• Title of article

    Cell state-of-charge inconsistency estimation for LiFePO4 battery pack in hybrid electric vehicles using mean-difference model

  • Author/Authors

    Zheng، نويسنده , , Yuejiu and Ouyang، نويسنده , , Minggao and Lu، نويسنده , , Languang and Li، نويسنده , , Jianqiu and Han، نويسنده , , Xuebing and Xu، نويسنده , , Liangfei and Ma، نويسنده , , Hongbin and Dollmeyer، نويسنده , , Thomas A. and Freyermuth، نويسنده , , Vincent، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2013
  • Pages
    10
  • From page
    571
  • To page
    580
  • Abstract
    Identification of cell SOC (state-of-charge) inconsistency for LiFePO4 battery packs is challenging due to the demanding conditions in hybrid electric vehicles (HEVs) and the relatively flat SOC–OCV (open circuit voltage) curve of LiFePO4 cells compared to others. We experimentally investigate cell voltages in a small battery pack and propose a Mean-plus-Difference Model (M+D Model). The M+D Model uses a cell mean model (CMM) representing the overall performance of the pack in high frequency. Meanwhile cell voltage differences (CVDs) between cells and the “mean cell” are studied by a cell difference model (CDM) in low frequency. A CDM considering SOC and internal resistance differences is subsequently presented and OCV differences are estimated. We further propose an SOC strategy to accurately identify cell SOC inconsistency by intermittently lowering pack SOC to 30% during HEV operation. Finally we discover that SOC differences can be determined with estimated OCV differences using SOC-difference/OCV-difference curve. The proposed method is verified by simulation and experiment. With the proposed method, LiFePO4 cell SOC inconsistency can be precisely estimated with existing measuring technology during HEV operating and cell equalization can be ultimately implemented.
  • Keywords
    Battery modeling , Hybrid Electric Vehicle , Battery pack , state-of-charge , Cell variations
  • Journal title
    Applied Energy
  • Serial Year
    2013
  • Journal title
    Applied Energy
  • Record number

    1606477