Automobile electronic control suspension control method based on automobile body acceleration

Abstract

The invention discloses an automobile electric control suspension control method based on automobile body acceleration, which is applied to an electric control suspension comprising a controllable actuator and comprises the following steps of: 1, collecting automobile body acceleration and automobile speed information in an automobile running process; 2, determining whether the automobile is in a normal road condition state or a special road condition state according to a result recognized by the working condition double recognizer; and 3, when the automobile is in a normal road condition state, the comfort coefficient is used, when the automobile is in a special input road condition state, the dynamic adjustment coefficient is used, and therefore real-time control over the suspension system is achieved. According to the method, whether the automobile is in the special road surface input state or not can be recognized under the condition that only the sprung mass acceleration of the automobile body is processed, so that the effect of adaptively adjusting the control coefficient of the controllable suspension is achieved, and therefore the controllable suspension is efficiently made to process different road surface characteristics.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of electric control suspension control algorithm, in particular to an automobile electric control suspension control method based on vehicle body acceleration. BACKGROUND

[0002] As a core component of today's intelligent networked vehicles, electric control suspension plays an important role in determining the comfort and stability of the occupants in the background of the increasing vehicle kerb mass. With the continuous reduction of development cycle and research and development cost of electric control suspension, its installed quantity has been breaking records in recent years. Although the number of vehicles equipped with electric control suspension is increasing, due to the complex and variable road conditions, the algorithm of electric control suspension is constantly being updated. Therefore, electric control suspension with adaptive complex road control algorithm gradually enters the market, which aims to solve the contradiction between the comfort and stability of the vehicle in motion, and make the vehicle more safe and reliable.

[0003] In the electric control suspension system, the core control method plays a decisive role, which is the main development core and difficulty. As mentioned earlier, the road conditions of the vehicle are often complex and variable, and the existing control method uses a single traditional classic control theory because of the computing power of the controller hardware. These single classic control theories such as PID control and skyhook control are mostly limited to an ideal state, and use fixed parameters to deal with complex road conditions, which makes the controller show some single control tendency after selection, and cannot exert the optimal performance of the electric control suspension. The existing complex control methods such as MPC and LQR either cannot be deployed on actual production vehicle controllers due to large amount of calculation, or also use a kind of robust control with tendency, which makes the current electric control suspension unable to achieve more comprehensive control effect on the comfort of random road input and the stability of road pulse input.

[0004] The current existing electric control suspension control method cannot adjust itself to the real-time road conditions, and cannot get out of the performance limitation of fixed parameters and tendency, which limits the application effect of electric control suspension on the vehicle chassis, greatly hindering the market application of electric control suspension. SUMMARY

[0005] In order to overcome the shortcomings of the prior art, an automobile electric control suspension control method based on vehicle body acceleration is proposed, which can realize the effect of identifying normal road input and road pulse input state by collecting only the body spring mass acceleration of the existing electric control suspension system, so as to realize real-time adjustment of the dynamic control interval, efficiently make the electric control suspension deal with different road characteristics, and further optimize the performance of the electric control suspension under such conditions.

[0006] To achieve the above object, the application adopts the following technical scheme: The automobile electric control suspension control method based on vehicle body acceleration has the characteristics that it is applied to semi-active or active electric control suspension containing controllable shock absorber and actuator, and is performed according to the following steps: Step 1, when the electric control suspension is working, the spring mass acceleration of the vehicle body in the process of vehicle driving is collected And the vehicle speed at time t ; Step 2, input And into the double-layer working condition identifier for processing to determine the road condition state of the automobile at time t, including: normal road condition state, special road condition state; Step 2.1, the first layer working condition identifier processes to obtain the road condition state of the automobile at time t, and determines the value of the first layer working condition identification identifier at time t; Step 2.2, the second layer working condition identifier processes to obtain the road condition state of the automobile at time t, and determines the value of the second layer working condition identification identifier at time t; Step 2.3, according to And , the final road condition state of the automobile at time t is determined; If =1 and =1, it indicates that the final road condition state of the automobile at time t is the special road condition state, and the final working condition identification identifier at time t is set; Step 3 is executed; Otherwise, it indicates that the final road condition state of the automobile at time t is the normal road condition state, and is set; Step 4 is executed; Step 3, the limited frequency H∞ control rate at time t in the special road condition state is calculated , so that the control force of the electric control suspension at time t is obtained; Step 4, the limited frequency H∞ control rate at time t in the normal road condition state is calculated , so that the control force of the electric control suspension at time t is obtained.

