Self-adaptive control method for electrically-controlled electric gear shifting executing mechanism

Abstract

The invention relates to a self-adaptive control method for an electrically-controlled electric gear shifting executing mechanism, and aims to overcome the influence of uncertain problems such as parameter perturbation and external interference in the gear shifting process and quickly and accurately complete the gear shifting action. The method comprises the following steps: firstly, modeling a gear shifting execution mechanism according to a working principle of the gear shifting execution mechanism; secondly, considering the uncertainty of external interference and the parameters of the gear-shifting direct current motor, adding a sliding mode control algorithm, optimizing a membership function of fuzzy sliding mode control through a genetic algorithm, and realizing the self-adaptive adjustment of sliding mode control gain and following the actual response characteristics of the gear-shifting direct current motor; and finally, a fuzzy PI controller is designed to carry out adaptive adjustment on the duty ratio of the gear-shifting direct current motor, and accurate tracking of the displacement of the gear-shifting execution mechanism is completed. According to the method, the tracking precision, the response speed, the anti-interference capability and the like of the control of the gear shifting execution mechanism are improved through the online self-adaptive adjustment of the control parameters.

Description

Technical Field

[0001] The invention belongs to the technical field of automobile shift control, and in particular relates to an adaptive control method for an electronically controlled electric shift actuator. Background Art

[0002] For new energy vehicle systems, how to achieve fast, accurate and smooth gear shifting is the core content of the control strategy, and the gear shifting and engaging operations are the basis and key to the gear shifting control. Due to the advantages of simple structure, high control accuracy and fast response speed, the electronically controlled electric gear shifting actuator has been widely used in a variety of medium and heavy-duty vehicles. The key to the control of the electronically controlled electric gear shifting actuator is to quickly track the target displacement of the combination set and reduce its displacement tracking error.

[0003] Some existing patents, such as the invention patent with patent number CN114278725A, use BP neural network to establish a shift control algorithm, including the feedforward calculation of BP network and the calculation rules of BP network weight coefficients, and formulate a shift control strategy based on smoothness. The invention patent with patent number CN109723814A proposes a shift control method for AMT mechanism. TCU optimizes AMT performance by accurately calibrating and controlling the gear selection position sensor, gear selection motor, gear shift position sensor, gear shift DC motor, etc. However, in actual control, the uncertainty changes in the internal parameters of the gear shift actuator and the external disturbance increase the control difficulty of the system, and even make the control fail in severe cases. Therefore, how to develop an adaptive electronically controlled electric gear shift actuator control algorithm that can quickly and accurately complete the gear shift action, thereby effectively shortening the power interruption time, is a difficulty that needs to be solved urgently. Summary of the invention

[0004] The present invention proposes an adaptive control method for an electronically controlled electric gear shift actuator. In order to overcome the influence of uncertainty problems such as parameter perturbations and external interference during the gear shifting process, the method adopts sliding mode control as the basic algorithm, optimizes the sliding mode control gain by a genetic algorithm, and uses fuzzy adaptive control to adjust the synchronizer displacement PI control parameters, thereby achieving performance improvements in the control tracking accuracy, response speed and anti-interference ability of the gear shift actuator.

[0005] The purpose of the present invention can be achieved by the following technical solutions:

[0006] An electronically controlled electric shift actuator, the shift actuator is composed of a shift DC motor, a gear reduction mechanism, a nut, a lead screw, a shift fork, a coupling sleeve, and an angular displacement sensor. The nut is fixedly connected to the shift fork, driving the shift fork to move linearly, thereby pushing the coupling sleeve to engage the target gear. The angular displacement sensor collects the angular displacement of the shift DC motor in real time, and determines whether the current axial displacement of the coupling sleeve reaches the target gear position, thereby realizing the displacement closed-loop control of the shift DC motor.

[0007] An adaptive control method for an electronically controlled electric shift actuator, the specific steps are as follows:

[0008] S1: Model the shift actuator and derive the voltage balance equation and torque balance equation of the shift DC motor;

[0009] S2: Design a sliding mode control algorithm to control the shifting DC motor, achieve fast tracking of the target displacement of the combination set, and reduce the influence of the uncertainty of the shifting DC motor parameters and external dynamic interference;

[0010] S3: Optimize the membership function of fuzzy sliding mode control through genetic algorithm, perform adaptive adjustment of sliding mode control gain, and improve the dynamic performance of the system state approaching the sliding surface;

[0011] S4: Design a fuzzy PI controller to adaptively adjust the duty cycle of the shifting DC motor and complete the adaptive following of the displacement of the shifting actuator.

