like Figure 1 As shown, the vehicle dynamics model construction method implementation system architecture 100 may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0053] Users can use the first terminal device 101, the second terminal device 102, or the third terminal device 103 to interact with the server 105 via the network 104 to receive or send messages, etc. The first terminal device 101, the second terminal device 102, or the third terminal device 103 can be various electronic devices with a display screen and supporting web browsing, including but not limited to smartphones, tablets, laptops, desktop computers, wearable devices, virtual reality devices, smart home devices, etc.

[0054] Server 105 can be a server that provides various services, such as a backend management server that supports the devices operated by users using the first terminal device 101, the second terminal device 102, or the third terminal device 103. The backend management server can analyze and process received requests and other data, and feed the processing results back to the terminal devices.

[0055] A server can be a standalone physical server, a server cluster or a distributed system consisting of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms. This disclosure does not impose any restrictions on this.

[0056] Server 105 can, for example, control the non-tested axles of a heavy-duty vehicle to ensure that the heavy-duty vehicle travels at a constant speed on a real road. The heavy-duty vehicle includes at least three axles, including one tested axle and at least one non-tested axle. Server 105 can, for example, decouple the tested axle from the non-tested axles of the heavy-duty vehicle and control the symmetrical steering of the wheels on both sides of the tested axle. Server 105 can, for example, collect lateral working condition data corresponding to each wheel on the tested axle. Server 105 can, for example, determine the tire return torque and wheel lateral force on the tested axle based on the lateral working condition data. Server 105 can, for example, calibrate the parameters in the tire lateral dynamics model in the vehicle dynamics model corresponding to the heavy-duty vehicle using the return torque and wheel lateral force.

[0057] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Server 105 can be a single physical server or a combination of multiple servers. Depending on actual needs, it can have any number of terminal devices, networks, and servers.

[0058] Under the above system architecture, this disclosure provides a method for constructing a vehicle dynamics model, which can be executed by any electronic device with computing power.

[0059] In some embodiments, the "independent axle trailer method" can be used to calibrate the parameters of the vehicle's mechanical model. For example, the unique advantages of the corner module vehicle platform can be used to construct a real-time test bench under road driving conditions. Specifically, the vehicle is controlled to travel at a constant speed, and at least one axle (the tested axle) is decoupled from the control of the other drive axles. The tested axle is controlled by an independent domain controller (CDCU), while the vehicle control unit (VCU) controls the other axles to maintain the vehicle speed. By applying tire characteristic test excitations such as pure sideslip and pure longitudinal slip to the tested axle, as well as driving / braking / steering step and sinusoidal frequency sweep tests during driving, its dynamic characteristics under real loads are obtained. The key is to control the left and right wheels of the tested axle to perform symmetrical steering of equal magnitude and opposite direction during the test to counteract the yaw moment, keep the vehicle traveling in a straight line, and at the same time make the wheel angle of the tested axle equal to the tire sideslip angle.

[0060] In some embodiments, this application provides a method for constructing a vehicle dynamics model, comprising: controlling the non-tested axle of a heavy-duty vehicle to drive at a constant speed on a real road; decoupling the control of the tested axle from the non-tested axle and controlling the symmetrical steering of the wheels on both sides of the tested axle; acquiring the tire rotation angle, wheel speed, and vehicle longitudinal speed of each wheel on the tested axle, wherein the tire slip angle of the wheel on the tested axle is equal to the tire rotation angle; and obtaining the measured lateral force of the wheel on the tested axle through force sensors installed at the wheels of the tested axle. Measured longitudinal force Measured roll moment Wherein the lateral force of the wheel on the tested axle is equal to the measured lateral force; through the formula Determine the wheel's return torque. ;in The offset of the main pin inclination. The caster trail is determined by the kingpin; the longitudinal slip ratio and lateral slip ratio of the tested axle are determined by the wheel speed, the vehicle longitudinal speed, and the tire slip angle; a preset dimensionless tire lateral force fitting model is used, with the wheel lateral force, self-aligning torque, longitudinal slip ratio, lateral slip ratio, and tire slip angle as inputs, to identify the wheel lateral adhesion coefficient, tire shape factor, tire trail, and lateral slip stiffness in the tire lateral dynamics model, and to obtain the relationship between the self-aligning torque and the tire slip angle, and the relationship between the wheel lateral force and the tire slip angle in the tire lateral dynamics model, wherein the vehicle dynamics model includes the tire lateral dynamics model.

[0061] The technical solutions provided in the above embodiments will now be explained in detail.

[0062] Figure 2 This is a flowchart illustrating a method for constructing a vehicle dynamics model according to an exemplary embodiment. The method provided in this disclosure can be executed by any electronic device with computing power, for example, the method can be executed by the above-described... Figure 1 The execution can be performed by a server or terminal device in the embodiments, or it can be performed by both a server and a terminal device. In the following embodiments, the server is used as the execution subject for illustration, but this disclosure is not limited to this.

[0063] Reference Figure 2 The vehicle dynamics model construction method provided in this disclosure may include the following steps.

[0064] Step S202: Control the non-tested axle of the heavy-duty vehicle so that the heavy-duty vehicle always travels at a constant speed on the real road; the heavy-duty vehicle includes at least three axles, and the at least three axles include one tested axle and at least one non-tested axle.

[0065] In some embodiments, the heavy-duty vehicle can be a multi-axle vehicle with an integrated corner module as its core, which has distributed drive, independent steering, electro-hydraulic braking and hydropneumatic suspension functions; each axle can be controlled independently, for example, the domain controller can execute steering, driving and braking respectively; furthermore, each wheel can also achieve completely independent control of steering, driving and braking.

[0066] In some embodiments, heavy-duty vehicles may adopt a modular architecture, with the entire vehicle consisting of multiple corner module assemblies. Each corner module highly integrates the drive motor, steering actuator, brake and suspension system near the wheel, thereby achieving independent control of a single wheel and completing the complex dynamic behavior of the entire vehicle through the collaborative work of multiple corner modules.

[0067] In some embodiments, heavy-duty vehicles can be tested under various load conditions, such as no load, loaded load, and fully loaded load.

[0068] In some embodiments, the heavy-duty vehicle may be a three-axle or more-axle vehicle. In this application, a three-axle heavy-duty vehicle will be used as an example for explanation and description, but this application is not limited thereto.

[0069] In some embodiments, a certain type of axle of a heavy-duty vehicle (such as the middle second axle) can be used as the tested axle, and axles other than the tested axle (such as the first axle and the third axle) can be used as non-tested axles.

[0070] In some embodiments, by controlling the non-tested axle of the heavy-duty vehicle, the uniform speed movement of the heavy-duty vehicle is executed to achieve a constant vehicle speed test condition on a real road.

[0071] Step S204: Decouple the tested axle of the heavy-duty vehicle from the non-tested axle and control the wheels on both sides of the tested axle to symmetrically steer.

[0072] In some embodiments, the vehicle control unit (VCU) can control the first and third axles (e.g., control the corner modules corresponding to the first and third axles) and other non-tested axles to maintain a constant vehicle speed to provide the main driving force, while the control authority of the tested axle (such as the second axle) is completely handed over to the independent domain controller (Chassis Domain Control Unit, CDCU) to achieve control decoupling.

[0073] In some embodiments, the domain controller described above can send equal-sized but opposite-direction steering angle commands (such as the left wheel) to the left and right wheels of the axle under test. Right wheel This causes symmetrical "toe-in steering" on both sides of the wheel, thereby utilizing the principle that the yaw moment generated by the lateral force of the wheel at the center of gravity cancels each other out, ensuring that the vehicle maintains straight-line driving while the steering angle of the wheel on the measured axle can be directly regarded as the tire's slip angle.

[0074] Step S206: Collect lateral working condition data corresponding to each wheel on the axle under test.

[0075] In some embodiments, lateral condition data may include at least one of the following: wheel angle as excitation input (which can be directly measured by a wheel-end angle sensor and is equivalent to tire slip angle under the test conditions), steering motor output torque as mechanical response (which can be used to calculate the tire wheel lateral force and return torque), and lateral acceleration, yaw rate (measured by an inertial measurement unit IMU to verify the vehicle's straight-line driving state and force balance) and current vehicle speed as verification and boundary conditions.

[0076] In some embodiments, lateral condition data may include tire slip angle, wheel speed, tire rolling radius, and vehicle longitudinal speed, wherein the tire slip angle of the wheel on the tested axle is equal to the tire slip angle. .

[0077] The aforementioned lateral operating condition data can be obtained directly from the vehicle's control center.

[0078] In some embodiments, collecting lateral working condition data corresponding to each wheel on the axle under test may further include the following steps: obtaining the measured lateral force of the axle under test through a force sensor (such as a six-component force sensor) installed at the wheel of the axle under test. Measured longitudinal force Measured roll moment Wherein the wheel lateral force is equal to the measured lateral force, and the wheel longitudinal force is equal to the measured longitudinal force.

[0079] Step S208: Determine the return torque of the tires and the lateral force of the wheels on the tested axle based on the lateral working condition data of the tested axle.

[0080] In some embodiments, the wheel angle recorded during symmetrical steering can be directly determined as the tire slip angle of that axle.

[0081] In some embodiments, the output torque feedback of the steering motor can be used, combined with the known transmission ratio of the steering system reduction mechanism and the kingpin positioning parameters, to convert the torque into a self-aligning torque and a wheel lateral force acting on the tire through mechanical calculation, thereby establishing the correspondence between the slip angle and the tire force (such as the self-aligning torque and the wheel lateral force), providing core data pairs for subsequent model parameter calibration.

[0082] In some embodiments, the measured lateral force on the wheel of the axle under test is obtained by a six-component force sensor installed at the wheel of the axle under test. Measured longitudinal force Measured roll moment The lateral force of the wheel is equal to the measured lateral force.

[0083] Step S210: The parameters in the tire lateral dynamics model of the vehicle dynamics model corresponding to the heavy-duty vehicle are calibrated by the return torque and wheel lateral force.

[0084] In some embodiments, calibrating the parameters in the tire lateral dynamics model of the vehicle dynamics model corresponding to a heavy-duty vehicle using the self-aligning torque and wheel lateral force may include the following steps: using formulas Determine the wheel's return torque. ;in Given the known kingpin inclination offset, Given the known kingpin caster trail; In some embodiments, calibrating the parameters in the tire lateral dynamics model of the vehicle dynamics model corresponding to the heavy-duty vehicle using the self-aligning torque and the wheel lateral force may include the following steps: determining the tire slip ratio of the wheel using the wheel speed, the tire rolling radius, and the vehicle longitudinal speed. ; through formula Determine the longitudinal slip ratio of the wheel And through the formula Determine the lateral slip ratio of the wheel. ;in It is the tire slip angle; through the fitting formula , , , Identify the restoring torque respectively and the tire slip angle The relationship, the lateral force and the tire slip angle The relationship; among which It is a dimensionless lateral force; It is a dimensionless lateral slip ratio; It is the lateral shape factor, which is the parameter to be identified; It is the lateral adhesion coefficient, which is the parameter to be identified; It is a vertical load; This is tire trail distance, a parameter to be identified. It is the lateral slip stiffness.

[0085] This application proposes a method for constructing vehicle dynamics models (specifically, a numerical modeling and force analysis method for tire dynamics of three-axle heavy-duty vehicles using a modular approach). It establishes a numerical decoupling method for inter-axle motion and tire forces in multi-axle heavy-duty vehicles, extracting uncoupled tire force data for pure sideslip and pure longitudinal slip conditions from real-vehicle driving data; achieving accurate mechanical analysis of tire lateral force, longitudinal force, and self-aligning torque; and constructing a high-fidelity numerical model of heavy-duty tire dynamics based on pure real-vehicle data, thus solving the problems of low accuracy and poor adaptability to operating conditions in existing models.

