Permanent magnet synchronous motor collaborative observer design method applied to electric vehicle

Abstract

The invention discloses a permanent magnet synchronous motor collaborative observer design method applied to an electric vehicle, which comprises the following steps: establishing a voltage equation of a permanent magnet synchronous motor (PMSM), establishing a torque equation, establishing a mechanical motion equation in combination with operation characteristics and braking requirements of the electric vehicle, designing a sliding mode surface, designing an observer structure, and designing an input and output relationship of the observer. The sliding mode surface can be adjusted in real time; and a super-spiral sliding-mode observer is designed, and high-frequency noise and external disturbance are suppressed in a super-spiral form. If the electric vehicle faces multiple working conditions, in order to reduce disturbance encountered by the system during working condition switching, fuzzy logic is coordinated. The super-spiral sliding mode control algorithm is adopted, and the dynamic response and the convergence speed of the sliding mode surface are accelerated. The response time is reduced to 0.001 second from 0.003 second of a traditional method, and the response speed is increased by about 67%.

Description

Technical Field

[0001] The technical field of the present invention belongs to the design and control technology of electric vehicles and electric drive systems thereof, and specifically relates to parameter identification and control methods of permanent magnet synchronous motors. Background Art

[0002] With the improvement of environmental protection awareness and the transformation of global energy structure, electric vehicles (EVs) have received extensive attention and research around the world because of their ability to significantly reduce air pollution and provide performance matching that of traditional fuel vehicles. In particular, in the selection of drive motors, the core component of electric vehicles, permanent magnet synchronous motors (PMSM) stand out among many motor types with their advantages of small size, high efficiency and fast response speed, and are widely used in the field of electric vehicles.

[0003] Currently, among the control technologies for PMSM, sliding mode control technology is widely used in sensorless motor control strategies due to its good anti-interference ability and precise control accuracy. In particular, various types of sliding mode observer (SMO) technology have developed rapidly in the field of PMSM control. At present, the closest existing technologies mainly include:

[0004] Non-singular Fast Terminal Sliding Mode Observer (NFTSMO): This technology achieves high-precision motor state observation and control over a wide speed range by combining an improved sliding surface design. However, despite NFTSMO's excellent performance in improving observation accuracy and rapidity, it still shows certain limitations in high-frequency noise processing and system robustness.

[0005] Fuzzy sliding mode observer: By introducing fuzzy logic control, this technology increases the adaptability and robustness of the system in the sliding mode control strategy. Although the introduction of fuzzy sliding mode observer effectively enhances the system's adaptability to complex working conditions, the design and adjustment process of fuzzy control rules is complicated, which increases the difficulty of system implementation.

[0006] Inclined integral sliding mode controller and observer: This technology improves the steady-state performance of the system by introducing an integral term to optimize the sliding mode control. However, this method is not good in terms of fast dynamic response and anti-disturbance capability, which limits its effectiveness in application scenarios that require high dynamic performance.

[0007] Although the above technologies have their own advantages, they still have some common disadvantages and limitations, mainly including:

[0008] Complex adjustment of sliding surface: The sliding surface design of the traditional sliding mode observer is complex, and the sliding mode parameters need to be adjusted frequently under different working conditions, which increases the difficulty of system implementation.

[0009] Insufficient anti-interference ability: In terms of dealing with external disturbances and high-frequency noise, the existing technology cannot fully meet the needs of high-precision control, affecting the accuracy and stability of motor control.

[0010] Slow response speed: Although the introduction of fuzzy control enhances the adaptability and robustness of the system, the performance of existing technologies is still insufficient in application scenarios that require fast dynamic response.

[0011] The above analysis shows that although the existing technology has made some progress in PMSM control, the sliding mode observer technology still needs to be further optimized to meet the needs of electric vehicles for high efficiency and high stability. Summary of the invention

[0012] Based on the above-mentioned deficiencies in the prior art, the present invention discloses a parameter identification and control method for a permanent magnet synchronous motor.

[0013] The following is a one-to-one analysis of the invention objectives and the problems of the prior art.

[0014] Simplify sliding surface design: By adopting a super-helical sliding mode observer, the sliding surface generation algorithm is optimized, the adjustment frequency and complexity are reduced, and the adaptability of the system is improved.

[0015] Enhance the anti-interference ability of the system: Use fuzzy algorithm to estimate the uncertainty boundary to solve the problem that the traditional super-helix algorithm is difficult to determine the upper limit of the boundary.

[0016] Improve the dynamic response capability of the system: The super-helical sliding mode observer converges faster than the traditional observer, enabling rapid observation and adjustment of the motor state.

