Surface-mounted permanent magnet synchronous motor all-parameter online identification and efficiency optimization control method considering iron loss influence

Abstract

The invention discloses a surface-mounted permanent magnet synchronous motor all-parameter online identification and efficiency optimization control method considering iron loss influence, and relates to the technical field of motor control, the method comprises the following steps: based on a mathematical model of an SPMSM considering motor iron loss, obtaining an expression of a d-axis current reference value of loss minimum control; an SPMSM parameter identification model of the lumped parameters is established, and on-line identification of stator resistance, inductance, permanent magnet flux linkage and iron consumption resistance is achieved based on identification of the lumped parameters; based on online identification of stator resistance, inductance, permanent magnet flux linkage and iron consumption resistance, through an expression of a d-axis current reference value of loss minimum control, setting of a current reference value under SPMSM loss minimum control is realized. The invention provides an effective method for all-parameter online identification and efficiency optimization control of the surface-mounted permanent magnet synchronous motor considering the iron loss influence, and the motor efficiency and robustness of the SPMSM are effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of motor control, and in particular to a method for online identification of all parameters and efficiency optimization control of a surface-mounted permanent magnet synchronous motor. Background Art

[0002] Permanent magnet synchronous motors (PMSMs) have the advantages of simple structure and high stability, and are widely used in power traction, CNC machine tools and other fields. In industrial servo applications where permanent magnet synchronous motors need to operate for long periods of time, efficiency is a key indicator of PMSM performance. When a permanent magnet synchronous motor operates in steady state, optimal motor efficiency is equivalent to minimal loss operation. Motor losses include copper loss, iron loss, mechanical loss, and stray loss. Copper loss and iron loss are the two most important sources of PMSM losses and are affected by the distribution of d- and q-axis currents.

[0003] In terms of establishing current solution models, there are currently two types: one is the direct solution method and the other is the indirect solution method.

[0004] 1. Direct solution: The mathematical model of a PMSM with iron losses is highly complex. Under the loss-minimizing control strategy for a PMSM, solving the analytical current expression involves high-order nonlinear equations, which makes direct solutions extremely difficult. To overcome this challenge, approximation is a common approach.

[0005] Specifically, on the one hand, a polynomial fitting is performed on the analytical expression of the current that satisfies the minimum loss condition; on the other hand, an approximation is performed on the PMSM equivalent circuit considering the influence of iron loss. Through the above approximation operation, the process of obtaining the d-axis current under the minimum loss condition is simplified.

[0006] Indirect solution methods: Indirect solution methods establish motor efficiency and loss calculation formulas or criteria that reflect motor loss conditions, and use search algorithms or integrators to obtain the current reference value for minimum loss. However, the implementation of such methods usually requires additional hardware circuits to detect input power, which significantly increases hardware costs. Especially in high-precision industrial applications, the cost of the sensor may exceed the cost of the controller itself.

[0007] Unlike conventional motor mathematical models, motor mathematical models that consider iron loss include not only stator resistance, inductance, and permanent magnet flux linkage, but also iron loss resistance. In existing literature on loss-minimizing control, table lookup methods are widely used to effectively mitigate the adverse effects of parameter mismatch. However, to fully account for the impact of ambient temperature variations and varying motor operating conditions, this table lookup method requires extensive pre-testing. This experimental process is not only tedious and complex, but also, from a practical perspective, it is impractical to conduct such comprehensive testing for every motor. Furthermore, the use of table lookup methods inevitably requires the application of interpolation algorithms, which inherently introduce certain errors, thus affecting the accuracy of parameter acquisition.

