A detection method for vehicle front wheel angle and its application

Abstract

This invention belongs to the field of automatic control technology, primarily related to the automation of agricultural vehicles, and more particularly to a method for detecting the front wheel angle of a vehicle and its application. This invention provides a method for estimating tire angle based on the rate of change of the steering wheel angle. This method uses the rate of change of the steering wheel angle as input, establishes a mathematical model of the vehicle's steering system, and uses the absolute body angle calculated from vehicle kinematics as a measurement to calculate the tire angle. This method can provide accurate and highly stable front wheel angle detection even when agricultural vehicles are operating at high speeds.

Description

Technical Field

[0001] The present invention belongs to automatic control technology, mainly relates to the field of agricultural machinery and vehicle automation, and in particular to a method for detecting the front wheel angle of a vehicle and its application. Background Art

[0002] In autonomous driving systems, real-time monitoring of vehicle driving information is crucial, especially tire angle monitoring. Accurate tire angle detection is a crucial prerequisite for vehicle control. Front wheel angle detection is typically achieved by installing Hall effect sensors or two IMUs. However, both solutions require sensors to be mounted on the vehicle's front axle, which can lead to wear and tear over extended periods of operation. Furthermore, both solutions are relatively costly.

[0003] To conveniently obtain the front wheel angle and reduce costs, Patent No. ZL202111455635.7 discloses a tire angle analysis method based on a gyroscope and steering wheel angle. This method uses an error model combined with a vehicle kinematic model and incorporates a Kalman filter method to estimate the front wheel angle. Because this invention uses encoder angle values ​​rather than angle differences to calculate the front wheel angle, the steering wheel may occasionally swing violently when the vehicle starts, and the accuracy of the front wheel angle detected when the agricultural vehicle exceeds 10 km / h is also reduced. Summary of the Invention

[0004] Therefore, the present invention proposes a method and application for detecting the front wheel turning angle of a vehicle, which is mainly used in the field of automatic driving of agricultural machinery and is used to estimate the tire turning angle of agricultural machinery vehicles to solve the above-mentioned problems.

[0005] In order to solve the above technical problems, we propose a method and application for detecting the front wheel angle of a vehicle.

[0006] The present invention provides the following technical solutions:

[0007] A method for detecting a front wheel angle of a vehicle comprises the following steps:

[0008] S100, establish a mathematical model of the vehicle steering system

[0009] S200, calculate the absolute angle of the vehicle body based on kinematics

[0010] S300, estimate the front wheel angle:

[0011] According to the S100 and S200, the state equation and observation equation are obtained as follows:

[0012] x k =F k x k-1 +B k uk +w k

[0013] z k =H k x k +v k

[0014] In the formula

[0015]

[0016] H k =[0 1],

[0017] w k is the discrete time process noise with covariance Q k , v k is the observation noise, whose covariance is given by R k Indicates that δ k represents the front wheel turning angle at time k, represents the front wheel angular velocity at time k, Δe is the sampling time interval, τ is the time constant, K is the transmission ratio of the steering system, and u k represents the steering wheel change rate, z k is the observed value at time k, x k represents the state vector at time k, x k-1 represents the state vector at time k-1, F k represents the state transition matrix, B k Represents the input matrix, H k represents the output matrix;

[0018] Based on the above equation, the Kalman filter algorithm used consists of two parts: prediction and update. The prediction part is:

[0019]

[0020] In the formula, - represents the estimated value, P is the state covariance matrix, and the update algorithm is:

[0021]

[0022] Where I is the unit matrix, K k is the gain at time k, is the state vector at time k predicted based on the state vector at time k-1, is the covariance P at k-1 moment k-1 The predicted covariance at time k, P k is the covariance at time k, and Represents F k and Hk The transposed matrix of the updated part is x k This is the front wheel steering angle calculated by the Kalman filter algorithm.

[0023] Preferably, in the above S200, the absolute turning angle of the vehicle body can be calculated by the following formula:

[0024]

[0025] Where, is the vehicle body yaw angular velocity, L is the wheelbase of the agricultural machinery vehicle, V is the vehicle's speed, and z is the absolute turning angle of the vehicle body. This value is the observation value of the subsequent Kalman filter.

[0026] The discretized observation equation can be expressed as:

[0027]

[0028] Where z k is the observed value at time k, δ k represents the front wheel turning angle at time k, represents the angular velocity of the front wheel at time k.

[0029] Preferably, in the above S100, the transfer function of the vehicle steering system is:

[0030]

[0031] Where s represents the s domain, which corresponds to t in the time domain, δ is the front wheel angle, τ is the time constant, u is the steering wheel change rate, and K is the transmission ratio of the steering system.

[0032] The transfer function expression in the time domain is:

[0033]

[0034] Where, is the front wheel angular velocity, is the first-order derivative with respect to time,

[0035] Discretize the expression in the time domain into:

[0036]

[0037] Where Δt is the sampling time interval, δ k represents the front wheel turning angle at time k, δ k-1 Represents the front wheel angle at time k-1. The discretized formula is the state equation used by the subsequent Kalman filter.