[0012] Furthermore, step S1 is specifically as follows:

[0013] The voltage balance equation and torque balance equation of the shifting DC motor are shown in equation (1):

[0014]

[0015] In the formula, θ DC is the shifting DC motor angle; U m Input DC voltage to the shift DC motor; R m is the internal resistance of the shifting DC motor; L m is the equivalent inductance of the shifting DC motor; K emf is the induced electromotive force coefficient of the shifting DC motor; ω DC is the speed of the shifting DC motor; T mgr is the shifting DC motor torque; K m is the motor torque coefficient; i m is the shifting DC motor current; T Lgr is the motor load torque; J m is the moment of inertia of the shifting DC motor; b m is the rotation damping coefficient of the shifting DC motor.

[0016] Furthermore, step S2 is specifically as follows:

[0017] S21: Define the angular displacement tracking error of the shifting DC motor as:

[0018]

[0019] In the formula, Z m is the displacement state variable, Z m =[z1,z2,z3];X md is the motor angular displacement setting value, X md =[x d ,0,0].

[0020] S22: Set the sliding surface function to:

[0021]

[0022] Where N s is the sliding mode constant.

[0023] S23: Solve the output of the sliding mode controller by combining the equivalent control law with the arrival control law. Derivative the sliding surface function, and we get:

[0024]

[0025] make Substituting formula (1) into formula (4), we get:

[0026]

[0027] The equivalent control law u of sliding mode control is calculated eq for:

[0028]

[0029] S24: Introducing the switching control law u sw , so that the system trajectory is stable on the sliding surface. In order to solve the chattering problem caused by the sign function, the hyperbolic tangent function is used instead of the traditional sign function:

[0030] u sw = -η1 tanh(s1) (7)

[0031] Combining the equivalent control law with the arrival control law, we can obtain the sliding mode control law as shown in equation (8):

[0032]

[0033] Furthermore, step S3 is specifically as follows:

[0034] S31: Determine the optimization variable as the sliding mode control gain η1;

[0035] S32: Evaluate and solve the fitness value of individuals in the population, and select the integral J of the absolute value of the angular displacement tracking error of the shifting DC motor e As a performance evaluation index, as shown in formula (9):

[0036]

[0037] In the formula, t up Indicates the initial time of the shifting DC motor; t end Indicates the moment when the shifting DC motor ends.

[0038] S33: Perform iterative selection, crossover and mutation operations until the iteration is stopped after the termination condition is met.

[0039] Further, step S4 is specifically as follows:

[0040] S41: Set the fuzzy input variable to the difference e between the actual synchronizer stroke and the target trajectory stroke and its change rate The output variable is the output variable PI controller proportional coefficient change Δk p And the integral coefficient change Δk i ; The fuzzy domain of input variables and output variables is set to [-4, 4], the corresponding system input fuzzy subset and output subset are defined as {NS, NB, ZO, PS, PB}, and the S-type and triangular membership functions are set.

[0041] S42: Formulate fuzzy control rules as follows:

[0042] Rule 1: When the synchronizer displacement error e is too large, the proportional coefficient k p Should be larger to improve the system response speed, the integral coefficient k i Should be close to zero.

[0043] Rule 2: When the synchronizer displacement error e and its rate of change When the size is medium, k p Should be small to prevent system overshoot, k i Should be medium size.

[0044] Rule 3: When the synchronizer displacement error e is small, k p , k i It should be large to ensure system stability.

[0045] Rule 4: When the synchronizer displacement error change rate When it is larger, reduce k appropriately p , k i .

[0046] S43: Defuzzify the control quantity generated by fuzzy reasoning using the center of gravity method, and the output quantity Δk of the fuzzy control rule p With Δk p The calculation method is shown in formula (10) and formula (11):

[0047]

[0048] Compared with the prior art, the advantages of the present invention are:

[0049] 1. The adaptive control method of an electronically controlled electric gear shift actuator of the present invention solves the uncertainty problems such as parameter perturbation and external interference in the gear shift process, improves the displacement tracking accuracy and stability of the gear shift process, and has important guiding significance for solving the problem of accurate control of the gear shift actuator;

[0050] 2. The adaptive control method of an electronically controlled electric shift actuator of the present invention adopts a sliding mode algorithm as the control basis, has a good advantage in dealing with uncertain interference problems, and uses fuzzy control to optimize the fixed switching gain in the sliding mode control rate, thereby ensuring the robust performance of the displacement tracking process;

[0051] 3. The adaptive control method of an electronically controlled electric shift actuator described in the present invention adopts a fuzzy PI control algorithm to adaptively adjust the duty cycle of the shift DC motor, complete the precise tracking of the displacement of the shift actuator, and provide a new way for the optimized control of the electronically controlled electric shift actuator. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 A schematic diagram of an electronically controlled electric shift actuator used in the embodiment;

[0053] Figure 2 A flow chart of an adaptive control method for an electronically controlled electric shift actuator used in an embodiment;

[0054] Figure 3 Comparison results of angular displacement tracking between the adaptive control method and the PID control method used in the embodiment;

[0055] Figure 4 Comparison results of angular displacement tracking errors between the adaptive control method and the PID control method used in the embodiment;

[0056] Figure 5 Comparison results of angular displacement tracking under interference between the adaptive control method used in the embodiment and the basic sliding mode control method and PID control method;

[0057] Figure 6The comparison results of angular displacement tracking error between the adaptive control method used in the embodiment and the basic sliding mode control method and PID control method under interference are shown.

