Nonlinear flux observer-based salient pole permanent magnet synchronous motor non-inductive control method
Through equivalent replacement method and phase-locked loop technology, a nonlinear magnetic flux model of the convex permanent magnet synchronous motor was constructed, and the rotor position information was extracted using phase-locked loop technology, which solved the complex parameter debugging in inductive control of the convex permanent magnet synchronous motor. The problem of this achieves faster and more reliable control effects.
Patent Information
- Application Number
- CN202411385086.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-30
- Publication Date
- 2024-12-20
AI Technical Summary
The existing inductive control method for convex permanent magnet synchronous motors based on nonlinear magnetic flux observers has the problem that there are many debugging parameters and are not easy to apply quickly in engineering.
By using equivalent replacement method and phase-locked loop technology, the nonlinear magnetic flux model of the convex permanent magnet synchronous motor is constructed by obtaining the reference relationship model and nonlinear magnetic flux model of the surface-mounted permanent magnet synchronous motor, and the phase-locked loop is used. Technology extracts rotor position information to achieve inductive control.
In actual engineering applications, the parameters that need to be adjusted are reduced, the reliability of control and the rapidity of engineering applications are improved, and the complexity of parameter debugging is solved.
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Figure CN119171793A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of motor control, and in particular to a sensorless control method for a salient-pole permanent magnet synchronous motor based on a nonlinear flux observer. Background Art
[0002] With the rapid development of modern industrial technology, especially the booming new energy vehicle industry, three-phase permanent magnet synchronous motor (PMSM) has been widely used in industrial manufacturing and multiple key components of new energy vehicles due to its small size, simple structure, high power factor and significant energy saving effect. For example, three-phase permanent magnet synchronous motor is used in core auxiliary systems such as power steering pump and air pump of new energy vehicles, which greatly improves the performance and energy efficiency of vehicles.
[0003] However, in the complex operating environment of new energy vehicles, the traditional permanent magnet synchronous motor control system that relies on position sensors faces many challenges. Specifically, the installation of position sensors not only increases the complexity and cost of the system, but is also easily affected by the working environment, resulting in reduced reliability, which in turn affects the stability and safety of the entire vehicle. Therefore, the development of efficient, reliable and low-cost sensorless control strategies is of great significance to improving the performance and market competitiveness of new energy vehicles.
[0004] At present, the sensorless control strategies of permanent magnet synchronous motors are mainly divided into three categories: back-EMF method, high-frequency signal injection method and flux linkage method. Each method has its own applicable scenarios and limitations: the back-EMF method performs well in the medium and high speed segments, but its performance is limited at low speeds; the high-frequency signal injection method shows advantages in the low speed segment, but it will increase system complexity and loss; and the flux linkage method, especially the nonlinear flux linkage method, effectively eliminates speed dependence by introducing flux linkage as a state variable, thereby achieving stable and high-performance control in the range of low speed to medium and high speed, without the need for frequent algorithm switching, which greatly enhances the engineering application reliability of the sensorless control strategy. Therefore, the nonlinear flux linkage observer also has a higher signal-to-noise ratio and better low-speed performance.
[0005] However, the nonlinear flux method is currently mostly designed for surface-mounted permanent magnet synchronous motors, and there are applicability issues for salient pole permanent magnet synchronous motors with more complex structures. In order to solve this problem, some related literature has proposed the concept of effective flux, aiming to unify the sensorless control strategy of surface-mounted permanent magnet synchronous motors and salient pole permanent magnet synchronous motors in order to achieve wider applicability. However, this strategy has many debugging parameters and is not easy to be quickly applied in engineering. Summary of the invention
[0006] In order to solve the problem in the prior art that the method of performing sensorless control on a salient-pole permanent magnet synchronous motor based on a nonlinear flux observer has many debugging parameters and is not easy to quickly apply in engineering, the present application provides a sensorless control method for a salient-pole permanent magnet synchronous motor based on a nonlinear flux observer.
