3-D temperature field reconstruction of lithium-ion battery pack using real-time distributed moving horizon estimation

As lithium-ion batteries are widely used in different fields, the thermal effect is of serious concern. How to achieve accurate temperature estimation in real time is the main challenge of current research. To address this problem, we propose a real-time distributed moving horizon estimation (RT-DMHE) based on partial differential equations describing thermal dynamics of a lithium-ion battery pack. It decomposes the real-time centralized moving horizon estimation (RT-CMHE) into multiple local estimators that run in parallel with information exchange from adjacent subsystems. Simulation validation shows that the root mean square error of temperature estimates from the proposed RT-DMHE is smaller than that of an existing distributed Kalman filter in literature. Moreover, compared to the RT-CMHE, the proposed RT-DMHE achieves comparable estimation accuracy while vastly reducing the average computation time per sample.