A method for predicting chatter of electric vehicle disc brakes

Abstract

The present invention discloses a method for predicting vibration of a disc brake of an electric vehicle, comprising the following steps: collecting acceleration, vehicle speed and brake pressure signals of the disc brake of the electric vehicle, and obtaining a reconstructed phase diagram by using a phase space reconstruction technique; establishing a drive-brake coupling model, and using the collected vehicle speed and brake pressure as input, simulating and obtaining a phase diagram and time history corresponding to the drive-brake coupling model; comparing the phase diagram obtained by using the phase space reconstruction technique with the phase diagram obtained by simulating the drive-brake coupling model, and judging whether the two are the same type of vibration; if they are the same type of vibration, further analyzing the time history; if they are different types of vibration, modifying the friction type parameter in the drive-brake coupling model; predicting vibration based on stored brake pressure data and vehicle speed data; if there is no corresponding brake pressure and vehicle speed in the stored data, using the drive-brake coupling model to predict vibration and saving the result to a storage device; the present invention can predict vibration based on the collected data.

Description

Technical Field

[0001] The invention relates to the technical field of automobile control, in particular to a method for predicting vibration of a disc brake of an electric vehicle. Background Art

[0002] Brake system judder refers to the vibration behavior of the brake system at low vehicle speeds and low brake pressures, often accompanied by harsh noises and other factors, which seriously impacts the vehicle's ride comfort. Previous studies have shown that brake pressure and vehicle speed have a significant impact on judder, and most previous studies have achieved this through passive control methods such as changing the brake's structural dimensions and selecting different materials. The rise of distributed drive electric vehicles has made active control methods using drive motors as actuators possible. One of the key steps in active control is the observation or prediction of judder. Existing technologies cannot predict judder based on real-time data. Summary of the Invention

[0003] The purpose of this section is to summarize some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the abstract and title of this application to avoid obscuring the purpose of this section, the abstract and the title of the invention, and such simplifications or omissions should not be used to limit the scope of the present invention.

[0004] In view of the above and / or existing problems in the existing chatter prediction, the present invention is proposed.

[0005] Therefore, the purpose of the present invention is to provide a method for predicting electric vehicle disc brake vibration, which can predict vibration based on collected data and provide basic support for electric vehicle disc brake vibration active control technology.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: a method for predicting vibration of electric vehicle disc brakes, comprising:

[0007] Acceleration sensor, vehicle speed sensor and brake pressure sensor are used to collect the acceleration, vehicle speed and brake pressure signals of the electric vehicle disc brake respectively, and the phase space reconstruction technology is used to obtain the reconstructed phase diagram;

[0008] A drive-brake coupling model for electric vehicle disc brakes is established, and the collected vehicle speed and brake pressure are used as input to simulate the phase diagram and time history corresponding to the drive-brake coupling model.

[0009] Compare the phase diagram obtained using phase space reconstruction technology with the phase diagram obtained by the drive-brake coupling model simulation to determine whether the two are the same type of vibration. If they are the same type of vibration, further analyze the time history. If they are different types of vibration, modify the friction type parameters in the drive-brake coupling model.

[0010] Judder is predicted based on the stored brake pressure data and vehicle speed data. If the stored data does not contain the corresponding brake pressure and vehicle speed, the drive-brake coupling model is used to predict judder and the results are saved in a storage device.

[0011] As a preferred solution of the electric vehicle disc brake vibration prediction method of the present invention, the specific steps of analyzing the time history are:

[0012] If the vibration is the same type, the time history obtained by phase space reconstruction technology is compared with the time history obtained by simulation, and the error between the two is calculated. If the error is not zero, the error result is fed back to the drive-brake coupling model to correct the model parameters. If the error is zero, the surface model parameters are correct and can be used for flutter prediction.

