Method for controlling gear shifting of vehicle, vehicle, processor and storage medium

Abstract

The invention discloses a method for controlling gear shifting of a vehicle, the vehicle, a processor and a storage medium, and belongs to the technical field of vehicle intelligent control. The method comprises the steps that target gear information of the vehicle, output shaft rotating speed measurement data of an output shaft at the current moment and output shaft rotating speed associated data are obtained; based on a particle filtering algorithm, correcting the output shaft rotating speed measurement data according to the output shaft rotating speed associated data to obtain a corrected output shaft rotating speed; according to the corrected rotating speed of the output shaft and the target gear information, the target motor rotating speed of the driving motor is determined; and controlling the driving motor according to the target motor rotating speed to enable the gear of the vehicle to reach the target gear. Based on the particle filter algorithm, the output shaft rotation speed measurement data are corrected according to the output shaft rotation speed associated data, the accuracy of the gearbox output shaft rotation speed measurement value is improved, the accuracy of the target motor rotation speed is further improved, and the success rate of vehicle gear shifting is improved.

Description

Technical Field

[0001] The present application relates to the technical field of vehicle intelligent control, and in particular to a method for controlling vehicle gear shifting, a vehicle, a processor, and a storage medium. Background Art

[0002] At present, when the vehicle is shifting gears, the electronically controlled mechanical automatic transmission needs to adjust the speed of the drive motor after the shift actuator disengages the gear, so that the speed of the synchronizer is close to the speed of the target gear, which is convenient for smooth and fast gear shifting. The speed of the gearbox output shaft is often measured by a Hall sensor, but when the vehicle is at a low speed or the speed changes drastically, the sensor measurement error is large, which easily leads to failure of the vehicle to shift gears. Therefore, the vehicle shifting method used in the prior art has the problem of low success rate. Summary of the invention

[0003] The purpose of the embodiments of the present application is to provide a method for controlling vehicle gear shifting, a vehicle, a processor, and a machine-readable storage medium, so as to solve the problem of low success rate of the vehicle gear shifting method used in the prior art.

[0004] In order to achieve the above-mentioned object, a first aspect of an embodiment of the present application provides a method for controlling vehicle gear shifting, wherein the vehicle includes a gearbox and a drive motor, the gearbox includes an output shaft, and the method includes:

[0005] Obtaining the target gear information of the vehicle, the output shaft speed measurement data of the output shaft at the current moment, and the output shaft speed related data;

[0006] Based on the particle filter algorithm, the output shaft speed measurement data is corrected according to the output shaft speed correlation data to obtain the corrected output shaft speed;

[0007] Determining a target motor speed of the drive motor according to the corrected output shaft speed and the target gear information;

[0008] The drive motor is controlled according to the target motor speed so that the gear position of the vehicle reaches the target gear position.

[0009] In an embodiment of the present application, based on a particle filtering algorithm, the output shaft speed measurement data is corrected according to the output shaft speed associated data to obtain a corrected output shaft speed, including: based on a predetermined state equation, determining the output shaft speed calculation value according to the output shaft speed associated data; using the output shaft speed calculation value as the initial value of the random variable, and based on the particle filtering algorithm and the predetermined observation equation, obtaining the probability density function after the output shaft speed is fused; determining the corrected output shaft speed according to the output shaft speed associated data and the probability density function after the output shaft speed is fused.

[0010] In an embodiment of the present application, a method for determining a state equation and an observation equation includes: obtaining a preset functional relationship between output shaft speed measurement data and output shaft speed correlation data; performing Taylor expansion processing on the preset functional relationship to obtain a state equation; and determining the observation equation based on a preset observation error amount.

[0011] In the embodiment of the present application, the target gear information includes the target gear set transmission ratio and the preset speed difference, and the preset speed difference is the allowable value of the speed difference between the coupling sleeve and the target gear; according to the corrected output shaft speed and the target gear information, it is determined that the target motor speed of the drive motor satisfies the following formula:

[0012] n target =n 0 ·i±Δn;

[0013] Among them, n target is the target motor speed, n 0 is the corrected output shaft speed, i is the target gear set transmission ratio, and Δn is the preset speed difference.

