Vehicle suspension adaptive compensation control method and system

Abstract

This application provides a vehicle suspension adaptive compensation control method and system. The method includes: acquiring the vehicle's motion state and the driver's steering input; determining the driver's desired response based on the driver's steering input and motion state; estimating the crosswind disturbance experienced by the vehicle online based on the motion state and the driver's desired response to obtain a crosswind disturbance estimate; determining an anti-roll compensation amount for suppressing vehicle body roll based on the crosswind disturbance estimate; and allocating the anti-roll compensation amount to the suspension adjustable actuator to perform adaptive compensation. This solves the problems in the prior art where it is difficult to distinguish between crosswind disturbance and driver steering intention, and where the suspension compensation response is lagging under crosswind conditions. It achieves online identification of crosswind disturbance experienced by the vehicle and active anti-roll compensation for vehicle body roll.

Description

Technical Field

[0001] This application relates to the field of vehicle control technology, specifically to a vehicle suspension adaptive compensation control method and system. Background Technology

[0002] Vehicles may encounter crosswinds while traveling at high speeds. Crosswinds exert lateral forces on the vehicle body and yaw moments around the vehicle's vertical axis, causing the vehicle to drift sideways and tilt. Crosswind disturbances are particularly pronounced in areas with strong winds, such as bridges, tunnel exits, and mountain passes, significantly impacting vehicle stability.

[0003] To reduce the impact of crosswinds on vehicle stability, vehicles are typically equipped with adjustable suspension systems that adjust the vehicle's attitude by controlling the suspension actuators. Existing vehicle stability control systems, upon sensing changes in lateral acceleration or yaw rate, trigger adjustment commands to the suspension actuators to suppress body roll or correct vehicle attitude.

[0004] However, in practical applications, existing suspension compensation methods still have the following objective problems: the lateral acceleration and yaw rate of the vehicle body are simultaneously affected by the driver's steering operation and external crosswind disturbances. The vehicle response caused by the two is similar in dimension and direction. It is difficult to distinguish the crosswind disturbance from the driver's active steering intention based solely on the lateral acceleration or yaw rate of the vehicle body. After the crosswind disturbance begins to act on the vehicle body, the existing suspension compensation method usually needs to adjust only after the vehicle body posture has deviated significantly. The compensation time is later than the time when the crosswind disturbance begins to act on the vehicle body, resulting in larger peak body roll and yaw rate and longer stabilization time. Summary of the Invention

[0005] In view of this, embodiments of this application provide a vehicle suspension adaptive compensation control method and system to solve the problems in the prior art where it is difficult to distinguish between crosswind disturbances and driver steering intentions, and the suspension compensation response is lagging under crosswind conditions. This enables online identification of crosswind disturbances experienced by the vehicle and active anti-roll compensation for vehicle body roll.

[0006] The first aspect of this application provides a vehicle suspension adaptive compensation control method, including: Acquire the vehicle's motion state and the driver's steering input; The driver's desired response is determined based on the driver's steering input and motion state. Based on the motion state quantity and the driver's expected response, the crosswind disturbance quantity experienced by the vehicle is estimated online to obtain the crosswind disturbance estimate. Based on the crosswind disturbance estimate, determine the anti-roll compensation amount used to suppress vehicle body roll; The anti-roll compensation amount is allocated to the adjustable suspension actuator to perform adaptive compensation.

[0007] A second aspect of this application provides a vehicle suspension adaptive compensation control system, comprising: The sensing module is used to acquire the vehicle's motion state and the driver's steering input. The crosswind disturbance observer module is used to determine the driver's desired response based on the driver's steering input and the motion state quantity, and to estimate the amount of crosswind disturbance experienced by the vehicle online based on the motion state quantity and the driver's desired response, thereby obtaining the crosswind disturbance estimate. The compensation decision module is used to determine the anti-roll compensation amount for suppressing vehicle body roll based on the crosswind disturbance estimate. The actuator allocation module is used to allocate the anti-roll compensation amount to the adjustable suspension actuators to perform adaptive compensation; The adjustable suspension actuator includes at least one of an air spring and a continuously damped control shock absorber.

[0008] The vehicle suspension adaptive compensation control method provided in the first aspect of this application acquires the vehicle's motion state and the driver's steering input, determines the driver's desired response based on the driver's steering input and vehicle speed, and estimates the crosswind disturbance experienced by the vehicle online based on the motion state and the driver's desired response. This allows the crosswind disturbance to be distinguished from the driver's steering intention even under active steering conditions, improving the accuracy of crosswind disturbance identification. Furthermore, by directly determining the anti-roll compensation amount for suppressing vehicle body roll based on the estimated crosswind disturbance, and then allocating the anti-roll compensation amount to the adjustable suspension actuator to perform adaptive compensation, the vehicle can initiate suspension compensation as soon as the crosswind disturbance is identified, shortening the compensation intervention time and thereby reducing the peak vehicle body roll and yaw rate under crosswind conditions, thus improving vehicle driving stability.

[0009] It is understandable that the beneficial effects of the second aspect mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 This is a flowchart illustrating the vehicle suspension adaptive compensation control method provided in an embodiment of the present invention; Figure 2 This is a flowchart illustrating the process of determining and verifying the attribution of crosswind disturbance estimates provided in an embodiment of the present invention. Figure 3 This is a schematic diagram of the vehicle suspension adaptive compensation control system provided in an embodiment of the present invention. Detailed Implementation

[0012] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0013] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0014] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0015] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0016] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0017] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0018] The vehicle suspension adaptive compensation control method provided in this invention can be applied to any type of vehicle, such as passenger cars, buses, and commercial vehicles, equipped with adjustable suspension actuators. It is particularly suitable for vehicles that may encounter strong crosswinds at high speeds, such as bridges, tunnel exits, and mountain passes. Specifically, the method can be executed by the vehicle chassis domain controller or a separate suspension controller running a computer program with corresponding functions. The suspension controller interacts with the six-axis inertial measurement unit, steering wheel angle sensor, four wheel speed sensors, four suspension height sensors, electronic stability control system, and adjustable suspension actuators via the vehicle controller area network (CAN) bus. This invention does not impose any restrictions on vehicle type.

[0019] like Figure 1 As shown, the vehicle suspension adaptive compensation control method provided in this embodiment of the invention includes the following steps S101 to S105 executed by the suspension controller: Step S101: Obtain the vehicle's motion state and the driver's steering input.

[0020] In application, the motion state variables and the driver steering input provide the raw input for subsequent crosswind disturbance estimation, driver desired response calculation, and anti-roll compensation decision-making. The motion state variables are jointly acquired by a six-axis inertial measurement unit, wheel speed sensors, and suspension height sensors, and include at least vehicle speed, measured lateral acceleration, measured yaw rate, measured roll angle, and measured roll rate. The vehicle speed is obtained by filtering and weighted averaging the wheel speed signals from the four wheel speed sensors. The measured lateral acceleration and measured yaw rate are directly provided by the three-axis accelerometer and three-axis gyroscope in the six-axis inertial measurement unit. The measured roll angle can be obtained either from the attitude calculation output of the six-axis inertial measurement unit or by back-calculating the height difference between the left and right suspension height sensors combined with the suspension geometry. The driver's steering input is acquired by a steering wheel angle sensor, including at least the steering wheel angle. When the vehicle is equipped with an optional onboard ultrasonic anemometer, the suspension controller also simultaneously acquires the measured signal output by the onboard ultrasonic anemometer as a verification signal for subsequent crosswind disturbance estimation. The signals from all the aforementioned sensors are integrated into the signal acquisition and preprocessing submodule within the suspension controller via a CAN bus, and are refreshed synchronously once every typical 10ms control cycle.

[0021] Step S102: Determine the driver's desired response based on the driver's steering input and motion state.

