Integrated drive cycle analysis for fuzzy logic based energy management in hybrid vehicles

This paper proposes a "traffic situation awareness" driven intelligent agent for energy management of parallel hybrid vehicles. A coordinating device that governs energy flow in the powertrain is proposed based on the idea that driving environment (traffic situation) as well as the vehicle's mode of operation and the style of driver behavior directly affect fuel usage and pollutant emissions. For the realization of driving situation awareness, identification processes for roadway type is performed by extracting the driving information from the (past) driving data. Expert knowledge that characterizes the relationship between the driving situation and fuel consumption and emissions is implemented in the fuzzy torque distributor that performs intelligent decisionmaking for the torque distribution task. Charge sustenance operation is performed in the State-of-Charge (SOC) compensator to keep the level of the state of charge within prescribed levels. The mission of the energy management system, so called Intelligent Energy Management Agent (IEMA), is to enable the vehicle to be driven in an economically and environmentally friendly way while satisfying the driver's performance demand. Simulation work is carried out for the validation of proposed IEMA, and the results reveal its viability for energy management of a parallel hybrid vehicle.