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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.