A design optimization method, device and equipment of an interior permanent magnet motor and a medium

Abstract

The application discloses a built-in permanent magnet motor design optimization method, device, equipment and medium, and relates to the technical field of electromagnetic design, and comprises the following steps: determining initial stator parameters and initial rotor parameters based on preset rated parameters by using a preset electromagnetic theory formula; constructing a constraint condition for constraining parameter values of each parameter from not exceeding a corresponding range based on a numerical range of the initial stator parameters and the initial rotor parameters; executing a first parameter optimization logic to optimize the initial stator parameters to obtain target stator parameters by using the constraint condition, and controlling the target stator parameters to remain unchanged; executing a second parameter optimization logic to optimize the initial rotor parameters to obtain target rotor parameters by using the constraint condition; and simulating based on the target stator parameters and the target rotor parameters by using a space vector pulse width modulation simulation technology to determine target design parameters. The application can solve the problem of parameter coupling in the design of the built-in permanent magnet motor, realize synchronous optimization of each parameter, and ensure the reliability of motor design.

Description

Technical Field

[0001] This invention relates to the field of electromagnetic design technology, and in particular to a design optimization method, apparatus, equipment and medium for an embedded permanent magnet motor. Background Technology

[0002] Driven by the deepening of the "dual carbon" goals and the rigid constraints of energy conservation and emission reduction, upgrading the energy efficiency of industrial motors has become a key breakthrough for the green transformation of the manufacturing industry. Currently, permanent magnet synchronous motors are accelerating their comprehensive replacement of traditional asynchronous motors. Built-in permanent magnet motors, due to their advantages such as wide speed range, high overload capacity, and dynamic response performance, have been widely used in new energy vehicles, rail transportation, and industrial servo systems. Large power equipment such as scraper conveyors, ball mills, and agitators commonly adopt built-in permanent magnet motors with V-shaped rotor structures. Furthermore, as the advantages of shaped coils—high slot fill factor and adaptability to high voltage levels—become increasingly prominent, traditional round wire coils are being gradually replaced.

[0003] However, when using molded coils in the design and optimization of built-in permanent magnet motors, the stator slot dimensions are strongly constrained by the coil dimensions. This leads to difficulties in coil manufacturing during optimization, and when optimizing the stator and rotor in tandem, it is difficult to achieve completely synchronous changes in various dimensional parameters. Therefore, how to consider the coupling of various parameters in a built-in permanent magnet motor to achieve motor design is a problem that needs to be solved in this field. Summary of the Invention

[0004] In view of this, the purpose of this invention is to provide a design optimization method, apparatus, device, and medium for an embedded permanent magnet motor, which can solve the parameter coupling problem in the design of an embedded permanent magnet motor, achieve synchronous optimization of various parameters, and ensure the reliability of the motor design. The specific solution is as follows: Firstly, this application provides a design optimization method for a built-in permanent magnet motor, including: The preset rated parameters of the built-in permanent magnet motor are determined, and the initial design parameters of the built-in permanent magnet motor are determined based on the preset rated parameters using preset electromagnetic theory formulas; the initial design parameters include initial stator parameters and initial rotor parameters. A first numerical range of the initial stator parameters and a second numerical range of the initial rotor parameters are determined, and a first preset constraint condition is constructed based on the first numerical range, and a second preset constraint condition is constructed based on the second numerical range; the constraint conditions are used to ensure that the parameter values ​​of each of the initial design parameters do not exceed the corresponding numerical range. Execute the first parameter optimization logic to optimize the initial stator parameters using the first preset constraint conditions to obtain the target stator parameters; The target stator parameters are kept constant, and the second parameter optimization logic is executed to optimize the initial rotor parameters using the second preset constraint conditions to obtain the target rotor parameters; Based on space vector pulse width modulation simulation technology, and based on the target stator parameters and the target rotor parameters, simulation results are obtained, and the target design parameters of the built-in permanent magnet motor are determined based on the simulation results.

[0005] Optionally, the initial stator parameters include the stator core inner diameter, stator core length, stator coil turns, stator tooth width, stator yoke thickness, and stator formed coil dimensions.

[0006] Optionally, executing the first parameter optimization logic to optimize the initial stator parameters using the first preset constraint conditions includes: Based on the first preset constraint conditions, the range of coil linewidth, the range of coil line height, and the range of stator split ratio of the built-in permanent magnet motor are determined. Keeping the permanent magnet width and permanent magnet thickness of the built-in permanent magnet motor unchanged, and optimizing the stator split ratio, stator tooth width and stator yoke thickness of the built-in permanent magnet motor based on the coil line width range, the coil line height range and the stator split ratio range.

[0007] Optionally, optimizing the stator split ratio, stator tooth width, and stator yoke thickness of the built-in permanent magnet motor based on the coil linewidth range, the coil line height range, and the stator split ratio range includes: The initial design parameters corresponding to each stator split ratio in the stator split ratio range are determined, and the target parameters in the stator split ratio range are determined based on the coil linewidth range and the coil lineheight range, according to the initial design parameters corresponding to each stator split ratio. Finite element simulation is performed based on the target parameters, and the stator crack ratio is optimized based on the simulation results to obtain the target crack ratio in the target stator parameters. The stator tooth width and stator yoke thickness are optimized based on the target split ratio to obtain the target tooth width and target yoke thickness in the target stator parameters.

