State of energy estimation of the echelon-use lithium-ion battery based on Takagi–Sugeno fuzzy optimization - Hou, Enguang; Wang, Zhen; Wang, Zhixue; Qiao, Xin; Liu, Guangmin (Frontiers in Energy Research, 2023)
Owing to the degradation of an echelon-use lithium-ion battery (EULIB), the Ohmic internal resistance (OIR) and actual capacity (AE) have both changed greatly, state of energy (SOE) can more accurately represent the state of a EULIB than state of charge (SOC) be-cause of working-voltage. To improve the accuracy and adaptability of SOE estimation, in the paper, we study the energy state estimation of a EULIB. First, the four-order resistor-capacitance equivalent model of a EULIB is established, and an unscented transformation is introduced to further improve SOE estimation accuracy. Second, a EULIB’s SOE is estimated based on an adaptive-unscented Kalman filter (AUKF), and the OIR and AE of a EULIB are estimated based on the AUKF. Third, a Takagi-Sugeno fuzzy model is introduced to optimize the OIR and AE of the EULIB, and the SOE estimation method is established based on an adaptive-dual-unscented Kalman filter (ADUKF). Through simulation experiments, verification, and comparison, energy decayed to 80%, 60%, and 40% of rated energy, even with a large initial error, with the initial value of the SOE starting at 100%, 60%, or 20%, the estimated SOE can track the actual value. It can be seen that the method has a strong adaptive ability, and the estimation accuracy error is less than 1.0%, indicating that the algorithm has high accuracy. The method presented in this paper pro-vides a new perspective for SOE estimation of EULIBs