Model‐based state of X estimation of lithium‐ion battery for electric vehicle applications

• DOI: 10.1002/er.7874
• Publication Date: 2022-03-28T13:15:54Z
• Authors: Prashant Shrivastava; Tey Kok Soon; Mohd Yamani Idna ...; Saad Mekhilef; Syed Bahari Ramad...
• Keywords: State of charge; Sliding window protocol

In developing an efficient battery management system (BMS), accurate and computationally states estimation algorithm is always required. this work, the highly model-based state of X (SOX) method proposed to concurrently estimate different such as charge (SOC), energy (SOE), power (SOP), health (SOH). First, SOC SOE performed using a new joint method, developed multi-time scale dual extended Kalman filter (DEKF). Then, SOP T-method 2RC model evaluate non-instantaneous peak during charge/discharge. Finally, current capacity simple coulomb counting (CCM)-based with sliding window. The performance SOX compared analyzed. experimental results show that estimated error less than 1% under considered dynamic load profile at three temperatures. After final convergence, maximum value absolute ±0.08 Ah. addition, low evaluated mean execution time (MET) justifies high computational efficiency method.