[0014] In an embodiment of the present application, the drive motor is controlled according to the target motor speed so that the gear position of the vehicle reaches the target gear position, including: obtaining the current motor speed of the drive motor; determining the target control torque of the drive motor according to the target motor speed and the current motor speed; adjusting the speed of the drive motor to the target motor speed according to the target control torque so that the gear position of the vehicle reaches the target gear position.

[0015] In an embodiment of the present application, the vehicle adopts PID control to determine the target control torque of the drive motor according to the target motor speed and the current motor speed, including: obtaining the current operating condition data of the vehicle; determining the target control parameters of the PID controller according to the current operating condition data based on a pre-built control parameter adaptive model, the control parameter adaptive model is used to output the control parameters corresponding to the operating condition data according to the input operating condition data; determining the motor speed difference of the drive motor according to the current motor speed and the target motor speed; based on the PID control model, determining the target control torque according to the motor speed difference and the target control parameters according to the PID control model.

[0016] In an embodiment of the present application, a method for constructing a control parameter adaptive model includes: obtaining multiple sample data, the sample data including operating condition data and control parameters corresponding to the operating condition data; establishing a neural network model; and training the neural network model based on the multiple sample data to obtain a control parameter adaptive model.

[0017] A second aspect of an embodiment of the present application provides a processor configured to execute the above-mentioned method for controlling vehicle gear shifting.

[0018] A third aspect of an embodiment of the present application provides a vehicle, comprising: a gearbox, the gearbox including an output shaft; a drive motor; and the above-mentioned processor.

[0019] A fourth aspect of an embodiment of the present application provides a machine-readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the above-mentioned method for controlling vehicle gear shifting is implemented.

[0020] The above technical solution obtains the target gear information of the vehicle, the output shaft speed measurement data of the output shaft at the current moment, and the output shaft speed related data, and then based on the particle filtering algorithm, corrects the output shaft speed measurement data according to the output shaft speed related data to obtain the corrected output shaft speed, and then determines the target motor speed of the drive motor according to the corrected output shaft speed and the target gear information, and finally controls the drive motor according to the target motor speed so that the gear of the vehicle reaches the target gear. The present application is based on a particle filtering algorithm, and corrects the output shaft speed measurement data according to the output shaft speed related data, thereby improving the accuracy of the gearbox output shaft speed measurement value, thereby improving the accuracy of the target motor speed, and is conducive to improving the success rate of vehicle gear shifting.

[0021] Other features and advantages of the embodiments of the present application will be described in detail in the subsequent specific implementation section. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The accompanying drawings are used to provide a further understanding of the embodiments of the present application and constitute a part of the specification. Together with the following specific implementations, they are used to explain the embodiments of the present application, but do not constitute a limitation on the embodiments of the present application. In the accompanying drawings:

[0023] Figure 1 A flow chart of a method for controlling vehicle gear shifting provided in an embodiment of the present application;

[0024] Figure 2 A flowchart of particle filter data fusion provided in a specific embodiment of the present application. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the specific implementation methods described herein are only used to illustrate and explain the embodiments of the present application, and are not used to limit the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0026] It should be noted that if the embodiments of the present application involve directional indications (such as up, down, left, right, front, back...), the directional indications are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0027] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present application, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or suggesting their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0028] During the vehicle shifting process, the shifting process of the electronically controlled mechanical automatic transmission mainly includes five steps: unloading and reducing torque, disengaging, speed regulation, engaging gears and torque recovery. When the TCU receives the shifting command, it first unloads the drive motor to reduce torque. At this time, the drive motor is in torque control mode. When the output torque of the drive motor is zero, the TCU controller controls the shift actuator to disengage the gear. At this time, the synchronizer is disengaged and in neutral position. When the TCU controller determines that the synchronizer is completely separated, the drive motor switches to speed control mode and controls the synchronizer to quickly approach the target gear speed. Then the TCU controller controls the shift actuator to achieve smooth gear engagement. Finally, the drive motor performs torque coordination control and torque recovery, and the entire shifting process ends. Among them, the "speed regulation" stage in the shifting process has a greater impact on the shifting time and the success rate of the shifting.

[0029] At present, the output shaft speed of an electronically controlled mechanical automatic transmission is often measured using a Hall sensor, but when the vehicle is at a low speed or the vehicle speed changes dramatically, the sensor measurement error is large, which can easily lead to a long gear shifting time or a gear shifting failure. In order to obtain a reliable output shaft speed of an electronically controlled mechanical automatic transmission to improve the vehicle's gear shifting success rate, the present application provides a method for controlling vehicle gear shifting.