[0008] Online identification technology of motor parameters provides an effective way to solve the above problems. However, most of the existing parameter identification methods are based on conventional motor mathematical models and mainly focus on the online identification of three parameters: stator resistance, inductance, and permanent magnet flux. For example, the invention patent with application number 202110360846.6 discloses a method for establishing an electromagnetic model of a full-parameter permanent magnet motor and a parameter identification method. The establishment method includes: correcting the flux equation according to the influence of the saturation effect on the permanent magnet flux, and on this basis, further correcting the flux equation and the voltage equation according to the influence of temperature on the permanent magnet flux and stator resistance. The parameter identification method includes: establishing a thermal network with the key components in the motor as nodes, calculating the losses in the motor that will obviously cause temperature rise according to the corrected electromagnetic model and distributing them to each node as a heat source, comprehensively considering the thermal resistance between nodes and the heat source of each node, and establishing a heat transfer equation; establishing an objective function based on the established equation, solving the minimum value of the objective function through temperature rise experiments, and thus identifying all parameters to be identified in the heat transfer equation.

[0009] However, current research on the online identification of stator resistance, inductance, permanent magnet flux linkage and iron loss resistance based on the mathematical model of SPMSM taking iron loss into consideration is still insufficient and lacks mature and effective technical means. Summary of the Invention

[0010] In response to the technical problem that it is difficult to perform online identification of the stator resistance, inductance, permanent magnet flux and iron loss resistance of the mathematical model of SPMSM considering the iron loss of the motor, the present invention proposes a full-parameter online identification and efficiency optimization control method of a surface-mounted permanent magnet synchronous motor considering the influence of iron loss, which realizes the online identification of all parameters of SPMSM including stator resistance, inductance, permanent magnet flux and iron loss resistance. It is suitable for the surface-mounted synchronous motor running in the speed working mode and can effectively improve the motor efficiency and robustness of the SPMSM.

[0011] In order to achieve the above object, the technical solution of the present invention is achieved as follows:

[0012] A method for online identification of all parameters and efficiency optimization control of a surface-mounted permanent magnet synchronous motor considering the influence of iron loss includes the following steps:

[0013] S1. Based on the mathematical model of the SPMSM considering the motor iron loss, obtain the expression of the d-axis current reference value for loss minimum control;

[0014] S2. Establish a lumped parameter SPMSM parameter identification model. Based on the identification of lumped parameters, online identification of stator resistance, inductance, permanent magnet flux linkage, and iron loss resistance is achieved.

[0015] S3. Based on the online identification of stator resistance, inductance, permanent magnet flux linkage, and iron loss resistance, the current reference value under SPMSM loss minimum control is set through the expression of the d-axis current reference value under loss minimum control.

[0016] Specifically, the method for obtaining the expression of the d-axis current reference value for loss minimum control based on the mathematical model of the SPMSM considering the motor iron loss is:

[0017] ① Based on the mathematical model of the SPMSM including the motor iron loss, the voltage equation I, torque equation, and expressions based on the stator d-axis and q-axis currents of the SPMSM are obtained;

[0018] ② Based on the expressions of the stator d and q axis currents, the relationship between the d and q axis current components that actually generate torque and the stator d and q axis currents is obtained, as well as the relationship between the iron loss current component in the d and q axis currents and the stator d and q axis currents; and the d axis current i is determined. d and q-axis current i q The mathematical relationships that exist;

[0019] Based on steps ① and ②, the loss minimization control of the SPMSM is equivalent to minimizing the sum of the copper loss and iron loss of the SPMSM motor by distributing the d-axis and q-axis currents, and the expression I of the copper loss and iron loss of the SPMSM motor is obtained;

[0020] According to the expression I of the copper loss and iron loss of the SPMSM motor and the extreme value solution equation and constraint conditions of the loss minimum control, the expression II of the iron loss of the SPMSM motor and the expression II of the copper loss of the SPMSM motor are obtained;

[0021] According to the expression II of the motor iron loss of SPMSM and the expression II of the motor copper loss of SPMSM, the expression of the d-axis current reference value under the loss minimum constraint is obtained.

