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Engine-off strategy are popular used in hybrid electric vehicles (HEV) for fuel saving. The engine of an HEV will start and stop frequently according to the road condition. In order to obtain excellent fuel economy and emissions performance, the fuel injection during engine quick start should be optimized. In this paper, the characteristic of mixture formation and the HC emissions at the first 5 cycles which contribute the most HCs were investigated. After the analysis of mixture preparation during start process, the HC emissions during engine quick start were optimized by means of cycle-by-cycle fuel injection control strategy. The fuel mixture concentration during start-up process fluctuates more dramatically under hot start condition. Typically, the mixture at 4th and 5th cycle is over-riched. Based on the original engine calibration, the fuel injection at the initial 5 cycles was optimized respectively.

According to the requirements of two-wheel vehicle's future market and the characteristic of urban road conditions in China, the advantages and disadvantages of three basic configurations for the Hybrid Electric Vehicle are compared, finally, the serial hybrid configuration is chosen to be applied to hybrid Electric Moped solution. The selection principle of main components of this hybrid powertrain system includes ICE, generator, battery and hub motor, and the optimal match for performance parameters of these components are introduced in this paper. Then, a hybrid system model is established based on AVL-CRUISE. The simulations of fuel efficiency and exhaust emissions for both serial hybrid moped and conventional motorcycle is offered.

In this paper an estimation method on location of peak pressure (LPP) employing flame ionization measurement, with the spark plug as a sensor, was discussed to achieve combustion parameters estimation at quick start of HEV engines. Through the cycle-based ion signal analysis, the location of peak pressure can be extracted in individual cylinder for the optimization of engine quick start control of HEV engine. A series of quick start processes with different cranking speed and engine coolant temperature are tested for establishing the relationship between the ion signals and the combustion parameters. An Artificial Neural Network (ANN) algorithm is used in this study for estimating these two combustion parameters. The experiment results show that the location of peak pressure can be well established by this method.