On-line detection system of state-of-charge in lead acid battery using multiple detectors

To realize a stable supply of electric power in an automobile, an accurate and reliable detection method of SOC (state-of-charge) in a lead acid battery is required. However the dynamics of the battery is very complicated. The characteristics of the battery greatly change due to its degradation. Moreover a automobile has many driving patterns, which are unknown beforehand. Thus it is not easy to detect the SOC analytically. In this paper, to overcome this problem, a new on-line SOC detection method using both neural network, online identification and multiple detectors is proposed. In order to increase the detection accuracy of degraded batteries, a detector is changed on-line in correspondence with a voltage-current characteristic of a battery. The detection accuracies for different sized batteries and various degradation states are investigated.