Clutch control method and system, vehicle and medium

Abstract

The invention provides a clutch control method and system, a vehicle and a medium, and belongs to the technical field of vehicle transmission control, and the method comprises the steps that a position deviation value sequence of a clutch is obtained, and the position deviation value sequence comprises a plurality of position deviation values; the position deviation value is equal to the difference value between the target position and the actual position of the clutch; pID control parameters are determined according to the working state of the clutch; performing filtering processing on the position deviation value sequence based on a least square method to obtain a filtering differential term coefficient; obtaining a variable speed integral item coefficient according to the position deviation value sequence, the variable speed integral threshold range and the integral item coefficient; generating a control signal according to a proportional term coefficient, the filtering differential term coefficient and the variable speed integral term coefficient; and the control signal is output to a clutch executing mechanism, and closed-loop control over the position of the clutch is achieved. According to the method, overshoot is remarkably reduced, and the robustness of clutch control is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle transmission control, and particularly relates to a clutch control method and system, a vehicle and a medium. BACKGROUND

[0002] AMT (Automated Manual Transmission) is gradually replacing the traditional MT (Manual Transmission) in the commercial vehicle field due to its low cost, simple structure, and easy maintenance. One of the core functions of the AMT system is to automatically control the engagement and disengagement of the clutch through the control system to replace the driver's operation of the clutch pedal. The performance of clutch control directly determines the starting and shifting quality of the vehicle and directly affects the service life of the key components of the transmission system. Therefore, achieving fast, smooth and accurate control of the clutch is a key challenge in the development of the AMT control system.

[0003] Currently, the classic PID (Proportion-Integral-Derivative) control algorithm is widely used in the industry to perform closed-loop control on the clutch position. This algorithm quickly responds to the position deviation through the proportion term (P), eliminates the steady-state error through the integral term (I), and suppresses oscillation and overshoot through the derivative term (D). In actual applications, engineers usually rely on a large number of bench tests and vehicle tests to repeatedly adjust and calibrate the three parameters (proportion gain Kp, integral gain Ki, and derivative gain Kd) of the PID controller in order to enable the actual displacement of the clutch to quickly and smoothly track the target displacement without obvious overshoot, oscillation or steady-state error.

[0004] However, this traditional PID control method has obvious limitations. First, its control performance is heavily dependent on a set of carefully calibrated, fixed PID parameters. When the clutch actuator (such as a pneumatic cylinder, solenoid valve, etc.) is replaced during project development, for example, due to product upgrades or configuration changes, its hardware characteristics (such as response delay, friction resistance) will change. At this time, the original PID parameters calibrated for the old hardware are often no longer applicable, resulting in a significant decline in the performance of the control system, with problems such as slow response, excessive overshoot, or continuous oscillation. Even if manual calibration is re-performed, it is highly dependent on the experience of engineers, and the parameters are mutually coupled, resulting in a long debugging period, high cost, and difficulty in achieving ideal control effects. Second, the traditional PID algorithm itself has inherent defects. The derivative element (D) is extremely sensitive to high-frequency noise in the sensor signal, and the noise will be amplified by the derivative element, thereby interfering with the stability of the control output and even causing high-frequency oscillation of the actuator. On the other hand, the integral element (I) will continuously accumulate errors when there is a large steady-state deviation in the system (for example, due to hardware wear or resistance changes), which can easily cause "integral saturation" and result in increased overshoot and slow response of the control system, and even system instability. To solve the above problems, the industry has made some improvement attempts, such as introducing a simple low-pass filter to preprocess the derivative signal. However, the filter with a fixed cutoff frequency, while effectively filtering noise, also introduces phase lag, which weakens the "prediction" function of the derivative element and affects the dynamic response performance of the system. For the integral saturation problem, conventional integral separation or anti-saturation measures are often simple in strategy and difficult to achieve the best balance between precision and stability under dynamic working conditions. SUMMARY

[0005] Therefore, it is necessary to provide a clutch control method, system, vehicle and medium to solve the technical problems of poor noise resistance of the derivative element and easy saturation of the integral element in the prior art.

[0006] To solve the above technical problems, in a first aspect, the present application provides a clutch control method, comprising: obtaining a position deviation value sequence of a clutch, the position deviation value sequence comprising a plurality of position deviation values, the position deviation value being equal to the difference between the target position and the actual position of the clutch; determining PID control parameters according to the working state of the clutch; filtering the position deviation value sequence based on the least squares method to obtain a filtered derivative term coefficient; obtaining a variable integral term coefficient according to the position deviation value sequence, a variable integral threshold range and an integral term coefficient; generating a control signal according to a proportional term coefficient, the filtered derivative term coefficient and the variable integral term coefficient; Output the control signal to a clutch actuator to realize closed-loop control on the position of the clutch.

[0007] In a possible implementation, the PID control parameter is determined according to the working state of the clutch, including: identifying the working state of the clutch; when the working state is that the clutch is in the disengaged state, determining the PID control parameter as a first coefficient; when the working state is that the clutch is in the engaged state, determining the PID control parameter as a second coefficient; the first coefficient is greater than the second coefficient.

[0008] In a possible implementation, the filtered differential term coefficient is obtained by filtering the position deviation value sequence based on a least square method, including: in a discrete time domain, taking the position deviation values of the last N sampling periods to form an observation sequence; N is a positive integer greater than 1; generating a fitting straight line for the observation sequence by the least square method, and determining the slope of the fitting straight line as a deviation change rate; performing product calculation on the deviation change rate, a differential value of the position deviation value sequence, and the differential term coefficient to obtain the filtered differential term coefficient.

[0009] In a possible implementation, the variable-speed integral term coefficient is obtained according to the position deviation value sequence, a variable-speed integral threshold range, and an integral term coefficient, including: determining the variable-speed integral threshold range; determining an integral coefficient adjustment factor according to the variable-speed integral threshold range and the position deviation value; performing product calculation on the integral coefficient adjustment factor and the integral term coefficient to obtain a dynamic integral parameter; performing product calculation on the dynamic integral parameter, an integral value of the position deviation value sequence, and the integral term coefficient to obtain the variable-speed integral term coefficient.