[0007] In a first aspect, the present application provides a sensorless control method for a salient-pole permanent magnet synchronous motor based on a nonlinear flux observer, which adopts the following technical solution: The sensorless control method of salient-pole permanent magnet synchronous motor based on nonlinear flux observer includes: Obtain a reference relationship model corresponding to the surface-mounted permanent magnet motor and a nonlinear flux model of the surface-mounted permanent magnet synchronous motor; wherein the reference relationship model includes a reference flux equation, a reference voltage equation and a reference torque equation; the reference flux equation represents the stator α-axis flux component ψ α and permanent magnet flux ψ f and the stator β-axis flux component ψ β and permanent magnet flux ψ f The reference voltage equation represents the stator α-axis voltage component u α and permanent magnet flux ψ f The relationship between the stator β-axis voltage component u β and permanent magnet flux ψ f The reference torque equation represents the electromagnetic torque T e and permanent magnet flux ψ f the relationship between; Obtain a first relationship model corresponding to the salient pole permanent magnet synchronous motor, and based on the first relationship model corresponding to the salient pole permanent magnet synchronous motor, the reference relationship model and the nonlinear flux model of the surface-mounted permanent magnet synchronous motor, adopt an equivalent replacement method to obtain the nonlinear flux model of the salient pole permanent magnet synchronous motor; wherein, the first relationship model includes a first flux equation, a first voltage equation and a first torque equation; the first flux equation characterizes the stator α-axis flux component ψ α and effective flux ψ act and the stator β-axis flux component ψ β and effective flux ψ act The relationship between the first voltage equation characterizes the stator α-axis voltage component u α and effective flux ψ act The relationship between the stator β-axis voltage component u β and effective flux ψ act The relationship between the first torque equation characterizes the electromagnetic torque T e and effective flux ψ act the relationship between; Based on the nonlinear flux model of the salient-pole permanent magnet synchronous motor, a phase-locked loop technology is used to extract rotor position information.
[0008] By adopting the above technical scheme, taking the first relationship model corresponding to the salient pole permanent magnet synchronous motor as the basis, and using the corresponding relationship equation of the surface-mounted permanent magnet synchronous motor and the nonlinear flux model of the surface-mounted permanent magnet synchronous motor as a reference, a nonlinear flux model for the salient pole permanent magnet synchronous motor is obtained; the nonlinear flux model of the salient pole permanent magnet synchronous motor is utilized, and the phase-locked loop technology is adopted to extract the rotor position information, so as to realize the sensorless control of the salient pole permanent magnet synchronous motor. In actual engineering applications, fewer parameters need to be adjusted, which well solves the problem that the existing method of sensorless control of the salient pole permanent magnet synchronous motor based on the nonlinear flux observer has many debugging parameters and is not easy to be quickly applied in engineering.
[0009] In a specific feasible implementation scheme, before obtaining the first relationship model corresponding to the salient-pole permanent magnet synchronous motor, the method further includes: Obtain an initial relationship model and an effective flux equation corresponding to the salient pole permanent magnet synchronous motor; wherein the initial relationship model includes an initial flux equation, an initial voltage equation and an initial torque equation; the initial flux equation represents the stator d-axis flux component ψ in a synchronous rotating coordinate system d and permanent magnet flux ψ f and the stator q-axis flux component ψ q and permanent magnet flux ψ f The relationship between the initial voltage equation represents the stator α-axis voltage component u in the stationary coordinate system. α and the stator α-axis flux component ψ α The relationship between the stator β-axis voltage component u β and the stator β-axis flux component ψ β The initial torque equation represents the electromagnetic torque T in the synchronous rotating coordinate system. e and permanent magnet flux ψ f The relationship between the effective flux equation and the effective flux ψ act and permanent magnet flux ψ f the relationship between; Based on the initial relationship model and the effective flux equation, a first relationship model corresponding to the salient-pole permanent magnet synchronous motor is determined.
[0010] By adopting the above technical solution, based on the concept of reference effective magnetic flux, the initial relationship model corresponding to the salient pole permanent magnet synchronous motor is converted and derived to obtain a first relationship model, which is convenient for subsequent comparison and equivalent replacement with the reference relationship model corresponding to the surface mounted permanent magnet motor.
[0011] In a specific embodiment, the reference flux equation includes: Where θ is the rotor angle, L s is the motor inductance, i α is the stator α-axis current component, i β is the stator β-axis current component; The reference voltage equation includes: Among them, R s is the stator resistance, ω e is the electrical angular speed; The reference torque equation includes: Among them, n p is the number of motor pole pairs; i q is the stator q-axis current component; The nonlinear flux model of the surface-mounted permanent magnet synchronous motor includes: in, for The first derivative of is the estimated value of the state variable x; γ is the observer gain; and for The two components of .
[0012] In a specific embodiment, the first torque equation includes: Among them, n p Motor pole pair number; i q is the stator q-axis current component; The first magnetic flux equation includes: Where θ is the rotor angle; L q is the stator q-axis inductance component; i α is the stator α-axis current component, i β is the stator β-axis current component; The first voltage equation includes: Among them, R s is the stator resistance; ω e is the electrical angular speed.
[0013] In a specific implementation scheme, the nonlinear flux linkage model of the salient pole permanent magnet synchronous motor includes: in, for The first derivative of is the estimated value of the state variable x; γ is the observer gain; and for The two components of θ is the rotor angle; L q is the stator q-axis inductance component, i α is the stator α-axis current component, i β is the stator β-axis current component; R s is the stator resistance.
