Potential of infrared temperature measurements for the online estimation of the state-of-charge of a Li-polymer battery

Abstract

The knowledge of the battery status in terms of state-of-health (SoH), state-of-charge (SoC), and state-of-power (SoP) is of great significance for the efficient usage of the available stored energy and to ensure the safety of electric vehicles. The SoC is the equivalent of the fuel tank gage as it indicates the amount of energy that can still be extracted from the battery before a recharge. Many techniques have been proposed in the literature for the estimation of the SoC based on more or less complex mathematical approaches. In general, the electric parameters of the battery were used. This work aims to trace a new path for the estimation of the SoC of a lithium polymer battery using thermal parameters instead of electric ones. Temperature measurements are already used in battery management systems with a different function than SoC evaluation. The approach presented here aims to give a more prominent role to the temperature data collected during the battery operation. This can serve as a main or secondary (cross-check) tool for the online estimation of the battery Soc.The battery temperature is measured during the discharge phase at a constant current and the following resting phase. Thermal imaging in the infrared band is applied to assess the presence of 2d inhomogeneity on the battery surface. The experimental data are coupled to an extensive theoretical analysis based on the lumped parameter model applying Newton's law of cooling in transient conditions. The first objective is the estimation of the open-circuit voltage over time, which is unknown during the operation. It is put in correlation to the SoC calculated with the Coulomb counting method. The open-circuit voltage versus SoC curve is essential for the online SoC determination. Theoretical results have been validated with the data of a multi-step test cycle performed on purpose. Finally, a new method for the online SoC estimation based on temperature measurements has been set up and validated.