[0010] In a possible implementation, the integral coefficient adjustment factor is determined according to the variable-speed integral threshold range and the position deviation value, including: comparing the size between the variable-speed integral threshold range and the absolute value of the position deviation value; the variable-speed integral threshold range includes an upper limit value and a lower limit value; when the absolute value of the position deviation value is less than or equal to the lower limit value, determining that the integral coefficient adjustment factor is equal to 1; when the absolute value of the position deviation value is greater than the lower limit value and less than or equal to the upper limit value, determining that the integral coefficient adjustment factor is equal to a ratio; the ratio is equal to a first difference value divided by a second difference value, the first difference value is equal to a difference between the upper limit value and the absolute value of the position deviation value, and the second difference value is equal to a difference between the upper limit value and the lower limit value; when the absolute value of the position deviation value is greater than the upper limit value, determining that the integral coefficient adjustment factor is equal to 0.

[0011] In a possible implementation, the method further includes: when the clutch is in the disengaged state, determining that the variable-speed integral threshold range is a first integral threshold range; when the working state is that the clutch is in the engaged state, determining that the variable-speed integral threshold range is a second integral threshold range; wherein the lower limit value of the second integral threshold range is greater than the lower limit value of the first integral threshold, and the upper limit value of the second integral threshold range is greater than the upper limit value of the first integral threshold.

[0012] In a possible implementation, the generating the control signal according to the proportional term coefficient, the filtered differential term coefficient and the variable-speed integral term coefficient includes: calculating a proportional term PID control parameter according to a product of the position deviation value and the proportional term coefficient; adding the proportional term PID control parameter, the filtered differential term coefficient and the variable-speed integral term coefficient to obtain the control signal.

[0013] In a second aspect, the present application also provides a clutch control system, including: an acquisition module, configured to acquire a position deviation value sequence of a clutch, the position deviation value sequence including a plurality of position deviation values, the position deviation value being equal to a difference between a target position and an actual position of the clutch; a parameter setting module, configured to determine a PID control parameter according to a working state of the clutch; a least square filtering module, configured to perform filtering processing on the position deviation value sequence based on a least square method to obtain a filtered differential term coefficient; a variable-speed integral module, configured to obtain a variable-speed integral term coefficient according to the position deviation value sequence, a variable-speed integral threshold range and an integral term coefficient; a signal synthesis module, configured to generate a control signal according to a proportional term coefficient, the filtered differential term coefficient and the variable-speed integral term coefficient; an execution driving module, configured to output the control signal to a clutch execution mechanism to realize closed-loop control on the position of the clutch.

[0014] In a third aspect, the present application also provides an intelligent vehicle, comprising a memory and a processor, wherein, The memory is configured to store a program. The processor is coupled to the memory and configured to execute the program stored in the memory to implement the steps of the clutch control method in any of the implementation manners described above.

[0015] In a fourth aspect, the present application also provides a computer-readable storage medium for storing computer-readable programs or instructions, which can implement the steps of the clutch control method in any of the implementation manners described above when executed by a processor.

[0016] The clutch control method provided by the present application can more accurately reflect the difference between the actual position and the target position of the clutch by first obtaining the position deviation value sequence of the clutch and performing accurate calculation, thereby generating a more accurate control signal and improving the accuracy of clutch position control. Further, filtering the position deviation value sequence based on the least square method can effectively filter out high-frequency noise, reduce the influence of external interference on the control signal, and improve the stability and reliability of the system. Further, by using the variable integral method and dynamically adjusting the integral term coefficient according to the size of the position deviation value to obtain a variable integral term coefficient, the overshoot or integral saturation problem caused by rapid accumulation of the integral term at large deviation is avoided, and the response speed and stability of the system are improved. Further, different PID control parameters are determined according to the working state (engaged or separated) of the clutch, which can better adapt to the control requirements of the clutch in different working states and improve the control effect. Further, the control signal is output to the clutch actuator to form a closed-loop control system, which can real-time feedback the actual position information of the clutch, timely adjust the control signal, and realize accurate control of the clutch position, thereby improving the control performance and service life of the clutch. On the basis of the original PID control system, the smoothness of the differential signal and the integral intensity are dynamically adjusted, which significantly reduces the overshoot, suppresses the oscillation, and improves the robustness of the clutch control. BRIEF DESCRIPTION OF DRAWINGS In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0017] Figure 1 An embodiment flowchart of the clutch control method provided by the present application is shown in the figure. Figure 2 The present application Figure 1An embodiment flowchart of S200 in the present application; Figure 3 An embodiment flowchart of S300 in the present application; Figure 1 An embodiment flowchart of S300 in the present application; Figure 4 An embodiment flowchart of S400 in the present application; Figure 1 An embodiment flowchart of S400 in the present application; Figure 5 An embodiment flowchart of S420 in the present application; Figure 4 An embodiment flowchart of S420 in the present application; Figure 6 An embodiment framework diagram of the clutch control according to the least square method and variable speed integral method provided by the present application; Figure 7 An embodiment structure diagram of the clutch control system provided by the present application; Figure 8 An embodiment structure diagram of the intelligent vehicle provided by the present application. DETAILED DESCRIPTION

[0018] The technical solutions in the embodiments of the present application will be clearly and completely described in connection with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0019] In the description of the embodiments of the present application, unless otherwise specified, the meaning of "a plurality of" is two or more. The association relationship of the associated objects is described by "and / or", which means that there can be three relationships, for example: A and / or B, which can represent the three cases of A alone, A and B together, and B alone.

[0020] The "first", "second", and the like described in the embodiments of the present application are only for the purpose of description, and cannot be understood as indicating or implying the relative importance of the indicated technical features or implicitly indicating the number of the indicated technical features. Therefore, the technical features limited by "first" and "second" can explicitly or implicitly include at least one of the features.

[0021] In this document, the reference to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily all refer to the same embodiment, nor is it necessarily mutually exclusive or alternative to other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0022] Before demonstrating the embodiments, the following terms will be explained.