[0014] In a specific embodiment, the initial magnetic flux equation includes: Among them, L d is the stator d-axis inductance component, L q is the stator q-axis inductance component; i d is the stator d-axis current component, i q is the stator q-axis current component; The initial voltage equation includes: Among them, R s is the stator resistance; i α is the stator α-axis current component, i β is the stator β-axis current component; The initial torque equation includes: Among them, n p Number of motor pole pairs; The effective flux equation includes: ψ act =(L d -L q )i d +ψ f (12).
[0015] In a specific implementation scheme, based on the nonlinear flux linkage model of the salient pole permanent magnet synchronous motor, a phase-locked loop technology is used to extract rotor position information, which specifically includes: in, is the estimated rotor angle; Δθ is the rotor angle θ and the estimated rotor angle The difference between and for The two components of is the estimated value of the state variable x; L q is the stator q-axis inductance component, i α is the stator α-axis current component, i β is the stator β-axis current component; K p =2ζω n , K i =ω n 2 ;ζ is the damping ratio;ω n is the natural angular frequency, ω n =2πf, f is the bandwidth.
[0016] In the second aspect, the present application provides a sensorless control system for a salient-pole permanent magnet synchronous motor based on a nonlinear flux observer, the control system comprising the sensorless control method for a salient-pole permanent magnet synchronous motor based on a nonlinear flux observer as described in the above-mentioned first aspect or any possible implementation scheme of the first aspect.
[0017] In the third aspect, the present application provides a terminal, which includes: a processor, a memory and a communication bus; the communication bus is used to realize the connection and communication between the processor and the memory, and the processor is used to execute one or more programs stored in the memory to realize the sensorless control method of the salient pole permanent magnet synchronous motor based on the nonlinear flux observer as described in the first aspect or any possible implementation scheme of the first aspect.
[0018] In a fourth aspect, the present application provides a computer-readable storage medium, which stores instructions. When the instructions are executed, the sensorless control method of a salient-pole permanent magnet synchronous motor based on a nonlinear flux observer is executed as described in the first aspect or any possible implementation scheme of the first aspect.
[0019] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: The first relationship model corresponding to the salient pole permanent magnet synchronous motor is used as a basis, and the corresponding relationship equation of the surface-mounted permanent magnet synchronous motor and the nonlinear flux model of the surface-mounted permanent magnet synchronous motor are used as references to obtain a nonlinear flux model for the salient pole permanent magnet synchronous motor. The nonlinear flux model of the salient pole permanent magnet synchronous motor is utilized, and the phase-locked loop technology is used to extract the rotor position information to realize the sensorless control of the salient pole permanent magnet synchronous motor. In actual engineering applications, fewer parameters need to be adjusted, which well solves the problem of more debugging parameters and difficulty in rapid application in engineering in the existing method of sensorless control of the salient pole permanent magnet synchronous motor based on the nonlinear flux observer. BRIEF DESCRIPTION OF THE DRAWINGS
[0020] Figure 1 It is a flow chart of a sensorless control method for a salient-pole permanent magnet synchronous motor based on a nonlinear flux observer in an embodiment of the present application; Figure 2 is a structural block diagram of using a phase-locked loop to extract rotor position information in an embodiment of the present application; Figure 3 (a) and (b) are waveform diagrams of estimated speed, actual speed and speed estimation error obtained by simulation in an embodiment of the present application; Figure 4 (a) and (b) are waveform diagrams of the actual angle, estimated angle, and angle estimation error obtained by simulation in an embodiment of the present application; Figure 5 is a stator dq axis current feedback waveform diagram obtained by simulation in an embodiment of the present application; Figure 6 (a) and (b) are examples of the present application. The angle tracking and angle estimation error waveforms obtained by simulation when ; Figure 7 (a) and (b) are examples of the present application. Schematic diagram of the angle tracking and angle estimation error waveforms obtained by simulation; Figure 8 (a) and (b) are examples of the present application. Schematic diagram of the angle tracking and angle estimation error waveforms obtained by simulation; Fig. 9 (a) and (b) are examples of the present application. Schematic diagram of the angle tracking and angle estimation error waveforms obtained by simulation. DETAILED DESCRIPTION
[0021] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.
[0022] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.
[0023] In the description of the embodiments of the present application, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprises", "has" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.
[0024] The present application provides a sensorless control method for a salient-pole permanent magnet synchronous motor based on a nonlinear flux observer. Figure 1 As shown, the method includes steps S1, S4-S5.
[0025] S1, obtaining a reference relationship model corresponding to the surface-mounted permanent magnet motor and a nonlinear flux model of the surface-mounted permanent magnet synchronous motor; wherein the reference relationship model includes a reference flux equation, a reference voltage equation and a reference torque equation; the reference flux equation represents the stator α-axis flux component ψ α and permanent magnet flux ψ f and the stator β-axis flux component ψ β and permanent magnet flux ψ f The reference voltage equation represents the stator α-axis voltage component u α and permanent magnet flux ψ f The relationship between the stator β-axis voltage component u β and permanent magnet flux ψ f The reference torque equation represents the electromagnetic torque T e and permanent magnet flux ψ f The relationship between.
