Parity-relation-based state-of-health monitoring of lead acid batteries for automotive applications

Effective vehicular power management requires accurate knowledge of battery state, including state-of-charge (SOC) and state-of-health (SOH). This paper presents an integrated algorithm for reliable battery SOH monitoring. The dynamics of lead acid batteries during engine cranking is investigated, and a new battery model is presented. Moreover, a parity-relation-based integrated method for battery SOH monitoring is proposed. It is shown that the diagnostic residual combines the SOH information provided by both battery resistance and voltage loss during engine cranking, hence enhancing diagnostic performance. Extensive evaluation results using real vehicle cranking data have verified the effectiveness of the proposed method.