Steering wheel angle closed-loop control performance optimization method and device, equipment and medium

Abstract

The invention relates to a steering wheel angle closed-loop control performance optimization method and device, equipment and a medium, and is applied to the technical field of automatic driving, and the method comprises the steps: obtaining a steering wheel target angle and a steering wheel actual angle in real time, inputting a difference value between the two angles into a first PID controller, and obtaining a steering wheel target angle speed; the vehicle speed is used for limiting the steering wheel target turning angle change rate, and the limited steering wheel target turning angle change rate is obtained; determining a feed-forward gain according to an absolute value of a difference value between the target steering wheel angle and the actual steering wheel angle; determining a feed-forward compensation rotation angle speed according to the limited steering wheel target rotation angle change rate and the feed-forward gain; and inputting the sum of the target steering wheel angular velocity and the feedforward compensation angular velocity and the difference between the sum and the actual steering wheel angular velocity into a second PID controller to obtain a target output torque. The response speed of the steering wheel can be improved.

Description

Technical Field

[0001] The present application relates to the field of autonomous driving technology, and in particular to a method, device, equipment and medium for optimizing the closed-loop control performance of a steering wheel angle. Background Art

[0002] Currently, Level 4 autonomous driving technology is still in its developmental stages, and the technology has not yet reached a level where the driver no longer needs to take over the vehicle. Therefore, Level 4 autonomous driving vehicles still need to retain a traditional steering wheel for the driver to take over the vehicle. Level 4 autonomous driving often requires controlling the vehicle's steering wheel angle at a small angle. After the Level 4 autonomous driving function is activated, when the ADU (Autonomous Driving Unit) sends a small steering angle command and requires the fully redundant R-Electronic Power Steering (Rack-Electronic Power Steering) to respond quickly, if a large slope ramp signal or a high-frequency sinusoidal signal is input, the conventional steering angle closed-loop control algorithm will suffer from insufficient dynamic response speed, excessive execution time for ramp input, and large phase delay and amplitude error for sinusoidal input. Summary of the Invention

[0003] In order to solve the above technical problems, the present application provides a method, device, electronic device and storage medium for optimizing the closed-loop control performance of a steering wheel angle.

[0004] According to a first aspect of the present application, a method for optimizing steering wheel angle closed-loop control performance is provided, comprising:

[0005] After the autonomous driving vehicle enters the autonomous driving mode, obtaining a target steering wheel angle and an actual steering wheel angle in real time, and inputting a difference between the target steering wheel angle and the actual steering wheel angle into a first PID controller to obtain a target steering wheel angle velocity;

[0006] Obtain the rotation angle and rotation direction of the motor rotor in real time, and determine the actual steering wheel angular speed based on the rotation angle and rotation direction of the motor rotor and the transmission ratio between the steering wheel and the motor;

[0007] Derivative the target steering wheel angle with respect to the signal period to determine a steering wheel target angle change rate, and limit the steering wheel target angle change rate using the speed of the autonomous driving vehicle to obtain a limited steering wheel target angle change rate;

[0008] determining a feedforward gain according to an absolute value of a difference between the target steering wheel angle and the actual steering wheel angle; wherein the feedforward gain is inversely correlated with the absolute value;

[0009] determining a feedforward compensation angular velocity according to the limited steering wheel target angle change rate and the feedforward gain;

[0010] The difference between the sum of the target steering wheel angular velocity and the feedforward compensation angular velocity and the actual steering wheel angular velocity is input into a second PID controller to obtain a target output torque.

[0011] Optionally, the steering wheel angle closed-loop control performance optimization method further includes:

[0012] When the steering wheel target angle change rate meets the preset conditions, the nonlinear damping control coefficient K1 is set to 1; when the steering wheel target angle change rate does not meet the preset conditions, the nonlinear damping control coefficient K1 is set to 0;

[0013] When the rotation speed of the motor rotor is less than or equal to a preset speed threshold, the motor rotor rotation coefficient Ms is set to 0; when the rotation speed of the motor rotor is greater than the preset speed threshold, the motor rotor rotation coefficient Ms is set according to the rotation speed of the motor rotor; wherein the motor rotor rotation coefficient Ms is positively correlated with the rotation speed of the rotor;

[0014] Setting a vehicle speed coefficient Vs according to the speed of the autonomous vehicle, wherein the vehicle speed coefficient Vs is proportional to the vehicle speed;

[0015] Obtaining a deformation angle of the torque angle sensor, resolving the deformation angle into a steering wheel steering torque, and setting a steering wheel hand torque coefficient Tp according to the steering wheel steering torque, wherein the steering wheel hand torque coefficient Tp is proportional to the steering wheel steering torque;

[0016] Multiplying the nonlinear damping control coefficient K1, the motor rotor rotation coefficient Ms, the vehicle speed coefficient Vs, and the steering wheel hand torque coefficient Tp, and processing the obtained product using the nonlinear damping gain Kg to obtain a nonlinear damping control torque, so that the nonlinear damping control torque is within a preset compensation torque range;

[0017] The target output torque is superimposed on the nonlinear damping control torque to obtain a final output torque.

[0018] Optionally, the limiting the steering wheel target angle change rate by using the speed of the autonomous driving vehicle includes:

[0019] Determining a target turning angle change rate limit value based on the speed of the autonomous driving vehicle, wherein the target turning angle change rate limit value is inversely proportional to the vehicle speed;

[0020] When the steering wheel target angle change rate is greater than the target angle change rate limit value, setting the steering wheel target angle change rate to the target angle change rate limit value;

[0021] When the steering wheel target angle change rate is less than or equal to the target angle change rate limit value, no processing is performed.

[0022] Optionally, determining the feedforward compensation angular velocity according to the limited steering wheel target angle change rate and the feedforward gain includes:

[0023] The feedforward compensation angular velocity is obtained by multiplying the limited steering wheel target angle change rate and the feedforward gain, and filtering the obtained product.

