Position-Based T-S Fuzzy Power Management for Tram With Energy Storage System

Energy storage systems (ESSs) play a significant role in performance improvement of future electric traction systems. This paper investigates an ESS based on supercapacitors for trams as a reliable technical solution with considerable energy saving potential. Operating the ESS onboard a tram brings the following benefits: reduction of peak power demands, decrease of power consumption, improvement of performance, and efficiency. Whereas the commonly used ESS power management (PM) has been dealing only with PM without vehicle position knowledge, the main emphasis of the presented research is put on position-based Takagi-Sugeno fuzzy (T-S fuzzy) PM for human-driven trams with an ESS. The tram position, located by, e.g., a Global Positioning System module, is used to predict future energy demands and power flows. This information is used in the preparation of the supercapacitor energy level and its power flow control. The optimal ESS power flow with respect to the tram position is a very complex problem. Therefore, soft computing techniques are used in this paper. The main part of the proposed ESS PM is the T-S fuzzy controller. The T-S fuzzy reduces problem dimensionality using expert knowledge represented by the rules. The output membership functions were optimized by differential evolution. The designed ESS PM was verified on real traffic data.