Variable frequency motor design method and device
By using multi-objective optimization algorithms and partial discharge risk assessment methods, and by iteratively adjusting the motor design optimization constraints, the insulation failure problem of variable frequency motors in high-altitude and low-pressure environments was solved, thereby improving the power density and ensuring the reliability of aviation motors.
Patent Information
- Application Number
- CN202511078821.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-01
- Publication Date
- 2025-10-21
AI Technical Summary
Existing technologies cannot improve the power density of aircraft motors while ensuring the insulation reliability of variable frequency motors. In particular, the risk of partial discharge increases in extreme environments with high altitude and low air pressure, which affects the normal operation of the motors.
By employing a multi-objective optimization algorithm and a partial discharge risk assessment method, the motor design optimization constraints are iteratively adjusted. Combined with thermal aging correction and electrostatic field simulation, the partial discharge initiation voltage is predicted to ensure that the motor design scheme has no risk of insulation failure, and the motor design parameters are ultimately optimized.
While ensuring insulation reliability, the power density of the aircraft motor was significantly improved, the risk of partial discharge was reduced, and the reliability and performance of the motor were enhanced.
Smart Images
Figure CN120822286A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of aviation motor design, and in particular to a variable frequency motor design method and device. Background Art
[0002] Variable-frequency motors are core components in electrified aviation. Insulation failure is a major factor in motor failure, making accurate insulation failure risk assessment crucial for ensuring motor reliability. Partial discharge is the primary cause of insulation failure in variable-frequency motor windings. Extreme operating environments like high altitude and low air pressure increase the risk of partial discharge, posing a threat to the proper functioning of aircraft motors.
[0003] In related technologies, in order to ensure the reliability of motors, "over-engineering" methods are usually adopted, such as using thicker insulation and limiting the maximum operating temperature of the windings, which reduces the performance of the motor and runs counter to the goal of aviation motors to pursue high power density.
[0004] Based on this, there is an urgent need for a variable frequency motor design method that can maximize the power density of aviation motors while ensuring insulation reliability. Summary of the Invention
[0005] The purpose of this application is to provide a variable frequency motor design method and device, which can maximize the power density of aviation motors while ensuring insulation reliability.
[0006] This application provides a variable frequency motor design method, including: Set motor optimization constraints; based on the motor optimization constraints, cyclically execute the motor design optimization strategy until the motor design scheme has no insulation failure risk, and obtain the final motor design scheme; wherein, the motor design optimization strategy includes: a first optimization strategy and a second optimization strategy; the first optimization strategy includes: based on the motor optimization constraints, using a multi-objective optimization algorithm to determine the motor design scheme; the second optimization strategy includes: judging whether the motor design scheme has insulation failure risk, and if the motor design scheme has insulation failure risk, revising the motor optimization constraints.
[0007] Optionally, based on the motor optimization constraints, the motor design optimization strategy is cyclically executed until the motor design scheme has no risk of insulation failure, and the final motor design scheme is obtained, including: taking the relevant design parameters of the motor as optimization variables and the power density of the motor as the optimization target, performing multi-objective optimization based on the multi-objective optimization algorithm, and obtaining the motor design scheme of the current round.
[0008] Optionally, based on the motor optimization constraints, the motor design optimization strategy is cyclically executed until the motor design scheme has no risk of insulation failure, and a final motor design scheme is obtained, including: predicting the maximum temperature of the motor winding based on the current round of motor design scheme, and predicting the partial discharge initiation voltage PDIV based on the maximum temperature, air pressure and humidity of the motor winding to obtain a PDIV prediction result; determining a thermal aging correction coefficient, and correcting the PDIV prediction result based on the thermal aging correction coefficient and the partial discharge safety factor to obtain a corrected PDIV; predicting the inter-turn voltage of the motor, and comparing the inter-turn voltage with the corrected PDIV to obtain a comparison result; if the comparison result indicates that the inter-turn voltage is less than the corrected PDIV, it is determined that the motor design scheme of the current round has no risk of insulation failure, and the motor design scheme of the current round is determined as the final motor design scheme.
