Fuzzy energy management strategy for tram with supercapacitors

Energy storage systems (ESS) have large impact on efficiency and reliability of modern electric traction systems. This paper investigates the fuzzy energy management strategy for ESS based on supercapacitors (SC) for human driven trams. Operating the SC on board of 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 Energy management strategies (EMSs) have been dealing without knowledge of vehicle position, the main interest of the presented research is put on the algorithm using the Global Positioning System (GPS). The tram position, located by a GPS 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 the respect to the tram position is a very complex problem. For this reason, soft computing techniques are used in this paper. The main part of the proposed ESS EMS is the Takagi-Sugeno Fuzzy controller (T-S Fuzzy). The T-S Fuzzy reduces problem dimensionality using the expert knowledge represented by the rules. The output membership functions were finaly optimized by the Differential Evolution (DE).