Motor speed regulation control method and device, vehicle, equipment and medium

Abstract

The invention discloses a motor speed regulation control method and device, a vehicle, equipment and a medium. The motor speed regulation control method comprises the steps that a voltage real signal of a motor at the current moment and a current real signal of the motor at the current moment are obtained; obtaining the back electromotive force of the motor based on the voltage real signal at the current moment and the current real signal at the current moment; based on the back electromotive force of the motor, obtaining a motor observation rotating speed of the motor at the current moment; determining a rotating speed deviation based on the motor expected rotating speed and the motor observed rotating speed at the current moment; obtaining an initial control parameter of the motor current signal and correction information of the initial control parameter based on the rotating speed deviation; and obtaining a target control parameter based on the initial control parameter and the correction information, obtaining a current signal at the next moment based on the target control parameter, and controlling the rotating speed of the motor based on the current signal at the next moment.

Description

Technical Field

[0001] The present application relates to the technical fields of electric vehicles, motors, etc., and in particular to a motor speed control method, device, vehicle, equipment and medium. Background Art

[0002] With the widespread use of electric vehicles, electric drive systems, as the power source of electric vehicles, have received widespread attention. Permanent-magnet synchronous motor (PMSM) is the most commonly used motor in electric drive systems of electric vehicles. How to optimize the permanent-magnet synchronous motor speed control system to improve the power performance of electric vehicles has become a research focus.

[0003] Related technologies Permanent magnet synchronous motors use position sensors (such as rotary transformers and eddy current sensors) to obtain the motor rotor position, and then obtain the motor speed, and control the motor speed through a controller. The use of position observers increases costs, and when the controller has insufficient control accuracy or severe jitter, it will cause safety problems. Summary of the invention

[0004] The embodiments of the present application aim to solve at least one of the technical problems in the related art to a certain extent. To this end, the embodiment of the present application aims to provide a motor speed control method, device, vehicle, equipment and medium.

[0005] The embodiment of the present application provides a motor speed control method, which includes: obtaining a real voltage signal and a real current signal of the motor at a current moment; obtaining the back electromotive force of the motor based on the real voltage signal and the real current signal at a current moment; obtaining the observed speed of the motor at a current moment based on the back electromotive force of the motor; determining the speed deviation based on the expected speed of the motor and the observed speed of the motor at a current moment; obtaining initial control parameters of the motor current signal and correction information of the initial control parameters based on the speed deviation; obtaining target control parameters based on the initial control parameters and the correction information, and obtaining the current signal at the next moment based on the target control parameters, and controlling the speed of the motor based on the current signal at the next moment.

[0006] Exemplarily, based on the back electromotive force of the motor, the motor observed speed at the current moment is obtained, including: based on the back electromotive force of the motor, obtaining the rotor position information of the motor; based on the rotor position information, obtaining the motor observed speed of the motor at the current moment.

[0007] Exemplarily, obtaining the back electromotive force of the motor based on the real voltage signal at the current moment and the real current signal at the current moment includes: estimating the current estimation signal at the current moment based on the real voltage signal at the current moment; obtaining the current error signal based on the current estimation signal at the current moment and the real current signal at the current moment; and processing the current error signal based on a preset correlation relationship to obtain the back electromotive force of the motor.

[0008] Exemplarily, the preset association relationship includes a functional relationship between the back electromotive force and the current signal error, the functional relationship includes at least one of an integral function and a switching function, the integral function is used to perform time integration on the current error signal, the variable of the switching function is the current signal error, and the mutation degree of the switching function is less than the preset mutation degree.

[0009] Exemplarily, after the switching function processes the current signal error to obtain a processing result, the processing result is integrated by an integral function, wherein the switching function includes a hyperbolic tangent function.

[0010] Exemplarily, based on the speed deviation, initial control parameters of the motor current signal and correction information of the initial control parameters are obtained, including: obtaining the initial control parameters based on the speed deviation; obtaining the rate of change of the speed deviation based on the speed deviation; obtaining correction information of the initial control parameters based on the speed deviation and the rate of change of the speed deviation.