[0017] The technical solution of the present invention includes:

[0018] Step 1: Establish the voltage equation for the PMSM

[0019]

[0020] Among them, u d and u q are the voltages of the d-axis and q-axis, i d and i q are the currents of the d-axis and q-axis respectively, R s is the stator resistance, L d and L q are the inductances of the d-axis and q-axis respectively, ω is the rotor angular velocity, λ f is the permanent magnet flux.

[0021] Step 2: Create the torque equation

[0022]

[0023] Among them, T e is the electromagnetic torque, and P is the number of pole pairs.

[0024] Step 3: Establish the mechanical motion equations based on the electric vehicle operating characteristics and braking requirements.

[0025]

[0026] Where J is the moment of inertia, T L is the load torque and B is the viscous friction coefficient.

[0027] Step 4: Design the sliding surface.

[0028] The sliding surface is defined as the state error of the motor: Among them, x d and x q are the actual state variables of the d-axis and q-axis respectively, and are the observed state variables of the d-axis and q-axis, respectively, and λ1 and λ2 are the coefficients of the sliding surface.

[0029] Step 5: Design the observer structure and the input-output relationship of the observer so that it can adjust the sliding surface in real time.

[0030]

[0031] Among them, f d and f q are the nonlinear functions of the d-axis and q-axis, respectively, and k d and k q is the superhelical sliding mode control gain, and sign(s) is the sign function of the sliding mode surface.

[0032] Step 6: Design of super-helical sliding mode observer, using super-helical form to suppress high-frequency noise and external disturbances.

[0033]

[0034] Among them, s1 and s2 are two state variables of the sliding surface, and k1 and k2 are superhelical control gains.

[0035] Step 7: If the electric vehicle is faced with multiple operating conditions, in order to reduce the disturbance encountered by the system when switching operating conditions, coordinate fuzzy logic.

[0036] Defining fuzzy rules

[0037] If A and Δe is B, then uis C

[0038] Among them, e is the state error, Δe is the error change rate, u is the control input, and A, B, and C are fuzzy sets.

[0039] The sliding mode control parameters can be adjusted online to adapt to different working conditions: u = ∑ i w i ·u i Among them, w i is the weight of the fuzzy rule, u i is the corresponding control input.

[0040] The technical solution of the present invention is: using the super-helical sliding mode control algorithm to automatically adjust the sliding surface and simplify the parameter adjustment process. The sliding surface adjustment time is reduced by 50%, and the calculation complexity is reduced by 30%. The traditional method has insufficient anti-interference ability and is easily affected by external interference, resulting in system instability. The present invention effectively enhances the anti-interference ability of the system by combining a super-helical sliding mode observer and a fuzzy controller. Under load disturbance, the speed error is reduced from 5.838r / min of the traditional method to 0.166r / min of this method, and the anti-interference ability is significantly improved. The traditional method has a slow response speed and poor system dynamic performance. The super-helical sliding mode control algorithm is adopted to accelerate the dynamic response and the convergence speed of the sliding surface. The response time is reduced from 0.003 seconds of the traditional method to 0.001 seconds, and the response speed is increased by about 67%. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a control block diagram of the present invention;

[0042] Figure 2 This is a control block diagram of the super spiral observer of the present invention;

[0043] Figure 3 is the fuzzy adaptive control block diagram; (a) is the membership function of s; (b) is the input The membership function of (c) is the membership function of the sliding mode control output gain k; DETAILED DESCRIPTION

[0044] like Figure 1 As shown, the technical solution of the present invention includes:

[0045] Step 1: Establish the voltage equation for the PMSM

[0046]

[0047] Among them, u d and u q are the voltages of the d-axis and q-axis, i d and i qare the currents of the d-axis and q-axis respectively, R s is the stator resistance, L d and L q are the inductances of the d-axis and q-axis respectively, ω is the rotor angular velocity, λ f is the permanent magnet flux.

[0048] Step 2: Create the torque equation

[0049]

[0050] Among them, T e is the electromagnetic torque, and P is the number of pole pairs.

[0051] Step 3: Establish the mechanical motion equations based on the electric vehicle operating characteristics and braking requirements.

[0052]

[0053] Where J is the moment of inertia, T L is the load torque and B is the viscous friction coefficient.

[0054] Step 4: Design the sliding surface.

[0055] The sliding surface is defined as the state error of the motor: Among them, x d and x q are the actual state variables of the d-axis and q-axis respectively, and are the observed state variables of the d-axis and q-axis, respectively, and λ1 and λ2 are the coefficients of the sliding surface.

[0056] Step 5: Design the observer structure and the input-output relationship of the observer so that it can adjust the sliding surface in real time.

[0057]

[0058] Among them, f d and f q are the nonlinear functions of the d-axis and q-axis, respectively, and k d and k q is the superhelical sliding mode control gain, and sign(s) is the sign function of the sliding mode surface.

