Electric vehicle battery parameter identification and SOC observability analysis: NiMH and Li‐S case studies. Issue 11 (27th July 2017)

• Record Type: Journal Article
• Authors: Fotouhi, Abbas; Auger, Daniel J.; Propp, Karsten; Longo, Stefano
• Is Part Of: IET power electronics. Volume 10:Issue 11(2017)
• Page Start: 1289
• Page End: 1297
• Publication Date: 2017-07-27
• Subjects: battery powered vehicles -- battery management systems -- equivalent circuits -- minimisation -- dynamometers -- parameter estimation -- secondary cells -- lithium -- sulphur; electric vehicle battery parameter identification -- SOC observability analysis -- NiMH cell -- electric vehicle battery management system -- nickel‐metal hydride cell -- lithium‐sulphur cell -- equivalent circuit battery model parameterisation -- prediction‐error minimisation algorithm -- Li‐S cell -- urban dynamometer driving schedule -- UDDS -- state‐of‐charge -- battery chemistry -- battery open circuit voltage -- OCV -- temperature 5 degC -- temperature 10 degC -- temperature 20 degC -- temperature 30 degC -- temperature 40 degC -- temperature 50 degC -- Li‐S; Power electronics -- Periodicals; 621.31705
• DOI: 10.1049/iet-pel.2016.0777
• Languages: English
• ISSNs: 1755-4535

Abstract

Abstract : In this study, battery model identification is performed to be applied in electric vehicle battery management systems. Two case studies are investigated: nickel‐metal hydride (NiMH), which is a mature battery technology, and lithium‐sulfur (Li‐S), a promising next‐generation technology. Equivalent circuit battery model parameterization is performed in both cases using the Prediction‐Error Minimization algorithm applied to experimental data. Performance of the Li‐S cell is also tested based on urban dynamometer driving schedule (UDDS). The identification results are then validated against the exact values of the battery parameters. The use of identified parameters for battery state‐of‐charge (SOC) estimation is also discussed. It is demonstrated that the set of parameters changes with a different battery chemistry. In the case of NiMH, the battery open circuit voltage (OCV) is adequate for SOC estimation whereas Li‐S battery SOC estimation is more challenging due to its unique features such as flat OCV‐SOC curve. An observability analysis shows that Li‐S battery SOC is not fully observable and the existing methods might not be applicable for it. Finally, the effect of temperature on the identification results and the observability are discussed by repeating the UDDS test at 5, 10, 20, 30, 40 and 50 degree Celsius