VRLA battery capacity estimation using soft computing analysis of the coup de fouet region

In a previous paper (1999), the authors discussed the use of parameters found within the coup de fouet region for estimating VRLA battery capacity. However, only the operating conditions of discharge rate, and environmental temperature were considered. The investigation presented in this paper considers the influence on the coup de fouet region of other operating conditions as well as the condition of the battery. The operating conditions considered are the: (1) depth of previous discharge; (2) time on float charge; and (3) float voltage. Battery conditions considered include those that occur due to: (1) accelerated ageing using thermal stress; and (2) water replenishment after thermal stress. Both operating and battery conditions have been shown to influence the form of the coup de fouet. To further expose the behaviour of the battery during this region, the contribution to the coup de fouet of both the positive and negative electrodes are presented. The paper suggests a preliminary capacity estimation model. The model is based on a fusion of soft and hard computing techniques. The series of tests conducted are sufficient to create the soft computing model which encompasses the relationships between the operating conditions and the coup de fouet parameters. This model enables the effects of the operating conditions on the coup de fouet to be eliminated. It follows that the remaining variation exhibited by the coup de fouet parameters is related to battery conditions only. Hard computing techniques are then employed to related the corrected coup de fouet parameter to capacity.