CQICO and Multiobjective Thermal Optimization for High-Speed PM Generator

Xiaochen Zhang; Weili Li; Chris Gerada; He Zhang; Jing Li; Michael Galea; David Gerada; Junci Cao

doi:10.1109/TMAG.2017.2658187

CQICO and Multiobjective Thermal Optimization for High-Speed PM Generator

Xiaochen Zhang, Weili Li, Chris Gerada, He Zhang, Jing Li, Michael Galea, David Gerada, Junci Cao

Research output: Journal Publication › Article › peer-review

12 Citations (Scopus)

Abstract

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.

Original language	English
Article number	7833042
Journal	IEEE Transactions on Magnetics
Volume	53
Issue number	6
DOIs	https://doi.org/10.1109/TMAG.2017.2658187
Publication status	Published - Jun 2017

Keywords

Continuous quantum immune clonal optimization (CQICO)
fluid-thermal
groove
high-speed permanent-magnet generator (HSPMG)
optimization

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Electrical and Electronic Engineering

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10.1109/TMAG.2017.2658187

Cite this

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title = "CQICO and Multiobjective Thermal Optimization for High-Speed PM Generator",

abstract = "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.",

keywords = "Continuous quantum immune clonal optimization (CQICO), fluid-thermal, groove, high-speed permanent-magnet generator (HSPMG), optimization",

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journal = "IEEE Transactions on Magnetics",

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T1 - CQICO and Multiobjective Thermal Optimization for High-Speed PM Generator

AU - Zhang, Xiaochen

AU - Li, Weili

AU - Gerada, Chris

AU - Zhang, He

AU - Li, Jing

AU - Galea, Michael

AU - Gerada, David

AU - Cao, Junci

PY - 2017/6

Y1 - 2017/6

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AB - 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.

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CQICO and Multiobjective Thermal Optimization for High-Speed PM Generator

Abstract

Keywords

ASJC Scopus subject areas

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