IDEAS home Printed from https://ideas.repec.org/a/kap/transp/v46y2019i6d10.1007_s11116-018-9925-0.html
   My bibliography  Save this article

The influence of passenger load, driving cycle, fuel price and different types of buses on the cost of transport service in the BRT system in Curitiba, Brazil

Author

Listed:
  • Dennis Dreier

    (KTH Royal Institute of Technology)

  • Semida Silveira

    (KTH Royal Institute of Technology)

  • Dilip Khatiwada

    (KTH Royal Institute of Technology)

  • Keiko V. O. Fonseca

    (Federal University of Technology – Paraná (UTFPR))

  • Rafael Nieweglowski

    (Volvo Bus Corporation)

  • Renan Schepanski

    (Volvo Bus Corporation)

Abstract

This study analyses the influence of passenger load, driving cycle, fuel price and four different types of buses on the cost of transport service for one bus rapid transit (BRT) route in Curitiba, Brazil. First, the energy use is estimated for different passenger loads and driving cycles for a conventional bi-articulated bus (ConvBi), a hybrid-electric two-axle bus (HybTw), a hybrid-electric articulated bus (HybAr) and a plug-in hybrid-electric two-axle bus (PlugTw). Then, the fuel cost and uncertainty are estimated considering the fuel price trends in the past. Based on this and additional cost data, replacement scenarios for the currently operated ConvBi fleet are determined using a techno-economic optimisation model. The lowest fuel cost ranges for the passenger load are estimated for PlugTw amounting to (0.198–0.289) USD/km, followed by (0.255–0.315) USD/km for HybTw, (0.298–0.375) USD/km for HybAr and (0.552–0.809) USD/km for ConvBi. In contrast, the coefficient of variation ($$C_{v}$$Cv) of the combined standard uncertainty is the highest for PlugTw ($$C_{v}$$Cv: 15–17%) due to stronger sensitivity to varying bus driver behaviour, whereas it is the least for ConvBi ($$C_{v}$$Cv: 8%). The scenario analysis shows that a complete replacement of the ConvBi fleet leads to considerable higher cost of transport service on the BRT route, amounting to an increase by 64% to 139%, depending on the bus fleet composition. Meanwhile, the service quality is improved resulting in 42% up to 64% less waiting time for passengers at a bus stop.

