This paper presents a novel topology optimization method for electrical machines, in which a Quadratic Unconstrained Binary Optimization type (QUBO-type) response surface is constructed using analytical data obtained offline. Moreover, quantum annealing is utilized to enhance the convergence of the optimization. Since the proposed method facilitates reduction in the number of inferior solutions in the optimization, convergence can be improved. The method is applied to an optimization problem of a magnetic head to verify basic operation of quantum annealing. Furthermore, the rotor of an interior permanent magnet motor (IPM motor) is optimized using the proposed method. The numerical results confirmed that the proposed method can enhance convergence of optimization without increasing computational costs.
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