Multi-objective optimization for multi-stage constant current charging for Li-ion batteries

恒流 电流(流体) 常量(计算机编程) 计算机科学 电气工程 工程类 程序设计语言
作者
Muhammad Usman Tahir,Ariya Sangwongwanich,Daniel‐Ioan Stroe,Frede Blaabjerg
出处
期刊:Journal of energy storage [Elsevier BV]
卷期号:86: 111313-111313 被引量:3
标识
DOI:10.1016/j.est.2024.111313
摘要

Fast charging is a key challenge for the widespread adoption of electric vehicles (EVs), as it can make EVs more convenient and appealing to consumers. Therefore, different charging methods are proposed to enhance the performance of lithium-ion batteries (LIBs). Multi-stage constant current (MSCC) charging can improve LIB's performance in several aspects, including charging time, charged capacity, temperature rise, average temperature rise, and charging energy efficiency. However, achieving a multi-objective performance during LIB charging is challenging. In this paper, the Taguchi method is used to determine the multi-objective optimal (MOO) charging profile for the MSCC charging strategy. The Orthogonal experiments are designed and conducted to find the optimal solutions for each performance parameter for a five-stage constant current (5SCC) charging profile. A comparison is conducted among the performance-based selective charging profiles to validate the optimal charging profile. Furthermore, a comparison is made between the obtained MOO charging profile and the classical equivalent constant current constant voltage (CCCV) method. Experimental results demonstrated that the MOO charging profile reduces the charging time with comparable temperature rise to the CCCV, making it promising for the future alternative efficient EV charging. These findings highlight the effectiveness of the MSCC approach in improving LIB performance.
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