[0008] Optionally, the initial rotor parameters include a first target angle, a second target angle, a magnetic bridge width, a minimum spacing between permanent magnets, and a magnetic bridge spacing; wherein, the first target angle is the included angle between the V-shaped permanent magnets in the built-in permanent magnet motor, and the second target angle is the angle occupied by each pole permanent magnet in the rotor of the built-in permanent magnet motor.

[0009] Optionally, controlling the target stator parameters to remain unchanged and executing the second parameter optimization logic to optimize the initial rotor parameters using the second preset constraint conditions includes: The target stator parameters are kept constant, and the corresponding permanent magnet size is determined based on the second preset constraint condition. The initial rotor parameters are optimized based on the permanent magnet dimensions to obtain the target rotor parameters.

[0010] Optionally, the simulation based on space vector pulse width modulation (SPWM) technology, and the simulation based on the target stator parameters and the target rotor parameters, to obtain corresponding simulation results, and the determination of the target design parameters of the built-in permanent magnet motor based on the simulation results, includes: The three-phase current at a preset frequency is determined based on space vector pulse width modulation simulation technology; Based on the three-phase current, the target stator parameters, and the target rotor parameters, simulations were performed to obtain the loss data of the built-in permanent magnet motor. The target design parameters of the built-in permanent magnet motor are determined based on the loss data and the preset rotor temperature rise.

[0011] Secondly, this application provides a design optimization device for a built-in permanent magnet motor, comprising: An initial parameter determination module is used to determine the preset rated parameters of the built-in permanent magnet motor, and to determine the initial design parameters of the built-in permanent magnet motor based on the preset rated parameters using preset electromagnetic theory formulas; the initial design parameters include initial stator parameters and initial rotor parameters; The parameter range determination module is used to determine a first numerical range of the initial stator parameters and a second numerical range of the initial rotor parameters, and to construct a first preset constraint condition based on the first numerical range and a second preset constraint condition based on the second numerical range; the constraint conditions are used to ensure that the parameter values ​​of each of the initial design parameters do not exceed the corresponding numerical range. The first parameter optimization module is used to execute the first parameter optimization logic to optimize the initial stator parameters using the first preset constraint conditions to obtain the target stator parameters; The second parameter optimization module is used to control the target stator parameters to remain unchanged and execute the second parameter optimization logic to optimize the initial rotor parameters using the second preset constraint conditions to obtain the target rotor parameters. The target parameter determination module is used to perform simulations based on space vector pulse width modulation simulation technology, based on the target stator parameters and the target rotor parameters, to obtain the corresponding simulation results, and to determine the target design parameters of the built-in permanent magnet motor based on the simulation results.

[0012] Thirdly, this application provides an electronic device, which includes a processor and a memory; wherein the memory is used to store a computer program, which is loaded and executed by the processor to implement the aforementioned design optimization method for a built-in permanent magnet motor.

[0013] Fourthly, this application provides a computer-readable storage medium for storing a computer program, which, when executed by a processor, implements the aforementioned design optimization method for a built-in permanent magnet motor.

[0014] This application first determines the preset rated parameters of the built-in permanent magnet motor, and then uses preset electromagnetic theory formulas to determine the initial design parameters of the built-in permanent magnet motor based on the preset rated parameters. The initial design parameters include initial stator parameters and initial rotor parameters. Then, it determines a first numerical range of the initial stator parameters and a second numerical range of the initial rotor parameters. Based on the first numerical range, it constructs a first preset constraint condition, and based on the second numerical range, it constructs a second preset constraint condition to ensure that the parameter values ​​of each initial design parameter do not exceed the corresponding numerical range. Then, it executes a first parameter optimization logic to optimize the initial stator parameters using the first preset constraint condition to obtain the target stator parameters and to keep the target stator parameters unchanged. Then, it executes a second parameter optimization logic to optimize the initial rotor parameters using the second preset constraint condition to obtain the target rotor parameters. Finally, it uses space vector pulse width modulation simulation technology to perform simulation based on the target stator parameters and the target rotor parameters to obtain the corresponding simulation results, and determines the target design parameters of the built-in permanent magnet motor based on the simulation results.

