Predicting Lithium-ion Battery Resistance Degradation using a Log-Linear Model

The resistance is one of the parameters that describes the performance of Lithium-ion (Li-ion) batteries, as it offers information about the battery efficiency and its power capability. However, similar to other performance parameters of Li-ion batteries, the resistance is dependent on the operating
conditions and increases while the battery is aging. Traditionally, to capture these dependencies, Li-ion cells are aged at different conditions using synthetic mission profiles and periodically the aging tests are stopped in order to measure the resistance at standard conditions. Most of the times, even though accurate information about the resistance behavior is obtained, they do not reflect the behavior from real-life applications. Thus, in this work we propose a method for extracting, modelling, and predicting the resistance directly from the battery dynamic mission profile. While the extraction mainly relied on data manipulation and bookkeeping, the modelling and subsequent prediction of the resistance used a log-linear model.