This paper proposes a novel Continuous Quantum Immune Clonal Optimization algorithm for thermal optimization on a 117 kW 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 is approved by simulation results. Then, the improved algorithm is applied to seek an optimized slot groove and improve HSPMG thermal performance, where the 3-D fluid-thermal coupling analyses are processed with a multiobjective optimal group composed of the highest temperature and 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.
|Journal||IEEE Transactions on Magnetics|
|Publication status||Published - Jun 2017|
- Continuous quantum immune clonal optimization (CQICO)
- high-speed permanent-magnet generator (HSPMG)
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Electrical and Electronic Engineering