Online Adaptive NeuroFuzzy Based Energy Management Schemes for Fuel-Cell Based Hybrid Power System

Hybrid power systems are now extensively being used due to their low fuel consumption and greater efficiency. In this context, fuel cell integration with conventional power sources is becoming an interesting solution. Choice of fuel cell as power source also serves to address many environmental concerns. Energy Management Schemes (EMSs) have great influence on dynamic performance and fuel consumption of these sources. EMS controls the power split between different energy sources to fulfill the power demand at load. In this paper, comparative analysis of different NeuroFuzzy based EMSs for emergency landing scenario of More Electric Air-Craft is presented. The performance validity of online adaptive NeuroFuzzy Wavelet Control has been checked against conventional NeuroFuzzy Takagi Sugeno Kang (TSK) control and classical PI control. State of the charge of battery and supercapacitor, fuel consumption and overall system efficiency have been chosen as performance metrics.