期刊
MATHEMATICAL PROBLEMS IN ENGINEERING
卷 2018, 期 -, 页码 -出版社
HINDAWI LTD
DOI: 10.1155/2018/3793492
关键词
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资金
- National Science and Technology Ministry [2015BAA09B01]
- National Natural Science Foundation of China [51377044]
- Natural Science Foundation of Hebei Province [E2017202284]
- Youth Foundation of Hebei Education Department [QN2017314, QN2017316]
The performance behavior of the lithiwn-ion battery can be simulated by the battery model and thus applied to a variety of practical situations. Although the particle swarm optimization (PSO) algorithm has been used for the battery model development, it is usually unable to find an optimal solution during the iteration process. To resolve this problem, an adaptive random disturbance PSO algorithm is proposed. The optimal solution can be updated continuously by obtaining a new random location around the particle's historical optimal location. There are two conditions considered to perform the model process. Initially, the test operating condition is used to validate the model effectiveness. Secondly, the verification operating condition is used to validate the model generality. The performance results show that the proposed model can achieve higher precision in the lithium-ion battery behavior, and it is feasible for wide applications in industry.
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