Electric wheel slippage rate estimation method based on adaptive filtering

Abstract

The invention discloses an electric wheel slippage rate estimation method based on adaptive filtering, which comprises the following steps of: 1, acquiring running parameters of a vehicle on a current road surface, including a tire rotating speed, a vehicle running speed, a vehicle steering wheel rotating angle and a hub motor driving torque; 2, acquiring an original slip rate estimated value of an electric wheel of the vehicle under a linear driving condition; 3, estimating the inherent frequency of an electric wheel system, and calculating the low-pass cut-off frequency of a filter; 4, acquiring a torque ripple order instantaneous frequency of the hub motor, and selecting a filter type and a cut-off frequency in combination with a low-pass cut-off frequency; and 5, carrying out preset adaptive filtering processing on the original slip rate of the electric wheel to obtain an accurate estimated value of the slip rate of the electric wheel. The method comprehensively considers the influence of the torque fluctuation of the hub motor in the electric wheel and the deformation of the tire body during the estimation of the slip rate, and effectively improves the estimation precision of the slip rate of the electric wheel while guaranteeing the safety.

Description

Technical Field

[0001] The present invention relates to the technical field of wheel hub motor driven vehicle dynamics control, and in particular to a method for estimating electric wheel slip rate based on adaptive filtering. Background Art

[0002] With the rapid development of new energy vehicles, in-wheel motor drive has become a hot topic in the electric vehicle field due to its advantages such as short transmission chains, flexible layout, fast response speed, and independent control. In particular, anti-slip control for in-wheel motor-driven vehicles has become a widely sought-after technology for high-performance in-wheel motor-driven vehicles. Wheel slip rate is a key state variable, and even the control target, in these control methods. The accuracy of its estimation determines the effectiveness, stability, and control accuracy of the traction control algorithm, and is crucial to vehicle safety.

[0003] In this regard, Chinese patent publication number CN111703429A discloses a method for estimating the longitudinal speed of a vehicle driven by an in-wheel motor. This method uses an extended Kalman filter algorithm, based on a seven-degree-of-freedom vehicle dynamics model and a magic formula tire model. Taking advantage of the fact that the longitudinal force of a vehicle driven by an in-wheel motor is accurately known, the method estimates the slip rate of each wheel separately. The method then combines the estimation algorithm residual with the speed calculated by the kinematic model to optimize the effective wheel speed, thereby calculating the vehicle's longitudinal speed. However, this patent suffers from poor real-time performance and accuracy when using complex state observations. Furthermore, the accuracy of the wheel slip rate estimation depends on the accuracy of the tire model. It does not consider the hysteresis effect caused by dynamic deformation of the tire carcass and the slip rate estimation error introduced by fluctuations in the in-wheel motor output torque, which can significantly affect the performance of the drive wheels under traction control.

[0004] In summary, the current state of slip estimation in the industry is as follows: First, the slip estimated using rim speed ignores the speed difference between rim speed and tire ring speed caused by tire deformation. The simplified power transmission mechanism in the in-wheel motor drive system reduces the interference of drive system vibration in the slip estimation process, while the vibration and hysteresis effects caused by tire dynamic deformation become more prominent, significantly affecting the accuracy and effectiveness of active drive control. Second, the motor is directly driven by the built-in in-wheel motor, and the torque fluctuation characteristics of the motor output directly affect the tire dynamic performance, causing wheel speed fluctuations, which in turn interfere with the accurate estimation of tire slip. If the estimated raw slip is low-pass filtered with a fixed cutoff frequency, the transient response characteristics of the tire force caused by tire dynamic deformation and in-wheel motor torque fluctuation cannot be reflected in the slip signal, resulting in large errors in the estimated slip. Therefore, to further improve the accuracy of in-wheel motor-driven vehicle dynamic control, the present invention proposes a slip estimation method for electric wheels based on adaptive filtering. Summary of the Invention