[0086] In some embodiments, a tire six-component force sensor can be configured on the target axle wheel as a means of obtaining the true value of tire force. It directly measures the longitudinal vertical force and the torque about the x, y, and z axes of the tire. This six-component force sensor can measure three forces (forces in the x, y, and z directions) and three torques acting on the center of the wheel. , ,as well as This consists of six components, which can completely describe all the forces and torques transmitted between the tire and the ground. Among them, torque... (Rolling moment, about the x-axis) is the torque that causes the wheel to reverse in the direction of travel; torque (Rolling resistance torque, about the y-axis) The torque that opposes the rolling of a wheel; torque (Returning torque, about the z-axis) is the steering torque that returns the wheels to center.

[0087] In some embodiments, the above-described vehicle dynamics model construction method may include the following.

[0088] 1. Decoupling of the degrees of freedom of independent axle trailers.

[0089] Select one axis, such as the intermediate axis, as the target analysis axis. Use non-target axes, or constraint auxiliary axes, to support the vehicle to travel at a constant speed in a straight line on a real road, thus constructing a mobile test bench environment. Through pre-calculated changes in vehicle weight, analyze and model the tire force characteristics under various load conditions.

[0090] 2. Decoupling of pure lateral force.

[0091] The wheels on both sides of the target axle are constrained by symmetrical steering motion with equal amplitude and opposite direction. Based on the vehicle dynamics equilibrium equation, symmetrical steering ensures that the yaw moments generated by the lateral forces of the two wheels at the vehicle's center of gravity are equal in magnitude, opposite in direction, and cancel each other out. This satisfies the numerical conditions that the vehicle's yaw rate and lateral acceleration are zero, allowing the vehicle to maintain a pure linear steady-state motion. Under the above decoupling conditions, a numerical equivalent relationship between the wheel rotation angle and the tire slip angle is established. The target wheel rotation angle is directly equivalent to the tire slip angle, completely eliminating the coupling interference of yaw motion on the lateral force, and obtaining the numerical conditions for pure slip operation.

[0092] 3. Decoupling of pure longitudinal sliding force.

[0093] The same linearly increasing torque excitation is applied to the wheels on both sides of the target analysis axle, starting from 0 and increasing uniformly until the monitored longitudinal slip ratio of the tires reaches 50%. Under the premise that the auxiliary axle supports the vehicle to always track the constant target speed, the numerical conditions of no lateral motion, no steering action, and only longitudinal tire slip are satisfied. The lateral force coupling interference is removed to obtain the numerical conditions of pure longitudinal slip.

[0094] 4. Decoupled acquisition of tire force data.

[0095] Synchronously collect target analysis axle lateral working condition data—wheel rotation angle (collected by rotation angle sensor), lateral acceleration (collected by inertial measurement unit), yaw rate (collected by inertial measurement unit), lateral force and self-aligning torque output by tire six-component force sensor, and longitudinal slip data (drive motor torque, wheel speed, vehicle speed, and longitudinal force output by tire six-component force sensor). Through force decoupling algorithm, the lateral working condition data is separated into pure lateral force, pure self-aligning torque, and pure longitudinal force data.

[0096] 5. Force analysis and numerical modeling.

[0097] Based on the decoupled tire force data, the force characteristics of tire lateral force-slip angle, longitudinal force-slip ratio, and self-aligning torque-slip angle were analyzed. The tire dynamics model parameters were identified using numerical optimization methods, and a high-fidelity tire numerical dynamics model was constructed.

[0098] In some embodiments, this application also provides a method for tire force analysis of heavy-duty vehicles using a three-axis angle module. This method can acquire uncoupled force data under pure lateral / longitudinal slip conditions based on the physical decoupling characteristics of independent axle trailers, enabling accurate force analysis and dynamic numerical modeling of tire lateral force, longitudinal force, and self-aligning torque. Under the designed decoupling conditions, the relative motion between the wheel center coordinate system and the ground contact coordinate system is locked. This prevents the raw output of the tire's six-component force sensor from being contaminated by the vehicle's motion inertia, allowing the wheel center force to be directly equivalent to a high-precision true value of the tire ground contact force through simple geometric offset correction (explicit transformation). In this state, the originally complex, nonlinear, and difficult-to-determine mapping degenerates into a simple algebraic mapping, which is unattainable for traditional vehicles in non-decoupled free-roaming conditions.

[0099] In some embodiments, the above-described triaxial angle module heavy-duty vehicle tire force analysis method may include the following process.

[0100] 1. Lateral force calculation.

[0101] In pure lateral force decoupling, the direction of the tire lateral force in the tire coordinate system is perpendicular to the tire's midline plane, and the tire slip angle is the angle between the tire's midline plane and the actual velocity direction. The motion constraints proposed in this application can isolate the effects of yaw rate and lateral acceleration and their resulting load transfer, greatly simplifying accurate tire state and force analysis. The tire rotation angle is equivalent to the tire slip angle (…). The tire six-component force sensor measures the wheel center lateral force, which is equivalent to the tire lateral force. ).

[0102] in, This refers to the tire slip angle. For the turning angle of the wheel, The lateral force at the tire contact patch is the target modeling value. The lateral force at the center of the wheel is the sensor output value.

[0103] 2. Calculation of longitudinal force on wheels.

[0104] In the pure longitudinal slip force decoupling experiment, under the premise of maintaining a constant speed constraint, the effects of longitudinal acceleration and its resulting pitch motion and load transfer are removed. The target shaft slip ratio is only related to its torque excitation. The slip ratio is calculated by outputting the speed data and vehicle speed data from the motor encoder. The longitudinal force at the wheel center measured by the tire six-component force sensor (the measured longitudinal force) is equivalent to the wheel longitudinal force ( ).in The target modeling value is the longitudinal force at the tire contact point (wheel longitudinal force). The value output by the sensor represents the longitudinal force (measured longitudinal force) at the center of the wheel.

[0105] In some embodiments, it can be achieved through Solving for slip ratio .in, This refers to the tire slip ratio; The wheel speed; The tire's rolling radius; Vehicle longitudinal speed.

[0106] 3. Calculation of backing torque.

[0107] The torque measured at the wheel center by the tire's six-component force sensor is equivalent to the linear superposition of the tire's self-aligning torque and the torques generated by the longitudinal and lateral forces with respect to the kingpin's geometric positioning parameters. For details, please refer to the formula. .in, The target modeling value is the self-aligning torque at the tire contact point. The sensor output value represents the torque around the z-axis at the center of the wheel. Given the kingpin inclination offset and known vehicle parameters; The kingpin caster trail is a known parameter of the vehicle.

[0108] By solving the above data, we can obtain the data shown in Table 1.

[0109] Table 1. Data that can be collected from pure lateral slip and pure longitudinal slip experiments.

[0110] Note: In the table, “√” indicates that the corresponding data can be collected for this type of experiment; “—” indicates that this data will not be collected for this experiment.

[0111] 4. Force characteristic analysis.

[0112] Based on the pure tire force data obtained through decoupling, characteristic curves of lateral force-slip angle, longitudinal force-slip ratio, and self-aligning torque-slip angle can be plotted respectively. Abnormal data points such as road noise and sensor drift are removed, and smoothing filtering is used to retain the nonlinear saturation characteristics of heavy-duty tires under large lateral slip and large slip ratio. By comparing the force characteristic curves under different vertical loads, the influence of load on tire stiffness, saturation force, peak slip ratio / slip angle can be clarified, providing accurate input for subsequent model parameter identification.

[0113] After obtaining the data shown in Table 1, this application can use the three-axis angle module heavy-duty vehicle tire dynamics numerical modeling method to construct a numerical model.

[0114] In some embodiments, a dimensionless longitudinal slip ratio can be defined first. Dimensionless lateral slip ratio Overall slip ratio .in, It can be the lateral slip stiffness of the tire, which can be achieved through... Sure; It can be the longitudinal slip stiffness of the tire, which can be achieved through... Sure.

[0115] For pure lateral dynamics of the tire, the relationship between lateral force and self-aligning torque and tire slip angle can be identified using pure lateral condition data. Specifically, this can be achieved through fitting formulas. Identify the relationship between lateral force and self-aligning torque and tire slip angle.

[0116] in: Dimensionless lateral force Dimensionless lateral slip ratio Lateral shape factor, which is the parameter to be identified.

[0117] In some embodiments, the lateral force can be calculated using dimensionless lateral force. and the restoring torque .

[0118] in, as well as .

[0119] in: Lateral adhesion coefficient, a parameter to be identified; Vertical load; Tire trail distance is a parameter to be identified.

[0120] For pure longitudinal tire dynamics, the relationship between longitudinal force and slip ratio can be identified using pure longitudinal skidding test data, for example, through fitting formulas. Identify the relationship between longitudinal force and slip ratio.

[0121] in: : Dimensionless longitudinal force; : Dimensionless longitudinal slip ratio; : Vertical shape factor, which is the parameter to be identified.

[0122] Calculation of longitudinal force using dimensionless longitudinal force .

[0123] in: Longitudinal adhesion coefficient, a parameter to be identified; Vertical load.

[0124] In some embodiments, the true value of the pure tire force obtained from decoupled tests (pure sideslip test, pure longitudinal slip test) can be used as the target value, and the least squares method can be used for optimization: set the set of parameters to be identified for the lateral force, longitudinal force, and self-aligning moment model (stiffness coefficient, saturation coefficient, shape factor, etc.); construct the objective function of the error between the simulation output and the experimental true value; iteratively optimize the parameters so that the root mean square error (RMSE) between the model output force and the sensor measured force is less than a set threshold.

[0125] In some embodiments, the integrated model can be embedded into a vehicle dynamics simulation environment, inputting real vehicle driving state quantities (vehicle speed, wheel speed, steering angle, load), and outputting real-time results of tire force and self-aligning torque; By comparing the simulation response with the actual vehicle test data, some parameters or model structures are iteratively adjusted until the simulation and test data match well.

[0126] In some embodiments, a real-vehicle bench testing method called the "independent axle trailer method" is proposed. This method does not require a traditional fixed test bench, but directly utilizes the platform characteristics of the corner module heavy-duty vehicle itself to construct a dynamic and reconfigurable "mobile test bench" during actual road driving, thereby conducting accurate dynamic characteristic tests on the tested axle (or corner module) under real load and tire-road interaction conditions.

[0127] The following section describes how to conduct tire testing in the "independent axle trailer method".

[0128] First, a pure lateral deviation test can be performed on the tire.

[0129] The following explains the experimental principle of the pure bias test: The first and third axles provide driving force and counteract the driving resistance to achieve uniform speed driving, while the wheels on both sides of the intermediate axle steer symmetrically and satisfy the following conditions. .in, The turning angle of the left wheel of the measured axle. : The turning angle of the wheel on the right side of the axle being measured.

[0130] In this driving mode, the yaw rates generated by the lateral forces of the two wheels acting on the vehicle's center of gravity cancel each other out. According to relevant definitions, the steering angle when driving steadily forward is the tire slip angle. The return torque and wheel lateral forces can be calculated through steering motor torque feedback and the transmission ratio of the reduction mechanism.

[0131] Figure 3 This is a flowchart illustrating a method for constructing a longitudinal dynamics model of a tire according to an exemplary embodiment.

[0132] In some embodiments, the vehicle dynamics model may further include a tire longitudinal dynamics model.

