Road interference detection and compensation control method for steering system

Abstract

The invention discloses a road interference detection and compensation control method for a steering system, and belongs to the technical field of vehicle steering systems. The method specifically comprises the steps of road bumping detection and steering system road interference compensation control, the road bumping detection is that a detection signal is obtained through a time window integration method by utilizing the amplitude difference of the high-frequency interference torque of the steering system, and the road bumping is detected by adopting a dynamic threshold value in combination with various signals such as the steering torque and the vehicle speed; the method can adapt to different vehicle speed scenes and realize accurate identification. According to the road surface interference compensation control method, a steering system kinetic model containing interference torque is established, an expansion state observer is innovatively designed, the system state and the total disturbance quantity are actively estimated, state information which cannot be obtained by a traditional sensor is obtained, and the steering system dynamic model is obtained through a feed-forward control and compensation control method. Effective disturbance torque compensation control is achieved, and the robustness of a steering control system under the working condition of a bumpy road surface is enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle steering systems, and more specifically to a method for detecting and compensating for road disturbance in a steering system. Background Art

[0002] During the driving process, road bumps are an important factor affecting vehicle comfort and safety. Bumpy roads usually interfere with the vehicle's suspension system and steering system. Especially under complex road conditions, the vehicle's steering system is more susceptible to road bumps, causing the driver to make steering errors or increase driving difficulty. This interference not only affects the driver's control experience, but may also bring safety hazards.

[0003] The steering system of existing vehicles generally enhances the vehicle's handling and steering ease by combining mechanical components and electronic control. However, when the vehicle is driving on a bumpy road, the interference torque of the steering system is often not effectively suppressed. In particular, when the road impact is large, the feedback torque on the steering wheel will fluctuate significantly, making it difficult for the driver to maintain precise steering control. In order to improve the steering stability of the vehicle under complex road conditions and reduce the interference of bumpy roads on the steering system, it is urgent to develop a control method that can effectively detect road bumps and suppress steering interference torque. Therefore, how to accurately detect road bumps and adjust the torque output in the steering system in real time through control algorithms has become an important technical means to improve vehicle driving comfort and safety. Summary of the invention

[0004] The present invention provides a method for detecting and compensating for road disturbance in a steering system, so as to solve the shortcomings of the existing vehicle steering system, such as the inability to effectively suppress the disturbance torque, which makes it difficult for the driver to maintain precise steering control.

[0005] The present invention adopts the following technical solution:

[0006] A method for detecting and compensating for road disturbances in a steering system, including road bump detection and steering system road disturbance compensation control;

[0007] The method for detecting road bumps includes: 1.1 using a high-pass filter to extract the high frequencies that clearly distinguish between smooth road and bumpy road signals, and taking the absolute value to obtain the amplitude of the high-frequency interference torque; 1.2 using a sliding time window integral to integrate the amplitude of the high-frequency torque to obtain a data area with high high-frequency energy, i.e., a road interference area; 1.3 using a dynamic threshold method to determine whether a bumpy road has been entered;

[0008] The method for road disturbance compensation control of the steering system includes: 2.1 establishing a steering system dynamics model including disturbance torque; 2.2 designing an extended state observer to estimate the total disturbance; 2.3 configuring the observer gain to configure the poles to ensure the stability of the observer system; 2.4 using feedforward control calculation to obtain a virtual control signal, and performing compensation control on the feedforward control to eliminate the influence of the total disturbance f on the control quantity.

[0009] Preferably, the frequency threshold of the high-pass filter is obtained by calibration, and the calibration principle is that the maximum integral of the torque signal amplitude passing through the high-pass filter on a smooth road is 5% of the original torque signal amplitude integral, ensuring that the torque signal applied by the driver is effectively filtered out.

[0010] The mathematical form of the above step 1.2 is as follows:

[0011]

[0012] Where, T d Represents the torque detected by the steering system torque angle sensor, H(T d ) is the high-frequency disturbance torque obtained by high-pass filter, and E is the result of integrating the high-frequency disturbance torque amplitude by sliding time window integration.

