Work

Multi-Objective Optimization of a Modular Unequal Tooth-Shoe PMLSM via an ARD-Kriging Surrogate-Assisted Framework

Year: 2026

Type: article

Abstract: This paper presents a novel dual-module Permanent Magnet Linear Synchronous Motor (PMLSM) featuring an unequal tooth-shoe topology, alongside a highly efficient surrogate-assisted framework to maximize average thrust and minimize thrust ripple. To overcome the computational bottleneck of expensive Finite Element Analysis (FEA), we propose a Constraint-Preserving Maximin Latin Hypercube Design (CP-MmLHD) coupled with an ARD-Kriging model and the Expected Hypervolume Improvement (EHVI) criterion. This closed-loop framework expertly handles strict geometric constraints and anisotropic parameter sensitivities. Within a strict budget of only 150 FEA evaluations, the framework successfully identifies a high-quality Pareto front. Notably, a representative optimal design reduces thrust ripple by over 80% without compromising average thrust. Furthermore, comparative experiments demonstrate superior computational efficiency over conventional algorithms, while multi-run statistical benchmarking and stochastic Monte Carlo analysis rigorously confirm the framework’s algorithmic robustness and manufacturing reliability.

Source: Applied Sciences

DOI: 10.3390/app16073218

Authors: Cheng Fang, Liang Guo, Jiawei Jiang, Bochen Wang, Wenqi Lu

Institution: Zhejiang Sci-Tech University

Language: English

Topic: Electric Motor Design and Analysis

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,896