[0007] The automobile electric control suspension control method based on vehicle body acceleration also has the characteristics that the step 2.1 includes: Step 2.1.1, the spring mass acceleration is converted into the acceleration time domain signal at time t; Step 2.1.2, set the length of the sliding window to , in the sliding window Internal pair Perform wavelet processing to obtain the Wavelet detail coefficients at layer scale ; Step 2.1.3, use formula (3) to calculate the Wavelet energy at layer scale : (3) In formula (3), Represents a sliding window in Moment Wavelet detail coefficients at layer scale; Step 2.1.4: Calculate the total wavelet energy at time t using formula (4) : (4) In formula (4), For the The weight at the layer scale, is the total number of scale layers; Step 2.1.5, if In preset time length The energy is continuously greater than the dynamic threshold energy set at time t. , it means that the first-layer working condition identifier recognizes that the road condition of the car at time t is a special road condition, and the first-layer working condition identification identifier at time t is is 1; otherwise, it means that the first-layer working condition identifier recognizes that the road condition of the car at time t is normal, and sets =0.

[0008] Furthermore, the step 2.2 includes: Step 2.2.1. Use formula (5) to obtain the peak acceleration dynamic threshold at time t : (5) In formula (5), is the basic acceleration threshold, is the speed sensitivity coefficient; Step 2.2.2, if ≥ , it means that the second-layer working condition identifier recognizes that the road condition of the car at time t is a special road condition, and sets the second-layer working condition identification identifier at time t is 1; otherwise, it indicates that the second layer road condition recognizer recognizes that the vehicle is in the normal road condition at time t, and = 0.

[0009] Further, in step 2.3, when , if the absolute value of the maximum value of the instantaneous amplitude of the vehicle body sprung mass acceleration signal at the subsequent n continuous time instants is less than the absolute value of the preset acceleration triggering threshold value amplitude , then the final road condition recognition identifier at time t+n is set as , which indicates that the final road condition of the vehicle at time t+n is the normal road condition.

[0010] Further, the step 3 comprises: Step 3.1, performing Hilbert transform on to obtain the Hilbert transform of ; Step 3.2, calculating the Hilbert analytic signal of using formula (7): (7) In formula (7), is the imaginary unit; Step 3.3, calculating the instantaneous amplitude and the phase of ; Step 3.4, based on the phase , calculating the instantaneous frequency of the vehicle body sprung mass acceleration time-domain signal : Step 3.5, calculating the dynamic control interval in the special road condition at time t using formula (10): : (10) In formula (10), and are the left boundary and the right boundary at time t, respectively, is the interval difference of the dynamic control interval ; Step 3.6, the electronic-controlled suspension controller calculates the limited frequency H∞ control rate at time t in the special road condition according to , so that the control force of the electronic-controlled suspension at time t is obtained by multiplying and the state quantity of the electronic-controlled suspension at time t.

[0011] Further, the step 4 comprises: Step 4.1, setting the dynamic control interval of the normal road condition at time t , wherein, and are the upper and lower limits in the normal road condition; Step 4.2, the electrically controlled suspension controller calculates the limited frequency H∞ control rate at time t in the normal road condition according to K 2, so as to multiply and the state quantity of the electrically controlled suspension at time t to obtain the control force of the electrically controlled suspension at time t.

[0012] The electronic device comprises a memory and a processor, and is characterized in that the memory is used to store a program supporting the processor to execute the automobile electrically controlled suspension control method, and the processor is configured to execute the program stored in the memory.

[0013] The computer readable storage medium stores a computer program, and the computer program is executed by the processor to execute the steps of the automobile electrically controlled suspension control method.

[0014] Compared with the prior art, the present application has the following advantages: 1. The present application does not increase other redundant parts on the basis of the existing electrically controlled suspension hardware, but only measures the body spring mass acceleration information through the self-provided acceleration sensor, and combines the speed of the automobile to judge the road condition encountered by the automobile. Compared with the traditional electrically controlled suspension control method, the present application can accurately identify whether the automobile is in random road input or pulse input, and efficiently improves the self-identification ability of the electrically controlled suspension and the pertinence of the subsequent control algorithm.

[0015] 2. The present application uses a set of multi-stage road input identification method to perform real-time wavelet analysis and acceleration threshold judgment on the body spring mass acceleration signal, and excludes the misidentification state in a mutual verification manner, thereby greatly improving the accuracy of the road state recognition of the controller for the road pulse input.

