IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i4p665-d207136.html
   My bibliography  Save this article

Comparison of Three Methods for Constructing Real Driving Cycles

Author

Listed:
  • José Ignacio Huertas

    (Energy and Climate Change Research Group, Tecnológico de Monterrey, Monterrey 64849, Mexico)

  • Luis Felipe Quirama

    (Grupo de Investigación en Gestión Energética, Universidad Tecnológica de Pereira, Pereira 660003, Colombia)

  • Michael Giraldo

    (Energy and Climate Change Research Group, Tecnológico de Monterrey, Monterrey 64849, Mexico)

  • Jenny Díaz

    (Department of Engineering, Universidad de Monterrey, Monterrey 66238, Mexico)

Abstract

This work compares the Micro-trips (MT), Markov chains–Monte Carlo (MCMC) and Fuel-based (FB) methods in their ability of constructing driving cycles (DC) that: (i) describe the real driving patterns of a given region and (ii) reproduce the real fuel consumption and emissions exhibited by the vehicles in that region. To that end, we selected four regions and monitored simultaneously the speed, fuel consumption and emissions of CO 2 , CO and NO x from a fleet of 15 buses of the same technology during eight months of normal operation. The driving patterns exhibited by drivers in each region were described in terms of 23 characteristic parameters (CPs) such as average speed and average positive kinetic energy. Then, for each region, we constructed their DC using the MT method and evaluated how close it describes the observed driving pattern in each region. We repeated the process using the MCMC and FB methods. Given the stochastic nature of MT and MCMC methods, the DCs obtained changed every time the methods were applied. Hence, we repeated the process of constructing the DCs up to 1000 times and reported their average relative differences and dispersion. We observed that the FB method exhibited the best performance producing DCs that describe the observed driving patterns. In all the regions considered in this study, the DCs produced by this method showed average relative differences smaller than 20% for all the CPs considered. A similar performance was observed for the case of fuel consumption and emission of pollutants.

Suggested Citation

  • José Ignacio Huertas & Luis Felipe Quirama & Michael Giraldo & Jenny Díaz, 2019. "Comparison of Three Methods for Constructing Real Driving Cycles," Energies, MDPI, vol. 12(4), pages 1-15, February.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:4:p:665-:d:207136
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/4/665/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/12/4/665/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ntziachristos, L. & Mellios, G. & Tsokolis, D. & Keller, M. & Hausberger, S. & Ligterink, N.E. & Dilara, P., 2014. "In-use vs. type-approval fuel consumption of current passenger cars in Europe," Energy Policy, Elsevier, vol. 67(C), pages 403-411.
    2. José I. Huertas & Michael Giraldo & Luis F. Quirama & Jenny Díaz, 2018. "Driving Cycles Based on Fuel Consumption," Energies, MDPI, vol. 11(11), pages 1-13, November.
    3. Brady, John & O’Mahony, Margaret, 2016. "Development of a driving cycle to evaluate the energy economy of electric vehicles in urban areas," Applied Energy, Elsevier, vol. 177(C), pages 165-178.
    4. Tietge, Uwe & Mock, Peter & Franco, Vicente & Zacharof, Nikiforos, 2017. "From laboratory to road: Modeling the divergence between official and real-world fuel consumption and CO2 emission values in the German passenger car market for the years 2001–2014," Energy Policy, Elsevier, vol. 103(C), pages 212-222.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Li Zhao & Kun Li & Wu Zhao & Han-Chen Ke & Zhen Wang, 2022. "A Sticky Sampling and Markov State Transition Matrix Based Driving Cycle Construction Method for EV," Energies, MDPI, vol. 15(3), pages 1-19, January.
    2. Guilherme Medeiros Soares de Andrade & Fernando Wesley Cavalcanti de Araújo & Maurício Pereira Magalhães de Novaes Santos & Fabio Santana Magnani, 2020. "Standardized Comparison of 40 Local Driving Cycles: Energy and Kinematics," Energies, MDPI, vol. 13(20), pages 1-20, October.

