Title :
Fuzzy prediction control strategy of EMS with energy hybridization of high energy and high power
Author :
Wang, Yaonan ; Yu, Qunming ; Yang, Huiqian ; Sorg, M. ; Stanislowski, R. ; Ament, C. ; Selzer, H.
Author_Institution :
Coll. of Electr. Eng. & Inf., Hunan Univ., Changsha, China
Abstract :
A combination of different electric energy supply with different feature is designed for high acceleration and high ranges and improves the whole system properties. Energy supply system with energy hybridization of high energy and high power need an intelligent management system in order to control power and state of charge. In this paper we proposed a fuzzy prediction control strategy of energy management system (EMS) based on a new forward-looking and causal structure model. This control strategy is mainly consisted of three controllers, including SOC prediction controller, recharge controller and power allocation controller. Simulation result shows that the driving range, the fuel economy and efficiency of fuzzy prediction control strategy have rapidly improvement compared with simple allocation (look-up table) control strategy. In the next step we will apply this control strategy with actual EV through "dspace autobox".
Keywords :
electric vehicles; energy management systems; fuzzy control; power control; predictive control; table lookup; EMS; causal structure model; dspace autobox; electric energy supply; energy hybridization; energy management system; forward-looking model; fuel economy; fuzzy prediction control strategy; intelligent management system; look-up table; power allocation controller; power power; recharge controller; Acceleration; Control systems; Energy management; Fuzzy control; Fuzzy systems; Hybrid intelligent systems; Medical services; Power system management; Power system modeling; Predictive models;
Conference_Titel :
Electrical Machines and Systems, 2005. ICEMS 2005. Proceedings of the Eighth International Conference on
Print_ISBN :
7-5062-7407-8
DOI :
10.1109/ICEMS.2005.202657