[0015] Through the above technical solution, this application can first determine the preset rated parameters of the motor, then calculate the initial design parameters using preset electromagnetic theory formulas, and define the numerical ranges of the stator and rotor parameters respectively, and construct the first and second preset constraints accordingly. The constraint parameter values ​​do not exceed the boundaries, avoiding the parameters from deviating from the reasonable range during the optimization process and ensuring the practicality of the optimization results. Then, the first parameter optimization logic is executed to optimize the initial stator parameters under the first preset constraint conditions to obtain the target stator parameters, decoupling the coupling effect of stator and rotor parameters. Then, keeping the target stator parameters unchanged, the second parameter optimization logic is executed to optimize the initial rotor parameters under the second preset constraint conditions to obtain the target rotor parameters. Finally, space vector pulse width modulation simulation is introduced to perform actual operating condition simulation based on the target stator and rotor parameters. The final target design parameters are determined based on the simulation results, thereby solving the problem of the disconnect between the existing design method and the actual operating conditions, improving the operating stability and service life of the motor. Therefore, this application can solve the parameter coupling problem in the design of built-in V-type permanent magnet motors, realize the synchronous change of various dimensional parameters, and help ensure the reliability of motor design. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0017] Figure 1 A flowchart of a design optimization method for a built-in permanent magnet motor is provided in this application; Figure 2 A schematic diagram of a permanent magnet structure is provided in this application; Figure 3 A structural schematic diagram of the first type of permanent magnet constraint dimensions provided in this application; Figure 4 A structural schematic diagram of the second type of permanent magnet constraint size provided in this application; Figure 5 A structural schematic diagram of the third type of permanent magnet constraint dimension provided in this application; Figure 6 A schematic diagram of a Pareto optimal solution provided in this application; Figure 7 A schematic diagram of parameters near the edge of a Pareto front provided for this application; Figure 8 This application provides a schematic diagram of a simulated three-phase current waveform; Figure 9 A schematic diagram of a design optimization device for a built-in permanent magnet motor provided in this application; Figure 10 This application provides a structural diagram of an electronic device. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] It should be noted that, in the description of this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. The terms "first," "second," etc., in this application are used to distinguish similar objects and are not used to describe a specific order or sequence.

[0020] When using molded coils in the design and optimization of built-in permanent magnet motors, the stator slot size is constrained by the coil size, which leads to difficulties in coil manufacturing and processing during optimization. Furthermore, when optimizing the stator and rotor in tandem, it is difficult to achieve complete synchronous changes in various dimensional parameters. This application can solve the problem of parameter coupling in the design of built-in V-type permanent magnet motors, achieve synchronous changes in various dimensional parameters, and ensure the reliability of motor design.

[0021] To enable those skilled in the art to better understand the present application, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0022] See Figure 1 As shown in the figure, an embodiment of the present invention discloses a design optimization method for a built-in permanent magnet motor, including: Step S11: Determine the preset rated parameters of the built-in permanent magnet motor, and use the preset electromagnetic theory formula to determine the initial design parameters of the built-in permanent magnet motor based on the preset rated parameters; the initial design parameters include the initial stator parameters and the initial rotor parameters.

[0023] In this embodiment, the preset rated parameters of the built-in permanent magnet motor are first determined, and the initial design parameters of the built-in permanent magnet motor are determined based on the preset rated parameters using preset electromagnetic theory formulas. The initial design parameters include initial stator parameters and initial rotor parameters. Specifically, this includes, but is not limited to, the preliminary calculation of the following parameters: preliminary calculation of the stator core inner diameter. D and core length L stk : ; in, P G represents the power of the permanent magnet motor, and G represents the motor constant. n Indicates the motor speed. This indicates the stator split ratio (the ratio of the stator's inner and outer diameters). Indicates the outer diameter of the stator core; Preliminary calculation of the number of coil turns N : ; in, E 0 represents the induced electromotive force, and C represents the potential constant. Indicates voltage utilization rate. Indicates the DC bus voltage; Preliminary calculations of stator teeth and yoke parameters: ; in, Indicates tooth width. Indicates yoke thickness. This represents the maximum magnetic flux density of the constrained teeth and yoke. Indicates the superposition factor. Z Indicates the number of slots. Represents the extreme number. Indicates the air gap magnetic flux density; Preliminary calculations of the wire width and wire height of the formed coil, i.e., the wire gauge, assuming the groove is divided into upper and lower sections: ; in, Indicates line width. Indicates line height, , Indicates insulation thickness; Preliminary calculation of permanent magnet dimensions: ; in, Indicates the width of the permanent magnet. Indicates the thickness of the permanent magnet. Indicates the polar arc coefficient. This indicates the remanence of a permanent magnet. Indicates the physical air gap. This represents the equivalent air gap considering the effect of slotting. Represents the Carter coefficient. This represents the leakage flux coefficient of a permanent magnet. This represents the maximum demagnetization coefficient of armature reaction.

[0024] Step S12: Determine the first numerical range of the initial stator parameters and the second numerical range of the initial rotor parameters, and construct a first preset constraint condition based on the first numerical range and a second preset constraint condition based on the second numerical range; the constraint condition is used to constrain the parameter values ​​of each initial design parameter to not exceed the corresponding numerical range.

[0025] In this embodiment, a first numerical range for the initial stator parameters and a second numerical range for the initial rotor parameters can be determined. A first preset constraint condition is constructed based on the first numerical range, and a second preset constraint condition is constructed based on the second numerical range. This ensures that the parameter values ​​of each initial design parameter do not exceed their corresponding numerical ranges. The aforementioned data ranges include, but are not limited to, the optimization range for the split ratio in the initial stator parameters. , ], constrained line gauge forming coil line width [ , Line height , ]、[ , ].

[0026] Step S13: Execute the first parameter optimization logic to optimize the initial stator parameters using the first preset constraint conditions to obtain the target stator parameters.

