Permanent magnet assisted synchronous reluctance machine rotor position estimation method based on effective flux linkage error compensation

Abstract

A kind of permanent magnet auxiliary synchronous reluctance motor rotor position estimation method based on effective flux linkage error compensation belongs to motor position sensorless control technical field.The present application is aimed at the problem that the rotor position estimation accuracy of existing hybrid flux observer is greatly influenced by motor parameter variation.It includes: the estimation of motor rotor position is realized by establishing hybrid effective flux observer;The disturbance caused by parameter mismatch of motor voltage equation is modeled, and a new state equation with effective flux linkage error and motor parameter as state variable is constructed;The effective flux linkage error caused by parameter mismatch in hybrid effective flux observer is observed by designing extended state observer based on effective flux linkage error;The effective flux linkage error caused by parameter mismatch is compensated by designing effective flux linkage error compensation method.The present application is used for motor rotor position estimation.

Description

TECHNICAL FIELD

[0001] The application relates to a rotor position estimation method for a permanent magnet assisted synchronous reluctance motor based on effective flux linkage error compensation and belongs to the technical field of motor position sensorless control. BACKGROUND

[0002] With the development of traffic electrification, the role of high-performance motor drive systems is becoming more and more important. The permanent magnet assisted synchronous reluctance motor (PMa-SynRM) has been widely concerned due to its simple rotor structure, high efficiency and low cost. Since the PMa-SynRM can use relatively inexpensive ferrite material and has higher demagnetization temperature and stronger durability, it is suitable for application in electric vehicles, mine hoists and traction systems. In order to improve the fault-tolerant operation capability of the drive system, it is very important to introduce a position sensorless control algorithm.

[0003] Most of the position estimation algorithms based on motor models require accurate motor parameters, and when the parameters are mismatched, the rotor position estimation error will increase. At present, the parameters with good robustness in the model method are the traditional hybrid flux observer and the nonlinear flux observer, among which the traditional hybrid flux observer has a simple structure and is easy to adjust parameters. However, the parameters of the PMa-SynRM are nonlinear, and therefore, it is very important to further improve the parameter robustness of the PMa-SynRM position estimation algorithm based on the hybrid flux observer.

[0004] At present, in order to improve the parameter robustness of the model method, there are generally two solutions: one is to combine the online parameter identification method; the other is to optimize the structure of the observer. Among them, the online parameter identification method is relatively simple to design, but it needs to inject an additional signal in the identification process, which brings additional calculation load. The method of optimizing the structure of the observer is the mainstream method for improving the parameter robustness of the position sensorless control algorithm at present. Therefore, it is necessary to provide a rotor position estimation method with high parameter robustness and low position estimation error to solve the problem of control performance degradation caused by high parameter mismatch degree when the traditional hybrid flux observer is applied to the PMa-SynRM. SUMMARY

[0005] In view of the problem that the rotor position estimation accuracy of the existing hybrid flux observer is greatly affected by the change of motor parameters, the application provides a rotor position estimation method for a permanent magnet assisted synchronous reluctance motor based on effective flux linkage error compensation.

[0006] The rotor position estimation method for the permanent magnet assisted synchronous reluctance motor based on effective flux linkage error compensation comprises the following steps:

[0007] Based on the voltage model, the current model and the estimated mathematical model of the permanent magnet assisted synchronous reluctance motor under the shaft system, a hybrid effective flux linkage observer equation is established;

[0008] Based on the estimated mathematical model of the permanent magnet assisted synchronous reluctance motor under the shaft system, a state equation is established with the effective flux linkage error and the motor parameters as state variables;

[0009] According to the state equation, an extended state observer based on the effective flux linkage error is designed to observe the effective flux linkage error caused by the mismatch of motor parameters in the hybrid effective flux linkage observer equation;

[0010] The rotor position and speed are observed by combining the hybrid effective flux linkage observer equation with the extended state observer, and the rotor position observation value and the speed observation value are fed back to the double closed loop control system to realize the position sensorless vector control of the motor.

