Permanent magnet synchronous motor MTPA variable step size current angle searching method based on stator current error

Abstract

The invention provides a permanent magnet synchronous motor MTPA variable step size current angle searching method based on a stator current error, and belongs to the field of permanent magnet synchronous motor control. The problems that a traditional variable step size search method is prone to being affected by current noise, and the stability of a system can be affected by differential operation are solved. The method comprises the steps of 1, establishing a function relationship between stator current and a current angle, and designing a gradient descent method according to the function relationship between the stator current and the current angle; and step 2, simplifying a gradient descent method according to a stator current error, and realizing variable-step current angle search. The motor is mainly used for improving the efficiency and the response speed of the motor.

Description

Technical Field

[0001] The present invention belongs to the field of permanent magnet synchronous motor control, and in particular relates to a permanent magnet synchronous motor MTPA variable step current angle search method based on stator current error. Background Art

[0002] Maximum torque per amp (MTPA) control of a permanent magnet synchronous motor (PMSM) is one of the core technologies for improving motor energy efficiency. Its core objective is to find the current vector angle that maximizes the ratio of electromagnetic torque to stator current amplitude. Traditional MTPA control methods rely primarily on precise motor parameter models or offline table lookup methods. However, in practical applications, these methods suffer from parameter mismatch and high storage resource usage. Consequently, search methods have become a research hotspot. Search methods are a common method for obtaining the current angle under maximum torque per amp (MTPA) conditions. Their basic concept is to adjust the current vector angle in real time through stator current feedback to find the optimal operating point. These methods do not rely on precise motor modeling or preset parameters, can mitigate the impact of parameter changes, and do not require complex motor modeling or pre-storage of large amounts of table lookup data, placing low hardware requirements.

[0003] Traditional search methods can be divided into fixed-step search and variable-step search methods based on the search step size. Fixed-step search methods use a fixed search step size, and the γ angle will eventually oscillate near the optimal point. Its characteristics are: if the search step size is set too large, the search speed increases, but the steady-state oscillation increases; if the step size is set too small, the opposite is true. The gradient descent variable-step search method, on the other hand, uses a variable step size strategy, assigning a larger step size at the beginning of the search to quickly approach the optimal point. When γ exceeds the optimal point and reverses, the step size is proportionally attenuated, allowing for a refined search near the optimal point. Compared to fixed-step search, variable-step search can approach the target faster. However, if the initial step size is set too large, multiple reverse steps are required to attenuate the step size, while if it is too small, the target is approached more slowly. Furthermore, due to the gradual decay of the step size, the variable-step search method slows down when it re-enters the search. Summary of the Invention

[0004] In view of this, the present invention aims to propose a variable-step current angle search method for a permanent magnet synchronous motor (MTPA) based on stator current error, so as to solve the problem that the traditional variable-step search method is easily affected by current noise and the existence of differential operation will affect the stability of the system.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] A variable-step current angle search method for a permanent magnet synchronous motor (MTPA) based on stator current error, the method comprising:

[0007] Step 1: Establish the functional relationship between stator current and current angle, and design a gradient descent method based on the functional relationship between stator current and current angle;

[0008] Step 2: Simplify the gradient descent method based on the stator current error to achieve variable step-size current angle search.

[0009] Furthermore, a preferred embodiment is proposed, wherein step 1 comprises:

[0010] According to the dq axis current equation and electromagnetic torque equation of the permanent magnet synchronous motor, the nonlinear relationship between the stator current and the current angle is established;

[0011] A gradient descent method is designed to make the current angle γ converge to the MTPA operating point along the negative gradient direction.

[0012] Furthermore, a preferred embodiment is proposed, in which the nonlinear relationship between the stator current and the current angle is:

[0013]

[0014] Among them, I s is the stator current, p n is the pole pair number, ψ f is the permanent magnet flux, L d is the d-axis inductance, L q They are q-axis inductance, T e is the electromagnetic torque, and γ is the current angle.

[0015] Furthermore, a preferred method is proposed, wherein the gradient descent method is:

[0016]

[0017] in, is the stator current gradient, γ k is the current angle of the kth iteration, and η is the learning rate.