[0022] In application, the driver's desired response is determined solely by the driver's steering intention and current vehicle speed, excluding crosswind disturbances. This provides a benchmark reference for the vehicle's expected response in the absence of crosswinds, serving as the basis for the subsequent crosswind disturbance observer module. A linear two-degree-of-freedom vehicle reference model is pre-built in the suspension controller. Using steering wheel angle and vehicle speed as inputs, the desired yaw rate and desired lateral velocity are calculated online in real time. The difference between this reference model and the measured response calculated from the total disturbances experienced by the actual vehicle (including crosswinds) represents the vehicle motion deviation caused by crosswind disturbances and other non-driver-intended disturbances, providing a basis for subsequent decoupling determination.

[0023] Step S103: Based on the motion state quantity and the driver's expected response, estimate the crosswind disturbance quantity experienced by the vehicle online to obtain the crosswind disturbance estimate.

[0024] In application, the suspension controller executes a crosswind disturbance observer module recursion once in each control cycle. The motion state variables and the driver's desired response are input into the crosswind disturbance observer module, which is composed of a driver reference model and an augmented state Kalman filter. The module outputs online estimates of the crosswind lateral force and crosswind yaw moment for the current control cycle as the crosswind disturbance estimate. This estimation process is based on the vehicle's lateral-yaw-roll coupled dynamics model. The crosswind disturbance is treated as an augmented state variable to be estimated and incorporated into the state vector for joint recursion. This allows the crosswind disturbance, which cannot be directly measured, to be inverted online through measurable motion state variables. Furthermore, the difference between the reference model and the measured response effectively decouples the driver's steering intention from the crosswind disturbance.

[0025] Step S104: Determine the anti-roll compensation amount for suppressing vehicle body roll based on the crosswind disturbance estimate.

[0026] In application, the suspension controller jointly determines the anti-roll compensation amount on two levels based on the crosswind disturbance estimate: First, the feedforward channel, where the suspension controller takes the estimated crosswind lateral force from the crosswind disturbance estimate as input and directly determines the feedforward axle load transfer amount for each wheel according to a pre-calibrated axle load transfer relationship to quickly establish the main anti-roll moment; second, the feedback channel, where the suspension controller uses a three-degree-of-freedom vehicle model including roll degrees of freedom as the prediction model. Based on the equivalent anti-roll moment of the feedforward axle load transfer amount for each wheel as a known feedforward input, the suspension controller solves for the expected anti-roll moment and expected additional yaw moment not covered by the feedforward channel. The feedforward channel and the feedback channel are linearly superimposed at the physical level of force; the former achieves rapid pre-compensation, and the latter achieves fine-tuning, together constituting the anti-roll compensation amount.

[0027] Step S105: Distribute the anti-roll compensation amount to the adjustable suspension actuator to perform adaptive compensation.

[0028] In application, the suspension controller allocates functions based on the frequency response characteristics of the adjustable suspension actuators: the low-frequency component of the anti-roll compensation is allocated to the adjustable suspension actuator (typically a combination of an air spring and a height control valve) for generating continuous vertical force, used to establish steady-state axle load transfer and basic anti-roll stiffness; the high-frequency component is allocated to the adjustable suspension actuator (typically a continuously damped control shock absorber) for generating transient damping force, used to quickly suppress transient roll impacts. Meanwhile, since the suspension system lacks the physical basis to generate yaw moment about the vehicle's vertical axis, the expected additional yaw moment obtained from the predictive model in the anti-roll compensation is not allocated to the adjustable suspension actuators, but is instead sent via the CAN bus to the electronic stability control system, where it is executed by the differential braking module.

[0029] The typical duration of each control cycle of the method is 10ms. In each control cycle, the suspension controller executes steps S101 to S105 in sequence and outputs control commands to the PWM drive circuit of the height control valve, the solenoid valve current drive circuit of the continuous damping control shock absorber, and the CAN bus receiving port of the electronic stability control system.

[0030] By simultaneously acquiring motion state quantities and driver steering input in step S101, subsequent steps can obtain the vehicle's measured response and driver intent within the same control cycle, avoiding the delay in control intervention caused by sensor detection lag in the "detect-then-respond" mode. By calculating the driver's expected response using a two-degree-of-freedom vehicle reference model in step S102, the crosswind disturbance observer module obtains a benchmark for the vehicle's response when there is no crosswind, providing necessary reference for decoupling driver intent and crosswind disturbance. By using the difference between the motion state quantities and the driver's expected response as input in step S103, the crosswind disturbance estimate is recursively derived online, making the crosswind lateral force and crosswind yaw moment, which cannot be directly measured, quantifiable signals that can be acquired online. This solves the problem of existing technologies relying on lateral acceleration or yaw rate to judge, which easily confuses driver steering intent with crosswind disturbance. By using both feedforward and feedback channels to jointly decide anti-roll compensation in step S104, the anti-roll compensation is determined. The system can establish the main anti-roll moment immediately upon identification of crosswind disturbances via the feedforward channel, thus significantly shortening the response time. Simultaneously, the feedback channel can perform refined solutions for residual disturbances not covered by the feedforward channel, avoiding insufficient control accuracy from a single channel. By performing frequency domain division of labor according to the frequency response characteristics of the adjustable suspension actuators in step S105, and assigning yaw moment tasks not belonging to the suspension's physical capabilities to the electronic stability control system, the design error of generating yaw moment in the suspension—which contradicts vehicle dynamics principles—is avoided, ensuring the entire scheme is physically consistent and engineering-feasible. In summary, without adding additional sensor hardware, the method integrates crosswind disturbance identification, decoupling, feedforward pre-compensation, feedback correction, frequency domain division of labor, and physical channel separation into a closed-loop process within a 10ms control cycle. This results in significantly reduced peak roll angle, significantly reduced yaw rate overshoot, and significantly shortened settling time compared to existing crosswind control schemes.

[0031] In one embodiment, step S102 includes: Using the steering wheel angle in the driver's steering input and the vehicle speed in the motion state as inputs to the linear two-degree-of-freedom vehicle reference model, the linear two-degree-of-freedom vehicle reference model is solved to obtain the desired yaw rate and desired lateral speed, which are used as the driver's desired response. The linear two-degree-of-freedom vehicle reference model is as follows: In the formula, The desired lateral velocity, The desired yaw rate, The steering wheel angle, , Let be the coefficient matrix of the linear two-degree-of-freedom vehicle reference model.

[0032] In application, the linear two-degree-of-freedom vehicle reference model describes the coupling relationship between the vehicle's lateral dynamics and yaw dynamics, using only steering wheel angle and vehicle speed as external excitations, and excluding crosswind disturbance terms; its coefficient matrix and The matrix is ​​determined by the vehicle's mass, moment of inertia about the vertical axis, wheelbase, front and rear axle lateral stiffness, and current vehicle speed, where vehicle speed is a time-varying parameter. and The model's output is refreshed online once per control cycle. and This represents the yaw rate and lateral velocity that the vehicle should produce at the current speed, driven by the current steering wheel angle, and without any external disturbances, i.e., the driver's true steering intention. The output of this model is directly fed into the state observer described in step S103, and participates in the decoupling estimation of crosswind disturbances as two components of the driver's desired response.

[0033] By physically separating driver intent from crosswind disturbance at the model level, the subsequent crosswind disturbance observer module can accurately distinguish how much of the vehicle response is due to driver active control and how much is due to external crosswind disturbance, eliminating the possibility of misjudging driver active steering as crosswind disturbance in existing threshold-triggered schemes. By using a two-degree-of-freedom model with the simplest structure and the least computational cost to solve for driver intent, the computation time of the reference model itself is much less than a typical control cycle compared to using a high-order nonlinear vehicle model, and therefore will not become a real-time bottleneck for the online recursion of the crosswind disturbance observer module. By updating the coefficient matrix online with the current vehicle speed, the reference model can output the expected response that matches the actual vehicle handling characteristics at low speed, high speed, and gear transition conditions, avoiding high-speed distortion under low-speed parameters or low-speed distortion under high-speed parameters, and keeping the crosswind disturbance recognition accuracy stable across the entire vehicle speed range.

