IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v132y2020icp30-46.html
   My bibliography  Save this article

Network-level energy consumption estimation for electric vehicles considering vehicle and user heterogeneity

Author

Listed:
  • Wang, Hua
  • Zhao, De
  • Meng, Qiang
  • Ong, Ghim Ping
  • Lee, Der-Horng

Abstract

As a green transport means, electric vehicle (EV) has received widespread attention in recent years and an increasing number of cities have been establishing their EV transport systems including EV fleet management and charging infrastructure. Transport policy-makers are concerning about the system performance of an EV charging system measured by energy consumption and user experience. We in this paper aim to develop an effective method for the expected total energy consumption estimation (ETEC) of EV charging systems deployed in a dense city. To achieve this objective, we firstly introduce the nonlinear charging profile, its impacts on energy consumption as well as user experience, and present an approach for estimating the nonlinear charging time. We then elaborate our method to estimate energy consumption for one-time EV charging by addressing four kinds of energy losses in charging process. Next, charging frequency by considering multi-type EVs, and their heterogeneities and different charging needs for normal and fast charging systems is analyzed in depth. These two together determine the network-wide energy consumption and a pro-rated approach is used to figure out the spatial distribution of energy consumption. A case study of Singapore is conducted in the end to validate the proposed methodology. Numerical results reveal a trade-off between energy saving and user experience, and also demonstrate the importance of considering heterogeneities of driving range, charging preference and daily travel mileage.