[0058] Labels in the figure: 1. shift DC motor, 2. gear reduction mechanism, 3. nut, 4. screw, 5. shift fork, 6. coupling sleeve, 7. angular displacement sensor. DETAILED DESCRIPTION

[0059] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described examples are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] Example 1

[0061] An electronically controlled electric shift actuator, the shift actuator is composed of a shift DC motor 1, a gear reduction mechanism 2, a nut 3, a lead screw 4, a shift fork 5, a coupling sleeve 6 and an angular displacement sensor 7, etc. Figure 1 As shown. The nut 3 is fixedly connected to the shift fork 5, driving the shift fork 5 to move linearly, thereby pushing the coupling sleeve 6 to engage the target gear. When the shifting conditions are met, the transmission controller TCU controls the shifting DC motor 1 to rotate and generate torque. After passing through the gear reduction mechanism 2, the nut 3 and the lead screw 4 are driven to realize the conversion of the shifting torque into the shifting flat force; the angular displacement sensor 7 collects the angular displacement of the shifting DC motor 1 in real time, and determines whether the current axial displacement of the coupling sleeve 6 reaches the target gear position, thereby realizing the displacement closed-loop control of the shifting DC motor 1.

[0062] Example 2

[0063] The flow chart of the adaptive control method of the electronically controlled electric shift actuator is as follows: Figure 2 First, the shift actuator is modeled according to its working principle; then, the sliding mode control algorithm is used to overcome the external interference and the uncertainty of the parameters of the shift DC motor, and the membership function of the fuzzy sliding mode control is optimized by the genetic algorithm to achieve adaptive adjustment of the sliding mode control gain; finally, the fuzzy PI control algorithm is developed to adaptively adjust the duty cycle of the shift DC motor and complete the precise tracking of the shift actuator displacement.

[0064] The adaptive control method of the electronically controlled electric shift actuator specifically comprises:

[0065] S1: Model the shift actuator and derive the voltage balance equation and torque balance equation of the shift DC motor 1

[0066] The voltage balance equation and torque balance equation of the shifting DC motor are shown in equation (1):

[0067]

[0068] In the formula, θ DC is the rotation angle of the shifting DC motor 1; U m Input DC voltage to the shift DC motor 1; R m is the internal resistance of the shifting DC motor 1; L m is the equivalent inductance of the shifting DC motor 1; K emf is the induced electromotive force coefficient of the shifting DC motor 1; ω DC is the speed of the shifting DC motor 1; T mgr is the torque of the shifting DC motor 1; K m is the torque coefficient of the shifting DC motor 1; i m is the current of the shifting DC motor 1; T Lgr is the load torque of the shifting DC motor 1; J m is the moment of inertia of the shifting DC motor 1; b m is the rotation damping coefficient of the shifting DC motor 1.

[0069] S2: Design a sliding mode control algorithm to control the shifting DC motor, achieve fast tracking of the target displacement of the combination set, and reduce the influence of the shifting DC motor parameter uncertainty and external dynamic interference.

[0070] The specific implementation method is:

[0071] S21: Define the angular displacement tracking error of the shifting DC motor 1 as:

[0072]

[0073] In the formula, Z m is the displacement state variable, Z m =[z1,z2,z3];X md is the motor angular displacement setting value, X md =[x d ,0,0].

[0074] S22: Set the sliding surface function to:

[0075]

[0076] Where N s is the sliding mode constant.

[0077] S23: Solve the output of the sliding mode controller by combining the equivalent control law with the arrival control law. Derivative the sliding surface function, and we get:

[0078]

[0079] make Substituting formula (1) into formula (4), we get:

[0080]

[0081] The equivalent control law u of sliding mode control is calculated eq for:

[0082]

[0083] S24: Introducing the switching control law u sw , so that the system trajectory is stable on the sliding surface. In order to solve the chattering problem caused by the sign function, the hyperbolic tangent function is used instead of the traditional sign function:

[0084] u sw = -η1 tanh(s1) (7)

[0085] Combining the equivalent control law with the arrival control law, we can obtain the sliding mode control law as shown in equation (8):

[0086]

[0087] S3: The membership function of the fuzzy sliding mode control is optimized through genetic algorithm, and the sliding mode control gain is adaptively adjusted to improve the dynamic performance of the system state approaching the sliding surface.