[0034] In one embodiment, step S103 includes: Using the motion state quantity and the steering wheel angle in the driver steering input quantity as the input of the state observer, the state observer performs online recursive estimation of the state vector of the pre-built state space model and outputs the crosswind disturbance estimation vector of the current control cycle as the crosswind disturbance estimation quantity. The state vector of the state-space model is: The observation vector of the state-space model is: The crosswind disturbance estimation vector is: In the formula, , , , These are lateral velocity, yaw rate, roll angle, and roll rate, respectively. The crosswind lateral force, The crosswind yaw moment, , , These are the measured lateral acceleration, measured yaw rate, and measured roll angle, respectively. , The first Each control cycle , The estimated value.

[0035] In application, the state observer specifically adopts an augmented state extended Kalman filter structure based on a driver reference model. The state space model is based on coupled equations including lateral dynamics, yaw dynamics, and roll dynamics, and uses crosswind lateral force and crosswind yaw moment as augmented state variables and vehicle inherent motion state variables. , , , Together, they form a 6-dimensional state vector for joint online estimation; the crosswind lateral force and the crosswind yaw moment are modeled according to a first-order Markov process to reflect the time-varying characteristics of the crosswind disturbance. In the formula, , For process noise, , The time constant is used. This is combined with the vehicle's four-wheel lateral-roll coupling dynamics equations. And the observation equations implemented by the IMU and suspension height sensor. The entire nonlinear system model can be expressed as: In the formula, The process noise has the following covariance matrix: ; To measure noise, its covariance matrix is: The extended Kalman filter in each control cycle The state vector is estimated recursively by performing one prediction step and one update step in sequence: Prediction step: The state transition Jacobian matrix is: Update steps: The observation Jacobian matrix is: In the formula, , These represent the prior state estimate and prior covariance given in the prediction step, respectively. , These are the posterior state estimate and posterior covariance given by the update step, respectively. Here is the Kalman gain matrix. Let be the observation vector for the k-th control period. After completing one prediction update recursion in each control period, the augmented state component is extracted from the updated posterior state estimate. The crosswind disturbance estimation vector for the current control cycle is composed and output as the crosswind disturbance estimate. The expected yaw rate in the driver's expected response is used as an auxiliary reference quantity in the decoupling determination (see the relevant description of the decoupling criteria in the subsequent embodiments) to determine whether the currently estimated disturbance truly originates from the crosswind.

[0036] By incorporating crosswind lateral force and crosswind yaw moment as augmented state variables into the state vector and jointly estimating them online with the vehicle's motion state, crosswind disturbances, which were originally unmeasurable by sensors, are transformed into quantifiable signals that can be acquired online. This breaks through the passive response mode that can only detect crosswinds after a significant deviation in vehicle posture. By modeling crosswind disturbances as a first-order Markov process, the augmented state Kalman filter has a reasonable time evolution model for crosswind disturbances, avoiding treating them as white noise and making the estimation memoryless, and also avoiding treating them as constant quantities and making the estimation unable to follow the transient changes of the actual crosswind. By using a driver reference model... The output, serving as a priori reference, works in conjunction with the extended Kalman filter to ensure that the estimation results only include components truly attributable to crosswinds. It avoids mistakenly including vehicle responses caused by driver steering in the disturbance estimation, providing a high-confidence signal for subsequent decoupling decisions and feedforward compensation. The extended Kalman filter, implemented through online refresh of the coefficient matrix, enables the observer to provide accurate estimates even with changes in vehicle speed, tire lateral stiffness, and suspension equivalent stiffness. It adapts to various crosswind scenarios, such as bridges, tunnel exits, and mountain passes, and obtains a fast, accurate, and driver-intention-decoupled crosswind disturbance signal, providing the necessary prerequisite for all downstream compensation stages.

[0037] In one embodiment, such as Figure 2 As shown, after obtaining the crosswind disturbance estimate, the process further includes: Step S301: When the absolute value of the steering wheel angle is less than the set steering wheel angle threshold, and the absolute value of the estimated crosswind force is greater than the set crosswind force threshold, it is determined that the current lateral excitation originates from crosswind disturbance. Step S302: When the absolute value of the steering wheel angle is not less than the steering wheel angle threshold, calculate the difference between the measured yaw rate and the expected yaw rate in the driver's expected response, and when the difference shows high-frequency asymmetric pulse characteristics, determine it as crosswind disturbance superimposed under the curve condition. Step S303: Obtain the measured crosswind disturbance signal. When the correlation between the measured crosswind disturbance signal and the crosswind disturbance estimate is lower than a set threshold, reduce the confidence weight of the crosswind disturbance estimate within the corresponding control period.

[0038] In application, the steering wheel angle threshold With the crosswind lateral force threshold Determined by real-vehicle calibration, these represent two boundaries: one where the driver has not initiated significant steering, and the other where the crosswind disturbance amplitude needs to be considered. The first criterion (straight-ahead crosswind recognition): when the steering wheel angle meets... And the crosswind lateral force estimate output by the observer satisfies At this time, it can be assumed that the vehicle is close to a straight-line state and the driver has no obvious intention to turn. The observed lateral excitation is mainly caused by crosswind disturbance. At this time, the crosswind disturbance estimation vector is directly identified as being generated by crosswind disturbance and sent as an effective input to the downstream compensation decision module.

[0039] Second criterion (Identification of crosswinds on curves): When the steering wheel angle meets the following conditions... At this time, the driver is actively steering, and estimating the amplitude solely based on the crosswind lateral force is insufficient to determine the nature of the disturbance. Therefore, the suspension controller calculates the difference between the measured yaw rate and the desired yaw rate in the driver's expected response: When there is no crosswind, this difference The main causes are model errors and road slope, with small amplitude, gradual changes, and a high correlation with steering wheel angle and its rate of change. However, when crosswinds are superimposed on curves, this difference will contain high-frequency asymmetric pulse components that cannot be explained by steering wheel angle and its rate of change, and these components are also related to the estimated crosswind yaw moment of the same period. They appear consistently in chronological order, and further in and When the two satisfy the aerodynamic coupling relationship of the vehicle (the ratio of the two is close to the longitudinal offset from the aerodynamic pressure center to the center of mass), it can be determined as the crosswind disturbance superimposed under the curve condition; at this time, the crosswind disturbance estimation vector is identified as the crosswind disturbance component superimposed in the curve, rather than the vehicle response generated by the driver's steering itself.

[0040] The third criterion (verification of measured signals): When the vehicle is equipped with optional onboard ultrasonic anemometers or other crosswind disturbance measurement signal sources, the suspension controller acquires the measured crosswind disturbance signal in each control cycle and compares its correlation with the crosswind disturbance estimate; when the correlation between the two is lower than a set threshold (e.g., the lower limit of the statistical cross-correlation coefficient), the reliability of the estimation result in this cycle is considered to have decreased, thereby reducing the confidence weight of the crosswind disturbance estimate in the downstream feedforward and feedback channels in this cycle, so as to avoid erroneous estimation that induces unexpected actions of the actuator.

[0041] By setting a straight-ahead crosswind recognition criterion that combines a steering wheel angle threshold and a crosswind lateral force threshold, the system can confidently attribute all estimated lateral excitations to crosswind disturbances when the driver is not steering. This allows for a rapid and clear response to sudden crosswinds without waiting for significant deviations in vehicle posture, shortening the time margin from disturbance occurrence to compensation activation. Furthermore, by calculating the difference between the measured and expected yaw rates under active steering conditions and identifying high-frequency asymmetric pulse characteristics that cannot be explained by steering input, the system can correctly identify the crosswind component superimposed on the driver's steering even when navigating curves through bridges, mountain passes, and other areas with strong crosswinds, thus avoiding [further issues]. The system avoids the disturbance caused by accidental activation during normal cornering and prevents missed detection when encountering crosswinds in curves. By introducing measured crosswind disturbance signals as a reliability check for the estimation results, the system has the ability to self-inhibit modeling errors or temporary divergences that may occur in the observer under extreme conditions. When the correlation is low, the system reduces the confidence weight and gives control to the feedback channel instead of blindly executing feedforward, thereby significantly reducing the probability of abnormal actuator action caused by accidental triggering. The synergistic effect of the above three criteria ensures that the crosswind disturbance estimate maintains high accuracy and high reliability under straight driving, curves, and severe disturbance conditions, providing a clean and reliable input signal for downstream feedforward pre-compensation and model prediction feedback correction.

