Battery condition monitoring (BCM) technologies about lead–acid batteries

Abstract A novel battery condition monitoring (BCM) technology for lead–acid batteries has been developed. We have developed a highly reliable SOC monitor that improves the estimated precision of the stored capacity to ±5% for both the flooded type and VRLA. A novel SOC estimation algorithm was also developed. The SOC value was obtained by the weighting combination of the values from the SOC–DCR table and the current integration. Kalman Filtering Theory contributed to developing this system. In order to improve the accuracy of the SOC–DCR table, we have derived a theoretical equation for the SOC–DCR relationship. This equation helps to interpolate the data and improve the accuracy of the SOC–DCR table.