[0011] Exemplarily, based on the speed deviation and the rate of change of the speed deviation, correction information of the initial control parameters is obtained, including: based on the speed deviation and the rate of change of the speed deviation, obtaining a fuzzy value of the speed deviation and a fuzzy value of the rate of change; using preset fuzzy rules, based on the fuzzy value of the speed deviation and the fuzzy value of the rate of change, obtaining the fuzzy value of the correction information; based on the fuzzy value of the correction information, obtaining the correction information.

[0012] Exemplarily, the initial control parameters include a proportional initial coefficient, an initial differential coefficient, and an initial integral coefficient; the correction information includes a proportional correction value, a differential correction value, and an integral correction value; the target control parameters include a target initial coefficient, a target differential coefficient, and a target integral coefficient; based on the initial control parameters and the correction information, the target control parameters are obtained, and based on the target control parameters, the current signal at the next moment is obtained, including: adding the initial proportional coefficient, the initial differential coefficient, and the initial integral coefficient to the proportional correction value, the differential correction value, and the integral correction value, respectively, to obtain the target proportional coefficient, the target differential coefficient, and the target integral coefficient; processing the speed deviation based on the target proportional coefficient to obtain the proportional term of the current signal; processing the rate of change of the speed deviation based on the target differential coefficient to obtain the differential term of the current signal; processing the integral data of the speed deviation based on the target integral coefficient to obtain the integral term of the current signal; obtaining the current signal at the next moment based on the proportional term of the current signal, the differential term of the current signal, and the integral term of the current signal.

[0013] Another embodiment of the present application provides a motor speed control device, which includes: an acquisition module, which is used to acquire the real voltage signal and the real current signal of the motor at the current moment; a first acquisition module, which is used to obtain the back electromotive force of the motor based on the real voltage signal and the real current signal at the current moment; a second acquisition module, which is used to obtain the observed motor speed of the motor at the current moment based on the back electromotive force of the motor; a determination module, which is used to determine the speed deviation based on the expected motor speed and the observed motor speed at the current moment; a third acquisition module, which obtains the initial control parameters of the motor current signal and the correction information of the initial control parameters based on the speed deviation; a fourth acquisition module, which obtains the target control parameters based on the initial control parameters and the correction information, and obtains the current signal at the next moment based on the target control parameters; a control module, which is used to control the speed of the motor based on the current signal at the next moment.

[0014] Another embodiment of the present application provides a vehicle, which is used to implement the steps of the method of any of the above embodiments.

[0015] Another embodiment of the present application provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method of any of the above embodiments when executing the computer program.

[0016] Another embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the method of any of the above embodiments are implemented.

[0017] In the above implementation, by obtaining the real voltage signal and the real current signal of the motor at the current moment; based on the real voltage signal and the real current signal at the current moment, the back electromotive force of the motor is obtained, and based on the back electromotive force of the motor, the observed motor speed of the motor at the current moment is obtained, thereby avoiding the use of traditional position sensors and reducing costs. And based on the expected motor speed and the observed motor speed at the current moment, the speed deviation is determined, based on the speed deviation, the initial control parameters of the motor current signal and the correction information of the initial control parameters are obtained, based on the initial control parameters and the correction information, the target control parameters are obtained, and based on the target control parameters, the current signal at the next moment is obtained, and the speed of the motor is controlled based on the current signal at the next moment; the control parameters are corrected by observing the speed and the speed deviation, so that the motor can control the motor speed more accurately, thereby improving the anti-interference performance of the motor speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A flow chart of a motor speed control method provided in an embodiment of the present application;

[0019] Figure 2 A schematic diagram of the rotor position detection of a super spiral sliding mode observer provided in the embodiment of the present application;

[0020] Figure 3 A schematic diagram of the fuzzy PID control structure provided for the implementation method of the present application;

[0021] Figure 4 A comparison diagram of the estimated position and the actual position based on the improved super-helical sliding mode observer provided in the embodiment of the present application;

[0022] Figure 5 A comparison diagram of the speed response characteristic curves of the permanent magnet synchronous motor under no-load and load mutation conditions provided in the embodiment of the present application;

[0023] Figure 6 A comparison diagram of the speed response characteristic curves of a permanent magnet synchronous motor under variable speed conditions provided in an embodiment of the present application;

[0024] Figure 7 A block diagram of a motor speed control device provided in another embodiment of the present application. DETAILED DESCRIPTION

[0025] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0026] With the widespread use of electric vehicles, electric drive systems, as the power source of electric vehicles, have received widespread attention. Permanent-magnet synchronous motor (PMSM) is the most commonly used motor in electric drive systems of electric vehicles. How to optimize the permanent-magnet synchronous motor speed control system to improve the power performance of electric vehicles has become a research focus.