[0024] Optionally, the step of differentiating the target steering wheel angle with respect to the signal period to determine the steering wheel target angle change rate includes:

[0025] If the absolute value of the target steering wheel angle is less than or equal to a preset angle threshold, and the slope of the ramp input is greater than the preset slope threshold or the frequency of the sinusoidal input is greater than a preset frequency, the target steering wheel angle is differentiated with respect to the signal period to determine the rate of change of the target steering wheel angle.

[0026] Optionally, determining the actual angular velocity of the steering wheel according to the rotation angle and rotation direction of the motor rotor and the transmission ratio relationship between the steering wheel and the motor includes:

[0027] Determine the rotation speed of the motor rotor according to the rotation angle and rotation direction of the motor rotor;

[0028] According to the transmission ratio relationship between the steering wheel and the motor, the rotational angular velocity of the motor rotor is converted into the actual angular velocity of the steering wheel.

[0029] Optionally, a method for determining whether the steering wheel target angle change rate meets a preset condition is:

[0030] When the steering wheel target angle change rate is 0 and the duration is greater than or equal to a preset time threshold, it is determined that the steering wheel target angle change rate meets the preset condition;

[0031] When the steering wheel target angle change rate is not 0, or the steering wheel target angle change rate is 0 but lasts for less than a preset time threshold, it is determined that the steering wheel target angle change rate does not meet the preset condition.

[0032] According to a second aspect of the present application, a device for optimizing steering wheel angle closed-loop control performance is provided, comprising:

[0033] a target angular velocity determination module, configured to obtain a target steering wheel angle and an actual steering wheel angle in real time after the autonomous vehicle enters the autonomous driving mode, and input a difference between the target steering wheel angle and the actual steering wheel angle into a first PID controller to obtain a target steering wheel angular velocity;

[0034] The actual angular speed determination module is used to obtain the rotation angle and rotation direction of the motor rotor in real time, and determine the actual angular speed of the steering wheel based on the rotation angle and rotation direction of the motor rotor and the transmission ratio between the steering wheel and the motor;

[0035] a module for determining a limited target steering angle change rate, configured to determine a steering wheel target angle change rate by differentiating the steering wheel target angle with respect to the signal period, and to limit the steering wheel target angle change rate using the speed of the autonomous vehicle to obtain a limited steering wheel target angle change rate;

[0036] a feedforward gain determination module, configured to determine a feedforward gain according to an absolute value of a difference between the target steering wheel angle and the actual steering wheel angle; wherein the feedforward gain is inversely correlated with the absolute value;

[0037] a feedforward compensation angular velocity determination module, configured to determine a feedforward compensation angular velocity according to the limited steering wheel target angle change rate and the feedforward gain;

[0038] The target output torque determination module is configured to input the difference between the sum of the target steering wheel angular velocity and the feedforward compensation angular velocity and the actual steering wheel angular velocity into a second PID controller to obtain a target output torque.

[0039] Optionally, the steering wheel angle closed-loop control performance optimization device further includes:

[0040] a nonlinear damping control coefficient setting module, configured to set the nonlinear damping control coefficient K1 to 1 when the steering wheel target angle change rate meets a preset condition; and to set the nonlinear damping control coefficient K1 to 0 when the steering wheel target angle change rate does not meet the preset condition;

[0041] a motor rotor rotation coefficient setting module, configured to set the motor rotor rotation coefficient Ms to 0 when the motor rotor rotation speed is less than or equal to a preset speed threshold; and to set the motor rotor rotation coefficient Ms according to the motor rotor rotation speed when the motor rotor rotation speed is greater than the preset speed threshold; wherein the motor rotor rotation coefficient Ms is positively correlated with the rotor rotation speed;

[0042] A vehicle speed coefficient setting module, used to set a vehicle speed coefficient Vs according to the speed of the autonomous driving vehicle, wherein the vehicle speed coefficient Vs is proportional to the vehicle speed;

[0043] a steering wheel hand torque coefficient setting module, configured to obtain a deformation angle of the torque angle sensor, resolve the deformation angle into a steering wheel steering torque, and set a steering wheel hand torque coefficient Tp according to the steering wheel steering torque, wherein the steering wheel hand torque coefficient Tp is proportional to the steering wheel steering torque;

[0044] a nonlinear damping control torque determination module, configured to multiply the nonlinear damping control coefficient K1, the motor rotor rotation coefficient Ms, the vehicle speed coefficient Vs, and the steering wheel hand torque coefficient Tp, and process the obtained product using a nonlinear damping gain Kg to obtain a nonlinear damping control torque, so that the nonlinear damping control torque is within a preset compensation torque range;

[0045] The final output torque determination module is configured to superimpose the target output torque and the nonlinear damping control torque to obtain a final output torque.

[0046] Optionally, the limited target angle change rate determination module is specifically used to differentiate the steering wheel target angle with respect to the signal period to determine the steering wheel target angle change rate, and determine the target angle change rate limit value according to the speed of the autonomous driving vehicle, wherein the target angle change rate limit value is inversely proportional to the vehicle speed; when the steering wheel target angle change rate is greater than the target angle change rate limit value, the steering wheel target angle change rate is set to the target angle change rate limit value to obtain the limited steering wheel target angle change rate; when the steering wheel target angle change rate is less than or equal to the target angle change rate limit value, no processing is performed.

[0047] Optionally, the feedforward compensation angular velocity determination module is specifically configured to multiply the limited steering wheel target angle change rate by the feedforward gain, and filter the obtained product to obtain the feedforward compensation angular velocity.

[0048] Optionally, the module for determining the target steering angle change rate after limitation is specifically configured to determine the steering wheel target angle change rate by differentiating the steering wheel target angle with respect to the signal period if the absolute value of the steering wheel target angle is less than or equal to a preset angle threshold, and the slope of the ramp input is greater than a preset slope threshold or the frequency of the sinusoidal input is greater than a preset frequency, and limit the steering wheel target angle change rate using the speed of the autonomous driving vehicle to obtain the limited steering wheel target angle change rate.