[0009] Optionally, based on the motor optimization constraints, the motor design optimization strategy is executed cyclically until the motor design scheme has no insulation failure risk, and a final motor design scheme is obtained, including: if the comparison result indicates that the inter-turn voltage is greater than or equal to the corrected PDIV, then it is determined that the current round of motor design scheme has insulation failure risk, and the motor optimization constraints are corrected to obtain corrected motor optimization constraints; and the next round of motor design scheme optimization is performed based on the corrected motor optimization constraints.
[0010] Optionally, the motor design scheme based on the current round predicts the maximum temperature of the motor winding, and performs a partial discharge inception voltage PDIV prediction based on the maximum temperature, air pressure and humidity of the motor winding to obtain a PDIV prediction result, including: based on the design parameters and actual operating conditions of the motor, using a lumped parameter thermal grid method to predict the winding temperature of the motor to obtain the maximum temperature of the motor winding; based on the electromagnetic wire parameters of the motor, the maximum temperature of the motor winding, air pressure and humidity, using an electrostatic field finite element simulation method to perform a PDIV prediction to obtain the PDIV prediction result.
[0011] Optionally, determining the thermal aging correction coefficient and correcting the PDIV prediction result based on the thermal aging correction coefficient and the partial discharge safety factor to obtain a corrected PDIV includes: determining the thermal aging correction coefficient based on the maximum temperature of the motor winding and the motor life requirement; and correcting the PDIV prediction result based on the thermal aging correction coefficient to obtain a corrected PDIV.
[0012] Optionally, predicting the inter-turn voltage of the motor includes: predicting the inter-turn voltage of the motor based on the drive parameters, electromagnetic wire parameters and winding design of the motor using a transmission line model and a high-frequency equivalent circuit model to obtain the inter-turn voltage of the motor.
[0013] The present application also provides a variable frequency motor design device, comprising: A condition setting module is used to set motor optimization constraints; a motor design module is used to cyclically execute motor design optimization strategies based on the motor optimization constraints until the motor design scheme has no insulation failure risk, thereby obtaining a final motor design scheme; wherein, the motor design optimization strategies include: a first optimization strategy and a second optimization strategy; the first optimization strategy includes: based on the motor optimization constraints, determining the motor design scheme using a multi-objective optimization algorithm; the second optimization strategy includes: judging whether the motor design scheme has an insulation failure risk, and if the motor design scheme has an insulation failure risk, revising the motor optimization constraints.
[0014] Optionally, the motor design module is specifically used to use relevant design parameters of the motor as optimization variables and the power density of the motor as the optimization target, perform multi-objective optimization based on a multi-objective optimization algorithm, and obtain a motor design solution for the current round.
[0015] Optionally, the motor design module is specifically used to predict the maximum temperature of the motor winding based on the current round of motor design scheme, and predict the partial discharge initiation voltage PDIV based on the maximum temperature, air pressure and humidity of the motor winding to obtain a PDIV prediction result; the motor design module is also specifically used to determine the thermal aging correction coefficient, and correct the PDIV prediction result based on the thermal aging correction coefficient and the partial discharge safety factor to obtain a corrected PDIV; the motor design module is also specifically used to predict the inter-turn voltage of the motor, and compare the inter-turn voltage with the corrected PDIV to obtain a comparison result; the motor design module is also specifically used to determine that there is no insulation failure risk in the motor design scheme of the current round if the comparison result indicates that the inter-turn voltage is less than the corrected PDIV, and determine the motor design scheme of the current round as the final motor design scheme.
[0016] Optionally, the motor design module is specifically used to determine that the current round of motor design scheme has an insulation failure risk if the comparison result indicates that the inter-turn voltage is greater than or equal to the corrected PDIV, and to correct the motor optimization constraints to obtain corrected motor optimization constraints; the motor design module is also specifically used to optimize the motor design scheme for the next round based on the corrected motor optimization constraints.
[0017] Optionally, the motor design module is specifically used to predict the winding temperature of the motor based on the design parameters and actual operating conditions of the motor using a lumped parameter thermal grid method to obtain the maximum temperature of the motor winding; the motor design module is also specifically used to perform PDIV prediction based on the electromagnetic wire parameters of the motor, the maximum temperature of the motor winding, air pressure and humidity using an electrostatic field finite element simulation method to obtain the PDIV prediction result.
[0018] Optionally, the motor design module is specifically used to determine the thermal aging correction coefficient based on the maximum temperature of the motor winding and the motor life requirement; the motor design module is also specifically used to correct the PDIV prediction result based on the thermal aging correction coefficient to obtain a corrected PDIV.
