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 invention relates to the technical field of wheel hub motor driven vehicle dynamics control, and in particular to an electric wheel slip rate estimation method based on adaptive filtering. Background Art

[0002] With the rapid development of new energy vehicles, the wheel hub motor drive mode has become a hot topic in the field of electric vehicles due to its advantages such as short transmission chain, flexible layout, fast response speed, and independent control. Among them, the road anti-skid control of wheel hub motor driven vehicles has become a widely concerned technology for high-performance wheel hub motor driven vehicles. Wheel slip rate is an important state variable and even a control target in these control methods. The accuracy of its estimation determines the effectiveness, stability and control accuracy of the traction control algorithm, which is crucial to vehicle driving safety.

[0003] In this regard, a Chinese patent with announcement number CN111703429A discloses a method for estimating the longitudinal speed of a vehicle driven by a hub 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, and takes advantage of the fact that the longitudinal force of a vehicle driven by a hub motor is accurately known. The method estimates the slip rate of each wheel, and combines the estimation algorithm residual with the speed calculated by the kinematic model to optimize the effective wheel speed, thereby calculating the longitudinal speed of the vehicle. However, in this patent, there are problems of poor real-time performance and accuracy when using complex state observations, and the accuracy of wheel slip rate estimation depends on the accuracy of the tire model. The hysteresis effect caused by the dynamic deformation of the tire carcass and the slip rate estimation error introduced by the output torque fluctuation of the hub motor are not considered, which will significantly affect the performance of the driving wheel under traction control.

[0004] In summary, the current estimation of electric wheel slip rate in the industry is as follows: on the one hand, the electric wheel slip rate estimated by using the rim speed ignores the speed difference between the rim speed and the tire ring speed caused by tire deformation, and the simplification of the power transmission mechanism in the hub motor drive system leads to the weakening of the interference of the transmission system vibration in the electric wheel slip rate estimation process, while the influence of the vibration and hysteresis effect caused by the dynamic deformation of the tire is more prominent, thus significantly affecting the accuracy and effectiveness of active drive control; on the other hand, the electric wheel is directly driven by the built-in hub motor, and the torque fluctuation characteristics of the motor output will directly affect the tire dynamic performance, thereby causing the fluctuation of the wheel speed, and then interfering with the accurate estimation of the tire slip rate. If a low-pass filter with a fixed cutoff frequency is used for the estimated original slip rate, the transient response characteristics of the tire force caused by the dynamic deformation of the tire and the torque fluctuation of the hub motor cannot be reflected in the electric wheel slip rate signal, resulting in a large error in the estimated slip rate. Therefore, in order to further improve the accuracy of the dynamic control of the hub motor driven vehicle, the present invention proposes an electric wheel slip rate estimation method based on adaptive filtering. Summary of the invention

[0005] Technical issues to be solved:

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

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

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

[0009] Step 1: If it is determined that the current driving state of the vehicle is longitudinal straight driving, there is no steering action, and it is in a driving state, then execute step 2; otherwise, return to step 1;

[0010] Step 2: Obtain vehicle driving parameters of the vehicle under driving conditions, and estimate the original slip rate of the electric wheel according to 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 according to the torsional natural frequency of the vehicle electric wheel system;

[0012] Step 4: acquiring 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] Further, in step 1, the method for determining the current driving state of the vehicle 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 the preset angle value and the wheel hub motor driving torque is a positive value, it is determined that the current driving state of the vehicle is longitudinal straight driving and is a driving condition;

[0018] 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 driving state of the vehicle 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] Further, in step 2, the method for estimating the original slip rate of the electric wheel is as follows:

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

[0022] According to the driving parameters, the original slip rate of the electric wheel of the vehicle is obtained by using the set slip rate calculation formula:

[0023]

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

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

[0026] Acquire the vehicle electric wheel system parameters; wherein the electric wheel system parameters include the tire rim and wheel 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 is obtained as:

[0028]

[0029] The filter low-pass cutoff frequency is proportional to the natural frequency and can be estimated using the following formula:

[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 relationship coefficient between the natural frequency and the peak frequency of the slip rate.

[0032] Further, 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:

[0033] According to the current driving parameters of the vehicle, the instantaneous frequency of the wheel hub motor torque fluctuation order is calculated as follows:

[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] Further, 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:

[0037] According to the instantaneous frequency f of the wheel hub motor torque fluctuation order order The filter low pass cutoff frequency f cutoff There are two situations when choosing the filter type:

[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 the k-order torque fluctuation of the hub motor order >Filter low pass cutoff frequency f cutoff ;

[0040] In case 1, if the torque fluctuation order 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 instantaneous frequency forder >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 stopband of the band-stop filter.