[0027] In this embodiment, a first parameter optimization logic can be executed to optimize the initial stator parameters using a first preset constraint condition, thereby obtaining the target stator parameters. The initial stator parameters may include the stator core inner diameter, stator core length, number of stator coil turns, stator tooth width, stator yoke thickness, and stator formed coil dimensions. Specifically, the coil linewidth range, coil lineheight range, and stator split ratio range of the stator formed coil dimensions can be determined first based on the first preset constraint condition, while keeping the permanent magnet width and thickness of the built-in permanent magnet motor unchanged. Based on the coil linewidth range, coil lineheight range, and stator split ratio range, the stator split ratio, stator tooth width, and stator yoke thickness of the built-in permanent magnet motor are optimized. In other words, in this embodiment, the permanent magnet width can be kept constant. and permanent magnet thickness The optimization range of the constraint split ratio remains unchanged. , ], constrained line gauge forming coil line width [ , Line height , ]、[ , ].

[0028] Furthermore, based on the range of coil linewidth, coil lineheight, and stator split ratio, when optimizing the stator split ratio, stator tooth width, and stator yoke thickness of the built-in permanent magnet motor, the initial design parameters corresponding to each stator split ratio within the range of stator split ratio can be determined. Based on the range of coil linewidth and coil lineheight, the first target parameter that meets the conditions within the range of stator split ratio is determined according to the initial design parameters corresponding to each stator split ratio. Then, finite element simulation is performed based on the first target parameter, and the stator split ratio is optimized based on the simulation results to obtain the target split ratio in the target stator parameters. Furthermore, the stator tooth width and stator yoke thickness are optimized based on the target split ratio to obtain the target tooth width and target yoke thickness in the target stator parameters.

[0029] In other words, in this embodiment, for each crack ratio value, other dimensional parameters can be calculated according to the parameter calculation process in step S11, while the number of turns is also included. N Re-adjust to integers. If the gauge exceeds the constraint range, discard the corresponding split ratio value. Then, the remaining range that meets the conditions is used to obtain the electromagnetic torque through finite element simulation. T e Core loss P Fe Meanwhile, the cost change during the split ratio change process is also considered: ; in, , , These represent the unit cost of the coil, permanent magnet, and iron core, respectively. , , These represent the weights of the coil, permanent magnet, and iron core, respectively. , This indicates the average length of the coil end and the length of the straight segment at the coil end. Indicates the effective number of series turns of each phase coil. Indicates the number of slots the coil spans. Indicates the inner bore diameter. , , These represent the densities of copper, iron, and permanent magnets, respectively. , These represent the net volumes of the stator core and rotor core, respectively.

[0030] Then set T e , P Fe The design weights k1, k2, and k3 for cost are used to determine the split ratio that yields the highest score, which corresponds to the optimal split ratio, based on the following formula. : ; Then maintain the optimal split ratio Keeping them constant, set the variation coefficients for tooth width and yoke thickness. , And their respective ranges of change; correspondingly, other parameters such as the gauge will change accordingly. Further, following the steps mentioned above, continue to eliminate coefficient values ​​that do not conform to the gauge constraints, and continue to repeat the corresponding parameter optimization steps until the optimal tooth width and yoke thickness are determined. , In this way, when optimizing, the stator slot size is strongly constrained by the coil size when using shaped coils, which reduces the difficulty of coil manufacturing and avoids problems such as excessive AC copper loss. Furthermore, when optimizing the stator and rotor together, the number of coil turns must be adjusted to an integer, thus achieving synchronous changes in various dimensional parameters.

[0031] Step S14: Keep the target stator parameters unchanged and execute the second parameter optimization logic to optimize the initial rotor parameters using the second preset constraint conditions to obtain the target rotor parameters.

[0032] In this embodiment, the target stator parameters can be kept constant, and the second parameter optimization logic can be executed to optimize the initial rotor parameters using the second preset constraint conditions, thereby obtaining the target rotor parameters. The initial rotor parameters include the first target angle. Second target perspective Magnetic bridge width and The shortest spacing of permanent magnets Spacing between magnetic bridges Among them, such as Figure 2 As shown, the first target angle is the angle between the V-shaped permanent magnets in the built-in permanent magnet motor, and the second target angle is the angle occupied by each pole permanent magnet in the rotor of the built-in permanent magnet motor. That is to say, in the rotor parameter optimization process of this embodiment, parameters such as... Figure 2 The six key optimization parameters shown are: Indicates a V-shaped angle. Indicates the width of the magnetic bridge at the included angle. Indicates the width of the outer magnetic bridge. This indicates the shortest distance between the permanent magnets at the included angle. Indicates the shortest distance of the outer magnetic bridge. This indicates the angle occupied by each permanent magnet pole. Equivalent to polar arc coefficient The conversion formula is as follows: .