[0133] refer to Figure 3 The above-mentioned method for constructing the longitudinal dynamics model of a tire may also include the following steps.

[0134] In step S302, during the process of the heavy-duty vehicle traveling at a constant speed, the torque of the tested axle is controlled to increase linearly from 0 until the slip ratio of the tested axle reaches a preset threshold.

[0135] In vehicle dynamics, slip ratio is a physical quantity used to describe the degree of wheel slippage during motion. Simply put, it quantifies the difference between the actual distance a wheel rolls and the theoretical distance calculated solely based on the number of wheel rotations.

[0136] In some embodiments, the preset threshold may be 50%, but this application is not limited thereto.

[0137] Step S304: During the torque increase process, collect longitudinal slip condition data corresponding to each wheel on the tested axle.

[0138] In some embodiments, longitudinal slip condition data can refer to the set of core parameters used to calibrate the longitudinal dynamics model of the tire, which are collected synchronously during a pure longitudinal slip test by controlling the torque of the axle under test to increase linearly from zero to a preset slip ratio threshold. These parameters may include the longitudinal force calculated by the torque feedback of the drive motor, the longitudinal slip ratio calculated based on the vehicle speed and wheel speed, and the wheel speed and vehicle speed as the basis for calculation. These data together construct the characteristic curve of the wheel longitudinal force changing with the slip ratio, which is the key basis for identifying model parameters such as longitudinal slip stiffness and longitudinal adhesion coefficient.

[0139] Step S306: Based on the longitudinal slip condition data, determine the longitudinal force and longitudinal slip ratio of each wheel on the tested axle at different times.

[0140] In some embodiments, the longitudinal force can be mechanically calculated based on the real-time torque feedback of the drive motor, combined with known mechanical parameters such as the reduction ratio of the transmission system and the tire rolling radius.

[0141] In some embodiments, the longitudinal slip ratio can be calculated by comparing the difference between the wheel rotation speed (feedback from the motor) and the actual vehicle speed (provided by the inertial measurement unit) at the same moment, which quantifies the degree of wheel slippage relative to the ground.

[0142] Step S308: Calibrate the parameters in the tire longitudinal dynamics model based on the longitudinal force and longitudinal slip ratio at different times.

[0143] In some embodiments, the parameters in the tire longitudinal dynamics model are calibrated based on the measured longitudinal force and longitudinal slip ratio at different times, including: by fitting... , , Identify the relationship between longitudinal force and slip ratio; among which It is the longitudinal adhesion coefficient, which is the parameter to be identified; Vertical load; It is a dimensionless longitudinal force; It is a dimensionless longitudinal slip ratio; It is the vertical shape factor, which is the parameter to be identified.

[0144] Below, this application will explain how to perform a pure longitudinal slip test on a tire in the "independent axle trailer method".

[0145] In some embodiments, the test principle of the above-described pure longitudinal slip test may include: after the first and third axles drive at a specified test speed for a certain period of time, the torque of the second axle increases linearly from 0 until the slip ratio approaches 50%. The torque of the first and third axles is controlled to maintain the test speed based on the target vehicle speed and rotational speed feedback. The longitudinal force can be calculated through the torque feedback of the drive motor and the transmission ratio of the reduction mechanism.

[0146] The following section will explain how to calibrate the parameters in the tire lateral dynamics model within the vehicle dynamics model corresponding to heavy-duty vehicles.

[0147] In some embodiments, the input data for calibrating the parameters in the tire dynamics model can be determined by referring to Table 2, which shows the output data of the tire characteristic testing method. Table 2 shows the parameter data that can be obtained after different vehicle experiments.

[0148] Table 2 Data that can be collected from rolling radius, pure lateral slip, and pure longitudinal slip experiments.

[0149] Note: In the table, “√” indicates that the corresponding data can be collected for this type of experiment; “—” indicates that this data will not be collected for this experiment.

[0150] In addition, the vertical load of each wheel can be recorded. Lateral slip stiffness Longitudinal slip stiffness Lateral friction coefficient longitudinal friction coefficient .

[0151] In some embodiments, for pure lateral dynamics of the tire, pure lateral condition data can be used to identify the relationship between the wheel lateral force and the self-aligning torque and the tire slip angle (see formula (1)).

[0152] (1) : Dimensionless lateral force; : Dimensionless lateral slip ratio; a parameter to be identified related to vertical load; Lateral shape factor, a parameter to be identified related to vertical load.

[0153] In some embodiments, the wheel lateral force can be calculated using dimensionless lateral force. and the restoring torque .in, Lateral adhesion coefficient, a parameter to be identified; Vertical load; Tire trail distance is a parameter to be identified.

[0154] In some embodiments, for pure longitudinal dynamics of the tire, the relationship between the longitudinal force of the wheel and the slip ratio can be identified using pure longitudinal slip test data (refer to formula (2)).

[0155] (2) : Dimensionless longitudinal force; : Dimensionless longitudinal slip ratio, a parameter to be identified that is related to the vertical load; : Longitudinal shape factor, a parameter to be identified related to vertical load.

[0156] In some embodiments, the longitudinal force of the wheel can be calculated using dimensionless longitudinal force. .

[0157] in: Longitudinal adhesion coefficient, a parameter to be identified. Vertical load.

[0158] Figure 4 This is a flowchart illustrating a method for determining suspension dynamic parameters according to an exemplary embodiment.

[0159] refer to Figure 4 The above method for determining suspension dynamic parameters may include the following steps.

[0160] Step S402: Control the heavy-duty vehicle to pass through various vertically excited road surfaces at different speeds under different loads.

[0161] Step S404: Collect sprung condition data of the wheels on the tested axle at different times. The sprung condition data includes at least one of sprung mass, suspension displacement and sprung vertical acceleration.

[0162] Step S406: Filter out the spring working condition data where the vertical acceleration on the spring is 0, and use it as the first working condition data.

[0163] Step S408: Filter the sprung condition data where the suspension displacement is 0, and use it as the second condition data.

[0164] Step S410: Fit the relationship curve between the total suspension force and the suspension displacement based on the first working condition data to fit the equivalent stiffness of the suspension.

[0165] Step S412: Fit the relationship curve between the total suspension force and the vertical acceleration based on the second working condition data to fit the equivalent damping coefficient of the suspension.

[0166] Step S414: Determine the suspension nonlinear characteristic parameter matrix of the heavy-duty vehicle based on the equivalent stiffness and equivalent damping coefficient, so as to construct a vehicle dynamics model based on the suspension nonlinear characteristic parameter matrix.

[0167] Figure 5 This is a flowchart illustrating yet another method for determining suspension dynamic parameters according to an exemplary embodiment.

[0168] refer to Figure 5 The above method for determining suspension dynamic parameters may include the following steps.

[0169] Step S502: Control the heavy-duty vehicle to pass through various vertically excited road surfaces at different speeds under different loads.

[0170] Step S504: Collect sprung condition data of the wheel on the tested axle at different times. The sprung condition data includes at least one of sprung mass, suspension displacement and sprung vertical acceleration.

[0171] Step S506: Based on the sprung mass and sprung vertical acceleration, determine the total suspension force corresponding to each sprung working condition data.

[0172] Step S508: Obtain the first function, which describes the relationship between the total suspension force, suspension displacement, and sprung vertical acceleration; the parameters to be identified in the first function are the nonlinear characteristic parameter matrix of the suspension of the heavy-duty vehicle.

[0173] In some embodiments, the first function described above may refer to formula (3), but this application is not limited thereto.

[0174] Step S510: Fit the first function with the total suspension force, suspension displacement and sprung vertical acceleration to determine the suspension nonlinear characteristic parameter matrix, so as to construct a vehicle dynamics model based on the suspension nonlinear characteristic parameter matrix.

[0175] Below, this application will explain and illustrate how to determine the nonlinear characteristic parameter matrix of the suspension of a heavy-duty vehicle in conjunction with specific embodiments.

[0176] In some embodiments, the input data for determining the suspension nonlinear characteristic parameter matrix of a heavy-duty vehicle may include: single-module sprung mass. Suspension displacement x; Vertical acceleration of sprung mass Through experimental design, sufficient input power is ensured across a wide frequency band (0.5-20Hz) to guarantee the recognition effect.

[0177] In some embodiments, the system model for determining the nonlinear characteristic parameter matrix of the suspension of a heavy-duty vehicle can be a dual-mass vibration system model.

[0178] In some embodiments, suspension output force It can be expressed as the superposition of elastic force and damping force (refer to formula 3). Formula (3) can be the first function mentioned above, but this application is not limited to it.

[0179] (3)

[0180] Where x is the relative displacement of the suspension; Equivalent stiffness characterizes the compression properties of a gas spring; The equivalent damping coefficient characterizes the resistance characteristics of oil flowing through the damping orifice; This is friction.

[0181] In some embodiments, a low-pass filter (cutoff frequency 5Hz) can be used to extract low-frequency components for equivalent stiffness calibration.

[0182] In some embodiments, a bandpass filter (5-15Hz) can be used to extract mid-to-high frequency components for equivalent damping coefficient calibration.

[0183] In some embodiments, the suspension nonlinear characteristic parameter matrix can be identified using the following method: screening speed. Data points to fit the total suspension force The relationship curve with x is used for equivalent stiffness fitting; screening. Data points to fit the total suspension force and The relationship curve is used for fitting the equivalent damping coefficient.

[0184] For the equivalent stiffness, a third-order polynomial least squares fitting method can be used: .

[0185] For the equivalent damping coefficient, a power function can be used to approximate it. .

[0186] In some embodiments, the fitted equivalent stiffness and equivalent damping coefficient can be generalized to the entire dataset. Then, the objective function is to minimize the sum of squared residuals, i.e. The nonlinear characteristic parameter matrix of the suspension of heavy-duty vehicles is obtained through iteration. .

[0187] Finally, the system friction force is estimated based on the offset at the extreme displacement. .

[0188] Using the above method, the nonlinear characteristic parameter matrix of the hydro-pneumatic suspension can be output: polynomial stiffness coefficient matrix. Equivalent damping coefficient Damping index System friction force i is an integer greater than 0.

[0189] In some embodiments, the equivalent stiffness and damping coefficient of the hydropneumatic suspension system simulation model based on the hydraulic and pneumatic components can be output as a true reference for the identified model under the same excitation input.

[0190] In some embodiments, a vehicle dynamics model can also be constructed using at least one of the following methods.

[0191] 1. Obtain the driving speed of the heavy-duty vehicle and the rotational speed of each wheel on the tested axle; based on the driving speed and the rotational speed of each wheel on the tested axle, determine the equivalent rolling radius of each wheel on the tested axle so as to construct a vehicle dynamics model based on the equivalent rolling radius.

[0192] Specifically, the equivalent rolling radius of a heavy-duty vehicle can be determined using the following methods.

[0193] For example, the IMU vehicle speed v during constant speed can be used in conjunction with the motor speed / wheel speed. Calculating the equivalent rolling radius of a tire .

[0194] In some embodiments, step and sinusoidal frequency sweep tests can be applied to the drive system, braking system, and steering system of each wheel on the tested axle during the vehicle's uniform speed movement.

[0195] This testing method can also be used for dynamic performance testing and modeling of chassis actuators. By directly using the vehicle's mass and inertia as loads, the test conditions closely resemble actual use, which helps improve modeling accuracy.

[0196] 2. Send torque signals to the drive motor corresponding to the axle under test; collect the speed signals fed back by the drive motor; based on the torque and speed signals, fit and calibrate the parameters in the tire drive mechanics model so as to construct a vehicle dynamics model based on the tire drive mechanics model; the torque signal is a step signal and / or a sinusoidal sweep frequency signal.

