@article { , title = {CQICO and multiobjective thermal optimization for high-speed PM generator}, abstract = {This paper proposes a novel Continuous Quantum Immune Clonal Optimization (CQICO) algorithm for thermal optimization on an 117kW high speed permanent magnet generator (HSPMG). The proposed algorithm mixes the Quantum Computation into the Immune Cloning Algorithm and causes better population diversity, higher global searching ability, and faster convergence which approved by simulation results. Then, the improved algorithm is applied to seek an optimized slot groove and improve HSPMG thermal performance, in which the 3-D fluid-thermal coupling analyses are processed with a multi-objective optimal group composed of the highest temperature and the temperature difference. Both the proposed algorithm and the obtained conclusions are of significances in the design and optimization of the cooling system in electric machines.}, doi = {10.1109/TMAG.2017.2658187}, eissn = {0018-9464}, issn = {0018-9464}, issue = {6}, journal = {IEEE Transactions on Magnetics}, note = { School:C-Eng,}, publicationstatus = {Published}, publisher = {Institute of Electrical and Electronics Engineers}, url = {https://nottingham-repository.worktribe.com/output/839068}, volume = {53}, keyword = {CQICO, HSPMG, Fluid-thermal, Groove, Optimization}, year = {2017}, author = {Zhang, Xiaochen and Li, Weili and Gerada, C. and Zhang, He and Li, Jing and Galea, Michael and Gerada, David and Cao, Junci} }