[0038] Preferably, the vehicle is equipped with a GNSS antenna and an IMU, and the steering wheel motor is equipped with an incremental encoder.

[0039] An application of a method for detecting the front wheel turning angle of a vehicle, running any of the above-mentioned methods for detecting the front wheel turning angle of a vehicle, is used to continuously estimate the tire turning angle when the agricultural machinery is operating normally.

[0040] An automatic driving agricultural machine, comprising:

[0041] memory for storing computer programs;

[0042] A processor is configured to implement the method for detecting the front wheel angle of a vehicle as described in any of the above items when executing the computer program.

[0043] A computer-readable storage medium stores a computer program, wherein the computer program, when executed by a processor, implements the method for detecting the front wheel angle of a vehicle as described in any one of the above items.

[0044] Compared with the prior art, the present invention has the following beneficial effects:

[0045] To address the high cost of existing tire angle measurement methods, as well as the lack of accuracy and unstable starting during high-speed operation of agricultural machinery, this present invention provides a method for estimating tire angle based on the rate of change of the steering wheel angle. This method uses the rate of change of the steering wheel angle as input, establishes a mathematical model of the vehicle's steering system, and uses the absolute body angle calculated from vehicle kinematics as the measurement variable to calculate the tire angle. This method provides accurate and highly stable front wheel angle detection even during high-speed operation of agricultural machinery. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0047] Figure 1 It is a schematic flow diagram of the present invention. DETAILED DESCRIPTION

[0048] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0049] like Figure 1 As shown, Figure 1 It is a flowchart of an embodiment of the present application.

[0050] The agricultural machinery must be equipped with a GNSS antenna and an IMU, and an incremental encoder on the steering wheel motor. The GNSS antenna obtains the vehicle's east and north coordinates, the IMU measures the vehicle's yaw rate, and the encoder measures the steering wheel angle.

[0051] 1. Mathematical model of vehicle steering system

[0052] The transfer function of the vehicle steering system is:

[0053]

[0054] Where s represents the s domain, which corresponds to t in the time domain, δ is the front wheel angle, τ is the time constant, u is the steering wheel change rate, and K is the gear ratio of the steering system. The transfer function includes a function from the steering wheel change rate u to the front wheel angular velocity A first-order delay system and an angular velocity from the front wheel angle The integral link to the front wheel angle δ. is the first-order derivative with respect to time. The steering wheel change rate can be calculated from the angle recorded by the encoder and the sampling frequency. The transmission ratio can be obtained by calibrating the relationship between the steering wheel angle and the front wheel angle. The expression of the transfer function in the time domain is:

[0055]

[0056] In order to use this model in a real system, the expression in the time domain is discretized as:

[0057]

[0058] Where Δt is the sampling time interval, δ k represents the front wheel turning angle at time k, δ k-1 Represents the front wheel angle at time k-1. The discretized formula is the state equation used by the subsequent Kalman filter.

[0059] 2. Calculate the absolute rotation angle of the vehicle based on kinematics

[0060] Kalman filtering requires measurement values ​​to update the filtering algorithm process. The measurement value used in the present invention is the absolute rotation angle of the vehicle body calculated based on vehicle kinematics, which can be calculated by the following formula:

[0061]

[0062] In the formula is the vehicle's yaw rate, L is the vehicle's wheelbase, and V is the vehicle's speed. z is the vehicle's absolute turning angle, which is the observation value of the subsequent Kalman filter.

[0063] The discretized observation equation can be expressed as:

[0064]

[0065] Where z k is the observation value at time k.

[0066] 3. Estimate the front wheel angle

[0067] Combining Equation 3 and Equation 5, the state equation and observation equation can be obtained as follows:

[0068] x k =F k x k-1 +B k u k +w k

[0069] z k =H k x k +v k

[0070] In the formula

[0071]

[0072] H k =[0 1].

[0073] w k is the discrete time process noise with covariance Q k .v k is the observation noise, and its covariance R k Indicates. k represents the front wheel turning angle at time k, represents the front wheel angular velocity at time k, Δt is the sampling time interval, τ is the time constant, K is the transmission ratio of the steering system, and u k represents the steering wheel change rate, z k is the observed value at time k. k represents the state vector at time k, x k-1 represents the state vector at time k-1, F k represents the state transition matrix, B k Represents the input matrix, H k Represents the output matrix.

[0074] Based on the above equation, the Kalman filter algorithm used in the present invention includes two parts: prediction and update. The prediction part is:

[0075]

[0076] Where ^ represents the estimated value and P is the state covariance matrix. The update algorithm is:

[0077]

[0078] Where I is the unit matrix, K k is the gain at time k, and the x calculated by the update part k This is the front wheel steering angle calculated by the Kalman filter algorithm. is the state vector at time k predicted based on the state vector at time k-1, is the covariance P at k-1 moment k-1 The predicted covariance at time k, P k is the covariance at time k. and Represents F k and H k The transposed matrix of .

[0079] Using the above algorithm, the tire angle can be continuously estimated when the agricultural machinery is operating normally.