[0018] Furthermore, a preferred embodiment is proposed, wherein step 2 comprises:

[0019] Select an initial current vector angle γ0 as the starting value of the search;

[0020] By applying the current angle perturbation Δγ k , obtain the stator current change;

[0021] According to the current change ΔI s Dynamically adjust the search step size δ k , the step size is related to |ΔI s | proportional to;

[0022] Set the search direction d k, construct the current angle iteration formula;

[0023] When the absolute value of the current error is less than the preset tolerance ε, the iteration is terminated and the optimal current angle γ is output. MTPA .

[0024] Furthermore, a preferred method is proposed, wherein the current variation ΔI s Dynamically adjust the search step size δ k ,include:

[0025] δ k =α|ΔI s (γ k )|

[0026] Among them, α is the step size coefficient.

[0027] Furthermore, a preferred method is proposed, wherein the search direction d k for:

[0028]

[0029] Furthermore, a preferred method is proposed, wherein the current angle iteration formula is:

[0030] γ k+1 =γ k -αΔI s (γ k ).

[0031] Based on the same inventive concept, the present invention also proposes a computer device, including a memory and a processor, wherein a computer program is stored in the memory. When the processor runs the computer program stored in the memory, the processor executes a permanent magnet synchronous motor MTPA variable step current angle search method based on stator current error as described in any one of the above items.

[0032] Based on the same inventive concept, the present invention also proposes a computer-readable storage medium, which stores a computer program. When the computer program is run by a processor, it executes the steps of a variable-step current angle search method for a permanent magnet synchronous motor MTPA based on stator current error as described above.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] Traditional variable-step current angle search methods are susceptible to interference from current noise, which affects the motor's control accuracy and performance. However, this invention, by simplifying the gradient calculation based on the stator current error, can effectively reduce the impact of current noise on the system, thereby improving system robustness.

[0035] In traditional variable-step search methods, differential operations are prone to introducing noise and instability, potentially causing the system's response to become unstable. By replacing differential calculations with stator current error feedback, this invention reduces system instability and enhances control system stability.

[0036] This invention uses a variable-step current angle search method to more accurately find the optimal current angle for achieving the best torque / power output (MTPA) while maintaining system stability. The proposed method dynamically adjusts the search step size based on the stator current error, enabling the system to adapt to different loads and operating conditions, improving its adaptability and flexibility.

[0037] The proposed method simplifies gradient calculations and differential operations and employs stator current error feedback for variable-step search. This not only effectively improves stability and accuracy, but also simplifies the calculation process, reducing the complex mathematical derivations and real-time computational burden. By optimizing the variable-step current angle search strategy, this method can find the optimal current angle in a shorter time, thereby improving the motor's efficiency and response speed, particularly under high-dynamic conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings, which constitute part of the present invention, are provided to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are provided to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings:

[0039] Figure 1 This is a flow chart of a variable-step current angle search method for a permanent magnet synchronous motor (MTPA) based on stator current error according to the present invention;

[0040] Figure 2 I of the present invention s -γ relationship diagram;

[0041] Figure 3 This is a flow chart of the search method of the present invention;

[0042] Figure 4 This is a graph showing the results of a current angle convergence speed comparison experiment according to the present invention. Figure 4 (a) is the current angle convergence speed at a fixed step size; Figure 4 (b) is the current angle convergence speed with variable step size; Figure 4 (c) is the current angle convergence speed of the variable step current angle search method described in the present invention. DETAILED DESCRIPTION

[0043] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely explain the technical solutions in the embodiments of the present invention. It should be noted that the embodiments of the present invention and the features therein can be combined with each other in the absence of conflict, and the embodiments described are only part of the embodiments of the present invention, not all of the embodiments.

[0044] Implementation method 1, see Figure 1 This embodiment describes a variable-step current angle search method for a permanent magnet synchronous motor (MTPA) based on stator current error, the method comprising:

[0045] Step 1: Establish the functional relationship between stator current and current angle, and design a gradient descent method based on the functional relationship between stator current and current angle;

[0046] Step 2: Simplify the gradient descent method based on the stator current error to achieve variable step-size current angle search.