[0027] In some examples, permanent magnet synchronous motors use position sensors (such as resolvers, eddy current sensors) to obtain the motor rotor position, and then obtain the motor speed, and use a PID controller (proportion-integration-differentiation) to control the motor speed. The use of position observers increases costs, and when the electric drive system frequently switches operating modes, the use of PID controllers will cause safety issues, and sudden load changes will weaken the power performance of permanent magnet synchronous motors.

[0028] In some examples, a sliding mode observer can be used to estimate the back EMF of the motor to obtain the position information of the rotor. Since the back EMF signal observed by the sliding mode observer contains a large number of discontinuous signals, a low-pass filter is needed to filter out these high-frequency signals to obtain a smooth back EMF waveform, but at the same time, it will cause phase lag problems and jitter, resulting in errors in the rotor position estimation, which in turn affects the accuracy of the permanent magnet synchronous motor speed control system.

[0029] In view of this, an embodiment of the present application provides a motor speed control method, which uses an improved super-helical sliding mode observer to replace the mainstream rotary transformers, eddy current sensors and other position sensors in the electric vehicle market to detect the motor rotor position, thereby reducing the cost of use, and uses a fuzzy PID speed controller to replace the common PID controller, thereby improving the speed interference resistance of the permanent magnet synchronous motor in the electric drive system.

[0030] Figure 1 A flow chart of a motor speed control method provided in an embodiment of the present application.

[0031] like Figure 1 As shown, the motor speed control method 100 provided in the embodiment of the present application includes, for example, steps S110 - S160 .

[0032] Step S110, obtaining the current real voltage signal and the current real current signal of the motor.

[0033] Exemplarily, actual voltage and current signal values ​​of a motor (permanent magnet synchronous motor) in an electric drive system of an electric vehicle are obtained.

[0034] Step S120, obtaining the back electromotive force of the motor based on the current voltage real signal and the current real signal.

[0035] Exemplarily, based on the obtained real voltage signal at the current moment and the real current signal at the current moment, they are input into a constructed mathematical model (such as including a super-helical sliding mode observer), and the back electromotive force of the motor can be obtained through calculation.

[0036] Step S130, based on the back electromotive force of the motor, the observed speed of the motor at the current moment is obtained.

[0037] Exemplarily, the position of the rotor can be obtained by performing relevant calculations based on the obtained back electromotive force of the motor. Since the position of the rotor changes with the change of the rotational speed, the observed rotational speed of the motor can be obtained based on the change of the rotor position.

[0038] Step S140, determining a speed deviation based on the expected speed of the motor and the observed speed of the motor at the current moment.

[0039] For example, usually, there is a deviation between the actual rotation speed of the motor and the expected rotation speed, and the rotation speed deviation can be obtained by calculating the difference between the two.

[0040] Step S150: obtaining initial control parameters of the motor current signal and correction information of the initial control parameters based on the rotational speed deviation.

[0041] Exemplarily, the obtained motor speed and speed deviation are input into a controller (e.g., a fuzzy PID controller), and according to the calculation rules of the fuzzy PID controller, the initial control parameters of the motor current signal and the correction values ​​of the motor current signal control parameters can be obtained. The fuzzy PID controller may include a basic PID controller or a traditional PID controller, and the initial control parameters can be obtained based on the speed deviation using the basic PID controller or the traditional PID controller.

[0042] Step S160, based on the initial control parameters and the correction information, the target control parameters are obtained, and based on the target control parameters, the current signal at the next moment is obtained, and the speed of the motor is controlled based on the current signal at the next moment.

[0043] Exemplarily, the final target control parameters can be obtained based on the correction value and initial control parameters obtained by the fuzzy PID controller. For example, the initial controller is corrected based on the correction value to obtain the target control parameter, and the current signal at the next moment is obtained based on the target control parameter. Finally, the current signal is input into the motor, so that the speed of the motor is controlled according to the current.