[0030] Figure 1 A flow chart of a method for controlling vehicle shifting provided in an embodiment of the present application. Figure 1 As shown, an embodiment of the present application provides a method for controlling vehicle gear shifting, the vehicle includes a gearbox and a drive motor, the gearbox includes an output shaft, and the method is described by taking the application of the method to a processor as an example. The method may include the following steps.

[0031] Step S101, obtaining target gear information of the vehicle, output shaft speed measurement data of the output shaft at the current moment, and output shaft speed related data.

[0032] Specifically, the target gear information of the vehicle refers to the data corresponding to the target gear that the vehicle needs to achieve, and is related to the target gear corresponding to the target gear. The output shaft speed measurement data of the output shaft at the current moment is the data measured by the Hall sensor. The output shaft speed-related data refers to the related data affected by the output shaft speed. For different gearboxes used in different vehicles, the output shaft speed-related data is different. Taking the electric drive AMT power shift gearbox as an example, when the drive motor shifts gears, the auxiliary motor performs torque compensation. Here, the speed of the auxiliary motor can be used as the output shaft speed-related data.

[0033] Step S102 , based on a particle filter algorithm, the output shaft speed measurement data is corrected according to the output shaft speed associated data to obtain a corrected output shaft speed.

[0034] Specifically, the particle filter algorithm approximates the probability density function by finding a set of random samples propagating in the state space, and replaces the integral operation with the sample mean, thereby obtaining the minimum variance estimation process of the system state. Its principle is Monte Carlo integration based on Bayesian filtering. It can be understood that in order to obtain a reliable output shaft speed of the electronically controlled mechanical automatic transmission, the embodiment of the present application adopts a particle filter algorithm to perform multi-source data fusion, and fuses the output shaft speed associated data with the output shaft speed measurement data to correct the output shaft speed measurement data and obtain the corrected output shaft speed measurement data. The accuracy of the output shaft speed measurement data of the transmission is improved, the variance of the random variable of the measured speed is significantly reduced, and it is conducive to improving the success rate of gear shifting.

[0035] Step S103, determining the target motor speed of the drive motor according to the corrected output shaft speed and the target gear information.

[0036] In one example, the target gear information may include a transmission ratio, which is the ratio between the speed of the gearbox input shaft and the speed of the output shaft. When the target gear is known, the transmission ratio under the gear can be obtained by referring to the transmission ratio table or related parameters of the gearbox. For a reduction transmission, the transmission ratio is greater than 1; for a speed increase transmission, the transmission ratio is less than 1. Further, the target motor speed of the drive motor can be calculated based on the corrected output shaft speed and the transmission ratio, and the target motor speed of the drive motor = the corrected output shaft speed × the transmission ratio.

[0037] Step S104, controlling the drive motor according to the target motor speed so that the gear position of the vehicle reaches the target gear position.

[0038] Specifically, the drive motor is controlled according to the target motor speed. This process is the "speed regulation" stage in the gear shifting process. The purpose of controlling the drive motor speed is to make the speed of the clutch sleeve or synchronizer close to the target gear speed. After controlling the drive motor speed, the gear shifting mechanism needs to be operated to shift the gear to the target gear. The purpose of accurate speed regulation is to shorten the gear shifting time and increase the success rate of gear shifting.

[0039] The above technical solution obtains the target gear information of the vehicle, the output shaft speed measurement data of the output shaft at the current moment, and the output shaft speed related data, and then based on the particle filtering algorithm, corrects the output shaft speed measurement data according to the output shaft speed related data to obtain the corrected output shaft speed, and then determines the target motor speed of the drive motor according to the corrected output shaft speed and the target gear information, and finally controls the drive motor according to the target motor speed so that the gear of the vehicle reaches the target gear. The present application is based on a particle filtering algorithm, and corrects the output shaft speed measurement data according to the output shaft speed related data, thereby improving the accuracy of the gearbox output shaft speed measurement value, thereby improving the accuracy of the target motor speed, and is conducive to improving the success rate of vehicle gear shifting.

[0040] In an embodiment of the present application, a method for determining a state equation and an observation equation includes: obtaining a preset functional relationship between output shaft speed measurement data and output shaft speed correlation data; performing Taylor expansion processing on the preset functional relationship to obtain a state equation; and determining the observation equation based on a preset observation error amount.

