Genetic optimization of charging current for lead-acid batteries in hybrid electric vehicles

VRLA batteries are of great importance in hybrid electric vehicle technology. They are generally equipped with intelligent chargers. The battery charger should be able to produce the desired charging current profile. Although reduction in charging time is unavoidable but the battery state of the health should not be sacrificed. In this paper a new model based optimization cost function is introduced which includes not only the charging time, but also the battery´s state of the health. Genetic optimization algorithm is employed to optimize the charging current for these batteries, in order to decrease charging time and improve the battery life time. Comparing this method with constant-current and multi step charging algorithms shows the superiority of the proposed method.