[0044] In the above embodiment, according to the real voltage signal at the current moment and the real current signal at the current moment, the position of the motor rotor can be obtained by inputting them into the super sliding mode observer, which replaces the position sensor (i.e., rotary transformer, eddy current sensor) used in the permanent magnet synchronous motor in the electric drive system of the electric vehicle, and plays a role in reducing costs. The super spiral sliding mode observer solves the phase lag problem. In addition, a fuzzy PID controller is used to replace the basic PID controller or the traditional PID controller, and the initial control parameters obtained by the basic PID controller or the traditional PID controller are corrected by the correction value, which improves the accuracy of the initial control parameters, has a good control effect, and improves the speed interference resistance of the permanent magnet synchronous motor in the electric drive system of the electric vehicle.

[0045] Figure 2 This is a schematic diagram of the rotor position detection principle of the super spiral sliding mode observer provided in the implementation mode of the present application.

[0046] like Figure 2 As shown, u α 、u β is the real voltage signal (actual voltage) of the motor at the current moment, i α 、i β is the real current signal (actual current) of the motor at the current moment, is the estimated value of back EMF, To estimate the current, To estimate the difference between the current and the actual current, is the estimated rotor position, and the subscripts α and β represent the values ​​of the α-axis and β-axis in the α-β coordinate system, respectively. The construction method of the super-helical sliding mode observer is as follows:

[0047] The super-twisting sliding mode observer can be constructed by applying the super-twisting sliding mode control algorithm (Super-Twisting Sliding Mode Control) to the sliding mode observer based on the mathematical model of the permanent magnet synchronous motor.

[0048] The super-helical sliding mode control algorithm expression is shown in formula (1):

[0049]

[0050] In formula (1), K1 and K2 are the gains of the sliding mode observer and both K1 and K2 are greater than 0, x1 and x2 represent state quantities, sgn() represents the sign function, and ρ1(x1,t) and ρ2(x2,t) represent external interference.

[0051] The super-helical sliding mode control algorithm is applied to the sliding mode observer. The design process is consistent with the conventional sliding mode observer. The super-helical sliding mode observer can be constructed as shown in formula (2):

[0052]

[0053] In formula (2), Represents the estimated current, R S , L S Represent the motor resistance and motor inductance respectively, sgn() represents the sign function, u α 、u β Represents the voltage of the motor, To estimate the difference between the current and the actual current, K1 and K2 are constants.

[0054] The mathematical model expression of the permanent magnet synchronous motor in the two-phase static coordinate system (i.e., the α-β coordinate system) is shown in formula (3):

[0055]

[0056] Subtracting formula (2) from formula (3), we can get formula (4):

[0057]

[0058] According to the above formula, the back electromotive force estimated by the super spiral sliding mode observer can be calculated as shown in formula (5), where K 1α , K 1β , K 2α , K 2β is a constant:

[0059]

[0060] As shown in formula (5), the switching function is the sgn() sign function. The implementation method of this specification uses the hyperbolic tangent function, which is shown in formula (6):

[0061]

[0062] in, α The curve coefficients representing the hyperbolic tangent function can be converted into the following form according to the hyperbolic tangent function formula (6):

[0063]

[0064] The back electromotive force can be obtained

[0065] Based on the real voltage signal at the current moment and the real current signal at the current moment, the back electromotive force of the motor is obtained, including: estimating the current estimation signal at the current moment based on the real voltage signal at the current moment; obtaining the current error signal based on the current estimation signal at the current moment and the real current signal at the current moment; processing the current error signal based on a preset correlation relationship to obtain the back electromotive force of the motor.

[0066] For example, Figure 2 As shown, the motor voltage u at the current moment α 、u β And the current motor current i α 、i β Input the super spiral sliding mode observer, and get the estimated current through the state prediction of the super spiral sliding mode observer The estimated current The real current i at the current moment α 、i β The current error signal is obtained by subtracting right Based on the preset relationship, the back electromotive force of the motor is obtained. When updating, the current moment calculated Replace the observer at the previous moment

[0067] The preset association relationship includes a functional relationship between the back electromotive force and the current signal error (such as formula 7), the functional relationship includes at least one of an integral function and a switching function, and the integral function is used to perform time integration on the current error signal (such as in formula 7). and The variable of the switching function is the current signal error, and the mutation degree of the switching function is less than the preset mutation degree.

