Abstract
This paper investigates a nonlinear modeling optimization of 12s/8p surface-mounted permanent magnet synchronous machines (SMPMSM) with a radial magnetization pattern. The modeling is based on subdomain model (SDM) computation, where the analytical models are developed to predict the electromagnetic (EM) performances, such as, average EM torque and EM torque ripple in PM machines. A genetic algorithm is applied to the proposed model in order to search for the optimal solutions. The objective function of the optimizations is obtaining a higher average EM torque and achieving the minimum EM torque ripple. The data, viz, and the average EM torque and its ripples predicted by SDM are employed in regression analysis in order to find the model of best fit. After that, the most suitable fit of the computing equation is selected. The preliminary and optimal designs of 12s/8p PM motors are also compared in terms of parameters and motor performance. As a result, the regression model and GA framework has reduced the use of magnet materials and the EM torque ripple of the SMPMSM, making it ideal for use in an electric car. Lastly, the proposed model can determine the appropriate configuration design parameters for SMPMSM in order to achieve the best motor performance.
Highlights
In recent years, electric vehicles (EVs) have been acknowledged as the alternatives to fuel vehicles [1]
Having a higher electromagnetic (EM) torque ripple influences the PM motor performances, which leads to greater vibrations and noise [3]
A design optimization method is proposed to optimize the motor performance in order to obtain the suitable design parameters. Numerical methods such as the finite element (FE) technique are commonly used to evaluate the performances of PM machines [4]; this method requires excessive computation time
Summary
Electric vehicles (EVs) have been acknowledged as the alternatives to fuel vehicles [1]. Electromagnetic performances are becoming more crucial in the design of PM machines in order to increase the dependability and operational resilience of EVs. The structural parameters of PM machines have a significant influence on electromagnetic motor performance, such as average electromagnetic torque and torque ripple. A design optimization method is proposed to optimize the motor performance in order to obtain the suitable design parameters. Numerical methods such as the finite element (FE) technique are commonly used to evaluate the performances of PM machines [4]; this method requires excessive computation time. The main contribution of this paper is to design the optimum setting framework in a manner with stochastic optimization algorithms, in order to evaluate the optimum electromagnetic performances that can provide the optimal solutions.
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