[0042] In one embodiment, step S104 includes: The crosswind lateral force estimate in the crosswind disturbance estimate is used as input, and the feedforward axle load transfer amount of each wheel is determined according to the preset axle load transfer relationship. The feedforward axle load transfer amount of each wheel is used as the anti-roll compensation amount. The calculation relationship for the feedforward axle load transfer of each wheel is as follows: In the formula, , , , These represent the feedforward axle load transfer amounts for the left front, right front, left rear, and right rear wheels, respectively. For the height of the vehicle's center of gravity, This refers to the front track width. Rear track width , These are the front axle distribution coefficient and the rear axle distribution coefficient, respectively.

[0043] In application, the feedforward channel is a key component for achieving rapid pre-compensation in this embodiment of the invention. The suspension controller extracts the estimated crosswind lateral force from the crosswind disturbance estimate in each control cycle. The steady-state feedforward axle load transfer required to resist crosswind roll is directly calculated based on the vehicle's geometric parameters and axle load distribution relationship. The feedforward distribution coefficients satisfy the constraints. Its specific value is obtained by calibrating the equivalent roll stiffness ratio of the front and rear suspensions. In a physical sense, After the height of the center of mass With wheelbase , The conversion of geometric parameters is transformed into an addition and subtraction between the left and right wheels, and a change in the front and rear axles. , The weighted axle load transfer amount cancels out the roll moment caused by crosswinds at the adjustable suspension actuator level, allowing the feedforward channel to proactively establish the main anti-roll moment before significant vehicle roll occurs, based solely on the crosswind lateral force estimate. This maximizes the use of feedforward lead to shorten system response lag, without waiting for the air springs' own frequency response establishment process. In this embodiment, the feedforward axle load transfer amount for each wheel serves as the anti-roll compensation amount.

[0044] By directly inputting the estimated crosswind lateral force value and calculating the feedforward axle load transfer amount according to a preset geometric relationship, the system can output the main anti-roll command within the same control cycle as soon as the crosswind disturbance is identified. Compared with the scheme based on roll response feedback, this significantly shortens the intervention time and maximizes the timing advantage of feedforward pre-compensation. By weighting the anti-roll tasks of the front and rear axles with the front and rear axle distribution coefficients, the front and rear suspensions share a reasonable proportion of axle load transfer according to their respective equivalent roll stiffness, avoiding single-axle overload or insufficient anti-roll contribution of a certain axle. By converting the complex three-dimensional vehicle dynamics into a simple algebraic relationship, the computational load of the feedforward channel is minimized, and it can be refreshed multiple times within each 10ms control cycle, ensuring that the feedforward command has sufficient tracking bandwidth for crosswind fluctuations. This feedforward channel and the subsequent feedback channel are superimposed and coordinated under the same anti-roll compensation framework. The former undertakes the main compensation and the latter undertakes the correction compensation. The two complement each other without conflict, and together they constitute a fast and precise anti-roll compensation capability.

[0045] In one embodiment, step S104 further includes: Using a three-degree-of-freedom vehicle model that includes roll freedom as the prediction model, the steady-state anti-roll moment corresponding to the feedforward axle load transfer of each wheel is added to the prediction model as a known feedforward input term; Based on the prediction model, under the constraints of virtual torque amplitude, virtual torque change rate, tire adhesion limit and suspension travel, the expected anti-roll moment and expected additional yaw moment not covered by the feedforward are solved. The discretized state equation of the prediction model is: Among them, state variables The control quantity is virtual torque. Disturbance term Provided by the crosswind disturbance estimate, , , , This is a coefficient matrix that is updated online based on the current vehicle speed, tire lateral stiffness, and equivalent suspension roll stiffness. The desired anti-rolling moment, Add a yaw moment to the desired value.

[0046] In application, the model prediction feedback correction is specifically implemented by the Model Predictive Controller (MPC) module within the suspension controller. The MPC module performs a rolling optimization solution once per control cycle, using the aforementioned three-degree-of-freedom vehicle discretized state equations, including roll degrees of freedom, as the prediction model within a length of... The predicted state trajectory is recursively projected forward within the time domain. The objective function is: In the formula, For reference output, it includes the desired roll angle (usually set to zero, i.e., to suppress roll) and the desired yaw rate in the driver's desired response. ; The output error weight matrix is... To control the incremental weight matrix, For the terminal cost matrix, To predict the length of the time domain, This term is introduced to control the increment and make the change in the control quantity smooth.

[0047] The MPC module considers the following constraints during the solution process, and these constraints take effect in each prediction step: Virtual torque amplitude constraint: Virtual torque rate of change constraint: Tire adhesion limit constraints (for each wheel ij): That is, the lateral force amplitude of each wheel does not exceed the road surface adhesion coefficient. The product of the vertical load on the wheel, and from this, the following can be derived. and The joint constraint boundary.

[0048] Suspension travel constraints: That is, the roll angle amplitude does not exceed the suspension mechanical limits. To avoid mechanical impacts to the suspension.

[0049] The MPC module transforms the constrained quadratic optimization problem into a standard quadratic programming (QP) form in each control cycle, solves it online using the interior point method or the effective set method, obtains the optimal virtual torque sequence, and takes the first element as the desired anti-rolling torque output for the current control cycle. With expected additional yaw moment .

[0050] The feedforward and feedback channels are seamlessly integrated at the prediction model level: the steady-state anti-rolling moment corresponding to the feedforward axle load transfer amount of each wheel is denoted as... The torque is not applied independently of MPC, but is written into the prediction model as a known feedforward input, so that the prediction model has already taken into account the contribution of the feedforward channel to the vehicle roll when recursively estimating the state trajectory. Therefore, the optimization variables of MPC only need to be the residual anti-roll moment and additional yaw moment not yet covered by the feedforward channel, and the solved... This represents the incremental correction to the feedforward channel, while the actual low-frequency anti-roll torque borne by the air spring is equal to the feedforward component. After being decomposed from the downstream frequency domain Low-frequency components obtained from the middle The sum of these two methods preserves the speed of feedforward pre-compensation while using feedback channels to refine the residual error between the prediction model and the actual vehicle. Furthermore, the coordination mechanism of the prediction model itself prevents the two channels from repeatedly compensating for the same crosswind disturbance.

[0051] By incorporating the steady-state anti-rolling moment corresponding to the feedforward axle load transfer of each wheel into the prediction model as a known feedforward input, the state prediction of MPC includes all steady-state contributions from the feedforward channels. This avoids repeated compensation for the same crosswind disturbance by both the feedforward and feedback channels, and avoids overcompensation and frequent actuator switching caused by the superposition of dual-path compensation. Furthermore, by using the crosswind disturbance estimation vector as an explicit disturbance term in the prediction model... This approach allows the MPC to consider the future impact of crosswinds when recursively calculating the state trajectory, providing significant foresight compared to schemes that only rely on current state feedback for control, thus solving the response lag problem. By performing constrained rolling optimization under virtual torque amplitude, rate of change, tire adhesion limits, and suspension travel constraints, the desired anti-roll torque and desired additional yaw torque are always kept within the physically executable range, avoiding actuator saturation or tire slippage due to constraint conflicts. By updating the coefficient matrix online based on vehicle speed, tire lateral stiffness, and equivalent suspension roll stiffness to form a linear time-varying prediction model, the MPC can provide the optimal solution matching the current vehicle physical characteristics under low speed, high speed, variable speed, and different road adhesion conditions. By using a quadratic objective function with control increment weighting rather than absolute control quantity weighting, the generated control commands change smoothly and oscillations are suppressed. Combined with the inherent multi-step look-ahead characteristics of the MPC, this significantly improves control accuracy and ride comfort compared to existing threshold-based switching control schemes.