[0197] Specifically, a torque signal can be sent to the drive motor of the intermediate shaft (the shaft being measured), and constant speed travel can be maintained through feedback control of the first and third shafts. By recording the actual torque (motor feedback speed) response curve, the response time, overshoot, and steady-state error of the drive system can be identified.

[0198] 3. Send a steering signal to the steering motor corresponding to the axle under test; collect the steering angle signal fed back by the steering motor; based on the steering signal and the steering angle signal, fit and calibrate the parameters in the tire steering mechanics model so as to construct a vehicle dynamics model based on the tire steering mechanics model; the steering signal is a step signal and / or a sinusoidal sweep frequency signal.

[0199] In some embodiments, equal and opposite torque signals can be sent to the steering motor of the intermediate shaft (measured shaft) for toe-in steering, and constant speed can be maintained through feedback control of the first and third shafts. During the operation of the heavy-duty vehicle, the steering angle signal output by the steering motor is collected.

[0200] In some embodiments, after completing tests on tire driving force and steering force, the parameters of the tire driving mechanics model and the tire steering mechanics model can be determined by the following methods.

[0201] Specifically, for parameter fitting of the hub motor (tire drive mechanics model) and the steering motor (tire steering mechanics model), the input data may include: controller request signals. Motor feedback speed / angle signal .

[0202] The parameters in the tire drive mechanics model and the tire steering mechanics model can be fitted by sampling the following second-order system model with time delay.

[0203] In some embodiments, the closed-loop transfer function of a second-order system model with time delay can be obtained by referring to formula (4).

[0204] (4)

[0205] In some embodiments, a controller request signal can be used. Motor feedback speed / angle signal By converting to the frequency domain (w) and then substituting into formula (4) for fitting, the response gain can be obtained. Damping ratio Natural frequency Time constant Parameters such as these.

[0206] 4. It can send braking signals to the braking system corresponding to the axle under test; collect the wheel cylinder pressure corresponding to the braking system; and fit and calibrate the parameters in the tire braking dynamics model based on the braking signal and wheel cylinder pressure, so as to construct a vehicle dynamics model based on the tire braking dynamics model; the braking signal is a step signal and / or a sinusoidal sweep frequency signal.

[0207] In some embodiments, a brake opening signal can be sent to the master cylinder of the measured axis (such as an intermediate axis) via drive-by-wire, and constant speed travel can be maintained through feedback control of the first and third axes. By recording the actual torque response curve, the response time, overshoot, and steady-state error of the braking system can be identified.

[0208] In some embodiments, the above-mentioned "signals" include step signals and sinusoidal sweep signals.

[0209] In some embodiments, the model parameters corresponding to the braking system can be determined by the following methods.

[0210] Input data: Controller request signal Wheel cylinder pressure .

[0211] System model: A second-order system model with time delay, whose closed-loop transfer function can be found in formula (5).

[0212] (5)

[0213] In some embodiments, a controller request signal can be used. Wheel cylinder pressure Transform to the frequency domain and then substitute into the above formula (5) for fitting to obtain the parameters in the tire braking dynamics model: response gain. Damping ratio Natural frequency Time constant .

[0214] In addition, a simulation model of the hydraulic braking system based on hydraulic components was established, and the braking pressure build-up characteristics were derived through PV (Pressure-Volume) characteristics as a true reference for the fitted model.

[0215] In some embodiments, under the conditions that the vehicle is stationary or at low speed and the test wheel is suspended, excitation signals such as step, ramp, and sine are applied to the drive system, steering system, and braking system respectively to obtain the independent dynamic response of each subsystem in the decoupled state and identify its basic parameters (such as moment of inertia, damping, friction, response delay, and hydraulic characteristics).

[0216] Figure 6 This is a flowchart illustrating a method for determining tire lateral stiffness according to an exemplary embodiment.

[0217] refer to Figure 6 The above method for determining tire lateral stiffness may include the following steps.

[0218] Step S602: Control the heavy-duty vehicle to be stationary or moving at low speed by controlling the non-tested axle.

[0219] Step S604: Apply a synchronous, unidirectional small-angle step steering command to all wheels of the heavy-duty vehicle.

[0220] Step S606: Collect the wheel rotation angle of the heavy-duty vehicle, wherein the wheel slip angle of the heavy-duty vehicle is equal to the wheel rotation angle.

[0221] Step S608: Determine the tire lateral stiffness of the heavy-duty vehicle based on the wheel slip angle; wherein the wheel lateral stiffness is used to construct the vehicle dynamics model.

[0222] In some embodiments, tire lateral stiffness can be determined by the constant angle skew method.

[0223] Specifically, under low-speed (≤10 km / h) straight-line driving conditions, synchronous and unidirectional small-angle step steering commands (such as ≤5°) can be applied to all six wheels to ensure that the tires are in the linear zone of the lateral slip characteristics. During the step time, the wheel steering angle can be approximated as the wheel lateral slip angle, and the linear tire lateral slip stiffness of the wheel can be determined with reference to formula (6).

[0224] (6)

[0225] in, For linear tire lateral stiffness, Where m is the wheel angle and m is the total vehicle mass. The lateral acceleration at the selected data point.

[0226] Figure 7 This is a flowchart illustrating a method for determining the basic parameters of a wheel under test, according to an exemplary embodiment.

[0227] refer to Figure 7 The method for determining the basic parameters of the wheel being tested may include the following steps.

[0228] Step S702: Control the heavy-load vehicle to stand still or move at low speed by controlling the non-tested axle.

[0229] Step S704: Control the wheel under test to be suspended in the air.

[0230] Step S706: Apply at least one of the following signals to the drive system and steering system corresponding to the wheel being tested: step signal, ramp signal, and sine signal.

[0231] Step S708: Obtain the independent dynamic response of the drive system and steering system in the decoupled state, and identify the basic parameters of the wheel under test based on the independent dynamic response. The basic parameters include at least one of the following: moment of inertia, damping coefficient, friction coefficient, and response delay.

[0232] In some embodiments, the hub motor can be controlled to operate in speed mode when the target wheel is suspended in the air. A series of step speed commands with different amplitudes (e.g., 30%, 50%, 80% of rated speed) are applied to it, and the motor (wheel) rotational angular velocity ω and its derivative, as well as the motor torque feedback T, are recorded according to the formula... Calculate the moment of inertia of the wheel when it is spinning freely, where .

[0233] In some embodiments, the kingpin steering motor can be controlled while the target wheel is suspended in the air. The output torque of the steering motor is measured by applying step, ramp, and sinusoidal steering angle commands. With the turning angle of the wheel The dynamic response is then fitted using formula (7), which includes at least one of the following: moment of inertia, damping coefficient, friction coefficient, and response delay.

[0234] (7)

[0235] in The moment of inertia of the steering motor driving the wheel to turn around the kingpin. Damping for the steering motor driving the wheels to steer around the kingpin. The restoring torque around the kingpin is generated by tire force and gravity. The dry friction torque of the steering body around the kingpin.

[0236] Figure 8 This is a flowchart illustrating a method for determining hydraulic characteristics according to an exemplary embodiment.

[0237] refer to Figure 8 The above-mentioned method for determining hydraulic characteristics may include the following steps.

[0238] Step S802: Control the heavy-duty vehicle to be stationary or moving at low speed by controlling the non-tested axle.

[0239] Step S804: Control the wheel under test to be suspended in the air.

[0240] Step S806: Control the master cylinder pressure of the braking system corresponding to the wheel under test to jump from the first value to the target value, and simultaneously measure the wheel cylinder pressure rise curve of the master cylinder.

[0241] Step S808: Determine the hydraulic characteristics of the braking system of the wheel under test based on the wheel cylinder pressure rise curve.

[0242] Specifically, you can press the brake pedal to increase the pressure in the master cylinder. From stable initial value (20% of rated braking pressure) step to target value Simultaneous measurement of wheel cylinder pressure The rising curve. The response is modeled as a first-order system. .

[0243] In some embodiments, the hydraulic circuit time constant is obtained by curve fitting. Target value The values ​​are 50%, 70%, and 90% of the rated braking pressure.

[0244] In some embodiments, a roll-off test is designed for the suspension system to determine the off-frequency and damping ratio. Under curb load, all three axles of the vehicle are simultaneously placed on the bumps, and a lateral sliding plate is installed at the landing point to relieve the lateral force of the wheels and avoid the influence of lateral stress on the suspension guiding mechanism. During the roll-off, it is ensured that all three axles and the left and right wheels land simultaneously to avoid the coupling effect of vehicle pitch and roll movements on vibration. Considering that the curb weight and tire size of the test vehicle are larger than those of conventional vehicles, the height of the bumps is appropriately increased and selected as 150mm.

[0245] In some embodiments, the vibration frequency T of the vehicle body and the amplitude of the k-th period can be recorded. ; vibration frequency of the wheel section .

[0246] In some embodiments, the natural frequency and damping ratio can be calculated using the time-domain method: sprung mass natural frequency Unsprung mass natural frequency Sprung mass vibration half-cycle decay rate Damping ratio .

[0247] In some embodiments, the natural frequency and damping ratio can be calculated using the frequency domain method: the resonant frequency can be extracted from the amplitude-frequency characteristics. (rad / s) (Hz), combined with the spring-loaded mass m, yields the stiffness. The frequency at the intersection of the bandwidth is obtained according to the peak response gain of 70% (0.707). , Damping ratio Damping coefficient .

[0248] Below, this application will explain and illustrate the method for constructing vehicle dynamics models with reference to specific embodiments.

[0249] Figure 9 This is another method for constructing a vehicle dynamics model according to an exemplary embodiment.

[0250] refer to Figure 9 The vehicle dynamics model construction method provided in this embodiment can include at least three test steps: benchmark test, bench test and whole vehicle test. After obtaining the working condition data through the above three steps, the parameters in the vehicle dynamics model are calibrated.

[0251] refer to Figure 9 This embodiment constructs a systematic testing system with a closed-loop linkage of "quasi-static benchmark characteristic calibration (bench test) - independent axle trailer bench dynamic decoupling test (bench test) - vehicle performance verification (vehicle test) - multi-source parameter identification".

[0252] Among them, the low-speed quasi-static test (quasi-static reference characteristic calibration) provides the system's linear and basic parameters, which can provide initial value references for the development of simplified dynamic models for control and subsequent parameter identification, and become the benchmark for subsequent high-dynamic tests.

[0253] The independent axle trailer method (dynamic decoupling test of independent axle trailer bench) utilizes the decoupling advantage of corner modules to obtain the nonlinear characteristics of tires and actuators under real loads; Standard operating condition testing (vehicle performance verification) is used to verify the handling and stability performance at the vehicle level and generate macroscopic response data for model validation; The parameter identification (multi-source parameter identification) module integrates the above three types of multi-source, multi-condition data to establish a high-fidelity vehicle dynamics model.

[0254] Below, this implementation will explain and describe each part of the above closed-loop system.

[0255] 1. A benchmark test method for the dynamic characteristics of a three-axis angle module heavy-duty vehicle (quasi-static benchmark characteristic calibration).

[0256] Under conditions where the vehicle is stationary or at low speed and the test wheels are suspended, step, ramp, and sine excitation signals are applied to the drive system, steering system, and braking system, respectively, to obtain the independent dynamic response of each subsystem in the decoupled state and identify its basic parameters (such as moment of inertia, damping, friction, response delay, and hydraulic characteristics).