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

[0042] 1. The present invention proposes an electric wheel slip estimation method based on adaptive filtering, taking into account the situation where the rim speed and the tire ring speed are not equal under the influence of the hysteresis effect caused by the dynamic deformation of the tire, and an adaptive filter with adjustable cutoff frequency is designed based on the inherent frequency characteristics of the electric wheel system. By adaptively filtering the original slip signal calculated by the rim speed measurement, a more accurate longitudinal instantaneous slip estimation is achieved, and a more accurate tire force response characteristic is obtained, thereby ensuring the effectiveness of traction control and improving the safety of the vehicle during driving;

[0043] 2. The present invention considers the problem of the impact of motor torque fluctuation on slip estimation and tire transient response characteristics under the direct drive mode of the wheel hub motor. The frequency value corresponding to the torque fluctuation order is derived through theoretical analysis, and the relationship between the torque fluctuation order frequency value and the low-pass cutoff frequency of the filter is compared. The filtering algorithm is divided into two types: a filtering method with torque fluctuation order frequency ≤ low-pass cutoff frequency and a filtering method with torque fluctuation order frequency > low-pass cutoff frequency, which realizes the accurate estimation of the electric wheel slip rate under the linear drive condition considering the influence of torque fluctuation;

[0044] 3. The present invention adopts an adaptive filtering method to realize the estimation of the instantaneous longitudinal slip rate of the electric wheel. The adjustment of the filter parameters is determined by combining online estimation and offline calibration. At the same time, the influence of the low-frequency interference signal of the vehicle body and the suspension and the high-frequency interference signal of 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. At the same time, the method has the characteristics of simple algorithm and easy implementation, which overcomes the problems of poor real-time 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 a control system for a vehicle driven by a wheel hub motor according to the present invention;

[0046] Figure 2 It is a flow chart of the electric wheel slip rate estimation method based on adaptive filtering of the present invention;

[0047] Figure 3This is a diagram of an 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 is further described below in conjunction with the accompanying drawings.

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

[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. Among them, 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 controller VCU sends the vehicle driving state information to the traction control system TCS via the CAN bus. The vehicle driving speed can be obtained by an inertial navigation sensor method, or it can be obtained by a global positioning system (GPS) and sent to the traction control system TCS. The original wheel speed signal can be calculated by 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 driving state at the current moment. Specifically, Figure 2 As shown, the following steps are included:

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

[0052] Firstly, the steering wheel angle and the wheel hub motor driving torque of the vehicle are obtained;

[0053] If the steering wheel angle of the vehicle is less than the preset angle value and the wheel hub motor driving torque is a positive value, it is determined that the current driving state of the vehicle is longitudinal straight driving and is 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 driving state of the vehicle 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 driving conditions, and estimate the original slip rate of the electric wheel according to 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 measuring with sensors, and the original slip rate of the electric wheel of the vehicle is obtained by using the set slip rate calculation formula:

[0059]

[0060] Among them, S is the original slip rate of the vehicle at the current moment, ω r is the tire speed, 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 according to 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 wheel 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 is obtained as:

[0064]

[0065] The filter low-pass cutoff frequency is proportional to the natural frequency and can be estimated using the following formula:

[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, J Ring is the rotational 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 under the driving condition.

[0069] According to the current driving parameters of the vehicle, the instantaneous frequency of the wheel hub motor torque fluctuation order is calculated as follows:

[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, the current harmonics cause the wheel hub motor torque fluctuation, and the torque fluctuation has obvious order characteristics, and the main order k is 6 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 wheel hub motor torque fluctuation order order The filter low pass cutoff frequency f cutoff The relationship between the filter type and filter selection 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 the k-order torque fluctuation of the hub motor order >Filter low pass cutoff frequency f cutoff .

[0076] In case 1, if the torque fluctuation order 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 instantaneous frequency 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 stopband 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 it is determined that the current driving state of the vehicle is longitudinal straight driving, there is no steering action, and it is in a driving state, then execute step 2; otherwise, return to step 1; Step 2: Obtaining vehicle driving parameters under driving conditions, and estimating the original slip rate of the electric wheel according to 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 according to the torsional natural frequency of the vehicle electric wheel system; Step 4: acquiring 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 the preset angle value and the wheel hub motor driving torque is a positive value, it is determined that the current driving state of the vehicle is longitudinal straight driving and is a driving condition; 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 driving state of the vehicle 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: Acquire the current driving state parameters of the vehicle; wherein the driving state parameters include the vehicle driving speed and tire speed; According to the driving parameters, the original slip rate of the electric wheel of the vehicle is obtained by using the set slip rate calculation formula: Among them, S is the original slip rate of the vehicle at the current moment, ω r is the tire speed, 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: Acquire the vehicle electric wheel system parameters; wherein the electric wheel system parameters include the tire rim and wheel 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 is obtained as: The filter low-pass cutoff frequency is proportional to the natural frequency and can be estimated using the following formula: 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 relationship 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 of the wheel hub motor torque fluctuation order is calculated as follows: 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, according to the relationship between the instantaneous frequency of the wheel hub motor torque fluctuation order and the preset filter low-pass cutoff frequency, the filter type and the filter cutoff frequency are selected, including: According to the instantaneous frequency f of the wheel hub motor torque fluctuation order order The filter low pass cutoff frequency f cutoff There are two situations when choosing the filter type: 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 the k-order torque fluctuation of the hub motor order >Filter low pass cutoff frequency f cutoff ; In case 1, if the torque fluctuation order 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 instantaneous frequency 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 stopband of the band-stop filter.

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