Abstract The aim of this paper was to explore the use of the multiple population genetic algorithm (MPGA) to optimize several parameters of permanent magnet eddy current drivers .At first,on the basis of the magnetic field analysis model,the analytical formulas of key parameters were deduced.By using permanent magnet thickness,pole-arc coefficient and copper plate thickness as variables and taking output torque,rotational inertia and the volume of the driver as optimization goals,this paper proposed a multi-objective optimization function with entropy coefficients and used the multiple population genetic algorithm to optimize parameters structure of the driver.Then,3D finite element analysis (3D-FEA) and experimental results proved the validity and feasibility of the proposed method.The results confirm that compared with other two optimization algorithms,optimization design result by the multiple population genetic algorithm based on the analytical model has better effect on optimization of structural parameters.
Shi Tongyu,Wang Dazhi,Li Zhao. Multi-Objective Optimization Design of PMECD by Multiple Population Genetic Algorithm[J]. Transactions of China Electrotechnical Society, 2016, 31(增刊2): 262-268.
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2016, Vol. 31 