[0049] Optionally, the actual angular velocity determination module is specifically used to obtain the rotation angle and rotation direction of the motor rotor in real time, determine the rotation speed of the motor rotor based on the rotation angle and rotation direction of the motor rotor; and convert the rotation angular velocity of the motor rotor into the actual angular velocity of the steering wheel based on the transmission ratio relationship between the steering wheel and the motor.

[0050] Optionally, the steering wheel angle closed-loop control performance optimization device further includes:

[0051] The judgment module is configured to determine that the target steering wheel angle change rate satisfies a preset condition when the target steering wheel angle change rate is zero and lasts for a period greater than or equal to a preset time threshold; and to determine that the target steering wheel angle change rate does not satisfy the preset condition when the target steering wheel angle change rate is not zero, or when the target steering wheel angle change rate is zero but lasts for a period less than the preset time threshold.

[0052] According to a third aspect of the present application, an electronic device is provided, comprising: a processor, wherein the processor is configured to execute a computer program stored in a memory, wherein the computer program implements the method described in the first aspect when executed by the processor.

[0053] According to a fourth aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the method described in the first aspect is implemented.

[0054] According to a fifth aspect of the present application, a computer program product is provided. When the computer program product is run on a computer, the computer is caused to execute the method described in the first aspect.

[0055] The technical solution provided by the embodiments of the present application has the following advantages compared with the prior art:

[0056] When the autonomous driving control unit sends a steering wheel angle request to the fully redundant R-EPS via the steering angle interface, it calculates the target steering wheel angle rate of change and limits it based on the autonomous vehicle's speed, resulting in a limited target steering wheel angle rate. The feedforward gain is determined based on the absolute value of the difference between the target steering wheel angle and the actual steering wheel angle. Typically, steering wheel angle response is slow when the angle difference is small. Therefore, a larger feedforward gain is set for smaller angle differences and a smaller one for larger angle differences. When the angle difference is small, increasing the feedforward gain enhances feedforward compensation, accelerating steering wheel response. When the angle difference is large, the feedforward compensation gain is smaller, weakening the feedforward compensation effect and preventing overshoot. Furthermore, the fully redundant R-EPS's response speed is improved for ramped or sinusoidal inputs, particularly for sinusoidal inputs with large phase delays. This issue, which is often caused by the large phase delay in the R-EPS response when the sinusoidal input frequency is high, is addressed. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0058] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0059] Figure 1 This is a schematic diagram of the connection relationship between the fully redundant R-EPS and the ADU on the CAN bus in an embodiment of the present application;

[0060] Figure 2 This is a flow chart of a method for optimizing the closed-loop control performance of the steering wheel angle of an autonomous driving vehicle in an embodiment of the present application;

[0061] Figure 3 A schematic diagram of determining the feedforward compensation angular velocity in an embodiment of the present application;

[0062] Figure 4 This is the ramp input response curve when the target angular velocity feedforward compensation algorithm is not enabled;

[0063] Figure 5 This is a ramp input response curve when the target angular velocity feedforward compensation algorithm is turned on in the embodiment of the present application;

[0064] Figure 6 This is the sinusoidal input response curve when the target angular velocity feedforward compensation algorithm is not enabled;

[0065] Figure 7 This is a sinusoidal input response curve when the target angular velocity feedforward compensation algorithm is turned on in the embodiment of the present application;

[0066] Figure 8 This is the response curve of the ADU controlling the steering wheel rotation;

[0067] Figure 9 This is another flow chart of the method for optimizing the closed-loop control performance of the steering wheel angle in the embodiment of the present application;

[0068] Figure 10 A schematic diagram of a nonlinear damping algorithm in an embodiment of the present application;

[0069] Figure 11 A schematic diagram of a method for optimizing the closed-loop control performance of a steering wheel angle in an embodiment of the present application;

[0070] Figure 12 This is a structural schematic diagram of a device for optimizing the closed-loop control performance of steering wheel angle of an autonomous driving vehicle in an embodiment of the present application;

[0071] Figure 13 This is a structural diagram of an electronic device in an embodiment of the present application. DETAILED DESCRIPTION

[0072] In order to more clearly understand the above-mentioned objectives, features and advantages of the present application, the scheme of the present application will be further described below. It should be noted that, in the absence of conflict, the embodiments of the present application and the features therein can be combined with each other.

[0073] In the following description, many specific details are set forth to facilitate a full understanding of the present application, but the present application can also be implemented in other ways different from those described herein; it is obvious that the embodiments in the specification are only part of the embodiments of the present application, not all of the embodiments.

[0074] Figure 1 The figure is a schematic diagram of the connection relationship between the fully redundant R-EPS and ADU on the CAN bus in the embodiment of the present application. Both controllers of the fully redundant R-EPS product have independent and autonomous steering angle control capabilities. When any controller fails, the other fault-free controller can continue to work as the main controller. The fully redundant R-EPS product ECU (Electronic Control Unit) opens the steering wheel angle request, control request and speed limit interface to the ADU, and sends its own response status to the ADU in the form of CAN communication messages.

[0075] See also Figure 2 , Figure 2This is a flow chart of a method for optimizing the closed-loop control performance of a steering wheel angle according to an embodiment of the present application, which may include the following steps:

[0076] In step S202, after the autonomous driving vehicle enters the autonomous driving mode, the target steering wheel angle and the actual steering wheel angle are obtained in real time, and the difference between the target steering wheel angle and the actual steering wheel angle is input into the first PID controller to obtain the target steering wheel angle speed.

[0077] The fully redundant R-EPS receives the control request sent by the ADU. The fully redundant R-EPS itself is in a state that satisfies the requirement to enter the autonomous driving mode. The front-wheel steering control function of the autonomous driving vehicle is activated. The ADU sends a steering wheel angle request to the fully redundant R-EPS. The steering wheel angle request includes the target steering wheel angle. The input modes of the steering wheel angle request include ramp input or sinusoidal input. The TAS (Torque Angle Sensor) can detect the angle of the steering wheel and send the detected signal to the R-EPS ECU via the SENT signal transmission protocol. The R-EPS ECU interprets the signal as the actual angle of the steering wheel, i.e., the actual steering wheel angle.

