The main purpose of this paper is to design and implement an intelligent stateof-charge (SOC) estimator for lead-acid batteries. The internal resistance, open-circuit voltage and short-circuit current are chosen as the characteristics of lead-acid batteries. First, many cycles of charging-discharging experiments for lead-acid batteries are made to measure and record the distributed range of characteristic values. Then, the impacts of battery life on these characteristics are also inspected. The battery capacity is classified into 21 states. The measured characteristic values are adopted to construct an extension evaluation method according to the extension matter-element model for differentiating the SOC of lead-acid batteries. Finally, a programmable system-on-chip (PSoC) microcontroller is employed to implement the proposed intelligent SOC estimator with the high precision, fast speed and small size of hardware circuits for lead-acid batteries. Some experimental results are presented to verify the effectiveness of the proposed intelligent SOC estimator. (20 refs)