[0026] In a possible implementation manner, the reference flux equation includes: Where θ is the rotor angle, L s is the motor inductance, i α is the stator α-axis current component, i β is the stator β-axis current component; The reference voltage equation includes: Among them, R s is the stator resistance, ω e is the electrical angular speed; The reference torque equation includes: Among them, n p is the number of motor pole pairs; i q is the stator q-axis current component; The nonlinear flux model of the surface-mounted permanent magnet synchronous motor includes: in, for The first derivative of is the estimated value of the state variable x, γ is the observer gain; y is the output variable, is the first-order derivative of the state variable x; and for The two components of .
[0027] The reference relationship model corresponding to the above-mentioned surface-mounted permanent magnet motor, namely the reference flux equation, the reference voltage equation and the reference torque equation, are known equations in the prior art; the nonlinear flux model of the surface-mounted permanent magnet synchronous motor is a formula used in the prior art for performing sensorless control on the surface-mounted permanent magnet synchronous motor. For the specific process and principle from the reference relationship model corresponding to the surface-mounted permanent magnet motor to the construction of the nonlinear flux model of the surface-mounted permanent magnet synchronous motor, those skilled in the art can refer to the relevant literature by themselves. The following is a general description of the process: First, based on the known flux, voltage and torque equations of the surface-mounted permanent magnet synchronous motor in the stationary coordinate system, that is, formula (1), formula (2) and formula (3), the flux equation in the stationary coordinate system is defined as the state variable x, where x contains two components x1 and x2, and x1 = ψ α 、x2=ψ β , substituting formula (1) into it, we can get an equation about the state variable x:
[0028] After that, the state variable x is first-order derived, that is, the first-order derivative of formula (4) is obtained to obtain the first-order derivative of the state variable x Since in formula (4), The derivative is equal to According to formula (2), we can get: Then define the output variable as y, where y contains two components y1 and y2. Then we can get the following formula:
[0029] Then, to construct the nonlinear flux observer for the surface-mounted permanent magnet motor, the estimated value of the state variable x is taken as And construct about The formula is: in, Contains two components and and for The two components of .
[0030] Finally, the nonlinear flux model of the surface-mounted permanent magnet synchronous motor is constructed, that is, formula (7) is: in, for The first derivative of is the estimated value of the state variable x; γ is the observer gain and γ>0, the value of γ can be adjusted according to the actual situation as needed; Combined with formula (5), y is the output variable, and for The two components of
[0031] According to formula (7), when When , the estimated value of the state variable Converges to the real motor value, so combining equations (4) and (6) can get equation (8), thereby estimating the rotor position θ:
[0032] S4, obtaining a first relationship model corresponding to the salient pole permanent magnet synchronous motor, and obtaining a nonlinear flux model of the salient pole permanent magnet synchronous motor by using an equivalent replacement method based on the first relationship model corresponding to the salient pole permanent magnet synchronous motor, the reference relationship model and the nonlinear flux model of the surface mounted permanent magnet synchronous motor; The first relational model includes a first flux equation, a first voltage equation and a first torque equation; the first flux equation represents the stator α-axis flux component ψ α and effective flux ψ act and the stator β-axis flux component ψ β and effective flux ψ act The relationship between the first voltage equation characterizes the stator α-axis voltage component u α and effective flux ψ act The relationship between the stator β-axis voltage component u β and effective flux ψ act The relationship between the first torque equation characterizes the electromagnetic torque T e and effective flux ψ act The relationship between.
[0033] In a possible implementation manner, the first torque equation includes: Among them, n p Motor pole pair number; i q is the stator q-axis current component; The first magnetic flux equation includes: Where θ is the rotor angle; L q is the stator q-axis inductance component; i α is the stator α-axis current component, i β is the stator β-axis current component; The first voltage equation includes: Among them, R s is the stator resistance; ω e is the electrical angular speed.
[0034] The nonlinear flux linkage model of the salient pole permanent magnet synchronous motor includes: in, for The first derivative of is the estimated value of the state variable x; γ is the observer gain, preferably, y is the output variable, is the first-order derivative of the state variable x; and for The two components of
[0035] When determining the value of the observer gain γ, the following method can be used: First, define the estimation error of the state variable as The error dynamics equation can be derived as: in, for The first derivative of .