[0005] Technical issues to be solved:

[0006] In order to solve the problems of the prior art such as large errors in estimated slip rates and driving safety caused by torque fluctuations and tire deformation in the above-mentioned electric wheels, the present invention proposes an electric wheel slip rate estimation method based on adaptive filtering. This method considers the influence of dynamic tire deformation and in-wheel motor torque fluctuations on the instantaneous slip rate estimation of the electric wheel, achieves accurate estimation of the longitudinal instantaneous slip rate and reduces costs, thereby improving the effectiveness of traction control and vehicle driving safety of in-wheel motor-driven vehicles.

[0007] The technical solution adopted in the present invention is as follows:

[0008] A method for estimating the slip rate of an electric wheel based on adaptive filtering comprises the following steps:

[0009] Step 1: If the vehicle is currently traveling in a straight longitudinal direction, without any steering action, and in a driving state, then execute step 2; otherwise, return to step 1.

[0010] Step 2: Obtaining vehicle driving parameters under a driving condition, and estimating an original slip rate of the electric wheel based on the vehicle driving parameters;

[0011] Step 3: Obtain the torsional natural frequency of the vehicle electric wheel system, and estimate the low-pass cutoff frequency of the filter based on the torsional natural frequency of the vehicle electric wheel system;

[0012] Step 4: obtaining the instantaneous frequency of the torque fluctuation order of the hub motor according to the vehicle driving parameters of the vehicle under the driving condition;

[0013] Step 5: Select the filter type and filter cutoff frequency according to the relationship between the instantaneous frequency of the wheel hub motor torque fluctuation order and the preset filter low-pass cutoff frequency;

[0014] Step 6: Adaptively filter the original slip rate of the electric wheel according to the filter to obtain an estimated slip rate of the electric wheel generated after filtering.

[0015] Furthermore, in step 1, the method for determining the current vehicle driving state is as follows:

[0016] Obtaining a steering wheel angle and a wheel hub motor driving torque of the vehicle;

[0017] If the steering wheel angle of the vehicle is less than a preset angle value and the wheel hub motor driving torque is a positive value, it is determined that the current vehicle driving state is longitudinal straight driving and is in a driving condition;

[0018] If the steering wheel angle of the vehicle is less than a preset angle value and the wheel hub motor driving torque is a negative value, it is determined that the current vehicle driving state is longitudinal straight driving and is in a braking condition;

[0019] If the steering wheel angle of the vehicle is greater than a preset angle value, it is determined that the vehicle's current driving state is steering driving.

[0020] Furthermore, in step 2, the method for estimating the original slip rate of the electric wheel is as follows:

[0021] Acquiring the current driving state parameters of the vehicle; wherein the driving state parameters include vehicle speed and tire speed;

[0022] According to the driving parameters, the slip ratio calculation formula shown in formula (1) is used to obtain the original slip ratio S of the electric wheel of the vehicle:

[0023]

[0024] Among them, S is the original slip rate of the vehicle at the current moment, ω r is the tire speed, R e is the tire radius, v x is the vehicle speed.

[0025] Furthermore, in step 3, estimating the filter low-pass cutoff frequency according to the torsional natural frequency of the vehicle electric wheel system includes:

[0026] Obtaining the vehicle electric wheel system parameters; wherein the electric wheel system parameters include the tire rim and hub motor moment of inertia, the tire ring moment of inertia, and the tire torsional stiffness;

[0027] According to the parameters of the electric wheel system, the natural frequency f is obtained using formula (2): n for:

[0028]

[0029] The filter low-pass cutoff frequency is proportional to the natural frequency. The filter low-pass cutoff frequency f is estimated using formula (3). cutoff :

[0030]

[0031] Among them, K r is the tire torsional stiffness, J r is the moment of inertia of the tire rim and hub motor, J Ring is the moment of inertia of the tire ring, and N is the proportional coefficient between the natural frequency and the peak frequency of the slip rate.