[0013] As a preferred solution of the electric vehicle disc brake vibration prediction method of the present invention, the specific steps of simulating and obtaining the phase diagram and time history corresponding to the drive-brake coupling model are as follows:

[0014] The equation of the drive-brake coupling model of the electric vehicle disc brake is:

[0015]

[0016]

[0017]

[0018] The collected brake pressure and vehicle speed values ​​are brought into the drive-brake coupling model to simulate and obtain the phase diagram and time history corresponding to the drive-brake coupling model;

[0019] Among them, x1 is the torsion angle of the transmission system, x2 is the torsion angular velocity of the transmission system, x3 is the displacement of the brake pad, x4 is the speed of the brake pad, x5 is the average disturbance of the friction model, m is the mass of the brake pad, k x is the stiffness of the brake pad, d x is the damping of the brake pad, I is the moment of inertia of the brake disc, T m is the driving motor torque, k θ is the stiffness of the transmission system, d θ is the damping of the transmission system, σ0 is the contact stiffness coefficient, σ1 is the contact damping coefficient, r is the radius of the brake disc, v s is the Stribeck speed, N is the brake pressure, μ s and μ d denote the static and dynamic friction coefficients, respectively, φ(x2, x4, x5) is the average deflection derivative of the bristles, g0 is the Stribeck scaling factor, and Ω0 is the wheel speed.

[0020] As a preferred embodiment of the electric vehicle disc brake vibration prediction method of the present invention, the method for determining whether the two vibrations are of the same type comprises the following steps:

[0021] If the vibration behaviors corresponding to the simulation model and the phase space reconstruction model are both stable equilibrium points or limit cycle oscillations, then the two are the same type of vibrations;

[0022] Otherwise it is not the same kind of vibration.

[0023] As a preferred solution of the electric vehicle disc brake vibration prediction method of the present invention, the method of modifying the friction type parameter in the drive-brake coupling model is specifically as follows:

[0024] If the actual measurement shows a limit cycle oscillation, and the simulation result of the drive-brake coupling model shows a stable equilibrium point, then change the relevant parameters of the variable x5 until a limit cycle oscillation appears;

[0025] If the actual measurement is a stable equilibrium point, but the simulation result of the drive-brake coupling model is a limit cycle oscillation, then change the relevant parameters of the variable x5 until a stable equilibrium point appears.

[0026] As a preferred solution of the electric vehicle disc brake vibration prediction method of the present invention, the specific steps of correcting the model parameters according to the obtained error are as follows:

[0027] By solving the mean value of the vibration signal within 2 seconds, the difference between the mean value of the measured signal and the mean value of the simulated signal is used as the error;

[0028] If the error shows that the measured signal is larger than the simulated signal, reduce the stiffness and damping parameters in the drive-brake coupling model to increase the mean value of the simulated signal until it is equal to the mean value of the measured signal;

[0029] If the error shows that the measured signal is smaller than the simulated signal, increase the stiffness and damping parameter values ​​in the drive-brake coupling model to reduce the mean value of the simulated signal until it is equal to the mean value of the measured signal.

[0030] As a preferred embodiment of the electric vehicle disc brake vibration prediction method of the present invention, the specific steps of predicting vibration are:

[0031] According to whether tremor occurs, the stored brake pressure value, vehicle speed value and whether tremor occurs are stored as a three-dimensional table

[0032] Calculate the maximum Lyapunov exponent of the measured vibration signal. If the maximum Lyapunov exponent is less than zero, no chatter occurs; otherwise, chatter occurs.

[0033] The stored brake pressure values, vehicle speed values, and whether judder occurs are stored in a three-dimensional table, and the measured brake pressure and vehicle speed signals are compared with the data in the three-dimensional table. If there is a corresponding data group in the three-dimensional table, the occurrence of judder can be determined through the array;

[0034] If there is no corresponding brake pressure and vehicle speed in the stored data, the brake pressure and vehicle speed values ​​are imported into the modified drive-brake coupling model as boundary conditions, and the corresponding Lyapunov exponent is calculated to determine whether tremor occurs.

[0035] The beneficial effects of the present invention are as follows: the present invention can predict whether electric vehicle brake judder occurs based on the collected data, and can also be used for the specific characteristics of electric vehicle brake judder, such as phase-frequency characteristics, amplitude-frequency characteristics and parameter conditions for judder occurrence, etc., providing basic support for the active control technology of electric vehicle disc brake judder. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort. Among them:

[0037] Figure 1 This is the phase diagram obtained by simulation.

