Driving Cycle Design Optimization of Less-Rare-Earth PM Motor Using Dimension Reduction Method

Abstract

In this paper, a driving cycle design optimization approach using the dimension reduction method is proposed for a less-rare-earth permanent magnet (LRE-PM) motor. In order to improve the efficiency of driving cycle optimization, the k-means clustering method, sensitivity analysis, and principal component analysis are utilized to reduce the dimensions of operating points, design parameters, and optimization objectives respectively. Furthermore, based on multi-objective genetic algorithm, improved motor performances of the whole driving cycle can be realized, including relatively high output torque, low torque ripple, low motor loss, and high demagnetization withstand capability. In addition, motor performances over the driving cycle before and after optimization are compared in detail. Finally, a prototype motor is built and tested. Both simulation and experimental results indicate that motor performances can be improved efficiently and comprehensively, which provides a potential research path for high-efficiency driving cycle optimization.