[0022] Specifically, the expression of the d-axis current reference value under the minimum loss constraint is:

[0023]

[0024] Among them, i d is the d-axis current, R s and R Fe are stator resistance and iron loss resistance respectively, L s ,λ f and ω e are inductance, permanent magnet flux amplitude and electric angular velocity respectively; T e is the motor torque, n p is the number of pole pairs of the surface-mounted permanent magnet synchronous motor.

[0025] Specifically, the method for establishing the SPMSM parameter identification model of lumped parameters and realizing online identification of stator resistance, inductance, permanent magnet flux linkage and iron loss resistance based on the identification of lumped parameters is as follows:

[0026] Obtain the SPMSM voltage equation II considering the iron loss resistance in steady state. Substitute the expression representing the relationship between the d-axis and q-axis current components that actually generate torque in the d-axis and q-axis currents and the stator d-axis and q-axis currents into the SPMSM voltage equation II to obtain the SPMSM voltage equation III.

[0027] The coefficients in the SPMSM voltage equation III are defined as lumped parameters a, b, c, and d respectively;

[0028] Establish the relationship between the lumped parameters and the motor parameters: Substitute the stator resistance R s Expressed as lumped parameters a, b, c, d and electrical angular velocity ω e function; the permanent magnet flux λ f Expressed as lumped parameters c, d and electrical angular velocity ω e function; the inductor L s Expressed as lumped parameters b, c, d and electrical angular velocity ω e function; the iron loss resistor R Fe Expressed as lumped parameters b, c, d and electrical angular velocity ω e function;

[0029] Under a preset time scale, by setting two different sets of d-axis currents, four sets of voltage and current information are obtained to construct a full-rank parameter identification matrix;

[0030] Based on the parameter identification matrix, the least square method with forgetting factor is used to identify the lumped parameters.

[0031] The identified lumped parameters are substituted into the relationship expression between the lumped parameters and the motor parameters to realize the online identification of all parameters of the SPMSM.

[0032] Specifically, the SPMSM voltage equation III is:

[0033]

[0034] Among them, u d and u q are d-axis and q-axis voltages, respectively, R s and R Fe are stator resistance and iron loss resistance respectively; i d and i q are d-axis and q-axis currents respectively;

[0035] The lumped parameters a, b, c, and d are:

[0036] Specifically, the stator resistance R s Expressed as:

[0037] Specifically, the permanent magnet flux λ f Expressed as:

[0038] Specifically, the inductor L s Expressed as:

[0039] Specifically, the iron loss resistor R Fe Expressed as:

[0040] Specifically, the parameter identification matrix is ​​expressed as:

[0041]

[0042] Among them, u d1 、u q1 、i d1 、i q1 are the d-axis and q-axis voltages and currents in the first stage; u d2 、u q2 、i d2 、i q2 are the d-axis and q-axis voltages and currents in the second stage;

[0043] The least squares method with forgetting factor is used to identify the lumped parameters. The iterative formula is:

[0044]

[0045] Where, Among them, θ(k) is the parameter matrix, is the coefficient matrix, K(k) is the gain matrix; α is the forgetting factor, P(k) is a 4th-order matrix, and I is a 4th-order identity matrix.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] The present invention provides an effective method for online identification of all parameters and efficiency optimization control of surface-mounted permanent magnet synchronous motors (SPMSMs) that consider the influence of iron loss. This method implements online identification of all parameters of the SPMSM, including stator resistance, inductance, permanent magnet flux linkage, and iron loss resistance. This method is applicable to surface-mounted synchronous motors operating in a speed operating mode and can effectively improve the efficiency and robustness of the SPMSMs. By setting the current reference value under SPMSM loss minimum control, it helps to track the minimum loss point of the surface-mounted permanent magnet synchronous motor, thereby improving the robustness of control. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0049] Figure 1 Flow chart of the method of the present invention.

[0050] Figure 2 is the mathematical model of the SPMSM including the motor iron loss.