[0038] Figure 2 This is the simulation time history diagram. DETAILED DESCRIPTION

[0039] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0040] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0041] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0042] Example 1

[0043] The first embodiment of the present invention provides a method for predicting vibration of a disc brake of an electric vehicle.

[0044] S1: Acceleration sensors, vehicle speed sensors, and brake pressure sensors are used to collect the acceleration, vehicle speed, and brake pressure signals of the electric vehicle disc brake, respectively, and the reconstructed phase diagram is obtained using phase space reconstruction technology;

[0045] S2: Establish a drive-brake coupling model for electric vehicle disc brakes, and use the collected vehicle speed and brake pressure as input to simulate and obtain the phase diagram and time history corresponding to the drive-brake coupling model;

[0046] S3: Compare the phase diagram obtained by phase space reconstruction technology in S1 with the phase diagram obtained by simulation of the drive-brake coupling model in S2 to determine whether they are the same type of vibration. If they are the same type of vibration, further analyze the time history. If they are different types of vibration, modify the friction type parameters in the drive-brake coupling model.

[0047] S4: predicting judder based on the stored brake pressure data and vehicle speed data. If the stored data does not contain corresponding brake pressure and vehicle speed, predicting judder using a drive-brake coupling model and saving the result to a storage device.

[0048] In step S2, the specific steps of simulating and obtaining the phase diagram and time history corresponding to the drive-brake coupling model are as follows:

[0049] S201: The equation of the drive-brake coupling model of the electric vehicle disc brake is,

[0050]

[0051]

[0052]

[0053] S202: Submitting the collected brake pressure and vehicle speed values ​​into a drive-brake coupling model, and simulating to obtain a phase diagram and time history corresponding to the drive-brake coupling model;

[0054] Among them, x1 is the torsion angle of the transmission system, x2 is the torsion angular velocity of the transmission system, x3 is the displacement of the brake pad, x4 is the speed of the brake pad, x5 is the average disturbance of the friction model, m is the mass of the brake pad, k x is the stiffness of the brake pad, d x is the damping of the brake pad, I is the moment of inertia of the brake disc, T m is the driving motor torque, k θ is the stiffness of the transmission system, d θis the damping of the transmission system, σ0 is the contact stiffness coefficient, σ1 is the contact damping coefficient, r is the radius of the brake disc, v s is the Stribeck speed, N is the brake pressure, μ s and μ d denote the static and dynamic friction coefficients respectively, φ(x2, x4, x5) is the average deflection derivative of the bristles, g0 is the Stribeck scaling factor, and Ω0 is the wheel speed.

[0055] Step S3 also includes the following steps:

[0056] S301: If the vibration is of the same type, compare the time history obtained using phase space reconstruction technology with the time history obtained by simulation, and calculate the error between the two. If the error is not zero, feed the error result back to the drive-brake coupling model to correct the model parameters. If the error is zero, it means that the surface model parameters are correct and can be used for flutter prediction.

[0057] In step S301, the method for determining whether the two vibrations are of the same type is as follows:

[0058] If the vibration behaviors corresponding to the simulation model and the phase space reconstruction model are both stable equilibrium points or limit cycle oscillations, then the two are the same type of vibrations;

[0059] Otherwise it is not the same kind of vibration.

[0060] The method for modifying the friction type parameters in the drive-brake coupling model is as follows:

[0061] If the actual measurement shows a limit cycle oscillation, and the simulation result of the drive-brake coupling model shows a stable equilibrium point, then change the relevant parameters of the variable x5 until a limit cycle oscillation appears;

[0062] If the actual measurement is a stable equilibrium point, but the simulation result of the drive-brake coupling model is a limit cycle oscillation, then change the relevant parameters of the variable x5 until a stable equilibrium point appears.

