锂(药物)
功率(物理)
离子
常量(计算机编程)
联轴节(管道)
国家(计算机科学)
电化学
恒流
热的
材料科学
控制理论(社会学)
物理
计算机科学
热力学
电极
控制(管理)
算法
医学
量子力学
人工智能
冶金
程序设计语言
内分泌学
作者
Wenxing Sun,Junkun Zhang,Ertao Lei,Jin Li,Kai Ma,Junchi Ma,Ying Li,Xinwei Li
出处
期刊:2020 7th International Forum on Electrical Engineering and Automation (IFEEA)
日期:2023-11-03
卷期号:: 655-663
标识
DOI:10.1109/ifeea60725.2023.10429671
摘要
Currently, lithium-ion batteries are widely used in industries such as new energy vehicles and energy storage as a clean new energy source. Battery power is a key indicator for measuring whether the battery system meets the requirements for new energy vehicle acceleration and climbing, as well as ensuring the normal operation of electrical equipment. In this work, a state of power (SOP) estimation method was proposed based on a simplified electrochemical-thermal coupling model and constant power condition. Firstly, based on the existing electrochemical model, a three-dimensional thermal description was added for prismatic batteries to construct an electrochemical-thermal coupling model. Secondly, by employing a model-driven approach and using a growth search algorithm, external characteristics estimation of the battery under constant power conditions was achieved. Finally, using voltage and current as constraints, a power-current dual-cycle growth search algorithm was proposed to complete SOP estimation based on constant power condition. Through simulations and experiments, it can be observed that this estimation algorithm can achieve SOP estimation across the entire State of Charge (SOC) range for different forecast time.
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