Estimating the Health Status of Li-ion NMC Batteries From Energy Characteristics for EV Applications
Abdelilah Hammou, Raffaele Petrone, Demba Diallo, Hamid Gualous
Abstract
Capacity and Direct Current Internal Resistance are good health indicators for Li-ion batteries. But they cannot be measured. This work proposes to estimate these indicators from already available current and voltage measurements. The estimators are based on third-order polynomials and energy features extracted during partial discharge and different depths of discharge under a dynamic profile (World harmonized Light vehicles Test Cycles). The estimations are validated with experimental measurements obtained from cycling three Lithium-Nickel-Manganese-Cobalt-Oxide/Graphite cells at a controlled temperature. The mean relative error for the Direct Current Internal Resistance estimation is less than 5% when the depth of discharge lies between 25% and 40%. It is lower than 2% for the capacity estimation. The method is simple and suitable for embedded battery monitoring as it uses already available voltage and current measurements.