    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. Yu, Rujie & Ren, Huanhuan & Liu, Yong & Yu, Biying, 2021. "Gap between on-road and official fuel efficiency of passenger vehicles in China," Energy Policy, Elsevier, vol. 152(C).
    2. José I. Huertas & Michael Giraldo & Luis F. Quirama & Jenny Díaz, 2018. "Driving Cycles Based on Fuel Consumption," Energies, MDPI, vol. 11(11), pages 1-13, November.
    3. Zvonimir Dabčević & Branimir Škugor & Jakov Topić & Joško Deur, 2022. "Synthesis of Driving Cycles Based on Low-Sampling-Rate Vehicle-Tracking Data and Markov Chain Methodology," Energies, MDPI, vol. 15(11), pages 1-21, June.
    4. Aderiana Mutheu Mbandi & Jan R. Böhnke & Dietrich Schwela & Harry Vallack & Mike R. Ashmore & Lisa Emberson, 2019. "Estimating On-Road Vehicle Fuel Economy in Africa: A Case Study Based on an Urban Transport Survey in Nairobi, Kenya," Energies, MDPI, vol. 12(6), pages 1-28, March.
    5. Mogno, Caterina & Fontaras, Georgios & Arcidiacono, Vincenzo & Komnos, Dimitrios & Pavlovic, Jelica & Ciuffo, Biagio & Makridis, Michail & Valverde, Victor, 2022. "The application of the CO2MPAS model for vehicle CO2 emissions estimation over real traffic conditions," Transport Policy, Elsevier, vol. 124(C), pages 152-159.
    6. Fan, Pengfei & Yin, Hang & Lu, Hongyu & Wu, Yizheng & Zhai, Zhiqiang & Yu, Lei & Song, Guohua, 2023. "Which factor contributes more to the fuel consumption gap between in-laboratory vs. real-world driving conditions? An independent component analysis," Energy Policy, Elsevier, vol. 182(C).
    7. Küng, Lukas & Bütler, Thomas & Georges, Gil & Boulouchos, Konstantinos, 2019. "How much energy does a car need on the road?," Applied Energy, Elsevier, vol. 256(C).
    8. Bishop, Justin D.K. & Molden, N. & Boies, Adam M, 2019. "Using portable emissions measurement systems (PEMS) to derive more accurate estimates of fuel use and nitrogen oxides emissions from modern Euro 6 passenger cars under real-world driving conditions," Applied Energy, Elsevier, vol. 242(C), pages 942-973.
    9. Craglia, Matteo & Cullen, Jonathan, 2019. "Do technical improvements lead to real efficiency gains? Disaggregating changes in transport energy intensity," Energy Policy, Elsevier, vol. 134(C).
    10. Tsiakmakis, Stefanos & Fontaras, Georgios & Dornoff, Jan & Valverde, Victor & Komnos, Dimitrios & Ciuffo, Biagio & Mock, Peter & Samaras, Zissis, 2019. "From lab-to-road & vice-versa: Using a simulation-based approach for predicting real-world CO2 emissions," Energy, Elsevier, vol. 169(C), pages 1153-1165.
    11. Triantafyllopoulos, Georgios & Kontses, Anastasios & Tsokolis, Dimitrios & Ntziachristos, Leonidas & Samaras, Zissis, 2017. "Potential of energy efficiency technologies in reducing vehicle consumption under type approval and real world conditions," Energy, Elsevier, vol. 140(P1), pages 365-373.
    12. Zhang, Shaojun & Wu, Ye & Un, Puikei & Fu, Lixin & Hao, Jiming, 2016. "Modeling real-world fuel consumption and carbon dioxide emissions with high resolution for light-duty passenger vehicles in a traffic populated city," Energy, Elsevier, vol. 113(C), pages 461-471.
    13. Bossink, Bart A.G., 2017. "Demonstrating sustainable energy: A review based model of sustainable energy demonstration projects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 1349-1362.
    14. Nicu Bizon & Mircea Raceanu & Emmanouel Koudoumas & Adriana Marinoiu & Emmanuel Karapidakis & Elena Carcadea, 2020. "Renewable/Fuel Cell Hybrid Power System Operation Using Two Search Controllers of the Optimal Power Needed on the DC Bus," Energies, MDPI, vol. 13(22), pages 1-26, November.
    15. Ye, Rui-Ke & Gao, Zhuang-Fei & Fang, Kai & Liu, Kang-Li & Chen, Jia-Wei, 2021. "Moving from subsidy stimulation to endogenous development: A system dynamics analysis of China's NEVs in the post-subsidy era," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    16. Emilia M. Szumska & Rafał S. Jurecki, 2021. "Parameters Influencing on Electric Vehicle Range," Energies, MDPI, vol. 14(16), pages 1-23, August.
    17. Zacharof, Nikiforos & Tietge, Uwe & Franco, Vicente & Mock, Peter, 2016. "Type approval and real-world CO2 and NOx emissions from EU light commercial vehicles," Energy Policy, Elsevier, vol. 97(C), pages 540-548.
    18. Nils Hooftman & Luis Oliveira & Maarten Messagie & Thierry Coosemans & Joeri Van Mierlo, 2016. "Environmental Analysis of Petrol, Diesel and Electric Passenger Cars in a Belgian Urban Setting," Energies, MDPI, vol. 9(2), pages 1-24, January.
    19. Tianming Gao & Vasilii Erokhin & Aleksandr Arskiy, 2019. "Dynamic Optimization of Fuel and Logistics Costs as a Tool in Pursuing Economic Sustainability of a Farm," Sustainability, MDPI, vol. 11(19), pages 1-16, October.
    20. Jiangbo Wang & Kai Liu & Toshiyuki Yamamoto, 2017. "Improving Electricity Consumption Estimation for Electric Vehicles Based on Sparse GPS Observations," Energies, MDPI, vol. 10(1), pages 1-12, January.

    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:jeners:v:12:y:2019:i:4:p:665-:d:207136. 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.