[0019] Optionally, the motor design module is specifically used to predict the inter-turn voltage of the motor based on the motor's drive parameters, electromagnetic wire parameters and motor winding design, using a transmission line model and a high-frequency equivalent circuit model to obtain the motor's inter-turn voltage.
[0020] The present application also provides a computer program product, comprising a computer program / instruction, which, when executed by a processor, implements the steps of any of the above-mentioned variable frequency motor design methods.
[0021] The present application also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of any of the above-described variable frequency motor design methods are implemented.
[0022] The present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of any of the above-mentioned variable frequency motor design methods are implemented.
[0023] The variable frequency motor design method and device provided in this application first sets motor optimization constraints; then, based on the motor optimization constraints, cyclically executes motor design optimization strategies until the motor design scheme has no insulation failure risk, thereby obtaining a final motor design scheme; wherein the motor design optimization strategies include: a first optimization strategy and a second optimization strategy; the first optimization strategy includes: determining the motor design scheme based on the motor optimization constraints using a multi-objective optimization algorithm; the second optimization strategy includes: determining whether the motor design scheme has insulation failure risk, and if so, revising the motor optimization constraints. In this way, the power density of the aviation motor can be maximized while ensuring insulation reliability. BRIEF DESCRIPTION OF THE DRAWINGS
[0024] In order to more clearly illustrate the technical solutions in the present application or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.
[0025] Figure 1 It is a structural diagram of the motor near-limit design system provided by this application; Figure 2 This is one of the flow charts of the variable frequency motor design method provided in this application; Figure 3 This is the second flow chart of the variable frequency motor design method provided by this application; Figure 4 It is a flow chart of the partial discharge risk assessment method provided in this application; Figure 5 It is a structural schematic diagram of the variable frequency motor design device provided by this application; Figure 6 It is a structural diagram of the electronic device provided in this application. DETAILED DESCRIPTION
[0026] To make the objectives, technical solutions, and advantages of this application more clear, the technical solutions of this application will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments of this application, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of this application.
[0027] The terms "first," "second," and the like in the specification and claims of this application are used to distinguish similar objects, and are not used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of this application can be implemented in an order other than that illustrated or described herein, and that the objects distinguished by "first," "second," and the like are generally of the same type, and do not limit the number of objects; for example, the first object can be one or more. In addition, the term "and / or" in the specification and claims refers to at least one of the connected objects, and the character " / " generally indicates that the objects connected are in an "or" relationship.
[0028] Excessive redundancy in aircraft motor design can limit power density, while insufficient redundancy (i.e., failure to accurately predict insulation failure risk) can lead to premature insulation failure. To address these technical issues, embodiments of this application provide a motor design method that considers insulation failure risk. Starting from the motor design, this method comprehensively considers the impact of electric drive parameters, motor design parameters, aviation operating conditions, and insulation life requirements under thermal aging to assess partial discharge risk. Based on this, the motor design optimization constraints are continuously adjusted, and multiple rounds of iterative design are performed. Ultimately, while ensuring insulation reliability, the motor power density is maximized, achieving a near-limit design.
[0029] like Figure 1 As shown, a motor near-limit design system based on the variable frequency motor design method in an embodiment of the present application is provided, and the system includes: Motor design requirement input unit: used to input motor design requirements, including torque, speed, etc. Motor design optimization unit: Based on the motor design requirements and optimization constraints, based on the multi-objective optimization tool, carry out motor multi-objective optimization to form the optimal solution. Partial discharge risk assessment unit: Based on the partial discharge risk assessment method proposed in the embodiment of the present application, the partial discharge risk of the optimized motor design is evaluated. Optimization constraint setting unit: In the first round of motor optimization, an optimization constraint is set mainly based on experience for carrying out motor multi-objective optimization. In the subsequent optimization process, the optimization constraints are continuously adjusted according to the output results of the partial discharge risk assessment unit. Final solution output unit: outputs the final motor design solution.
[0030] It should be noted that the motor winding includes multiple insulation systems. The variable frequency motor design method in the embodiment of the present application focuses on the inter-turn insulation of the variable frequency motor winding, which is the most vulnerable part.
