Investigation of an Optimal Multistage Fast Charging Strategy for Li-ion Batteries
碩士 === 龍華科技大學 === 電機工程系碩士班 === 100 === Nowadays, commercial lithium-ion batteries are playing important roles to supply power for mobile phones, laptop computers, and other electronics. In order to maximize the performance of lithium–ion batteries, a strategy which contain advanced rapid charging pa...
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ndltd-TW-100LHU054420132015-10-13T21:50:44Z http://ndltd.ncl.edu.tw/handle/73376884144081451491 Investigation of an Optimal Multistage Fast Charging Strategy for Li-ion Batteries 最佳化多階段鋰電池快速充電策略之研究 Meng-Chang Tsai 蔡孟昌 碩士 龍華科技大學 電機工程系碩士班 100 Nowadays, commercial lithium-ion batteries are playing important roles to supply power for mobile phones, laptop computers, and other electronics. In order to maximize the performance of lithium–ion batteries, a strategy which contain advanced rapid charging pattern and improve battery cycle life is required. In this thesis, a Particle-Swarm-Optimization (PSO)-based algorithm is presented, and the evaluation of an optimal five-stage fast charging strategy is judged from the Fuzzy controller, the best charging current of each part are founded by using PSO. By using WBCS3000 which is from WonATech company to track and record the data of the battery when it is on charging process. The proposed PSO-based algorithm can be integrated into a commercially available battery tester to search for the optimal rapid charging pattern. The problem formulation, implementation procedure, and parameter setting method are described and explained in detail. Experimental results show that the obtained rapid charging pattern is capable of charging the batteries higher than 90% available capacity within 51 minutes. And also increase cycle life and make the charging process be more effective than the conventional constant current–constant voltage (CC-CV) method. Shun-Chung Wang 王順忠 2012 學位論文 ; thesis 64 zh-TW |
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碩士 === 龍華科技大學 === 電機工程系碩士班 === 100 === Nowadays, commercial lithium-ion batteries are playing important roles to supply power for mobile phones, laptop computers, and other electronics. In order to maximize the performance of lithium–ion batteries, a strategy which contain advanced rapid charging pattern and improve battery cycle life is required. In this thesis, a Particle-Swarm-Optimization (PSO)-based algorithm is presented, and the evaluation of an optimal five-stage fast charging strategy is judged from the Fuzzy controller, the best charging current of each part are founded by using PSO. By using WBCS3000 which is from WonATech company to track and record the data of the battery when it is on charging process. The proposed PSO-based algorithm can be integrated into a commercially available battery tester to search for the optimal rapid charging pattern. The problem formulation, implementation procedure, and parameter setting method are described and explained in detail. Experimental results show that the obtained rapid charging pattern is capable of charging the batteries higher than 90% available capacity within 51 minutes. And also increase cycle life and make the charging process be more effective than the conventional constant current–constant voltage (CC-CV) method.
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author2 |
Shun-Chung Wang |
author_facet |
Shun-Chung Wang Meng-Chang Tsai 蔡孟昌 |
author |
Meng-Chang Tsai 蔡孟昌 |
spellingShingle |
Meng-Chang Tsai 蔡孟昌 Investigation of an Optimal Multistage Fast Charging Strategy for Li-ion Batteries |
author_sort |
Meng-Chang Tsai |
title |
Investigation of an Optimal Multistage Fast Charging Strategy for Li-ion Batteries |
title_short |
Investigation of an Optimal Multistage Fast Charging Strategy for Li-ion Batteries |
title_full |
Investigation of an Optimal Multistage Fast Charging Strategy for Li-ion Batteries |
title_fullStr |
Investigation of an Optimal Multistage Fast Charging Strategy for Li-ion Batteries |
title_full_unstemmed |
Investigation of an Optimal Multistage Fast Charging Strategy for Li-ion Batteries |
title_sort |
investigation of an optimal multistage fast charging strategy for li-ion batteries |
publishDate |
2012 |
url |
http://ndltd.ncl.edu.tw/handle/73376884144081451491 |
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