Suggested Citation

  • Wang, Hua & Zhao, De & Meng, Qiang & Ong, Ghim Ping & Lee, Der-Horng, 2020. "Network-level energy consumption estimation for electric vehicles considering vehicle and user heterogeneity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 30-46.
    • Handle: RePEc:eee:transa:v:132:y:2020:i:c:p:30-46
    DOI: 10.1016/j.tra.2019.10.010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856419304069
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tra.2019.10.010?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. Apostolaki-Iosifidou, Elpiniki & Codani, Paul & Kempton, Willett, 2017. "Measurement of power loss during electric vehicle charging and discharging," Energy, Elsevier, vol. 127(C), pages 730-742.
    2. Yang, S.C. & Li, M. & Lin, Y. & Tang, T.Q., 2014. "Electric vehicle’s electricity consumption on a road with different slope," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 41-48.
    3. Wang, Hua & Zhao, De & Meng, Qiang & Ong, Ghim Ping & Lee, Der-Horng, 2019. "A four-step method for electric-vehicle charging facility deployment in a dense city: An empirical study in Singapore," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 224-237.
    4. Scarinci, Riccardo & Rast, Frédéric & Bierlaire, Michel, 2017. "Needed reduction in mobility energy consumption to meet the goal of a 2000-watt society," Transportation Research Part A: Policy and Practice, Elsevier, vol. 101(C), pages 133-148.
    5. Burski, Zbigniew & Mijalska-Szewczak, Izabela & Wasilewski, Jacek & Szczepanik, Małgorzata, 2016. "Evaluation of energy consumption of vehicles in EU Trans-European Transport Network," Transportation Research Part A: Policy and Practice, Elsevier, vol. 92(C), pages 120-130.
    6. Fiori, Chiara & Ahn, Kyoungho & Rakha, Hesham A., 2016. "Power-based electric vehicle energy consumption model: Model development and validation," Applied Energy, Elsevier, vol. 168(C), pages 257-268.
    7. Fan Yang & Yuanyuan Xie & Yelin Deng & Chris Yuan, 2018. "Predictive modeling of battery degradation and greenhouse gas emissions from U.S. state-level electric vehicle operation," Nature Communications, Nature, vol. 9(1), pages 1-10, December.
    8. Enjian Yao & Zhiqiang Yang & Yuanyuan Song & Ting Zuo, 2013. "Comparison of Electric Vehicle’s Energy Consumption Factors for Different Road Types," Discrete Dynamics in Nature and Society, Hindawi, vol. 2013, pages 1-7, December.
    9. Cedric De Cauwer & Joeri Van Mierlo & Thierry Coosemans, 2015. "Energy Consumption Prediction for Electric Vehicles Based on Real-World Data," Energies, MDPI, vol. 8(8), pages 1-21, August.
    10. Poudenx, Pascal, 2008. "The effect of transportation policies on energy consumption and greenhouse gas emission from urban passenger transportation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(6), pages 901-909, July.
    11. Liu, Kai & Wang, Jiangbo & Yamamoto, Toshiyuki & Morikawa, Takayuki, 2016. "Modelling the multilevel structure and mixed effects of the factors influencing the energy consumption of electric vehicles," Applied Energy, Elsevier, vol. 183(C), pages 1351-1360.
    12. Gardner, Lauren M. & Duell, Melissa & Waller, S. Travis, 2013. "A framework for evaluating the role of electric vehicles in transportation network infrastructure under travel demand variability," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 76-90.
    13. Chen, T. Donna & Kockelman, Kara M. & Hanna, Josiah P., 2016. "Operations of a shared, autonomous, electric vehicle fleet: Implications of vehicle & charging infrastructure decisions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 243-254.
    14. Wang, Ning & Pan, Huizhong & Zheng, Wenhui, 2017. "Assessment of the incentives on electric vehicle promotion in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 101(C), pages 177-189.
    15. Pelletier, Samuel & Jabali, Ola & Laporte, Gilbert & Veneroni, Marco, 2017. "Battery degradation and behaviour for electric vehicles: Review and numerical analyses of several models," Transportation Research Part B: Methodological, Elsevier, vol. 103(C), pages 158-187.
    16. Plötz, Patrick & Funke, Simon Árpád & Jochem, Patrick, 2018. "The impact of daily and annual driving on fuel economy and CO2 emissions of plug-in hybrid electric vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 331-340.
    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. Wang, Hua & Zhao, De & Cai, Yutong & Meng, Qiang & Ong, Ghim Ping, 2021. "Taxi trajectory data based fast-charging facility planning for urban electric taxi systems," Applied Energy, Elsevier, vol. 286(C).
    2. Breschi, Valentina & Ravazzi, Chiara & Strada, Silvia & Dabbene, Fabrizio & Tanelli, Mara, 2023. "Driving electric vehicles’ mass adoption: An architecture for the design of human-centric policies to meet climate and societal goals," Transportation Research Part A: Policy and Practice, Elsevier, vol. 171(C).
    3. Andrea Di Martino & Seyed Mahdi Miraftabzadeh & Michela Longo, 2022. "Strategies for the Modelisation of Electric Vehicle Energy Consumption: A Review," Energies, MDPI, vol. 15(21), pages 1-20, October.
    4. Hong Gao & Kai Liu & Xinchao Peng & Cheng Li, 2020. "Optimal Location of Fast Charging Stations for Mixed Traffic of Electric Vehicles and Gasoline Vehicles Subject to Elastic Demands," Energies, MDPI, vol. 13(8), pages 1-16, April.
    5. Li, Baicheng & Szeto, W.Y. & Zou, Liang, 2022. "Optimal fare and fleet size regulation in a taxi/ride-sourcing market with congestion effects, emission externalities, and gasoline/electric vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 157(C), pages 215-243.
    6. Liu, Yang & Zhang, Qi & Lyu, Cheng & Liu, Zhiyuan, 2021. "Modelling the energy consumption of electric vehicles under uncertain and small data conditions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 313-328.
    7. Xu, Min & Meng, Qiang, 2020. "Optimal deployment of charging stations considering path deviation and nonlinear elastic demand," Transportation Research Part B: Methodological, Elsevier, vol. 135(C), pages 120-142.