[0078] The target steering wheel angle and the actual steering wheel angle typically have a certain error. By calculating the difference between the target and actual steering wheel angles and inputting this difference into the first PID controller, the target steering wheel angle velocity can be obtained. This control loop is an angle closed loop, with the actual steering wheel angle serving as the feedback angle for the closed loop.

[0079] Step S204 , obtaining the rotation angle and rotation direction of the motor rotor in real time, and determining the actual angular velocity of the steering wheel according to the rotation angle and rotation direction of the motor rotor and the transmission ratio relationship between the steering wheel and the motor.

[0080] The fully redundant R-EPS motor is a permanent magnet synchronous motor. The rotation angle and rotation direction of the motor rotor are obtained through the RPS (Rotation Position Sensor). The rotation speed of the motor rotor is determined based on the rotation angle and rotation direction of the motor rotor. For example, the rotation speed of the motor rotor can be estimated by the Kalman filter algorithm, and the rotation angular velocity of the motor rotor can be converted into the actual angular velocity of the steering wheel based on the transmission ratio relationship between the steering wheel and the motor. The actual angular velocity of the steering wheel is used as the feedback angular velocity of the speed closed loop. In the related art, the difference between the target steering wheel angular velocity and the actual steering wheel angular velocity is passed through a second PID controller to obtain the target output torque. This control loop is a speed closed loop. It can be seen that the existing steering wheel angle closed loop control includes an angle closed loop and a speed closed loop.

[0081] In step S206, the steering wheel target angle is differentiated with respect to the signal period to determine the steering wheel target angle change rate, and the steering wheel target angle change rate is limited by the speed of the autonomous driving vehicle to obtain a limited steering wheel target angle change rate.

[0082] The target steering angle velocity feedforward compensation algorithm can perform feedforward compensation based on the speed of the autonomous vehicle. Optionally, a target steering angle rate limit can be determined based on the speed of the autonomous vehicle. The target steering angle rate limit is inversely proportional to the vehicle speed. Higher speeds correspond to lower target steering angle rate limits, improving driving safety. For example, different target steering angle rate limits can be set based on different speed gradients. If the autonomous vehicle's speed is within a certain speed gradient, the target steering angle rate limit corresponding to that speed gradient is determined as the target steering angle rate limit corresponding to the autonomous vehicle's speed. When the steering wheel target steering angle rate exceeds the target steering angle rate limit, the target steering angle rate is set to the target steering angle rate limit to prevent excessive steering angle rate increases. When the steering wheel target steering angle rate is less than or equal to the target steering angle rate limit, no action is taken.

[0083] In some embodiments, if the absolute value of the target steering wheel angle is less than or equal to a preset angle threshold, such as 20°, the requested steering wheel angle is considered to be small. Furthermore, if the slope of the ramp input is greater than a preset slope threshold or the frequency of the sinusoidal input is greater than a preset frequency, the R-EPS response is insufficiently rapid, with significant response delay and amplitude error for sinusoidal inputs. Adjusting the angle and velocity closed-loop parameters may not achieve both fast and stable dynamic performance. In this case, step S206 is executed, where the steering wheel is controlled according to the target angle velocity feedforward compensation algorithm.

[0084] If the absolute value of the target steering wheel angle is greater than the preset angle threshold, or if the absolute value of the target steering wheel angle is less than or equal to the preset angle threshold and the slope of the ramp input is less than or equal to the preset slope threshold or the frequency of the sinusoidal input is less than or equal to the preset frequency, since the R-EPS responds relatively quickly, the steering wheel can also be controlled according to the existing steering wheel angle closed-loop control method.

[0085] Step S208 : determining a feedforward gain according to the absolute value of the difference between the target steering wheel angle and the actual steering wheel angle; wherein the feedforward gain is inversely correlated with the absolute value.

[0086] Typically, steering wheel angle response is slow when the angle difference is small. Therefore, a larger feedforward gain is set where the angle difference is small, and a smaller feedforward gain is set where the angle difference is large. When the angle difference is small, increasing the feedforward gain enhances the feedforward compensation effect, speeding up steering wheel response. When the angle difference is large, the feedforward compensation gain is smaller, weakening the feedforward compensation effect and preventing overshoot.

[0087] Step S210 : determining a feedforward compensation angular velocity according to the limited steering wheel target angle change rate and the feedforward gain.

[0088] In this embodiment of the present application, the feedforward compensation angular velocity can be obtained by multiplying the limited target steering wheel angle change rate by the feedforward gain. Since obtaining the target steering wheel angle change rate through derivation introduces high-frequency noise, the feedforward compensation angular velocity can also be obtained by multiplying the limited target steering wheel angle change rate by the feedforward gain and filtering the resulting product to obtain a smoother feedforward compensation angular velocity.

[0089] like Figure 3 As shown, the steering wheel target angle in the steering wheel angle request sent by the ADU CAN signal message cycle T S The steering wheel target angle change rate is obtained by taking the derivative, and the steering wheel target angle change rate is limited by the vehicle speed to obtain the limited steering wheel target angle change rate. The TAS sensor can collect the actual steering wheel angle θ, based on the steering wheel target angle The absolute value of the difference between the actual steering wheel angle θ and the feedforward gain can be used to determine the feedforward gain. The feedforward compensation angular velocity is obtained by multiplying the limited steering wheel target angle change rate and the feedforward gain and performing low-pass filtering.

[0090] In step S212, the difference between the sum of the target steering wheel angular velocity and the feedforward compensation angular velocity and the actual steering wheel angular velocity is input into a second PID controller to obtain a target output torque.

[0091] By adding the feedforward compensation angular velocity to the target steering wheel angular velocity and then calculating the difference between the two values and the actual steering wheel angular velocity, the magnitude of the difference can be increased. This increases the input to the second PID controller, which in turn increases the output and, consequently, the target output torque. This improves the response speed when controlling steering wheel rotation using the target output torque.

