Prognostics and Health monitoring of Lead acid battery

Abstract

The ever-increasing number of electrical loads in the commercial vehicle emphasizes the significance of lead acid battery used for starting and the powering of electrical systems in a commercial vehicle. In order to monitor the health of the battery, parameters SOC (State of Charge) and SOH (State of Heath) are introduced. The existing methods to calculate these parameters use impedance monitoring based approach which requires an expensive current sensor. This paper describes a smart algorithm and the experimental verification of the algorithm that uses only voltage values for predicting the failure of the battery. The voltage waveforms during a cranking event is studied by the ECU (Engine Control Unit) and the health of the battery is determined based on it. A parameter, SOH measure is obtained from the algorithm and the value of this parameter reduces with increase in life of the battery. If the value of the SOH measure reduces below a threshold, then the failure of the battery is predicted before the actual failure. The algorithm is validated with the help of real time data obtained from the vehicles. This method of calculating the SOH is resourceful and cost-effective as it exploits the data that’s already available in the ECU namely battery voltage and ambient temperature. Thus, it does not warrant an addition of sensor to the system in place.