[0023] PID (Proportional-Integral-Derivative): A PID controller is a feedback controller widely used in industrial automation and control systems. It is used to regulate the system output to make it close to or equal to the desired setpoint. The PID controller combines proportional, integral, and derivative control methods to adjust the system error, thereby achieving precise control. The mathematical expression for the PID control signal u(t) is: ; Where Kp is the proportional term coefficient, Ki is the integral term coefficient, and Kd is the differential term coefficient.

[0024] The actual position y of the current clutch is obtained from the displacement sensor. current The target position y of the clutch is calculated based on the driving intention and vehicle status. target (i.e., the expected value), calculate the position deviation value as the input parameter for subsequent PID control, as shown in the following formula: e=y target -y current .

[0025] Among them, y target For the actual position of the clutch, y target The target position for the clutch is set. The proportional coefficient K is preset accordingly. p Integral coefficient K i Differential coefficient K d These coefficients are filled with preset values ​​early in the algorithm model development. Based on the positional deviation value and the proportional coefficient K... p The product of the positional deviation sequence, the integral sum of the integral term coefficients K i The product of the product, the differential value of the positional deviation sequence and the coefficient of the differential term K d The product of these three factors, and their sum, constitute the output of the PID algorithm, which is the PID control signal. This PID control signal corresponds to the clutch solenoid valve. The clutch solenoid valve controls the opening time within a time interval by adjusting the duty cycle, thereby controlling the airflow supplied to the clutch piston and ultimately regulating the rate at which the clutch opens or locks.

[0026] The algorithm model is written into a transmission control unit as a sub-module. During later real vehicle or bench testing, the proportional term coefficient P, the integral term coefficient I and the differential term coefficient D are adjusted and modified through calibration testing, so that the final result meets the performance requirements. However, when a new clutch actuator is matched with the transmission during project development, the original control system performs poorly, and even after modification and calibration, the ideal state cannot be achieved. At this time, the debugging time is long, and the effect is not good.

[0027] To solve the above problems, the present application provides a clutch control method, system, vehicle and medium, which are described below respectively.

[0028] Figure 1 An embodiment flowchart of the clutch control method provided by the present application is shown in Figure 1 The clutch control method comprises the following steps. S100, acquiring a position deviation value sequence of a clutch, the position deviation value sequence comprising a plurality of position deviation values, the position deviation value being equal to the difference between a target position and an actual position of the clutch.

[0029] It should be noted that the actual position value (y_current) of the clutch is acquired in real time by a displacement sensor, and the target position value (y_target) of the clutch is calculated according to the driving intention and the vehicle state. Then the difference between the target position and the actual position, i.e. the position deviation value (e = y_target - y_current), is calculated. The position deviation values at a plurality of continuous sampling time points are arranged in time sequence to form the position deviation value sequence. For example, assuming that the target position is 10 mm and the actual position is 8 mm at a certain time point, the position deviation value at this time point is 2 mm. Ten position deviation values are obtained by continuous sampling for 10 times at a fixed time interval (such as 0.005 s), and are arranged in sequence to form the position deviation value sequence {e1, e2, …, e10}.

[0030] S200, determining PID control parameters according to the working state of the clutch.

[0031] It should be noted that: the working state of the clutch mainly includes engagement and disengagement. For different working states, different PID control parameters (proportional term coefficient Kp, integral term coefficient Ki and differential term coefficient Kd) are preset. Generally, the disengagement PID coefficient is greater than the engagement PID coefficient, and the disengagement PID coefficient and the engagement PID coefficient are both related to the resistance, that is, the greater the exhaust resistance, the greater the disengagement PID coefficient, and the greater the intake resistance, the greater the engagement PID coefficient. In the actual control process, the current state of the clutch is determined by the program, and the corresponding control parameters are determined. When the clutch is in the engagement state, the preset control parameters are Kp_eng, Ki_eng and Kd_eng; when the clutch is in the disengagement state, the preset control parameters are Kp_sep, Ki_sep and Kd_sep. If it is detected that the clutch is currently in the engagement state, Kp_eng, Ki_eng and Kd_eng are selected as the control parameters.

[0032] S300, filtering the position deviation value sequence based on the least square method to obtain a filtered differential term coefficient.

[0033] It should be noted that: at the discrete time point k, the position deviation values of the last N sampling points are taken to obtain the position deviation value sequence {e_k-N+1, e_k-N+2,..., e_k}, and the position deviation value sequence is fitted and filtered based on the least square method to obtain the filtered differential term coefficient.

[0034] S400, obtaining a gear shift integral term coefficient according to the position deviation value sequence, a gear shift integral threshold range and an integral term coefficient.

[0035] It should be noted that: the gear shift integral threshold range is preset, and the gear shift integral threshold range includes an upper limit value and a lower limit value. For each position deviation value e in the position deviation value sequence, the absolute value of the position deviation value e is compared with the size of the gear shift integral threshold range, and the gear shift integral term coefficient is determined according to the comparison result and the integral term coefficient .

[0036] S500, generating a control signal according to the proportional term coefficient, the filtered differential term coefficient and the gear shift integral term coefficient; S600, outputting the control signal to the clutch actuator to realize closed-loop control of the position of the clutch.

[0037] It should be noted that: according to the PID control algorithm formula, the control signal is obtained according to the proportional term coefficient, the filter differential term coefficient and the variable speed integral term coefficient. The generated control signal u(t) is output to the clutch actuator (such as clutch solenoid valve), the duty cycle of the solenoid valve is controlled, and then the air flow provided to the clutch piston is controlled, and finally the opening or locking rate of the clutch is adjusted, realizing closed-loop control of the clutch position.