[0068] Exemplarily, after the current signal error is processed by the switching function to obtain a processing result, the processing result is integrated by an integral function, wherein the switching function includes a hyperbolic tangent function.

[0069] For example, Figure 2 As shown, the current error signal After the switch function processing (after the switch function processing, such as referring to formula 7 and Then the processing result is integrated by the integral function (such as in formula 7 and The back electromotive force of the motor can be calculated by formula 7

[0070] Based on the back electromotive force of the motor, the motor observed speed at the current moment is obtained, including: based on the back electromotive force of the motor, the motor rotor position information is obtained; based on the rotor position information, the motor observed speed at the current moment is obtained.

[0071] For example, Figure 2 As shown, the back electromotive force is obtained by the super spiral sliding mode observer Based on the principle of the inverse tangent function, the inverse tangent of the back electromotive force needs to be solved to extract the rotor position information. Since the position change of the rotor at a certain moment is closely related to its speed change, according to the rotor position information The actual speed of the motor can be obtained.

[0072] In the above embodiment, the super-helical sliding mode control algorithm is used to improve the sliding mode observer, and a super-helical sliding mode observer is constructed. Since the super-helical algorithm itself contains an integral term, the low-pass filter can be omitted in its structural design, thereby solving the phase lag problem caused by the low-pass filter. In addition, the switching function of the super-helical sliding mode observer uses a hyperbolic tangent function instead of a sign function, thereby reducing the occurrence of chattering.

[0073] Figure 3 A schematic diagram of the fuzzy PID control structure provided for the implementation mode of the present application.

[0074] like Figure 3 As shown, n r is the expected value of the motor speed output by the controller, n is the actual value of the motor speed, e is the error between the expected value of the motor speed and the actual value of the motor speed, e c is the deviation change rate, and the actual value of the motor speed n is based on the rotor position information For example, the rotor position information The relevant conversion is performed to obtain the real value n of the motor speed. Fuzzy PID control is to use fuzzy control to control K in the PID controller. p , K i , K d Correction is performed, where the input is the error e and the error change rate e c , the fuzzy controller output is the PID correction value, that is, △K p , △K i , △K d , and compare it with the output of the traditional PID controller Combined with other control parameters, the correction of control parameters can be realized.

[0075] Based on the speed deviation, the initial control parameters of the motor current signal and the correction information of the initial control parameters are obtained, including: obtaining the initial control parameters based on the speed deviation; obtaining the rate of change of the speed deviation based on the speed deviation; obtaining the correction information of the initial control parameters based on the speed deviation and the rate of change of the speed deviation.

[0076] Exemplarily, based on the speed deviation and the rate of change of the speed deviation, correction information of the initial control parameters is obtained, including: based on the speed deviation and the rate of change of the speed deviation, obtaining a fuzzy value of the speed deviation and a fuzzy value of the rate of change; using preset fuzzy rules, based on the fuzzy value of the speed deviation and the fuzzy value of the rate of change, obtaining the fuzzy value of the correction information; based on the fuzzy value of the correction information, obtaining the correction information.

[0077] For example, Figure 3 As shown, according to the speed deviation e between the motor speed expected value nr and the motor speed actual value n, the deviation change rate e is calculated c , based on the speed deviation e, the initial control parameters can be obtained The speed deviation e and the deviation change rate e c Fuzzy processing is performed to obtain the fuzzy value E of the speed deviation and the fuzzy value Ec of the rate of change, and the PID correction value is obtained based on the fuzzy rules. For example, fuzzy reasoning is performed based on E and Ec using the rules in the fuzzy rule base to obtain the correction information △K p , △K i , △K d The corresponding fuzzy value for △K p , △K i , △K d The corresponding fuzzy value is defuzzified to obtain the correction information, which includes △K p , △K i , △K d (precise value), then △K p , △K i , △K d Input to the PID controller.