[0052] In one embodiment, step S105 includes: For the desired anti-rolling moment Low-pass filtering is performed to obtain the low-frequency component. and extract high-frequency components. ; The low-frequency component is solved into the feedback axle load adjustment amount for each wheel, and the calculation formula for the feedback axle load adjustment amount for each wheel is as follows: The feedforward axle load transfer amount and the feedback axle load adjustment amount of each wheel are superimposed to obtain the total axle load target value of each wheel: The suspension adjustable actuators used to generate continuous vertical force are controlled according to the target value of the total axle load of each wheel, and the high-frequency components are distributed to the suspension adjustable actuators used to generate transient damping force. In the formula, , This is the torque-axle load conversion factor. , , These are the total axle load target value, feedforward axle load transfer amount, and feedback axle load adjustment amount for the same cycle, respectively.

[0053] In application, the adjustable suspension actuator for generating continuous vertical force is specifically a combination of an air spring and a height control valve, while the adjustable suspension actuator for generating transient damping force is specifically a continuously damped control (CDC) shock absorber. The former relies on the gas compression characteristics to provide a large load-bearing, low-bandwidth steady-state vertical force, suitable for steady-state / gradually changing anti-roll tasks. The latter relies on a solenoid valve to adjust the damping coefficient in real time to provide transient damping force related to the relative motion speed of the suspension, suitable for high-frequency transient anti-roll tasks. Based on this, a frequency domain division strategy is designed to create an adjustable cutoff frequency first-order low-pass / high-pass filter. In the frequency domain, it is decomposed into low-frequency components. With high frequency components Considering that the demand for high-frequency anti-roll capability increases with higher vehicle speeds and faster crosswind fluctuations, the cutoff frequency is adaptively adjusted according to the current vehicle speed and crosswind fluctuation frequency using the following formula: In the formula, The cutoff frequency used in the current control cycle. The base cutoff frequency is typically 1~2Hz. Current vehicle speed; The frequency of crosswind fluctuations is determined by the observer. Zero-crossing rate or spectral analysis estimation of the signal; , This is for calibrating the gain coefficient. This adaptive adjustment law enables the CDC vibration damper to handle more high-frequency components under high-speed and high-frequency disturbance conditions, making full use of its fast response capability.

[0054] Low frequency components The torque-axle load conversion relationship is used to calculate the feedback axle load adjustment amount for each wheel, which is then linearly superimposed with the feedforward axle load transfer amount for each wheel output by the feedforward channel at the force level to obtain the target value of the total axle load for each wheel. The total axle load target value is constrained by the tire load-bearing capacity. After being superimposed on the static load of each wheel, the target air pressure is calculated based on the effective area and stiffness characteristics of the air springs. The system uses PWM signals to drive the intake and exhaust solenoid valves of the height control valve, performing closed-loop regulation of the air pressure in the four airbags within each control cycle, thereby achieving steady-state shaft load transfer and establishing the foundation's anti-tilting stiffness. (High-frequency components) The target damping force of the CDC shock absorber is calculated by combining the relative motion speed of each wheel suspension. Then, the target current of the solenoid valve of each wheel CDC is obtained according to the damping force-solenoid valve current calibration curve of the CDC shock absorber. The current drive circuit drives the continuous damping control shock absorber in real time to respond quickly and suppress transient roll at the moment of suspension impact. It should be noted that the CDC shock absorber is a semi-active dissipation device. It can only track the high-frequency torque component in the dissipation quadrant where the damping force is opposite to the relative motion speed of the suspension. When the required high-frequency force needs to be in the same direction as the motion, that is, when energy is actively injected, the CDC is truncated according to its achievable minimum / maximum damping boundary. The unachieved torque residual is taken over by the air spring roll stiffness channel and subsequent cooperative safety mode.

[0055] By decomposing the desired anti-tilting moment into low-frequency and high-frequency components in the frequency domain using a low-pass / high-pass filter and distributing them to the air spring and continuously damped control damper respectively, the two types of actuators each undertake the task in the frequency band where their physical characteristics best match. The air spring handles steady-state axle load transfer without having to deal with high-frequency impacts outside its bandwidth, while the continuously damped control damper handles transient damping force without having to maintain steady-state load for a long time. The physical advantages of the two types of actuators complement each other. By adaptively adjusting the cutoff frequency according to vehicle speed and crosswind fluctuation frequency, the boundary of frequency domain division dynamically matches the spectral characteristics of crosswind under different operating conditions, avoiding situations where a fixed cutoff frequency scheme results in one actuator exceeding its bandwidth capacity under high speed or strong variable frequency crosswinds. By combining the feedforward axle load transfer amount with the... The feedback shaft load adjustment is linearly superimposed at the force level rather than the torque level, so that the steady-state compensation of the feedforward channel and the fine correction of the feedback channel are naturally integrated in physical entity without logical conflict. The superposition result directly corresponds to the target air pressure of the air spring. By truncating the CDC damper in the active quadrant according to its achievable boundary and transferring the unrealized torque residual to the air spring roll stiffness channel and subsequent cooperative safety mode, the entire frequency domain allocation strategy can ensure execution reliability without relying on the assumption that the CDC exceeds its physical feasible region. In summary, the actuator allocation scheme significantly reduces the total energy consumption compared to the single CDC scheme, significantly accelerates the transient response compared to the single air spring scheme, and maintains a smooth and oscillating anti-roll control effect across the entire frequency band.

[0056] In one embodiment, the desired additional yaw moment Mz,des is applied to the vehicle via differential braking by the electronic stability control system: When the measured yaw rate is less than the expected yaw rate in the driver's expected response, brake the inner rear wheel; When the measured yaw rate is greater than the expected yaw rate, brake the outer front wheel; The braking pressure amplitude of the differential braking is positively correlated with the amplitude of the desired additional yaw moment.

[0057] In application, the suspension system primarily generates roll moments around the vehicle's longitudinal axis through vertical force adjustment, making it difficult to generate yaw moments around the vehicle's vertical axis that can be directly used for yaw stability control. Although vertical load transfer has a slight impact on yaw through tire vertical load-lateral coupling, its magnitude and controllability are insufficient to handle yaw control tasks. Therefore, the desired additional yaw moment obtained from step S104 is... Instead of being assigned to the suspension actuators, the brakes are sent by the suspension controller to the vehicle's electronic stability control system via the CAN bus. The differential brake control unit of the electronic stability control system then translates this into a single-wheel braking pressure command according to the following logic: When When the vehicle exhibits understeer, the differential brake control unit of the electronic stability control system applies braking pressure commands to the inner rear wheel (i.e., the inner rear wheel in the direction the driver desires to yaw, determined by the sign of the steering wheel angle), to increase the vehicle's active yaw response; when When the vehicle exhibits an oversteer tendency, the differential brake control unit of the electronic stability control system applies braking pressure commands to the outer front wheel to suppress excessive yaw response. In both cases, the amplitude of the target braking pressure is similar to... The amplitude is positively correlated and is obtained by reverse lookup from the pressure-yaw moment calibration curve of the hydraulic control unit (HCU) of the electronic stability control system. The differential braking command is executed in parallel with the anti-roll command output by the suspension controller via the CAN bus. The two are independent at the execution level and there is no command coupling.

[0058] By explicitly assigning the yaw moment task to the electronic stability control system, rather than forcibly causing the suspension system to generate yaw moments beyond its physical capabilities, the entire compensation scheme can be directly deployed on the existing chassis domain controller. By automatically selecting the braked wheels based on the relationship between the measured yaw rate and the driver's desired yaw rate, differential braking can both increase the vehicle's active yaw response during understeer and suppress unexpected yaw motion during oversteer, covering two typical yaw instability trends under crosswind conditions. By binding the target braking pressure amplitude and the desired additional yaw moment amplitude as a positive correlation, the braking intensity and yaw control requirements are matched in magnitude, avoiding deceleration fluctuations and brake wear caused by excessive braking, and also avoiding yaw control failure caused by insufficient braking. By issuing differential braking commands and suspension anti-roll commands in parallel at the execution level via the CAN bus, the suspension's anti-roll task and the ESC's anti-yaw task are completely separated in physical channels and executed in parallel in time, achieving optimal vehicle stability under crosswind conditions.