[0092] See also Figure 4 and Figure 5, are the slope input response curves when the target angular velocity feedforward compensation algorithm is not enabled and when the target angular velocity feedforward compensation algorithm is enabled. It can be seen that after the target angular velocity feedforward compensation algorithm is enabled, the fully redundant R-EPS can quickly respond to the target steering wheel angle. Figure 6 and Figure 7 , respectively, show the sinusoidal input response curves when the target angular velocity feedforward compensation algorithm is disabled and enabled. It can be seen that with the target angular velocity feedforward compensation algorithm enabled, the fully redundant R-EPS also responds quickly to the target steering wheel angle. Furthermore, the R-EPS response phase delay is reduced, and the following amplitude error is lowered.

[0093] In this embodiment of the present application, when the ADU sends a target steering wheel angle to the fully redundant R-EPS and requests a rapid response, it can utilize a target angular velocity feedforward compensation algorithm to calculate a feedforward compensation angular velocity based on vehicle speed, the target steering wheel angle, and the actual steering wheel angle. Using the feedforward compensation angular velocity to compensate for the target steering wheel angular velocity addresses the issue of insufficient responsiveness in the fully redundant R-EPS, as well as the significant phase delay and amplitude error associated with sinusoidal inputs.

[0094] In the automatic driving mode, due to the inertia of the steering wheel and the column, the pinion and the column are connected by an elastic torsion bar, which introduces certain obstacles and external interference to the steering wheel angle closed-loop control system. That is, the inertia of the steering wheel and the column causes the deformation of the TAS sensor torsion bar, introduces certain oscillation interference, and the dynamic stability of the response process becomes worse. When the steering wheel responds quickly to the steering wheel angle request sent by the ADU, there will be problems such as overshoot and callback, and the time to enter the steady state is too long. Specifically, when the ADU controls the steering wheel to start accelerating and the steering wheel decelerates when approaching the target steering wheel angle, a large steering wheel hand torque will be generated. This torque will cause the response delay to become longer and bring certain overshoot and angle fluctuations, weakening the dynamic response performance. For example Figure 8 As shown in the figure, when the target steering wheel angle is 40°, the inertia moment of the steering wheel when it is turned causes fluctuations in the actual steering wheel angle. Based on this, the embodiment of the present application also introduces a nonlinear damping control algorithm to optimize the closed-loop control performance of the steering wheel angle.

[0095] See also Figure 9 , Figure 9 This is another flow chart of the steering wheel angle closed-loop control performance optimization method in the embodiment of the present application. Figure 2 Based on the embodiment, the following steps are also included:

[0096] Step S902 : When the steering wheel target angle change rate meets the preset condition, the nonlinear damping control coefficient K1 is set to 1; when the steering wheel target angle change rate does not meet the preset condition, the nonlinear damping control coefficient K1 is set to 0.

[0097] The nonlinear damping control coefficient K1 controls whether the nonlinear damping control algorithm is enabled. When the target steering wheel angle rate of change meets the preset conditions, the nonlinear damping control coefficient K1 is set to 1, indicating that the nonlinear damping control algorithm is enabled. Otherwise, the nonlinear damping control coefficient K1 is set to 0, indicating that the nonlinear damping control algorithm is disabled.

[0098] Optionally, a method for determining whether the steering wheel target angle change rate meets a preset condition is:

[0099] When the target steering wheel angle change rate is zero and persists for a time greater than or equal to a preset time threshold, the target steering wheel angle change rate is determined to meet the preset condition. When the target steering wheel angle change rate is not zero, or when the target steering wheel angle change rate is zero but persists for a time less than the preset time threshold, the target steering wheel angle change rate is determined to not meet the preset condition. Specifically, when the target steering wheel angle remains unchanged for a long period (e.g., approximately 100ms), the nonlinear damping control algorithm is activated; otherwise, the nonlinear damping control algorithm is deactivated.

[0100] Step S904 , when the rotation speed of the motor rotor is less than or equal to the preset speed threshold, the motor rotor rotation coefficient Ms is set to 0; when the rotation speed of the motor rotor is greater than the preset speed threshold, the motor rotor rotation coefficient Ms is set according to the rotation speed of the motor rotor.

[0101] A nonlinear deadband module can be configured for the motor rotor rotation coefficient, Ms. When the motor rotor's rotation speed is low, the motor rotor rotation coefficient, Ms, can be set to 0. When the motor rotor's rotation speed is high, the motor rotor rotation coefficient, Ms, is set based on the motor rotor's rotation speed, meaning that the motor rotor rotation coefficient, Ms, is not zero. The higher the motor rotor's rotation speed, the greater the need for increased nonlinear damping torque. Therefore, the motor rotor rotation coefficient, Ms, is positively correlated with the rotor's rotation speed.

[0102] Step S906: Set the vehicle speed coefficient Vs according to the speed of the autonomous driving vehicle, wherein the vehicle speed coefficient Vs is proportional to the vehicle speed.

[0103] The nonlinear damping torque can also be adjusted according to different vehicle speeds. The higher the vehicle speed, the greater the nonlinear damping torque.

[0104] Step S908: Obtain the deformation angle of the torque angle sensor, resolve the deformation angle into the steering torque of the steering wheel, and set the steering wheel hand torque coefficient Tp according to the steering torque of the steering wheel.

[0105] In autonomous driving mode, as the ADU controls the steering wheel angle to follow the target steering wheel angle, the inertia of the steering column and steering wheel causes the TAS sensor torsion bar to deform. This torsion bar deformation angle signal is detected and transmitted to the R-EPS ECU via the SENT signal transmission protocol. The R-EPS ECU interprets this signal as steering wheel torque. The direction of the steering wheel torque is opposite to the target output torque. The steering wheel hand torque coefficient Tp can be set based on the steering wheel torque and is proportional to the steering wheel torque.