[0013] The dynamic threshold method used in the above step 1.3 specifically includes: first, the vehicle passes through the same bumpy road surface at different speeds to obtain the time window integral of the high-frequency interference torque amplitude at different speeds; second, a time window integral interpolation table of vehicle speed and high-frequency interference torque amplitude is established to obtain the dynamic threshold for bump judgment at different speeds; finally, the data obtained by the window amplitude integral is judged, and the bump / smooth state flag is output to provide a state basis for subsequent road disturbance control.

[0014] The dynamic equation of the steering system dynamics model in step 2.1 is as follows:

[0015]

[0016] In the formula, J s is the system moment of inertia, B u is the system damping coefficient, K s is the system stiffness coefficient, δ d is the steering wheel angle of the steering system, T e is the output torque of the motor after torque increase; f is the total disturbance, including the violent fluctuation of steering torque caused by road bumps, the torque applied by the driver and other unmodeled interference items; Formula (2) is rewritten as a state equation:

[0017]

[0018] y is the output of the steering system; f is also used as a state quantity for the observer to estimate, and the steering system model is transformed into formula (4):

[0019]

[0020] The extended state observer adopts the Romberg observer, and constructs the state space equation by adding a correction term based on the output error to the original system, as shown in the following equation (5):

[0021]

[0022] In the formula, is the state quantity The observed value of Output y = δ d The observed value of is the observed value output by the extended state observer; A is the state matrix, B is the input matrix, and the values ​​of A and B are the same as the steering system modeling equation, that is, C is the output matrix, which is set according to the needs of the controller; L is the observer gain matrix, that is, the weighting of the deviation, the observer gain L = [l1 l2 l3)] T ; The observer equation is expanded into the following formula (6):

[0023]

[0024] The step 2.3 specifically includes the following process:

[0025] First solve the characteristic root λ equation (7) of the system:

[0026]

[0027] By configuring the observer pole on the negative real axis to ensure that the state estimate converges to the actual value quickly and without oscillation, assuming the pole is -ω, we have:

[0028]

[0029] The gain coefficient can be obtained: After determining the value of ω, the observer gain L is obtained.

[0030] The above compensation control method is to set T e In is the compensation term for the total disturbance, u o is the virtual control quantity calculated by the feedforward control. After the compensation control, the steering system expression becomes: The feedforward control algorithm can be used to design the steering wheel angle δ according to the control method of the disturbance-free system.d With virtual input u o The control law between them.

[0031] It can be seen from the above description of the present invention that, compared with the prior art, the present invention has the following advantages:

[0032] 1. The present invention utilizes the amplitude difference of the high-frequency interference torque of the steering system, obtains the detection signal through the time window integration method, combines multiple signals such as steering torque and vehicle speed, and adopts a dynamic threshold to detect road bumps. It can adapt to different vehicle speed scenes and realize accurate identification.

[0033] 2. The present invention establishes a steering system dynamics model including interference torque, and innovatively designs an extended state observer to actively estimate the system state and the total disturbance, obtain state information that traditional sensors cannot obtain, and realize effective interference torque compensation control through the method of feedforward control plus compensation control, thereby enhancing the robustness of the steering control system under bumpy road conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a schematic diagram of the steering control system framework of the present invention. DETAILED DESCRIPTION

[0035] The specific implementation of the present invention is described below with reference to the accompanying drawings. In order to fully understand the present invention, many details are described below, but for those skilled in the art, the present invention can be implemented without these details. For well-known components, methods and processes, they are not described in detail below.

