Modeling And Simulation Of EV With Energy Hybridization

In this paper we proposed a EV model of energy hybridization with high energy and high power for great acceleration and long ranges and improve the whole system properties. This model is consisted of specified drive cycle, driver controller, power limitation, brake controller, vehicle mechanical limitation, transmission, motor, energy supply system and energy management system. Based on the model we finished a serial of analyses including effect of mass and battery configuration on vehicle performance.The energy storage system of the electric vehicle with energy hybridization consists of Zinc/air, battery, NiMH battery and ultracapacitor. The Zinc/air battery supplies energy for the constant load and operates for the basic energy supplement. On the other hand the NiMH battery is for the middle term energy supply. It supports the energy requirement in long term acceleration process and as an energetic recovery system for braking process and downhill drive. For guaranteeing the optimal handling characteristics even at work peak the ultracapacitor is used. This electric storage-media works as a double layer capacitor and under extreme situation of acceleration and is able to supply additional electric energy.In this paper we proposed a fuzzy control strategy and a power comparison control strategy of energy management system based on a model of energy hybridization EV. The inputs of fuzzy control strategy of EMS include the required power, the soc of NiMH battery and soc of ultracapacitor. The outputs of fuzzy control of EMS include the distributed power factors of three energy components. Each input and output can have different number of fuzzy sets. Power comparison control strategy of EMS is performed though comparison between the actual required power and the maximum supplying and absorbing power of energy storage components in order to distribute the power. Meantime determination methods of maximum supplying and absorbing power of energy storage components are described. Simulation result shows that the driving range, the fuel economy and efficiency of fuzzy control strategy and power comparison control strategy have improved compared with simple look-up table control strategy.