[0016] 3. The present application adjusts different limited H∞ control frequency intervals by analyzing the instantaneous frequency in real time when the road pulse and other special inputs are encountered, so as to achieve a more targeted control effect and automatically optimize the automobile ride comfort in the normal state and the stability in the special input state. BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 is a control principle flowchart of the present application; Figure 2 is a multi-layer identification principle flowchart of the present application;​ Figure 3 is a schematic diagram of a quarter electrically controlled active suspension model. DETAILED DESCRIPTION

[0018] In this embodiment, as shown in Figure 1 , a vehicle electrically controlled suspension control method based on vehicle body acceleration is applied to an electrically controlled suspension containing a controllable actuator. The acceleration sensor of the original vehicle is used to measure the sprung mass acceleration information of the vehicle body. In combination with the speed of the vehicle, the road conditions encountered by the vehicle are determined. Different frequency ranges are controlled according to different road input characteristics. Different dynamic control frequency domain is allocated to calculate different H∞ control matrix to output electrically controlled suspension control force, so as to accurately deploy different control characteristics and achieve good electrically controlled suspension control effect.

[0019] Specifically, the control method includes a working condition double identifier using the vehicle body sprung mass acceleration as the judgment input and a dynamic adjustment algorithm control after identification.

[0020] As shown in Figure 3 , the electrically controlled active suspension dynamic model is constructed by using formula (a) and formula (b): (a) (b) In formula (a) and formula (b), , are the vehicle body sprung mass and the non-sprung mass, respectively; are the vertical displacements of the vehicle body, the wheel and the road surface, respectively; are the suspension stiffness and damping, respectively; is the tire stiffness; is the suspension active control force.

[0021] The input information of the system is the vehicle body sprung mass acceleration and the vehicle speed ; the control method is performed according to the following steps: Step 1, when the electrically controlled suspension is working, the vehicle body sprung mass acceleration and the vehicle speed at time t during the vehicle driving process are collected.

[0022] Step 2, as shown in Figure 2 , input and into the double-layer working condition identifier for processing to determine the road condition state of the vehicle at time t, including: normal road condition state, special road condition state; Step 2.1, the first layer working condition identifier processes The road condition state of the vehicle at time t is obtained and a first layer working condition recognition identifier at time t is determined . Step 2.1.1, the sprung mass acceleration is converted into an acceleration time domain signal at time t according to formula (1) : (1) Step 2.1.2, the length of the sliding window is set as , and wavelet processing is performed on in the sliding window according to formula (2) to obtain a wavelet detail coefficient at a first layer scale at time t . (2) In formula (2), is a wavelet analysis operator using a DB2 wavelet base.

[0023] Step 2.1.3, the wavelet energy at the first layer scale at time t is calculated using formula (3) : (3) In formula (3), denotes the wavelet detail coefficient at the first layer scale at time t in the sliding window . Step 2.1.4, the total wavelet energy at time t is calculated using formula (4) : (4) In formula (4), is a weight at the first layer scale, and is the total number of scales.

[0024] Step 2.1.5, if continues for more than a set dynamic threshold energy at time t for a preset time length , it indicates that the first layer working condition recognition identifier recognizes that the road condition state of the vehicle at time t is a special road condition state, and the first layer working condition recognition identifier at time t is set as 1; otherwise, it indicates that the first layer working condition recognition identifier recognizes that the road condition state of the vehicle at time t is a normal road condition state, and = 0.

[0025] Step 2.2, a second layer working condition recognition identifier is determined​​​​​​ Processing is performed to obtain the road condition of the car at time t, and determine the second-level working condition identification identifier at time t The value of Step 2.2.1. Use formula (5) to obtain the peak acceleration dynamic threshold at time t : (5) In formula (5), is the basic acceleration threshold, is the speed sensitivity coefficient.

[0026] Step 2.2.2, if ≥ , it means that the second-layer working condition identifier recognizes that the road condition of the car at time t is a special road condition, and sets the second-layer working condition identification identifier at time t is 1; otherwise, it means that the second-layer working condition identifier recognizes that the road condition of the car at time t is normal, and sets =0.

[0027] Step 2.3, according to and , determine the final road condition of the car at time t; like =1 and =1, it means that the final road condition of the car at time t is a special road condition, and the final working condition identification identifier at time t is ; Execute step 3; Otherwise, if =1 and =0, =0 and =1, =0 and =0 means that the final road condition of the car at time t is normal, and let ; Go to step 4.