[0051] Figure 3 1 is a waveform diagram of motor copper loss, motor iron loss, loss and motor efficiency as a function of d-axis current in one embodiment of the present invention.

[0052] Figure 4 This is a voltage and current extraction process under two different torques in one embodiment of the present invention.

[0053] Figure 5 This is a process block diagram of parameter identification of the surface-mounted permanent magnet synchronous motor of the present invention. DETAILED DESCRIPTION

[0054] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without creative work are within the scope of protection of the present invention.

[0055] A full-parameter online identification and efficiency optimization control method for surface-mounted permanent magnet synchronous motor considering the influence of iron loss is proposed. Figure 1 As shown, the following steps are included:

[0056] S1. Based on the mathematical model of the SPMSM considering the motor iron loss, obtain the expression of the d-axis current reference value for loss minimization control.

[0057] When establishing a mathematical model of a surface mounted permanent magnet synchronous motor (SPMSM) that takes into account the influence of motor iron loss, the iron loss component is presented in the form of iron loss resistance. The mathematical model of the SPMSM that includes motor iron loss is as follows: Figure 2 As shown, the voltage equation I and torque equation of SPMSM are expressed as follows:

[0058]

[0059] The voltage equation I of SPMSM is the motor stator voltage equation including transient terms.

[0060] Where R s and R Fe are stator resistance and iron loss resistance respectively; u d and u q are d-axis and q-axis voltages respectively; i dt and i qt are the d-axis and q-axis current components that actually generate torque in the d-axis and q-axis currents respectively; L s ,λ f and ω e are inductance, permanent magnet flux amplitude and electric angular velocity respectively; T e is the motor torque; p is the differential operator, n p is the number of pole pairs of the surface-mounted permanent magnet synchronous motor; ω e is the electrical angular velocity.

[0061] Expressions based on d-axis and q-axis currents:

[0062]

[0063] The relationship between the d-axis and q-axis current components that actually generate torque and the d-axis and q-axis currents is obtained:

[0064]

[0065] And the relationship between the iron loss current component in the d and q axis currents and the d and q axis currents:

[0066]

[0067] Where i d and i q are d-axis and q-axis currents respectively; i dFe and iqFe are the iron loss current components in the d and q axis currents respectively.

[0068] Furthermore, the d-axis current i d and q-axis current i q The following relationship exists:

[0069]

[0070] The motor losses of an SPMSM include copper loss, iron loss, mechanical loss, and stray loss. Copper and iron losses are affected by the distribution of currents along the d and q axes. Therefore, the SPMSM's loss minimization control (LMC) is equivalent to minimizing the sum of the SPMSM's copper and iron losses by allocating currents along the d and q axes.

[0071] The expression I for the copper loss and iron loss of the SPMSM motor is:

[0072]

[0073] Where, P Cu is the motor copper loss; P Fe is the motor iron loss.

[0074] When the SPMSM is in speed control mode, the torque is determined by the load. When the load is constant, the LMC control of the SPMSM is expressed as an extreme value solution under conditional constraints:

[0075]

[0076] Where, P loss are the copper loss and iron loss of the motor.

[0077] Since the motor copper loss and iron loss are related to the d-axis current i d , the q-axis current component i that actually generates torque in the q-axis current qt The expression of the q-axis current component i that actually generates torque in the q-axis current of SPMSM under given speed and torque conditions is: qt is a constant value. At this time, the expression II of the motor iron loss of the SPMSM is expressed as:

[0078] P Fe =A(a1i d 2 +b1i d +c1) (9)

[0079] Where:

[0080]

[0081] Among them, A is the overall coefficient of motor iron loss, a1 is the square term coefficient of d-axis current, b1 is the first term coefficient of d-axis current, and c1 is the q-axis current component i that generates torque. qt Fixed value item.

