Optimal energy management of a hybrid electric bus with a battery-supercapacitor storage system using genetic algorithm

This paper is focused on a series hybrid electric bus (SHEB). A rule-based energy management strategy is proposed by controlling the state of charge (SOC) of the battery (BT) and a variable output control for the auxiliary power unit (APU). Furthermore, a power splitter control is developed to split the power among BT and supercapacitor (SC). The optimization to obtain the values for the control levels is carried out with multi-objective genetic algorithm (GA). The aim of the optimization is to minimize the daily operating cost of the bus. The objective functions are the costs related to fuel and energy (BT and SC degradation by cycling cost, recharge from the grid cost) consumption. The results are given in a Pareto front with a set of optimal solutions, the optimal one will depend of an analysis on which objective has priority to be minimized and what are the consequences of this decision on the other one.