[0033] Correspondingly, the target stator parameters can be kept constant, the corresponding permanent magnet dimensions can be determined based on the second preset constraint conditions, and the initial rotor parameters can be optimized based on the permanent magnet dimensions to obtain the target rotor parameters. In other words, the stator dimensions can be kept constant, reasonable variation ranges can be set for each of the six optimization parameters, and constraints can be imposed on some dimensions to avoid geometric interference problems when the six optimization parameters change simultaneously. Firstly, as... Figure 3 As shown, in Figure 3 At point ①, to ensure that the permanent magnet can be reliably placed into its slot, the dimension d1 at this point is constrained to be ≥ 1 mm. The specific constraint expression is as follows: ; Secondly, as Figure 4 As shown, Figure 4 At point ②, to ensure that the permanent magnet can be reliably placed into its slot, the dimension d2 at this point is constrained to be ≥ 1 mm. The specific constraint expression is as follows: ; Finally, as Figure 5 As shown, Figure 5At point ③, to prevent this straight segment from being submerged, the dimension d3 at this point is constrained to be ≥ 1 mm. The specific constraint expression is as follows (where dm0 is the depth of the permanent magnet embedded in its slot): ; Subsequently, a multi-objective genetic algorithm was used to collaboratively optimize rotor parameters. The initial dimensions served as the baseline generated by the Design of Experiments (DOE). The optimization objectives were to maximize the average torque and minimize torque ripple. The optimized cases were then placed in a coordinate system with the average torque as the horizontal axis and torque ripple as the vertical axis. Points on the Pareto front (points with minimum torque ripple for the same average torque / maximum average torque for the same torque ripple) were selected as the optimized results to achieve optimization of the rotor's magnetic bridge dimensions. This approach avoids the problem of numerous and coupled dimensional parameters of the rotor's magnetic bridge, which can easily lead to geometric interference when dimensions change, thus achieving accurate optimization of rotor parameters.

[0034] Step S15: Based on space vector pulse width modulation simulation technology, and based on the target stator parameters and the target rotor parameters, simulation is performed to obtain the corresponding simulation results, and the target design parameters of the built-in permanent magnet motor are determined based on the simulation results.

[0035] In this embodiment, the three-phase current at a preset frequency can be determined based on space vector pulse width modulation simulation technology. Simulations are then performed based on the three-phase current, target stator parameters, and target rotor parameters to obtain the loss data of the built-in permanent magnet motor. Finally, the loss data and the preset rotor temperature rise are used as the basis for the calculation. T r Determine the target design parameters for the built-in permanent magnet motor. That is, this embodiment needs to consider the impact of frequency conversion drive and iterate the dimensions. Specifically, SVPWM (Space Vector Pulse Width Modulation) frequency conversion control can be used to obtain the three-phase current at a specific switching frequency fc. Data from one electrical cycle after the three-phase current envelope stabilizes is extracted and used as a current source to supply the three-phase windings for finite element simulation. The stator and rotor iron losses at this point are obtained, and all motor losses at this point are used as the basis for temperature rise simulation, focusing on rotor temperature rise. T r ,like T r The reliability range has been exceeded, and the core length needs to be increased. L stk Then reduce the current amplitude, and repeat the above steps until the current is reduced. T rThe design is now complete, keeping the parameters within a reliable range. This completes the design and optimization of the built-in V-type permanent magnet motor. By comprehensively considering the coupling between various design parameters, synergistic optimization of these parameters is achieved, and problems such as increased rotor losses and severe heat generation can be avoided.

[0036] In one specific embodiment, taking a 3300V powered motor with a rated speed of 1004rpm and a rated power of 855kW as an example, the design optimization method of the corresponding built-in permanent magnet motor will be specifically described, including: First, calculate the initial dimensions, select a slot / pole number of 84 / 16, and set... , The calculated initial dimensions are shown in Table 1 below: Table 1 Initial Dimensions

[0037] Then, the stator split ratio (ratio of inner to outer diameter) and tooth and yoke dimensions were optimized. Specifically, the split ratio optimization range was set from 0.7 to 0.8 (in increments of 0.1), with bc ≥ 5 mm, 1.1 mm ≤ hc ≤ 2.1 mm, and 1.5 ≤ bc / hc ≤ 6. After removing split ratio values ​​that did not meet the conditions, the split ratio variation range was reduced to 0.75-0.8. The changes in other parameters caused by the split ratio variation and the comparison of finite element simulation results are shown in Table 2 below. Table 2. Schematic diagram of parameter changes

[0038] In this embodiment, it can then be set that... T e , P Fe Cost T e The highest weight, P Fe The weight of the group with the lowest weight was selected, and groups 4-6 were retained after screening. Further calculation showed that the costs of these three groups were 7.86, 7.80, and 7.97 (unit: 10,000 yuan), respectively. Therefore, group 5 was finally selected, with a split ratio of 0.76.

[0039] Furthermore, keeping the crack ratio constant, the tooth width and yoke thickness coefficients are set respectively. , The variation range is 0.9-1.0 with a step size of 0.02, and 0.9-1.1 with a step size of 0.05. The constraint range of the line gauge is the same as above, thus updating... The variation range is 0.94-1.04 with a step size of 0.02. The finite element simulation process is then repeated, at which point... P Fe The weight is set to the highest. Te The weight is set to the minimum. Finally, the optimal coefficient is selected. , The values ​​are 0.98 and 1.04 respectively. The stator dimension parameters were ultimately optimized through the above steps, and the stator dimension parameter updates are shown in Table 3 below: Table 3. Stator Dimension Parameter Update Diagram

[0040] Then, based on the above stator size parameters, the rotor's magnetic isolation bridge and other dimensions are optimized. First, the initial values ​​and variation ranges of the six key parameters of the rotor to be optimized are determined, as shown in Table 4 below: Table 4. Schematic diagram of initial values ​​and variation range of rotor parameters

[0041] Then, constrained according to the dimensions of d1-d3 in the previous embodiment, the initial values ​​of each parameter in the table above are used as the benchmark for the Multi-Objective Genetic Algorithm (MOGA) DOE, and the optimization objectives are selected as maximizing the average torque and minimizing the torque ripple. The population size N1, the total number of generations N2, and the number of algorithm iterations N are determined according to the following formula. iter : ; in, , These represent the number of parameter variables and the number of optimization objectives, respectively.

