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Investigating the error sources of the online state of charge estimation methods for lithium-ion batteries in electric vehicles
Journal of Power Sources ( IF 8.1 ) Pub Date : 2017-12-22 , DOI: 10.1016/j.jpowsour.2017.11.094
Yuejiu Zheng , Minggao Ouyang , Xuebing Han , Languang Lu , Jianqiu Li

Sate of charge (SOC) estimation is generally acknowledged as one of the most important functions in battery management system for lithium-ion batteries in new energy vehicles. Though every effort is made for various online SOC estimation methods to reliably increase the estimation accuracy as much as possible within the limited on-chip resources, little literature discusses the error sources for those SOC estimation methods. This paper firstly reviews the commonly studied SOC estimation methods from a conventional classification. A novel perspective focusing on the error analysis of the SOC estimation methods is proposed. SOC estimation methods are analyzed from the views of the measured values, models, algorithms and state parameters. Subsequently, the error flow charts are proposed to analyze the error sources from the signal measurement to the models and algorithms for the widely used online SOC estimation methods in new energy vehicles. Finally, with the consideration of the working conditions, choosing more reliable and applicable SOC estimation methods is discussed, and the future development of the promising online SOC estimation methods is suggested.



中文翻译:

调查电动汽车锂离子电池在线充电状态估计方法的错误来源

充电状态(SOC)估计通常被认为是新能源汽车中锂离子电池的电池管理系统中最重要的功能之一。尽管已尽力使各种在线SOC估计方法在有限的片上资源内尽可能可靠地提高估计精度,但很少有文献讨论这些SOC估计方法的误差源。本文首先从常规分类中回顾了常用的SOC估计方法。提出了一种新的观点,着眼于SOC估计方法的误差分析。从测量值,模型,算法和状态参数的角度分析了SOC估计方法。随后,提出了误差流程图,分析了从信号测量到新能源汽车中广泛使用的在线SOC估计方法的模型和算法的误差来源。最后,结合工作条件,讨论了选择更可靠,适用的SOC估计方法,并提出了有前途的在线SOC估计方法的未来发展方向。

更新日期:2017-12-22
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