[0036] This embodiment provides a method for detecting and compensating for road disturbance in a steering system, based on a steering control system framework, referring to Figure 1 The steering control system framework includes a steering system model, an extended state observer (ESO) for real-time estimation of the internal state and external disturbance of the system, a compensation control module and a feedforward controller module. The steering system road disturbance detection and compensation control method specifically includes the following steps:

[0037] 1. Road Bump Detection

[0038] By collecting the amplitude of the interference torque caused by the road surface to the steering system, it is possible to determine whether the vehicle is on a bumpy road. Since the torque detected by the steering system torque angle sensor includes the torque applied by the driver, and the frequency of this part of the torque is relatively low, a suitable high-pass filter is used to filter the torque applied by the driver, and the high-frequency torque signal passing through the high-pass filter can be used to judge the degree of road bumps. The frequency threshold of the high-pass filter can be obtained by calibration, and the calibration principle is: the maximum integral of the torque signal amplitude passing through the high-pass filter on a smooth road is 5% of the integral of the original torque signal amplitude, that is, to ensure that the torque signal applied by the driver is effectively filtered out.

[0039] After using high-pass filtering to extract the high frequencies that clearly distinguish between smooth and bumpy road signals, the absolute value is taken to obtain the amplitude of the high-frequency interference torque. Then, the high-frequency data amplitude is integrated using a sliding time window integral to obtain the data area with higher high-frequency energy, that is, the road interference area. The mathematical form of the process is as follows (1):

[0040]

[0041] Where, T d Represents the torque detected by the steering system torque angle sensor, H(T d ) is the high-frequency disturbance torque obtained by high-pass filter, and E is the result of integrating the high-frequency disturbance torque amplitude by sliding time window integration.

[0042] Since the amplitude of the disturbance torque generated by passing through a bumpy road will generally increase with the increase of vehicle speed, it is not possible to use a fixed threshold to determine whether the vehicle has entered a bumpy road. Therefore, the present invention adopts a dynamic threshold method, which is as follows: first, the vehicle passes through the same bumpy road at different speeds to obtain the time window integral of the high-frequency disturbance torque amplitude at different speeds; second, establish a time window integral interpolation table of vehicle speed and high-frequency disturbance torque amplitude, and obtain the dynamic threshold for bump judgment at different speeds; finally, judge the data obtained by the window amplitude integral, output the bump / stable state flag, and provide a state basis for subsequent road disturbance control.

[0043] 2. Steering System Road Disturbance Compensation Control Method

[0044] The main control goal of the present invention is to suppress the violent fluctuation of steering torque caused by road bumps, which requires compensatory control of the steering motor torque. Therefore, an extended state observer (ESO) is used to estimate the interference in real time and suppress road interference through feedforward compensation.

[0045] The main function of the extended state observer (ESO) is to estimate the internal state and external disturbance of the system in real time so as to effectively offset these uncertainties in the controller design and thus achieve accurate compensation control of the system output.

[0046] The basic idea of ​​ESO is to regard the uncertain dynamics and disturbances in the system as an additional "extended state" and incorporate it into the design of the observer. This means that in addition to the conventional system state, the extended state observer also estimates an additional state vector, which contains all internal dynamics and external disturbances that may affect the behavior of the system but cannot be directly measured. In this way, ESO can estimate and compensate for these uncertain factors in real time, so that the control system can still achieve accurate output tracking or control in the presence of disturbances. Therefore, the specific method of road disturbance supplementary control of the steering system is as follows:

[0047] 2.1 Establishing the steering system dynamics model

[0048] First, the dynamic modeling of the steering system is carried out. The general expression of the dynamic equation of the steering system can be written as formula (2):

[0049]

[0050] In the formula, J s is the system moment of inertia, B u is the system damping coefficient, K s is the system stiffness coefficient, δ d is the steering wheel angle of the steering system, T e is the output torque of the motor after torque increase. The total internal and external disturbance is set to f, which includes the drastic fluctuation of the steering torque caused by road bumps, the torque applied by the driver, and other unmodeled disturbances.

[0051] Rewriting equation (2) into the form of state equation is:

[0052]

[0053] y is the output of the steering system.