[0042] Furthermore, the optimized case is placed in a planar coordinate system with the average torque on the horizontal axis and the torque pulsation on the vertical axis, such as... Figure 6 As shown in the figure, the curve represents the Pareto front (the curve where the optimal solution is located). It can be seen that points on the Pareto front all satisfy the following conditions: minimum torque ripple for the same average torque / maximum average torque for the same torque ripple. Furthermore, in the range where the average torque ≥ 9400 Nm, as... Figure 7 As shown, five sets of parameters closest to the edge of the Pareto front were selected, and their data are shown in Table 5 below: Table 5. Parameters closest to the edge on the Pareto front.

[0043] In the parameters in the table above, although number 515 achieves the maximum torque output, Excessive thinness could lead to insufficient mechanical strength, so parameter 253 was ultimately selected as the optimized rotor parameter. Through rotor size optimization, the motor's average torque increased by 7.4%, and under torque ripple, it was only 23% of the initial design.

[0044] Finally, the impact of the frequency converter drive can be considered, and the iteration size can be determined. First, the actual frequency converter switching frequency and other parameters are determined and substituted into the SVPWM simulation circuit, as shown in Table 6 below: Table 6. Simulation Results (Illustrated)

[0045] The simulation stability conditions can then be set as follows: the average torque and the actual dq-axis current fluctuate by less than 1% within one electrical cycle. The simulation then yields the actual three-phase current waveforms under variable frequency drive, as shown below. Figure 8 As shown, the current data of the complete cycle closest to the steady state is then extracted as the excitation and fed into the three-phase windings. The iron loss under variable frequency drive and iron loss under sinusoidal excitation are obtained from the simulation. The comparison results are shown in Table 7 below. It can be concluded that under variable frequency drive, the iron loss of rotor and stator increases to 1.12 times and 1.10 times the original, respectively.

[0046] Table 7. Schematic diagram of loss comparison results

[0047] Further updates to the loss data were made, constraining the maximum winding temperature to be <110℃ and the maximum rotor temperature to be <95℃. Temperature rise simulations revealed maximum winding temperatures of 112℃ and maximum rotor temperatures of 103℃, both exceeding the limits. Therefore, the core length Lstk ​​was increased to 560mm, and the rated current amplitude was simultaneously reduced. Finally, through iteration, the maximum temperatures of the winding and rotor were limited to 103℃ and 94℃ respectively, thus completing the design and optimization of the built-in permanent magnet motor.

[0048] See Figure 9 As shown in the embodiments, this application also discloses a design optimization device for a built-in permanent magnet motor, including: The initial parameter determination module 11 is used to determine the preset rated parameters of the built-in permanent magnet motor, and to determine the initial design parameters of the built-in permanent magnet motor based on the preset rated parameters using preset electromagnetic theory formulas; the initial design parameters include initial stator parameters and initial rotor parameters. The parameter range determination module 12 is used to determine the first numerical range of the initial stator parameters and the second numerical range of the initial rotor parameters, and to construct a first preset constraint condition based on the first numerical range and a second preset constraint condition based on the second numerical range; the constraint condition is used to constrain the parameter values ​​of each of the initial design parameters to not exceed the corresponding numerical range. The first parameter optimization module 13 is used to execute the first parameter optimization logic to optimize the initial stator parameters using the first preset constraint conditions to obtain the target stator parameters; The second parameter optimization module 14 is used to control the target stator parameters to remain unchanged and execute the second parameter optimization logic to optimize the initial rotor parameters using the second preset constraint conditions to obtain the target rotor parameters; The target parameter determination module 15 is used to perform simulation based on space vector pulse width modulation simulation technology, based on the target stator parameters and the target rotor parameters, to obtain the corresponding simulation results, and to determine the target design parameters of the built-in permanent magnet motor based on the simulation results.

[0049] This embodiment first determines the preset rated parameters of the motor, then calculates the initial design parameters using preset electromagnetic theory formulas, and defines the numerical ranges of the stator and rotor parameters respectively. Correspondingly, it constructs first and second preset constraints, ensuring that the constraint parameter values ​​do not exceed the boundaries, thus preventing parameters from deviating from reasonable ranges during optimization and guaranteeing the practicality of the optimization results. Next, it executes the first parameter optimization logic to optimize the initial stator parameters under the first preset constraints, obtaining the target stator parameters and decoupling the coupling effect between stator and rotor parameters. Then, keeping the target stator parameters unchanged, it executes the second parameter optimization logic to optimize the initial rotor parameters under the second preset constraints, obtaining the target rotor parameters. Finally, it introduces space vector pulse width modulation simulation, performs actual operating condition simulation based on the target stator and rotor parameters, and determines the final target design parameters based on the simulation results. This solves the problem of existing design methods being disconnected from actual operating conditions, improves the motor's operational stability and service life, and thus solves the parameter coupling problem in the design of built-in V-type permanent magnet motors, achieving synchronous changes in various dimensional parameters and ensuring the reliability of the motor design.

