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This paper presents an online method for the estimation of the state of health (SOH) of valve-regulated lead acid (VRLA) batteries. The proposed method is based on the state of charge (SOC) of the battery. The SOC is estimated using the extended Kalman filter and a neural-network model of the battery. Then, the SOH is estimated online based on the relationship between the SOC and the battery open-circuit voltage using fuzzy logic and the recursive least squares method. To obtain the open-circuit voltage while the battery is operating, the reflective charging process is employed. Experimental results show good estimation of the SOH of VRLA batteries.
Shahriari et al. (Fri,) studied this question.