[0080] The above process can be summarized as follows:

[0081] A GNSS antenna and IMU are installed on the agricultural machinery, and an incremental encoder is installed on the steering wheel motor. The GNSS antenna obtains the vehicle's coordinate position and speed information, the IMU obtains the vehicle's yaw rate, and the encoder obtains the steering wheel angle.

[0082] This solution requires measuring the wheelbase L of the agricultural vehicle before starting operation. According to vehicle kinematics, the absolute rotation angle z of the vehicle body during movement can be calculated as

[0083]

[0084] In the formula is the vehicle's yaw rate, L is the vehicle's wheelbase, and V is the vehicle's speed. The calculated turning angle is the observation value of the subsequent filtering algorithm.

[0085] Based on the steering wheel angle value read by the encoder and the sampling frequency, the steering wheel change rate can be calculated. This value serves as the input value of the state equation.

[0086] Based on the above observations and input values, a Kalman filter algorithm can be designed to estimate the vehicle's front wheel angle. The mathematical model used in the algorithm is

[0087]

[0088] Where Δt is the sampling time interval, δ k represents the front wheel turning angle at time k, is the front wheel angular velocity at time k, τ represents the time constant in the steering model, u k is the steering wheel change rate, K is the transmission ratio, z k is the observation value at time k.

[0089] Based on the above mathematical model, the extended Kalman filter algorithm can be used to estimate the front wheel angle. By repeating the above process, the tire angle can be continuously estimated while the agricultural machinery is operating normally.

[0090] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0091] Finally, it should be noted that the above descriptions are merely preferred embodiments 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 aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A method for detecting a front wheel angle of a vehicle, characterized in that: The following steps are involved: S100, establish a mathematical model of the vehicle steering system S200, calculate the absolute angle of the vehicle body based on kinematics S300, estimate the front wheel angle: According to the S100 and S200, the state equation and observation equation are obtained as follows: x k =F k x k-1 +B k u k +w k z k =H k x k +v k In the formula H k ＝[0 1]， w k is the discrete time process noise with covariance Q k , v k is the observation noise, whose covariance is given by R k Indicates that δ k represents the front wheel turning angle at time k, represents the front wheel angular velocity at time k, Δt is the sampling time interval, τ is the time constant, K is the transmission ratio of the steering system, and u k represents the steering wheel change rate, z k is the observed value at time k, x k represents the state vector at time k, x k-1 represents the state vector at time k-1, F k represents the state transition matrix, B k Represents the input matrix, H k represents the output matrix; Based on the above equation, the Kalman filter algorithm used consists of two parts: prediction and update. The prediction part is: In the formula, ^ represents the estimated value, P is the state covariance matrix, and the update algorithm is: Where I is the identity matrix, K k is the gain at time k, is the state vector at time k predicted based on the state vector at time k-1, is the covariance P at k-1 time k-1 The predicted covariance at time k, P k is the covariance at time k, and Represents F k and H k The transposed matrix of the updated part is x k This is the front wheel steering angle calculated by the Kalman filter algorithm.

2. The method for detecting the front wheel turning angle of a vehicle according to claim 1, wherein: In the above-mentioned S200, the absolute turning angle of the vehicle body can be calculated by the following formula: Where, is the vehicle body yaw angular velocity, L is the wheelbase of the agricultural machinery vehicle, V is the vehicle's speed, and z is the absolute turning angle of the vehicle body. This value is the observation value of the subsequent Kalman filter. The discretized observation equation can be expressed as: Where z k is the observed value at time k, δ k represents the front wheel turning angle at time k, represents the angular velocity of the front wheel at time k.

3. The method for detecting the front wheel angle of a vehicle according to claim 1, wherein: In the above-mentioned S100, the transfer function of the vehicle steering system is: Where s represents the s domain, which corresponds to t in the time domain, δ is the front wheel angle, τ is the time constant, u is the steering wheel change rate, and K is the transmission ratio of the steering system. The transfer function expression in the time domain is: Where, is the front wheel angular velocity, is the first-order derivative with respect to time, Discretize the expression in the time domain into: Where Δt is the sampling time interval, δ k represents the front wheel turning angle at time k, δ k-1 Represents the front wheel angle at time k-1. The discretized formula is the state equation used by the subsequent Kalman filter.

4. The method for detecting the front wheel turning angle of a vehicle according to claim 1, wherein: The vehicle is equipped with a GNSS antenna and an IMU, and the steering wheel motor is equipped with an incremental encoder.

5. An application of a method for detecting a vehicle front wheel angle, characterized in that: A method for detecting the front wheel turning angle of a vehicle as described in any one of claims 1 to 4 is used to continuously estimate the tire turning angle when the agricultural machinery is in normal operation.

6. An automatic driving agricultural machine, characterized in that: include: memory for storing computer programs; A processor, configured to implement the method for detecting the front wheel angle of a vehicle as claimed in any one of claims 1 to 4 when executing the computer program.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for detecting the front wheel angle of a vehicle according to any one of claims 1 to 4 is implemented.

Images