[0031] The variable frequency motor design method provided by the embodiment of the present application is described in detail below with reference to the accompanying drawings through specific embodiments and their application scenarios.
[0032] like Figure 2 As shown, an embodiment of the present application provides a variable frequency motor design method, which may include the following steps 201 and 202: Step 201: Set motor optimization constraints.
[0033] For example, before designing a motor, motor optimization constraints can be set based on experience, such as torque ripple, efficiency, maximum winding temperature, and other relevant conditions used to constrain motor design. The motor design solution cannot exceed the constraints of the motor optimization constraints.
[0034] Step 202: Based on the motor optimization constraint conditions, the motor design optimization strategy is cyclically executed until the motor design solution does not have the insulation failure risk, thereby obtaining a final motor design solution.
[0035] Among them, the motor design optimization strategy includes: a first optimization strategy and a second optimization strategy; the first optimization strategy includes: based on the motor optimization constraints, using a multi-objective optimization algorithm to determine the motor design scheme; the second optimization strategy includes: judging whether the motor design scheme has the risk of insulation failure, and if the motor design scheme has the risk of insulation failure, then correcting the motor optimization constraints.
[0036] For example, after obtaining the motor optimization constraint conditions based on experience, the motor design can be performed based on the motor optimization constraint conditions. Specifically, Figure 3 As shown in the figure, the optimization design process mainly includes: performing multi-objective motor optimization based on the motor optimization constraints to obtain a preliminary motor design scheme. Then, based on this motor design scheme, it is determined whether there is a risk of insulation failure. If the motor design scheme does have an insulation failure risk, the motor optimization constraints are revised and a new round of motor design is carried out. Otherwise, it is determined that the motor design scheme meets the design requirements and is selected as the final motor design scheme.
[0037] Specifically, the above step 202, which is the step of obtaining the motor equipment solution for the current round, may further include the following step 202a: Step 202a: Use the relevant design parameters of the motor as optimization variables and the power density of the motor as the optimization target, perform multi-objective optimization based on the multi-objective optimization algorithm, and obtain the motor design solution for the current round.
[0038] For example, common parameters such as motor structural parameters are selected as optimization variables, and the power density of the aviation motor is used as the optimization target. Based on common optimization algorithms (such as multi-objective optimization algorithms such as genetic algorithms), multi-objective motor optimization is carried out to obtain the motor design plan for the current round.
[0039] Specifically, after obtaining the motor design solution for the current round, the above step 202 may further include the following steps 202b, 202c, 202d, and 202e: Step 202b: Based on the current round of motor design solutions, the maximum temperature of the motor winding is predicted, and the partial discharge inception voltage (PDIV) is predicted based on the maximum temperature of the motor winding, air pressure, and humidity to obtain a PDIV prediction result.
[0040] Illustratively, the partial discharge inception voltage (PDIV) refers to the lowest voltage at which partial discharge occurs for the first time in an insulating material under the action of an electric field.
[0041] Specifically, in the above step 202b, the step of predicting the maximum temperature of the motor winding and predicting the partial discharge inception voltage based on the maximum temperature of the motor winding may further include the following steps 202b1 and 202b2: Step 202b1: Based on the design parameters and actual operating conditions of the motor, the winding temperature of the motor is predicted using a lumped parameter thermal grid method to obtain the maximum temperature of the motor winding.
[0042] Step 202b2: Based on the electromagnetic wire parameters of the motor, the maximum temperature of the motor winding, the air pressure and the temperature, a PDIV prediction is performed using an electrostatic field finite element simulation method to obtain the PDIV prediction result.
[0043] For example, Figure 3 As shown in the figure, after obtaining the current motor design, the lumped parameter thermal grid method can be used to predict the maximum winding temperature based on the motor design parameters and actual operating conditions. PDIV prediction is then achieved using electrostatic field finite element simulation, based on the magnet wire parameters, maximum winding temperature, and environmental conditions.
[0044] Step 202c: determine a thermal aging correction factor, and correct the PDIV prediction result based on the thermal aging correction factor and the partial discharge safety factor to obtain a corrected PDIV.
[0045] For example, after the partial discharge inception voltage is predicted, it is necessary to correct the partial discharge inception voltage based on the thermal aging correction coefficient.