[0257] (1) Lateral stiffness - constant rotation angle oblique method.

[0258] Under low-speed (≤10 km / h) straight-line driving conditions, apply synchronous, same-direction small-angle step steering commands (≤5°) to all six wheels to ensure that the tires are in the linear zone of the lateral slip characteristics. During the step time, the wheel steering angle can be approximated as the wheel slip angle. The linear tire lateral slip stiffness of the wheel can be determined with reference to formula (6).

[0259] (2) Drive motor - idling method.

[0260] With the target wheel suspended in the air, the hub motor is controlled to operate in speed mode. A series of step speed commands with different amplitudes (such as 30%, 50%, and 80% of rated speed) are applied to it, and the angular velocity of the motor (wheel) is recorded. Its derivative and motor torque feedback T, according to the formula Calculate the moment of inertia of the wheel when it is spinning freely, where .

[0261] (3) Steering motor - idling method.

[0262] With the target wheel suspended in the air, control the kingpin steering motor. Measure the steering motor output torque by applying step, ramp, and sinusoidal steering angle commands. With the turning angle of the wheel The dynamic response is then fitted using formula (7), which includes at least one of the following: moment of inertia, damping coefficient, friction coefficient, and response delay.

[0263] (4) Braking system – static method.

[0264] Depress the brake pedal to increase the pressure in the master cylinder. From stable initial value (20% of rated braking pressure) step to target value Simultaneous measurement of wheel cylinder pressure The rising curve. The response is modeled as a first-order system. The time constant of the hydraulic circuit was obtained through curve fitting. The target values ​​Ps are 50%, 70%, and 90% of the rated braking pressure.

[0265] (5) Gas suspension - roll-down method.

[0266] Figure 10 This is a schematic diagram of an oil-gas suspension test platform according to an exemplary embodiment.

[0267] refer to Figure 10 For the suspension system of heavy-duty vehicles, a roll-off test can be designed to determine the deflection frequency and damping ratio. Under curb load conditions, all three axles of the vehicle are simultaneously placed on cams (such as...). Figure 10 On the bump shown, a lateral sliding plate is installed at the landing point to relieve the lateral force of the wheels and avoid the influence of lateral stress on the suspension guiding mechanism. When pushing down, ensure that all three axles and the left and right wheels land simultaneously to avoid the coupling effect of vehicle pitch and roll on vibration. Considering that the curb weight and tire size of the test vehicle are larger than those of conventional vehicles, the height of the bump is appropriately increased, for example, to 150mm.

[0268] Record the vibration frequency T of the vehicle body and the amplitude of the kth period. ; vibration frequency of the wheel section .

[0269] Time-domain method for calculating natural frequency and damping ratio: natural frequency of sprung mass Unsprung mass natural frequency Sprung mass vibration half-cycle decay rate Damping ratio .

[0270] Frequency domain method for calculating natural frequency and damping ratio: extracting resonant frequency from amplitude-frequency characteristics (rad / s) (Hz), combined with the spring-loaded mass m, yields the stiffness. The frequency at the intersection of the bandwidth is obtained according to the peak response gain of 70% (0.707). , Damping ratio Damping coefficient .

[0271] 2. A bench test method for the dynamic characteristics of a three-axle angle module heavy-duty vehicle (dynamic decoupling test of an independent axle trailer bench).

[0272] Figure 11 This is a flowchart illustrating a bench testing method according to an exemplary embodiment.

[0273] refer to Figure 11 The above bench test method may include the following process.

[0274] Step S1102: Initialize the test vehicle.

[0275] Step S1104: Set up the test equipment on the vehicle and determine whether it meets the test requirements.

[0276] If the experimental requirements are met, proceed to step S1106. If the experimental requirements are not met, return to step S1102.

[0277] Step S1106: Start trailer axle mode (i.e., independent axle trailer).

[0278] In some embodiments, in trailer axle mode, the domain controller can take over the intermediate axle, and the vehicle controller can control the first and third axles to maintain the driving state required by the operating conditions.

[0279] Step S1108: Select test items and set test conditions.

[0280] Step S1110, pure tire lateral deviation test.

[0281] If a pure sideslip test is being conducted, the entire vehicle can be controlled to move forward at a constant speed through the non-test axle, and symmetrical reverse steering angles can be applied to the two wheels of the non-test axle.

[0282] Step S1112, tire pure longitudinal slip test.

[0283] If a pure longitudinal slip test is being conducted, the heavy-duty vehicle can be controlled to travel at a constant speed by controlling the non-tested axle. During the constant speed travel, the torque of the tested axle is controlled to increase linearly from 0 until the slip ratio of the tested axle reaches a preset threshold (e.g., 50%).

[0284] Step S1114: Determine the tire rolling radius.

[0285] If a tire rolling radius determination experiment is conducted, the axle under test can be kept rolling freely.

[0286] Step S1116: Actuator response characteristics are determined.

[0287] To conduct actuator response characteristic experiments, sinusoidal or step input signals can be applied to the axle under test.

[0288] Step S1118, Data Acquisition and Processing.

[0289] Step S1120: Restore the vehicle control strategy.

[0290] The "independent axle trailer method" utilizes the unique advantages of the corner module vehicle platform to construct a real-time test bench for road driving conditions. Specifically, the vehicle is controlled to travel at a constant speed, with at least one axle (the tested axle) decoupled from the other drive axles. An independent domain controller (CDCU) controls the tested axle, while the vehicle controller (VCU) controls the other axles to maintain vehicle speed. The tested axle's dynamic characteristics under real loads are obtained by applying tire characteristic test excitations such as pure sideslip and pure longitudinal slip, as well as driving / braking step and sinusoidal frequency sweep tests during operation. The key innovation lies in controlling the left and right wheels of the tested axle to perform symmetrical steering of equal magnitude but opposite direction during testing to counteract yaw moments, maintain straight-line vehicle travel, and simultaneously ensure that the wheel angle of the tested axle equals the tire sideslip angle.

[0291] This section proposes a real-vehicle bench testing method called the "independent axle trailer method." This method eliminates the need for traditional fixed test benches. Instead, it directly utilizes the platform characteristics of the corner module heavy-duty vehicle itself to construct a dynamic and reconfigurable "mobile test bench" during actual road driving. This allows for precise dynamic characteristic testing of the tested axle (or corner module) under real load and tire-road interaction conditions.

[0292] (1) Tire test.

[0293] 1. Pure lateral deviation test.

[0294] Test principle: The first and third axles provide driving force and counteract driving resistance to achieve constant speed driving, while the wheels on both sides of the middle axle steer symmetrically and satisfy the following conditions. .in, The turning angle of the left wheel of the measured axle. : The turning angle of the wheel on the right side of the axle being measured.

[0295] In this driving mode, the yaw rates generated by the lateral forces of the two wheels acting on the vehicle's center of gravity cancel each other out. According to relevant definitions, the steering angle when driving steadily forward is the tire slip angle. The return torque and wheel lateral forces can be calculated through steering motor torque feedback and the transmission ratio of the reduction mechanism.

[0296] 2. Pure longitudinal slip test.

[0297] Test Principle: After the first and third axles reach the specified test speed and travel at a constant speed for a certain period of time, the torque of the second axle increases linearly from 0 until the slip ratio approaches 50%. The torque of the first and third axles is controlled to maintain the test speed based on the target vehicle speed and rotational speed feedback. The longitudinal force of the wheels can be calculated through the torque feedback of the drive motor and the transmission ratio of the reduction mechanism.

[0298] 3. Rolling radius.

[0299] The equivalent rolling radius of the tire can be calculated using the relationship between the IMU vehicle speed v and the motor speed / wheel speed ω during constant speed operation. .

[0300] (2) Step and sinusoidal sweep frequency tests of drive, braking and steering systems.

[0301] This testing method can also be used for dynamic performance testing and modeling of chassis actuators. By directly using the vehicle's mass and inertia as loads, the test conditions closely resemble actual use, which helps improve modeling accuracy.

[0302] Drive: A torque signal is sent to the intermediate shaft drive motor, and constant speed is maintained through feedback control of the first and third axes. By recording the actual torque response curves, the response time, overshoot, and steady-state error of the drive system are identified.

[0303] Braking: A braking opening signal is sent to the MCU of the central axis master cylinder, and constant speed is maintained through feedback control of the first and third axes. By recording the actual torque response curve, the response time, overshoot, and steady-state error of the braking system are identified.

[0304] Steering: Sends equal and opposite torque signals to the steering motor on the intermediate shaft for toe-in steering, and maintains constant speed through feedback control of the first and third shafts.

[0305] The above "signals" include step signals and sinusoidal sweep signals.

[0306] 3. A vehicle-wide test method for the dynamic characteristics of a three-axis angle module heavy-duty vehicle (vehicle performance verification).

[0307] Under different load conditions (prepared, half-loaded, fully loaded), a series of standardized vehicle-level composite operating condition tests are performed, including: oblique driving condition (for calibrating steering system response and tire lateral stiffness), acceleration and braking condition (for calibrating drive and braking system response and power / braking performance), vertical excitation passing condition (for calibrating suspension system frequency response and ride comfort), and Ackermann steering and slalom condition (for calibrating vehicle handling stability).

[0308] (1) Dynamics - Drive system.

[0309] By applying a uniform step or sinusoidal torque command to all in-wheel motors, the response process of the actual output torque and speed of the motors is measured at constant vehicle speeds (e.g., 10, 20, 30 km / h). Treating the drive system as a second-order system, its equivalent transfer function is fitted using the response curve to obtain the system gain, damping ratio, and response delay. By analyzing the acceleration curve under constant torque, the vehicle's acceleration capability and steady-state driving resistance at different speeds are calculated, providing a basis for vehicle energy management and power matching.

[0310] (2) Braking performance – braking system.

[0311] On a straight road, the vehicle travels at a constant initial speed (e.g., 20 km / h). The driver or the drive-by-wire system increases the brake pedal opening (or master cylinder pressure) in steps, maintaining a brief period of stability each time. The wheel cylinder pressures and the vehicle's longitudinal deceleration are recorded simultaneously. This is based on the overall vehicle force balance. .

[0312] Reverse the braking force of each axle, among which For the pressure of each wheel cylinder, For the overall vehicle quality, The longitudinal deceleration is then used to plot the "wheel cylinder pressure-braking torque" relationship curve. By obtaining the braking force growth characteristics across the entire pressure range, precise calibration of the pressure-torque control mapping for the EHB (Electro-Hydraulic Brake) system is provided.

[0313] (3) Ride comfort – suspension system.

[0314] Vehicles were allowed to pass through two typical vertically excited road surfaces at different speeds under different loads.

[0315] Continuous random excitation of road surfaces (such as asphalt, gravel, Belgian roads): Obtain the steady-state response of the suspension to broadband random inputs.

[0316] Discrete impact excitation (such as speed bumps at a specific height): Obtain the suspension's damping response to transient impacts.

[0317] Spectral analysis was performed on signals such as vehicle vertical acceleration and suspension dynamic deflection to obtain the vibration transfer function of the suspension system at different frequencies, and its nonlinear equivalent stiffness was obtained by separating the frequency bands. Damping Calculate the root mean square (RMS) values ​​of the sprung mass acceleration at the cargo box, suspension dynamic travel, and tire dynamic load to evaluate the ride comfort while carrying cargo.

[0318] (4) Handling stability – steering system and suspension system.

[0319] Design and execute a series of standardized steering input conditions to measure the vehicle's yaw and lateral motion response.