[0054] Taking f as a state variable for the observer to estimate, the steering system model can be transformed into equation (4):

[0055]

[0056] 2.2 Establishing the Extended State Observer

[0057] Since the torque angle sensor can only measure δ d , the total disturbance f cannot be measured, so it is necessary to construct an extended state observer to estimate f. Here, the commonly used Romberg observer is used to construct the state space equation by adding a correction term based on the output error to the original system. Its general form is as follows:

[0058]

[0059] In the formula, is the state quantity The observed value of Output y = δ d The observed value of is the observed value output by the extended state observer. A is the state matrix, B is the input matrix, and the values ​​of A and B are the same as the steering system modeling equation, that is, C is the output matrix, which can be set according to the needs of the controller. This solution outputs all three state variables, C = I (I is the unit matrix). L is the observer gain matrix, that is, the weighting of the deviation, the observer gain L = [l1 l2 l3)] T .

[0060] Then the above observer equation is expanded into equation (6):

[0061]

[0062] 2.3 Selecting observer gain

[0063] If the value estimated by the observer is to converge to the actual value, the stability of the observer system needs to be satisfied. The present invention configures the poles by configuring the observer gain to ensure the stability of the observer system.

[0064] First solve the characteristic root λ equation (7) of the system:

[0065]

[0066] By configuring the observer pole on the negative real axis, the state estimate is ensured to converge to the actual value quickly and without oscillation. Assuming the pole is -ω, we have:

[0067]

[0068] The gain coefficient can be obtained:

[0069] The larger the ω in the observer, the faster the estimated value converges to the actual value, but at this time the observer gain L is also larger, and the influence of sensor noise becomes greater, so a more reasonable approach is to make the observer bandwidth ω slightly higher than the frequency of the state variable and much lower than the frequency of the noise. The high-pass filter frequency threshold calibrated in step 1 not only filters most of the state signal, but also passes high-frequency sensor noise. This threshold can meet the requirements of the observer ω. After determining the value of ω, the observer gain L is obtained.

[0070] 2.4 Compensation control strategy

[0071] The overall framework of the steering control system is shown in the attached Figure 1 As shown, is the target steering wheel angle required for vehicle control. The overall control is divided into two parts. The first part is feedforward control, which outputs a virtual control signal u according to the error between the steering wheel target angle information and the current angle information observed by the extended state observer. o The other part is compensation control, which aims to eliminate the influence of the total disturbance f on the control quantity and turn the control object of feedback control (the sum of compensation control and steering system) into an interference-free control object.

[0072] Compensation control method: T e In is the compensation term for the total disturbance, u o is the virtual control quantity calculated by the feedforward control. After the compensation control, the steering system expression becomes:

[0073]

[0074] The feedforward control algorithm can be used to design the steering wheel angle δ according to the control method of the disturbance-free system. d With virtual input u o The present invention takes PD control as an example to illustrate the control law between Figure 1 It can be seen that the controller input is the angle error value and the derivative of the error value but K p , K d They are proportional coefficient and differential coefficient respectively. Appropriate coefficients can be obtained through experience debugging to obtain better control effect.

[0075] The road bump detection and interference compensation control method of the present invention is not limited to the steering system used above, but can be applied to any system using motor steering assistance, including electric power steering system and electro-hydraulic coupling power steering system. In addition, the application object can be passenger cars or commercial vehicles.

[0076] The above is only a specific implementation of the present invention, but the design concept of the present invention is not limited thereto. Any non-substantial changes to the present invention using this concept shall be deemed as an infringement of the protection scope of the present invention.