[0046] Specifically, the above step 202c may further include the following steps 202c1 and 202c2: Step 202c1: Determine the thermal aging correction coefficient based on the maximum temperature of the motor winding and the motor life requirement.
[0047] Step 202c2: Based on the thermal aging correction coefficient, correct the PDIV prediction result to obtain a corrected partial discharge inception voltage PDIV.
[0048] For example, Figure 3As shown, in this embodiment of the present application, a thermal aging correction factor can be determined based on the maximum temperature of the motor windings and the life requirements of the aircraft motor to correct the partial discharge inception voltage (PDIV) prediction results. It should be noted that while using the thermal aging correction factor to correct the prediction results, the partial discharge inception voltage (PDIV) can also be corrected using the partial discharge safety factor (PD safety factor).
[0049] Step 202d: predict the inter-turn voltage of the motor, and compare the inter-turn voltage with the corrected PDIV to obtain a comparison result.
[0050] For example, after obtaining the corrected partial discharge inception voltage, the predicted motor turn-to-turn voltage can be compared with the partial discharge inception voltage PDIV, and based on the comparison result, it can be determined whether the current round of motor design has the risk of insulation failure.
[0051] Specifically, in the above step 202d, the step of predicting the inter-turn voltage of the motor may further include the following step 202d1: Step 202d1: Based on the drive parameters, electromagnetic wire parameters and winding design of the motor, the inter-turn voltage of the motor is predicted using a transmission line model and a high-frequency equivalent circuit model to obtain the inter-turn voltage of the motor.
[0052] Step 202e: If the comparison result indicates that the turn-to-turn voltage is less than the corrected PDIV, it is determined that the current round of motor design does not have the risk of insulation failure, and the current round of motor design is determined as the final motor design.
[0053] For example, Figure 3 As shown, when the inter-turn voltage V t-t If the value is less than the corrected PDIV, there is no risk of partial discharge in the inter-turn insulation of the motor. At this point, the current round of motor design scheme can be determined as the final motor design scheme.
[0054] Exemplarily, the above step 202 may further include the following steps 202f1 and 202f2: Step 202f1: If the comparison result indicates that the turn-to-turn voltage is greater than or equal to the corrected PDIV, it is determined that the current round of motor design has an insulation failure risk, and the motor optimization constraint conditions are corrected to obtain corrected motor optimization constraint conditions.
[0055] Step 202f2: Optimize the motor design scheme for the next round based on the revised motor optimization constraints.
[0056] For example, Figure 3As shown, when the inter-turn voltage V t-t If the value is greater than or equal to the corrected PDIV, there is a risk of partial discharge in the inter-turn insulation of the motor. At this time, the motor optimization constraints can be corrected, and the next round of motor design optimization can be carried out based on the corrected motor optimization constraints.
[0057] For example, Figure 4 As shown, it is a flow chart of the partial discharge risk assessment method based on motor system parameters in an embodiment of the present application. The partial discharge risk assessment method based on motor system parameters includes the following steps: Step 1: According to the motor design parameters, actual working conditions and ambient temperature, the lumped parameter thermal grid method is applied to predict the maximum temperature of the winding. Step 2: Based on the electromagnetic wire parameters, maximum winding temperature, humidity and air pressure conditions determined during motor design, combined with electrostatic field finite element simulation, PDIV prediction is achieved. Step 3: According to the temperature and aviation motor life requirements, the thermal aging correction factor is determined, and the PDIV prediction results are corrected. Step 4: According to the IEC standard, the predicted PDIV is corrected using the partial discharge safety factor; Step 5: According to the motor drive parameters, electromagnetic wire parameters and winding design, the transmission line model and high-frequency equivalent circuit model are applied to predict the turn-to-turn voltage V t-t Step 6: When the inter-turn voltage V t-t Less than the corrected PDIV, there is no risk of partial discharge in the motor turn-to-turn insulation; when the turn-to-turn voltage V t-t If the value is greater than or equal to the corrected PDIV, there is a risk of partial discharge in the motor inter-turn insulation.