Suggested Citation

  • Dennis Dreier & Semida Silveira & Dilip Khatiwada & Keiko V. O. Fonseca & Rafael Nieweglowski & Renan Schepanski, 2019. "The influence of passenger load, driving cycle, fuel price and different types of buses on the cost of transport service in the BRT system in Curitiba, Brazil," Transportation, Springer, vol. 46(6), pages 2195-2242, December.
    • Handle: RePEc:kap:transp:v:46:y:2019:i:6:d:10.1007_s11116-018-9925-0
    DOI: 10.1007/s11116-018-9925-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11116-018-9925-0
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11116-018-9925-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhang, Shaojun & Wu, Ye & Liu, Huan & Huang, Ruikun & Un, Puikei & Zhou, Yu & Fu, Lixin & Hao, Jiming, 2014. "Real-world fuel consumption and CO2 (carbon dioxide) emissions by driving conditions for light-duty passenger vehicles in China," Energy, Elsevier, vol. 69(C), pages 247-257.
    2. Ribau, João P. & Sousa, João M.C. & Silva, Carla M., 2015. "Reducing the carbon footprint of urban bus fleets using multi-objective optimization," Energy, Elsevier, vol. 93(P1), pages 1089-1104.
    3. Ribau, João P. & Silva, Carla M. & Sousa, João M.C., 2014. "Efficiency, cost and life cycle CO2 optimization of fuel cell hybrid and plug-in hybrid urban buses," Applied Energy, Elsevier, vol. 129(C), pages 320-335.
    4. Kwang Kim & Seung-hoon Cheon & Sam-jin Lim, 2011. "Performance assessment of bus transport reform in Seoul," Transportation, Springer, vol. 38(5), pages 719-735, September.
    5. Ma, Hongrui & Balthasar, Felix & Tait, Nigel & Riera-Palou, Xavier & Harrison, Andrew, 2012. "A new comparison between the life cycle greenhouse gas emissions of battery electric vehicles and internal combustion vehicles," Energy Policy, Elsevier, vol. 44(C), pages 160-173.
    6. Ke, Bwo-Ren & Chung, Chen-Yuan & Chen, Yen-Chang, 2016. "Minimizing the costs of constructing an all plug-in electric bus transportation system: A case study in Penghu," Applied Energy, Elsevier, vol. 177(C), pages 649-660.
    7. Saxe, M. & Folkesson, A. & Alvfors, P., 2008. "Energy system analysis of the fuel cell buses operated in the project: Clean Urban Transport for Europe," Energy, Elsevier, vol. 33(5), pages 689-711.
    8. Wang, Hewu & Zhang, Xiaobin & Ouyang, Minggao, 2015. "Energy consumption of electric vehicles based on real-world driving patterns: A case study of Beijing," Applied Energy, Elsevier, vol. 157(C), pages 710-719.
    9. Xu, Yanzhi & Gbologah, Franklin E. & Lee, Dong-Yeon & Liu, Haobing & Rodgers, Michael O. & Guensler, Randall L., 2015. "Assessment of alternative fuel and powertrain transit bus options using real-world operations data: Life-cycle fuel and emissions modeling," Applied Energy, Elsevier, vol. 154(C), pages 143-159.
    10. Hellgren, Jonas, 2007. "Life cycle cost analysis of a car, a city bus and an intercity bus powertrain for year 2005 and 2020," Energy Policy, Elsevier, vol. 35(1), pages 39-49, January.
    11. Luigi dell’Olio & Angel Ibeas & Francisco Ruisánchez, 2012. "Optimizing bus-size and headway in transit networks," Transportation, Springer, vol. 39(2), pages 449-464, March.
    12. Yu, Qian & Li, Tiezhu & Li, Hu, 2016. "Improving urban bus emission and fuel consumption modeling by incorporating passenger load factor for real world driving," Applied Energy, Elsevier, vol. 161(C), pages 101-111.
    13. Xu, Yanzhi & Li, Hanyan & Liu, Haobing & Rodgers, Michael O. & Guensler, Randall L., 2017. "Eco-driving for transit: An effective strategy to conserve fuel and emissions," Applied Energy, Elsevier, vol. 194(C), pages 784-797.
    14. Onat, Nuri Cihat & Kucukvar, Murat & Tatari, Omer, 2015. "Conventional, hybrid, plug-in hybrid or electric vehicles? State-based comparative carbon and energy footprint analysis in the United States," Applied Energy, Elsevier, vol. 150(C), pages 36-49.
    15. Farkas, Ferenc & Nagy, Valéria & Bai, Attila, 2014. "Tests of Differential Diesel Fuels in Engine Testing Room," APSTRACT: Applied Studies in Agribusiness and Commerce, AGRIMBA, vol. 8(1), pages 1-8.
    16. Correa, G. & Muñoz, P. & Falaguerra, T. & Rodriguez, C.R., 2017. "Performance comparison of conventional, hybrid, hydrogen and electric urban buses using well to wheel analysis," Energy, Elsevier, vol. 141(C), pages 537-549.
    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. Timilsina,Govinda R. & Malla,Sunil, 2021. "Do Investments in Clean Technologies Reduce Production Costs ? Insights from the Literature," Policy Research Working Paper Series 9714, The World Bank.
    2. Kumar, Ashok & Singh, Dilip & Mahapatra, S.K., 2022. "Energy and carbon budgeting of the pearl millet-wheat cropping system for environmentally sustainable agricultural land use planning in the rainfed semi-arid agro-ecosystem of Aravalli foothills," Energy, Elsevier, vol. 246(C).
    3. Dennis Dreier & Björn Rudin & Mark Howells, 2020. "Comparison of management strategies for the charging schedule and all-electric operation of a plug-in hybrid-electric bi-articulated bus fleet," Public Transport, Springer, vol. 12(2), pages 363-404, June.