[0320] Inclined driving condition: All wheels steer synchronously in the same direction, producing a pure lateral translation tendency. Used to calibrate the overall delay of the steering system and verify the vehicle consistency of tire lateral stiffness.

[0321] Steady-state yaw rate (Ackerman steering): An acceleration cycle is performed with a fixed steering wheel angle or fixed Ackerman angles for each wheel, measuring the relationship between yaw rate and lateral acceleration. This is used to determine the vehicle's understeer / oversteer characteristics and yaw rate gain.

[0322] Angular step / angular pulse input: During high-speed constant-speed driving, a fixed steering wheel angle (step) or a brief pulse angle is suddenly applied. This is used to analyze the transient response time, overshoot, and settling time of vehicle yaw motion, and to evaluate dynamic convergence.

[0323] Snake test: The vehicle traverses a series of equally spaced cones at a specified speed. By measuring the average yaw rate, lateral acceleration, and passage time, the dynamic steering performance and stability margin of the vehicle within its limits are comprehensively evaluated.

[0324] 4. A unified dynamic model calibration method for the dynamic characteristics of a three-axis angle module heavy-duty vehicle (multi-source parameter identification).

[0325] By integrating multi-source and multi-condition test data obtained from benchmark tests, bench tests, and whole vehicle tests, and employing system identification and parameter fitting methods, various parameters of a unified vehicle dynamics model are calibrated.

[0326] (1) Tire.

[0327] The input data can be found in Table 2.

[0328] System model: A unified tire dynamics model.

[0329] Identification method: You can refer to the identification method corresponding to formula (1).

[0330] For pure longitudinal dynamics of tires, the identification method corresponding to formula (2) can be referred to.

[0331] (2) Hub motor and steering motor.

[0332] Input data: Controller request signal u(t), motor feedback speed / angle signal y(t).

[0333] System model: A second-order system model with time delay, whose closed-loop transfer function is: .

[0334] Identification method: System identification and fitting software.

[0335] Output results: response gain K, damping ratio ζ, natural frequency Time constant τ.

[0336] (3) Braking system.

[0337] Input data: Controller request signal Wheel cylinder pressure .

[0338] System model: A second-order system model with time delay, whose closed-loop transfer function is: .

[0339] Identification method: System identification and fitting software.

[0340] Output results: response gain K, damping ratio ζ, natural frequency Time constant τ.

[0341] In addition, a simulation model of the hydraulic braking system based on hydraulic components was established, and the braking pressure build-up characteristics were derived through PV characteristics as a true reference for the fitting model.

[0342] (4) Gas suspension.

[0343] Input data: Sprout mass of a single module Suspension displacement x; Vertical acceleration of sprung mass Through experimental design, sufficient input power is ensured across a wide frequency band (0.5-20Hz) to guarantee the recognition effect.

[0344] System Model: A two-mass vibration system model, where the suspension output force is represented as the superposition of elastic and damping forces. .

[0345] Where x is the relative displacement of the suspension; Equivalent stiffness characterizes the compression properties of a gas spring; The equivalent damping coefficient characterizes the resistance characteristics of oil flowing through the damping orifice; This is friction.

[0346] Low-frequency components were extracted using a low-pass filter (cutoff frequency 5Hz) for equivalent stiffness calibration.

[0347] A bandpass filter (5-15Hz) is used to extract mid-to-high frequency components for equivalent damping coefficient calibration.

[0348] Identification method: Filtering speed Data points to fit the total suspension force and The relationship curve is used for equivalent stiffness fitting; screening. Data points to fit the total suspension force and The relationship curve is used for fitting the equivalent damping coefficient.

[0349] For the equivalent stiffness, a third-order polynomial least squares fit is used: .

[0350] The equivalent damping coefficient is fitted using a power function. .

[0351] Extended to the entire dataset .

[0352] The objective function is to minimize the sum of squared residuals, i.e. .

[0353] Iteratively obtain the parameter matrix .

[0354] Finally, the system friction force is estimated based on the offset at the extreme displacement. .

[0355] Output results. Nonlinear characteristic parameter matrix of the hydro-pneumatic suspension: polynomial stiffness coefficient matrix. Equivalent damping coefficient Damping index System friction force i is an integer greater than 0.

[0356] In addition, a simulation model of an oil-pneumatic suspension system based on hydraulic and pneumatic components is established. Under the same excitation input, the equivalent stiffness and damping coefficient are output as a true value reference for the identified model.

[0357] Below, this application also provides an embodiment of the above-mentioned dynamic decoupling test method for independent axle trailer trolley, combined with a specific application scenario.

[0358] First, this embodiment improves an embodiment of an independent axle trailer test bench.

[0359] This embodiment uses a heavy-duty vehicle with a three-axle configuration and two corner modules per axle as an example to describe in detail the implementation process of the method of the present invention. Each corner module of the vehicle integrates hub motor drive, kingpin motor steering, electro-hydraulic braking and hydropneumatic suspension functions, and is controlled collaboratively by the vehicle controller (VCU) and the axle domain controllers (CDCU).

[0360] Test preparation: Select a straight, dry asphalt road surface as the test road. Ensure the vehicle is in good technical condition and that the safety control logic (CDCU emergency stop switch, signal failure monitoring, etc.) is activated and tested to be effective.

[0361] Independent axle trailer method establishment: The control strategy is set as follows: the VCU controls the first and third axles to maintain a constant test vehicle speed (e.g., 20 km / h) and provides the main driving force for the whole vehicle to overcome driving resistance; the control authority of the second axle (the tested axle) is completely handed over to the independent CDCU, and the VCU sets its drive motor torque request to zero, so that it enters the "towed" state.

[0362] A tire pure sideslip test may include the following procedures.

[0363] 1. After the VCU controls the vehicle to travel at a constant speed of 20km / h, the CDCU sends equal and opposite steering commands to the left and right wheels of the second axle (e.g., left wheel +4°, right wheel -4°) to implement "toe-in steering".

[0364] 2. Due to the yaw moments generated by symmetrical steering, the vehicle maintains a basically straight trajectory under the fine-tuning of the first and third axles by the VCU. At this time, the steering angle of the second axle wheels... This can be considered as the slip angle of the tire on that axle. .

[0365] 3. Read the output torque of the steering motor via CDCU. It can indirectly solve the lateral force of the tire wheel. The lateral acceleration of the IMU is recorded synchronously as a verification.

[0366] 4. Change the steering angle command (e.g., ±2°, ±6°), repeat the test, and obtain the wheel lateral force and self-centering torque data under different slip angles.

[0367] A tire longitudinal slip test may include the following procedures.

[0368] 1. The VCU controls the vehicle to accelerate to 30 km / h and enter constant speed cruising.

[0369] 2. The CDCU gradually increases the torque command of the second shaft drive motor (linearly increasing from 0), causing the wheel of that shaft to slip.

[0370] 3. The VCU adjusts its drive torque in real time based on the feedback of the first and third axle wheel speeds to try to maintain the target vehicle speed.

[0371] Synchronously record the actual output torque T of the second-axis drive motor (reflecting longitudinal force) ), second axle wheel speed And vehicle speed v. Calculate the longitudinal slip ratio. The rolling radius is obtained through testing or is a temporary nominal value.

[0372] 4. Stop the test when the slip ratio approaches 50%, and obtain the result. and The relationship curve.

[0373] Roll radius test: Record a stable vehicle speed during the free rolling phase without drive or braking (e.g., the constant speed phase before the pure sideslip test). Second axle wheel speed (From motor feedback). Calculate the rolling radius. .

[0374] Dynamic response testing of the drive / braking / steering system: In "independent axle trailer" mode, the CDCU can perform step or sinusoidal frequency sweep excitation tests on the drive motor, braking system, and steering motor of the second axle respectively. For example, a step torque command with an amplitude of 500 Nm is applied to the drive motor, and its actual torque response curve is recorded; a sinusoidal frequency sweep angle command of 0.5-5 Hz is applied to the steering motor, and the angle tracking is recorded. The VCU always compensates for the disturbance of the tested axle excitation to the overall vehicle speed by controlling the first and third axes, keeping the test conditions stable.

[0375] Next, this application provides an embodiment of a unified dynamic model parameter calibration and verification scheme.

[0376] Data fusion and preprocessing: Multi-source data collected from benchmark, bench, and vehicle tests are synchronized, aligned, and filtered based on a unified timestamp.

[0377] Parameter identification and fitting.

[0378] Tires: Using pure sideslip and pure longitudinal slip experimental data obtained from bench tests, and based on a unified tire dynamics model, the tire sideslip stiffness under different vertical loads was obtained. longitudinal stiffness Shape factor coefficient of friction Key parameters, such as the self-aligning torque characteristic parameters.

[0379] Actuators: For the step / sweep frequency response data of the drive motor, steering motor, and braking system, system identification software is used to fit their second-order transfer function models with time delay to obtain the gain of each system. Damping ratio Natural frequency and time delay .

[0380] Suspension: Based on the frequency offset and damping ratio from comprehensive benchmark tests, as well as the filtered suspension force-displacement and force-velocity relationship data from vehicle ride comfort tests, the nonlinear stiffness polynomial coefficients of the hydropneumatic suspension were calibrated using the piecewise fitting and optimization algorithm described in the embodiments. And damping power function parameters .

[0381] Model Integration and Validation: The calibrated parameters are input into a pre-defined unified multibody dynamics model. Vehicle test data not used for parameter identification (e.g., a slalom test under a different load) are used as input to drive the simulation model. Key variables such as yaw rate and lateral acceleration output from the simulation are compared with real vehicle test data. Error analysis (e.g., root mean square error RMSE, correlation coefficient) is then performed. Verify the model's fidelity. If the error exceeds the acceptable range, iteratively adjust some parameters or the model structure until the simulation and experimental data match well.

[0382] The above embodiments have at least the following beneficial effects: 1. For the first time, a complete, hierarchical, and systematic method for testing and calibrating dynamic parameters of distributed-drive, independently steering multi-axle corner module heavy-duty vehicles is proposed. The testing scheme is broken down into "bench test - bench test - vehicle test", and the parameter calibration scheme is broken down into "corner module execution components - corner module system - corner module vehicle". The method is flexible, progressive, and complementary, filling a gap in this field. 2. Initial reference values ​​and simplified model parameters are obtained through benchmark testing, equivalent dynamic characteristics of components are obtained through bench testing, and coupling characteristics and parameter calibration effects are verified through vehicle testing, forming a progressive strategy. In the design of test conditions and inputs, the unique advantages of the corner module vehicle platform—high control freedom and independent actuation of each wheel—are fully utilized. The subsystems and single-module responses of interest are decoupled from the overall vehicle dynamics, effectively separating complex coupling effects and significantly improving the accuracy and efficiency of parameter identification. 3. The proposed "independent axle trailer method" and its safety control logic ensure the accuracy and safety of testing under actual vehicle driving conditions, eliminating the need for separate test benches or test sites for each subsystem, thus giving the solution good versatility and engineering operability. 4. The high-fidelity unified dynamic model and parameter set output from the calibration can be directly used for the development, simulation, and verification of vehicle control strategies (such as torque vector distribution, special steering modes, and electro-hydraulic coordinated braking), possessing significant engineering application value.

[0383] It should be particularly noted that the steps in each embodiment of the above-described vehicle dynamics model construction method can be interchanged, substituted, added to, or deleted from each other. Therefore, these reasonable permutations and combinations of the vehicle dynamics model construction method should also fall within the protection scope of this disclosure, and the protection scope of this disclosure should not be limited to the described embodiments.