[0063] In step S301, the specific steps of correcting the model parameters according to the obtained error are:

[0064] By solving the mean value of the vibration signal within 2 seconds, the difference between the mean value of the measured signal and the mean value of the simulated signal is taken as the error;

[0065] If the error shows that the measured signal is larger than the simulated signal, reduce the stiffness and damping parameters in the drive-brake coupling model to increase the mean value of the simulated signal until it is equal to the mean value of the measured signal;

[0066] If the error shows that the measured signal is smaller than the simulated signal, increase the stiffness and damping parameter values ​​in the drive-brake coupling model to reduce the mean value of the simulated signal until it is equal to the mean value of the measured signal.

[0067] In step S4, the specific steps of predicting chatter are:

[0068] storing the stored brake pressure value, vehicle speed value, and whether the vibration occurs in a three-dimensional table according to whether the vibration occurs;

[0069] Calculate the maximum Lyapunov exponent of the measured vibration signal. If the maximum Lyapunov exponent is less than zero, no chatter occurs; otherwise, chatter occurs.

[0070] The stored brake pressure values, vehicle speed values, and whether judder occurs are stored in a three-dimensional table, and the measured brake pressure and vehicle speed signals are compared with the data in the three-dimensional table. If there is a corresponding data group in the three-dimensional table, the occurrence of judder can be determined through the array;

[0071] If there is no corresponding brake pressure and vehicle speed in the stored data, the brake pressure and vehicle speed values ​​are imported into the modified drive-brake coupling model as boundary conditions, and the corresponding Lyapunov exponent is calculated to determine whether tremor occurs.

[0072] Example 2

[0073] The second embodiment of the present invention uses a vibration prediction method for electric vehicle disc brakes to perform vibration prediction control. The vibration suppression method includes the following steps:

[0074] S1: Acceleration sensor, vehicle speed sensor and brake pressure sensor are used to collect acceleration, vehicle speed and brake pressure signals of electric vehicle disc brake respectively, and phase space reconstruction technology is used to obtain the reconstructed phase diagram. Assuming that the collected vehicle speed is 0.8m / s, the brake pressure is 9Pa, and the torque T output by the drive motor is m =0;

[0075] S2: Bring the parameters in Table 1 and the vehicle speed signal and brake pressure signal collected in step S1 into the following drive-brake coupling model, and simulate to obtain the corresponding phase diagram (such as Figure 1 ) and time history (e.g. Figure 2 ), it can be seen that under this set of brake pressure and vehicle speed, the brake system will experience extreme vibration.

[0076]

[0077]

[0078]

[0079] Table 1 Simulation parameters

[0080]

[0081] S3: Compare the phase diagram obtained by phase space reconstruction technology in S1 with the phase diagram obtained by simulation of the drive-brake coupling model in S2 to determine whether they are the same type of vibration. It is assumed that both are limit cycle vibrations.

[0082] S4: Based on the assumption in S3 that both are extreme vibrations, compare and analyze the time histories in S1 and S2. Here, assuming that the error is zero, it indicates that the model is correct.

[0083] S5: The corresponding maximum Lyapunov exponent calculated based on the drive-brake coupling model is 0, indicating that judder has occurred. The vehicle speed, brake pressure, and whether judder has occurred are stored in a three-dimensional table, which can be used to predict the occurrence of judder.

[0084] It can be seen from the above embodiments that the method of the present invention can be used to predict whether electric vehicle vibration occurs based on collected data, and the prediction method is simple.