Claims

1. A method for detecting and compensating for road disturbance in a steering system, characterized in that: Including road bump detection and steering system road disturbance compensation control; The method for detecting road bumps includes: 1.1 using a high-pass filter to extract the high frequencies that clearly distinguish between smooth road and bumpy road signals, and taking the absolute value to obtain the amplitude of the high-frequency interference torque; 1.2 using a sliding time window integral to integrate the amplitude of the high-frequency torque to obtain a data area with high high-frequency energy, i.e., a road interference area; 1.3 using a dynamic threshold method to determine whether a bumpy road has been entered; The method for road disturbance compensation control of the steering system includes: 2.1 establishing a steering system dynamics model including disturbance torque; 2.2 designing an extended state observer to estimate the total disturbance; 2.3 configuring the observer gain to configure the poles to ensure the stability of the observer system; 2.4 using feedforward control calculation to obtain a virtual control signal, and performing compensation control on the feedforward control to eliminate the influence of the total disturbance f on the control quantity.

2. A method for detecting and compensating for road disturbance in a steering system according to claim 1, characterized in that: The frequency threshold of the high-pass filter is obtained by calibration. The calibration principle is that the maximum integral of the torque signal amplitude passing through the high-pass filter on a smooth road is 5% of the integral of the original torque signal amplitude, ensuring that the torque signal applied by the driver is effectively filtered out.

3. A method for detecting and compensating for road disturbance in a steering system according to claim 1, characterized in that: The mathematical form of step 1.2 is as follows: Where, T d Represents the torque detected by the steering system torque angle sensor, H(T d ) is the high-frequency disturbance torque obtained by high-pass filter, and E is the result of integrating the high-frequency disturbance torque amplitude by sliding time window integration.

4. A method for detecting and compensating for road disturbance in a steering system as claimed in claim 1, characterized in that: The dynamic threshold method used in step 1.3 specifically includes: first, the vehicle passes through the same bumpy road surface at different speeds to obtain the time window integral of the high-frequency interference torque amplitude at different speeds; second, a time window integral interpolation table of vehicle speed and high-frequency interference torque amplitude is established to obtain the dynamic threshold for bump judgment at different speeds; finally, the data obtained from the window amplitude integral is judged, and the bump / smooth state flag is output to provide a state basis for subsequent road disturbance control.

5. A method for detecting and compensating for a steering system road disturbance as claimed in claim 1, characterized in that: The dynamic equation of the steering system dynamics model in step 2.1 is as follows: In the formula, J s is the system moment of inertia, B u is the system damping coefficient, K s is the system stiffness coefficient, δ d is the steering wheel angle of the steering system, T e The output torque of the motor after torque increase; f is the total disturbance, including the violent fluctuation of steering torque caused by road bumps, the torque applied by the driver and other unmodeled disturbances; Equation (2) is rewritten as the state equation: y is the output of the steering system; f is also used as a state quantity for the observer to estimate, and the steering system model is transformed into formula (4):

6. A method for detecting and compensating for road disturbance in a steering system as claimed in claim 5, characterized in that: The extended state observer adopts the Romberg observer, and constructs the state space equation by adding a correction term based on the output error to the original system, as shown in the following equation (5): In the formula, is the state quantity The observed value of Output y = δ d The observed value of is the observation output of the extended state observer; A is the state matrix, B is the input matrix, and the values ​​of A and B are the same as the steering system modeling equation, that is, C is the output matrix, which is set according to the needs of the controller; L is the observer gain matrix, that is, the weighting of the deviation, the observer gain L = [l1 l2 l3)] T ; The observer equation is expanded into the following formula (6):

7. A method for detecting and compensating for road disturbance in a steering system as claimed in claim 1, characterized in that: The step 2.3 specifically includes the following process: First solve the characteristic root λ equation (7) of the system: By configuring the observer pole on the negative real axis to ensure that the state estimate converges to the actual value quickly and without oscillation, assuming the pole is -ω, we have: The gain coefficient can be obtained: After determining the value of ω, the observer gain L is obtained.

8. A method for detecting and compensating for road disturbance in a steering system as claimed in claim 1, characterized in that: The compensation control method is to set T e In is the compensation term for the total disturbance, u o is the virtual control quantity calculated by the feedforward control. After the compensation control, the steering system expression becomes: The feedforward control algorithm can be used to design the steering wheel angle δ according to the control method of the disturbance-free system. d With virtual input u o The control law between them.

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