Enhanced Raccoon Optimization Algorithm for PMSM Electrical Parameter Identification

Zhihong Hu, Jihao Zhan, Zelan Li, Xiangqing Hou, Zhiang Fu and Xiaoliang Yang ()
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Zhihong Hu: College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China
Jihao Zhan: College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China
Zelan Li: School of Wind Energy Engineering, Hunan Electrical College of Technology, Xiangtan 411101, China
Xiangqing Hou: School of Elevator Engineering, Hunan Electrical College of Technology, Xiangtan 411101, China
Zhiang Fu: College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China
Xiaoliang Yang: College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China

Energies, 2025, vol. 18, issue 4, 1-16

Abstract: This article proposes an improved algorithm for the parameter identification of permanent magnet synchronous motors (PMSMs). An enhanced raccoon optimization algorithm (EROA) was formed by combining the raccoon optimization algorithm (ROA) with the adaptive exploration radius, raccoon-washing-food-inspired, and escaping-predator strategies. First, using some of the functions in IEEE CEC2015, the EROA solution has a large improvement in convergence speed and solution accuracy compared with other algorithms. Second, the EROA solution is more stable under the same conditions, as demonstrated by MATLAB parameter identification simulation. Finally, EROA is applied to motor parameter identification through motor control experiments.

Keywords: PMSM; parameter identification; ROA improvement (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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