[0384] It should be noted that the scope of protection of this application should include, but is not limited to, the specific implementation methods described in the embodiments. Any alternative solution that uses a different name but substantially performs the same function and achieves the same technical effect falls within the scope of protection defined by the claims of this application.

[0385] Based on the same inventive concept, this disclosure also provides a vehicle dynamics model construction device, as described in the following embodiments. Since the principle by which this device solves the problem is similar to that of the above-described method embodiments, the implementation of this device embodiment can refer to the implementation of the above-described method embodiments, and repeated details will not be elaborated further.

[0386] Figure 12 This is a block diagram illustrating a vehicle dynamics model building apparatus according to an exemplary embodiment. (Refer to...) Figure 12 The vehicle dynamics model building device 1200 provided in this embodiment may include: a constant speed control module 1201, a symmetrical steering control module 1202, a lateral working condition data acquisition module 1203, a wheel lateral force determination module 1204, and a lateral dynamics model calibration module 1205.

[0387] The uniform speed control module 1201 can be used to control the non-tested axle of the heavy-duty vehicle, ensuring that the heavy-duty vehicle travels at a constant speed on a real road. The heavy-duty vehicle includes at least three axles, comprising one tested axle and at least one non-tested axle. The symmetrical steering control module 1202 can be used to decouple the tested axle from the non-tested axles of the heavy-duty vehicle and control the symmetrical steering of the wheels on both sides of the tested axle. The lateral working condition data acquisition module 1203 can be used to collect lateral working condition data corresponding to each wheel on the tested axle; the lateral working condition data includes tire steering angle. The parameters include wheel speed, tire rolling radius, and vehicle longitudinal speed, wherein the tire slip angle of the wheel on the tested axle is equal to the tire rotation angle. The wheel lateral force determination module 1204 can be used to determine the tire return torque and wheel lateral force on the tested axle based on the lateral working condition data of the tested axle; the lateral dynamics model calibration module 1205 can be used to calibrate the parameters in the tire lateral dynamics model in the vehicle dynamics model corresponding to the heavy-duty vehicle using the return torque and the wheel lateral force.

[0388] The process of collecting lateral working condition data corresponding to each wheel on the tested axle includes: obtaining the measured lateral force of the wheels on the tested axle using a six-component force sensor installed at the wheel of the tested axle. Measured longitudinal force Measured roll moment Wherein the wheel lateral force is equal to the measured lateral force; wherein, determining the return torque of the tires on the tested axle based on the lateral working condition data of the tested axle includes: using the formula Determine the wheel's return torque. ;in Given the known kingpin inclination offset, Given the caster trail; wherein, the parameters in the tire lateral dynamics model of the vehicle dynamics model corresponding to the heavy-duty vehicle are calibrated using the self-aligning torque and the wheel lateral force, including: determining the tire slip ratio of the wheel using the wheel speed, the tire rolling radius, and the vehicle longitudinal speed. ; through formula Determine the longitudinal slip ratio of the wheel And through the formula Determine the lateral slip ratio of the wheel. ;in It is the tire slip angle; through the fitting formula , , , Identify the restoring torque respectively and the tire slip angle The relationship, the lateral force and the tire slip angle The relationship; among which It is a dimensionless lateral force; It is a dimensionless lateral slip ratio; It is the lateral shape factor, which is the parameter to be identified; It is the lateral adhesion coefficient, which is the parameter to be identified; It is a vertical load; This is tire trail distance, a parameter to be identified. It is the lateral slip stiffness; It refers to the longitudinal slip stiffness of the tire.

[0389] It should be noted that the above-mentioned module, as part of the device, can be executed in a computer system such as a set of computer-executable instructions.

[0390] In some embodiments, the vehicle dynamics model further includes a tire longitudinal dynamics model; wherein, the vehicle dynamics model construction device 1200 may include: a torque control module, a longitudinal slip condition data acquisition module, a longitudinal slip ratio determination module, and a tire longitudinal dynamics model calibration module.

[0391] The torque control module can be used to control the torque of the tested axle to increase linearly from 0 during the constant speed driving of the heavy-duty vehicle until the slip ratio of the tested axle reaches a preset threshold. The longitudinal slip condition data acquisition module can be used to acquire longitudinal slip condition data corresponding to each wheel on the tested axle during the torque increase process. The longitudinal slip ratio determination module can be used to determine the wheel longitudinal force and longitudinal slip ratio at different times on each wheel of the tested axle based on the longitudinal slip condition data; wherein the wheel longitudinal force is equal to the measured longitudinal force. The tire longitudinal dynamics model calibration module can be used to calibrate the parameters in the tire longitudinal dynamics model based on the wheel longitudinal force and longitudinal slip ratio at different times. The calibration of the parameters in the tire longitudinal dynamics model based on the wheel longitudinal force and longitudinal slip ratio at different times includes: fitting... , , Identify the longitudinal force of the wheel in the longitudinal dynamics model of the tire. and longitudinal slip ratio The relationship; among which It is the longitudinal adhesion coefficient, which is the parameter to be identified; Vertical load; It is a dimensionless longitudinal force. It is a dimensionless longitudinal slip ratio. It is the vertical shape factor, which is the parameter to be identified.

[0392] In some embodiments, the vehicle dynamics model building device 1200 may include: a first road surface testing module, a first sprung condition data acquisition module, a first condition data filtering module, a second condition data filtering module, an equivalent stiffness fitting module, an equivalent damping coefficient fitting module, and a suspension determination module.

[0393] The system includes several modules: a first road surface testing module to control the heavy-duty vehicle to pass through various vertically excited road surfaces at different speeds under different loads; a first sprung condition data acquisition module to collect sprung condition data of the wheels on the tested axle at different times, including at least one of sprung mass, suspension displacement, and sprung vertical acceleration; a first condition data filtering module to filter sprung condition data with zero sprung vertical acceleration as the first condition data; and a second condition data filtering module to filter sprung condition data with zero suspension displacement as the second condition data. The second operating condition data; the equivalent stiffness fitting module can be used to fit the relationship curve between the total suspension force and the suspension displacement based on the first operating condition data, so as to fit the equivalent stiffness of the suspension; the equivalent damping coefficient fitting module can be used to fit the relationship curve between the total suspension force and the vertical acceleration based on the second operating condition data, so as to fit the equivalent damping coefficient of the suspension; the suspension determination module can be used to determine the nonlinear characteristic parameter matrix of the suspension of the heavy-duty vehicle based on the equivalent stiffness and the equivalent damping coefficient, so as to construct the vehicle dynamics model based on the nonlinear characteristic parameter matrix of the suspension.

[0394] In some embodiments, the vehicle dynamics model building device 1200 may include: a second road surface testing module, a second sprung condition data acquisition module, a suspension total force determination module, a first function acquisition module, and a first function fitting module.

[0395] The system includes several modules: a second road surface testing module for controlling the heavy-duty vehicle to pass through various vertically excited road surfaces at different speeds under different loads; a second sprung condition data acquisition module for acquiring sprung condition data of the wheels on the tested axle at different times, including at least one of sprung mass, suspension displacement, and sprung vertical acceleration; a suspension total force determination module for determining the suspension total force corresponding to each sprung condition data based on the sprung mass and the sprung vertical acceleration; a first function acquisition module for acquiring a first function describing the relationship between the suspension total force, the suspension displacement, and the sprung vertical acceleration; the parameter to be identified in the first function is the suspension nonlinear characteristic parameter matrix of the heavy-duty vehicle; and a first function fitting module for fitting the first function with the suspension total force, the suspension displacement, and the sprung vertical acceleration to determine the suspension nonlinear characteristic parameter matrix, so as to construct the vehicle dynamics model based on the suspension nonlinear characteristic parameter matrix.

[0396] In some embodiments, the vehicle dynamics model building device 1200 may include: an equivalent rolling radius determination module, a tire driving mechanics model calibration module, a tire steering mechanics model calibration module, and a tire braking mechanics model calibration module.

[0397] The equivalent rolling radius determination module can be used to acquire the driving speed of the heavy-duty vehicle and the rotational speed of each wheel on the tested axle; based on the driving speed and the rotational speed of each wheel on the tested axle, it determines the equivalent rolling radius of each wheel on the tested axle, so as to construct the vehicle dynamics model based on the equivalent rolling radius; the tire drive mechanics model calibration module can be used to send a torque signal to the drive motor corresponding to the tested axle; acquire the rotational speed signal fed back by the drive motor; and fit and calibrate the parameters in the tire drive mechanics model based on the torque signal and the rotational speed signal, so as to construct the vehicle dynamics model based on the tire drive mechanics model; the torque signal is a step signal and / or a sinusoidal sweep frequency signal; tire steering mechanics model calibration. The module can be used to send a steering signal to the steering motor corresponding to the axle under test; collect the steering angle signal fed back by the steering motor; and fit and calibrate the parameters in the tire steering mechanics model based on the steering signal and the steering angle signal, so as to construct the vehicle dynamics model based on the tire steering mechanics model; the steering signal is a step signal and / or a sinusoidal sweep frequency signal. The tire braking dynamics model calibration module can be used to send a braking signal to the braking system corresponding to the axle under test; collect the wheel cylinder pressure corresponding to the braking system; and fit and calibrate the parameters in the tire braking dynamics model based on the braking signal and the wheel cylinder pressure, so as to construct the vehicle dynamics model based on the tire braking dynamics model; the braking signal is a step signal and / or a sinusoidal sweep frequency signal.

[0398] In some embodiments, the vehicle dynamics model building device 1200 may further include: a first low-speed control module, a steering angle command application module, a wheel steering angle acquisition module, and a tire lateral stiffness determination module.

[0399] The first low-speed control module can be used to control the heavy-duty vehicle to be stationary or moving at low speed through the non-tested axle; the steering angle command application module can be used to apply synchronous, unidirectional small-angle step steering angle commands to all wheels of the heavy-duty vehicle; the wheel steering angle acquisition module can be used to acquire the wheel steering angle of the heavy-duty vehicle, wherein the wheel slip angle of the heavy-duty vehicle is equal to the wheel steering angle; the tire slip stiffness determination module can be used to determine the tire slip stiffness of the heavy-duty vehicle based on the wheel slip angle; wherein the wheel slip stiffness is used to construct the vehicle dynamics model.

[0400] In some embodiments, the vehicle dynamics model building device 1200 may further include: a second low-speed control module, a wheel suspension control module, a signal application module, and a wheel basic parameter determination module.

[0401] The second low-speed control module can be used to control the heavy-duty vehicle to be stationary or to travel at low speed through the non-tested axle; the wheel suspension control module can be used to control the tested wheel to be suspended; the signal application module can be used to apply at least one of a step signal, a ramp signal, and a sine signal to the drive system and steering system corresponding to the tested wheel, respectively; the wheel basic parameter determination module can be used to obtain the independent dynamic response of the drive system and steering system in the decoupled state, and identify the basic parameters of the tested wheel based on the independent dynamic response, wherein the basic parameters include at least one of rotational inertia, damping coefficient, friction coefficient, and response delay.

[0402] In some embodiments, the vehicle dynamics model building device 1200 may further include: a third low-speed control module, a wheel suspension control module, a wheel cylinder pressure measurement module, and a wheel cylinder characteristic determination module.

[0403] The third low-speed control module can be used to control the heavy-duty vehicle to be stationary or to travel at low speed through the non-tested axle; the wheel suspension control module can be used to control the tested wheel to be suspended; the wheel cylinder pressure measurement module can be used to control the master cylinder pressure of the braking system corresponding to the tested wheel to jump from a first value to a target value, and simultaneously measure the wheel cylinder pressure rise curve of the master cylinder; the wheel cylinder characteristic determination module can be used to determine the hydraulic characteristics of the braking system of the tested wheel based on the wheel cylinder pressure rise curve.