[0059] In one embodiment, the method further includes switching between at least four control modes with hysteresis based on crosswind disturbance estimates, yaw rate deviations, and vehicle roll angles; the at least four control modes include a normal mode, a pre-compensation mode, an active compensation mode, and a cooperative safety mode. When the crosswind disturbance estimate meets the first entry condition, the pre-compensation mode is switched from the normal mode, and the application of the feedforward axle load transfer amount of each wheel is activated. When at least one of the crosswind disturbance estimate, the yaw rate deviation, or the vehicle roll angle meets the second entry condition, the active compensation mode is switched in, and the feedforward axle load transfer of each wheel and the model prediction feedback correction are activated. When the adjustable suspension actuator reaches saturation and the yaw rate deviation meets the third entry condition, the cooperative safety mode is activated, the compensation output of the adjustable suspension actuator is locked, the electronic stability control system takes over the yaw control, and the vehicle height is reduced.

[0060] In application, the mode switching module within the suspension controller performs a mode determination and switching once in each control cycle. The mode switching module estimates the amplitude based on the crosswind lateral force. yaw rate deviation amplitude with body roll angle As a basic criterion, and based on the state parameters of each adjustable suspension actuator (such as the maximum air pressure of the air spring)... Continuous damping control vibration damper maximum current With saturation mark Brake pedal status and the current vehicle speed provided by the electronic stability control system via the CAN bus. With road surface adhesion coefficient As an auxiliary criterion, all decision thresholds incorporate hysteresis characteristics and are used in conjunction with a hysteresis timer. Exit confirmation is performed to prevent the pattern from oscillating frequently near the threshold boundary.

[0061] The main logic of the mode switching process within each control cycle consists of the following four steps.

[0062] Step 1: Update the dynamic threshold. The mode switching module updates the dynamic threshold based on the current vehicle speed. With road surface adhesion coefficient Lookup table to update pre-compensation threshold Active compensation threshold Maximum tolerance for yaw rate deviation in normal mode Active compensation trigger deviation threshold Collaborative security mode trigger deviation threshold With roll angle threshold and the corresponding hysteresis , Among the typical values, This corresponds to a slight crosswind (wind speed of approximately 8 m / s). This corresponds to a significant crosswind (wind speed of approximately 12 m / s). Greater than .

[0063] Step two, exit the current mode judgment (rollback from high mode to low mode). All exit conditions must be met continuously for a specified time to take effect, managed by a hysteresis timer. When the current mode is cooperative security mode, if , If the driver has not pressed the brake pedal, and all three conditions are met simultaneously for a duration of at least 5 seconds, the coordination indicator will be reset, and the electronic stability control system will be notified to gradually release the brakes, the vehicle body will return to standard height, the mode will revert to pre-compensation mode, and the hysteresis timer will be cleared; if the current mode is active compensation mode, if , If both conditions are met simultaneously and the duration is not less than 3 seconds, the mode will revert to pre-compensation mode and the hysteresis timer will be cleared; when the current mode is pre-compensation mode, if If the duration is not less than 2 seconds, the mode will revert to normal mode and the hysteresis timer will be cleared.

[0064] Step 3: Enter a higher mode judgment (upgrade from low mode to high mode). Upgrade conditions are checked from highest to lowest priority; once met, the process begins immediately without delay. The condition for upgrading to cooperative safety mode (entering from active compensation mode) is: the air pressure of any air spring ≥ Or the CDC current equals (Suspension saturation), and If the duration is not less than a delay (e.g., 200ms), the mode switches to cooperative safety mode, executes the cooperative safety entry sequence, and skips subsequent upgrade judgments in this cycle. The condition for proactive compensation mode upgrade (entering from normal or pre-compensation mode) is: the current mode is not equal to cooperative safety mode, and... , or If any one of the three conditions is met, the system switches to active compensation mode, initiating model predictive feedback correction, actuator frequency domain division activation, and feedforward and feedback shaft load coordination activation. The additional yaw torque output by the MPC is transmitted via the CAN bus to the electronic stability control system for differential braking (the yaw control channel is activated from this mode onwards). If the system jumps directly from normal mode, the pre-compensation feedforward basis is established simultaneously in this control cycle. The conditions for upgrading to pre-compensation mode (entering from normal mode) are: the current mode is equal to the normal mode, and... Alternatively, if the onboard ultrasonic anemometer detects a sudden increase in lateral wind speed, the mode will switch to pre-compensation mode, activating feedforward axle load transfer, pre-charging the air springs to approximately 70% of the target air pressure, and keeping the CDC dampers in comfort mode.

[0065] Step four, hysteresis timer management. For the exit condition being monitored, if the cycle is not met, the corresponding timer is immediately reset; if it is met, the control cycle time is incremented. This ensures that the current mode is only exited when the state remains stable, preventing instantaneous fluctuations from causing mode oscillations.

[0066] The cooperative safety mode has a dedicated entry and exit sequence, which is completed collaboratively by the suspension controller and the electronic stability control system via the CAN bus. Let the moment when the entry condition is met be... :exist Suspension controller set coordination flag Equal to 1, mode state machine latch; in Always lock the current air spring pressure With CDC current At the current maximum value, the suspension roll compensation torque is kept constant; Continuous frame messages containing the target yaw moment are sent to the electronic stability control system via the CAN bus. Collaborative activation marker Current vehicle speed With the estimated road surface adhesion coefficient After receiving the data, the electronic stability control system takes over yaw control and initiates differential braking; The suspension controller commands the height control valve to open the exhaust valve, lowering the vehicle body to the calibrated minimum safe position at an allowable rate of approximately 10 mm / s (typically about 30 mm lower than the standard height), reducing the center of gravity and increasing rollover protection. During operation, the MPC background continues to run, but the output... No new compensation commands will be added to the suspension that has been locked to the saturation limit according to the above timing. The suspension will maintain the maximum anti-roll torque output without decay, and will only be used as a reference for the smooth recovery of suspension control when exiting this mode. All actions are performed by the electronic stability control system. When exiting the cooperative safety mode, the suspension controller first notifies the electronic stability control system via CAN to gradually release the braking pressure according to the slope limit (typically no more than -20 bar / s), while the air springs inflate back to their normal height. Reset to 0, exit smoothly.

[0067] By managing the system state in four hierarchical modes—normal, pre-compensation, active compensation, and cooperative safety—the vehicle employs corresponding control strategies under different intensities of crosswinds, such as no crosswind, slight crosswind, significant crosswind, and suspension saturation. This avoids the comfort and energy consumption losses caused by continuously using the highest intensity control, while also preventing the insufficient capability of lightweight control schemes under strong crosswinds, forming a four-layer progressive safety protection. By adding hysteresis to all entry and exit thresholds and combining them with minimum duration constraints, mode switching does not oscillate frequently near the threshold boundaries due to sensor noise or instantaneous disturbances, ensuring the stability and predictability of the vehicle's control behavior. By defining the cooperative safety mode as a dual-condition coupled criterion of suspension actuator saturation and yaw deviation exceeding a severe threshold, this ensures that the mode is only triggered when the suspension is no longer able to further suppress body roll and the yaw control itself shows a significant tendency to become unstable, avoiding unnecessary reduction in vehicle height and resulting in a loss of comfort. Furthermore, by using the cooperative safety mode... , , , The precise timing sequence of four actions—mode latching, suspension saturation locking, ESC takeover, and vehicle lowering—ensures that suspension compensation and braking takeover work in an orderly and coordinated manner within a millisecond-level time window, avoiding any momentary gaps during the handover of control. By maintaining maximum anti-roll output during the operation of the coordinated safety mode without attenuation of the suspension, and simultaneously allowing the MPC to run in the background for smooth recovery upon exit, the vehicle simultaneously receives the strongest anti-roll torque from the suspension and differential braking yaw stabilization capability from the ESC during the most dangerous phase, forming a joint protection of suspension and braking. Upon exiting, the suspension first notifies the ESC to gradually release the brakes according to the slope limit and inflate to restore the vehicle height, avoiding secondary disturbances to the vehicle's posture due to sudden brake removal. The above mode switching logic and coordinated timing sequence together ensure that the invention has both rapid and accurate normal compensation capability under all crosswind conditions and redundant safety protection capability under extreme conditions, significantly improving the vehicle's driving stability and anti-rollover capability on strong crosswind sections such as bridges, tunnel exits, and mountain passes.

