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A fuel-optimal driving strategy for a single vehicle with CVT

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  • Tang, Tie-Qiao
  • Liao, Peng
  • Ou, Hui
  • Zhang, Jian

Abstract

The efficiency of the continuously variable transmission (CVT) is within 70∼95%, so the effects on the fuel consumption cannot be ignored. In this paper, we first analyze the quantitative relationship between the running states of inertial combustion engine with CVT and the fuel consumption, and then propose a fuel-optimal driving strategy for a vehicle with CVT. In the strategy, the vehicle speed and acceleration, the engine torque and speed, and the CVT ratio in the processes of acceleration, uniform motion and deceleration are calculated. The numerical results show that when the driving distance is less than a critical value, this vehicle experiences an acceleration–deceleration process, otherwise this vehicle experiences an acceleration–constant–deceleration process. The results can provide a fuel-optimal strategy for a vehicle under different driving distance, which can be used to the human driving guidance, the driving assistance system and the autonomous vehicles.

Suggested Citation

  • Tang, Tie-Qiao & Liao, Peng & Ou, Hui & Zhang, Jian, 2018. "A fuel-optimal driving strategy for a single vehicle with CVT," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 114-123.
    • Handle: RePEc:eee:phsmap:v:505:y:2018:i:c:p:114-123
    DOI: 10.1016/j.physa.2018.03.050
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    References listed on IDEAS

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    1. Cheng, Rongjun & Ge, Hongxia & Sun, Fengxin & Wang, Jufeng, 2018. "An extended macro model accounting for acceleration changes with memory and numerical tests," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 270-283.
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    5. Ou, Hui & Tang, Tie-Qiao, 2018. "An extended two-lane car-following model accounting for inter-vehicle communication," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 260-268.
    6. Sharma, Sapna, 2015. "Lattice hydrodynamic modeling of two-lane traffic flow with timid and aggressive driving behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 401-411.
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    Citations

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    Cited by:

    1. Liao, Peng & Tang, Tie-Qiao & Wang, Tao & Zhang, Jian, 2019. "A car-following model accounting for the driving habits," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 108-118.
    2. Shi, Xiaoyu & Zhang, Jian & Jiang, Xia & Chen, Juan & Hao, Wei & Wang, Bo, 2024. "Learning eco-driving strategies from human driving trajectories," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 633(C).
    3. Qiao, Yan-feng & Xue, Yu & Wang, Xue & Cen, Bing-ling & Wang, Yi & Pan, Wei & Zhang, Yan-xin, 2021. "Investigation of PM emissions in cellular automata model with slow-to-start effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    4. de Salvo Junior, Orlando & Saraiva de Souza, Maria Tereza & Vaz de Almeida, Flávio G., 2021. "Implementation of new technologies for reducing fuel consumption of automobiles in Brazil according to the Brazilian Vehicle Labelling Programme," Energy, Elsevier, vol. 233(C).
    5. Wang, Xue & Xue, Yu & Cen, Bing-ling & Zhang, Peng & He, Hong-di, 2020. "Study on pollutant emissions of mixed traffic flow in cellular automaton," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    6. Salvo, Orlando de & Vaz de Almeida, Flávio G., 2019. "Influence of technologies on energy efficiency results of official Brazilian tests of vehicle energy consumption," Applied Energy, Elsevier, vol. 241(C), pages 98-112.

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