Electric vehicles (EVs) have become a hot research topic due to the petroleum crisis and air pollution issues, and Hybrid EVs (HEVs) equipped with engines and motors are popular nowadays due to their advantage over Pure EVs. The energy distribution between the engine and the motor is the major task of the control strategy or energy management for HEVs. Rule-based and optimization-based approaches are developed in this area, but not much work has been done for large-size super-capacitor (SC) equipped HEVs, like Hybrid buses. In this paper, a new optimization-based control strategy for a hybrid bus equipped with SCs as the energy regeneration system is presented. Considering the driving patterns of a bus that is of frequent accelerations and decelerations, it is proposed to characterize each time instant by its speed and acceleration, and the energy distribution is optimized based on these two state variables. To obtain a global solution, genetic algorithm (GA) is utilized for the optimization procedure, and then the obtained solutions are incorporated into a loop-up table for rule-based control. The approach is tested under three levels of load conditions and different driving cycles, and the simulation results show that significant improvements can be obtained after optimization.