[0011] According to the permanent magnet assisted synchronous reluctance motor rotor position estimation method based on the effective flux linkage error compensation, the voltage model and the current model of the permanent magnet assisted synchronous reluctance motor are:

[0012]

[0013] In the formula, is the effective flux linkage vector estimation value of the voltage model, u αβ is the stator voltage vector under the static shaft system, u αβ =[u α u β ] T , u α is the stator voltage α-axis component under the static shaft system, u β is the stator voltage β-axis component under the static shaft system, R s is the stator resistance, i αβ is the stator current vector under the static shaft system, i αβ =[i α i β ] T , i α is the stator current α-axis component under the static shaft system, i β is the stator current β-axis component under the static shaft system, is the d-axis inductance estimation value;

[0014] is the effective flux linkage vector estimation value of the current model, is the q-axis inductance estimation value, i δ is the stator current δ-axis component under the estimated shaft system, is the permanent magnet flux linkage estimation value.

[0015] The permanent magnet auxiliary synchronous reluctance motor rotor position estimation method based on effective flux linkage error compensation according to the application is characterized in that the mathematical model of the permanent magnet auxiliary synchronous reluctance motor under the estimated shaft system is as follows:

[0016]

[0017] wherein is the real value of the effective flux linkage, u is the stator voltage vector under the estimated shaft system, I is a unit matrix, is the estimated value of the motor electric angular velocity, L d is the real value of the d-axis inductance, J is an orthogonal matrix, i is the stator current vector under the estimated shaft system, i = [i γ i δ ] T , i γ is the stator current γ-axis component under the estimated shaft system;

[0018]

[0019] The permanent magnet auxiliary synchronous reluctance motor rotor position estimation method based on effective flux linkage error compensation according to the application is characterized in that the difference between the effective flux linkage vector estimated values of the voltage model and the current model is taken as feedback, and the mixed effective flux linkage observer equation is established as follows:

[0020]

[0021] wherein K is a feedback gain matrix, K = kI, and k is a gain coefficient.

[0022] The permanent magnet auxiliary synchronous reluctance motor rotor position estimation method based on effective flux linkage error compensation according to the application is characterized in that the mathematical model of the permanent magnet auxiliary synchronous reluctance motor under the estimated shaft system is deformed, and the state equation taking the effective flux linkage error and the motor parameters as state variables is established as follows:

[0023]

[0024] wherein is the stator voltage input quantity of the estimated shaft system, f γδ is the disturbance quantity of the estimated shaft system;

[0025]

[0026] wherein is the d-axis inductance error value;

[0027] is the effective flux linkage error vector of the current model;

[0028]

[0029] wherein is the effective flux error amplitude, is the position estimation error of the extended state observer;

[0030]

[0031] wherein is the q-axis inductance error value, is the permanent magnet flux error value.

[0032] According to the permanent magnet assisted synchronous reluctance motor rotor position estimation method based on effective flux error compensation of the present application, the extended state observer based on the effective flux error is:

[0033]

[0034] is the estimated stator current vector estimation value of the estimated shaft system, is the disturbance estimation value of the estimated shaft system, and β1 is the gain one of the extended state observer and β2 is the gain two of the extended state observer.

[0035] According to the permanent magnet assisted synchronous reluctance motor rotor position estimation method based on effective flux error compensation of the present application, when the system is in a steady state, tends to 0, at which time the effective flux error estimation amplitude is:

[0036]

[0037] wherein is the γ-axis disturbance estimation value, is the δ-axis disturbance estimation value.