[0032] Furthermore, in step 4, the instantaneous frequency of the torque fluctuation order of the hub motor is obtained according to the vehicle driving parameters of the vehicle under the driving condition, including:

[0033] According to the current driving parameters of the vehicle, the instantaneous frequency f of the wheel hub motor torque fluctuation order is calculated using formula (4): order for:

[0034]

[0035] Wherein, n is the rotation speed of the hub motor, P is the number of motor pole pairs, and k is the order of the torque fluctuation of the hub motor.

[0036] Furthermore, in step 5, the filter type and filter cutoff frequency are selected according to the relationship between the instantaneous frequency of the torque fluctuation order of the hub motor and the preset low-pass cutoff frequency of the filter, including:

[0037] According to the instantaneous frequency f of the torque fluctuation order of the hub motor order The filter low-pass cutoff frequency f cutoff The relationship between the filter type and the filter type is divided into the following two situations:

[0038] Case 1: Instantaneous frequency f of k-order torque fluctuation of hub motor order ≤Filter low-pass cutoff frequency f cutoff ;

[0039] Case 2: Instantaneous frequency f of k-order torque fluctuation of hub motor order >Filter low-pass cutoff frequency f cutoff ;

[0040] In case 1, if the torque fluctuation order of the hub motor is instantaneous frequency f order ≤Filter low-pass cutoff frequency fcutoff , the adaptive filtering algorithm selects the preset low-pass filter algorithm, and the low-pass cutoff frequency is the filter cutoff frequency f cutoff In case 2, if the torque fluctuation order of the hub motor is f order >Filter low-pass cutoff frequency f cutoff , then select the preset band-stop filter algorithm, the stop-band frequency range is [f cutoff ,f order ], where f cutoff is the lower limit of the stop band of the band-stop filter, f order is the upper limit of the stop band of the band-stop filter.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] 1. This invention proposes a method for estimating the slip rate of an electric wheel based on adaptive filtering. This method considers the hysteresis effect caused by dynamic tire deformation, where the rim speed and tire ring speed are unequal. An adaptive filter with adjustable cutoff frequency is designed based on the inherent frequency characteristics of the electric wheel system. By adaptively filtering the raw slip rate signal calculated from rim speed measurements, a more accurate longitudinal instantaneous slip rate estimation is achieved, resulting in a more precise tire force response characteristic, thereby ensuring the effectiveness of traction control and improving vehicle safety during driving.

[0043] 2. This invention addresses the challenge of how motor torque fluctuations affect slip estimation and tire transient response characteristics under direct drive from in-wheel motors. Through theoretical analysis, the frequency values corresponding to the torque fluctuation orders are derived. By comparing the relationship between the torque fluctuation order frequencies and the filter's low-pass cutoff frequency, the filtering algorithm is divided into two types: one for torque fluctuation order frequencies ≤ the low-pass cutoff frequency and the other for torque fluctuation order frequencies > the low-pass cutoff frequency. This enables accurate estimation of the electric wheel slip rate under linear drive conditions, taking into account the influence of torque fluctuations.

[0044] 3. The present invention uses an adaptive filtering method to estimate the instantaneous longitudinal slip rate of the electric wheel. The filter parameters are adjusted by combining online estimation and offline calibration. The influence of low-frequency interference signals from the vehicle body and suspension and high-frequency interference signals from the road surface on the adaptive filtering algorithm used to estimate the instantaneous longitudinal slip rate is taken into account, thereby improving the robustness of the electric wheel slip rate estimation method. Furthermore, this method has the advantages of being simple and easy to implement, overcoming the problems of poor real-time performance and accuracy when using complex state observation, and can effectively improve the stability of the algorithm. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 This is a schematic diagram of the control system of a vehicle driven by an in-wheel motor according to the present invention;

[0046] Figure 2 Flowchart of the electric wheel slip rate estimation method based on adaptive filtering of the present invention;

[0047] Figure 3 This is a diagram of the electric wheel model that takes into account the torsional deformation of the electric tire body and the torque fluctuation of the hub motor in the present invention. DETAILED DESCRIPTION

[0048] The present invention will be further described below with reference to the accompanying drawings.

