IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i3p709-d317378.html
   My bibliography  Save this article

Optimal Battery Sizing for Electric Truck Delivery

Author

Listed:
  • Donkyu Baek

    (Politecnico di Torino, 10129 Torino, Italy)

  • Yukai Chen

    (Politecnico di Torino, 10129 Torino, Italy)

  • Naehyuck Chang

    (Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea)

  • Enrico Macii

    (Politecnico di Torino, 10129 Torino, Italy)

  • Massimo Poncino

    (Politecnico di Torino, 10129 Torino, Italy)

Abstract

Finding the cost-optimal battery size in the context of parcel delivery with Electric Vehicles (EVs) requires solving a tradeoff between using the largest possible battery (so as to maximize the number of deliveries over a given time) and the relative costs (initial investment plus the unnecessary increase of the truck weight during delivery). In this paper, we propose a framework for the optimal battery sizing for parcel delivery with an electric truck; we implement an electric truck simulator including a nonlinear battery model to evaluate revenue, battery cost, charging cost, and overall profit for annual delivery. Our framework finds the cost-optimal battery size for different parcel weight distributions and customer location distributions. We analyze the effect of battery sizing on the profit, which is up to 56%.

Suggested Citation

  • Donkyu Baek & Yukai Chen & Naehyuck Chang & Enrico Macii & Massimo Poncino, 2020. "Optimal Battery Sizing for Electric Truck Delivery," Energies, MDPI, vol. 13(3), pages 1-15, February.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:3:p:709-:d:317378
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/3/709/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/3/709/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Song, Ziyou & Li, Jianqiu & Han, Xuebing & Xu, Liangfei & Lu, Languang & Ouyang, Minggao & Hofmann, Heath, 2014. "Multi-objective optimization of a semi-active battery/supercapacitor energy storage system for electric vehicles," Applied Energy, Elsevier, vol. 135(C), pages 212-224.
    3. Kyuhyun Sim & Ram Vijayagopal & Namdoo Kim & Aymeric Rousseau, 2019. "Optimization of Component Sizing for a Fuel Cell-Powered Truck to Minimize Ownership Cost," Energies, MDPI, vol. 12(6), pages 1-13, March.
    4. Vora, Ashish P. & Jin, Xing & Hoshing, Vaidehi & Saha, Tridib & Shaver, Gregory & Varigonda, Subbarao & Wasynczuk, Oleg & Tyner, Wallace E., 2017. "Design-space exploration of series plug-in hybrid electric vehicles for medium-duty truck applications in a total cost-of-ownership framework," Applied Energy, Elsevier, vol. 202(C), pages 662-672.
    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. Johannes Karlsson & Anders Grauers, 2023. "Case Study of Cost-Effective Electrification of Long-Distance Line-Haul Trucks," Energies, MDPI, vol. 16(6), pages 1-22, March.
    2. Yukai Chen & Sara Vinco & Donkyu Baek & Stefano Quer & Enrico Macii & Massimo Poncino, 2020. "Cost-Aware Design and Simulation of Electrical Energy Systems," Energies, MDPI, vol. 13(11), pages 1-33, June.
    3. Johannes Karlsson & Anders Grauers, 2023. "Energy Distribution Diagram Used for Cost-Effective Battery Sizing of Electric Trucks," Energies, MDPI, vol. 16(2), pages 1-19, January.
    4. Jahangir Samet, Mehdi & Liimatainen, Heikki & Pihlatie, Mikko & van Vliet, Oscar Patrick René, 2024. "Levelized cost of driving for medium and heavy-duty battery electric trucks," Applied Energy, Elsevier, vol. 361(C).
    5. Donkyu Baek & Yukai Chen & Naehyuck Chang & Enrico Macii & Massimo Poncino, 2020. "Battery-Aware Electric Truck Delivery Route Exploration," Energies, MDPI, vol. 13(8), pages 1-18, April.
    6. Ren, Lei & Zhou, Sheng & Peng, Tianduo & Ou, Xunmin, 2022. "Greenhouse gas life cycle analysis of China's fuel cell medium- and heavy-duty trucks under segmented usage scenarios and vehicle types," Energy, Elsevier, vol. 249(C).
    7. Johannes Karlsson & Anders Grauers, 2023. "Agent-Based Investigation of Charger Queues and Utilization of Public Chargers for Electric Long-Haul Trucks," Energies, MDPI, vol. 16(12), pages 1-25, June.
    8. Wojciech Cieslik & Weronika Antczak, 2023. "Research of Load Impact on Energy Consumption in an Electric Delivery Vehicle Based on Real Driving Conditions: Guidance for Electrification of Light-Duty Vehicle Fleet," Energies, MDPI, vol. 16(2), pages 1-19, January.

