电池(电)
汽车工程
电池组
动态规划
计算机科学
电
气体压缩机
能源管理
模拟
功率(物理)
能量(信号处理)
工程类
电气工程
机械工程
统计
物理
数学
量子力学
算法
作者
Yue Wu,Zhiwu Huang,Dongjun Li,Heng Li,Jun Peng,Daniel‐Ioan Stroe,Ziyou Song
出处
期刊:Applied Energy
[Elsevier]
日期:2024-01-01
卷期号:353: 122090-122090
被引量:3
标识
DOI:10.1016/j.apenergy.2023.122090
摘要
The control of a battery thermal management system (BTMS) is essential for the thermal safety, energy efficiency, and durability of electric vehicles (EVs) in hot weather. To address the battery cooling optimization problem, this paper utilizes dynamic programming (DP) to develop an online rule-based control strategy. Firstly, an electrical–thermal-aging model of the LiFePO4 battery pack is established. A control-oriented onboard BTMS model is proposed and verified under different speed profiles and temperatures. Then in the DP framework, a cost function consisting of battery aging cost and cooling-induced electricity cost is minimized to obtain the optimal compressor power. By exacting three rules ”fast cooling, slow cooling, and temperature-maintaining” from the DP result, a near-optimal rule-based cooling strategy, which uses as much regenerative energy as possible to cool the battery pack, is proposed for online execution. Simulation results show that the proposed online strategy can dramatically improve the driving economy and reduce battery degradation under diverse operation conditions, achieving less than a 2.18% difference in battery loss compared to the offline DP. Recommendations regarding battery cooling under different real-world cases are finally provided.
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