This article presents a general framework for a multiobjective design optimization of permanent magnet motors based on a drive cycle using finite element (FE) simulation. The aim is to develop an optimization algorithm with the accuracy of FEs but relatively much faster than a complete optimization procedure using finite element simulation. Optimization for a number of designs considering the drive cycle is a very large problem and doing it with FE simulation becomes unreasonable soon as the number of designs increases. This problem is handled by splitting the process into smaller processes of determining feasible designs at each step including designs constraints. The algorithm is highly configurable and works by reducing the search space at each step, thereby the information provided at the end of each step is very useful for specifying additional constraints for the next step or rerun of current step. Given all the electrical, mechanical, and thermal constraints, the algorithm provides either a final optimal design satisfying all the specifications or the best design that satisfies all the constraints. In this article, a surface-mounted permanent magnet motor is considered as an example for design optimization to demonstrate the workflow of this semi-automatic optimization algorithm.
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