Comparative Study of Kalman Filter and H infinity Filter for Current Sensorless Battery Health Analysis

The battery is an important component in an electric vehicle. Batteries are connected in series into a battery pack to meet system voltage requirements. Problems will arise if the health conditions of the battery cells used are not uniform. For this reason, it is necessary to analyze the health of the battery cell on the battery pack. Analysis of the health of each battery cell will increase the cost of A Battery Management System because it uses many sensors. This work performs a comparison of the Kalman Filter and H infinity Filter algorithms to analyze the health of battery cells without using a current sensor. Reducing the current sensor will provide financial benefits because the current sensor is one of the expensive sensors in the BMS. The comparison results show both methods can estimate the battery cell voltage. The estimation results are then used to determine the residual voltage in each battery cell. A battery that has a good condition when compared to other battery cells in the battery pack will provide the smallest residual value. The Kalman Filter method provides a better sensitivity picture than the H Infinity Filter, although it needs to be validated in the next research.