[0050] In some specific embodiments, the initial stator parameters include the stator core inner diameter, stator core length, number of stator coil turns, stator tooth width, stator yoke thickness, and stator formed coil dimensions.

[0051] In some specific embodiments, the first parameter optimization module 13 specifically includes: The parameter range determination submodule is used to determine the range of coil linewidth, coil line height, and stator split ratio of the stator forming coil size based on the first preset constraint conditions. The stator parameter optimization submodule is used to keep the permanent magnet width and permanent magnet thickness of the built-in permanent magnet motor unchanged, and optimize the stator split ratio, stator tooth width and stator yoke thickness of the built-in permanent magnet motor based on the coil line width range, the coil line height range and the stator split ratio range.

[0052] In some specific embodiments, the stator parameter optimization submodule specifically includes: The target parameter determination unit is used to determine the initial design parameters corresponding to each stator split ratio in the stator split ratio range, and to determine the target parameters in the stator split ratio range based on the coil linewidth range and the coil line height range, according to the initial design parameters corresponding to each stator split ratio. The target split ratio determination unit is used to perform finite element simulation based on the target parameters and optimize the stator split ratio based on the simulation results to obtain the target split ratio in the target stator parameters. The stator parameter optimization unit is used to optimize the stator tooth width and stator yoke thickness based on the target split ratio to obtain the target tooth width and target yoke thickness in the target stator parameters.

[0053] In some specific embodiments, the initial rotor parameters include a first target angle, a second target angle, a magnetic bridge width, a minimum spacing between permanent magnets, and a magnetic bridge spacing; wherein, the first target angle is the included angle between the V-shaped permanent magnets in the built-in permanent magnet motor, and the second target angle is the angle occupied by each pole permanent magnet in the rotor of the built-in permanent magnet motor.

[0054] In some specific embodiments, the second parameter optimization module 14 specifically includes: A size determination unit is used to control the target stator parameters to remain unchanged and determine the corresponding permanent magnet size based on the second preset constraint condition; The rotor parameter optimization unit is used to optimize the initial rotor parameters based on the permanent magnet dimensions to obtain the target rotor parameters.

[0055] In some specific embodiments, the target parameter determination module 15 specifically includes: The current determination unit is used to determine the three-phase current at a preset frequency based on space vector pulse width modulation simulation technology. The loss determination unit is used to perform simulation based on the three-phase current, the target stator parameters, and the target rotor parameters to obtain the loss data of the built-in permanent magnet motor. The parameter determination unit is used to determine the target design parameters of the built-in permanent magnet motor based on the loss data and the preset rotor temperature rise.

[0056] Furthermore, embodiments of this application also disclose an electronic device, Figure 10 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content of the diagram should not be construed as limiting the scope of this application.

[0057] Figure 10This is a schematic diagram of the structure of an electronic device 20 provided in an embodiment of this application. Specifically, the electronic device 20 may include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 stores a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the design optimization method for the built-in permanent magnet motor disclosed in any of the foregoing embodiments. Alternatively, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0058] In this embodiment, the power supply 23 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol it follows can be any communication protocol applicable to the technical solution of this application, and is not specifically limited here; the input / output interface 25 is used to acquire external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs, and is not specifically limited here.

[0059] In addition, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk or optical disk, etc. The resources stored thereon can include operating system 221, computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0060] The operating system 221 is used to manage and control the various hardware devices on the electronic device 20 and the computer program 222, which may be Windows Server, Netware, Unix, Linux, etc. In addition to including a computer program capable of performing the design optimization method for the built-in permanent magnet motor executed by the electronic device 20 as disclosed in any of the foregoing embodiments, the computer program 222 may further include computer programs capable of performing other specific tasks.

[0061] Furthermore, this application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the aforementioned design optimization method for an embedded permanent magnet motor. Specific steps of this method can be found in the corresponding content disclosed in the foregoing embodiments, and will not be repeated here.

[0062] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section.

[0063] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0064] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0065] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0066] The technical solutions provided in this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A design optimization method for a built-in permanent magnet motor, characterized in that, include: Determine the preset rated parameters of the built-in permanent magnet motor, and use the preset electromagnetic theory formula to determine the initial design parameters of the built-in permanent magnet motor based on the preset rated parameters; The initial design parameters include initial stator parameters and initial rotor parameters; Determine a first numerical range for the initial stator parameters and a second numerical range for the initial rotor parameters, and construct a first preset constraint condition based on the first numerical range and a second preset constraint condition based on the second numerical range; The constraints are used to ensure that the parameter values ​​of each of the initial design parameters do not exceed the corresponding numerical range. Execute the first parameter optimization logic to optimize the initial stator parameters using the first preset constraint conditions to obtain the target stator parameters; The target stator parameters are kept constant, and the second parameter optimization logic is executed to optimize the initial rotor parameters using the second preset constraint conditions to obtain the target rotor parameters; Based on space vector pulse width modulation simulation technology, and based on the target stator parameters and the target rotor parameters, simulation results are obtained, and the target design parameters of the built-in permanent magnet motor are determined based on the simulation results.