    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. Feng, Yanbiao & Dong, Zuomin, 2020. "Integrated design and control optimization of fuel cell hybrid mining truck with minimized lifecycle cost," Applied Energy, Elsevier, vol. 270(C).
    2. Lane, Blake & Kinnon, Michael Mac & Shaffer, Brendan & Samuelsen, Scott, 2022. "Deployment planning tool for environmentally sensitive heavy-duty vehicles and fueling infrastructure," Energy Policy, Elsevier, vol. 171(C).
    3. Wang, Bin & Xu, Jun & Cao, Binggang & Ning, Bo, 2017. "Adaptive mode switch strategy based on simulated annealing optimization of a multi-mode hybrid energy storage system for electric vehicles," Applied Energy, Elsevier, vol. 194(C), pages 596-608.
    4. Gu, Xubo & Bai, Hanyu & Cui, Xiaofan & Zhu, Juner & Zhuang, Weichao & Li, Zhaojian & Hu, Xiaosong & Song, Ziyou, 2024. "Challenges and opportunities for second-life batteries: Key technologies and economy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    5. Yang, Jibin & Xu, Xiaohui & Peng, Yiqiang & Zhang, Jiye & Song, Pengyun, 2019. "Modeling and optimal energy management strategy for a catenary-battery-ultracapacitor based hybrid tramway," Energy, Elsevier, vol. 183(C), pages 1123-1135.
    6. Muhammad Khalid, 2019. "A Review on the Selected Applications of Battery-Supercapacitor Hybrid Energy Storage Systems for Microgrids," Energies, MDPI, vol. 12(23), pages 1-34, November.
    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. Anselma, Pier Giuseppe, 2022. "Computationally efficient evaluation of fuel and electrical energy economy of plug-in hybrid electric vehicles with smooth driving constraints," Applied Energy, Elsevier, vol. 307(C).
    9. Jiajun Liu & Tianxu Jin & Li Liu & Yajue Chen & Kun Yuan, 2017. "Multi-Objective Optimization of a Hybrid ESS Based on Optimal Energy Management Strategy for LHDs," Sustainability, MDPI, vol. 9(10), pages 1-18, October.
    10. Mehdi Jahangir Samet & Heikki Liimatainen & Oscar Patrick René van Vliet & Markus Pöllänen, 2021. "Road Freight Transport Electrification Potential by Using Battery Electric Trucks in Finland and Switzerland," Energies, MDPI, vol. 14(4), pages 1-22, February.
    11. Jiaming Zhou & Chunxiao Feng & Qingqing Su & Shangfeng Jiang & Zhixian Fan & Jiageng Ruan & Shikai Sun & Leli Hu, 2022. "The Multi-Objective Optimization of Powertrain Design and Energy Management Strategy for Fuel Cell–Battery Electric Vehicle," Sustainability, MDPI, vol. 14(10), pages 1-19, May.
    12. Ren, Lei & Zhou, Sheng & Peng, Tianduo & Ou, Xunmin, 2022. "Greenhouse gas life cycle analysis of China's fuel cell medium- and heavy-duty trucks under segmented usage scenarios and vehicle types," Energy, Elsevier, vol. 249(C).
    13. Jiang, Hongliang & Xu, Liangfei & Li, Jianqiu & Hu, Zunyan & Ouyang, Minggao, 2019. "Energy management and component sizing for a fuel cell/battery/supercapacitor hybrid powertrain based on two-dimensional optimization algorithms," Energy, Elsevier, vol. 177(C), pages 386-396.
    14. Zhou, Quan & Zhang, Wei & Cash, Scott & Olatunbosun, Oluremi & Xu, Hongming & Lu, Guoxiang, 2017. "Intelligent sizing of a series hybrid electric power-train system based on Chaos-enhanced accelerated particle swarm optimization," Applied Energy, Elsevier, vol. 189(C), pages 588-601.
    15. Hou, Jun & Song, Ziyou & Park, Hyeongjun & Hofmann, Heath & Sun, Jing, 2018. "Implementation and evaluation of real-time model predictive control for load fluctuations mitigation in all-electric ship propulsion systems," Applied Energy, Elsevier, vol. 230(C), pages 62-77.
    16. Zhang, Hongtao & Li, Xianguo & Liu, Xinzhi & Yan, Jinyue, 2019. "Enhancing fuel cell durability for fuel cell plug-in hybrid electric vehicles through strategic power management," Applied Energy, Elsevier, vol. 241(C), pages 483-490.
    17. Aharon, Ilan & Shmilovitz, Doron & Kuperman, Alon, 2017. "Multimode power processing interface for fuel cell range extender in battery powered vehicle," Applied Energy, Elsevier, vol. 204(C), pages 572-581.
    18. Diana Lemian & Florin Bode, 2022. "Battery-Supercapacitor Energy Storage Systems for Electrical Vehicles: A Review," Energies, MDPI, vol. 15(15), pages 1-13, August.
    19. Muataz Abotabik & Richard T. Meyer, 2021. "Switched Optimal Control of a Heavy-Duty Hybrid Vehicle," Energies, MDPI, vol. 14(20), pages 1-20, October.
    20. Huang, Jiangfan & An, Qing & Zhou, Mingyu & Tang, Ruoli & Dong, Zhengcheng & Lai, Jingang & Li, Xin & Yang, Xiangguo, 2024. "A self-adaptive joint optimization framework for marine hybrid energy storage system design considering load fluctuation characteristics," Applied Energy, Elsevier, vol. 361(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:gam:jeners:v:13:y:2020:i:3:p:709-:d:317378. 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.