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Online State-of-Health Estimation of VRLA Batteries Using State of Charge

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2 Author(s)
Shahriari, M. ; Dept. of Electr. Eng., Iran Univ. of Sci. & Technol., Tehran, Iran ; Farrokhi, M.

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.

Published in:

Industrial Electronics, IEEE Transactions on  (Volume:60 ,  Issue: 1 )