[0036] Afterwards, according to the Lyapunov theory, the stability analysis of formula (28) is performed, and it can be concluded that at a constant speed, γ must satisfy: If γ is too large, it will cause the estimated magnetic flux to oscillate significantly, resulting in system oscillation. If γ is too small, the angle convergence speed will be too slow, affecting the dynamic performance of the system. It is necessary to continuously adjust γ to meet the static and dynamic performance of the system. Therefore, the value of γ is determined through debugging experience as follows:
[0037] Those skilled in the art can understand that, in step S4, an equivalent replacement method is used to obtain a nonlinear flux model of a salient-pole permanent magnet synchronous motor, which specifically includes: The first relational model corresponding to the salient pole permanent magnet synchronous motor, i.e., the first torque equation (13), the first flux equation (17) and the first voltage equation (20), is analogized to the reference relational model, i.e., the reference torque equation (3), the reference flux equation (1) and the reference voltage equation (2). It can be seen that the equations involved in the salient pole permanent magnet synchronous motor are compared with the equations involved in the surface mounted permanent magnet synchronous motor. f Equivalently replaced by ψ act , L s Equivalently replaced by L q Therefore, the ψ in the nonlinear flux model of the surface-mounted permanent magnet synchronous motor is f and L s By performing equivalent substitution, we can obtain a nonlinear flux model suitable for salient pole permanent magnet synchronous motors, that is, replace ψ in formula (7) with f Equivalently replace it with ψ act , L s Equivalently replace with L q , we can get formula (23).
[0038] S5, based on the nonlinear flux model of the salient pole permanent magnet synchronous motor, using phase-locked loop technology to extract rotor position information.
[0039] In a possible implementation, based on the nonlinear flux linkage model of the salient pole permanent magnet synchronous motor, a phase-locked loop technology is used to extract rotor position information, specifically including: in, Estimate the angle of the rotor, that is, the desired rotor position information; Δθ is the rotor angle θ and the estimated rotor angle The difference between and for The two components of For K p and K i , K p =2ζω n , K i =ω n 2 ; where ζ is the damping ratio, ω n is the natural angular frequency; the value of ζ is generally 0.707; ω n =2πf, f is the bandwidth, the unit is Hz; That is to say, according to the nonlinear flux model formula (23) and formula (26) of the salient pole permanent magnet synchronous motor, the method of this embodiment is adopted. In actual use, as long as the rate of change of the angle does not exceed the bandwidth f of the phase-locked loop, the system can track well. The node before the integration is the speed estimation value The parameters that need to be debugged in the entire debugging process are only the gain γ and the phase-locked loop bandwidth f, and the parameters that need to be debugged are relatively few.
[0040] Since the flux estimated by the nonlinear observer has noise and high-frequency jitter, a phase-locked loop is used to extract the rotor position information. Figure 2 , using a phase-locked loop, to obtain the estimated rotor angle The specific description of the process of the equation is: First, the input of the phase-locked loop can be obtained using the sum-difference formula: When the error value is small, So there is Substituting formula (25) into formula (24), we can obtain Will It is denoted as Δθ, and after transformation, it is obtained:
[0041] After that, construct the formula for PI control: The transfer function of formula (26) can be regarded as a standard second-order system, and the proportional and integral gains of the PI controller are K p =2ζω n , K i =ω n 2 ;and
[0042] Therefore, steps S1, S4-S5 take the first relationship model corresponding to the salient pole permanent magnet synchronous motor as the basis, and use the corresponding relationship equation of the surface-mounted permanent magnet synchronous motor and the nonlinear flux model of the surface-mounted permanent magnet synchronous motor as a reference, so as to obtain the nonlinear flux model for the salient pole permanent magnet synchronous motor; the nonlinear flux model of the salient pole permanent magnet synchronous motor is utilized, and the phase-locked loop technology is adopted to extract the rotor position information to realize the sensorless control of the salient pole permanent magnet synchronous motor. In actual engineering applications, fewer parameters need to be adjusted, which well solves the problem that the existing method of sensorless control of the salient pole permanent magnet synchronous motor based on the nonlinear flux observer has many debugging parameters and is not easy to be quickly applied in engineering.
[0043] In a possible implementation manner, before step S4, obtaining the first relationship model corresponding to the salient-pole permanent magnet synchronous motor, further includes steps S2-S3: S2, obtaining the initial relationship model and effective flux equation corresponding to the salient pole permanent magnet synchronous motor; wherein the initial relationship model includes an initial flux equation, an initial voltage equation and an initial torque equation; the initial flux equation represents the stator d-axis flux component ψ in the synchronous rotating coordinate system d and permanent magnet flux ψ f and the stator q-axis flux component ψ q and permanent magnet flux ψ f The relationship between the initial voltage equation represents the stator α-axis voltage component u in the stationary coordinate system. α and the stator α-axis flux component ψ α The relationship between the stator β-axis voltage component u β and the stator β-axis flux component ψ β The initial torque equation represents the electromagnetic torque T in the synchronous rotating coordinate system. e and permanent magnet flux ψ f The relationship between the effective flux equation and the effective flux ψ act and permanent magnet flux ψ f the relationship between; S3. Determine a first relationship model corresponding to the salient-pole permanent magnet synchronous motor based on the initial relationship model and the effective flux equation.
