A New Surrogate-assisted Robust Multi-objective Optimization Algorithm for an Electrical Machine Design

For a multi-objective optimization problem applied to the electric machine design, a new surrogate-assisted robust algorithm is proposed in this research. The proposed algorithm can find a robust and well-distributed Pareto front set rapidly and precisely for robust nondominated solutions using a surrogate model and an uncertainty consideration with a worst-case scenario. The outstanding performances of the proposed algorithm are verified by test functions. Furthermore, through the application of the optimal design process of a surface-mounted permanent magnet synchronous motor for an electric bicycle, the feasibility of this algorithm is verified.

[1]  Sang-Yong Jung,et al.  Minimization of a Cogging Torque for an Interior Permanent Magnet Synchronous Machine using a Novel Hybrid Optimization Algorithm , 2014 .

[2]  Sang-Yong Jung,et al.  Optimal Design of an Axial Flux Permanent Magnet Synchronous Motor for the Electric Bicycle , 2016, IEEE Transactions on Magnetics.

[3]  Changliang Xia,et al.  Torque Ripple Minimization of PMSM Using Parameter Optimization Based Iterative Learning Control , 2016 .

[4]  Sang-Yong Jung,et al.  A Novel Sequential-Stage Optimization Strategy for an Interior Permanent Magnet Synchronous Generator Design , 2018, IEEE Transactions on Industrial Electronics.

[5]  V. Kamaraj,et al.  Data Interpolation and Design Optimisation of Brushless DC Motor Using Generalized Regression Neural Network , 2015 .

[6]  Din-Yuen Chan,et al.  A Reinforcement-Learning-Based Assisted Power Management With QoR Provisioning for Human–Electric Hybrid Bicycle , 2012, IEEE Transactions on Industrial Electronics.

[7]  Seungjae Min,et al.  Optimal Rotor Design of IPM Motor for Improving Torque Performance Considering Thermal Demagnetization of Magnet , 2015, IEEE Transactions on Magnetics.

[8]  Sang-Yong Jung,et al.  Optimal Design of an Interior Permanent Magnet Synchronous Motor by Using a New Surrogate-Assisted Multi-Objective Optimization , 2015, IEEE Transactions on Magnetics.

[9]  C. Magele,et al.  Managing uncertainties in electromagnetic design problems with robust optimization , 2004, IEEE Transactions on Magnetics.

[10]  P. Di Barba,et al.  Multi-Objective Pareto Optimization of Electromagnetic Devices Exploiting Kriging With Lipschitzian Optimized Expected Improvement , 2018, IEEE Transactions on Magnetics.

[11]  Lin Liu,et al.  A Novel Method of Reducing the Cogging Torque in SPM Machine with Segmented Stator , 2017 .

[12]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[13]  Carlos A. Coello Coello,et al.  Handling multiple objectives with particle swarm optimization , 2004, IEEE Transactions on Evolutionary Computation.

[14]  Jean-Louis Coulomb,et al.  A Surrogate Genetic Programming Based Model to Facilitate Robust Multi-Objective Optimization: A Case Study in Magnetostatics , 2013, IEEE Transactions on Magnetics.

[15]  B. X. Du,et al.  Dynamic Behavior of Magnetostriction-Induced Vibration and Noise of Amorphous Alloy Cores , 2015, IEEE Transactions on Magnetics.

[16]  Ziyan Ren,et al.  Utilizing Kriging Surrogate Models for Multi-Objective Robust Optimization of Electromagnetic Devices , 2014, IEEE Transactions on Magnetics.

[17]  Sukjin Choi,et al.  A Study on the Design of Full-LTS 18-GHz ECR Ion Source for Heavy Ion Accelerator , 2016, IEEE Transactions on Applied Superconductivity.

[18]  C. Koh,et al.  An Adaptive Optimization Algorithm Based on Kriging Interpolation with Spherical Model and its Application to Optimal Design of Switched Reluctance Motor , 2014 .

[19]  Yong-Jae Kim,et al.  Multiobjective Optimization Design of Small-Scale Wind Power Generator With Outer Rotor Based on Box–Behnken Design , 2016, IEEE Transactions on Applied Superconductivity.

[20]  Lie-Tong Yan,et al.  In-wheel permanent-magnet brushless DC motor drive for an electric bicycle , 2002 .

[21]  Sang-Yong Jung,et al.  A Novel Surrogate-Assisted Multi-Objective Optimization Algorithm for an Electromagnetic Machine Design , 2015, IEEE Transactions on Magnetics.

[22]  Bernhard Sendhoff,et al.  Generalizing Surrogate-Assisted Evolutionary Computation , 2010, IEEE Transactions on Evolutionary Computation.

[23]  Gyu-Hong Kang,et al.  Drive System Design for a Permanent Magnet Motor with Independent Excitation Winding for an Electric Bicycle , 2010 .