[0049] In this embodiment, a method for estimating the slip rate of an electric wheel based on adaptive filtering is provided. The method is based on a filter type and an adaptive filter with adjustable filter parameters designed based on the natural frequency characteristics of the vehicle system vibration and the torque fluctuation characteristics of the hub motor. The method adaptively filters the original slip rate signal estimated by measuring the wheel rim speed to achieve accurate estimation of the slip rate of the electric wheel. The method can be applied to vehicles and control systems driven by hub motors.

[0050] like Figure 1 As shown, the present invention relates to a wheel speed sensor, a traction control system TCS, a vehicle controller VCU, a drive motor controller MCU, a CAN bus and an electric wheel system. Figure 3 As shown. The electric wheel slip rate estimation method based on adaptive filtering designed by the present invention is integrated into the traction control system TCS, and the vehicle driving state information is sent from the vehicle controller VCU to the traction control system TCS via the CAN bus. The vehicle driving speed can be obtained by the inertial sensor method, or it can be obtained by the global positioning system (GPS) and sent to the traction control system TCS. The original wheel speed signal can be obtained by calculating the wheel hub motor speed, or it can be directly measured by the wheel speed sensor and sent to the traction control system TCS. The driving torque is obtained by the drive motor controller MCU and sent to the traction control system TCS via the CAN bus. The steering wheel angle is directly collected by the steering wheel angle sensor and sent to the traction control system TCS to judge the current driving state. Specifically, as Figure 2 As shown, the following steps are included:

[0051] Step 1: If the vehicle is currently traveling in a straight longitudinal direction without any steering action and is in a driving state, then execute step 2; otherwise, return to step 1.

[0052] First, obtain the steering wheel angle and wheel hub motor driving torque of the vehicle;

[0053] If the steering wheel angle of the vehicle is less than the preset angle value and the wheel hub motor driving torque is positive, it is determined that the current vehicle driving state is longitudinal straight driving and is in a driving condition, and step 2 is executed;

[0054] If the steering wheel angle of the vehicle is less than the preset angle value and the wheel hub motor driving torque is a negative value, it is determined that the current vehicle driving state is longitudinal straight driving and is in a braking condition, and the process returns to step 1;

[0055] If the steering wheel angle of the vehicle is greater than the preset angle value, it is determined that the current driving state of the vehicle is steering driving, and the process returns to step 1.

[0056] Step 2: Obtain vehicle driving parameters under the driving condition, and estimate the original slip rate of the electric wheel based on the vehicle driving parameters.

[0057] Wherein, the driving state parameters include the vehicle driving speed and tire speed obtained by sensor measurement;

[0058] First, the vehicle driving state parameters are obtained by sensor measurement, and the slip rate calculation formula shown in formula (1) is used to obtain the original slip rate S of the electric wheel of the vehicle:

[0059]

[0060] Among them, S is the original slip rate of the vehicle at the current moment, ω r is the tire speed, R e is the tire radius, v x is the vehicle speed.

[0061] Step 3: Obtain the torsional natural frequency of the vehicle electric wheel system, and estimate the low-pass cutoff frequency of the filter based on the torsional natural frequency of the vehicle electric wheel system;

[0062] First, the vehicle electric wheel system parameters are obtained; wherein the electric wheel system parameters include the tire rim and hub motor moment of inertia, the tire ring moment of inertia, and the tire torsional stiffness (obtained through vehicle electric wheel system test calibration);

[0063] According to the parameters of the electric wheel system, the natural frequency f is obtained using formula (2): n for:

[0064]

[0065] The filter low-pass cutoff frequency is proportional to the natural frequency. The filter low-pass cutoff frequency f is estimated using formula (3). cutoff :

[0066]

[0067] Among them, K r is the tire torsional stiffness, J r is the moment of inertia of the tire rim and hub motor, JRing is the moment of inertia of the tire ring, and N is the proportional relationship coefficient between the natural frequency and the peak frequency of the slip rate (obtained through experimental calibration, in this embodiment, N=4).