[0038] In summary, the clutch control method provided by the embodiment of the application can more accurately reflect the difference between the actual position and the target position of the clutch by obtaining the position deviation value sequence of the clutch and performing accurate calculation, thereby generating more accurate control signals and improving the accuracy of clutch position control. Further, the position deviation value sequence is filtered based on the least square method, which can effectively filter out high-frequency noise and reduce the influence of external interference on the control signal, thereby improving the stability and reliability of the system. Further, the variable speed integral method is used, and the variable speed integral term coefficient is obtained by dynamically adjusting the integral term coefficient according to the size of the position deviation value, thereby avoiding the problems of overshoot or integral saturation caused by rapid accumulation of the integral term at large deviation, and improving the response speed and stability of the system. Further, different PID control parameters are determined according to the working state (engagement or separation) of the clutch, which can better adapt to the control requirements of the clutch under different working states and improve the control effect. Further, the control signal is output to the clutch actuator to form a closed-loop control system, which can real-time feedback the actual position information of the clutch, timely adjust the control signal, realize accurate control of the clutch position, and improve the control performance and service life of the clutch. On the basis of the original PID control system, the smoothness of the differential signal and the integral intensity are dynamically adjusted, which significantly reduces the overshoot, suppresses the oscillation, and improves the robustness of the clutch control.

[0039] In some embodiments of the application, as shown in Figure 2 Step S200 includes: S210, identifying the working state of the clutch.

[0040] It should be noted that: the current position or speed information of the clutch can be obtained through sensors (such as position sensors, speed sensors), and the working state of the clutch is identified according to the clutch position. If the clutch position is less than a certain threshold (for example, near the completely separated position), it is determined to be in a separated state; if the clutch position is greater than a certain threshold (for example, near the completely engaged position), it is determined to be in an engaged state. Or according to the difference between the engine speed and the transmission input shaft speed to identify the working state of the clutch, if the speed difference is greater than the threshold (the clutch plate is separated, and the difference between the engine speed and the transmission input shaft speed is large), it is considered that the clutch is in a separated state; if the speed difference is less than the threshold (the clutch plate is pressed, and the engine speed and the transmission speed are basically synchronous), it is considered that the clutch is in an engaged state. The working state of the clutch can also be comprehensively judged and identified in combination with the vehicle state (such as vehicle speed, accelerator pedal position, brake pedal position, etc.). The working state of the clutch can also be inferred by the state flag of the control command sent by the TCU (Transmission Control Unit, transmission control unit), for example, isSeparating = true indicates that the clutch is in a separated state, and isSeparating = false indicates that the clutch is in an engaged state.

[0041] S220, when the working state is that the clutch is in a separated state, determining that the PID control parameter is a first coefficient.

[0042] It should be noted that: two groups of PID control parameters are preset, one group is used for the clutch in a separated state (first coefficient), and the other group is used for the clutch in an engaged state (second coefficient). The value of the first coefficient is greater than the second coefficient to adapt to the control requirements in the separated state. When the controller determines that the clutch is in a separated state (isSeparating = true), the first coefficient is selected as the PID control parameter. The first coefficient includes a proportional term coefficient Kp_sep, an integral term coefficient Ki_sep and a differential term coefficient Kd_sep.

[0043] S230, when the working state is that the clutch is in an engaged state, determining that the PID control parameter is a second coefficient; the first coefficient is greater than the second coefficient.

[0044] It should be noted that: when the controller judges that the clutch is in the engaged state (isSeparating = false), the second preset coefficient is selected as the PID control parameter. The second coefficient includes the proportional term coefficient Kp_eng, the integral term coefficient Ki_eng and the differential term coefficient Kd_eng. Ensure that the first coefficient is greater than the second coefficient to adapt to the control requirements in the separation state. For example, the PID coefficient in the separation state needs stronger control strength to overcome the exhaust resistance, and the PID coefficient in the engaged state needs milder control strength to avoid excessive impact. For example, the first preset coefficient is: Kp_sep=2.0, Ki_sep=0.5, Kd_sep=0.3. When the controller judges that the clutch is in the separation state, these parameters are selected as the PID control parameter. The second preset coefficient is: Kp_eng=1.5, Ki_eng=0.3, Kd_eng=0.2. When the controller judges that the clutch is in the engaged state, these parameters are selected as the PID control parameter. Among them, compare the two groups of parameters: Kp_sep>Kp_eng, Ki_sep>Ki_eng, Kd_sep>Kd_eng.

[0045] In this embodiment, when the clutch is separated, larger PID control parameters (first coefficients) are used, which can more effectively overcome the exhaust resistance, ensure that the clutch can be quickly and accurately separated, reduce the separation time, improve the shifting efficiency, reduce the shifting delay, and improve the driving performance. When the clutch is engaged, smaller PID control parameters (second coefficients) are used, which can avoid excessive impact and wear caused by excessive control strength, ensure smooth engagement of the clutch, and improve driving comfort. Further, by dynamically selecting the PID control parameters according to the working state of the clutch, different working conditions can be better adapted to, the flexibility and adaptability of the control system are improved, and in the separation and engagement processes, the optimized PID parameters are used respectively, the position of the clutch can be more accurately controlled, the position deviation is reduced, and the control precision is improved. Further, by optimizing the PID control parameters, the impact and wear of the clutch during engagement and separation are reduced, the service life of the clutch is prolonged, the stability and reliability of the control system are improved, clutch failures caused by improper control are reduced, and the overall reliability of the vehicle is improved.

[0046] Due to the decline in the adaptability of the PID parameters caused by the change of the hardware parameters, in order to solve the above problems, in some embodiments of the present application, as shown in Figure 3 The step S300 includes: S310, in the discrete time domain, the position deviation values of the last N sampling periods are taken to form an observation sequence; N is a positive integer greater than 1.

[0047] It should be noted that a fixed sampling period (such as 0.005 seconds) is set, and the position deviation value of the clutch is continuously collected according to the period. In the discrete time domain k , the position deviation values of the last N sampling periods are selected to form an observation sequence, and the observation sequence can be represented as {ek −N+1 , ek −N+2 ,..., ek}. For example, if N = 10, the observation sequence will include the position deviation values of the last 10 sampling periods.

[0048] S320, a fitting straight line is generated for the observation sequence by the least square method, and the slope of the fitting straight line is determined as the deviation change rate.