[0082] Similarly, the motor copper loss expression II of SPMSM is expressed as:

[0083] P Cu =D(a1i d 2 +b1i d +c1) (11)

[0084] Where:

[0085]

[0086] In the simulation, the curves of the motor copper loss, motor iron loss, mechanical loss and motor efficiency of the SPMSM with the change of d-axis current are plotted respectively, as shown in Figure 2. Figure 3 As shown in the figure, the motor copper loss and iron loss are expressed as a quadratic function of the d-axis current, in the form of a parabola with an upward opening. Combining equations (9) and (11), the expression of the d-axis current reference value under the loss minimum constraint is obtained:

[0087]

[0088] S2. Establish a lumped parameter SPMSM parameter identification model. Based on the identification of lumped parameters, online identification of stator resistance, inductance, permanent magnet flux linkage, and iron loss resistance is achieved.

[0089] The voltage equation II of the SPMSM considering the iron loss resistance in steady state is expressed as:

[0090]

[0091] Furthermore, substituting equation (4) into equation (14), we obtain the SPMSM voltage equation III:

[0092]

[0093] In the SPMSM voltage equation III, the stator resistance, inductance, permanent magnet flux linkage, and iron loss resistance are integrated into four coefficients. Therefore, the four coefficients in the SPMSM voltage equation III are defined as lumped parameters, which are:

[0094]

[0095] According to Equations (15) and (16), in order to realize the motor parameter identification of SPMSM, it is necessary to establish the relationship expression between the lumped parameters and the motor parameters.

[0096] By observing formula (16), the stator resistance R s Expressed as lumped parameters a, b, c, d and electrical angular velocity ω e Function:

[0097]

[0098] The permanent magnet flux λ f Expressed as lumped parameters c, d and electrical angular velocity ω e Function:

[0099]

[0100] The inductor L s Expressed as lumped parameters b, c, d and electrical angular velocity ω e Function:

[0101]

[0102] The iron loss resistor R Fe Expressed as lumped parameters b, c, d and electrical angular velocity ω e Function:

[0103]

[0104] Equations (17) to (20) show the relationship between the four parameters to be identified and the four lumped parameters of the SPMSM.

[0105] In order to verify the accuracy of the SPMSM parameter identification model based on lumped parameters proposed in this invention and the feasibility of simultaneous online identification of stator resistance, inductance, permanent magnet flux linkage and iron loss resistance, in this embodiment, by setting two different sets of d-axis currents at a smaller time scale, four sets of voltage and current information are obtained to construct a full-rank parameter identification matrix. The implementation process is as follows: Figure 4 shown.

[0106] The constructed identification matrix is ​​expressed as:

[0107]

[0108] Where u d1 、u q1 、i d1 、i q1 are the d-axis and q-axis voltages and currents in the first stage; u d2 、u q2 、i d2 、i q2 are the d-axis and q-axis voltages and currents in the second stage.

[0109] At the same time, the present invention uses the least square method with forgetting factor (Recursive Least Square, RLS) to realize the identification of lumped parameters. The least square method with forgetting factor is used to realize the identification of lumped parameters. First, the initialization is performed and the initial value of the parameter is set to Set to zero and set the initial value of the covariance matrix to P(0) = δ -1 I (δ is a small positive number), followed by a recursive update process, measuring the input and output to obtain the measured values ​​of the stator voltage and current, thereby constructing the identification parameter matrix Φ(k). The current input matrix is ​​calculated according to Equation (23), and the four output equations are combined. The parameters are updated synchronously through matrix operations to avoid the error accumulation of single-output step-by-step processing. The gain matrix K(k) can be updated using the matrix inversion lemma. The updated parameters θ(k) are updated by correcting the estimated values ​​to reduce the residual. The updated covariance matrix P(k) is used to reduce the influence of old data on subsequent estimates. Regarding the forgetting factor α, when α = 1, there is no forgetting, which is suitable for static parameters. When α < 1, exponentially weighted forgetting is used to enhance the ability to track time-varying parameters.

