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Assessment of Energy Consumption Characteristics of Ultra-Heavy-Duty Vehicles under Real Driving Conditions

Author

Listed:
  • Seongin Jo

    (School of Mechanical Engineering, Chonnam National University, 77 Yongbong-ro, Buk-gu, Gwangju 61186, Republic of Korea
    These authors contributed equally to this work.)

  • Hyung Jun Kim

    (National Institute of Environmental Research, 42 Hwangyeong-ro, Seo-gu, Inchon 22689, Republic of Korea
    These authors contributed equally to this work.)

  • Sang Il Kwon

    (National Institute of Environmental Research, 42 Hwangyeong-ro, Seo-gu, Inchon 22689, Republic of Korea)

  • Jong Tae Lee

    (National Institute of Environmental Research, 42 Hwangyeong-ro, Seo-gu, Inchon 22689, Republic of Korea)

  • Suhan Park

    (School of Mechanical and Aerospace Engineering, Konkuk University, 120 Neungdong-ro, Gwangjin-gu, Seoul 05029, Republic of Korea)

Abstract

Passenger cars account for the largest share of GHG emissions in the road sector. However, given that the number of heavy-duty vehicles registered is lower but accounts for about a quarter of GHG emissions in the road sector, it is necessary to reduce carbon dioxide (CO 2 ) emissions by improving the fuel efficiency of heavy-duty vehicles. However, experiments using dynamometers during the vehicle development process consume a lot of time and cost. Conversely, simulations can quantitatively analyze the sensitivity of parameters and accelerate optimization. Therefore, in this study, we modeled a heavy-duty vehicle using an AVL Cruise simulation and analyzed the effects of payload, air drag coefficient, and rolling resistance on fuel economy, CO 2 emission, and the valid window ratio among the moving average window (MAW) for three driving routes. When the average vehicle speed was higher, the effect of the air drag coefficient on fuel economy was high. Additionally, when the average vehicle speed was lowered, the effect of the reduced rolling resistance on improving fuel efficiency was higher than that of the reducing air drag. Thus, the fuel efficiency improvement rate according to each 10% decrease in rolling resistance was higher by 2.2%, on average, in the low average speed route. Additionally, it was confirmed that the valid window ratio was high when driving in a section with a high vehicle speed first. Thus, the valid window ratio was almost 100% in the test of the route conditions starting from the highway section.

Suggested Citation

  • Seongin Jo & Hyung Jun Kim & Sang Il Kwon & Jong Tae Lee & Suhan Park, 2023. "Assessment of Energy Consumption Characteristics of Ultra-Heavy-Duty Vehicles under Real Driving Conditions," Energies, MDPI, vol. 16(5), pages 1-18, February.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:5:p:2333-:d:1083564
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    References listed on IDEAS

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    1. Su, Sheng & Ge, Yang & Hou, Pan & Wang, Xin & Wang, Yachao & Lyu, Tao & Luo, Wanyou & Lai, Yitu & Ge, Yunshan & Lyu, Liqun, 2021. "China VI heavy-duty moving average window (MAW) method: Quantitative analysis of the problem, causes, and impacts based on the real driving data," Energy, Elsevier, vol. 225(C).
    2. Isabella Yunfei Zeng & Shiqi Tan & Jianliang Xiong & Xuesong Ding & Yawen Li & Tian Wu, 2021. "Estimation of Real-World Fuel Consumption Rate of Light-Duty Vehicles Based on the Records Reported by Vehicle Owners," Energies, MDPI, vol. 14(23), pages 1-19, November.
    3. Sasanka Katreddi & Arvind Thiruvengadam, 2021. "Trip Based Modeling of Fuel Consumption in Modern Heavy-Duty Vehicles Using Artificial Intelligence," Energies, MDPI, vol. 14(24), pages 1-12, December.
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    Cited by:

    1. Vasyl Mateichyk & Nataliia Kostian & Miroslaw Smieszek & Igor Gritsuk & Valerii Verbovskyi, 2023. "Review of Methods for Evaluating the Energy Efficiency of Vehicles with Conventional and Alternative Power Plants," Energies, MDPI, vol. 16(17), pages 1-25, August.

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