Battery Pack Data Imputation Technique For Dynamic Profiles

Lithium-ion batteries play a key role in electric mobility applications, where monitoring the health and behavior of individual cells is essential to ensure safety and performance over time. However, intermittent or persistent data gaps can arise due to several causes, such as sensor faults, communication breakdowns, or inadequate data acquisition infrastructure. Such missing data can disrupt the cell balancing process, leading to differences between cells and stress in specific cells, accelerating their degradation. This paper presents an imputation method based on the Unscented Kalman Filter (UKF) to reconstruct missing voltage measurements. The results presented here can help prevent early cell degradation and extend the useful life of the full battery pack.