[0106] In step S910, the nonlinear damping control coefficient K1, the motor rotor rotation coefficient Ms, the vehicle speed coefficient Vs and the steering wheel hand torque coefficient Tp are multiplied, and the obtained product is processed using the nonlinear damping gain Kg to obtain the nonlinear damping control torque, so that the nonlinear damping control torque is within the preset compensation torque range.

[0107] See also Figure 10 , Figure 10 This is a schematic diagram of the nonlinear damping algorithm used in the embodiments of this application. The nonlinear damping control torque is obtained by multiplying the nonlinear damping control coefficient K1, the motor rotor rotation coefficient Ms, the vehicle speed coefficient Vs, the steering wheel hand torque coefficient Tp, and the nonlinear damping gain Kg. The direction of the nonlinear damping control torque is opposite to the target output torque.

[0108] The nonlinear damping gain Kg is a preset fixed value used to adjust the resulting nonlinear damping control torque. For example, if the nonlinear damping control coefficient K1 is 1, the motor rotor rotation coefficient Ms is 4000, the vehicle speed coefficient Vs is 100, and the steering wheel hand torque coefficient Tp is 200, the nonlinear damping gain Kg is 0.00000002, and the nonlinear damping control torque = 1 × 4000 × 100 × 200 × 0.00000002 = 1.6 Nm.

[0109] Step S912: superimpose the target output torque and the nonlinear damping control torque to obtain the final output torque.

[0110] Figure 11 This is a schematic diagram of a method for optimizing the closed-loop control performance of the steering wheel angle in an embodiment of the present application. The steering wheel target angular velocity is obtained by angle closed-loop calculation. The feedforward compensation angular velocity is obtained by the target angular velocity feedforward compensation algorithm The target steering wheel angular velocity With feedforward compensation angular velocity Add them together and add them to the actual steering wheel angular velocity The absolute value of the subtraction is input into the PID controller to obtain the target output torque T b The nonlinear damping control torque T is obtained by using the nonlinear damping control algorithm. d , due to the damping control torque T d The direction and target output torque T b In the opposite direction, the target output torque T b and nonlinear damping control torque T d Superposition, the final output torque T aim .

[0111] The steering wheel angle closed-loop control performance optimization method of the embodiment of the present application is to start the nonlinear damping control algorithm when the target angle change rate meets the preset conditions. When the rotation speed of the motor rotor is greater than the preset speed threshold, the response overshoot and response angle fluctuation are reduced by superimposing the nonlinear damping torque, so that the steering wheel angle can quickly and smoothly track the target steering wheel angle command sent by the ADU during the following control. When the rotation speed of the motor rotor is less than or equal to the preset speed threshold, the nonlinear damping control torque is 0, the system damping is weak, and it can still respond to the target steering wheel angle at a relatively fast speed. After superimposing the nonlinear damping control algorithm, the steering wheel angle following process is both fast and stable, and the system has good dynamic performance.

[0112] It should be noted that although the steps of the method of the present disclosure are described in a specific order in the drawings, this does not require or imply that the steps must be performed in this specific order, or that all steps must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.

[0113] Corresponding to the above method embodiment, the present application embodiment also provides a steering wheel angle closed-loop control performance optimization device, see Figure 12 The steering wheel angle closed-loop control performance optimization device 1200 includes:

[0114] a target angular velocity determination module 1202 for obtaining a target steering wheel angle and an actual steering wheel angle in real time after the autonomous vehicle enters the autonomous driving mode, and inputting the difference between the target steering wheel angle and the actual steering wheel angle into a first PID controller to obtain a target steering wheel angular velocity;

[0115] The actual angular velocity determination module 1204 is configured to obtain the rotation angle and rotation direction of the motor rotor in real time and determine the actual angular velocity of the steering wheel based on the rotation angle and rotation direction of the motor rotor and the transmission ratio between the steering wheel and the motor;

[0116] a limited target steering angle change rate determination module 1206 for determining the target steering wheel angle change rate by differentiating the target steering wheel angle with respect to the signal period, and limiting the target steering wheel angle change rate using the speed of the autonomous vehicle to obtain the limited target steering wheel angle change rate;

[0117] A feedforward gain determination module 1208 is configured to determine a feedforward gain based on the absolute value of the difference between the target steering wheel angle and the actual steering wheel angle; wherein the feedforward gain is inversely correlated with the absolute value;

[0118] a feedforward compensation angular velocity determination module 1210 for determining a feedforward compensation angular velocity according to a limited steering wheel target angle change rate and a feedforward gain;

[0119] The target output torque determination module 1212 is configured to input the difference between the sum of the target steering wheel angular velocity and the feedforward compensation angular velocity and the actual steering wheel angular velocity into the second PID controller to obtain the target output torque.

[0120] Optionally, the steering wheel angle closed-loop control performance optimization device 1200 further includes:

[0121] A nonlinear damping control coefficient setting module is used to set the nonlinear damping control coefficient K1 to 1 when the steering wheel target angle change rate meets the preset conditions; and to set the nonlinear damping control coefficient K1 to 0 when the steering wheel target angle change rate does not meet the preset conditions;

[0122] a motor rotor rotation coefficient setting module, configured to set the motor rotor rotation coefficient Ms to 0 when the motor rotor rotation speed is less than or equal to a preset speed threshold; and to set the motor rotor rotation coefficient Ms according to the motor rotor rotation speed when the motor rotor rotation speed is greater than the preset speed threshold; wherein the motor rotor rotation coefficient Ms is positively correlated with the rotor rotation speed;

[0123] A vehicle speed coefficient setting module, used to set a vehicle speed coefficient Vs according to the speed of the autonomous driving vehicle, wherein the vehicle speed coefficient Vs is proportional to the vehicle speed;

[0124] A steering wheel hand torque coefficient setting module is used to obtain the deformation angle of the torque angle sensor, interpret the deformation angle as the steering wheel steering torque, and set the steering wheel hand torque coefficient Tp according to the steering wheel steering torque. The steering wheel hand torque coefficient Tp is proportional to the steering wheel steering torque.