[0058] The variable frequency motor design method provided in an embodiment of the present application first sets motor optimization constraints; then, based on the motor optimization constraints, iteratively executes motor design optimization strategies until the motor design solution has no insulation failure risk, thereby obtaining a final motor design solution; wherein the motor design optimization strategies include: a first optimization strategy and a second optimization strategy; the first optimization strategy includes: determining the motor design solution based on the motor optimization constraints using a multi-objective optimization algorithm; the second optimization strategy includes: determining whether the motor design solution has insulation failure risk, and if so, revising the motor optimization constraints. In this way, the power density of the aviation motor can be increased as much as possible while ensuring insulation reliability.
[0059] It should be noted that the variable frequency motor design method provided in the embodiments of the present application can be executed by a variable frequency motor design device, or a control module in the variable frequency motor design device for executing the variable frequency motor design method. In the embodiments of the present application, the variable frequency motor design device provided in the embodiments of the present application is described by taking the variable frequency motor design device executing the variable frequency motor design method as an example.
[0060] It should be noted that in the embodiments of the present application, the variable frequency motor design methods shown in the above-mentioned figures are each illustrated by way of example in conjunction with one of the figures in the embodiments of the present application. In specific implementations, the variable frequency motor design methods shown in the above-mentioned figures may also be implemented in conjunction with any other combinable figures shown in the above-mentioned embodiments, and will not be further described here.
[0061] The variable frequency motor design device provided in the present application is described below, and the variable frequency motor design method described below and described above can refer to each other.
[0062] Figure 5 This is a schematic diagram of the structure of the variable frequency motor design device provided in the embodiment of the present application, as shown in FIG. Figure 5 As shown, specifically including: The condition setting module 501 is used to set the motor optimization constraints; the motor design module 502 is used to cyclically execute the motor design optimization strategy based on the motor optimization constraints until the motor design scheme has no insulation failure risk and the final motor design scheme is obtained; wherein, the motor design optimization strategy includes: a first optimization strategy and a second optimization strategy; the first optimization strategy includes: based on the motor optimization constraints, using a multi-objective optimization algorithm to determine the motor design scheme; the second optimization strategy includes: judging whether the motor design scheme has an insulation failure risk, and if the motor design scheme has an insulation failure risk, then correcting the motor optimization constraints.
[0063] Optionally, the motor design module 502 is specifically configured to use relevant design parameters of the motor as optimization variables and the power density of the motor as the optimization target, perform multi-objective optimization based on a multi-objective optimization algorithm, and obtain a motor design solution for the current round.
[0064] Optionally, the motor design module 502 is specifically used to predict the maximum temperature of the motor winding based on the current round of motor design scheme, and predict the partial discharge initiation voltage PDIV based on the maximum temperature, air pressure and humidity of the motor winding to obtain a PDIV prediction result; the motor design module 502 is also specifically used to determine the thermal aging correction coefficient, and correct the PDIV prediction result based on the thermal aging correction coefficient and the partial discharge safety factor to obtain a corrected PDIV; the motor design module 502 is also specifically used to predict the inter-turn voltage of the motor, and compare the inter-turn voltage with the corrected PDIV to obtain a comparison result; the motor design module 502 is also specifically used to determine that there is no insulation failure risk in the current round of motor design scheme if the comparison result indicates that the inter-turn voltage is less than the corrected PDIV, and determine the current round of motor design scheme as the final motor design scheme.
[0065] Optionally, the motor design module 502 is specifically used to determine that the current round of motor design scheme has an insulation failure risk if the comparison result indicates that the inter-turn voltage is greater than or equal to the corrected PDIV, and to correct the motor optimization constraints to obtain corrected motor optimization constraints; the motor design module 502 is also specifically used to optimize the motor design scheme for the next round based on the corrected motor optimization constraints.
[0066] Optionally, the motor design module 502 is specifically used to predict the winding temperature of the motor based on the design parameters and actual operating conditions of the motor using a lumped parameter thermal grid method to obtain the maximum temperature of the motor winding; the motor design module 502 is also specifically used to perform PDIV prediction based on the electromagnetic wire parameters of the motor, the maximum temperature of the motor winding, air pressure and temperature using an electrostatic field finite element simulation method to obtain the PDIV prediction result.
[0067] Optionally, the motor design module 502 is specifically used to determine the thermal aging correction coefficient based on the maximum temperature of the motor winding and the motor life requirement; the motor design module 502 is also specifically used to correct the PDIV prediction result based on the thermal aging correction coefficient to obtain a corrected PDIV.