[0044] Therefore, referring to the concept of effective magnetic flux, the initial relationship model corresponding to the salient pole permanent magnet synchronous motor is converted and derived to obtain the first relationship model, which is convenient for subsequent comparison and equivalent replacement with the reference relationship model corresponding to the surface mounted permanent magnet motor.
[0045] Specifically, based on the initial relationship model and the effective flux equation, a first relationship model corresponding to the salient pole permanent magnet synchronous motor is obtained, which specifically includes: Based on the initial flux equation and the effective flux equation, obtaining the first flux equation; The first voltage equation is obtained based on the initial voltage equation, the initial flux equation and the effective flux equation; the first torque equation is obtained based on the initial torque equation and the effective flux equation.
[0046] In a possible implementation manner, the initial magnetic flux equation includes: Among them, L d is the stator d-axis inductance component, L q is the stator q-axis inductance component; i d is the stator d-axis current component, i q is the stator q-axis current component; The initial voltage equation includes: Among them, R s is the stator resistance; i α is the stator α-axis current component, i β is the stator β-axis current component; The initial torque equation includes: Among them, n p Number of motor pole pairs; The effective flux equation includes: ψ act =(L d -L q )i d +ψ f (12) Among them, L d is the stator d-axis inductance component; i d is the stator d-axis current component.
[0047] The derivation and calculation process of step S3 is described in detail below: On the one hand, according to the effective flux equation (12), we get ψ f =ψ act -(L d -Lq )i d ; Substitute it into the initial magnetic flux equation (10), and we get: Therefore, according to formula (14), the effective flux ψ act The dq-axis component ψ in the synchronously rotating coordinate system actd and ψ actq They are: That is, the effective flux vector ψ act The q-axis component is in the same direction as the d-axis, and the q-axis component is 0. Then transform it to the stationary coordinate system and obtain the effective magnetic flux α-β axis component ψ actα and ψ actβ They are: In addition, according to formula (14), transforming it to the stationary coordinate system, we can obtain: ψ α =ψ actα +L q i α =ψ act cosθ+L q i α ψ β =ψ actβ +L q i β =ψ act sinθ+L q i β Among them, ψ actα is the component of effective magnetic flux on the α axis, ψ actβ is the component of the effective magnetic flux on the β axis; the first magnetic flux equation is as follows:
[0048] Further, according to formula (17) and the initial voltage equation, formula (17) is derived and and Substituting the initial voltage equation, we can obtain formula (18): According to formula (16), the result of the last term in formula (18) is: Substituting formula (19) into formula (18), we can get the first voltage equation, formula (20), which is:
[0049] On the other hand, according to the effective flux equation (12) and the initial torque equation (11), the equation (11) is transformed into: Substituting formula (12) into the equation, we can obtain the first torque equation:
[0050] So far, the first flux equation, the first voltage equation and the first torque equation have been obtained according to the initial flux equation, the effective flux equation and the initial voltage equation.
[0051] It can be understood by those skilled in the art that in a salient pole permanent magnet synchronous motor,
[0052] In order to verify the feasibility of the sensorless control strategy of the salient-pole permanent magnet synchronous motor based on the nonlinear flux observer in this embodiment, a simulation model is built in the Matlab / Simulink environment. The parameters of the built-in salient-pole permanent magnet synchronous motor are shown in Table 1. The simulation switching frequency is 8 kHz, the PWM period Ts=0.000125, and the gain γ value is 2000.
[0053] Table 1 Parameters of salient pole permanent magnet synchronous motor Before simulation, discretization method is first performed: In order to ensure the accuracy of modeling discretization, the state transition matrix is used for discretization. By transforming formula (23), we can get: In formula (32), let Then we get: After rearranging, we can get the following equation: in, B is the identity matrix,
[0054] Discretize using the state transfer matrix: x(k+1)=A d (k)x(k)+B d (k)u(k) (37) Where k refers to the kth moment after quantization, and the simulation and experimental discretization adopts the second-order form, that is, Further deduction based on formulas (38) and (39) yields:
[0055] The steady-state and dynamic performance of the system are verified as follows: Simulation condition 1: The motor starts running without load from the initial static state and adjusts the speed to 800r / min. After 2 seconds, the rated torque is suddenly increased. The simulation results are as follows: Figure 3 As shown in (a), the maximum drop in motor speed is 85r / min, and it recovers to 800r / min within 0.4 seconds. After stabilization, the maximum error between the actual motor speed and the estimated speed does not exceed 1r / min. Figure 4 In (a) and (b), the maximum instantaneous error of the actual motor angle is -0.08 rad compared with the estimated angle. After stabilization, the error range of the estimated angle is -0.015 rad to 0.008 rad. The change impact of the motor stator dq axis current at 2 seconds is small, and the operation is stable. Figure 5 shown.