[0068] This invention also provides a vehicle suspension adaptive compensation control system for executing the steps described in the embodiments of the vehicle suspension adaptive compensation control method. This system can be run as a virtual device within the vehicle chassis domain controller by the chassis domain controller's processor, or it can exist as an independent suspension controller.

[0069] like Figure 3 As shown, the vehicle suspension adaptive compensation control system 100 provided in this embodiment of the invention includes: The sensing module 101 is used to acquire the vehicle's motion state and the driver's steering input. The crosswind disturbance observer module 102 is used to determine the driver's expected response based on the driver's steering input and vehicle speed, and to estimate the amount of crosswind disturbance experienced by the vehicle online based on the motion state quantity and the driver's expected response, so as to obtain the crosswind disturbance estimate. The compensation decision module 103 is used to determine the anti-roll compensation amount for suppressing vehicle body roll based on the crosswind disturbance estimate. Actuator allocation module 104 is used to allocate the anti-roll compensation amount to the adjustable suspension actuator to perform adaptive compensation; The adjustable suspension actuator includes at least one of an air spring and a continuously damped control shock absorber.

[0070] In application, the vehicle suspension adaptive compensation control system adopts a three-layer architecture of perception layer, decision layer, and execution layer. The perception module belongs to the perception layer, the crosswind disturbance observer module, the compensation decision module and the actuator allocation module belong to the decision layer and are integrated into a suspension controller. The adjustable suspension actuator and the electronic stability control system connected via CAN bus belong to the execution layer.

[0071] The sensing module consists of a six-axis inertial measurement unit (IMU), a steering wheel angle sensor, four wheel speed sensors, four suspension height sensors, and optionally four air spring pressure sensors and an optional onboard ultrasonic anemometer. All sensors are electrically connected to the suspension controller via a CAN bus or a dedicated low-voltage analog / digital signal line. The six-axis IMU is fixedly mounted near the vehicle's center of gravity, with its three-axis accelerometer and three-axis gyroscope's sensitive axes corresponding to the longitudinal, lateral, and vertical axes of the vehicle coordinate system, respectively, outputting measured lateral acceleration. Measured yaw rate Measured roll angle The vehicle's roll angle is measured in conjunction with the actual roll rate signal. A steering wheel angle sensor is fixedly mounted on the steering column, forming a direct mechanical connection with it, and outputs a steering wheel angle δ signal. Four wheel speed sensors are fixedly mounted on the four wheel hubs, each outputting a wheel speed pulse signal to the suspension controller via its signal line to calculate the vehicle speed. Four suspension height sensors are fixedly installed at the connection points between the vehicle body and the suspension, outputting the suspension height at each corner. Signal; four optional air spring pressure sensors are installed at the inlet of the air chambers of the four air springs, outputting the corresponding air pressure. Signal; An optional vehicle-mounted ultrasonic anemometer is fixedly installed on the roof or front bulkhead, outputting a measured wind speed signal as a verification signal for estimating crosswind disturbance. Multiple signals output from the sensors in the aforementioned sensing module are collected via a CAN bus to the signal acquisition and preprocessing submodule inside the suspension controller, and synchronously refreshed at a 10ms control cycle.

[0072] The crosswind disturbance observer module exists as a program module embedded within the suspension controller, consisting of a driver reference model submodule and an augmented state extended Kalman filter submodule connected sequentially. The input port of the driver reference model submodule is connected to the preprocessed signal ports of the steering wheel angle sensor and wheel speed sensor in the sensing module via the internal data bus of the suspension controller, receiving signals respectively. and Its output port sends out and The augmented state extended Kalman filter submodule, as well as the compensation decision module and mode switching module, serve as the driver's desired response. The augmented state extended Kalman filter submodule has two input ports: one receives the observation vector z composed of measured lateral acceleration, measured yaw rate, and measured roll angle from the self-sensing module; the other receives data from the driver reference model submodule. , As a priori reference; its output port sends out the 6-dimensional posterior state estimation vector via the internal data bus. , Downstream compensation decision-making module and mode switching module.

[0073] The compensation decision module also exists as a program module within the suspension controller, consisting of two sub-units: the feedforward channel sub-module and the model prediction controller sub-module, working in parallel within the same anti-roll compensation framework. The input port of the feedforward channel sub-module receives the output from the crosswind disturbance observer module. Its output port sends out the feedforward axle load transfer amount for each wheel. and the corresponding equivalent anti-rolling moment The model predictive controller submodule has three input ports, which receive: the measured motion state quantities from the self-sensing module, the crosswind disturbance estimation vector from the crosswind disturbance observer module, and the equivalent anti-tilting moment from the feedforward channel submodule. As a known feedforward input to the prediction model, its output port is split into two paths, one for the desired anti-rolling moment and the other for the expected anti-rolling moment. With expected additional yaw moment The compensation decision module further integrates a mode switching module. The input port of the mode switching module receives the crosswind disturbance estimate, yaw rate deviation, and vehicle roll angle. Its output port sends the current control mode signal to the feedforward channel submodule, the model prediction controller submodule, and the actuator allocation module to coordinate the activation of each channel.

[0074] The actuator allocation module is also a program module within the suspension controller, consisting of a frequency domain division submodule and a hardware driver interface submodule connected sequentially. The input port of the frequency domain division submodule receives input from the compensation decision module. After low-pass filtering, the result is obtained Subtraction yields ; Further torque-axle load conversion yields the feedback axle load adjustment for each wheel. , and the feedforward channel Linear superposition at the confluence node forms Then calculate the target air pressure. The signal is then output through the PWM drive circuit inside the suspension controller to the height control valves of the four air springs and the solenoid valves for intake and exhaust. The PWM signal line is indirectly electrically connected (through a drive amplification). The damping force, calculated in reverse, is output via the current drive circuit inside the suspension controller to the solenoid valves of the four CDC dampers. The current signal lines are also indirectly electrically connected (via drive amplification). The hardware driver interface submodule also includes a CAN bus transmission channel. The brakes are sent to the CAN receiving port of the electronic stability control system in the form of continuous CAN frames. The differential braking module of the electronic stability control system calculates the braking pressure command of each wheel according to its internal pressure-yaw moment calibration curve, and then drives the brake calipers of each wheel to achieve differential braking through its hydraulic control unit (HCU).

[0075] The four continuously damped control shock absorbers in the actuator layer are fixedly installed at the four corner suspension positions between the suspension and the vehicle body. The shock absorber piston rod is connected to the vehicle body via a rubber bushing, and the shock absorber base is hinged to the lower control arm of the suspension via a pin shaft. The four air springs are fixedly installed at the four corner suspension positions between the suspension and the vehicle body. The air inlet of each air spring is connected to the corresponding height control valve via an air pipe. The air source port of the height control valve is connected to the air compressor and the air tank via an air pipe. When the intake solenoid valve is open, compressed air is indirectly injected into the air chamber via an air pipe. When the exhaust solenoid valve is open, the gas in the air chamber is indirectly discharged via an air pipe, thereby realizing bidirectional adjustment of the air pressure of each air spring. The electronic stability control system communicates with the suspension controller via the vehicle CAN bus. Its internal hydraulic control unit is connected to the brake calipers of each wheel via standard hydraulic lines to form a hydraulic circuit, thereby realizing the physical execution of differential braking commands to the specific wheel braking force.

[0076] In application, each program module in the vehicle suspension adaptive compensation control system can run as a software unit on the processor of the suspension controller or the vehicle chassis domain controller, or it can be implemented through different logic circuits integrated within the suspension controller, or it can be implemented through the collaboration of multiple distributed controllers in the vehicle's electronic and electrical architecture; the specific model selection of the aforementioned sensors, actuators and the suspension controller does not constitute a limitation of the present invention.