[0047] Traditional variable-step current angle search methods are susceptible to interference from current noise, which can affect motor control accuracy and performance. However, this implementation simplifies gradient calculations through feedback control based on stator current errors, effectively reducing the impact of current noise on the system and improving system robustness.

[0048] In traditional variable-step search methods, differential operations are prone to introducing noise and instability, potentially causing unstable system responses. However, by replacing differential calculations with stator current error feedback, this implementation reduces system instability and enhances control system stability.

[0049] This implementation utilizes a variable-step current angle search method to more accurately find the optimal current angle for optimal torque / power output (MTPA) while maintaining system stability. This method dynamically adjusts the search step size based on the stator current error, enabling the system to adapt to different loads and operating conditions, improving its adaptability and flexibility.

[0050] The method proposed in this embodiment simplifies gradient calculations and differential operations and uses stator current error feedback for variable-step search. This not only effectively improves stability and accuracy, but also simplifies the calculation process, reducing the complex mathematical derivations and real-time computational burden. By optimizing the variable-step current angle search strategy, this method can find the optimal current angle in a shorter time, thereby improving the motor's efficiency and response speed, especially under high dynamic conditions.

[0051] Embodiment 2: This embodiment further limits the variable-step current angle search method for a permanent magnet synchronous motor (MTPA) based on stator current error described in Embodiment 1. Step 1 includes:

[0052] According to the dq axis current equation and electromagnetic torque equation of the permanent magnet synchronous motor, the nonlinear relationship between the stator current and the current angle is established;

[0053] A gradient descent method is designed to make the current angle γ converge to the MTPA operating point along the negative gradient direction.

[0054] A nonlinear relationship between the stator current and the current angle is established based on the dq-axis current equations and electromagnetic torque equations of the permanent magnet synchronous motor. Compared with the linear approximation relationship, this nonlinear modeling is more in line with the actual working state of the motor, improving the calculation accuracy and search accuracy.

[0055] In this embodiment, a gradient descent method is designed to converge the current angle along the negative gradient to the MTPA operating point. This method uses gradient information for optimization to quickly and efficiently find the current angle that enables the motor to achieve maximum torque per ampere (MTPA).

[0056] By performing gradient descent optimization on the current angle, this implementation ensures that the current angle accurately converges to the MTPA operating point. The MTPA point is a key point in motor performance optimization, enabling maximum torque output and reducing current consumption during operation, thereby improving motor efficiency and performance. Accurately locating the MTPA operating point helps improve motor performance under varying load conditions and ensures efficient operation.

[0057] Implementation method 3: This implementation method further limits the variable-step current angle search method for a permanent magnet synchronous motor MTPA based on stator current error described in implementation method 2. The nonlinear relationship between the stator current and the current angle is:

[0058]

[0059] Among them, I s is the stator current, p n is the pole pair number, ψ f is the permanent magnet flux, L d is the d-axis inductance, L q They are q-axis inductance, T e is the electromagnetic torque, and γ is the current angle.

[0060] Implementation 4: This implementation further limits the variable-step current angle search method for a permanent magnet synchronous motor MTPA based on stator current error described in Implementation 3. The gradient descent method is:

[0061]

[0062] in, is the stator current gradient, γk is the current angle of the kth iteration, and η is the learning rate.

[0063] By designing a gradient descent method and a variable step size strategy, the search step size can be dynamically adjusted, making each iteration more efficient. Adaptive step size adjustment gradually reduces the step size as the optimal solution is approached, avoiding oscillations or convergence instability caused by over-adjustment. This approach improves computational efficiency while ensuring solution accuracy and reduces the computational burden of excessive iterations.

[0064] Dynamically adjusting the search step size based on the stator current error rather than the stator current differential simplifies the traditional gradient descent search process by reducing the computational effort. Furthermore, the gradient descent design effectively avoids the local optimal solution issues that can occur with traditional fixed-step search methods. Especially during motor operation, where parameters can change at any time, the gradient descent method can address system uncertainties through real-time adjustments, maintaining system stability and robustness.