[0056] Simulation condition 2: The motor is loaded and adjusted to the rated speed in 4 seconds. During the speed adjustment process, the maximum error between the actual motor speed and the estimated speed is 24r / min. After stabilization, the maximum error is 1r / min. Figure 3 As shown in (b) in .
[0057] It can be seen from the above simulation results that the motor has a fast dynamic response, a small fluctuation in the estimated speed, and a small angle tracking error, which meets the control requirements and verifies the effectiveness of the method adopted in this embodiment.
[0058] The motor parameter deviation is verified as follows: In order to verify the robustness of parameter changes, the motor direct axis inductance Quadrature-axis inductance Stator resistance Permanent magnet flux The parameter values are set as shown in Table 1. Under rated speed conditions, deviations are made according to the conditions. The effective range of deviations and angle error data are shown in Table 2. Under each parameter deviation condition, the steady-state speed error is ±1rpm.
[0059] Figure 6-Figure 9 The corresponding angle tracking and angle estimation errors when the motor parameters deviate. Specifically, Figure 6 (a) and (b) represent , the corresponding actual angle and estimated angle waveforms, and the angle estimation error waveform; Figure 7 (a) and (b) represent , the corresponding actual angle and estimated angle waveforms, and the angle estimation error waveform; Figure 8 (a) and (b) represent , the corresponding actual angle and estimated angle waveforms, and the angle estimation error waveform; Fig. 9 (a) and (b) represent , the corresponding actual angle and estimated angle waveforms, as well as the angle estimation error waveform.
[0060] According to the simulation results, the angle estimation is accurate, the speed estimation is stable and convergent, the fluctuation range is small, and the system can remain stable within a certain parameter deviation range. The method of this embodiment improves the robustness of the system.
[0061] Table 2 Parameter deviation range of system stability Therefore, based on the nonlinear flux observer of the surface-mounted permanent magnet synchronous motor, this application refers to the concept of effective flux and designs a nonlinear flux algorithm that is also suitable for salient pole permanent magnet synchronous motors. The simulation and experimental results show that the algorithm has simple parameter debugging, fast motor dynamic response, small estimated speed fluctuation and angle tracking error, strong robustness to parameter changes, and high engineering practical value.
[0062] An embodiment of the present application also provides a sensorless control system for a salient-pole permanent-magnet synchronous motor based on a nonlinear flux observer, and applies the sensorless control method for a salient-pole permanent-magnet synchronous motor based on a nonlinear flux observer described in the above embodiment.
[0063] An embodiment of the present application also provides a terminal, which includes: a processor, a memory and a communication bus; the communication bus is used to realize the connection and communication between the processor and the memory, and the processor is used to execute one or more programs stored in the memory to realize the sensorless control method of the salient pole permanent magnet synchronous motor based on the nonlinear flux observer as described in the above embodiment.
[0064] An embodiment of the present application also provides a computer-readable storage medium, which stores instructions. When the instructions are executed, the sensorless control method of a salient-pole permanent magnet synchronous motor based on a nonlinear flux observer as described in the above embodiment is executed.
[0065] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.
Claims
1. A sensorless control method for a salient-pole permanent magnet synchronous motor based on a nonlinear flux observer, characterized in that: include: Obtain a reference relationship model corresponding to the surface-mounted permanent magnet motor and a nonlinear flux model of the surface-mounted permanent magnet synchronous motor; wherein the reference relationship model includes a reference flux equation, a reference voltage equation and a reference torque equation; the reference flux equation represents the stator α-axis flux component ψ α and permanent magnet flux ψ f and the stator β-axis flux component ψ β and permanent magnet flux ψ f The reference voltage equation represents the stator α-axis voltage component u α and permanent magnet flux ψ f The relationship between the stator β-axis voltage component u β and permanent magnet flux ψ f The reference torque equation represents the electromagnetic torque T e and permanent magnet flux ψ f the relationship between; Obtain a first relationship model corresponding to the salient pole permanent magnet synchronous motor, and based on the first relationship model corresponding to the salient pole permanent magnet synchronous motor, the reference relationship model and the nonlinear flux model of the surface-mounted permanent magnet synchronous motor, adopt an equivalent replacement method to obtain the nonlinear flux model of the salient pole permanent magnet synchronous motor; wherein, the first relationship model includes a first flux equation, a first voltage equation and a first torque equation; the first flux equation represents the stator α-axis flux component ψ α and effective flux ψ act and the stator β-axis flux component ψ β and effective flux ψ act The relationship between the first voltage equation characterizes the stator α-axis voltage component u α and effective flux ψ act The relationship between the stator β-axis voltage component u β and effective flux ψ act The relationship between the first torque equation characterizes the electromagnetic torque T e and effective flux ψ act the relationship between; Based on the nonlinear flux model of the salient-pole permanent magnet synchronous motor, a phase-locked loop technology is used to extract rotor position information.