[0404] Since the functions of the vehicle dynamics model building device 1200 have been described in detail in their respective method embodiments, they will not be repeated here.

[0405] The modules described in the embodiments of this disclosure can be implemented in software or hardware. These modules can also be located in a processor. The names of these modules do not, in certain circumstances, constitute a limitation on the module unit itself.

[0406] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a portion of a module or program segment containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer program instructions.

[0407] Furthermore, the above figures are merely illustrative of the processes included in the method according to exemplary embodiments of this disclosure and are not intended to be limiting. It is readily understood that the processes shown in the above figures do not indicate or limit the temporal order of these processes. Additionally, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0408] Figure 13 A schematic diagram of an electronic device suitable for implementing embodiments of the present disclosure is shown. It should be noted that... Figure 13 The vehicle dynamics model building electronics 1300 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments disclosed herein.

[0409] like Figure 13 As shown, the vehicle dynamics model building electronics 1300 includes a central processing unit (CPU 1301), which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM 1302) or a program loaded from storage section 1308 into random access memory (RAM 1303). The RAM 1303 also stores various programs and data required for the operation of the vehicle dynamics model building electronics 1300. The CPU 1301, ROM 1302, and RAM 1303 are interconnected via bus 1304. An input / output (I / O) interface 1305 is also connected to bus 1304.

[0410] The following components are connected to I / O interface 1305: an input section 1306 including a keyboard, mouse, etc.; an output section 1307 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 1308 including a hard disk, etc.; and a communication section 1309 including a network interface card such as a LAN card, modem, etc. The communication section 1309 performs communication processing via a network such as the Internet. Drive 1310 is also connected to I / O interface 1305 as needed. Removable media 1311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 1310 as needed so that computer programs read from them can be installed into storage section 1308 as needed.

[0411] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program containing computer program instructions for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 1309, and / or installed from removable medium 1311. When the computer program is executed by the central processing unit (CPU 1301), it performs the functions defined above in the system of this disclosure.

[0412] It should be noted that the computer-readable storage medium disclosed herein may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable computer program instructions. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable storage medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. Computer program instructions contained on a computer-readable storage medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0413] In another aspect, this disclosure also provides a computer-readable storage medium, which may be included in the device described in the above embodiments; or it may exist independently and not assembled into the device. The computer-readable storage medium carries one or more programs that, when executed by the device, enable the device to perform the following functions: controlling the non-tested axle of a heavy-duty vehicle to ensure the heavy-duty vehicle travels at a constant speed on a real road; the heavy-duty vehicle includes at least three axles, including one tested axle and at least one non-tested axle; decoupling the tested axle from the non-tested axle and controlling the symmetrical steering of the wheels on both sides of the tested axle; collecting lateral working condition data corresponding to each wheel on the tested axle; determining the tire return torque and wheel lateral force on the tested axle based on the lateral working condition data; and calibrating the parameters in the tire lateral dynamics model of the vehicle dynamics model corresponding to the heavy-duty vehicle using the return torque and wheel lateral force.

[0414] According to one aspect of this disclosure, a computer program product or computer program is provided, comprising computer program instructions stored in a computer-readable storage medium. The computer program instructions are read from the computer-readable storage medium, and a processor executes the computer program instructions to implement the methods provided in various optional implementations of the above embodiments.

[0415] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions of the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, or portable hard drive) and includes several computer program instructions to cause an electronic device (such as a server or terminal device) to execute the method according to the embodiments of this disclosure.

[0416] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the claims.

[0417] It should be understood that this disclosure is not limited to the detailed structures, drawing arrangements or implementations shown herein; rather, this disclosure is intended to cover various modifications and equivalent arrangements contained within the spirit and scope of the appended claims.

Claims

1. A vehicle dynamics model building method, characterized by, include: By controlling the non-tested axle of the heavy-duty vehicle to make the heavy-duty vehicle travel at a constant speed on the real road, the control of the tested axle and the non-tested axle of the heavy-duty vehicle is decoupled and the wheels on both sides of the tested axle are controlled to turn symmetrically. The tire rotation angle, wheel speed, and vehicle longitudinal speed of each wheel on the tested axle are collected, wherein the tire slip angle of the wheel on the tested axle is equal to the tire rotation angle. The measured lateral force on the wheel of the tested axle is obtained by a force sensor installed at the wheel of the tested axle. Measured longitudinal force Measured roll moment The wheel lateral force of the tested axle is equal to the measured lateral force. Through formula Determine the wheel's return torque. ;in The offset of the main pin inclination. Main pin tilt trail; The longitudinal slip ratio and lateral slip ratio of the tested axle are determined by the wheel speed, the vehicle longitudinal speed, and the tire slip angle. A pre-defined dimensionless tire lateral force fitting model is adopted, using wheel lateral force, self-aligning torque, longitudinal slip ratio, lateral slip ratio, and tire slip angle as inputs. The wheel lateral adhesion coefficient, tire shape factor, tire trailing distance, and lateral slip stiffness in the tire lateral dynamics model are identified, and the relationship between self-aligning torque and tire slip angle, and the relationship between wheel lateral force and tire slip angle in the tire lateral dynamics model are obtained. The vehicle dynamics model includes the tire lateral dynamics model.

2. The vehicle dynamics model construction method according to claim 1, characterized in that, The vehicle dynamics model further includes a tire longitudinal dynamics model; wherein, the method further includes: During the uniform speed driving of the heavy-duty vehicle, the torque of the tested axle is controlled to increase linearly from 0 until the slip ratio of the tested axle reaches a preset threshold. During the torque increase process, longitudinal slip condition data corresponding to each wheel on the tested axle are collected; Based on the longitudinal slip condition data, determine the longitudinal force and longitudinal slip ratio of each wheel on the tested axle at different times; wherein the longitudinal force of the wheel is equal to the measured longitudinal force. The parameters in the tire longitudinal dynamics model are calibrated based on the wheel longitudinal force and longitudinal slip ratio at different times. The parameters in the tire longitudinal dynamics model are calibrated based on the wheel longitudinal force and longitudinal slip ratio at different times, including: by fitting... , , Identify the longitudinal force of the wheel in the longitudinal dynamics model of the tire. and longitudinal slip ratio The relationship; among which It is the longitudinal adhesion coefficient, which is the parameter to be identified; Vertical load; It is a dimensionless longitudinal force. It is a dimensionless longitudinal slip ratio. It is the vertical shape factor, which is the parameter to be identified; It refers to the longitudinal slip stiffness of the tire.

3. The vehicle dynamics model construction method according to claim 1, characterized in that, The method further includes: Control the heavy-duty vehicle to pass through various vertically excited road surfaces at different speeds under different loads; Collect sprung condition data of the wheels on the tested axle at different times. The sprung condition data includes at least one of sprung mass, suspension displacement and sprung vertical acceleration. Select the spring working condition data where the vertical acceleration on the spring is 0 as the first working condition data; Select the sprung condition data where the suspension displacement is 0 as the second condition data; The relationship curve between the total suspension force and the suspension displacement is fitted based on the first working condition data to fit the equivalent stiffness of the suspension. The relationship curve between the total suspension force and the vertical acceleration is fitted based on the second working condition data to fit the equivalent damping coefficient of the suspension. The suspension nonlinear characteristic parameter matrix of the heavy-duty vehicle is determined based on the equivalent stiffness and the equivalent damping coefficient, so as to construct the vehicle dynamics model based on the suspension nonlinear characteristic parameter matrix.

4. The vehicle dynamics model construction method according to claim 1, characterized in that, The method further includes: Control the heavy-duty vehicle to pass through various vertically excited road surfaces at different speeds under different loads; Collect sprung condition data of the wheels on the tested axle at different times. The sprung condition data includes at least one of sprung mass, suspension displacement and sprung vertical acceleration. Based on the sprung mass and the sprung vertical acceleration, determine the total suspension force corresponding to each sprung working condition data; Obtain a first function, which describes the relationship between the total suspension force, the suspension displacement, and the sprung vertical acceleration; the parameter to be identified in the first function is the suspension nonlinear characteristic parameter matrix of the heavy-duty vehicle. The first function is fitted by the total suspension force, the suspension displacement, and the sprung vertical acceleration to determine the suspension nonlinear characteristic parameter matrix, so as to construct the vehicle dynamics model based on the suspension nonlinear characteristic parameter matrix.

5. The vehicle dynamics model construction method according to claim 1, characterized in that, The method also includes constructing the vehicle dynamics model by at least one of the following methods: The driving speed of the heavy-duty vehicle and the rotational speed of each wheel on the axle under test are obtained. Based on the driving speed and the rotational speed of each wheel on the tested axle, the equivalent rolling radius of each wheel on the tested axle is determined so as to construct the vehicle dynamics model based on the equivalent rolling radius; A torque signal is sent to the drive motor corresponding to the axle under test; a speed signal fed back by the drive motor is collected; based on the torque signal and the speed signal, the parameters in the tire drive mechanics model are fitted and calibrated so as to construct the vehicle dynamics model based on the tire drive mechanics model; the torque signal is a step signal and / or a sinusoidal sweep frequency signal; A steering signal is sent to the steering motor corresponding to the axle under test; the steering angle signal fed back by the steering motor is collected; based on the steering signal and the steering angle signal, the parameters in the tire steering mechanics model are fitted and calibrated so as to construct the vehicle dynamics model based on the tire steering mechanics model; the steering signal is a step signal and / or a sinusoidal sweep frequency signal; A braking signal is sent to the braking system corresponding to the axle under test; the wheel cylinder pressure corresponding to the braking system is collected; based on the braking signal and the wheel cylinder pressure, the parameters in the tire braking dynamics model are fitted and calibrated so as to construct the vehicle dynamics model based on the tire braking dynamics model; the braking signal is a step signal and / or a sinusoidal sweep frequency signal.

6. The vehicle dynamics model construction method according to claim 1, characterized in that, The method further includes: The heavy-duty vehicle is controlled to be stationary or move at low speed by the non-tested axle; Apply synchronous, unidirectional, small-angle step steering commands to all wheels of the heavy-duty vehicle; The wheel rotation angle of the heavy-duty vehicle is collected, wherein the wheel slip angle of the heavy-duty vehicle is equal to the wheel rotation angle. The tire lateral stiffness of the heavy-duty vehicle is determined based on the wheel slip angle; wherein the wheel lateral stiffness is used to construct the vehicle dynamics model.

7. The vehicle dynamics model construction method according to claim 1, characterized in that, The method further includes: The heavy-duty vehicle is controlled to be stationary or move at low speed by the non-tested axle; Control the wheel being tested to remain suspended in the air; The master cylinder pressure of the braking system corresponding to the wheel under test is controlled to jump from a first value to a target value, and the wheel cylinder pressure rise curve of the master cylinder is measured simultaneously. The hydraulic characteristics of the braking system of the tested wheel are determined based on the wheel cylinder pressure rise curve.

8. An electronic device, characterized in that, include: Memory and processor; The memory is used to store computer program instructions; the processor calls the computer program instructions stored in the memory to implement the vehicle dynamics model construction method as described in any one of claims 1-7.

9. A computer-readable storage medium storing computer program instructions thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the vehicle dynamics model construction method as described in any one of claims 1-7.

10. A computer program product comprising computer program instructions stored in a computer-readable storage medium, characterized in that, When the computer program instructions are executed by the processor, they implement the vehicle dynamics model construction method according to any one of claims 1-7.

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