An online heat generation estimation method for lithium-ion batteries using dual-temperature measurements

Estimation of heat generation in lithium-ion batteries (LiBs) is critical for enhancing battery performance and safety. Here, we present a method for estimating total heat generation in LiBs based on dual-temperature measurement (DTM) and a two-state thermal model, which is both accurate and fast for online applications. We demonstrate that the algorithm can keep track of the heat generation rate in real-time under scenarios of designed multi-stepwise heat generation profile and regular fast charging processes. Moreover, the algorithm requires no knowledge of the thermal boundary conditions, providing robustness against changes in convection conditions and ambient temperatures. Finally, this method can capture heat generation induced by abnormal exothermic reactions, which could be a useful tool for detection of battery thermal failures.