State of health estimation of lithium-ion batteries based on remaining area capacity

Abstract

Accurate state of health (SOH) estimation can ensure the safe and reliable operation of the battery and prolong its service life. A new SOH evaluation method including the concepts of characteristic probability (CP) and remaining area capacity (RAC) are introduced in the framework of probability density function (PDF). Battery SOH evaluation models are respectively established for the lithium-iron phosphate (LFP) battery module and nickel-cobalt-aluminium (NCA) cell based on laboratory data at 1/3C-rate and 1C-rate at the sampling frequency of 1 min, and the effects of different CP values on the RAC - SOH models are investigated. The results show that there is a strong linear positive correlation between RAC and SOH whether charge and discharge conditions, while the model with the maximum PDF peak height as health factor is not ideal to assess battery SOH during discharging. The smaller the CP value, the better the effect of the RAC - SOH model. The R2 values of RAC - SOH models of NCA cell and LFP battery module are up to 0.99 at appropriate characteristic probability. The RMSE between the real and the estimated value of NASA battery SOH is not >1.2 % based on the RAC - SOH model. The improved PDF method has accurate and robust performance for the SOH estimation of different batteries.