[0088] The specific implementation method is:

[0089] S31: Determine the optimization variable as the sliding mode control gain η1;

[0090] S32: Evaluate and solve the fitness value of individuals in the population, and select the integral J of the absolute value of the angular displacement tracking error of the shifting DC motor e As a performance evaluation index, as shown in formula (9):

[0091]

[0092] In the formula, t up Indicates the initial time of the shifting DC motor 1; t end Indicates the time when the shifting DC motor 1 ends.

[0093] S33: Perform iterative selection, crossover and mutation operations until the iteration is stopped after the termination condition is met.

[0094] S4: Design a fuzzy PI controller to adaptively adjust the duty cycle of the shifting DC motor 1 to complete the adaptive following of the displacement of the shifting actuator.

[0095] The specific implementation method is:

[0096] S41: Set the fuzzy input variable to the difference e between the actual synchronizer stroke and the target trajectory stroke and its change rate The output variable is the output variable PI controller proportional coefficient change Δk p And the integral coefficient change Δk i ; The fuzzy domain of input variables and output variables is set to [-4, 4], the corresponding system input fuzzy subset and output subset are defined as {NS, NB, ZO, PS, PB}, and the S-type and triangular membership functions are set.

[0097] S42: Formulate fuzzy control rules as follows:

[0098] Rule 1: When the synchronizer displacement error e is too large, the proportional coefficient k p Should be larger to improve the system response speed, the integral coefficient k i Should be close to zero.

[0099] Rule 2: When the synchronizer displacement error e and its rate of change When the size is medium, k p Should be small to prevent system overshoot, k i Should be medium size.

[0100] Rule 3: When the synchronizer displacement error e is small, k p , k i It should be large to ensure system stability.

[0101] Rule 4: When the synchronizer displacement error change rate When it is larger, reduce k appropriately p , k i .

[0102] S43: Defuzzify the control quantity generated by fuzzy reasoning using the center of gravity method, and the output quantity Δk of the fuzzy control rule p With Δk p The calculation method is shown in formula (10) and formula (11):

[0103]

[0104] The angular displacement tracking and error comparison results of the adaptive control method and the PID control method proposed in the present invention are shown in Figure 2. Figure 3 and Figure 4 As shown in the figure, there is a large overshoot in displacement tracking under PID control, and it takes about 0.5s to stabilize to the target displacement. Compared with PID control, the displacement tracking error under the adaptive control method is smaller, and the tracking process takes less time, and the target displacement can be reached quickly without overshoot within 0.24s.

[0105] The angular displacement tracking and error comparison results of the adaptive control method proposed in the present invention, the basic sliding mode control method, and the PID control method under interference are shown in the following figure. Figure 5 and Figure 6 As shown in the figure, both the adaptive control method and the basic sliding mode control method can cope with the changes in internal parameters well and basically maintain the original tracking control performance, while the PID controller has a more obvious overshoot phenomenon and can only stabilize to the target value when it is close to 0.7s. In the case of resistance torque noise interference, the sliding mode anti-disturbance controller can basically ensure the stable tracking of the target trajectory, while the sliding mode control and PID controller will have different degrees of oscillation.

[0106] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. All equivalent structural changes made by using the contents of the present invention specification and drawings under the inventive concept of the present invention, or directly / indirectly applied in other related technical fields are included in the patent protection scope of the present invention.

Claims

1. An electronically controlled electric shift actuator, characterized in that: The gear shift actuator comprises a gear shift DC motor (1), a gear reduction mechanism (2), a nut (3), a lead screw (4), a gear shift fork (5), a coupling sleeve (6), and an angular displacement sensor (7). The nut (3) is fixedly connected to the gear shift fork (5) to drive the gear shift fork (5) to perform linear motion, thereby pushing the coupling sleeve (6) to engage a target gear position. The angular displacement sensor (7) collects the angular displacement of the gear shift DC motor (1) in real time and determines whether the current axial displacement of the coupling sleeve (6) reaches the target gear position, thereby realizing closed-loop displacement control of the gear shift DC motor (1).

2. An adaptive control method for an electronically controlled electric shift actuator as claimed in claim 1, characterized in that: The specific steps are as follows: S1: Model the shift actuator and derive the voltage balance equation and torque balance equation of the shift DC motor; S2: Design a sliding mode control algorithm to control the shifting DC motor, achieve fast tracking of the target displacement of the combination set, and reduce the influence of the uncertainty of the shifting DC motor parameters and external dynamic interference; S3: Optimize the membership function of fuzzy sliding mode control through genetic algorithm, perform adaptive adjustment of sliding mode control gain, and improve the dynamic performance of the system state approaching the sliding surface; S4: Design a fuzzy PI controller to adaptively adjust the duty cycle of the shifting DC motor and complete the adaptive following of the displacement of the shifting actuator.

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