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In this paper, a new surrogate assisted multi-objective optimization algorithm is presented to optimize an interior permanent magnet synchronous motor (IPMSM) design for fuel cell electric vehicle. The proposed algorithm is a multi-objective algorithm (MOO) that can both maximize the efficiency and torque amplitude and minimize the torque ripple to improve the power transmission efficiency, noise,...
Stochastic optimization of computationally expensive problems is a relatively new field of research in evolutionary computation (EC). At present, few EC works have been published to handle problems plagued with constraints that are expensive to compute. This paper presents a surrogate-assisted memetic co-evolutionary framework to tackle both facets of practical problems, i.e. the optimization problems...
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