[0065] Embodiment 5: This embodiment further limits the variable-step current angle search method for a permanent magnet synchronous motor (MTPA) based on stator current error described in Embodiment 1. Step 2 includes:

[0066] Select an initial current vector angle γ0 as the starting value of the search;

[0067] By applying the current angle perturbation Δγ k , obtain the stator current change;

[0068] According to the current change ΔI s Dynamically adjust the search step size δ k , the step size is related to |ΔI s | proportional to;

[0069] Set the search direction d k , construct the current angle iteration formula;

[0070] When the absolute value of the current error is less than the preset tolerance ε, the iteration is terminated and the optimal current angle γ is output. MTPA .

[0071] Traditional MTPA algorithms typically rely on gradient calculations to determine the optimal current angle, a complex process that is sensitive to system noise. However, using stator current error feedback to adjust the search step size through simple current change feedback can reduce the amount of computation while improving search efficiency.

[0072] The step size is proportional to the current change and can be adjusted dynamically based on the current error. This means that when the error is large, a larger step size helps to quickly approach the optimal solution; when the error is small, a smaller step size allows for a more refined search, thereby improving the algorithm's convergence speed and accuracy.

[0073] While traditional methods require precise motor models and gradient information, this method relies on feedback signals from stator current errors and does not require complex mathematical models or parameter estimation. Therefore, this method is more flexible and adaptable.

[0074] By setting an error threshold (ε) as the iteration termination condition, the search is terminated when the absolute value of the current error is less than the preset tolerance, effectively avoiding over-calculation and improving the stability of the algorithm. In addition, the strategy of dynamically adjusting the step size and adaptive search direction helps to improve the accuracy of the current angle solution, thereby optimizing motor performance.

[0075] Implementation 6: This implementation is a further limitation of the MTPA variable step current angle search method based on stator current error described in Implementation 5. s Dynamically adjust the search step size δ k ,include:

[0076] δ k =α|ΔI s (γ k )|

[0077] Among them, α is the step size coefficient.

[0078] Implementation 7: This implementation is a further limitation of the MTPA variable step current angle search method based on stator current error described in Implementation 5. The search direction d k for:

[0079]

[0080] Embodiment 8: This embodiment further limits the variable-step current angle search method for a permanent magnet synchronous motor (MTPA) based on stator current error described in embodiment 5. The current angle iteration formula is:

[0081] γ k+1 =γ k -αΔI s (γ k ).

[0082] Implementation method 9. A computer device described in this implementation method includes a memory and a processor, wherein a computer program is stored in the memory. When the processor runs the computer program stored in the memory, the processor executes a permanent magnet synchronous motor MTPA variable step current angle search method based on stator current error described in any one of implementation methods 1 to 8.

[0083] Implementation method ten. A computer-readable storage medium described in this implementation method stores a computer program, and when the computer program is executed by a processor, the steps of a variable-step current angle search method for a permanent magnet synchronous motor MTPA based on stator current error are executed as described in any one of implementation methods one to eight.

[0084] Implementation method 11, see Figure 2 、 Figure 3 and Figure 4 This embodiment is a specific example of the variable step current angle search method for a permanent magnet synchronous motor (MTPA) based on stator current error described in the first embodiment, and is also used to explain the second to eighth embodiments. Specifically:

[0085] Step 1: Pass the stator current I s The gradient descent method is designed based on the relationship between the current angle γ.

[0086] Permanent magnet synchronous motor dq axis current and stator current I s The relationship is

[0087]

[0088] Where: γ is the current angle; i d 、i q are the d-axis and q-axis stator currents respectively.

[0089] The electromagnetic torque equation of permanent magnet synchronous motor is:

[0090]

[0091] Where: T e is the electromagnetic torque; L d , L q are the d-axis and q-axis inductances respectively; ψ f is the permanent magnet flux; p n is the pole pair number.

[0092] Combining equations (1) and (2), we can get the stator current I s Relationship with current angle γ:

[0093]

[0094] Figure 2 I is the constant torque s -γ relationship diagram. It can be seen that for function I s (γ) has only one minimum point, which is the MTPA operating point of the motor. The gradient of this point is ▽I s (γ)=0. According to Figure 2 It can be found that when the motor runs on the left side of the optimal current vector angle (γ<γ MTPA ), stator current gradient ▽I s (γ)<0; when the motor runs on the right side of the optimal current vector angle (γ>γ MTPA ), stator current gradient ▽I s (γ)>0. Based on this characteristic, as long as we search along the direction of the negative gradient, we can converge to the minimum point, which is the gradient descent method. Its formula is:

[0095]

[0096] Where: γ k is the current angle of the kth iteration, and η is the learning rate.