[0068] Step 4: Obtain the instantaneous frequency of the torque fluctuation order of the hub motor according to the vehicle driving parameters of the vehicle under the driving condition.

[0069] According to the current driving parameters of the vehicle, the instantaneous frequency f of the wheel hub motor torque fluctuation order is calculated using formula (4): order for:

[0070]

[0071] Where n is the wheel hub motor speed, P is the number of wheel hub motor pole pairs, and k is the order of the wheel hub motor torque fluctuation. Due to the presence of harmonic components in the wheel hub motor phase current, current harmonics cause wheel hub motor torque fluctuation. Torque fluctuation has a distinct order characteristic, with the main order k being six times the current fundamental frequency.

[0072] Step 5: Select the filter type and filter cutoff frequency according to the relationship between the instantaneous frequency of the wheel hub motor torque fluctuation order and the preset filter low-pass cutoff frequency.

[0073] According to the instantaneous frequency f of the torque fluctuation order of the hub motor order The filter low-pass cutoff frequency f cutoff The relationship between the filter type and the filter type is divided into the following two situations:

[0074] Case 1: Instantaneous frequency f of k-order torque fluctuation of hub motor order ≤Filter low-pass cutoff frequency f cutoff ;

[0075] Case 2: Instantaneous frequency f of k-order torque fluctuation of hub motor order >Filter low-pass cutoff frequency f cutoff ;

[0076] In case 1, if the torque fluctuation order of the hub motor is instantaneous frequency f order ≤Filter low-pass cutoff frequency f cutoff , the adaptive filtering algorithm selects the preset low-pass filter algorithm, and the low-pass cutoff frequency is the filter cutoff frequency f cutoff In case 2, if the torque fluctuation order of the hub motor is f order >Filter low-pass cutoff frequency f cutoff , then select the preset band-stop filter algorithm, the stop-band frequency range is [f cutoff ,f order ], where f cutoff is the lower limit of the stop band of the band-stop filter, forder is the upper limit of the stop band of the band-stop filter.

[0077] Step 6: Adaptively filter the original slip rate of the electric wheel according to the adaptive filter to obtain an estimated slip rate of the electric wheel generated after filtering.

Claims

1. A method for estimating electric wheel slip rate based on adaptive filtering, characterized in that: The following steps are involved: Step 1: If the vehicle is currently traveling in a straight longitudinal direction, without any steering action, and in a driving state, then execute step 2; otherwise, return to step 1. Step 2: Obtaining vehicle driving parameters under a driving condition, and estimating an original slip rate of the electric wheel based on the vehicle driving parameters; Step 3: Obtain the torsional natural frequency of the vehicle electric wheel system, and estimate the low-pass cutoff frequency of the filter based on the torsional natural frequency of the vehicle electric wheel system; Step 4: obtaining the instantaneous frequency of the torque fluctuation order of the hub motor according to the vehicle driving parameters of the vehicle under the driving condition; Step 5: Select the filter type and filter cutoff frequency according to the relationship between the instantaneous frequency of the wheel hub motor torque fluctuation order and the preset filter low-pass cutoff frequency; Step 6: Adaptively filter the original slip rate of the electric wheel according to the filter to obtain an estimated slip rate of the electric wheel generated after filtering.