2. The sensorless control method of a salient-pole permanent magnet synchronous motor based on a nonlinear flux observer according to claim 1 is characterized in that: Before obtaining the first relationship model corresponding to the salient-pole permanent magnet synchronous motor, the method further includes: Obtain an initial relationship model and an effective flux equation corresponding to the salient pole permanent magnet synchronous motor; wherein the initial relationship model includes an initial flux equation, an initial voltage equation and an initial torque equation; the initial flux equation represents the stator d-axis flux component ψ in a synchronous rotating coordinate system d and permanent magnet flux ψ f and the stator q-axis flux component ψ q and permanent magnet flux ψ f The relationship between the initial voltage equation represents the stator α-axis voltage component u in the stationary coordinate system. α and the stator α-axis flux component ψ α The relationship between the stator β-axis voltage component u β and the stator β-axis flux component ψ β The initial torque equation represents the electromagnetic torque T in the synchronous rotating coordinate system. e and permanent magnet flux ψ f The relationship between the effective flux equation and the effective flux ψ act and permanent magnet flux ψ f the relationship between; Based on the initial relationship model and the effective flux equation, a first relationship model corresponding to the salient-pole permanent magnet synchronous motor is determined.
3. The sensorless control method of a salient-pole permanent magnet synchronous motor based on a nonlinear flux observer according to claim 1 is characterized in that: The reference flux equation includes: Where θ is the rotor angle, L s is the motor inductance, i α is the stator α-axis current component, i β is the stator β-axis current component; The reference voltage equation includes: Among them, R s is the stator resistance, ω e is the electrical angular speed; The reference torque equation includes: Among them, n p is the number of motor pole pairs; i q is the stator q-axis current component; The nonlinear flux model of the surface-mounted permanent magnet synchronous motor includes: in, for The first derivative of is the estimated value of the state variable x; γ is the observer gain; and for The two components of .
4. The sensorless control method of a salient-pole permanent magnet synchronous motor based on a nonlinear flux observer according to claim 1 is characterized in that: The first torque equation includes: Among them, n p Motor pole pair number; i q is the stator q-axis current component; The first magnetic flux equation includes: Where θ is the rotor angle; L q is the stator q-axis inductance component; i α is the stator α-axis current component, i β is the stator β-axis current component; The first voltage equation includes: Among them, R s is the stator resistance; ω e is the electrical angular speed.
5. The sensorless control method of a salient-pole permanent magnet synchronous motor based on a nonlinear flux observer according to claim 1, characterized in that: The nonlinear flux linkage model of the salient pole permanent magnet synchronous motor includes: in, for The first derivative of is the estimated value of the state variable x; γ is the observer gain; and for The two components of θ is the rotor angle; L q is the stator q-axis inductance component, i α is the stator α-axis current component, i β is the stator β-axis current component; R s is the stator resistance.
6. The sensorless control method of a salient-pole permanent magnet synchronous motor based on a nonlinear flux observer according to claim 2 is characterized in that: The initial flux equation includes: Among them, L d is the stator d-axis inductance component, L q is the stator q-axis inductance component; i d is the stator d-axis current component, i q is the stator q-axis current component; The initial voltage equation includes: Among them, R s is the stator resistance; i α is the stator α-axis current component, i β is the stator β-axis current component; The initial torque equation includes: Among them, n p is the number of motor pole pairs; The effective flux equation includes: ψ act =(L d -L q )i d +ψ f (12)。 7. The sensorless control method of a salient-pole permanent magnet synchronous motor based on a nonlinear flux observer according to claim 1, characterized in that: Based on the nonlinear flux linkage model of the salient pole permanent magnet synchronous motor, the phase-locked loop technology is used to extract the rotor position information, which specifically includes: in, is the estimated rotor angle; Δθ is the rotor angle θ and the estimated rotor angle The difference between and for The two components of is the estimated value of the state variable x; L q is the stator q-axis inductance component, i α is the stator α-axis current component, i β is the stator β-axis current component; K p =2ζω n , K i =ω n 2 ;ζ is the damping ratio;ω n is the natural angular frequency, ω n =2πf, f is the bandwidth.
8. A sensorless control system for a salient-pole permanent magnet synchronous motor based on a nonlinear flux observer, characterized in that: A sensorless control method for a salient-pole permanent magnet synchronous motor based on a nonlinear flux observer is applied.
9. A terminal, characterized in that: include: A processor, a memory and a communication bus; the communication bus is used to realize the connection and communication between the processor and the memory, and the processor is used to execute one or more programs stored in the memory to realize the sensorless control method of the salient-pole permanent magnet synchronous motor based on the nonlinear flux observer as described in any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the sensorless control method of a salient-pole permanent magnet synchronous motor based on a nonlinear flux observer as described in any one of claims 1 to 7 is executed.