A permanent magnet synchronous motor MTPA variable step current angle search method based on stator current error

Abstract

This invention proposes a variable-step current angle search method for permanent magnet synchronous motors (MTPA) based on stator current error, belonging to the field of permanent magnet synchronous motor control. It solves the problems of traditional variable-step search methods being susceptible to current noise and the impact of differential operations on system stability. The method includes: Step 1: Establishing the functional relationship between stator current and current angle, and designing a gradient descent method based on this relationship; Step 2: Simplifying the gradient descent method based on the stator current error to achieve variable-step current angle search. It mainly improves the efficiency and response speed of the motor.

Description

Technical Field

[0001] This invention belongs to the field of permanent magnet synchronous motor control, and in particular relates to a variable step size current angle search method for permanent magnet synchronous motors based on stator current error (MTPA). Background Technology

[0002] Maximum torque-to-current ratio (MTPA) control of permanent magnet synchronous motors (PMSMs) is one of the core technologies for improving motor energy efficiency. Its core lies in finding the current vector angle that maximizes the ratio of electromagnetic torque to stator current amplitude. Traditional MTPA control methods mainly rely on precise motor parameter models or offline lookup tables, but these suffer from parameter mismatch and high storage resource consumption in practical applications. Therefore, search methods have gradually become a research hotspot. The search method is a common approach to obtaining the current angle under maximum torque-to-current ratio (MTPA) conditions. Its basic idea is to adjust the current vector angle in real time through stator current feedback to find the optimal operating point. It does not rely on precise motor modeling and preset parameters, can avoid the influence of parameter changes, and does not require complex motor modeling or pre-storing large amounts of lookup data, thus having low hardware requirements.

[0003] Traditional search methods can be categorized into fixed-step search methods and variable-step search methods based on their search step size. Fixed-step search methods have a fixed search step size, and the γ angle eventually oscillates around the optimum. A key characteristic is that if the search step size is too large, the search speed increases, but steady-state oscillations also increase; conversely, if the step size is too small, the opposite occurs. Gradient descent's variable-step search method employs a variable-step strategy. It initially assigns a larger step size to quickly approach the optimum, and then gradually decreases the step size when γ exceeds the optimum and reverses direction, allowing for a more refined search around the optimum. Variable-step search approaches the target faster than fixed-step search; however, if the initial step size is too large, multiple reverses are needed to decrease the step size, while a small step size results in a slower approach. Furthermore, due to the gradually decreasing step size, variable-step search methods are slower when re-entering the search. Summary of the Invention

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

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

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

[0007] Step 1: Establish the functional relationship between stator current and current angle, and design the 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 includes:

[0010] Based on the dq axis current equation and electromagnetic torque equation of the permanent magnet synchronous motor, a nonlinear relationship between stator current and current angle is established.

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

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

[0013]

[0014] Among them, I s For stator current, p n Let ψ be the extreme logarithm. f For permanent magnet flux linkage, L d For the d-axis inductance, L q These are the q-axis inductances, T e γ is the electromagnetic torque, and γ is the current angle.

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

[0016]

[0017] in, For the stator current gradient, γ k Let η be the current angle in the k-th iteration, and η be the learning rate.

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

[0019] Choose an initial current vector angle γ0 as the starting value for the search;

[0020] By applying a current angle perturbation Δγ k To obtain the change in stator current;

[0021] Based on the change in current ΔI s Dynamically adjust the search step size δ k The step size is related to |ΔI s |Proportional;

[0022] Set search direction d kConstruct an iterative formula for the current angle;

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

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

[0025] δ k =α|ΔI s (γ k )|

[0026] Where 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 iterative formula for the current angle 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 the memory stores a computer program, and when the processor runs the computer program stored in the memory, the processor executes a variable step size current angle search method for permanent magnet synchronous motors (MTPA) based on stator current error as described in any of the preceding claims.