[0041] It can be understood that before the output shaft speed associated data and the gearbox output shaft speed measurement data are fused according to the particle filter algorithm, a preparation stage for fusion is required to determine the state equation and the observation equation. Specifically, in the embodiment of the present application, the preset functional relationship between the output shaft speed measurement data and the output shaft speed associated data can be:

[0042] n 0 =g(n′);

[0043] Among them, n 0 is the output shaft speed measurement data, n′ is the output shaft speed correlation data, and g() is the function correlating the two.

[0044] The embodiment of the present application takes the electric drive AMT power shift gearbox as an example. When the drive motor shifts gears, the auxiliary motor performs torque compensation. Here, the speed of the auxiliary motor is used as the output shaft speed related data. Therefore, the preset function relationship is specifically:

[0045]

[0046] Among them, i gis the transmission ratio from the output shaft to the auxiliary motor. When a solution is adopted in which a sensor is added at a position less affected by external environment such as the input end, the g() function varies according to the situation, and the embodiments of the present application are applicable.

[0047] Taking into account the measurement error of the output shaft-related data and the errors such as the wear of the transmission system, the above equation is Taylor expanded to obtain the state equation of the embodiment of the present application:

[0048] N k =f(N k-1 )+Q=N k-1 +g′(n′ k-1 )·(n′ k -n′ k-1 )+Q,Q~N(0,σ Q );

[0049] Among them, N k is the output shaft speed at time k, which is considered to be a random variable, not a definite value, n′ k is the value of the output axis associated data at time k, g′(n′ k-1 ) is the derivative value of the functional relationship from the output shaft associated data to the output shaft speed at time k-1, Q is the error of the state equation, which is a preset range value, considering that it obeys Gaussian distribution, σ Q is its variance.

[0050] The embodiment of the present application uses the sensor measurement data of the gearbox output shaft, that is, the output shaft speed measurement data as observation, so the observation equation is:

[0051] Y k =h(N k )+R,R~N(0,σ R );

[0052] Among them, h(N k ) is the functional relationship from the output shaft speed to the sensor output value at time k, R is the observation error caused by the sensor measurement accuracy, is a preset value, determined according to the sensor used, usually a range value, considering that it obeys Gaussian distribution, σ R is its variance. k is the sensor observation output data, which is considered to be a random variable.

[0053] In this way, according to the above technical solution, the preparation work before sensor data fusion is completed, providing a basis for subsequent sensor fusion.

[0054] In an embodiment of the present application, based on a particle filtering algorithm, the output shaft speed measurement data is corrected according to the output shaft speed associated data to obtain a corrected output shaft speed, including: based on a predetermined state equation, determining the output shaft speed calculation value according to the output shaft speed associated data; using the output shaft speed calculation value as the initial value of the random variable, and based on the particle filtering algorithm and the predetermined observation equation, obtaining the probability density function after the output shaft speed is fused; determining the corrected output shaft speed according to the output shaft speed associated data and the probability density function after the output shaft speed is fused.

[0055] Specifically, Figure 2 This is a flow chart of particle filter data fusion provided by a specific embodiment of the present application. Figure 2 As shown, based on the particle filtering algorithm, data fusion of the output shaft speed associated data and the output shaft speed measurement data may include the following steps:

[0056] 1. Initial value of the state equation.

[0057] Specifically, based on the above state equation, the output shaft speed calculated value is calculated according to the output shaft speed associated data, where the output shaft speed associated data refers to the measurement value collected by the sensor at the current moment or the previous historical moment. The time when data fusion starts is defined as time 0, and the output shaft speed calculated value at time 0 is defined as the initial value of the random variable N 0 , which obeys Gaussian distribution.

[0058] 2. Particle sampling.

[0059] Specifically, generate N 0 n sample particles: And generate the corresponding weights of the initial value sample particles The output weights are all set to 1 / n. represents the i-th particle at time 0, represents the weight of the i-th particle at time 0.

[0060] 3. Update the prediction step.

[0061] Specifically, the prediction step is updated to generate the next moment N 1 Sample particles:

[0062]

[0063] Wherein, f() is the aforementioned predetermined state equation functional relationship, and Q is the error of the aforementioned state equation.

