Surrogate Model‐Based Optimisation Design and Rotor Stress Analysis of High‐Speed Permanent Magnet Motor

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ABSTRACT To address the challenges of high‐dimensional design variables, strong non‐linearity, and high computational costs in high‐speed permanent magnet synchronous motors (HSPMSMs), this paper proposes a comprehensive optimal design methodology. First, a high‐precision Kriging surrogate model is constructed to replace the Finite Element Model (FEM), and its accuracy is validated using the multiple correlation coefficient ( R 2 ) and the root mean square error (RMSE). Subsequently, to avoid the local optimum problem of particle swarm optimisation (PSO), an improved particle swarm optimisation (IPSO) is developed, which combines an exponentially decreasing inertia weight with asynchronous learning factors to enhance global search capability. The proposed IPSO is then utilised to optimise the motor. Subsequently, to address the mechanical strength constraints, rotor strength is evaluated through analytical calculations and FEM. Consequently, a multi‐layer sleeve design is studied to improve the low utilisation of the single‐layer sleeve, including its thickness distribution and the number of layers. Finally, the optimal solution is verified by testing on a 100 kW, 20,000 rpm HSPMSM prototype. This paper can be used as a valuable reference for the optimal design of HSPMSM.

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