[0032] Based on the same inventive concept, the present invention also proposes a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of a variable step size current angle search method for permanent magnet synchronous motors (MTPA) based on stator current error as described in any of the above-mentioned methods.

[0033] Compared with the prior art, the beneficial effects of the present invention are:

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

[0035] In traditional variable step-size search methods, differential operations are prone to introducing noise and instability, which may lead to unstable system responses. However, by using stator current error feedback to replace differential calculations, this invention reduces system instability and enhances the stability of the control system.

[0036] This invention employs a variable-step current angle search method, which, while maintaining system stability, can more accurately find the optimal current angle to achieve the best torque-to-power output (MTPA). The method proposed in this invention can dynamically adjust the search step size based on the stator current error, thereby enabling the system to adapt to different loads and operating conditions, improving the system's adaptability and flexibility.

[0037] The method proposed in this invention simplifies gradient calculation and differential operations, and employs stator current error feedback for variable step-size search. This not only effectively improves stability and accuracy but also simplifies the calculation process, reducing complex mathematical derivations and the burden of real-time computation. By optimizing the variable step-size current angle search strategy, this method can find the optimal current angle in a shorter time, thereby improving the efficiency and response speed of the motor, especially under high dynamic conditions. Attached Figure Description

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

[0039] Figure 1 This is a flowchart of the MTPA variable step size current angle search method for permanent magnet synchronous motors based on stator current error, as described in this invention.

[0040] Figure 2 The I described in this invention s -γ relationship diagram;

[0041] Figure 3 This is a flowchart of the search method described in this invention;

[0042] Figure 4 This is a graph showing the experimental results comparing the current angle convergence rate described in this invention. Figure 4 (a) represents the fixed-step current angle convergence rate; Figure 4 (b) represents the convergence rate of the variable step size current angle; Figure 4 (c) represents the current angle convergence rate of the variable step size current angle search method described in this invention. Detailed Implementation

[0043] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of the present invention can be combined with each other, and the described embodiments are only some embodiments of the present invention, not all embodiments.

[0044] Implementation Method 1, see Figure 1 This embodiment describes a variable step size current angle search method for a permanent magnet synchronous motor (MTPA) based on stator current error. The method includes:

[0045] Step 1: Establish the functional relationship between stator current and current angle, and design the 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 size current angle search methods are easily affected by current noise, which can impact the control accuracy and performance of the motor. This implementation simplifies gradient calculation through feedback control based on stator current error, effectively reducing the impact of current noise on the system and thus improving its robustness.

[0048] In traditional variable step-size search methods, differential operations are prone to introducing noise and instability, which may lead to unstable system responses. However, by using stator current error feedback to replace differential calculations, this implementation reduces system instability and enhances the stability of the control system.

[0049] This embodiment employs a variable step-size current angle search method, which, while maintaining system stability, can more accurately find the optimal current angle to achieve the best torque / power output (MTPA). The method proposed in this embodiment can dynamically adjust the search step size based on the stator current error, thereby enabling the system to adapt to different loads and operating conditions, improving the system's adaptability and flexibility.

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

[0051] Implementation Method Two: This implementation method further defines the variable step size current angle search method for permanent magnet synchronous motors (MTPA) based on stator current error described in Implementation Method One. Step 1 includes:

[0052] Based on the dq axis current equation and electromagnetic torque equation of the permanent magnet synchronous motor, a nonlinear relationship between stator current and current angle is established.

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

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

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

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

[0057] Implementation Method 3: This implementation method further defines the variable step size current angle search method for permanent magnet synchronous motors (MTPA) based on stator current error described in Implementation Method 2. The nonlinear relationship between the stator current and the current angle is as follows:

[0058]

[0059] Among them, I s For stator current, p n Let ψ be the extreme logarithm. f For permanent magnet flux linkage, L d For the d-axis inductance, L q These are the q-axis inductances, T e γ is the electromagnetic torque, and γ is the current angle.

