Desİgn的永磁同步电机采用了electrİc vehİcles wİth的帮助下的partİcle群algorİthm和ansys-maxwell

Yildirim Özüpak, M. Çınar
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引用次数: 0

摘要

性能和效率是电动机中最重要的参数之一。对发动机的改进不仅提高了发动机的性能,而且还影响了生产成本。永磁同步电机(PMSM)是一种广泛应用于电动汽车的电机,具有转矩密度高、效率高、易于生产等优点。在这项研究中,110kw(可调速永磁同步电机)AS-PMSM设计用于电动汽车应用。将ANSYS-Maxwell和粒子群优化(PSO)算法的结果与优化设计的计算结果与实测数据进行了比较。在设计研究中,采用了理论计算、粒子群算法和基于ANSYS-Maxwell软件的有限元方法。在此基础上,进行了发动机的计算机辅助设计。首先,确定了发动机的基本设计和性能指标。利用ANSYS-Maxwell软件对电机的转矩脉动、铁损、效率和电磁分析等参数进行了分析和优化。然后对电机进行了电学、磁学和性能分析。详细研究了所采用的方法对发动机性能的影响。在发动机性能研究中,效率值是在各种工况下确定的。通过将ANSYS结果与粒子群算法结果进行比较,验证了改进研究的有效性和设计研究的验证性。分析结果表明,所设计的电机满足预期功率值和设计性能标准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DESİGN OF THE PERMANENT MAGNET SYNCHRONOUS MOTOR USED IN ELECTRİC VEHİCLES WİTH THE HELP OF THE PARTİCLE SWARM ALGORİTHM AND ANSYS-MAXWELL
Performance and efficiency are among the most important parameters in electric motors. Improvements to the engine not only increase engine performance, but also affect production costs. Permanent Magnet Synchronous Motor (PMSM) is a motor widely used in electric vehicles with its high torque density, high efficiency and production advantages. In this study, 110 kW (Adjust-Speed Permanent Magnet Synchronous Motor) AS-PMSM was designed for electric vehicle applications. The results of ANSYS-Maxwell and Particle Swarm Optimization (PSO) algorithms and the calculations of the optimized design were compared in line with the obtained data. In the design study, theoretical calculations, PSO algorithm and finite element method (FEM) based ANSYS-Maxwell software were used. Based on these values, the computer aided design of the engine was carried out. First of all, the basic design and performance criteria of the engine were determined. Parameters of the motor such as torque ripple, iron loss, efficiency and electromagnetic analysis were analyzed and optimized with ANSYS-Maxwell. Then, electrical, magnetic and performance analyzes of the motor were made. How the engine performance changes with the methods used has been examined in detail. Efficiency values were determined under various operating conditions in engine performance studies. The validity of the improvement study and the verification of the design study were examined by comparing the ANSYS results with the PSO algorithm results. The analysis results showed that the designed electric motor met the desired power values and design performance criteria.
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