[0077] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A vehicle suspension adaptive compensation control method, characterized in that, include: Acquire the vehicle's motion state and the driver's steering input; The driver's desired response is determined based on the driver's steering input and motion state. Based on the motion state quantity and the driver's expected response, the crosswind disturbance quantity experienced by the vehicle is estimated online to obtain the crosswind disturbance estimate. Based on the crosswind disturbance estimate, determine the anti-roll compensation amount used to suppress vehicle body roll; The anti-roll compensation amount is allocated to the adjustable suspension actuator to perform adaptive compensation.

2. The vehicle suspension adaptive compensation control method as described in claim 1, characterized in that, The step of determining the driver's desired response based on the driver's steering input and motion state includes: Using the steering wheel angle in the driver's steering input and the vehicle speed in the motion state as inputs to the linear two-degree-of-freedom vehicle reference model, the linear two-degree-of-freedom vehicle reference model is solved to obtain the desired yaw rate and desired lateral speed, which are used as the driver's desired response. The linear two-degree-of-freedom vehicle reference model is as follows: In the formula, The desired lateral velocity, The desired yaw rate, The steering wheel angle, , Let be the coefficient matrix of the linear two-degree-of-freedom vehicle reference model.

3. The vehicle suspension adaptive compensation control method as described in claim 2, characterized in that, The step of estimating the crosswind disturbance experienced by the vehicle online based on the motion state quantity and the driver's expected response, to obtain the crosswind disturbance estimate, includes: Using the motion state quantity and the steering wheel angle in the driver steering input quantity as the input of the state observer, the state observer performs online recursive estimation of the state vector of the pre-built state space model and outputs the crosswind disturbance estimation vector of the current control cycle as the crosswind disturbance estimation quantity. The state vector of the state-space model is: The observation vector of the state-space model is: The crosswind disturbance estimation vector is: In the formula, , , , These are lateral velocity, yaw rate, roll angle, and roll rate, respectively. The crosswind lateral force, The crosswind yaw moment, , , These are the measured lateral acceleration, measured yaw rate, and measured roll angle, respectively. , The first Each control cycle , The estimated value.

4. The vehicle suspension adaptive compensation control method as described in claim 3, characterized in that, After obtaining the crosswind disturbance estimate, the process also includes: When the absolute value of the steering wheel angle is less than the set steering wheel angle threshold, and the absolute value of the estimated crosswind force is greater than the set crosswind force threshold, it is determined that the current lateral excitation originates from crosswind disturbance. When the absolute value of the steering wheel angle is not less than the steering wheel angle threshold, the difference between the measured yaw rate and the expected yaw rate in the driver's expected response is calculated, and when the difference exhibits high-frequency asymmetric pulse characteristics, it is determined to be crosswind disturbance superimposed under the curve condition. Acquire measured crosswind disturbance signals. When the correlation between the measured crosswind disturbance signals and the estimated crosswind disturbance is lower than a set threshold, reduce the confidence weight of the estimated crosswind disturbance within the corresponding control period.

5. The vehicle suspension adaptive compensation control method as described in claim 3, characterized in that, The step of determining the anti-roll compensation amount for suppressing vehicle body roll based on the crosswind disturbance estimate includes: The crosswind lateral force estimate in the crosswind disturbance estimate is used as input, and the feedforward axle load transfer amount of each wheel is determined according to the preset axle load transfer relationship. The feedforward axle load transfer amount of each wheel is used as the anti-roll compensation amount. The calculation relationship for the feedforward axle load transfer of each wheel is as follows: In the formula, , , , These represent the feedforward axle load transfer amounts for the left front, right front, left rear, and right rear wheels, respectively. For the height of the vehicle's center of gravity, This refers to the front track width. Rear track width , These are the front axle distribution coefficient and the rear axle distribution coefficient, respectively.

6. The vehicle suspension adaptive compensation control method as described in claim 5, characterized in that, The step of determining the anti-roll compensation amount for suppressing vehicle roll based on the crosswind disturbance estimate also includes model prediction feedback correction of the feedforward axle load transfer amount for each wheel: Using a three-degree-of-freedom vehicle model that includes roll freedom as the prediction model, the steady-state anti-roll moment corresponding to the feedforward axle load transfer of each wheel is added to the prediction model as a known feedforward input term; Based on the prediction model, under the constraints of virtual torque amplitude, virtual torque change rate, tire adhesion limit and suspension travel, the expected anti-roll moment and expected additional yaw moment not covered by the feedforward are solved. The discretized state equation of the prediction model is: Among them, state variables The control quantity is a virtual torque. Disturbance term Provided by the crosswind disturbance estimate, , , , This is a coefficient matrix that is updated online based on the current vehicle speed, tire lateral stiffness, and equivalent suspension roll stiffness. The desired anti-rolling moment, Add a yaw moment to the desired value.

7. The vehicle suspension adaptive compensation control method as described in claim 6, characterized in that, The step of distributing the anti-roll compensation amount to the adjustable suspension actuator to perform adaptive compensation includes: For the desired anti-rolling moment Low-pass filtering is performed to obtain the low-frequency component. and extract high-frequency components. ; The low-frequency component is solved into the feedback axle load adjustment amount for each wheel, and the calculation formula for the feedback axle load adjustment amount for each wheel is as follows: The feedforward axle load transfer amount and the feedback axle load adjustment amount of each wheel are superimposed to obtain the target value of the total axle load for each wheel: The suspension adjustable actuators used to generate continuous vertical force are controlled according to the total axle load target value of each wheel, and the high-frequency components are distributed to the suspension adjustable actuators used to generate transient damping force. In the formula, , This is the torque-axle load conversion factor. , , These are the total axle load target value, feedforward axle load transfer amount, and feedback axle load adjustment amount for the same cycle, respectively.

8. The vehicle suspension adaptive compensation control method as described in claim 6, characterized in that, The desired additional yaw moment Differential braking is applied to the vehicle via the electronic stability control system: When the measured yaw rate is less than the expected yaw rate in the driver's expected response, brake the inner rear wheel; When the measured yaw rate is greater than the expected yaw rate, brake the outer front wheel; The braking pressure amplitude of the differential braking is positively correlated with the amplitude of the desired additional yaw moment.

9. The vehicle suspension adaptive compensation control method as described in claim 6, characterized in that, The method further includes hysteresis-based mode switching between at least four control modes based on crosswind disturbance estimates, yaw rate deviations, and roll angles; the at least four control modes include a normal mode, a pre-compensation mode, an active compensation mode, and a cooperative safety mode. When the crosswind disturbance estimate meets the first entry condition, the pre-compensation mode is switched from the normal mode, and the application of the feedforward axle load transfer amount of each wheel is activated. When at least one of the crosswind disturbance estimate, the yaw rate deviation, or the roll angle meets the second entry condition, the active compensation mode is switched in, and the feedforward axle load transfer of each wheel and the model prediction feedback correction are activated. When the adjustable suspension actuator reaches saturation and the yaw rate deviation meets the third entry condition, the cooperative safety mode is activated, the compensation output of the adjustable suspension actuator is locked, the electronic stability control system takes over the yaw control, and the vehicle height is reduced.

10. A vehicle suspension adaptive compensation control system, characterized in that, include: The sensing module is used to acquire the vehicle's motion state and the driver's steering input. The crosswind disturbance observer module is used to determine the driver's desired response based on the driver's steering input and the motion state quantity, and to estimate the amount of crosswind disturbance experienced by the vehicle online based on the motion state quantity and the driver's desired response, thereby obtaining the crosswind disturbance estimate. The compensation decision module is used to determine the anti-roll compensation amount for suppressing vehicle body roll based on the crosswind disturbance estimate. The actuator allocation module is used to allocate the anti-roll compensation amount to the adjustable suspension actuators to perform adaptive compensation; The adjustable suspension actuator includes at least one of an air spring and a continuously damped control shock absorber.

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