[0110] The iterative formula based on RLS is:

[0111]

[0112] Where,

[0113]

[0114] Where θ(k) is the parameter matrix, is the coefficient matrix, K(k) is the gain matrix; α is the forgetting factor, P(k) is a 4th-order matrix, and I is a 4th-order identity matrix.

[0115] Substituting the identified lumped parameters into Equations (17) to (20), the online identification of all parameters of the SPMSM can be realized, as follows: Figure 5 In addition, the d-axis and q-axis voltages used need to take into account the effects of digital control delay and inverter nonlinear voltage error.

[0116] Figure 5 This is a flowchart for the parameter identification process of a surface-mounted permanent magnet synchronous motor. The control block diagram adopts a dual closed-loop control structure, and the overall system architecture is: outer speed loop (PI controller) → inner current loop (PI controller) → SVPWM inverter → SPMSM motor. The system's d-axis reference current is set to the optimal value obtained by equation (13). The three-phase current and three-phase voltage obtained by the sensor are passed through a low-pass filter to remove high-frequency interference. The current and voltage values ​​in the three-phase stationary coordinate system are converted to the dq-axis coordinate system through coordinate transformation. The processed data are substituted into equation (21), and the motor parameters to be identified are calculated using equations (17)-(20).

[0117] S3. Based on the online identification of stator resistance, inductance, permanent magnet flux linkage, and iron loss resistance, the current reference value under SPMSM loss minimum control is accurately set through the expression of the d-axis current reference value under loss minimum control.

[0118] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for online identification of all parameters and efficiency optimization control of a surface-mounted permanent magnet synchronous motor considering the influence of iron loss, characterized in that: The following steps are involved: S1. Based on the mathematical model of the SPMSM considering the motor iron loss, obtain the expression of the d-axis current reference value for loss minimum control; S2. Establish a lumped parameter SPMSM parameter identification model. Based on the identification of lumped parameters, online identification of stator resistance, inductance, permanent magnet flux linkage, and iron loss resistance is achieved. S3. Based on the online identification of stator resistance, inductance, permanent magnet flux linkage, and iron loss resistance, the current reference value under SPMSM loss minimum control is set through the expression of the d-axis current reference value under loss minimum control.

2. The method for online identification of all parameters and efficiency optimization control of a surface-mounted permanent magnet synchronous motor considering the influence of iron loss according to claim 1 is characterized in that: The method for obtaining the expression of the d-axis current reference value for loss minimum control based on the mathematical model of the SPMSM considering the motor iron loss is: ① Based on the mathematical model of the SPMSM including the motor iron loss, the voltage equation I, torque equation, and expressions based on the stator d-axis and q-axis currents of the SPMSM are obtained; ② Based on the expressions of the stator d and q axis currents, the relationship between the d and q axis current components that actually generate torque and the stator d and q axis currents is obtained, as well as the relationship between the iron loss current component in the d and q axis currents and the stator d and q axis currents; and the d axis current i is determined. d and q-axis current i q The mathematical relationships that exist; Based on steps ① and ②, the loss minimization control of the SPMSM is equivalent to minimizing the sum of the copper loss and iron loss of the SPMSM motor by distributing the d-axis and q-axis currents, and the expression I of the copper loss and iron loss of the SPMSM motor is obtained; According to the expression I of the copper loss and iron loss of the SPMSM motor and the extreme value solution equation and constraint conditions of the loss minimum control, the expression II of the iron loss of the SPMSM motor and the expression II of the copper loss of the SPMSM motor are obtained; According to the expression II of the motor iron loss of SPMSM and the expression II of the motor copper loss of SPMSM, the expression of the d-axis current reference value under the loss minimum constraint is obtained.