2. The method for estimating electric wheel slip rate based on adaptive filtering according to claim 1, characterized in that: In step 1, the method for determining the current vehicle driving state is as follows: Obtaining a steering wheel angle and a wheel hub motor driving torque of the vehicle; If the steering wheel angle of the vehicle is less than a preset angle value and the wheel hub motor driving torque is a positive value, it is determined that the current vehicle driving state is longitudinal straight driving and is in a driving condition; If the steering wheel angle of the vehicle is less than a preset angle value and the wheel hub motor driving torque is a negative value, it is determined that the current vehicle driving state is longitudinal straight driving and is in a braking condition; If the steering wheel angle of the vehicle is greater than a preset angle value, it is determined that the vehicle's current driving state is steering driving.

3. The method for estimating electric wheel slip rate based on adaptive filtering according to claim 1, characterized in that: In step 2, the method for estimating the original slip rate of the electric wheel is as follows: Acquiring the current driving state parameters of the vehicle; wherein the driving state parameters include vehicle speed and tire speed; According to the driving parameters, the slip ratio calculation formula shown in formula (1) is used to obtain the original slip ratio S of the electric wheel of the vehicle: Among them, S is the original slip rate of the vehicle at the current moment, ω r is the tire speed, R e is the tire radius, v x is the vehicle speed.

4. The method for estimating electric wheel slip rate based on adaptive filtering according to claim 1, characterized in that: In step 3, estimating the filter low-pass cutoff frequency according to the torsional natural frequency of the vehicle electric wheel system includes: Obtaining the vehicle electric wheel system parameters; wherein the electric wheel system parameters include the tire rim and hub motor moment of inertia, the tire ring moment of inertia, and the tire torsional stiffness; According to the parameters of the electric wheel system, the natural frequency f is obtained using formula (2): n for: The filter low-pass cutoff frequency is proportional to the natural frequency. The filter low-pass cutoff frequency f is estimated using formula (3). cutoff : Among them, K r is the tire torsional stiffness, J r is the moment of inertia of the tire rim and hub motor, J Ring is the moment of inertia of the tire ring, and N is the proportional coefficient between the natural frequency and the peak frequency of the slip rate.

5. The method for estimating electric wheel slip rate based on adaptive filtering according to claim 1, characterized in that: In step 4, according to the vehicle driving parameters of the vehicle under the driving condition, the instantaneous frequency of the torque fluctuation order of the hub motor is obtained, including: According to the current driving parameters of the vehicle, the instantaneous frequency f of the wheel hub motor torque fluctuation order is calculated using formula (4): order for: Wherein, n is the rotation speed of the hub motor, P is the number of motor pole pairs, and k is the order of the torque fluctuation of the hub motor.

6. The method for estimating electric wheel slip rate based on adaptive filtering according to claim 1, characterized in that: In step 5, the filter type and filter cutoff frequency are selected according to the relationship between the instantaneous frequency of the wheel hub motor torque fluctuation order and the preset filter low-pass cutoff frequency, including: According to the instantaneous frequency f of the torque fluctuation order of the hub motor order The filter low-pass cutoff frequency f cutoff The relationship between the filter type and the filter type is divided into the following two situations: Case 1: Instantaneous frequency f of k-order torque fluctuation of hub motor order ≤Filter low-pass cutoff frequency f cutoff ; Case 2: Instantaneous frequency f of k-order torque fluctuation of hub motor order >Filter low-pass cutoff frequency f cutoff ; In case 1, if the torque fluctuation order of the hub motor is instantaneous frequency f order ≤Filter low-pass cutoff frequency f cutoff , the adaptive filtering algorithm selects the preset low-pass filter algorithm, and the low-pass cutoff frequency is the filter cutoff frequency f cutoff In case 2, if the torque fluctuation order of the hub motor is f order >Filter low-pass cutoff frequency f cutoff , then select the preset band-stop filter algorithm, the stop-band frequency range is [f cutoff ,f order ], where f cutoff is the lower limit of the stop band of the band-stop filter, f order is the upper limit of the stop band of the band-stop filter.

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