电池组
电流(流体)
健康状况
计算机科学
锂(药物)
电池(电)
估计
锂离子电池
离子
国家(计算机科学)
可靠性工程
汽车工程
工程类
材料科学
电气工程
功率(物理)
热力学
系统工程
算法
医学
内分泌学
物理
有机化学
化学
作者
Xiaopeng Tang,Furong Gao,Kailong Liu,Qi Liu,Aoife Foley
标识
DOI:10.1109/tie.2021.3108715
摘要
The inevitable battery ageing is a bottleneck that hinders the advancement of battery-based energy storage systems. Developing a feasible health assessment strategy for battery pack is important but challenging due to the joint requirements of the computational burden, modeling cost, estimation accuracy, and battery equalization. This article proposes a balancing current ratio (BCR) based solution to achieve reliable state-of-health (SoH) estimations of all series-connected cells within a pack while significantly reduce the overall reliance on cell-level battery models. Specifically, after employing BCR to describe the properties of the balancing process, the voltage-based active balancing is combined into the SoH estimator design for the first time, leading to a weighted fusion strategy to effectively estimate SoHs of all cells within a pack. Hardware-in-the-loop experiments show that even if a parameter-fixed open-circuit-voltage-resistance model is used for modeling, the typical estimation error of our proposed solution can still be bounded by only 1.5%, which is 70% lower than that of the benchmarking algorithms. Due to the model-free nature of the integrated voltage-based balancing, the robustness and flexibility of the proposed pack SoH estimation solution are also significantly improved.
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