3. The method for online identification of all parameters and efficiency optimization control of a surface-mounted permanent magnet synchronous motor considering the influence of iron loss according to claim 2 is characterized in that: The expression of the d-axis current reference value under the minimum loss constraint is: Among them, i d is the d-axis current, R s and R Fe are stator resistance and iron loss resistance respectively, L s ,λ f and ω e are inductance, permanent magnet flux amplitude and electric angular velocity respectively; T e is the motor torque, n p is the number of pole pairs of the surface-mounted permanent magnet synchronous motor.

4. The method for online identification of all parameters and efficiency optimization control of a surface-mounted permanent magnet synchronous motor considering the influence of iron loss according to claim 2 is characterized in that: The method for establishing the SPMSM parameter identification model of lumped parameters and realizing online identification of stator resistance, inductance, permanent magnet flux linkage and iron loss resistance based on the identification of lumped parameters is as follows: Obtain the SPMSM voltage equation II considering the iron loss resistance in steady state. Substitute the expression representing the relationship between the d-axis and q-axis current components that actually generate torque in the d-axis and q-axis currents and the stator d-axis and q-axis currents into the SPMSM voltage equation II to obtain the SPMSM voltage equation III. The coefficients in the SPMSM voltage equation III are defined as lumped parameters a, b, c, and d respectively; Establish the relationship between the lumped parameters and the motor parameters: Substitute the stator resistance R s Expressed as lumped parameters a, b, c, d and electrical angular velocity ω e function; the permanent magnet flux λ f Expressed as lumped parameters c, d and electrical angular velocity ω e function; the inductor L s Expressed as lumped parameters b, c, d and electrical angular velocity ω e function; the iron loss resistor R Fe Expressed as lumped parameters b, c, d and electrical angular velocity ω e function; Under a preset time scale, by setting two different sets of d-axis currents, four sets of voltage and current information are obtained to construct a full-rank parameter identification matrix; Based on the parameter identification matrix, the least square method with forgetting factor is used to identify the lumped parameters. The identified lumped parameters are substituted into the relationship expression between the lumped parameters and the motor parameters to realize the online identification of all parameters of the SPMSM.

5. The method for online identification of all parameters and efficiency optimization control of a surface-mounted permanent magnet synchronous motor considering the influence of iron loss according to claim 4 is characterized in that: The SPMSM voltage equation III is: Among them, u d and u q are d-axis and q-axis voltages, respectively, R s and R Fe are stator resistance and iron loss resistance respectively; i d and i q are d-axis and q-axis currents respectively; The lumped parameters a, b, c, and d are:

6. The method for online identification of all parameters and efficiency optimization control of a surface-mounted permanent magnet synchronous motor considering the influence of iron loss according to claim 4 is characterized in that: The stator resistance R s Expressed as:

7. The method for online identification of all parameters and efficiency optimization control of a surface-mounted permanent magnet synchronous motor considering the influence of iron loss according to claim 4 is characterized in that: The permanent magnet flux λ f Expressed as:

8. The method for online identification of all parameters and efficiency optimization control of a surface-mounted permanent magnet synchronous motor considering the influence of iron loss according to claim 4 is characterized in that: The inductor L s Expressed as:

9. The method for online identification of all parameters and efficiency optimization control of a surface-mounted permanent magnet synchronous motor considering the influence of iron loss according to claim 4 is characterized in that: The iron loss resistor R Fe Expressed as:

10. The method for online identification of all parameters and efficiency optimization control of a surface-mounted permanent magnet synchronous motor considering the influence of iron loss according to claim 4, characterized in that: The parameter identification matrix is ​​expressed as: Among them, u d1 、u q1 、i d1 、i q1 are the d-axis and q-axis voltages and currents in the first stage; u d2 、u q2 、i d2 、i q2 are the d-axis and q-axis voltages and currents in the second stage; The least squares method with forgetting factor is used to identify the lumped parameters. The iterative formula is: Where, Among them, θ(k) is the parameter matrix, is the coefficient matrix, K(k) is the gain matrix; α is the forgetting factor, P(k) is a 4th-order matrix, and I is a 4th-order identity matrix.

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