[0028] Step 3: Calculate the finite frequency H∞ control rate at time t under special road conditions , thus obtaining the control force of the electronically controlled suspension at time t; Step 3.1: According to formula (6), Perform Hilbert transform and get Hilbert transform ; (6) In formula (6), is the Cauchy principal value.

[0029] Step 3.2, calculating the Hilbert analytic signal of the body sprung mass acceleration time domain signal : (7) In formula (7), is the imaginary unit.

[0030] Step 3.3, calculating the instantaneous amplitude and phase of the Hilbert analytic signal ; (8) Step 3.4, calculating the instantaneous frequency of the body sprung mass acceleration time domain signal based on the phase , using formula (9); (9) Step 3.5, calculating the dynamic control interval in the special road condition at time t using formula (10): (10) In formula (10), and are the left limit and right limit at time t respectively, is the interval difference of the dynamic control interval .

[0031] Step 3.6, the electronic-controlled suspension controller calculates the finite frequency H∞ control rate at time t in the special road condition, so as to multiply by the state quantity of the electronic-controlled suspension at time t, and obtain the control force of the electronic-controlled suspension at time t. Step 4, calculating the finite frequency H∞ control rate

[0032] at time t in the normal road condition, so as to obtain the control force of the electronic-controlled suspension at time t; Step 4.1, setting the dynamic control interval in the normal road condition at time t, wherein, and are the upper and lower limits in the normal road condition; Step 4.2, the electronic-controlled suspension controller calculates the finite frequency H∞ control rate K2 at time t in the normal road condition according to , so as to multiply by the state quantity of the electronic-controlled suspension at time t, and obtain the control force of the electronic-controlled suspension at time t. ​​​

[0033] When entering step 2.3, that is, when If The absolute value of the maximum value of the instantaneous amplitude of the subsequent n consecutive time points is less than the preset acceleration trigger threshold amplitude The final working condition recognition identifier at the t+n time point Indicates that the final road condition state of the automobile at the t+n time point is a normal road condition state.

[0034] In this embodiment, the classification of the above-mentioned special input road condition control interval And the normal road condition dynamic control interval It is not limited to a fixed combination in a certain case, and the dynamic control interval can be further subdivided according to specific conditions and requirements, so as to achieve more detailed targeted control and achieve the effect of multiple intervals.

[0035] In this embodiment, an electronic device includes a memory for storing a program supporting a processor to execute the above method, and a processor configured to execute the program stored in the memory.

[0036] In this embodiment, a computer readable storage medium has a computer program stored thereon, and the computer program is executed by a processor to perform the steps of the above method.

[0037] To sum up, the method of the present application mainly uses the body spring mass acceleration and the vehicle speed in the driving process of the automobile as the input information, analyzes and classifies the body spring mass acceleration caused by different road conditions, accurately judges the different states, and adjusts different frequency control intervals to match the control requirements of the corresponding stage, so that the electric control suspension has multiple control characteristics and tendencies. Under the background of not significantly increasing the burden of the controller, better control effect is obtained, compared with the existing single and fixed parameter control method, the electric control suspension can meet the dual demands of comfort and handling stability on the actual road. While providing an automobile electric control suspension control method based on body acceleration, the application range of the frequency domain control method is also expanded.

Claims

1. A method of controlling an electronically controlled suspension of an automobile based on acceleration of a vehicle body, characterized by, is applied to a semi-active or active electronically controlled suspension comprising controllable shock absorbers and actuators and is performed in the following steps: Step 1, Collecting the sprung mass acceleration of the vehicle body during the driving process of the vehicle when the electric control suspension is working and the vehicle speed at time t ; Step 2, the input double-layer working condition recognizer is processed to determine the road condition state of the automobile at time t, including: normal road condition state, special road condition state and input double-layer working condition recognizer is processed to determine the road condition state of the automobile at time t, including: normal road condition state, special road condition state Step 2.1, the first layer road condition identifier processes the data to obtain the road condition state of the vehicle at time t and determine the value of the first layer road condition identifier at time t Step 2.2, the second layer road condition identifier processes the data to obtain the road condition state of the vehicle at time t and determine the value of the second layer road condition identifier at time t Step 2.3, the third layer road condition identifier processes the data to obtain the road condition state of the vehicle at time t and Step 2.2, the second layer working condition identifier pair processes the data to obtain the road condition state of the vehicle at time t and determine the value of the second layer working condition identification identifier at time t . Step 2.3, determining the final road condition state of the car at time t according to and ; If = 1 and = 1, it indicates that the final road condition state of the automobile at time t is a special road condition state, and the final road condition identification identifier at time t is set as ; step 3 is executed. Otherwise, it indicates that the final road condition state of the car at time t is normal road condition state, and let Step 4 is executed. Step 3, calculate the limited frequency H∞ control rate at t moment under special road condition Thus, the control force of the electronically controlled suspension at t moment is obtained. Step 4, calculate the limited frequency H∞ control rate at t time under normal road condition Thus, the control force of the electronically controlled suspension at t time is obtained.

