Multi-objective optimization of two-stage thermo-electric cooler using differential evolution: MO optimization of TEC using DE
In this chapter, the technical issues of two-stage TEC were discussed. After that, a new method of optimizing the dimension of TECs using differential evolution to maximize the cooling rate and coefficient of performance was proposed. A input current to hot side and cold side of and the number ratio...
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| Main Authors: | , , , |
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| Format: | Book |
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IGI Global
2015
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84958102760&doi=10.4018%2f978-1-4666-8823-0.ch004&partnerID=40&md5=8c63fa8761cf55001301e2678c9f6558 http://eprints.utp.edu.my/31537/ |
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| Summary: | In this chapter, the technical issues of two-stage TEC were discussed. After that, a new method of optimizing the dimension of TECs using differential evolution to maximize the cooling rate and coefficient of performance was proposed. A input current to hot side and cold side of and the number ratio between the hot stage and cold stage are searched the optima solutions. Thermal resistance is taken into consideration. The results of optimization obtained by using differential evolution were validated by comparing with those obtained by using genetic algorithm and show better performance in terms of stability, computational efficiency, robustness. This work revealed that differential evolution more stable than genetic algorithm and the Pareto front obtained from multi-objective optimization balances the important role between cooling rate and coefficient of performance. © 2016 by IGI Global. All rights reserved. |
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