[0097] When the torque is constant, the current vector angle at the minimum stator current is what we are looking for. In this case, we have:

[0098]

[0099] Where: I s,MTPA is the stator current during MTPA operation.

[0100] According to I s The property of (γ) (convex function), if a negative proportional coefficient K is introduced, the derivative of γ with respect to time satisfies:

[0101]

[0102] According to Lyapunov's stability theorem, it can be proved that the above formula will make γ approach its minimum value, that is, γ MTPA .

[0103] Step 2: Simplify the gradient descent method based on the stator current error through equivalence proof.

[0104] Gradient descent requires complex gradient calculations, and numerical differentiation in gradient calculations is unstable and sensitive to noise. Actual currents contain noise, so directly calculating the gradient can easily lead to directional misjudgments. Furthermore, gradient descent requires manual setting of the learning rate, making its implementation complex. Therefore, this embodiment optimizes the gradient descent method as follows.

[0105] By using the current error as feedback to directly affect the next stator current angle search, the same control purpose as the gradient descent method is achieved. s <0, maintain the direction of current angle search, ΔI s >0, the direction of the current angle search is reversed. In this way, the algorithm can converge γ to the minimum point without gradient calculation, which reduces the computational complexity. In addition, the proposed method is insensitive to current noise and is less likely to misjudge the search direction. Another advantage of the proposed method is that the search step size is proportional to ΔI s Proportional to I s Approaching I s,MTPA , ΔI s This gradually decreases, which naturally reduces the current angle search step size, which is what the search method expects. Furthermore, because current fluctuations significantly interfere with the values ​​sampled at intervals, a periodic average approach is used here, where the step size adjustment is based on the cumulative change rather than the instantaneous gradient, reducing the interference of current fluctuations.

[0106] The equivalence of the proposed search method and the gradient descent method is explained below.

[0107] The step size update rule of the proposed method is:

[0108] γ k+1 =γ k +Δγ k (7)

[0109] Where: △γ k =d k δ k , d k is the search direction, which can be 1 or -1; δ k =α|△I s | is the k-th dynamic step size, and α is the step size coefficient.

[0110] Current change ΔI s It can be approximated as:

[0111]

[0112] And for the dynamic step size:

[0113]

[0114] Since the step size changes smoothly and has little impact, considering the computational complexity, approximate calculation is used in actual engineering, and the impact of the historical step size can be ignored. The approximate value is:

[0115]

[0116] Where: λ is the approximate step gain coefficient.

[0117] Through the above analysis, the search direction d k satisfy:

[0118]

[0119] Therefore, the update rule for the step size can be written as:

[0120]

[0121] The above formula is equivalent to:

[0122]

[0123] At this time, the update formula of the current angle is consistent with the update formula (4) of the gradient descent method. It can be seen that this improvement is equivalent to the gradient descent method, but the proposed method does not require the calculation of differentials, which simplifies the implementation process of the gradient descent method.

[0124] The proposed search method is described in detail below through a flow chart.

[0125] Figure 3 The flowchart of the proposed search method is shown in Figure 1. First, an initial current vector angle γ0 is selected as the starting value of the search, and k is set to 0. Then, a current angle disturbance △γ is applied, and the first-order difference of the stator current △I is calculated after the current vector angle is updated. s (γ k ); Set the error tolerance ε. If the absolute value of the current difference is less than ε, stop searching and output the current vector angle △γ at this time. k+1 Otherwise, according to the current angle iteration formula △γ k+1 =-α△I s (γ k ) continues to perturb the current angle and performs the next cycle until it converges to the MTPA operating point.

[0126] The above scheme can realize the current vector angle search during the MTPA operation of the permanent magnet synchronous motor.