[0064] At this time, the predicted value N 1 The probability density function of is:

[0065]

[0066] Among them, δ() is the Dirichlet function, represents the i-th particle at time 1. This process actually changes the position of the sample particle, but the weight of the sample particle remains unchanged.

[0067] 4. Observation step update.

[0068] Specifically, the weight of the sample particle is updated by introducing the transmission output shaft speed measurement value as the observation quantity. Suppose the sensor observation data y at the current moment is 1 , the probability density function of the speed prediction value should be:

[0069]

[0070] Where, H() is the observation equation function relationship determined above, y 1 is the sensor observation data, f R () is the PDF (probability density function) of the random error caused by sensor accuracy, corresponding to the aforementioned random variable R. According to the above, it is in the form of a Gaussian distribution with a mean of 0 and a variance determined by the sensor parameters as σ R η is the normalization parameter.

[0071] make

[0072] Then we have:

[0073]

[0074] At this point, the speed measurement value of the gearbox output shaft Hall sensor and the output shaft speed correlation value are data fused.

[0075] 5. Particle resampling.

[0076] Specifically, in order to avoid particle degradation, when it is determined that the weight of each particle reaches a set threshold, the sample particles are resampled through a resampling algorithm, and then the output shaft speed is calculated at a subsequent moment.

[0077] Finally, the corrected output shaft speed is determined according to the speed prediction probability density function. Specifically, the corrected output shaft speed of the gearbox at time k is the expectation of the speed prediction probability density function, and the specific result is shown in the following formula:

[0078]

[0079] in, is the expected output shaft speed after correction, is the position of the i-th sampled particle at time k, which is updated through the third prediction step; is the weight of the ith particle at time k, which is updated through the observation step in the fourth step.

[0080] In this way, multi-source data fusion is performed through the particle filtering algorithm, which improves the accuracy of the output shaft speed measurement data of the gearbox and significantly reduces the variance of the random variable of the measured speed.

[0081] In the embodiment of the present application, the target gear information includes the target gear set transmission ratio and the preset speed difference, and the preset speed difference is the allowable value of the speed difference between the coupling sleeve and the target gear; according to the corrected output shaft speed and the target gear information, it is determined that the target motor speed of the drive motor satisfies the following formula:

[0082] n target =n 0 ·i±Δn;

[0083] Among them, n target is the target motor speed, n 0 is the corrected output shaft speed, i is the target gear set transmission ratio, and Δn is the preset speed difference.

[0084] It can be understood that, in general, the target motor speed is determined based on the transmission ratio of the gearbox and the output shaft speed. However, in the actual operation process, the speed of the drive motor may also be affected by other factors, such as the load, efficiency, temperature, etc. of the motor. Therefore, in order to improve the accuracy of the target motor speed calculation, the embodiment of the present application further adjusts and optimizes the calculation of the target motor speed according to the characteristics of the motor. The target gear information in the embodiment of the present application may include the target gear set transmission ratio and the allowable value of the speed difference between the coupling sleeve and the target gear, both of which are determined according to the actual situation of the vehicle. In this way, the target motor speed calculated based on the above formula is more accurate.

[0085] In an embodiment of the present application, the drive motor is controlled according to the target motor speed so that the gear position of the vehicle reaches the target gear position, including: obtaining the current motor speed of the drive motor; determining the target control torque of the drive motor according to the target motor speed and the current motor speed; adjusting the speed of the drive motor to the target motor speed according to the target control torque so that the gear position of the vehicle reaches the target gear position.

[0086] It can be understood that after determining the target motor speed, in order to adjust the motor speed to the target speed, the corresponding target control torque needs to be determined. The target control torque is the output torque of the drive motor corresponding to when the motor speed reaches the target motor speed. Specifically, the embodiment of the present application can adopt a PID control method to obtain the current motor speed of the drive motor, and then calculate the motor speed difference based on the current motor speed and the target motor speed, and then input the motor speed difference into the PID control model, and calculate the corresponding target control torque in combination with the preset PID control parameters. Among them, the PID control parameters can be pre-set according to the vehicle situation. Finally, the input current of the drive motor is adjusted according to the target control torque, and then the motor speed of the drive motor is adjusted so that the drive motor reaches the target motor speed, so that the gear position of the vehicle reaches the target gear position.