[0038] the effective flux error estimation vector is:

[0039]

[0040] According to the permanent magnet assisted synchronous reluctance motor rotor position estimation method based on effective flux error compensation of the present application, the effective flux error estimation vector observed by the extended state observer based on the effective flux error is added into the feedback loop of the hybrid effective flux observer equation, so as to realize compensation on the effective flux error in the equation, and the compensated equation is:

[0041]

[0042] ​The method of the application is used to realize motor position sensorless control under high parameter mismatch degree. The method realizes estimation of motor rotor position by establishing a hybrid effective flux linkage observer; the method models disturbance of motor voltage equation caused by parameter mismatch, and constructs a new state equation taking effective flux linkage error and motor parameters as state variables; the method realizes observation of effective flux linkage error caused by parameter mismatch in the hybrid effective flux linkage observer by designing an extended state observer based on effective flux linkage error; and the method realizes compensation of effective flux linkage error caused by parameter mismatch by designing an effective flux linkage error compensation method. Compared with a position estimation method based on a traditional hybrid flux linkage observer, the method of the application does not depend on q-axis inductance parameters and flux linkage parameters, can maintain low position estimation error and observation stability under high parameter mismatch degree, and has practical value.

[0043] The method of the application is simple and easy to implement, and the implementation process is not affected by changes of motor flux linkage and q-axis inductance parameters, and has high dynamic performance. The method provides an important guarantee for realizing high-performance and high-parameter-robust position sensorless control of a permanent magnet assisted synchronous reluctance motor. BRIEF DESCRIPTION OF DRAWINGS

[0044] Figure 1 is a principle block diagram of the method of the application for motor position sensorless vector control; in the diagram, ω e * is a given speed of the speed outer loop, is a speed observation value obtained by the method of the application, is a given value of a stator current δ-axis component, is a given value of a stator current γ-axis component, is a given value of a stator voltage δ-axis component, is a given value of a stator voltage γ-axis component, is a given value of a stator voltage α-axis component, is a given value of a stator voltage β-axis component, i a is a value of a-phase current, i c is a value of c-phase current, t d is a system dead time;

[0045] Figure 2 is a reference coordinate system diagram of the method of the application for permanent magnet assisted synchronous reluctance motor rotor position estimation based on effective flux linkage error compensation; in the diagram, α-β axis represents a stationary axis system, d-q axis represents an actual rotating axis system, and γ-δ axis represents an estimated axis system;

[0046] Figure 3 is a whole control block diagram of the method of the application for permanent magnet assisted synchronous reluctance motor rotor position estimation based on effective flux linkage error compensation; is the component of the estimated value of the effective flux linkage vector of the voltage model on the α axis in the stationary axis system, is the component of the estimated value of the effective flux linkage vector of the voltage model on the β axis in the stationary axis system, is the component of the estimated value of the effective flux linkage vector of the voltage model on the γ axis in the estimated axis system, is the component of the estimated value of the effective flux linkage vector of the voltage model on the δ axis in the estimated axis system, is the component of the estimated value of the effective flux linkage vector of the current model on the γ axis in the estimated axis system, is the component of the estimated value of the effective flux linkage vector of the current model on the γ axis in the estimated axis system, U dc is the bus voltage, is the δ axis component of the estimated value of the stator current vector in the estimated axis system;

[0047] Figure 4 and Figure 5 is a comparison diagram of position estimation errors of the method of the present application and the conventional hybrid flux linkage observer under different load conditions;

[0048] wherein Figure 4 is a schematic diagram of position estimation errors of the conventional hybrid flux linkage observer under different load conditions;

[0049] Figure 5 is a schematic diagram of position estimation errors of the hybrid effective flux linkage observer of the method of the present application under different load conditions. DETAILED DESCRIPTION

[0050] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0051] It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict.

[0052] The present application will be further described below in combination with the drawings and specific embodiments, but is not limited by the present application.

[0053] DETAILED DESCRIPTION Figures 1 to 3 As shown in the drawings, the present application provides a rotor position estimation method for a permanent magnet auxiliary synchronous reluctance motor based on effective flux linkage error compensation,

[0054] Based on the voltage model, the current model and the mathematical model of the permanent magnet auxiliary synchronous reluctance motor in the estimated axis system of the permanent magnet auxiliary synchronous reluctance motor, a hybrid effective flux linkage observer equation is established.

