Review of Real Time Implementation of State of Health of a Li-Ion Battery

Nowadays usages of electric vehicles are increased due to abnormal price hike of petrol, pollution-free driving and less noise, lightweight. The battery’s SoH provides important details to the BMS to decide the battery life conditions. The function of BMS is to provide safe and efficient operating conditions to the battery. BMS protects the battery from over-voltage, under-voltage, over-charge and over-discharge, over-temperature, and under temperature. Due to ageing problem, the internal resistance is increased hence the retention capacity of the battery is reduced, the internal resistance is inversely proportional to the battery capacity. The SoH cannot be measured directly, it is estimated from the internal resistance and the capacity of the battery. Early prognosis of Battery gives the replacement of the battery and avoid any accident because of battery malfunction. The fast and accurate method of estimating the State of Health is remaining challenge in the area of battery’s research. This paper provides the various estimating algorithms, implementation methods and their advantages and disadvantages. It provides overall estimation of SoH techniques which were used in literature survey.