[0078] In the above embodiment, a fuzzy PID speed controller is used to control the motor speed. Since fuzzy control does not require an accurate model of the controlled object, it has a good control effect on the controlled object with nonlinear characteristics such as the permanent magnet synchronous motor, improves the safety problems caused by the frequent operating mode switching of the electric drive system and the weakening of the power performance caused by the sudden change of load, and improves the speed interference resistance of the permanent magnet synchronous motor in the electric drive system of the electric vehicle.

[0079] The initial control parameters include an initial proportional coefficient, an initial differential coefficient, and an initial integral coefficient; the correction information includes a proportional correction value, a differential correction value, and an integral correction value; the target control parameters include a target initial coefficient, a target differential coefficient, and a target integral coefficient; based on the initial control parameters and the correction information, the target control parameters are obtained, and based on the target control parameters, the current signal at the next moment is obtained, including: adding the initial proportional coefficient, the initial differential coefficient, and the initial integral coefficient to the proportional correction value, the differential correction value, and the integral correction value, respectively, to obtain the target proportional coefficient, the target differential coefficient, and the target integral coefficient; processing the speed deviation based on the target proportional coefficient to obtain the proportional term of the current signal; processing the rate of change of the speed deviation based on the target differential coefficient to obtain the differential term of the current signal; processing the integral data of the speed deviation based on the target integral coefficient to obtain the integral term of the current signal; obtaining the current signal at the next moment based on the proportional term of the current signal, the differential term of the current signal, and the integral term of the current signal.

[0080] For example, according to the initial coefficient of the ratio Initial differential coefficient Initial integration coefficient And the proportional correction value △K p , differential correction value △K i , integral correction value △K d , we can get the target proportionality coefficient K p 、Target differential coefficient K i , target integral coefficient K d .

[0081] For example, at the Nth sampling time, the three parameters of proportion, integration and differentiation after being processed by the PID controller are shown in formula (8):

[0082]

[0083] In formula (8), is the initial value of PID control parameter (initial control parameter); △K p , △K i , △K d It is the PID correction value after fuzzy rule processing.

[0084] According to the output K of the fuzzy PID controller p , K i , K d (target control parameter) to control the controlled object. p , K i , K dThe error e is processed separately to obtain the proportional term, integral term and differential term of the error e, and the output result of PID control (the output result is, for example, the current of the motor) is obtained based on the proportional term, integral term and differential term. The current is input into the motor to control the rotation of the motor so that the speed of the motor is n.

[0085] In the above embodiment, the output result of PID control is obtained based on proportion, integration and differentiation, so that the calculation result is more accurate and has a good control effect.

[0086] Figure 4 A comparison diagram of the estimated position and the actual position based on the improved super-helical sliding mode observer provided in the embodiment of the present application, Figure 5 This is a comparison diagram of the speed response characteristic curves of the permanent magnet synchronous motor under no-load and load mutation conditions provided in the implementation manner of the present application. Figure 6 A comparison diagram of the speed response characteristic curves of a permanent magnet synchronous motor under variable speed conditions provided in an embodiment of the present application.

[0087] like Figure 4 As shown in the figure, the horizontal axis represents time and the vertical axis represents the rotor position. It can be seen from the figure that the estimated position based on the improved super-helical sliding mode observer is very close to the actual position, which proves that the improved super-helical sliding mode observer can reduce the estimation error and the rotor position estimation accuracy is higher. Figure 5 , Figure 6 As shown, the horizontal axis represents time and the vertical axis represents the speed. It can be seen from the figure that compared with the PMSM speed control system based on traditional PID control, the PMSM speed control system based on fuzzy PID control has a more stable speed response and better control effect under no-load and load mutation conditions and variable speed conditions.

[0088] The present invention is based on an improved super-helical sliding mode observer to replace position sensors such as electric rotary transformers / eddy current sensors. Compared with the first-order sliding mode observer, the super-helical sliding mode observer contains an integral term, and the low-pass filter can be omitted in structure, which solves the phase lag problem. In addition, the switching function uses a hyperbolic tangent function instead of a sign function, which improves the jitter phenomenon of the sliding mode observer. And because the permanent magnet synchronous motor is a nonlinear system, the use of a traditional PID controller has a poor effect on the motor speed control, while fuzzy control does not require an accurate model of the controlled object, so it has a good control effect on the controlled object with nonlinear characteristics. The present invention improves the accuracy of rotor position estimation, enhances the anti-interference performance of the speed, and reduces the cost of the electric drive assembly of electric vehicles.

