加权
遗传算法
计算机科学
电流(流体)
联轴节(管道)
热的
恒流
数学优化
常量(计算机编程)
控制理论(社会学)
电子工程
工程类
数学
电气工程
物理
机械工程
控制(管理)
人工智能
气象学
声学
程序设计语言
作者
Zhiyong Xu,Guangcai Zhao,Xuefeng Liu,Yuhang Kuai,Bin Duan,Chenghui Zhang
标识
DOI:10.1109/cvci56766.2022.9964532
摘要
This paper presents a multi-objective optimized charging strategy based on an electro-thermal coupling model. The charging current affects charging time, charging capacity and temperature rise and needs to be well balanced and carefully optimized. The charging strategy proposed in this paper takes three factors mentioned above into account and performs a multi-objective optimization to obtain the best combination of charging currents by means of a genetic algorithm. By varying the weighting parameters, a certain objective is targeted or optimized in a balanced manner. Compared to the conventional constant current charging strategy, this charging strategy has the advantages of shorter charging time, higher charging capacity, and lower maximum temperature rise.
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