[0055] At the same time, based on the mathematical model of the permanent magnet assisted synchronous reluctance motor under the estimated shaft system, a state equation is established with the effective flux error and motor parameters as state variables;

[0056] An extended state observer based on effective flux error is designed according to the state equation to observe the effective flux error caused by motor parameter mismatch in the hybrid effective flux observer equation;

[0057] An effective flux error compensation method is designed, and the hybrid effective flux observer equation is combined with the extended state observer to observe the rotor position and speed. The rotor position observation values ​​and speed observation values ​​are fed back to the dual closed-loop control system to realize position sensorless vector control of the motor.

[0058] In this embodiment, the voltage equation of the permanent magnet assisted synchronous reluctance motor is analyzed, and an extended state observer based on the effective flux error is designed to observe and compensate for the effective flux error in the system, thereby reducing the position estimation error caused by parameter mismatch of the observer.

[0059] Combine Figures 1 to 3 This embodiment is further described as follows. Figure 2 The figure shows the reference coordinate system of the present invention. The α-β axis, dq axis and γ-δ axis are respectively the stationary, actual rotation and estimated rotation axis systems. The output position of the observer is defined to be aligned with the γ axis. The position estimation error is expressed as ω e and are the actual and estimated motor electrical angular velocities, respectively.

[0060] like Figure 3 The figure shows the overall control block diagram of this embodiment, which includes dual closed-loop control, a hybrid effective flux observer, and an extended state observer based on effective flux error. When the system is in dual closed-loop vector control, the outer speed loop compares the set speed with the observed speed value to output the current setpoint. The inner current loop compares the setpoint current with the acquired actual current to generate the voltage control signal required for SVPWM. This voltage signal is modulated by the SVPWM module and fed into the inverter to achieve motor control. This embodiment enables observation of rotor position and speed information, utilizing this information to achieve sensorless closed-loop control.

[0061] Furthermore, the voltage model and current model of the permanent magnet assisted synchronous reluctance motor are:

[0062]

[0063] In the formula is the estimated value of the effective flux vector of the voltage model, uαβ is the stator voltage vector under the stationary shaft system, u αβ =[u α u β ] T ,u α is the α-axis component of the stator voltage under the stationary shaft system, u β is the β-axis component of the stator voltage under the stationary shaft system, R s is the stator resistance, i αβ is the stator current vector in the stationary shaft system, i αβ =[i α i β ] T ,i α is the α-axis component of the stator current in the stationary shaft system, i β is the β-axis component of the stator current in the stationary shaft system, is the estimated value of d-axis inductance;

[0064] is the estimated value of the effective flux vector of the current model, is the estimated value of q-axis inductance, i δ To estimate the δ-axis component of the stator current in the shaft system, is the estimated value of the permanent magnet flux.

[0065] In this embodiment, the mathematical model of the permanent magnet assisted synchronous reluctance motor under the estimated shaft system is:

[0066]

[0067] In the formula is the true value of effective flux, u is the stator voltage vector under the estimated shaft system, u=[u γ u δ ] T ,u γ To estimate the γ-axis component of the stator voltage under the shaft system, u δ is the estimated δ-axis component of the stator voltage under the shaft system; I is the unit matrix, is the estimated value of the motor electrical angular velocity, L d is the true value of the d-axis inductance, J is an orthogonal matrix, i is the stator current vector under the estimated axis system, i=[i γ i δ ] T ,i γ To estimate the γ-axis component of the stator current under the shaft system;

[0068]

[0069] Furthermore, according to the observer design principle, the difference between the effective flux vector estimates of the voltage model and the current model is used as feedback to establish the hybrid effective flux observer equation:

[0070]

[0071] where K is the feedback gain matrix, K = kI, k is the gain coefficient.

[0072] The mathematical model of the permanent magnet assisted synchronous reluctance motor under the estimated shaft system is deformed to establish the state equation with the effective flux error and motor parameters as the state variables:

[0073]

[0074] where is the stator voltage input of the estimated shaft system, f γδ is the disturbance of the estimated shaft system;

[0075]

[0076] where is the d-axis inductance error value;

[0077] is the effective flux error vector of the current model;

[0078]

[0079] where is the effective flux error amplitude, is the rotor position estimation error of the extended state observer, where θ e is the true value of the rotor position, is the observed value of the rotor position;

[0080]

[0081] where is the q-axis inductance error value, is the permanent magnet flux error value.