[0127] The present invention is used to conduct experimental verification on an actual three-phase permanent magnet synchronous motor towing test platform, where the motor has a rated power of 2.2kW and a DC bus voltage of 540V. Figure 4The experimental results of the MTPA current angle obtained using different search methods at 400 rpm for the motor are shown. The initial search angle is 108°. It can be seen that the fixed-step and variable-step methods require four search steps to reach the steady-state value, while the proposed method only requires three. The fixed-step method exhibits oscillations in the steady-state current angle, while the variable-step method and the proposed method eliminate these oscillations. Compared with the variable-step method, the proposed method reduces the convergence time from 1.03s to 0.62s, a 39.8% reduction in convergence time, validating the effectiveness of the proposed method.

[0128] Those skilled in the art will appreciate that embodiments of the present disclosure may be provided as methods, systems, or computer program products. Thus, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present disclosure may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0129] The present disclosure is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present disclosure. It should be understood that each process and / or block in the flowchart and / or block diagram and the combination of processes and / or blocks in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including the instruction device, which implements the function specified in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0130] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0131] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present disclosure and are not intended to limit its scope of protection. Although the present disclosure has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that after reading the present disclosure, those skilled in the art can still make various changes, modifications or equivalent substitutions to the specific implementation methods of the invention, but these changes, modifications or equivalent substitutions are all within the scope of protection of the disclosed claims.

Claims

1. A variable step current angle search method for a permanent magnet synchronous motor (MTPA) based on stator current error, characterized in that: The method comprises: Step 1: Establish the functional relationship between stator current and current angle, and design a gradient descent method based on the functional relationship between stator current and current angle; Step 2: Simplify the gradient descent method based on the stator current error to achieve variable step-size current angle search.

2. The method for searching the current angle of a permanent magnet synchronous motor (MTPA) with a variable step size based on the stator current error according to claim 1 is characterized in that: The step 1 comprises: According to the dq axis current equation and electromagnetic torque equation of the permanent magnet synchronous motor, the nonlinear relationship between the stator current and the current angle is established; A gradient descent method is designed to make the current angle γ converge to the MTPA operating point along the negative gradient direction.

3. The method for searching the current angle of a permanent magnet synchronous motor (MTPA) with a variable step size based on the stator current error according to claim 2 is characterized in that: The nonlinear relationship between the stator current and the current angle is: Among them, I s is the stator current, p n is the pole pair number, ψ f is the permanent magnet flux, L d is the d-axis inductance, L q They are q-axis inductance, T e is the electromagnetic torque, and γ is the current angle.

4. The method for searching the current angle of a permanent magnet synchronous motor (MTPA) with a variable step size based on the stator current error according to claim 3 is characterized in that: The gradient descent method is: in, is the stator current gradient, γ k is the current angle of the kth iteration, and η is the learning rate.

5. The method for searching the current angle of a permanent magnet synchronous motor (MTPA) with a variable step size based on the stator current error according to claim 1 is characterized in that: The step 2 includes: Select an initial current vector angle γ0 as the starting value of the search; By applying the current angle perturbation Δγ k , obtain the stator current change; According to the current change ΔI s Dynamically adjust the search step size δ k , the step size is related to |ΔI s | proportional to; Set the search direction d k , construct the current angle iteration formula; When the absolute value of the current error is less than the preset tolerance ε, the iteration is terminated and the optimal current angle γ is output. MTPA .

6. The method for searching the current angle of a permanent magnet synchronous motor (MTPA) with a variable step size based on stator current error according to claim 5 is characterized in that: The current variation ΔI s Dynamically adjust the search step size δ k ,include: d k =α|ΔI s (c k )| Among them, α is the step size coefficient.

7. The method for searching the current angle of a permanent magnet synchronous motor (MTPA) with a variable step size based on the stator current error according to claim 5 is characterized in that: The search direction d k for:

8. The method for searching the current angle of a permanent magnet synchronous motor (MTPA) with a variable step size based on stator current error according to claim 5 is characterized in that: The current angle iteration formula is: c k+1 =c k -aΔI s (c k )。 9. A computer device, characterized in that: The invention comprises a memory and a processor, wherein a computer program is stored in the memory. When the processor runs the computer program stored in the memory, the processor executes a permanent magnet synchronous motor MTPA variable step current angle search method based on stator current error according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, executes the steps of a variable-step current angle search method for a permanent magnet synchronous motor (MTPA) based on stator current error according to any one of claims 1 to 8.

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