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An experimental ultra lightweight compact vehicle named “the Waseda Future Vehicle” has been designed and developed, aiming at a simultaneous achievement of low exhaust gas emissions, high fuel economy and driving performance. The vehicle is powered by a dual-type hybrid system having a SI engine, electric motor and generator. A high performance lithium-ion battery unit is used for electricity storage. A variety of driving cycles were reproduced using the hybrid vehicle on a chassis dynamometer. By changing the logics and parameters in the electronic control unit (ECU) of the engine, a significant improvement in emissions was possible, achieving a very high fuel economy of 34 km/h at the Japanese 10-15 drive mode. At the same time, a numerical simulation model has been developed to predict fuel economy. This would be very useful in determining design factors and optimizing operating conditions in the hybrid power system.

For a series hybrid electric vehicle (SHEV), the electric motor is responsible for driving the wheels, while the engine drives the only generator to provide electricity. SHEVs set a control strategy to make the engine run near the fixed operating point with high thermal efficiency, thereby effectively reducing fuel consumption. The powertrain system of HEV is more complex than that of a conventional drive system using only an internal combustion engine, and it is time-consuming to obtain the optimal components specification values and control parameters. Therefore, automatic optimization methods are required nowadays. We used Genetic Algorithm (GA) as the optimization method and optimize powertrain specifications and control parameter values to reduce fuel consumption. The results show that it is an effective optimization method.