1 results about "Central composite design" patented technology

This invention discloses a multi-objective optimization method for motors that integrates neural networks and NSGA-III, relating to the fields of motor body design optimization and neural learning technology. The method first clarifies the optimization objectives and design variable constraints of maximizing average torque, efficiency, and minimizing torque ripple. Samples are collected and preprocessed through central composite design and finite element simulation. An FNN-CNN hybrid mapping model is constructed, simultaneously extracting local and global features, and establishing a high-precision mapping relationship with a MAE less than 3% as the training termination condition. Based on NSGA-III, θ dominance relations, density indices, and FC functions are introduced to optimize Nadir point estimation and genetic operations, achieving multi-objective collaborative optimization. Finally, the optimization effect is verified through finite element simulation. This invention improves mapping accuracy and the uniformity of the optimized solution distribution, has a faster convergence speed, and strong robustness, making it applicable to various permanent magnet motors and effectively solving the problems of inaccurate modeling and inefficient convergence in traditional methods.