[0068] Optionally, the motor design module 502 is specifically used to predict the inter-turn voltage of the motor based on the motor drive parameters, electromagnetic wire parameters and motor winding design using a transmission line model and a high-frequency equivalent circuit model to obtain the inter-turn voltage of the motor.
[0069] The variable frequency motor design device provided in this application first sets motor optimization constraints; then, based on the motor optimization constraints, it cyclically executes the motor design optimization strategy until the motor design scheme has no insulation failure risk, thereby obtaining the final motor design scheme; wherein, the motor design optimization strategy includes: a first optimization strategy and a second optimization strategy; the first optimization strategy includes: determining the motor design scheme based on the motor optimization constraints using a multi-objective optimization algorithm; the second optimization strategy includes: determining whether the motor design scheme has insulation failure risk, and if so, revising the motor optimization constraints. In this way, the power density of the aviation motor can be increased as much as possible while ensuring insulation reliability.
[0070] Figure 6 An example of a physical structure diagram of an electronic device is shown below. Figure 6As shown, the electronic device may include: a processor 610, a communications interface 620, a memory 630, and a communications bus 640. The processor 610, communications interface 620, and memory 630 communicate with each other via the communications bus 640. The processor 610 can invoke logic instructions stored in the memory 630 to execute a variable-frequency motor design method. The method includes: first, setting motor optimization constraints; then, iteratively executing motor design optimization strategies based on the motor optimization constraints until the motor design eliminates insulation failure risk, thereby obtaining a final motor design. The motor design optimization strategies include: a first optimization strategy and a second optimization strategy. The first optimization strategy includes determining a motor design based on the motor optimization constraints using a multi-objective optimization algorithm; the second optimization strategy includes determining whether the motor design eliminates insulation failure risk and, if so, modifying the motor optimization constraints. This method maximizes the power density of aircraft motors while ensuring insulation reliability.
[0071] In addition, the logical instructions in the above-mentioned memory 630 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present application, or the part that contributes to the existing technology, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program code.
[0072] On the other hand, the present application also provides a computer program product, the computer program product including a computer program stored on a computer-readable storage medium, the computer program including program instructions, when the program instructions are executed by a computer, the computer can execute the variable frequency motor design method provided by the above methods, the method comprising: first, setting motor optimization constraints; then, based on the motor optimization constraints, cyclically executing the motor design optimization strategy until the motor design scheme does not have the risk of insulation failure, and obtaining the final motor design scheme; wherein the motor design optimization strategy includes: a first optimization strategy and a second optimization strategy; the first optimization strategy includes: based on the motor optimization constraints, using a multi-objective optimization algorithm to determine the motor design scheme; the second optimization strategy includes: determining whether the motor design scheme has the risk of insulation failure, and if the motor design scheme has the risk of insulation failure, then modifying the motor optimization constraints. In this way, the power density of the aviation motor can be increased as much as possible while ensuring insulation reliability.
[0073] On the other hand, the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the variable frequency motor design method provided above, the method comprising: first, setting motor optimization constraints; then, based on the motor optimization constraints, cyclically executing the motor design optimization strategy until the motor design scheme does not have the risk of insulation failure, thereby obtaining a final motor design scheme; wherein the motor design optimization strategy comprises: a first optimization strategy and a second optimization strategy; the first optimization strategy comprises: determining the motor design scheme based on the motor optimization constraints using a multi-objective optimization algorithm; the second optimization strategy comprises: determining whether the motor design scheme has the risk of insulation failure, and if the motor design scheme has the risk of insulation failure, then modifying the motor optimization constraints. In this way, the power density of the aviation motor can be increased as much as possible while ensuring insulation reliability.
[0074] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.
[0075] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.
[0076] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.
Claims
1. A variable frequency motor design method, characterized in that: include: Set motor optimization constraints; Based on the motor optimization constraints, the motor design optimization strategy is cyclically executed until the motor design solution has no insulation failure risk, thereby obtaining a final motor design solution; Among them, the motor design optimization strategy includes: a first optimization strategy and a second optimization strategy; the first optimization strategy includes: based on the motor optimization constraints, using a multi-objective optimization algorithm to determine the motor design scheme; the second optimization strategy includes: judging whether the motor design scheme has the risk of insulation failure, and if the motor design scheme has the risk of insulation failure, then correcting the motor optimization constraints.