[0049] It should be noted that the data points in the observation sequence can be fitted by a straight line, and the last N sampling points {ek −N+1 , ek −N+2 ,..., ek} are fitted.

[0050] Assume that the signal in the window can be represented as: ; Where, is the slope (corresponding to the differential term), and b is the intercept (corresponding to the base value). The above is the fitting straight line, which means that the straight line that best fits the N sampling points at the discrete time point k is the straight line that satisfies the minimum sum of squares of the residual between the expected value and each observation value, as follows:

[0051] Where, is the observation value, is the model expected value.

[0052] That is, the slope and the intercept b are solved by the least square method, so that the sum of squares of the residual between the fitting straight line and the observation data points is minimized. The specific steps are as follows: Construct the coefficient matrix A and the observation vector y: , ; Solve the matrix: ; Finally, the slope is calculated. The slope is the differential of e filtered to remove noise in the sampling range (discrete time domain), and the calculated slope is determined as the deviation change rate.

[0053] S330, the filter differential term coefficient is calculated by multiplying the deviation change rate, the differential value of the position deviation value sequence, and the differential term coefficient.

[0054] It should be noted that the differential value of the position deviation value sequence can be approximated as the difference between adjacent position deviation values divided by the sampling period. The rate of change of the deviation , the differential value of the position deviation value sequence, and the differential term coefficient K d The product calculation is performed to obtain the filtered differential term coefficient.

[0055] In this embodiment, fitting the position deviation value sequence by the least squares method can effectively filter out high-frequency noise, reduce the influence of external interference on the differential term, and improve the stability and reliability of the system. The slope (rate of change of deviation) obtained by the least squares fitting can provide a smoother differential signal, avoid the sharp fluctuations of the differential term caused by noise, and improve the control accuracy. Further, the rate of change of deviation is determined by fitting the slope of the straight line, which can more accurately reflect the trend of the position deviation value, thereby generating a more accurate filtered differential term coefficient. The filtered differential term coefficient is dynamically calculated according to the actual position deviation value sequence, which can better adapt to different working conditions, improve the flexibility and adaptability of the control system, effectively suppress the overshoot and oscillation of the system, and improve the response speed and stability of the system.

[0056] As the adaptability of the hardware parameter change decreases, steady-state error is likely to occur, at which time the deviation value e is large. Since the steady-state error is difficult to eliminate, the integral term is continuously accumulated, which eventually leads to overshoot. To solve the above problem, in some embodiments of the present application, as shown in Figure 4 , step S400 includes: S410, determining the variable-speed integral threshold range; S420, determining an integral coefficient adjustment factor according to the variable-speed integral threshold range and the position deviation value.

[0057] It should be noted that two sets of variable-speed integral threshold ranges are preset in the controller, which are a first integral threshold range (used for the disengaged state) and a second integral threshold range (used for the engaged state). The specific values are set according to actual application requirements and system characteristics. For each position deviation value e, its absolute value |e| is calculated. The size of the variable-speed integral threshold range and the absolute value of the position deviation value is compared, and the integral coefficient adjustment factor is determined according to the comparison result.

[0058] S430, performing product calculation according to the integral coefficient adjustment factor and the integral term coefficient to obtain a dynamic integral parameter.

[0059] It should be noted that the integral term coefficient is preset in the controller, and the dynamic integral parameter is obtained by multiplying the integral term coefficient and the integral coefficient adjustment factor, wherein the calculation formula of the dynamic integral parameter is as follows: ; wherein K i is an integral term coefficient, is an integral coefficient adjustment factor, is the position deviation value, is a dynamic integral parameter.

[0060] S440, multiplying the dynamic integral parameter, the integral value of the sequence of position deviation values, and the integral term coefficient to obtain the variable-speed integral term coefficient.

[0061] It should be noted that the integral value is obtained by integrating the sequence of position deviation values, and the variable-speed integral term coefficient is obtained by multiplying the integral term coefficient, the dynamic integral parameter, and the integral value of the sequence of position deviation values.

[0062] In this embodiment, variable-speed integral method is introduced in the integral term to avoid rapid accumulation of the integral term at large deviation, causing overshoot or integral saturation. When the clutch is separated, a smaller threshold range can be used to respond to small deviation more sensitively, quickly adjust the control signal, and ensure that the clutch can be quickly and accurately separated. When the clutch is engaged, a larger threshold range can be used to respond to large deviation more smoothly, avoid overshoot and oscillation caused by rapid accumulation of the integral term, and ensure smooth engagement of the clutch. Further, dynamically selecting the variable-speed integral threshold range according to the working state of the clutch can better adapt to different working conditions and improve the flexibility and adaptability of the control system. By optimizing the threshold range, the position of the clutch can be more accurately controlled, the position deviation can be reduced, and the control precision can be improved.

[0063] In some embodiments of the present application, as shown in Figure 5 step S420 includes: S421, comparing the size between the variable-speed integral threshold range and the absolute value of the position deviation value; the variable-speed integral threshold range includes an upper limit value and a lower limit value.

[0064] It should be noted that the variable-speed integral threshold range is preset in the controller, including an upper limit value e2 and a lower limit value e1. These threshold values are set according to actual application requirements and system characteristics. For each position deviation value e, the absolute value |e| is calculated. The absolute value |e| of the position deviation value is compared with the preset upper limit value e2 and lower limit value e1 to determine its interval.

[0065] S422, when the absolute value of the position deviation value is less than or equal to the lower limit value, determining that the integral coefficient adjustment factor is equal to 1.

[0066] S423、when the absolute value of the position deviation value is greater than the lower limit value and less than or equal to the upper limit value, determining that the integral coefficient adjustment factor is equal to a ratio; the ratio is equal to a first difference value divided by a second difference value, the first difference value is equal to a difference between the upper limit value and the absolute value of the position deviation value, and the second difference value is equal to a difference between the upper limit value and the lower limit value.

[0067] S424、when the absolute value of the position deviation value is greater than the upper limit value, determining that the integral coefficient adjustment factor is equal to 0.