[0059] like Figure 2 As shown, step 6: super-helical sliding mode observer design, using super-helical form to suppress high-frequency noise and external disturbances.

[0060]

[0061] Among them, s1 and s2 are two state variables of the sliding surface, and k1 and k2 are superhelical control gains.

[0062] Figure 3 As shown, step 7: If the electric vehicle faces multiple operating conditions, in order to reduce the disturbance encountered by the system when switching operating conditions, coordinated fuzzy logic is used.

[0063] Defining fuzzy rules

[0064] Ife is A andΔe isB,then u isC

[0065] Among them, e is the state error, Δe is the error change rate, u is the control input, and A, B, and C are fuzzy sets.

[0066] The sliding mode control parameters can be adjusted online to adapt to different working conditions: u = ∑ i w i ·u i Among them, w i is the weight of the fuzzy rule, u i is the corresponding control input.

[0067] The specific algorithm numerical implementation example of the above method is:

[0068]

[0069]

[0070] The present invention utilizes a super-helical sliding mode control algorithm to automatically adjust the sliding surface, thereby simplifying the parameter adjustment process. The sliding surface adjustment time is reduced by 50%, and the computational complexity is reduced by 30%. The traditional method has insufficient anti-interference ability and is easily affected by external interference, resulting in system instability. The present invention effectively enhances the anti-interference ability of the system by combining a super-helical sliding mode observer and a fuzzy controller. Under load disturbance, the speed error is reduced from 5.838r / min of the traditional method to 0.166r / min of this method, and the anti-interference ability is significantly improved. The traditional method has a slow response speed and poor system dynamic performance. The super-helical sliding mode control algorithm is adopted to accelerate the dynamic response and the convergence speed of the sliding surface. The response time is reduced from 0.003 seconds of the traditional method to 0.001 seconds, and the response speed is increased by about 67%.

Claims

1. A method for designing a cooperative observer for a permanent magnet synchronous motor applied to an electric vehicle, characterized in that: The following steps are involved: Step 1: Establish the voltage equation of permanent magnet synchronous motor PMSM; Step 2: Create the torque equation Among them, T e is the electromagnetic torque, P is the number of pole pairs; i d and L q are the currents of the d-axis and q-axis respectively, L d and L q are the inductances of the d-axis and q-axis, respectively, f is the permanent magnet flux linkage; Step 3: Establish the mechanical motion equations based on the electric vehicle operating characteristics and braking requirements Where J is the moment of inertia, T L is the load torque, ω is the rotor angular velocity, and B is the viscous friction coefficient; Step 4: Design the sliding surface The sliding surface is defined as the state error of the motor: Among them, x d and x q are the actual state variables of the d-axis and q-axis respectively, and are the observed state variables of the d-axis and q-axis, respectively, λ1 and λ2 are the coefficients of the sliding surface; Step 5: Design the observer structure and the input-output relationship of the observer so that it can adjust the sliding surface in real time; Step 6: Design of super-helical sliding mode observer, using super-helical form to suppress high-frequency noise and external disturbances Among them, s1 and s2 are two state variables of the sliding surface, k1 and k2 are superhelical control gains; Step 7: If the electric vehicle is faced with multiple operating conditions, in order to reduce the disturbance encountered by the system when switching operating conditions, the fuzzy logic is coordinated: Defining fuzzy rules IfisAandΔeisB,thenisC Specific explanation: The If part describes a precondition or the fuzzy state of the input. In fuzzy logic, this condition is usually a fuzzy description of one or more input variables; where e is the state error, Δe is the error change rate, u is the control input, and A, B, and C are fuzzy sets; The sliding mode control parameters can be adjusted online to adapt to different working conditions: u = ∑ i w i ·u i Among them, w i is the weight of the fuzzy rule, u i is the corresponding control input.

2. The method for designing a cooperative observer for a permanent magnet synchronous motor applied to an electric vehicle according to claim 1, characterized in that: The voltage equation of the permanent magnet synchronous motor PMSM is: Among them, u d and u q are the voltages of the d-axis and q-axis, i d and i q are the currents of the d-axis and q-axis respectively, R s is the stator resistance, L d and L q are the inductances of the d-axis and q-axis respectively, ω is the rotor angular velocity, λ f is the permanent magnet flux.

3. The method for designing a cooperative observer for a permanent magnet synchronous motor applied to an electric vehicle according to claim 1, characterized in that: The observer structure of step 5 is: Among them, f d and f q are the nonlinear functions of the d-axis and q-axis, u d and u q are the voltages of the d-axis and q-axis, respectively, and k d and k q is the superhelical sliding mode control gain, and sign(s) is the sign function of the sliding mode surface.

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