2. The method according to claim 1, characterized in that The motor design optimization strategy is cyclically executed based on the motor optimization constraint conditions until the motor design solution does not have the risk of insulation failure, thereby obtaining a final motor design solution, including: The relevant design parameters of the motor are used as optimization variables and the power density of the motor is used as the optimization target. Multi-objective optimization is performed based on the multi-objective optimization algorithm to obtain the motor design scheme for the current round.
3. The method according to claim 1, characterized in that The motor design optimization strategy is cyclically executed based on the motor optimization constraint conditions until the motor design solution does not have the risk of insulation failure, thereby obtaining a final motor design solution, including: Based on the current round of motor design solutions, the maximum temperature of the motor winding is predicted, and the partial discharge inception voltage (PDIV) is predicted based on the maximum temperature of the motor winding, air pressure, and humidity to obtain a PDIV prediction result; Determining a thermal aging correction factor, and correcting the PDIV prediction result based on the thermal aging correction factor and a partial discharge safety factor to obtain a corrected PDIV; Predicting an inter-turn voltage of the motor, and comparing the inter-turn voltage with the corrected PDIV to obtain a comparison result; If the comparison result indicates that the turn-to-turn voltage is less than the corrected PDIV, it is determined that the current round of motor design scheme does not have the risk of insulation failure, and the current round of motor design scheme is determined as the final motor design scheme.
4. The method according to claim 3, characterized in that The motor design optimization strategy is cyclically executed based on the motor optimization constraint conditions until the motor design solution does not have the risk of insulation failure, thereby obtaining a final motor design solution, including: If the comparison result indicates that the turn-to-turn voltage is greater than or equal to the corrected PDIV, it is determined that the motor design scheme of the current round has an insulation failure risk, and the motor optimization constraint condition is corrected to obtain the corrected motor optimization constraint condition; The next round of motor design optimization is carried out based on the revised motor optimization constraints.
5. The method according to claim 3, characterized in that The motor design scheme based on the current round predicts the maximum temperature of the motor winding, and the partial discharge inception voltage (PDIV) is predicted based on the maximum temperature of the motor winding, air pressure, and humidity to obtain a PDIV prediction result, including: Based on the design parameters and actual operating conditions of the motor, the motor winding temperature is predicted using a lumped parameter thermal grid method to obtain the maximum temperature of the motor winding; Based on the electromagnetic wire parameters of the motor, the maximum temperature of the motor winding, air pressure and humidity, PDIV prediction is performed using an electrostatic field finite element simulation method to obtain the PDIV prediction result.
6. The method according to claim 3, characterized in that The determining of the thermal aging correction factor and correcting the PDIV prediction result based on the thermal aging correction factor and the partial discharge safety factor to obtain a corrected PDIV includes: Determining the thermal aging correction factor based on the maximum temperature of the motor winding and the motor life requirement; The PDIV prediction result is corrected based on the thermal aging correction factor and the partial discharge safety factor to obtain a corrected PDIV.
7. The method according to claim 3, characterized in that The method of predicting the inter-turn voltage of the motor includes: Based on the motor's drive parameters, electromagnetic wire parameters, and motor winding design, the motor's inter-turn voltage is predicted using a transmission line model and a high-frequency equivalent circuit model to obtain the motor's inter-turn voltage.
8. A variable frequency motor design device, characterized in that: The device comprises: Condition setting module, used to set motor optimization constraint conditions; A motor design module is used to cyclically execute the motor design optimization strategy based on the motor optimization constraints until the motor design solution has no insulation failure risk, thereby obtaining a final motor design solution; Among them, the motor design optimization strategy includes: a first optimization strategy and a second optimization strategy; the first optimization strategy includes: based on the motor optimization constraints, using a multi-objective optimization algorithm to determine the motor design scheme; the second optimization strategy includes: judging whether the motor design scheme has the risk of insulation failure, and if the motor design scheme has the risk of insulation failure, then correcting the motor optimization constraints.
9. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the variable frequency motor design method according to any one of claims 1 to 7 when executing the program.
10. A computer-readable storage medium, characterized in that A computer program is stored thereon, and when the computer program is executed by a processor, the steps of the variable frequency motor design method according to any one of claims 1 to 7 are implemented.