[0060] Implementation Method Four: This implementation method further defines the variable step size current angle search method for permanent magnet synchronous motors (MTPA) based on stator current error described in Implementation Method Three. The gradient descent method is as follows:

[0061]

[0062] in, For the stator current gradient, γk Let η be the current angle in the k-th iteration, and η be 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. The adaptive adjustment of the step size gradually decreases as the solution approaches the optimum, thus avoiding oscillations or convergence instability caused by over-adjustment. This method improves computational efficiency while ensuring solution accuracy and reducing the computational burden of excessive iterations.

[0064] By dynamically adjusting the search step size based on stator current error rather than stator current derivative, the search process of the traditional gradient descent method is simplified by reducing computational load. Furthermore, the design of the gradient descent method effectively avoids the local optima problem that may occur with traditional fixed-step-size search methods. Especially during motor operation, parameters may change at any time; the gradient descent method can address system uncertainties through real-time adjustments, maintaining system stability and robustness.

[0065] Implementation Method 5: This implementation method further defines the MTPA variable step size current angle search method for permanent magnet synchronous motors based on stator current error described in Implementation Method 1. Step 2 includes:

[0066] Choose an initial current vector angle γ0 as the starting value for the search;

[0067] By applying a current angle perturbation Δγ k To obtain the change in stator current;

[0068] Based on the change in current ΔI s Dynamically adjust the search step size δ k The step size is related to |ΔI s |Proportional;

[0069] Set search direction d k Construct an iterative formula for the current angle;

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

[0071] Traditional MTPA algorithms typically rely on gradient calculations to determine the optimal current angle, which is computationally complex and sensitive to system noise. However, by employing stator current error feedback, the search step size is adjusted through simple current change feedback, reducing computational complexity while improving search efficiency.

[0072] The step size is proportional to the change in current and can be dynamically adjusted 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 precise search, thereby improving the algorithm's convergence speed and accuracy.

[0073] Traditional methods require accurate motor models and gradient information, while this method relies on the feedback signal of stator current error and does not require complex mathematical models and parameter estimation. Therefore, this method is more flexible and adaptable.

[0074] By setting an error threshold (ε) as the iteration termination condition, the search terminates when the absolute value of the current error is less than a preset tolerance, effectively avoiding overcomputation and improving the stability of the algorithm. Furthermore, the strategy of dynamically adjusting the step size and adaptive search direction helps improve the accuracy of the current angle calculation, thereby optimizing the motor's performance.

[0075] Implementation Method Six: This implementation method further defines the variable step size current angle search method for permanent magnet synchronous motors (MTPA) based on stator current error described in Implementation Method Five. The method is based on the current change ΔI... s Dynamically adjust the search step size δ k ,include:

[0076] δ k =α|ΔI s (γ k )|

[0077] Where α is the step size coefficient.

[0078] Implementation Method Seven: This implementation method further defines the variable step size current angle search method for permanent magnet synchronous motors (MTPA) based on stator current error described in Implementation Method Five. The search direction d... k for:

[0079]

[0080] Implementation Method Eight: This implementation method further defines the variable step size current angle search method for permanent magnet synchronous motors (MTPA) based on stator current error described in Implementation Method Five. The current angle iteration formula is as follows:

[0081] γ k+1 =γ k -αΔI s (γ k ).

[0082] Implementation Method Nine: A computer device according to this implementation method includes a memory and a processor. The memory stores a computer program. When the processor runs the computer program stored in the memory, the processor executes a variable step size current angle search method for permanent magnet synchronous motors (MTPA) based on stator current error, as described in any one of Implementation Methods One to Eight.

[0083] Implementation Method 10: A computer-readable storage medium according to this implementation method stores a computer program, which, when executed by a processor, performs the steps of a variable step size current angle search method for permanent magnet synchronous motors (MTPA) based on stator current error, as described in any one of Implementation Methods 1 to 8.

