IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i10p6176-d819106.html
   My bibliography  Save this article

Development of a Real-World Eco-Driving Cycle for Motorcycles

Author

Listed:
  • Triluck Kusalaphirom

    (Department of Civil Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, Thailand)

  • Thaned Satiennam

    (Department of Civil Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, Thailand)

  • Wichuda Satiennam

    (Department of Civil Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, Thailand)

  • Atthapol Seedam

    (Faculty of Agriculture and Technology, Rajamangala University of Technology Isan Surin Campus, Surin 32000, Thailand)

Abstract

Climate change is a major issue all around the world. The transportation industry currently accounts for most CO 2 emissions. The goal of this research is to develop a real-world eco-driving cycle for internal combustion engine motorcycles that can reduce fuel consumption and CO 2 emissions. This study developed onboard measuring equipment to measure the speed profile and fuel consumption of a motorcycle driving in real time. A total of 78 motorcycle riders rode a test motorcycle with the onboard equipment along a road network to collect real-world data. All of the collected real-world data were analyzed by cluster analysis based on fuel consumption (km/L) to divide riders into two groups, high-fuel-consumption riders and low-fuel-consumption riders. The collected real-world data of the low-fuel-consumption riders were used to develop a real-world eco-driving cycle, whereas the collected real-world data from the high-fuel-consumption riders were used to develop a real-world non-eco-driving cycle. The CO 2 emissions were calculated by the speed profiles of the developed driving cycles. The findings reveal that the real-world eco-driving cycle provided a fuel consumption rate 39.3% lower than the real-world non-eco-driving cycle. In addition, the real-world eco-driving cycle provided a CO 2 emission rate 17.4% lower than the real-world non-eco-driving cycle. The application of the developed real-world eco-driving cycle for motorcycles is proposed.

Suggested Citation

  • Triluck Kusalaphirom & Thaned Satiennam & Wichuda Satiennam & Atthapol Seedam, 2022. "Development of a Real-World Eco-Driving Cycle for Motorcycles," Sustainability, MDPI, vol. 14(10), pages 1-14, May.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:10:p:6176-:d:819106
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/10/6176/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/10/6176/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhang, Jin & Wang, Zhenpo & Liu, Peng & Zhang, Zhaosheng & Li, Xiaoyu & Qu, Changhui, 2019. "Driving cycles construction for electric vehicles considering road environment: A case study in Beijing," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    2. Subramaniam Saravana Sankar & Yiqun Xia & Julaluk Carmai & Saiprasit Koetniyom, 2020. "Optimal Eco-Driving Cycles for Conventional Vehicles Using a Genetic Algorithm," Energies, MDPI, vol. 13(17), pages 1-15, August.
    3. Chien-Hsun Wu & Yong-Xiang Xu, 2019. "The Optimal Control of Fuel Consumption for a Heavy-Duty Motorcycle with Three Power Sources Using Hardware-in-the-Loop Simulation," Energies, MDPI, vol. 13(1), pages 1-16, December.
    4. Kurani, Kenneth S & Sanguinetti, Angela & Park, Hannah, 2015. ""Actual Results May Vary": A Behavioral Review of Eco-Driving for Policy Makers," Institute of Transportation Studies, Working Paper Series qt39z9766p, Institute of Transportation Studies, UC Davis.
    5. Yang Wang & Alessandra Boggio-Marzet, 2018. "Evaluation of Eco-Driving Training for Fuel Efficiency and Emissions Reduction According to Road Type," Sustainability, MDPI, vol. 10(11), pages 1-16, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mariano Gallo & Mario Marinelli, 2020. "Sustainable Mobility: A Review of Possible Actions and Policies," Sustainability, MDPI, vol. 12(18), pages 1-39, September.
    2. Juan Francisco Coloma & Marta García & Gonzalo Fernández & Andrés Monzón, 2021. "Environmental Effects of Eco-Driving on Courier Delivery," Sustainability, MDPI, vol. 13(3), pages 1-21, January.
    3. Michał Adamczak & Adrianna Toboła & Jadwiga Fijałkowska & Piotr Cyplik & Maciej Tórz, 2020. "Analysis of Incentives to Eco-Driving for Car Rental Companies’ Customers," Sustainability, MDPI, vol. 12(24), pages 1-20, December.
    4. Marek Fertsch & Adrianna Tobola, 2021. "Intelligent Transport Solutions of Logistics 4.0 in the Context of Changes in Driving Style: A Systematic Literature Review," European Research Studies Journal, European Research Studies Journal, vol. 0(2B), pages 850-859.
    5. Alzaghrini, Nadine & Milovanoff, Alexandre & Roy, Riddhiman & Abdul-Manan, Amir F.N. & McKechnie, Jon & Posen, I. Daniel & MacLean, Heather L., 2024. "Closing the GHG mitigation gap with measures targeting conventional gasoline light-duty vehicles – A scenario-based analysis of the U.S. fleet," Applied Energy, Elsevier, vol. 359(C).
    6. Zhang, Jin & Wang, Zhenpo & Liu, Peng & Zhang, Zhaosheng, 2020. "Energy consumption analysis and prediction of electric vehicles based on real-world driving data," Applied Energy, Elsevier, vol. 275(C).
    7. David Watling & Patrícia Baptista & Gonçalo Duarte & Jianbing Gao & Haibo Chen, 2022. "Systematic Method for Developing Reference Driving Cycles Appropriate to Electric L-Category Vehicles," Energies, MDPI, vol. 15(9), pages 1-28, May.
    8. Schücking, Maximilian & Jochem, Patrick, 2021. "Two-stage stochastic program optimizing the cost of electric vehicles in commercial fleets," Applied Energy, Elsevier, vol. 293(C).
    9. Yiwen Zhou & Fengxiang Guo & Simin Wu & Wenyao He & Xuefei Xiong & Zheng Chen & Dingan Ni, 2022. "Safety and Economic Evaluations of Electric Public Buses Based on Driving Behavior," Sustainability, MDPI, vol. 14(17), pages 1-17, August.
    10. Hongli Liu & Weiguo Yun & Bin Li & Mengling Dai & Yangyuhang Wang, 2023. "A Quantitative Study on Driving Behavior Economy Based on Big Data from the Pure Electric Bus," Sustainability, MDPI, vol. 15(10), pages 1-16, May.
    11. Cui, Yuepeng & Zou, Fumin & Xu, Hao & Chen, Zhihui & Gong, Kuangmin, 2022. "A novel optimization-based method to develop representative driving cycle in various driving conditions," Energy, Elsevier, vol. 247(C).
    12. Chih-Chao Chung & Yuh-Ming Cheng & Ru-Chu Shih & Shi-Jer Lou, 2019. "Research on the Learning Effect of the Positive Emotions of "Ship Fuel-Saving Project" APP for Engineering Students," Sustainability, MDPI, vol. 11(4), pages 1-23, February.
    13. Ran Tu & Junshi Xu & Tiezhu Li & Haibo Chen, 2022. "Effective and Acceptable Eco-Driving Guidance for Human-Driving Vehicles: A Review," IJERPH, MDPI, vol. 19(12), pages 1-14, June.
    14. Sanguinetti, Angela & Queen, Ella & Yee, Christopher & Akanesuvan, Kantapon, 2020. "Average impact and important features of onboard eco-driving feedback: A meta-analysis," Institute of Transportation Studies, Working Paper Series qt9hm406d5, Institute of Transportation Studies, UC Davis.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:10:p:6176-:d:819106. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.