[0125] a nonlinear damping control torque determination module, configured to multiply the nonlinear damping control coefficient K1, the motor rotor rotation coefficient Ms, the vehicle speed coefficient Vs, and the steering wheel hand torque coefficient Tp, and process the resulting product using the nonlinear damping gain Kg to obtain a nonlinear damping control torque, such that the nonlinear damping control torque is within a preset compensation torque range;

[0126] The final output torque determination module is used to superimpose the target output torque and the nonlinear damping control torque to obtain the final output torque.

[0127] Optionally, the limited target angle change rate determination module 1206 is used to differentiate the steering wheel target angle with respect to the signal period to determine the steering wheel target angle change rate, and determine the target angle change rate limit value based on the speed of the autonomous driving vehicle, wherein the target angle change rate limit value is inversely proportional to the vehicle speed; when the steering wheel target angle change rate is greater than the target angle change rate limit value, the steering wheel target angle change rate is set to the target angle change rate limit value to obtain the limited steering wheel target angle change rate; when the steering wheel target angle change rate is less than or equal to the target angle change rate limit value, no processing is performed.

[0128] Optionally, the feedforward compensation angular velocity determination module 1208 is specifically configured to multiply the limited steering wheel target angle change rate by the feedforward gain, and filter the obtained product to obtain the feedforward compensation angular velocity.

[0129] Optionally, the limited target angle change rate determination module 1206 is specifically used to determine the steering wheel target angle change rate by taking the derivative of the steering wheel target angle with respect to the signal period if the absolute value of the steering wheel target angle is less than or equal to a preset angle threshold, and the slope of the ramp input is greater than the preset slope threshold or the frequency of the sinusoidal input is greater than a preset frequency, and limit the steering wheel target angle change rate using the speed of the autonomous driving vehicle to obtain the limited steering wheel target angle change rate.

[0130] Optionally, the actual angular velocity determination module 1204 is specifically used to obtain the rotation angle and rotation direction of the motor rotor in real time, determine the rotation speed of the motor rotor based on the rotation angle and rotation direction of the motor rotor; and convert the rotation angular velocity of the motor rotor into the actual angular velocity of the steering wheel based on the transmission ratio relationship between the steering wheel and the motor.

[0131] Optionally, the steering wheel angle closed-loop control performance optimization device 1200 further includes:

[0132] The judgment module is used to determine that the steering wheel target angle change rate meets the preset conditions when the steering wheel target angle change rate is 0 and the duration is greater than or equal to the preset time threshold; when the steering wheel target angle change rate is not 0, or the steering wheel target angle change rate is 0 but the duration is less than the preset time threshold, determine that the steering wheel target angle change rate does not meet the preset conditions.

[0133] The specific details of each module or unit in the above device have been described in detail in the corresponding method, so they will not be repeated here.

[0134] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiment of the application, the features and functions of two or more modules or units described above can be concretized in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into multiple modules or units to be concretized.

[0135] An embodiment of the present application also provides an electronic device, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to execute the above-mentioned steering wheel angle closed-loop control performance optimization method in this example embodiment.

[0136] Reference Figure 13 , Figure 13 This is a structural diagram of an electronic device in an embodiment of the present application. The specific embodiment of the present application does not limit the specific implementation of the electronic device.

[0137] like Figure 13 As shown, the electronic device may include: a processor 1302 , a communication interface 1304 , a memory 1306 , and a communication bus 1308 .

[0138] The processor 1302 , the communication interface 1304 , and the memory 1306 communicate with each other via a communication bus 1308 .

[0139] The communication interface 1304 is used to communicate with other electronic devices or servers.

[0140] The processor 1302 is configured to execute the program 1310 , and specifically may execute the relevant steps in the above method embodiment.

[0141] Specifically, the program 1310 may include program codes, which include computer operation instructions.

[0142] Processor 1302 may be a central processing unit, a specific integrated circuit, or one or more integrated circuits configured to implement the embodiments of the present application. The one or more processors included in the smart device may be processors of the same type, such as one or more CPUs, or may be processors of different types, such as one or more CPUs and one or more ASICs.

[0143] The memory 1306 is used to store the program 1310. The memory 1306 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0144] The program 1310 can be specifically used to enable the processor 1302 to execute the steps in the above-mentioned embodiment of the steering wheel angle closed-loop control performance optimization method.

[0145] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and modules can refer to the corresponding process descriptions in the aforementioned method embodiments and will not be repeated here.

[0146] A computer-readable storage medium is also provided in an embodiment of the present application, on which a computer program is stored. When the computer program is executed by a processor, the above-mentioned steering wheel angle closed-loop control performance optimization method is implemented.

[0147] It should be noted that the computer-readable storage medium shown in this application can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination thereof. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, device or device. The program code contained on the computer-readable storage medium can be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, radio frequency, etc., or any suitable combination thereof.

[0148] In an embodiment of the present application, a computer program product is further provided. When the computer program product is run on a computer, the computer is caused to execute the above-mentioned steering wheel angle closed-loop control performance optimization method.

[0149] It should be noted that, in this document, relational terms such as "first" and "second" 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, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device comprising the element.

[0150] The foregoing description is intended only to provide specific embodiments of the present application, which will enable those skilled in the art to understand and implement the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments described herein, but is intended to be construed in the broadest manner consistent with the principles and novel features disclosed herein.