    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. Ji, Wei, 2018. "Data-Driven Behavior Analysis and Implications in Plug-in Electric Vehicle Policy Studies," Institute of Transportation Studies, Working Paper Series qt6dw4d18t, Institute of Transportation Studies, UC Davis.
    2. Ali Saadon Al-Ogaili & Ali Q. Al-Shetwi & Hussein M. K. Al-Masri & Thanikanti Sudhakar Babu & Yap Hoon & Khaled Alzaareer & N. V. Phanendra Babu, 2021. "Review of the Estimation Methods of Energy Consumption for Battery Electric Buses," Energies, MDPI, vol. 14(22), pages 1-28, November.
    3. Dennis Dreier & Björn Rudin & Mark Howells, 2020. "Comparison of management strategies for the charging schedule and all-electric operation of a plug-in hybrid-electric bi-articulated bus fleet," Public Transport, Springer, vol. 12(2), pages 363-404, June.
    4. Harris, Andrew & Soban, Danielle & Smyth, Beatrice M. & Best, Robert, 2018. "Assessing life cycle impacts and the risk and uncertainty of alternative bus technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 97(C), pages 569-579.
    5. Harris, Andrew & Soban, Danielle & Smyth, Beatrice M. & Best, Robert, 2020. "A probabilistic fleet analysis for energy consumption, life cycle cost and greenhouse gas emissions modelling of bus technologies," Applied Energy, Elsevier, vol. 261(C).
    6. Nenming Wang & Guwen Tang, 2022. "A Review on Environmental Efficiency Evaluation of New Energy Vehicles Using Life Cycle Analysis," Sustainability, MDPI, vol. 14(6), pages 1-35, March.
    7. Dennis Dreier & Mark Howells, 2019. "OSeMOSYS-PuLP: A Stochastic Modeling Framework for Long-Term Energy Systems Modeling," Energies, MDPI, vol. 12(7), pages 1-26, April.
    8. Marmiroli, Benedetta & Venditti, Mattia & Dotelli, Giovanni & Spessa, Ezio, 2020. "The transport of goods in the urban environment: A comparative life cycle assessment of electric, compressed natural gas and diesel light-duty vehicles," Applied Energy, Elsevier, vol. 260(C).
    9. 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.
    10. Paul Baustert & Tomás Navarrete Gutiérrez & Thomas Gibon & Laurent Chion & Tai-Yu Ma & Gabriel Leite Mariante & Sylvain Klein & Philippe Gerber & Enrico Benetto, 2019. "Coupling Activity-Based Modeling and Life Cycle Assessment—A Proof-of-Concept Study on Cross-Border Commuting in Luxembourg," Sustainability, MDPI, vol. 11(15), pages 1-24, July.
    11. Crossin, Enda & Doherty, Peter J.B., 2016. "The effect of charging time on the comparative environmental performance of different vehicle types," Applied Energy, Elsevier, vol. 179(C), pages 716-726.
    12. Ribau, João P. & Sousa, João M.C. & Silva, Carla M., 2015. "Reducing the carbon footprint of urban bus fleets using multi-objective optimization," Energy, Elsevier, vol. 93(P1), pages 1089-1104.
    13. Siqin Xiong & Junping Ji & Xiaoming Ma, 2019. "Comparative Life Cycle Energy and GHG Emission Analysis for BEVs and PhEVs: A Case Study in China," Energies, MDPI, vol. 12(5), pages 1-17, March.
    14. Xianchun Tan & Yuan Zeng & Baihe Gu & Yi Wang & Baoguang Xu, 2018. "Scenario Analysis of Urban Road Transportation Energy Demand and GHG Emissions in China—A Case Study for Chongqing," Sustainability, MDPI, vol. 10(6), pages 1-32, June.
    15. Bigazzi, Alexander, 2019. "Comparison of marginal and average emission factors for passenger transportation modes," Applied Energy, Elsevier, vol. 242(C), pages 1460-1466.
    16. Xu, Yanzhi & Gbologah, Franklin E. & Lee, Dong-Yeon & Liu, Haobing & Rodgers, Michael O. & Guensler, Randall L., 2015. "Assessment of alternative fuel and powertrain transit bus options using real-world operations data: Life-cycle fuel and emissions modeling," Applied Energy, Elsevier, vol. 154(C), pages 143-159.
    17. Cui, Yuepeng & Xu, Hao & Zou, Fumin & Chen, Zhihui & Gong, Kuangmin, 2021. "Optimization based method to develop representative driving cycle for real-world fuel consumption estimation," Energy, Elsevier, vol. 235(C).
    18. Kain Glensor & María Rosa Muñoz B., 2019. "Life-Cycle Assessment of Brazilian Transport Biofuel and Electrification Pathways," Sustainability, MDPI, vol. 11(22), pages 1-31, November.
    19. Wen, Jianping & Zhao, Dan & Zhang, Chuanwei, 2020. "An overview of electricity powered vehicles: Lithium-ion battery energy storage density and energy conversion efficiency," Renewable Energy, Elsevier, vol. 162(C), pages 1629-1648.
    20. Tu, Ran & Gai, Yijun (Jessie) & Farooq, Bilal & Posen, Daniel & Hatzopoulou, Marianne, 2020. "Electric vehicle charging optimization to minimize marginal greenhouse gas emissions from power generation," Applied Energy, Elsevier, vol. 277(C).

    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:kap:transp:v:46:y:2019:i:6:d:10.1007_s11116-018-9925-0. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.