[0082] The true value of the effective flux is: is the amplitude of the true value of the effective flux;

[0083] L q is the true value of the q-axis inductance, i q is the q-axis current value, ψ f is the true value of the permanent magnet flux.

[0084] Further, the extended state observer based on the effective flux error is:

[0085]

[0086] For estimating the stator current vector estimate of the shaft system, For estimating the disturbance estimate of the shaft system, β1 is the gain one of the extended state observer, and β2 is the gain two of the extended state observer.

[0087] In this embodiment, when the system is in steady state, it can be considered that tends to 0, and with the addition of compensation, the rotor position estimation error of the extended state observer tends to 0, at which time the effective flux error estimation amplitude is:

[0088]

[0089] In the formula is the γ-axis disturbance estimate, is the δ-axis disturbance estimate;

[0090] The effective flux error estimation vector is:

[0091]

[0092] Further, the effective flux error compensation method is designed as follows: the effective flux error estimation vector observed by the extended state observer based on the effective flux error is added to the feedback loop of the hybrid effective flux observer equation, so as to realize compensation for the effective flux error in the equation. The compensated equation is:

[0093]

[0094] After the compensation is completed, the effective flux error caused by parameter mismatch can be suppressed, and the position estimation error can be reduced. The effective flux in the observed voltage model is observed, and the current rotor position and speed are obtained by using the phase-locked loop (PLL). Finally, the observed position information and speed information are fed back to the double-closed-loop control system, so as to realize the position sensorless vector control of the motor.

[0095] Verification test:

[0096] This was verified on a permanent magnet-assisted synchronous reluctance motor (PMSM) dynamoelectric test platform. A 2.2kW PMSM and a permanent magnet synchronous motor were coaxially coupled via a coupling. The PMSM served as the control motor, while the PMSM served as the load motor. The two inverters were connected using a common DC bus. A vector control algorithm was implemented using an STM32F103VCT6 ARM processor to control the PMSM. The inverter switching frequency was 6kHz.

[0097] The main parameters of the permanent magnet synchronous motor used are: rated power 2.2kW, rated current 4.8A, rated speed 1500r / min, L d =152.4mH, L q =41.8mH, pole pair number P=3, R=3.00Ω.

[0098] Figure 4 and Figure 5 The figure shows the position estimation error comparison between the proposed method and the traditional hybrid flux observer under different load conditions. The inductance parameter of the observer is set to a fixed value and the motor speed is 1000r / min. Figure 4 It can be observed that the no-load error of the traditional hybrid flux observer is around 0°. As the load increases, the magnetic saturation effect of the inductor becomes more obvious, the actual inductance is smaller than the observer inductance, and the position estimation error also increases. At rated load, the rotor position estimation error reaches 15.8°. Figure 5 It can be seen that the position estimation error of the hybrid effective flux observer proposed in the present invention is reduced to around 10.8°. It can be seen that the hybrid effective flux observer proposed in the present invention is more robust to parameter mismatch than the traditional hybrid flux observer.

[0099] Although the present invention is described herein with reference to specific embodiments, it should be understood that these embodiments are merely illustrative of the principles and applications of the invention. It should be understood that many modifications may be made to the illustrative embodiments, and that other arrangements may be devised, without departing from the spirit and scope of the invention as defined by the appended claims. It should be understood that the various dependent claims and features described herein may be combined in ways other than those described in the original claims. It should also be understood that features described in conjunction with individual embodiments may be used in conjunction with other described embodiments.