[0089] Figure 7 A block diagram of a motor speed control device provided in another embodiment of the present application.

[0090] The present specification provides a motor speed control device 700, see Figure 7 The motor speed control device 700 includes: an acquisition module 710, a first acquisition module 720, a second acquisition module 730, a determination module 740, a third acquisition module 750, a fourth acquisition module 760, and a control module 770.

[0091] Exemplarily, the acquisition module 710 is used to acquire the real voltage signal and the real current signal of the motor at the current moment.

[0092] Exemplarily, the first obtaining module 720 is used to obtain the back electromotive force of the motor based on the voltage real signal at the current moment and the current real signal at the current moment.

[0093] Exemplarily, the second obtaining module 730 is used to obtain the motor observed speed of the motor at the current moment based on the back electromotive force of the motor.

[0094] Exemplarily, the determination module 740 is used to determine the speed deviation based on the expected speed of the motor and the observed speed of the motor at the current moment.

[0095] Exemplarily, the third obtaining module 750 is used to obtain the initial control parameter of the motor current signal and the correction information of the initial control parameter based on the rotation speed deviation.

[0096] Exemplarily, the fourth obtaining module 760 is used to obtain the target control parameter based on the initial control parameter and the correction information, and obtain the current signal at the next moment based on the target control parameter.

[0097] Exemplarily, the control module 770 is used to control the rotation speed of the motor based on the current signal at the next moment.

[0098] It can be understood that the specific implementation process of the motor speed control device 700 can refer to the implementation process of the motor speed control method above, and will not be repeated here.

[0099] An embodiment of the present application provides a vehicle, and the vehicle is used to implement the steps of the method of any one of the above embodiments.

[0100] An embodiment of the present application provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the method of any of the above embodiments can be performed.

[0101] An embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the method in any one of the above embodiments are implemented.

[0102] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this application, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or otherwise processing in a suitable manner if necessary, and then stored in a computer memory.

[0103] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0104] In the description of the present application, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In the present application, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0105] In the description of the present application, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0106] In addition, the terms "first", "second", etc. used in the embodiments of the present application are only used for descriptive purposes and should not be understood as indicating or implying relative importance, or implicitly indicating the number of technical features indicated in the present embodiment. Therefore, the features defined by the terms "first", "second", etc. in the embodiments of the present application can explicitly or implicitly indicate that at least one of the features is included in the embodiment. In the description of the present application, the word "multiple" means at least two or two or more, such as two, three, four, etc., unless otherwise clearly and specifically defined in the embodiments.

[0107] In this application, unless otherwise clearly specified or limited in the embodiments, the terms "installed", "connected", "connected" and "fixed" etc. appearing in the embodiments should be understood in a broad sense. For example, the connection can be a fixed connection, a detachable connection, or an integrated connection. It can be understood that it can also be a mechanical connection, an electrical connection, etc.; of course, it can also be a direct connection, or an indirect connection through an intermediate medium, or it can be the internal connection of two elements, or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to the specific implementation situation.

[0108] In the present application, unless otherwise clearly specified and limited, a first feature being “above” or “below” a second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, a first feature being “above”, “above”, and “above” a second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. A first feature being “below”, “below”, and “below” a second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0109] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A motor speed control method, characterized in that: The method comprises: Obtain the current voltage real signal and the current real signal of the motor; Based on the real voltage signal and the real current signal at the current moment, the back electromotive force of the motor is obtained; Based on the back electromotive force of the motor, obtaining the motor observed speed at the current moment; Determine the speed deviation based on the expected speed of the motor and the observed speed of the motor at the current moment; Based on the speed deviation, obtaining initial control parameters of the motor current signal and correction information of the initial control parameters; Based on the initial control parameter and the correction information, a target control parameter is obtained, and based on the target control parameter, a current signal at a next moment is obtained, and the rotation speed of the motor is controlled based on the current signal at the next moment.