[0085] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for predicting chatter of electric vehicle disc brakes, characterized by: It includes the following steps, Acceleration sensor, vehicle speed sensor and brake pressure sensor are used to collect the acceleration, vehicle speed and brake pressure signals of the electric vehicle disc brake respectively, and the phase space reconstruction technology is used to obtain the reconstructed phase diagram; A drive-brake coupling model for electric vehicle disc brakes is established, and the collected vehicle speed and brake pressure are used as input to simulate and obtain the corresponding phase diagram and time history of the drive-brake coupling model. Compare the phase diagram obtained using phase space reconstruction technology with the phase diagram obtained by the drive-brake coupling model simulation to determine whether the two are the same type of vibration. If they are the same type of vibration, further analyze the time history. If they are different types of vibration, modify the friction type parameters in the drive-brake coupling model. Predicting judder based on stored brake pressure and vehicle speed data; if the stored data does not contain corresponding brake pressure and vehicle speed, predicting judder using a drive-brake coupling model and saving the results to a storage device; The specific steps for analyzing the time history are: If the vibration is the same type, the time history obtained by phase space reconstruction technology is compared with the time history obtained by simulation, and the error between the two is calculated. If the error is not zero, the error result is fed back to the drive-brake coupling model to correct the model parameters. If the error is zero, the surface model parameters are correct and can be used for chatter prediction. The method for determining whether the two vibrations are of the same type comprises the following steps: If the vibration behaviors corresponding to the simulation model and the phase space reconstruction model are both stable equilibrium points or limit cycle oscillations, then the two are the same type of vibrations; Otherwise it is not the same kind of vibration; The specific steps for predicting chatter are: storing the stored brake pressure value, vehicle speed value, and whether the vibration occurs in a three-dimensional table according to whether the vibration occurs; Calculate the maximum Lyapunov exponent of the measured vibration signal. If the maximum Lyapunov exponent is less than zero, no chatter occurs; otherwise, chatter occurs. The stored brake pressure values, vehicle speed values, and whether judder occurs are stored in a three-dimensional table, and the measured brake pressure and vehicle speed signals are compared with the data in the three-dimensional table. If there is a corresponding data group in the three-dimensional table, whether judder occurs can be determined based on the data group; If there is no corresponding brake pressure and vehicle speed in the stored data, the brake pressure and vehicle speed values ​​are imported into the modified drive-brake coupling model as boundary conditions, and the corresponding Lyapunov exponent is calculated to determine whether tremor occurs.

2. The electric vehicle disc brake vibration prediction method according to claim 1, wherein: The specific steps for simulating and obtaining the phase diagram and time history corresponding to the drive-brake coupling model are as follows: The equation of the drive-brake coupling model of the electric vehicle disc brake is: The collected brake pressure and vehicle speed values ​​are brought into the drive-brake coupling model to simulate and obtain the phase diagram and time history corresponding to the drive-brake coupling model; Among them, x1 is the torsion angle of the transmission system, x2 is the torsion angular velocity of the transmission system, x3 is the displacement of the brake pad, x4 is the speed of the brake pad, x5 is the average disturbance of the friction model, m is the mass of the brake pad, k x is the stiffness of the brake pad, d x is the damping of the brake pad, I is the moment of inertia of the brake disc, T m is the driving motor torque, k θ is the stiffness of the transmission system, d θ is the damping of the transmission system, σ0 is the contact stiffness coefficient, σ1 is the contact damping coefficient, r is the radius of the brake disc, v s is the Stribeck speed, N is the brake pressure, μ s and μ d denote the static and dynamic friction coefficients respectively, φ(x2, x4, x5) is the average deflection derivative of the bristles, g0 is the Stribeck scaling factor, and Ω0 is the wheel speed.

3. The electric vehicle disc brake vibration prediction method according to claim 1, wherein: The method for modifying the friction type parameters in the drive-brake coupling model is as follows: If the actual measurement shows a limit cycle oscillation, and the simulation result of the drive-brake coupling model shows a stable equilibrium point, then change the relevant parameters of the variable x5 until a limit cycle oscillation appears; If the actual measurement is a stable equilibrium point, but the simulation result of the drive-brake coupling model is a limit cycle oscillation, then change the relevant parameters of the variable x5 until a stable equilibrium point appears.

4. The electric vehicle disc brake vibration prediction method according to any one of claims 1 to 3, characterized in that: The specific steps for correcting the model parameters according to the obtained errors are: By solving the mean value of the vibration signal within 2 seconds, the difference between the mean value of the measured signal and the mean value of the simulated signal is used as the error; If the error shows that the measured signal is larger than the simulated signal, reduce the stiffness and damping parameters in the drive-brake coupling model to increase the mean value of the simulated signal until it is equal to the mean value of the measured signal; If the error shows that the measured signal is smaller than the simulated signal, increase the stiffness and damping parameter values ​​in the drive-brake coupling model to reduce the mean value of the simulated signal until it is equal to the mean value of the measured signal.

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