[0084] Implementation Method 11, see below Figure 2 , Figure 3 and Figure 4 This embodiment describes a specific implementation of the MTPA variable step size current angle search method for permanent magnet synchronous motors based on stator current error described in Embodiment 1. It also serves to explain Embodiments 2 through 8. Specifically:

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

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

[0087]

[0088] In the formula: γ is the current angle; i d i q These are the d-axis and q-axis stator currents, respectively.

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

[0090]

[0091] In the formula: T e For electromagnetic torque; L d L q These are the d-axis and q-axis inductances, respectively; ψ f For permanent magnet flux linkage; p n It is an extreme logarithm.

[0092] By combining equations (1) and (2), the stator current I can be obtained. s Relationship with current angle γ:

[0093]

[0094] Figure 2 I when the torque is constant s -γ relationship diagram. It can be seen that for function I... s (γ) has one and only one local minimum point, which is the MTPA operating point of the motor, and the gradient at this point is ▽I. s (γ) = 0. According to... Figure 2 It can be observed that when the motor operates to the left of the optimal current vector angle (γ < γ), MTPA Stator current gradient ▽I s (γ)<0; while when the motor is running to the right of the optimal current vector angle (γ>γ) MTPA Stator current gradient ▽I s (γ)>0. Based on this property, 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, and its formula is:

[0095]

[0096] In the formula: γ k Let η be the current angle in the k-th iteration, and η be the learning rate.

[0097] For a constant torque, the current vector angle at the minimum stator current is the desired value, and at this point:

[0098]

[0099] In the formula: I s,MTPA This is the stator current during MTPA operation.

[0100] According to I s The property of (γ) (convex function): If a negative proportionality constant K is introduced, such that the derivative of γ with respect to time satisfies:

[0101]

[0102] According to Lyapunov's stability theorem, it can be proved that the above equation will cause γ to approach its minimum value, i.e., γ MTPA .

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

[0104] Gradient descent requires complex gradient calculations, which are inherently unstable and sensitive to noise. Since noise exists in real-world currents, directly calculating the gradient can easily lead to misjudgment of direction. Furthermore, gradient descent requires manually setting the learning rate, making it relatively complex. Therefore, this implementation proposes the following optimizations to the gradient descent method.

[0105] By directly applying the current error as feedback to the next stator current angle search, the same control objective as the gradient descent method is achieved. s When <0, maintain the direction of current angle search, ΔI s When the current angle is greater than 0, the search direction of the current angle is reversed. This allows the algorithm to converge to the minimum point without gradient calculation, reducing computational complexity. Furthermore, the proposed method is insensitive to current noise and less prone to misjudgment of the search direction. Another advantage of the proposed method is that the search step size is related to ΔI. s Proportional to I s Approaching I s,MTPA ΔI s Gradually decreasing the step size naturally reduces the current angle search step size, which is what the search method aims for. Furthermore, since current fluctuations significantly interfere with the values ​​sampled at intervals, a periodic averaging method is used here, with the step size adjustment based on cumulative changes rather than instantaneous gradients, thus reducing the interference from current fluctuations.

[0106] The equivalence between the proposed search method and the gradient descent method will be explained below.

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

[0108] γ k+1 =γ k +Δγ k (7)

[0109] In the formula: △γ k =d k δ k d k For the search direction, take 1 or -1; δ k =α|△I s | represents the dynamic step size for the kth iteration, and α is the step size coefficient.

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

[0111]

[0112] Regarding the dynamic step size:

[0113]

[0114] Since the step size changes smoothly and has a relatively small impact, and considering the computational complexity, an approximate calculation is used in practical engineering. The influence of historical step sizes can be ignored, and the approximation is:

[0115]

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

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

[0118]

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

[0120]

[0121] The above equation is equivalent to:

[0122]

[0123] At this point, the update formula for 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. However, the proposed method does not require the calculation of the differential, which simplifies the implementation process of the gradient descent method.

