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Abstract:The major contribution of this paper is to propose a Fuzzy Logic Global Power Management Strategy for Hybrid Electric Vehicles (HEVs) that are driven by the PM-EVT (PM machine-Electric Variable Transmission) powertrain, such that the PM-EVT will have superior advantages over other types of powertrains, including the current Toyota Prius powertrain for series-parallel HEVs. This has been investigated throughout three aspects. The first is the optimum power splitting between the Internal Combustion Engine (ICE) and the PM-EVT. The second is maximizing the vehicle's energy capture during the braking process. Finally, sustaining the State of Charge (SOC) of the battery is adopted by a robust ON/OFF controller of the ICE. These goals have been accomplished by developing three fuzzy logic (FL) controllers. The FL controllers are designed based on the state of charge of the battery, vehicle's velocity, traction torque, and the vehicle's requested power. The integration of the studied system is accomplished via the Energetic Macroscopic Representation (EMR) simulation model strategy based on the software Matlab/Simulink. The PM-EVT based HEV system with the proposed power management strategy is validated by comparing to the Toyota Prius HEV. The vehicle's performances have been analyzed throughout a combined long-trip driving cycle that represents the normal and the worst operating conditions. The simulation results show that global control system is effective to control the engine's operating points within the highest efficiency region, exploiting of EVT machines for capturing maximum braking energy, as well as to sustain the SOC of the battery while satisfy the drive ability. The proposed control strategy OPEN ACCESSEnergies 2012, 5 1176 for the studied HEVs sounds interesting and feasible as supported by a large amount of simulation results.

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His research interests include modeling and control of motor drives, motion-control systems, wind energy systems, digital signal processing-based computer control systems, computational intelligent of power electronics, electric drives and power systems, intelligent control theories including fuzzy logic, neural networks, and wavelets, nonlinear control, optimal control, and robust control. MD. RABIUL ISLAM (Senior Member, IEEE) received the Ph.D. degree in electrical engineering from the

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