2. The method according to claim 1, characterized in that The step of obtaining the observed motor speed of the motor at the current moment based on the back electromotive force of the motor includes: Based on the back electromotive force of the motor, obtaining rotor position information of the motor; Based on the rotor position information, the motor observed speed at the current moment is obtained.

3. The method according to claim 1 or 2, characterized in that: The step of obtaining the back electromotive force of the motor based on the voltage real signal at the current moment and the current real signal at the current moment includes: Based on the real voltage signal at the current moment, the current estimation signal at the current moment is estimated; Based on the current estimation signal at the current moment and the current real signal at the current moment, a current error signal is obtained; The current error signal is processed based on a preset association relationship to obtain the back electromotive force of the motor.

4. The method according to claim 3, characterized in that The preset association relationship includes a functional relationship between back electromotive force and current signal error, the functional relationship includes at least one of an integral function and a switching function, the integral function is used to perform time integration on the current error signal, the variable of the switching function is the current signal error, and the mutation degree of the switching function is less than a preset mutation degree.

5. The method according to claim 4, characterized in that After the current signal error is processed by the switching function to obtain a processing result, the processing result is integrated by the integral function, wherein the switching function includes a hyperbolic tangent function.

6. The method according to claim 5, characterized in that The step of obtaining the initial control parameter of the motor current signal and the correction information of the initial control parameter based on the speed deviation includes: Based on the rotation speed deviation, obtaining the initial control parameter; Based on the speed deviation, obtaining a rate of change of the speed deviation; Based on the rotational speed deviation and the rate of change of the rotational speed deviation, correction information of the initial control parameter is obtained.

7. The method according to claim 6, characterized in that The obtaining correction information of the initial control parameter based on the speed deviation and the rate of change of the speed deviation includes: Based on the rotation speed deviation and the rate of change of the rotation speed deviation, a fuzzy value of the rotation speed deviation and a fuzzy value of the rate of change are obtained; Using a preset fuzzy rule, based on the fuzzy value of the speed deviation and the fuzzy value of the change rate, a fuzzy value of the correction information is obtained; Based on the fuzzy value of the correction information, correction information is obtained.

8. The method according to claim 6 or 7, characterized in that: The initial control parameters include a proportional initial coefficient, an initial differential coefficient, and an initial integral coefficient; the correction information includes a proportional correction value, a differential correction value, and an integral correction value; the target control parameters include a target initial coefficient, a target differential coefficient, and a target integral coefficient; the target control parameters are obtained based on the initial control parameters and the correction information, and the current signal at the next moment is obtained based on the target control parameters, including: The initial proportional coefficient, the initial differential coefficient, and the initial integral coefficient are added to the proportional correction value, the differential correction value, and the integral correction value respectively to obtain the target proportional coefficient, the target differential coefficient, and the target integral coefficient; Processing the speed deviation based on a target proportional coefficient to obtain a proportional term of a current signal; Processing the rate of change of the rotational speed deviation based on a target differential coefficient to obtain a differential term of the current signal; Processing the integral data of the rotation speed deviation based on the target integral coefficient to obtain an integral term of the current signal; Based on the proportional term of the current signal, the differential term of the current signal, and the integral term of the current signal, the current signal at the next moment is obtained.

9. A motor speed control device, characterized in that: The device comprises: An acquisition module is used to acquire the current voltage real signal and the current real signal of the motor; A first obtaining module is used to obtain the back electromotive force of the motor based on the voltage real signal and the current real signal at the current moment; A second obtaining module is used to obtain the motor observed speed of the motor at a current moment based on the back electromotive force of the motor; A determination module, used to determine a speed deviation based on an expected speed of the motor and an observed speed of the motor at a current moment; A third obtaining module, based on the speed deviation, obtains initial control parameters of the motor current signal and correction information of the initial control parameters; A fourth obtaining module, which obtains a target control parameter based on the initial control parameter and the correction information, and obtains a current signal at a next moment based on the target control parameter; The control module is used to control the speed of the motor based on the current signal at the next moment.

10. A vehicle, characterized in that: The vehicle is used to implement the steps of the method according to any one of claims 1-8.

11. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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