[0068] It should be noted that: if the absolute value of the position deviation value |e| is less than or equal to the lower limit value e1, the integral coefficient adjustment factor is equal to 1, and the integral coefficient adjustment factor is set to 1. If the absolute value of the position deviation value |e| is greater than the lower limit value e1 and less than or equal to the upper limit value e2, the integral coefficient adjustment factor is calculated as a ratio. If the absolute value of the position deviation value |e| is greater than the upper limit value e2, the integral coefficient adjustment factor is equal to 0. That is, the integral coefficient adjustment factor satisfies the following equation:

[0069] In this embodiment, when the absolute value of the position deviation value is less than or equal to the lower limit value e1, the integral coefficient adjustment factor =1, the contribution of the integral term to the control signal is the largest, which can quickly respond to small deviations and help to quickly reduce the deviation. When the absolute value of the position deviation value is greater than the upper limit value e2, the integral coefficient adjustment factor =0, the contribution of the integral term to the control signal is zero, which effectively prevents integral saturation and avoids overshoot and instability caused by the integral term being too large. When the absolute value of the position deviation value is between e1 and e2 (i.e., the absolute value of the position deviation value |e| is greater than the lower limit value e1 and less than or equal to the upper limit value e2), the integral coefficient adjustment factor is adjusted in a linear proportion, achieving a smooth transition from fast integration to integral suppression, avoiding sudden changes in the control signal, and improving the stability of the system. Further, the variable-speed integration method is used to dynamically adjust the integral coefficient according to the size of the position deviation value, which can better adapt to different working conditions, improve the flexibility and adaptability of the control system, and effectively reduce the overshoot of the system, improve the stability and response speed of the system. Further, by dynamically adjusting the integral coefficient, the position of the clutch can be more accurately controlled, the position deviation can be reduced, the control precision can be improved, and the robustness of the system is improved, so that the system can still maintain good control performance when facing different working conditions and disturbances.

[0070] In some embodiments of the application, the method further comprises: when the clutch is in the disengaging state, determining that the variable-integration threshold range is a first integration threshold range; when the working state is that the clutch is in the engaging state, determining that the variable-integration threshold range is a second integration threshold range; wherein a lower limit value of the second integration threshold range is greater than a lower limit value of the first integration threshold, and an upper limit value of the second integration threshold range is greater than an upper limit value of the first integration threshold.

[0071] It should be noted that: in the controller, two sets of variable-integration threshold ranges are pre-set, which are a first integration threshold range (used for the disengaging state) and a second integration threshold range (used for the engaging state). The first integration threshold range includes a lower limit value e1_sep and an upper limit value e2_sep, and if the clutch is in the disengaging state (isSeparating = true), the first integration threshold range is selected as the current variable-integration threshold range. The second integration threshold range includes a lower limit value e1_eng and an upper limit value e2_eng, and e1_eng>e1_sep and e2_eng>e2_sep, and if the clutch is in the engaging state (isSeparating = false), the second integration threshold range is selected as the current variable-integration threshold range.

[0072] In this embodiment, when the clutch is disengaging, a smaller threshold range (the first integration threshold range) is used, which can more sensitively respond to small deviations, quickly adjust the control signal, and ensure that the clutch can quickly and accurately disengage. When the clutch is engaged, a larger threshold range (the second integration threshold range) is used, which can more smoothly respond to large deviations, avoid overshoot and oscillation caused by rapid accumulation of the integral term, and ensure smooth engagement of the clutch. Further, dynamically selecting the variable-integration threshold range according to the working state of the clutch can better adapt to different working conditions, improve the flexibility and adaptability of the control system, and through optimization of the threshold range, the position of the clutch can be more accurately controlled, the position deviation can be reduced, and the control precision can be improved. Further, a smaller threshold range can quickly respond to small deviations, reduce the accumulation of the integral term, thereby reducing overshoot and oscillation, and quickly responding to small deviations helps to quickly reduce the deviation, improve the response speed and stability of the system, and a larger threshold range can smoothly respond to large deviations, avoid rapid accumulation of the integral term, and further reduce overshoot and oscillation, and smoothly responding to large deviations helps to reduce system oscillation and improve the overall stability of the system. Further, by optimizing the control strategy, the impact and wear of the clutch during engagement and disengagement can be reduced, the service life of the clutch can be prolonged, the stability and reliability of the control system can be improved, clutch failures caused by improper control can be reduced, and the overall reliability of the vehicle can be improved.

[0073] In some embodiments of the present application, step S500 comprises: S510, multiplying the position deviation value and the proportional term coefficient to obtain a proportional term PID control parameter; S520, adding the proportional term PID control parameter, the filtered derivative term coefficient and the variable integral term coefficient to obtain the control signal.

[0074] It should be noted that the position deviation value at the current time is obtained, the proportional term coefficient corresponding to the clutch working state determined in step S200 is selected, the position deviation value is multiplied by the proportional term coefficient determined in S200 to obtain the proportional term PID control parameter. The filtered derivative term coefficient obtained in step S300, the variable integral term coefficient obtained in step S400 and the proportional term PID control parameter are added to obtain the final control signal. The control signal can be expressed as follows:

[0075] Wherein, is the rate of change of deviation, is a dynamic integral parameter, Kp is a proportional term coefficient, Kd is a derivative term coefficient, and e(t) is a position deviation value sequence.

[0076] In this embodiment, the proportional term, the filtered derivative term and the variable integral term are calculated respectively, and they are added to obtain the control signal, which can more accurately reflect the current state and control requirements of the system, thereby improving the control accuracy. The dynamic calculation of the proportional term, the filtered derivative term and the variable integral term can better adapt to different working conditions, improve the flexibility and adaptability of the control system. Further, the proportional term, the filtered derivative term and the variable integral term are integrated to achieve more comprehensive control effect, improve the overall stability of the system, and through dynamic adjustment of each control parameter, the system can better adapt to different working conditions and environmental changes, and improve the robustness of the system.