2. The design optimization method for the built-in permanent magnet motor according to claim 1, characterized in that, The initial stator parameters include the stator core inner diameter, stator core length, number of stator coil turns, stator tooth width, stator yoke thickness, and stator formed coil dimensions.

3. The design optimization method for the built-in permanent magnet motor according to claim 2, characterized in that, The execution of the first parameter optimization logic to optimize the initial stator parameters using the first preset constraint conditions includes: Based on the first preset constraint conditions, the range of coil linewidth, the range of coil line height, and the range of stator split ratio of the built-in permanent magnet motor are determined. Keeping the permanent magnet width and permanent magnet thickness of the built-in permanent magnet motor unchanged, and optimizing the stator split ratio, stator tooth width and stator yoke thickness of the built-in permanent magnet motor based on the coil line width range, the coil line height range and the stator split ratio range.

4. The design optimization method for the built-in permanent magnet motor according to claim 3, characterized in that, The optimization of the stator split ratio, stator tooth width, and stator yoke thickness of the built-in permanent magnet motor based on the coil linewidth range, the coil line height range, and the stator split ratio range includes: The initial design parameters corresponding to each stator split ratio in the stator split ratio range are determined, and the target parameters in the stator split ratio range are determined based on the coil linewidth range and the coil lineheight range, according to the initial design parameters corresponding to each stator split ratio. Finite element simulation is performed based on the target parameters, and the stator crack ratio is optimized based on the simulation results to obtain the target crack ratio in the target stator parameters. The stator tooth width and stator yoke thickness are optimized based on the target split ratio to obtain the target tooth width and target yoke thickness in the target stator parameters.

5. The design optimization method for the built-in permanent magnet motor according to claim 1, characterized in that, The initial rotor parameters include a first target angle, a second target angle, a magnetic bridge width, a minimum spacing between permanent magnets, and a magnetic bridge spacing; wherein, the first target angle is the included angle between the V-shaped permanent magnets in the built-in permanent magnet motor, and the second target angle is the angle occupied by each permanent magnet in the rotor of the built-in permanent magnet motor.

6. The design optimization method for the built-in permanent magnet motor according to claim 5, characterized in that, The process of keeping the target stator parameters constant and executing second parameter optimization logic to optimize the initial rotor parameters using the second preset constraint conditions includes: The target stator parameters are kept constant, and the corresponding permanent magnet size is determined based on the second preset constraint condition. The initial rotor parameters are optimized based on the permanent magnet dimensions to obtain the target rotor parameters.

7. The design optimization method for an embedded permanent magnet motor according to any one of claims 1 to 6, characterized in that, The simulation based on space vector pulse width modulation (SPWM) technology, and based on the target stator parameters and the target rotor parameters, is used to obtain corresponding simulation results. Based on these simulation results, the target design parameters of the built-in permanent magnet motor are determined, including: The three-phase current at a preset frequency is determined based on space vector pulse width modulation simulation technology; Based on the three-phase current, the target stator parameters, and the target rotor parameters, simulations were performed to obtain the loss data of the built-in permanent magnet motor. The target design parameters of the built-in permanent magnet motor are determined based on the loss data and the preset rotor temperature rise.

8. A design optimization device for a built-in permanent magnet motor, characterized in that, include: An initial parameter determination module is used to determine the preset rated parameters of the built-in permanent magnet motor, and to determine the initial design parameters of the built-in permanent magnet motor based on the preset rated parameters using preset electromagnetic theory formulas; the initial design parameters include initial stator parameters and initial rotor parameters; The parameter range determination module is used to determine a first numerical range of the initial stator parameters and a second numerical range of the initial rotor parameters, and to construct a first preset constraint condition based on the first numerical range and a second preset constraint condition based on the second numerical range. The constraints are used to ensure that the parameter values ​​of each of the initial design parameters do not exceed the corresponding numerical range. The first parameter optimization module is used to execute the first parameter optimization logic to optimize the initial stator parameters using the first preset constraint conditions to obtain the target stator parameters; The second parameter optimization module is used to control the target stator parameters to remain unchanged and execute the second parameter optimization logic to optimize the initial rotor parameters using the second preset constraint conditions to obtain the target rotor parameters; The target parameter determination module is used to perform simulations based on space vector pulse width modulation simulation technology, based on the target stator parameters and the target rotor parameters, to obtain the corresponding simulation results, and to determine the target design parameters of the built-in permanent magnet motor based on the simulation results.

9. An electronic device, characterized in that, The electronic device includes a processor and a memory; wherein the memory is used to store a computer program, which is loaded and executed by the processor to implement the design optimization method for the built-in permanent magnet motor as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, Used to store a computer program, which, when executed by a processor, implements the design optimization method for an embedded permanent magnet motor as described in any one of claims 1 to 7.

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