Aging-aware equivalent circuit model for SOH estimation in lithium-ion batteries

Abstract

Li-ion battery internal impedance is a crucial pa-rameter for state of health estimation. In this paper, a 3RC equivalent circuit model of the battery is considered. This model is also able to simulate the aging of the battery by extracting the battery parameter dependencies with aging. By observing the changes in the model parameters, it is possible to extract the battery state of heath. This means that starting from an impedance measurement it is possible to estimate the state of health of the battery. This could be a very attractive solution for the battery swapping industry, where keeping track of the aging can help identify early signs of degradation or potential safety hazards, thereby increasing customer satisfaction, optimizing operational efficiency and maximizing the return of investment. In this work, a neural network for state of health estimation from internal resistance is developed and it is able to correctly estimate state of health with a mean absolute relative error of 4.25%