    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. Wang, Hua & Zhao, De & Cai, Yutong & Meng, Qiang & Ong, Ghim Ping, 2021. "Taxi trajectory data based fast-charging facility planning for urban electric taxi systems," Applied Energy, Elsevier, vol. 286(C).
    2. 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.
    3. Adriana Skuza & Emilia M. Szumska & Rafał Jurecki & Artur Pawelec, 2024. "Modeling the Impact of Traffic Parameters on Electric Vehicle Energy Consumption," Energies, MDPI, vol. 17(21), pages 1-19, October.
    4. Zhao, Yang & Wang, Zhenpo & Shen, Zuo-Jun Max & Zhang, Lei & Dorrell, David G. & Sun, Fengchun, 2022. "Big data-driven decoupling framework enabling quantitative assessments of electric vehicle performance degradation," Applied Energy, Elsevier, vol. 327(C).
    5. Al-Wreikat, Yazan & Serrano, Clara & Sodré, José Ricardo, 2021. "Driving behaviour and trip condition effects on the energy consumption of an electric vehicle under real-world driving," Applied Energy, Elsevier, vol. 297(C).
    6. Luin, Blaž & Petelin, Stojan & Al-Mansour, Fouad, 2019. "Microsimulation of electric vehicle energy consumption," Energy, Elsevier, vol. 174(C), pages 24-32.
    7. Vepsäläinen, Jari & Otto, Kevin & Lajunen, Antti & Tammi, Kari, 2019. "Computationally efficient model for energy demand prediction of electric city bus in varying operating conditions," Energy, Elsevier, vol. 169(C), pages 433-443.
    8. Hong Gao & Kai Liu & Xinchao Peng & Cheng Li, 2020. "Optimal Location of Fast Charging Stations for Mixed Traffic of Electric Vehicles and Gasoline Vehicles Subject to Elastic Demands," Energies, MDPI, vol. 13(8), pages 1-16, April.
    9. Huang, Hai-chao & He, Hong-di & Peng, Zhong-ren, 2024. "Urban-scale estimation model of carbon emissions for ride-hailing electric vehicles during operational phase," Energy, Elsevier, vol. 293(C).
    10. Feng, Zhanyu & Zhang, Jian & Jiang, Han & Yao, Xuejian & Qian, Yu & Zhang, Haiyan, 2024. "Energy consumption prediction strategy for electric vehicle based on LSTM-transformer framework," Energy, Elsevier, vol. 302(C).
    11. Li, Hai & Zheng, Peng & Zhang, Tingsheng & Zou, Yingquan & Pan, Yajia & Zhang, Zutao & Azam, Ali, 2021. "A high-efficiency energy regenerative shock absorber for powering auxiliary devices of new energy driverless buses," Applied Energy, Elsevier, vol. 295(C).
    12. Sun, Xilei & Fu, Jianqin, 2024. "Many-objective optimization of BEV design parameters based on gradient boosting decision tree models and the NSGA-III algorithm considering the ambient temperature," Energy, Elsevier, vol. 288(C).
    13. Muhammed Alhanouti & Frank Gauterin, 2024. "A Generic Model for Accurate Energy Estimation of Electric Vehicles," Energies, MDPI, vol. 17(2), pages 1-21, January.
    14. Karol Tucki & Olga Orynycz & Antoni Świć & Mateusz Mitoraj-Wojtanek, 2019. "The Development of Electromobility in Poland and EU States as a Tool for Management of CO 2 Emissions," Energies, MDPI, vol. 12(15), pages 1-22, July.
    15. Asghari, Mohammad & Mirzapour Al-e-hashem, S. Mohammad J., 2021. "Green vehicle routing problem: A state-of-the-art review," International Journal of Production Economics, Elsevier, vol. 231(C).
    16. Andrea Di Martino & Seyed Mahdi Miraftabzadeh & Michela Longo, 2022. "Strategies for the Modelisation of Electric Vehicle Energy Consumption: A Review," Energies, MDPI, vol. 15(21), pages 1-20, October.
    17. Rémy Cleenwerck & Hakim Azaioud & Majid Vafaeipour & Thierry Coosemans & Jan Desmet, 2023. "Impact Assessment of Electric Vehicle Charging in an AC and DC Microgrid: A Comparative Study," Energies, MDPI, vol. 16(7), pages 1-17, April.
    18. Polychronis Spanoudakis & Gerasimos Moschopoulos & Theodoros Stefanoulis & Nikolaos Sarantinoudis & Eftichios Papadokokolakis & Ioannis Ioannou & Savvas Piperidis & Lefteris Doitsidis & Nikolaos C. Ts, 2020. "Efficient Gear Ratio Selection of a Single-Speed Drivetrain for Improved Electric Vehicle Energy Consumption," Sustainability, MDPI, vol. 12(21), pages 1-19, November.
    19. Li, Lifu & Liu, Qin, 2019. "Acceleration curve optimization for electric vehicle based on energy consumption and battery life," Energy, Elsevier, vol. 169(C), pages 1039-1053.
    20. Salina Daud & Wan Noordiana Wan Hanafi & Bamidele Victor Ayodele & Jegatheesan Rajadurai & Siti Indati Mustapa & Nurul Nadiah Ahmad & Wan Mohammad Taufik Wan Abdullah & Siti Norhidayah Toolib & Maryam, 2023. "Residential Consumers’ Lifestyle Energy Usage and Energy Efficiency in Selected States in Malaysia," Energies, MDPI, vol. 16(8), pages 1-18, April.

    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:eee:transa:v:132:y:2020:i:c:p:30-46. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    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.