Plating Mechanism Detection in Lithium-ion batteries, by using a particle-filtering based estimation technique

Plating of metallic Lithium (Li) is an important battery degradation, failure mechanism, and a safety concern of Lithium-ion (Li-ion) batteries during charging process, which can short circuit the battery and lead to uncontrollable energetic chemical reactions. It happens when the transport rate of Li ions to the negative electrode exceeds the rate that Li ions can be inserted (intercalated) into the graphite. This paper presents a two-step Plating Mechanism Detection (PMD) algorithm which is based on the model-based fault diagnosis theory. In the first step, an estimation of the Li ions' transport rate in both positive and negative electrodes is obtained from an electrochemical model of the battery through a particle filtering approach. Estimated data are then compared with their boundary values in order to generate an appropriate fault alarm. Simulation results are provided to show the effectiveness of the proposed PMD algorithm.