Claims

1. A method for estimating the rotor position of a permanent magnet assisted synchronous reluctance motor based on effective flux error compensation, characterized in that: Based on the voltage model, current model and mathematical model of the permanent magnet assisted synchronous reluctance motor under the estimated shaft system, a hybrid effective flux observer equation is established; At the same time, based on the mathematical model of the permanent magnet assisted synchronous reluctance motor under the estimated shaft system, a state equation is established with the effective flux error and motor parameters as state variables; An extended state observer based on effective flux error is designed according to the state equation to observe the effective flux error caused by motor parameter mismatch in the hybrid effective flux observer equation; The hybrid effective flux observer equation is combined with the extended state observer to observe the rotor position and speed; the rotor position observation value and the speed observation value are fed back to the dual closed-loop control system to realize the position sensorless vector control of the motor; The extended state observer based on the effective flux error is: To estimate the stator current vector under the shaft system, is the estimated value of the disturbance of the estimated shaft system, β1 is the gain of the extended state observer, β2 is the gain of the extended state observer; u is the stator voltage vector under the estimated shaft system, R s is the stator resistance, is the estimated value of d-axis inductance, is the estimated value of the motor electrical angular velocity, J is an orthogonal matrix, is the estimated value of the effective flux vector of the current model, i is the stator current vector under the estimated shaft system, i=[i γ i δ ] T ,i δ To estimate the δ-axis component of the stator current under the shaft system, i γ To estimate the γ-axis component of the stator current under the shaft system; When the system is in steady state, Approaching 0, is the effective flux error vector of the current model; the estimated amplitude of the effective flux error is for: In the formula is the estimated value of the γ-axis disturbance, is the estimated value of the δ-axis disturbance; Effective flux error estimation vector for:

2. The method for estimating the rotor position of a permanent magnet assisted synchronous reluctance motor based on effective flux error compensation according to claim 1, characterized in that: The voltage model and current model of the permanent magnet assisted synchronous reluctance motor are: In the formula is the estimated value of the effective flux vector of the voltage model, u αβ is the stator voltage vector under the stationary shaft system, u αβ =[u α u β ] T ,u α is the α-axis component of the stator voltage under the stationary shaft system, u β is the β-axis component of the stator voltage under the stationary shaft system, i αβ is the stator current vector in the stationary shaft system, i αβ =[i α i β ] T ,i α is the α-axis component of the stator current in the stationary shaft system, i β is the β-axis component of the stator current in the stationary shaft system; is the estimated value of q-axis inductance, is the estimated value of the permanent magnet flux.

3. The method for estimating the rotor position of a permanent magnet assisted synchronous reluctance motor based on effective flux error compensation according to claim 2, characterized in that: The mathematical model of the permanent magnet assisted synchronous reluctance motor under the estimated shaft system is: In the formula is the true value of the effective magnetic flux, I is the unit matrix, L d is the true value of d-axis inductance; 4. The method for estimating the rotor position of a permanent magnet assisted synchronous reluctance motor based on effective flux error compensation according to claim 3, characterized in that: The difference between the effective flux vector estimates of the voltage model and the current model is used as feedback to establish the hybrid effective flux observer equation: Where K is the feedback gain matrix, K=kI, and k is the gain coefficient.

5. The method for estimating the rotor position of a permanent magnet assisted synchronous reluctance motor based on effective flux error compensation according to claim 4, characterized in that: The mathematical model of the permanent magnet assisted synchronous reluctance motor under the estimated shaft system is transformed, and the state equation with the effective flux error and motor parameters as state variables is established as follows: In the formula To estimate the stator voltage input of the shaft system, f γδ To estimate the disturbance of the shaft system; In the formula is the d-axis inductance error value; In the formula is the effective flux linkage error amplitude, is the position estimation error of the extended state observer; In the formula is the q-axis inductance error value, is the permanent magnet flux linkage error value.

6. The method for estimating the rotor position of a permanent magnet assisted synchronous reluctance motor based on effective flux error compensation according to claim 5, characterized in that: The effective flux error estimation vector obtained by the extended state observer based on the effective flux error is Adding it to the feedback loop of the hybrid effective flux observer equation can compensate for the effective flux error in the equation. The compensated equation is:

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