[0087] In an embodiment of the present application, the vehicle adopts PID control to determine the target control torque of the drive motor according to the target motor speed and the current motor speed, including: obtaining the current operating condition data of the vehicle; determining the target control parameters of the PID controller according to the current operating condition data based on a pre-built control parameter adaptive model, the control parameter adaptive model is used to output the control parameters corresponding to the operating condition data according to the input operating condition data; determining the motor speed difference of the drive motor according to the current motor speed and the target motor speed; based on the PID control model, determining the target control torque according to the motor speed difference and the target control parameters according to the PID control model.

[0088] In an embodiment of the present application, a method for constructing a control parameter adaptive model includes: obtaining multiple sample data, the sample data including operating condition data and control parameters corresponding to the operating condition data; establishing a neural network model; and training the neural network model based on the multiple sample data to obtain a control parameter adaptive model.

[0089] Specifically, the vehicle in the embodiment of the present application adopts the PID control method. It can be understood that according to the above-mentioned formula for determining the target motor speed, the speed regulation time of the drive motor is as follows:

[0090]

[0091] Among them, n current is the current motor speed of the drive motor, is the acceleration of the drive motor, J in is the moment of inertia of the output shaft of the drive motor, T m is the output torque of the driving motor, i 1 with i 2They are transmission ratios of different gears. It can be seen from the above formula that the speed regulation time of the drive motor is related to the output torque of the motor. The PID controller can well control the drive motor to quickly and accurately reach the specified target motor speed. The PID control method is shown in the following formula:

[0092]

[0093] err = n targer -n current ;

[0094] Where err is the speed difference between the current motor speed and the target motor speed, K P , K I and K D are the three control parameters of the PID control algorithm.

[0095] Since the three control parameters of the drive motor PID controller will change with different working conditions, the speed regulation effect of the drive motor will be different from the bench test effect, which will also lead to an increase in gear shifting time or gear shifting failure. Therefore, in order to allow the drive motor to quickly adjust to the target motor speed, in addition to quickly and accurately measuring the output shaft speed of the gearbox, it is also necessary to adaptively adjust the PID control parameters of the drive motor according to different working conditions. In this regard, the embodiment of the present application constructs a control parameter adaptive model to determine the optimal control parameters corresponding to different working condition data, so as to achieve accurate and rapid control of the motor speed of the drive motor under different vehicle working conditions.

[0096] Specifically, the construction of the control parameter adaptive model may include the following steps:

[0097] 1. Determine the operating data that affects the control effect of the drive motor.

[0098] 2. Conduct bench tests.

[0099] 3. Evaluate the drive motor speed control curve indicators based on the test results.

[0100] 4. Determine the optimal PID model control parameters corresponding to different operating condition data to obtain sample data, which includes the operating condition data and the control parameters corresponding to the operating condition data.

[0101] 5. Establish a neural network model. The training input of the neural network model is different operating conditions data, and the output is the optimal PID model control parameters corresponding to each operating condition data. The neural network model is trained according to the sample data to obtain a constructed control parameter adaptive model.

[0102] In this way, the control parameter adaptive model can output adaptive PID control parameters to the controller according to different working conditions, so as to achieve accurate and rapid control of the motor speed of the drive motor under different vehicle working conditions.

[0103] It should be noted that the present invention performs multi-source data fusion through a particle filtering algorithm, thereby improving the accuracy of the measured value of the gearbox output shaft speed, significantly reducing the variance of the measured speed random variable, and constructing an adaptive parameter adjustment model of the PID controller through a neural network, thereby ensuring that the drive motor reaches the target speed quickly and accurately, saving shifting time and improving the shifting success rate.

[0104] The method for controlling vehicle gear shifting provided in the present application can be used for a power-shift AMT gearbox. When the auxiliary motor performs torque compensation, the auxiliary motor speed and the output shaft sensor data are integrated in the embodiment of the present application to obtain a highly reliable gearbox output shaft speed, and then the drive motor speed is controlled by a parameter-adaptive PID controller.

[0105] The method for controlling vehicle gear shifting provided in the present application can also be used in conventional AMT gearboxes. By arranging a Hall sensor at a position with little interference such as the input shaft or the intermediate shaft, the gearbox output shaft related data is obtained, and then the output shaft sensor data is integrated with it through the method of the present application to obtain a highly reliable gearbox output shaft speed, and then the drive motor speed is controlled by a parameter adaptive PID controller.

