Application of Particle Swarm Optimization Combined With Response Surface Methodology to Transverse Flux Permanent Magnet Motor Optimization

As a result of the 3-D magnetic field and complex structure, existing motor design programs are not suitable for the transverse flux permanent magnet motor (TFPMM). Hence, a method combining particle swarm optimization (PSO) algorithm and response surface methodology (RSM) is proposed to optimize a TFPMM. The optimization aims to maximize the no-load electromotive force (EMF) to get higher torque density in the same volume of the motor. First, central composite design method is adopted for experiments on geometrical design variables. Next, the finite-element method is utilized for simulations to determine the coefficients of the second-order analytical model for the RSM. The optimal solution of the model is then obtained by MATLAB PSO toolbox. Finally, we compare the optimized model with a prototype owning the same volume. The results show that with optimization, the no-load back EMF is improved by 10%, so is the output torque, which illustrates the effectiveness of the optimization method.