Multi-Objective Optimization Design of an Axial-Flux Permanent Magnet Flywheel Machine Using Fuzzy Inference Taguchi Method

This is the authors' abstract. We don't add key points for this paper.

The Taguchi method is an efficient method for machine optimization design. Unfortunately, the conventional Taguchi method is hard to obtain a complete set of nondominated solutions due to the restriction of the objective quantity. To alleviate the problem, this paper describes a fuzzy inference Taguchi method, which introduces the fuzzy inference system to translate the multiple optimization targets to a single target based on orthogonal design of the experiment established by the Taguchi method for obtaining the complete set of nondominated solutions. The proposed approach is applied to the optimization design for an axial-flux permanent magnet flywheel machine. After the optimal selection analysis, the best combination of the machine structural parameters is obtained. By comparing the optimization results of the proposed method with those of the conventional Taguchi method, the superiority and validity of the proposed method are certified.