This research aims at developing the suboptimal energy management strategy by using artificial neural network (ANN) for a triple-electrical-energy electric vehicle (EV). The controller hardware designs will be implemented in the future. Firstly, we constructed a low-order dynamic equations that abstracted the characteristics of the vehicle, including energy sources (the fuel cell, lithium battery, and supercapacitor), driver’s model, traction motor, transmission, and longitudinal vehicle dynamics, etc.. The key parameters were mostly retrieved from the commercialization software-Advanced Vehicle Simulator (ADVISOR). Base on the vehicle structure of the Toyota Mirai, we built the range-extended EV. The powertrain system included an 110kW fuel cell set, a 40Ah lithium-ion battery set, and a 165F/48V supercapacitor and a 150kW AC motor. The ECMS control strategy included a six-layer for-loop: the battery state-of-health (SOH), power demand, the battery state-of-charge (SOC??), the