The drivers' hysteretic perception to surrounding environment will affect vehicular fuel economy, especially for the heavy-duty vehicles driving under complex conditions and long distance in mountainous areas. Unreasonable acceleration or deceleration on the slope will increase the fuel consumption. Improving the performance of the engine and the transmission system has limited energy saving potential, and most fuel-efficient driving assistant systems don't consider the road conditions. The main purpose of this research is to introduce an economic driving scheme with consideration of the prestored slope information in which the vehicle speed in mountainous slopes is reasonably planned to guide the driver's behavior for reduction of the fuel consumption. Economic driving optimization algorithm with low space dimension and fast computation speed is established to plan accurate and real-time economic driving scheme. The optimization algorithm with less dependence on experimental data of the fuel consumption characteristics has good adaptability to various vehicles. The slope gradient and length are measured and stored in real time in the first drive and will be used for the optimization in the future drive when a vehicle is on same slopes. Economic driving scheme will guide the driver to adjust the vehicle speed reasonably during the uphill process and distribute working time of the engine brake and the wheel brakes effectively during the downhill process so as to reduce the fuel consumption. The simulations are conducted to validate the effectiveness of economic driving optimization algorithm. From the simulation results, economic driving scheme increases the fuel economy by 7% – 12.3% averagely compared with the drive at a constant speed. The transportation costs and the abrasion of the wheel brakes will be effectively reduced when economic driving scheme is applied to advanced driver assistance systems.


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    Titel :

    Fuel-Efficient Driving for Motor Vehicles Based on Slope Recognition


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:
    Mei, Binyu (Autor:in) / Tan, Gangfeng (Autor:in) / Ping, Xianyao (Autor:in) / Wu, Yahui (Autor:in) / Pang, Yuxin (Autor:in)

    Kongress:

    WCX™ 17: SAE World Congress Experience ; 2017



    Erscheinungsdatum :

    2017-03-28




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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