Online State-of-health(SOH) estimation for a LiMn₂O₄ cell based on fuzzy-logic

This paper investigates a new approach based on the fuzzy-logic controlled methodology that is suitable for analyzing and evaluating large format $LiMn_2O_4$ cell performance via online state-of-health (SOH) estimation for energy storage system (ESS) applications. First of all, the values of the cell resistance R and maximum cell capacity $Q_{max}$ are calculated from three factors such as voltage, current, and time that were measured by discharging/charging sequence. Then, using two values R and $Q_{max}$ previously calculated, present SOH of an arbitrary $LiMn_2O_4$ cell can be estimated using the defined fuzzy-logic inference system. The main advantage of this approach is wide parameters tuning possibility for good correspondence of SOH decay with other accurate estimation method and the possibility to perform suitable online SOH estimation.