[0124] The proposed search method will be explained in detail below using a flowchart.

[0125] Figure 3 The flowchart of the proposed search method is shown below. First, an initial current vector angle γ0 is selected as the starting value for the search, and k = 0 is set. Then, a current angle perturbation Δγ is applied, the current vector angle is updated, and the first-order difference ΔI of the stator current is calculated. s (γ k Set an error tolerance ε. If the absolute value of the current difference is less than ε, stop the search and output the current vector angle Δγ at this time. k+1 Otherwise, follow the iterative formula for the current angle Δγ. k+1 =-α△I s (γ k Continue to apply perturbation to the current angle for the next cycle until it converges to the MTPA operating point.

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

[0127] The present invention was used to conduct experimental verification on a real three-phase permanent magnet synchronous motor towing experimental platform. The motor has a rated power of 2.2kW and a DC bus voltage of 540V. Figure 4Experimental results were presented for obtaining the MTPA current angle of the motor at 400 r / min using different search methods, with an initial search angle of 108° for all methods. It can be seen that the fixed-step method and the variable-step method require four search steps to reach the steady-state value, while the proposed method only requires three search steps. For the fixed-step method, the steady-state current angle exhibits oscillations, while the variable-step method and the proposed method can eliminate these oscillations. Compared with the variable-step method, the convergence time of the proposed method is reduced from 1.03 s to 0.62 s, a reduction of 39.8%, verifying the effectiveness of the proposed method.

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

[0129] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 The computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0130] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

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

Claims

1. A variable step size current angle search method for permanent magnet synchronous motors (MTPA) based on stator current error, characterized in that, The method includes: Step 1: Establish the functional relationship between stator current and current angle, and design the 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; Step 1 includes: Based on the dq axis current equation and electromagnetic torque equation of the permanent magnet synchronous motor, a nonlinear relationship between stator current and current angle is established. Design a gradient descent method to make the current angle γ converge to the MTPA operating point along the negative gradient direction; The nonlinear relationship between the stator current and the current angle is as follows: in, I s For stator current, p n For extreme logarithms, ψ f It is a permanent magnet flux chain. L d for d Shaft inductor, L q They are respectively q Shaft inductor, T e For electromagnetic torque, γ It is the current angle; The gradient descent method is as follows: in, For the stator current gradient, γ k For the first k The current angle of the next iteration. η This is the learning rate.

2. The method for searching the MTPA (Metal Magnet Synchronous Motor) current angle based on stator current error according to claim 1, characterized in that, Step 2 includes: Choose an initial current vector angle γ 0, used as the starting value for the search; By applying a current angle perturbation To obtain the change in stator current; Based on the change in current Dynamically adjust search step size δ k Step size and Proportional; Set search direction d k Construct an iterative formula for the current angle; The iteration terminates when the absolute value of the current error is less than the preset tolerance ε, and the optimal current angle is output. γ MTPA .

3. The method for searching the MTPA (Metal Magnet Synchronous Motor) current angle based on stator current error according to claim 2, characterized in that, The amount of current change Dynamically adjust search step size δ k , include: in, This is the step size coefficient.

4. The MTPA variable step size current angle search method for permanent magnet synchronous motors based on stator current error according to claim 2, characterized in that, The search direction d k for: 。 5. The MTPA variable step size current angle search method for permanent magnet synchronous motors based on stator current error according to claim 2, characterized in that, The iterative formula for the current angle is: 。 6. A computer device, characterized in that: It includes a memory and a processor, wherein the memory stores a computer program, and when the processor runs the computer program stored in the memory, the processor executes a variable step size current angle search method for permanent magnet synchronous motors based on stator current error as described in any one of claims 1-5.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of the MTPA variable step size current angle search method for permanent magnet synchronous motors based on stator current error as described in any one of claims 1-5.

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