A novel grouping method for lithium-ion battery pack considering cell divergence

作者：Xiong Rui^*; Lv Liang; Mu Hao

来源：2017 Chinese Automation Congress, CAC 2017, 2017-10-20 To 2017-10-22.

DOI：10.1109/CAC.2017.8243716

• Battery capacity
• Battery modules
• Clustering methods
• Internal resistance
• Lithium ions
• Principal factor analysis
• SOC estimations
• State of charge

The inconsistency between battery monomers are often ignored in the process of battery SOC (State of Charge) estimation, the usual approach is to consider a battery module as a whole, and to obtain the 'averaged SOC'by using the method of SOC estimation applied in one cell. In fact, because of the inconsistencies of battery capacity, the initial SOC, internal resistance and other parameters, there are some 'special batteries'existing in the battery module, which is easy to be over-charged or over-discharged. In this paper, two approaches are proposed for mitigating the effects of inconsistency, in order to reduce the initial inconsistency, a PFA (principal factor analysis) based screening and clustering method was presented for grouping optimization;to obtain more accurate SOC estimation results, a reliability analysis based SOC correction considering cell divergence was done.

• 出版日期2017
• 单位北京理工大学