[0077] For example, a least squares filter is constructed: in the operation of the AMT controller, since the program running period is a fixed step in the sampling range, and the target response vector, i.e. e of each running period, can also be obtained, therefore in this system, the input signal matrix and the target response vector are both discrete signals, to solve the slope of the fitting curve , the following formula can be used: ; Wherein, k is the slope , x is the sampling time, and y is e of each sampling point.

[0078] In this embodiment, the sampling range is selected to be 10 steps, each step is 0.005s, and the formula is finally simplified to obtain the following results: ; The response signal e of the past 10 cycles is sampled in sequence, and the slope is obtained according to the above simplified formula, which is the differential value of e.

[0079] The framework for controlling the clutch according to the least square method and the variable speed integral method is shown in Figure 6 When |e| is greater than the set upper limit e2, the clutch separation and engagement integral coefficients are both 0 at this time, the integral term effective coefficient = 0, that is, no integral operation is performed, and the integral action is completely inhibited; when |e| is less than the set upper limit e2 and greater than the lower limit e1, the original clutch separation and engagement integral coefficients are multiplied by the corresponding coefficients, that is, when e1 < |e| ≤ e2: separation PID coefficient × = (e2 - |e|) / (e2 - e1), and the engagement PID coefficient × = (e2 - |e|) / (e2 - e1); when |e| is less than the set lower limit e1, that is, |e| ≤ e1, the integral term effective coefficient = 1, and the integral coefficients of the clutch separation and engagement processes are directly output. The clutch separation and engagement processes use their preset integral coefficients Ki_sep and Ki_eng respectively, and are multiplied by the coefficient , to obtain the actual integral gain Ki_actual = Ki × .

[0080] In order to better implement the clutch control method in the embodiment of the present application, on the basis of the clutch control method, the present application also provides a clutch control system, as shown in Figure 7 The clutch control system 700 comprises: An acquisition module 701 is configured to acquire a position deviation value sequence of a clutch, wherein the position deviation value sequence comprises a plurality of position deviation values, and each position deviation value is equal to a difference between a target position and an actual position of the clutch; A parameter setting module 702 is configured to determine a PID control parameter according to a working state of the clutch; A least square filtering module 703 is configured to perform filtering processing on the position deviation value sequence based on a least square method to obtain a filtered differential term coefficient; A variable speed integral module 704 is configured to obtain a variable speed integral term coefficient according to the position deviation value sequence, a variable speed integral threshold range and an integral term coefficient; A signal synthesis module 705 is configured to generate a control signal according to a proportional term coefficient, the filtered differential term coefficient and the variable speed integral term coefficient; An execution driving module 706 is configured to output the control signal to a clutch execution mechanism to realize closed-loop control on the position of the clutch.

[0081] The clutch control system 700 provided by the above embodiments can implement the technical solutions described in the above clutch control method embodiments, and the principles of the specific implementation of each module or unit can be referred to the corresponding content in the above clutch control method embodiments, which will not be described here.

[0082] As shown in Figure 8 The present application also correspondingly provides an intelligent vehicle 800. The intelligent vehicle 800 includes a processor 801, a memory 802 and a display 803. Figure 8 Only part of the components of the intelligent vehicle 800 are shown, but it should be understood that all the shown components are not required to be implemented, and more or less components can be alternatively implemented.

[0083] The processor 801 can be a central processing unit (CPU), a microprocessor or other data processing chip in some embodiments, used to run the program code or process data stored in the memory 802, such as the clutch control method in the present application.

[0084] In some embodiments, the processor 801 can be a single server or a group of servers. The group of servers can be centralized or distributed. In some embodiments, the processor 801 can be local or remote. In some embodiments, the processor 801 can be implemented in a cloud platform. In an embodiment, the cloud platform can include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an inter-internal, a multi-cloud, etc., or any combination thereof.

[0085] The memory 802 can be an internal storage unit of the intelligent vehicle 800 in some embodiments, such as a hard disk or a memory of the intelligent vehicle 800. The memory 802 can also be an external storage device of the intelligent vehicle 800 in other embodiments, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the intelligent vehicle 800.

[0086] Further, the memory 802 can include both the internal storage unit and the external storage device of the intelligent vehicle 800. The memory 802 is used to store the application software and various data installed on the intelligent vehicle 800.

[0087] The display 803 can be an LED display, a liquid crystal display, a touch liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, etc. in some embodiments. The display 803 is used to display information of the intelligent vehicle 800 and to display a visualized user interface. The components 801-803 of the intelligent vehicle 800 communicate with each other through a system bus.

[0088] In an embodiment, when the processor 801 executes the DDDD program in the memory 802, the following steps can be implemented: obtain a position deviation value sequence of the clutch, the position deviation value sequence comprising a plurality of position deviation values, the position deviation value being equal to a difference between a target position and an actual position of the clutch; determine a PID control parameter according to an operating state of the clutch; filter the position deviation value sequence based on a least square method to obtain a filtered differential term coefficient; obtain a variable integral term coefficient according to the position deviation value sequence, a variable integral threshold range and an integral term coefficient; generate a control signal according to a proportional term coefficient, the filtered differential term coefficient and the variable integral term coefficient; output the control signal to a clutch actuator to implement closed-loop control on the position of the clutch.

[0089] It should be understood that, when the processor 801 executes the DDDD program in the memory 802, in addition to the above functions, other functions can also be implemented, which can be referred to the description of the corresponding method embodiments.

[0090] Further, the type of the intelligent vehicle 800 mentioned in the embodiments of the present application is not specifically limited, and the intelligent vehicle 800 can be a mobile phone, a tablet computer, a personal digital assistant (PDA), a wearable device, a laptop, etc. Exemplary embodiments of the portable intelligent vehicle include but are not limited to a portable intelligent vehicle running an IOS, an android, a microsoft or other operating system. The above portable intelligent vehicle can also be other portable intelligent vehicles, such as a laptop having a touch-sensitive surface (e.g. a touch panel). It should also be understood that, in some other embodiments of the present application, the intelligent vehicle 800 can also not be a portable intelligent vehicle, but a desktop computer having a touch-sensitive surface (e.g. a touch panel).

