Online Determination of Lithium-ion Battery State of Health based on Normalized Change of State of Temperature for e-Mobility Applications

Accurate estimation of lithium-ion battery state of health (SOH) is essential for safe and reliable operation, especially for e-mobility applications due to dynamic variation of operating parameters. Existing SOH estimation methods primarily depend on changes in battery terminal voltage and capacity fade. Experimental and practical data demonstrated that the battery capacity fade is significantly influenced by battery operating temperature and discharge current profiles. Therefore, existing methods fail to provide accurate SOH information in practical scenarios despite excellent performance in a laboratory environment. A solution to that, an adaptive and robust SOH estimation method based on normalized change of battery state of temperature is proposed in this paper for practical applications. The proposed SOH estimation method accommodates the influence of the rate of change of battery temperature due to battery aging, making the method highly adaptive to the change in operating parameters and the rise in battery internal resistances due to aging. The proposed method is then validated using experimental data which are collected on one 21700 NMC lithium-ion battery cell under a wide range of operating conditions.