Claims

1. A method for optimizing the closed-loop control performance of steering wheel angle of an autonomous driving vehicle, characterized in that: include: After the autonomous driving vehicle enters the autonomous driving mode, obtaining a target steering wheel angle and an actual steering wheel angle in real time, and inputting a difference between the target steering wheel angle and the actual steering wheel angle into a first PID controller to obtain a target steering wheel angle velocity; Obtain the rotation angle and rotation direction of the motor rotor in real time, and determine the actual steering wheel angular speed based on the rotation angle and rotation direction of the motor rotor and the transmission ratio between the steering wheel and the motor; Derivative the target steering wheel angle with respect to the signal period to determine a steering wheel target angle change rate, and limit the steering wheel target angle change rate using the speed of the autonomous driving vehicle to obtain a limited steering wheel target angle change rate; determining a feedforward gain according to an absolute value of a difference between the target steering wheel angle and the actual steering wheel angle; wherein the feedforward gain is inversely correlated with the absolute value; determining a feedforward compensation angular velocity according to the limited steering wheel target angle change rate and the feedforward gain; The difference between the sum of the target steering wheel angular velocity and the feedforward compensation angular velocity and the actual steering wheel angular velocity is input into a second PID controller to obtain a target output torque.

2. The method according to claim 1, characterized in that The method further comprises: When the steering wheel target angle change rate meets the preset conditions, the nonlinear damping control coefficient K1 is set to 1; when the steering wheel target angle change rate does not meet the preset conditions, the nonlinear damping control coefficient K1 is set to 0; When the rotation speed of the motor rotor is less than or equal to a preset speed threshold, the motor rotor rotation coefficient Ms is set to 0; when the rotation speed of the motor rotor is greater than the preset speed threshold, the motor rotor rotation coefficient Ms is set according to the rotation speed of the motor rotor; wherein the motor rotor rotation coefficient Ms is positively correlated with the rotation speed of the rotor; Setting a vehicle speed coefficient Vs according to the speed of the autonomous vehicle, wherein the vehicle speed coefficient Vs is proportional to the vehicle speed; Obtaining a deformation angle of the torque angle sensor, resolving the deformation angle into a steering wheel steering torque, and setting a steering wheel hand torque coefficient Tp according to the steering wheel steering torque, wherein the steering wheel hand torque coefficient Tp is proportional to the steering wheel steering torque; Multiplying the nonlinear damping control coefficient K1, the motor rotor rotation coefficient Ms, the vehicle speed coefficient Vs, and the steering wheel hand torque coefficient Tp, and processing the obtained product using the nonlinear damping gain Kg to obtain a nonlinear damping control torque, so that the nonlinear damping control torque is within a preset compensation torque range; The target output torque is superimposed on the nonlinear damping control torque to obtain a final output torque.

3. The method according to claim 1, characterized in that The method of limiting the steering wheel target angle change rate by using the speed of the autonomous driving vehicle includes: Determining a target turning angle change rate limit value based on the speed of the autonomous driving vehicle, wherein the target turning angle change rate limit value is inversely proportional to the vehicle speed; When the steering wheel target angle change rate is greater than the target angle change rate limit value, setting the steering wheel target angle change rate to the target angle change rate limit value; When the steering wheel target angle change rate is less than or equal to the target angle change rate limit value, no processing is performed.

4. The method according to claim 1, wherein The step of determining a feedforward compensation angular velocity according to the limited steering wheel target angle change rate and the feedforward gain includes: The feedforward compensation angular velocity is obtained by multiplying the limited steering wheel target angle change rate and the feedforward gain, and filtering the obtained product.

5. The method according to claim 1, wherein Derivative of the target steering wheel angle with respect to the signal period to determine the steering wheel target angle change rate includes: If the absolute value of the target steering wheel angle is less than or equal to a preset angle threshold, and the slope of the ramp input is greater than the preset slope threshold or the frequency of the sinusoidal input is greater than a preset frequency, the target steering wheel angle is differentiated with respect to the signal period to determine the rate of change of the target steering wheel angle.

6. The method according to claim 1, characterized in that The method of determining the actual angular velocity of the steering wheel according to the rotation angle and rotation direction of the motor rotor and the transmission ratio relationship between the steering wheel and the motor includes: Determine the rotation speed of the motor rotor according to the rotation angle and rotation direction of the motor rotor; According to the transmission ratio relationship between the steering wheel and the motor, the rotational angular velocity of the motor rotor is converted into the actual angular velocity of the steering wheel.

7. The method according to claim 2, characterized in that The method for determining whether the steering wheel target angle change rate meets the preset conditions is: When the steering wheel target angle change rate is 0 and the duration is greater than or equal to a preset time threshold, it is determined that the steering wheel target angle change rate meets the preset condition; When the steering wheel target angle change rate is not 0, or the steering wheel target angle change rate is 0 but lasts for less than a preset time threshold, it is determined that the steering wheel target angle change rate does not meet the preset condition.

8. A device for optimizing the closed-loop control performance of steering wheel angle of an autonomous vehicle, characterized in that: include: a target angular velocity determination module, configured to obtain a target steering wheel angle and an actual steering wheel angle in real time after the autonomous vehicle enters the autonomous driving mode, and input a difference between the target steering wheel angle and the actual steering wheel angle into a first PID controller to obtain a target steering wheel angular velocity; The actual angular speed determination module is used to obtain the rotation angle and rotation direction of the motor rotor in real time, and determine the actual angular speed of the steering wheel based on the rotation angle and rotation direction of the motor rotor and the transmission ratio between the steering wheel and the motor; a module for determining a limited target steering angle change rate, configured to determine a steering wheel target angle change rate by differentiating the steering wheel target angle with respect to the signal period, and to limit the steering wheel target angle change rate using the speed of the autonomous vehicle to obtain a limited steering wheel target angle change rate; a feedforward gain determination module, configured to determine a feedforward gain according to an absolute value of a difference between the target steering wheel angle and the actual steering wheel angle; wherein the feedforward gain is inversely correlated with the absolute value; a feedforward compensation angular velocity determination module, configured to determine a feedforward compensation angular velocity according to the limited steering wheel target angle change rate and the feedforward gain; The target output torque determination module is configured to input the difference between the sum of the target steering wheel angular velocity and the feedforward compensation angular velocity and the actual steering wheel angular velocity into a second PID controller to obtain a target output torque.

9. An electronic device, characterized in that: include: A processor, wherein the processor is configured to execute a computer program stored in a memory, wherein the computer program, when executed by the processor, implements the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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