[0091] Correspondingly, the embodiment of the present application further provides a computer readable storage medium for storing computer readable programs or instructions, which can realize the steps or functions in the clutch control method provided by the above-mentioned method embodiments when executed by a processor.

[0092] Those skilled in the art can understand that all or part of the processes of the above-mentioned embodiment methods can be completed by a computer program instructing relevant hardware (such as a processor, a controller, etc.) to complete, and the computer program can be stored in a computer readable storage medium. The computer readable storage medium is a disk, an optical disk, a read-only memory or a random access memory, etc.

[0093] The clutch control method, system, vehicle and medium provided by the present application are described in detail above, and the principles and implementation manners of the present application are described by applying specific examples in this paper. The above embodiment is only used to help understand the method and core idea of the present application; meanwhile, for those skilled in the art, according to the idea of the present application, the specific implementation manner and application range will be changed, and the above description should not be understood as a limitation of the present application.

Claims

1. A clutch control method, characterized in that, Includes the following steps: Obtain a sequence of position deviation values ​​for the clutch, the sequence of position deviation values ​​including multiple position deviation values, the position deviation value being equal to the difference between the target position and the actual position of the clutch; Determine the PID control parameters based on the operating state of the clutch; The position deviation value sequence is filtered using the least squares method to obtain the filter differential term coefficients. The variable speed integral term coefficients are obtained based on the position deviation value sequence, the variable speed integral threshold range, and the integral term coefficients. A control signal is generated based on the proportional term coefficient, the filter differential term coefficient, and the variable speed integral term coefficient; The control signal is output to the clutch actuator to achieve closed-loop control of the clutch position.

2. The clutch control method according to claim 1, characterized in that, Determining the PID control parameters based on the operating state of the clutch includes: Identify the operating status of the clutch; When the working state is that the clutch is in the disengaged state, the PID control parameter is determined to be the first coefficient; When the working state is that the clutch is engaged, the PID control parameter is determined to be the second coefficient; the first coefficient is greater than the second coefficient.

3. The clutch control method according to claim 1, characterized in that, The filtering of the position deviation value sequence based on the least squares method to obtain the filter differential term coefficients includes: In the discrete time domain, the position deviation values ​​of the most recent N sampling periods are used to form the observation sequence; N is a positive integer greater than 1. A fitted straight line is generated for the observed sequence using the least squares method, and the slope of the fitted straight line is determined to be the rate of change of deviation. The filter differential coefficient is obtained by multiplying the deviation change rate, the differential value of the position deviation value sequence, and the differential coefficient.

4. The clutch control method according to claim 1, characterized in that, The step of obtaining the variable speed integral term coefficient based on the position deviation value sequence, the variable speed integral threshold range, and the integral term coefficient includes: Determine the range of the variable speed integral threshold; The integral coefficient adjustment factor is determined based on the variable speed integral threshold range and the position deviation value; The dynamic integral parameters are obtained by multiplying the integral coefficient adjustment factor and the integral term coefficient; The variable speed integral term coefficient is obtained by multiplying the dynamic integral parameter, the integral value of the position deviation value sequence, and the integral term coefficient.

5. The clutch control method according to claim 4, characterized in that, The step of determining the integral coefficient adjustment factor based on the variable speed integral threshold range and the position deviation value includes: Compare the magnitude of the absolute value of the variable speed integral threshold range with the absolute value of the position deviation value; the variable speed integral threshold range includes an upper limit value and a lower limit value; When the absolute value of the position deviation is less than or equal to the lower limit value, the integral coefficient adjustment factor is determined to be equal to 1. When the absolute value of the position deviation is greater than the lower limit and less than or equal to the upper limit, the integral coefficient adjustment factor is determined to be equal to the ratio; the ratio is equal to the first difference divided by the second difference, the first difference is equal to the difference between the upper limit and the absolute value of the position deviation, and the second difference is equal to the difference between the upper limit and the lower limit. When the absolute value of the position deviation is greater than the upper limit value, the integral coefficient adjustment factor is determined to be equal to 0.

6. The clutch control method according to claim 5, characterized in that, Also includes: When the clutch is in the disengaged state, the speed change integral threshold range is determined to be the first integral threshold range; When the working state is that the clutch is engaged, the speed change integral threshold range is determined to be the second integral threshold range. Wherein, the lower limit of the second integration threshold range is greater than the lower limit of the first integration threshold, and the upper limit of the second integration threshold range is greater than the upper limit of the first integration threshold.

7. The clutch control method according to any one of claims 1 to 6, characterized in that, The step of generating a control signal based on the proportional term coefficient, the filter differential term coefficient, and the variable speed integral term coefficient includes: The proportional PID control parameters are obtained by multiplying the position deviation value with the proportional term coefficient. The control signal is obtained by adding the proportional PID control parameters, the filter derivative coefficient, and the variable speed integral coefficient.

8. A clutch control system, characterized in that, include: The acquisition module is used to acquire a sequence of position deviation values ​​of the clutch, the sequence of position deviation values ​​includes multiple position deviation values, and the position deviation value is equal to the difference between the target position and the actual position of the clutch; The parameter setting module is used to determine the PID control parameters according to the working state of the clutch. The least squares filtering module is used to filter the position deviation value sequence based on the least squares method to obtain the filter differential term coefficients. The variable speed integral module is used to obtain the variable speed integral term coefficients based on the position deviation value sequence, the variable speed integral threshold range, and the integral term coefficients. The signal synthesis module is used to generate a control signal based on the proportional term coefficient, the filter differential term coefficient, and the variable speed integral term coefficient; The drive module is used to output the control signal to the clutch actuator to achieve closed-loop control of the clutch position.

9. An intelligent vehicle, characterized in that, Including memory and processor, among which, The memory is used to store programs; The processor, coupled to the memory, is used to execute the program stored in the memory to implement the steps of the clutch control method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, Used to store computer-readable programs or instructions, which, when executed by a processor, can implement the steps of the clutch control method according to any one of claims 1 to 7.

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