Electric vehicle battery parameter identification and SOC observability analysis: NiMH and Li‐S case studies

摘要

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-sulphur (Li-S),a promising next-generation technology. Equivalent circuit battery model parameterisation is performed in both cases using theprediction-error minimisation algorithm applied to experimental data. Performance of a Li-S cell is also tested based on urbandynamometer driving schedule (UDDS) and the proposed parameter identification framework is applied in this case as well. Theidentification results are then validated against the exact values of the battery parameters. The use of identified parameters forbattery state-of-charge (SOC) estimation is also discussed. It is shown that the set of parameters needed can change with adifferent battery chemistry. In the case of NiMH, the battery open circuit voltage (OCV) is adequate for SOC estimation whereasLi-S battery SOC estimation is more challenging due to its unique features such as flat OCV–SOC curve. An observabilityanalysis shows that Li-S battery SOC is not fully observable and the existing methods in the literature might not be applicablefor a Li-S cell. Finally, the effect of temperature on the identification results and the observability is discussed by repeating theUDDS test at 5, 10, 20, 30, 40 and 50°C.