@inproceedings{2202296f9cff4d27af3e69310276ed33,
title = "Efficiency Optimization Control of PMSM Based on a Novel LDW\_PSO Over Wide Speed Range",
abstract = "In order to increase the efficiency of permanent magnet synchronous motor (PMSM) under flexible operating mode, this article presents a novel linear decreasing inertia weight particle swarm optimization (LDWPSO) to search for the optimal efficiency point. The equivalent circuit model and loss analysis are provided to figure out the initial value and boundary of the particle swarm, with the inertia weight adjust from the speed error. Therefore, the global search and local search capabilities of PSO shall be balanced. it can effectively improve the accuracy and rate of the optimization progress. A simulation work was carried out to compare the performance of search controller based on LDWPSO with that of traditional search controller based on gradient descent algorithm. The result shows that the LDWPSO based strategy performs better over a wide speed range, with higher efficiency and faster rate of convergence.",
keywords = "Efficiency optimization, Linear decreasing inertia weight particle swarm optimization (LDWPSO), Permanent magnet synchronous motor (PMSM), Wide speed range",
author = "Chong Zhou and Kun Mao",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 7th International Conference on Computing, Control and Industrial Engineering, CCIE 2023 ; Conference date: 25-02-2023 Through 26-02-2023",
year = "2023",
doi = "10.1007/978-981-99-2730-2\_9",
language = "英语",
isbn = "9789819927296",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "79--85",
editor = "\{S. Shmaliy\}, Yuriy and Anand Nayyar",
booktitle = "7th International Conference on Computing, Control and Industrial Engineering, CCIE 2023 - Advances in Computing, Control and Industrial Engineering VII",
address = "德国",
}