2. The vehicle electronic suspension control method based on vehicle body acceleration according to claim 1, characterized in that: said step 2.1 comprises: Step 2.1.1, adding the sprung mass acceleration converted to the acceleration time domain signal at time t ; Step 2.1.2, set the length of the sliding window to , in the sliding window Internal pair Perform wavelet processing to obtain the Wavelet detail coefficients at layer scale ; Step 2.1.3, calculating t for the i-th layer at time t using formula (3) Wavelet energy at layer scale : (3) In formula (3), representing a sliding window in the moment wavelet detail coefficients at the layer scale; Step 2.1.

4. Calculating the total wavelet energy at time t using formula (4) : (4) In formula (4), is the first weight at the layer scale, is the total number of scales; Step 2.1.5, if In preset time length The energy is continuously greater than the dynamic threshold energy set at time t. , it means that the first-layer working condition identifier recognizes that the road condition of the car at time t is a special road condition, and the first-layer working condition identification identifier at time t is is 1; otherwise, it means that the first-layer working condition identifier recognizes that the road condition of the car at time t is normal, and sets =0.

3. The vehicle electronic suspension control method based on vehicle body acceleration according to claim 2, wherein: said step 2.2 comprises: Step 2.2.1, obtaining the peak acceleration dynamic threshold at time t using formula (5) : (5) In formula (5), is a base acceleration threshold, is a velocity sensitivity coefficient; Step 2.2.2, if ≥ , it means that the second-layer working condition identifier recognizes that the road condition of the car at time t is a special road condition, and sets the second-layer working condition identification identifier at time t is 1; otherwise, it means that the second-layer working condition identifier recognizes that the road condition of the car at time t is normal, and sets =0.

4. The method according to claim 1, wherein the method is characterized by, When If the absolute value of the maximum value of the instantaneous amplitudes of the subsequent consecutive n time instants is less than the preset acceleration trigger threshold amplitude , the final working condition recognition identifier at the time instant t+n is set to indicate that the final road condition state of the automobile at the time instant t+n is the normal road condition state.

5. The method according to claim 2, wherein the acceleration of the vehicle body is detected by a sensor provided in the vehicle body. said step 3 comprises: Step 3.1, the Hilbert transform is performed on to obtain the Hilbert transform of ;​ Step 3.2, calculating with formula (7) the Hilbert analytic signal : (7) In formula (7), is the imaginary unit; Step 3.3, calculating the instantaneous amplitude of and the phase of ; Step 3.4: Phase-based , calculate the time domain signal of the vehicle body sprung mass acceleration The instantaneous frequency : Step 3.5, calculating the dynamic control interval at time t for the special road condition using formula (10) : (10) In formula (10), and are left and right limits at time t, respectively, is the interval difference of the dynamic control interval . Step 3.6, the electronic suspension controller is based on , calculate the finite frequency H∞ control rate at time t under special road conditions , thus After multiplying it by the state quantity of the electronically controlled suspension at time t, the control force of the electronically controlled suspension at time t is obtained.

6. The method of claim 1, wherein the method further comprises: said step 4 comprises: Step 4.1, setting a dynamic control interval for normal road conditions at time t wherein, and are upper and lower limits for normal road conditions. Step 4.2, the electronic-controlled suspension controller calculates the limited frequency H∞ control rate at time t under normal road conditions , and the control force of the electronic-controlled suspension at time t is obtained after multiplying the state quantity of the electronic-controlled suspension at time t by the limited frequency H∞ control rate. K 2, thereby ​ 7. An electronic device comprising a memory and a processor, characterized in that said memory is configured to store a program supporting the processor to perform the method of controlling an automotive electronically controlled suspension according to any one of claims 1-6, and the processor is configured to execute the program stored in the memory.

8. A computer-readable storage medium having stored thereon a computer program, characterized in that said computer program, when executed by a processor, performs the steps of the method of controlling an automotive electronically controlled suspension according to any one of claims 1-6.

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