[0106] An embodiment of the present application also provides a processor configured to execute the method for controlling vehicle gear shifting in the above-mentioned implementation.

[0107] An embodiment of the present application also provides a vehicle, including: a gearbox, the gearbox including an output shaft; a drive motor; and the processor in the above embodiment.

[0108] An embodiment of the present application also provides a machine-readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the method for controlling vehicle gear shifting in the above-mentioned embodiment is implemented.

[0109] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0110] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0111] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0112] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0113] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0114] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0115] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0116] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0117] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for controlling vehicle gear shifting, characterized in that: The vehicle comprises a gearbox and a drive motor, the gearbox comprises an output shaft, and the method comprises: Obtaining target gear information of the vehicle, output shaft speed measurement data of the output shaft at the current moment, and output shaft speed related data; Based on a particle filter algorithm, the output shaft speed measurement data is corrected according to the output shaft speed associated data to obtain a corrected output shaft speed; Determining a target motor speed of the drive motor according to the corrected output shaft speed and the target gear information; The drive motor is controlled according to the target motor speed so that the gear position of the vehicle reaches the target gear position.

2. The method according to claim 1, characterized in that The method of correcting the output shaft speed measurement data based on the output shaft speed associated data based on the particle filter algorithm to obtain a corrected output shaft speed includes: Based on a predetermined state equation, determining a calculated value of the output shaft speed according to the output shaft speed associated data; The calculated value of the output shaft speed is used as the initial value of the random variable, and based on the particle filter algorithm and the predetermined observation equation, a probability density function of the output shaft speed after fusion is obtained; The corrected output shaft speed is determined according to the output shaft speed associated data and the probability density function after the output shaft speed is fused.

3. The method according to claim 2, characterized in that The method for determining the state equation and the observation equation includes: Acquire a preset functional relationship between the output shaft speed measurement data and the output shaft speed correlation data; Performing Taylor expansion processing on the preset functional relationship to obtain the state equation; The observation equation is determined according to a preset observation error amount.

4. The method according to claim 1, characterized in that The target gear information includes a target gear set transmission ratio and a preset speed difference, wherein the preset speed difference is an allowable value of a speed difference between the coupling sleeve and the target gear; The target motor speed of the drive motor is determined to satisfy the following formula according to the corrected output shaft speed and the target gear information: a target =n0·i±Δn; Among them, n target is the target motor speed, n0 is the corrected output shaft speed, i is the target gear set transmission ratio, and Δn is the preset speed difference.

5. The method according to claim 1, characterized in that The step of controlling the drive motor according to the target motor speed so that the gear position of the vehicle reaches the target gear position includes: Obtaining the current motor speed of the drive motor; Determining a target control torque of the drive motor according to the target motor speed and the current motor speed; The speed of the drive motor is adjusted to the target motor speed according to the target control torque, so that the gear position of the vehicle reaches the target gear position.

6. The method according to claim 5, characterized in that The vehicle adopts PID control, and the target control torque of the drive motor is determined according to the target motor speed and the current motor speed, including: Acquiring current operating condition data of the vehicle; Based on a pre-built control parameter adaptive model, a target control parameter of a PID controller is determined according to the current operating condition data, wherein the control parameter adaptive model is used to output a control parameter corresponding to the operating condition data according to the input operating condition data; Determining a motor speed difference of the drive motor according to the current motor speed and the target motor speed; Based on a PID control model, the target control torque is determined according to the motor speed difference and the target control parameter according to the PID control model.

7. The method according to claim 6, characterized in that The method for constructing the control parameter adaptive model includes: Acquire a plurality of sample data, wherein the sample data includes operating condition data and control parameters corresponding to the operating condition data; Build a neural network model; The neural network model is trained according to the plurality of sample data to obtain the control parameter adaptive model.

8. A processor, characterized in that: The method is configured to execute the method for controlling vehicle gear shifting according to any one of claims 1 to 7.

9. A vehicle, characterized in that: include: a gearbox, the gearbox comprising an output shaft; Drive motor; A processor according to claim 8.

10. A machine-readable storage medium storing a program or an instruction, characterized in that: When the program or the instruction is executed by a processor, the method for controlling vehicle gear shifting according to any one of claims 1 to 7 is implemented.

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