Optimal design of a short primary double‐sided linear induction motor based on derived Quasi‐3D equivalent circuit model using an improved differential evolution. Issue 12 (8th August 2022)

• Record Type: Journal Article
• Authors: Wang, Hanming; Zhao, Jinghong; Xue, Jie; Chen, Hansi; Guo, Guoqiang; Xiong, Yiyong; Yan, Sinian
• Is Part Of: IET electric power applications. Volume 16:Issue 12(2022)
• Page Start: 1521
• Page End: 1541
• Publication Date: 2022-08-08
• Subjects: Electric power -- Periodicals; Electric power systems -- Periodicals; 621.305
• DOI: 10.1049/elp2.12238
• Languages: English
• ISSNs: 1751-8660

Abstract

Abstract: Due to its simple construction, the linear induction motor (LIM) provides a linear driving force without any intermediate motion translation system. LIMs are widely used in various industrial applications, including maglev rail transit and the national defense industry. However, LIMs are affected by the end effect and suffer from problems such as low efficiencies and low power factors. To make improvements, in this paper, an ensemble multi‐objective optimal design method for a short primary double‐sided linear induction motor (SP‐DLIM) is proposed. First, a simplified Quasi‐3D equivalent circuit model (ECM) for an SP‐DLIM applicable to the model in this paper is derived. The 3‐D transient finite element method and an experimental prototype are utilised to prove that the derived ECM is accurate enough to solve the SP‐DLIM optimisation problem. Second, an ensemble multi‐objective optimal design method of SP‐DLIM is presented, with proposed design constraints and four different optimisation problems. Then, an improved differential evolutionary (IDE) algorithm is proposed to optimise the efficiency, power factor, and tooth weight of the motor. The three‐dimensional time‐stepping finite element method is utilised to verify the validity of the optimisation method. Further, a comparison of the results suggests that the IDE yields the best performance to those of other advanced heuristic algorithms.