IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v296y2024ics0360544224008272.html
   My bibliography  Save this article

Profit-effective component sizing for electric delivery trucks with dual motor coupling powertrain

Author

Listed:
  • Ju, Fei
  • Du, Wei
  • Zhuang, Weichao
  • Li, Bingbing
  • Wang, Tao
  • Wang, Weiwei
  • Ma, Huijie

Abstract

This study proposes a novel component sizing method for electric delivery trucks (EDTs) employing dual motor coupling powertrain (DMCP) to enhance both the energy efficiency and operating profitability. A control-oriented model for the EDT is first established, encompassing the three-mode DMCP dynamics. Variations in component size and mass have been modeled, with consideration of their effects on the load capacity. To maximize the average profit per kilometer over the truck’s lifespan, four objective functions are defined to accommodate to the diverse types of cargo being transported. We formulate the optimization problem in a bi-level form, and propose a solution method that combines particle swarm optimization (PSO) handling parameter filtering with iterative dynamic programming (IDP) to minimize energy consumption. Three real-world delivery tests show that component sizing leads to an increase in the average profit per kilometer by 2.62%–8.10%. Upon evaluating the impact of powertrain and battery mass/volume on cargo capacity, the battery pricing ceases to impact the sizing of components. However, the electricity price and freight significantly influence the optimal size of components. Moreover, a sensitivity analysis focusing on market price factors underscores the importance of component sizing for maximizing profit, particularly in scenarios where freight costs fluctuate in commercial settings.

Suggested Citation

  • Ju, Fei & Du, Wei & Zhuang, Weichao & Li, Bingbing & Wang, Tao & Wang, Weiwei & Ma, Huijie, 2024. "Profit-effective component sizing for electric delivery trucks with dual motor coupling powertrain," Energy, Elsevier, vol. 296(C).
  • Handle: RePEc:eee:energy:v:296:y:2024:i:c:s0360544224008272
    DOI: 10.1016/j.energy.2024.131055
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544224008272
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2024.131055?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. Zhu, Tao & Wills, Richard G.A. & Lot, Roberto & Kong, Xiaodan & Yan, Xingda, 2021. "Optimal sizing and sensitivity analysis of a battery-supercapacitor energy storage system for electric vehicles," Energy, Elsevier, vol. 221(C).
    2. Zhang, Shuo & Xiong, Rui & Zhang, Chengning & Sun, Fengchun, 2016. "An optimal structure selection and parameter design approach for a dual-motor-driven system used in an electric bus," Energy, Elsevier, vol. 96(C), pages 437-448.
    3. Kim, Dong-Min & Lee, Soo-Gyung & Kim, Dae-Kee & Park, Min-Ro & Lim, Myung-Seop, 2022. "Sizing and optimization process of hybrid electric propulsion system for heavy-duty vehicle based on Gaussian process modeling considering traction motor characteristics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    4. Kwon, Kihan & Seo, Minsik & Min, Seungjae, 2020. "Efficient multi-objective optimization of gear ratios and motor torque distribution for electric vehicles with two-motor and two-speed powertrain system," Applied Energy, Elsevier, vol. 259(C).
    5. Maino, Claudio & Misul, Daniela & Musa, Alessia & Spessa, Ezio, 2021. "Optimal mesh discretization of the dynamic programming for hybrid electric vehicles," Applied Energy, Elsevier, vol. 292(C).
    6. Pei, Huanxin & Hu, Xiaosong & Yang, Yalian & Tang, Xiaolin & Hou, Cong & Cao, Dongpu, 2018. "Configuration optimization for improving fuel efficiency of power split hybrid powertrains with a single planetary gear," Applied Energy, Elsevier, vol. 214(C), pages 103-116.
    7. Mahmoodi-k, Mehdi & Montazeri, Morteza & Madanipour, Vahid, 2021. "Simultaneous multi-objective optimization of a PHEV power management system and component sizing in real world traffic condition," Energy, Elsevier, vol. 233(C).
    8. Kiyoung Kim & Namdoo Kim & Jongryeol Jeong & Sunghwan Min & Horim Yang & Ram Vijayagopal & Aymeric Rousseau & Suk Won Cha, 2021. "A Component-Sizing Methodology for a Hybrid Electric Vehicle Using an Optimization Algorithm," Energies, MDPI, vol. 14(11), pages 1-15, May.
    9. Rodriguez, Mauricio & Arcos–Aviles, Diego & Martinez, Wilmar, 2023. "Fuzzy logic-based energy management for isolated microgrid using meta-heuristic optimization algorithms," Applied Energy, Elsevier, vol. 335(C).
    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. Miranda, Matheus H.R. & Silva, Fabrício L. & Lourenço, Maria A.M. & Eckert, Jony J. & Silva, Ludmila C.A., 2022. "Vehicle drivetrain and fuzzy controller optimization using a planar dynamics simulation based on a real-world driving cycle," Energy, Elsevier, vol. 257(C).
    2. Kim, Dong-Min & Lee, Soo-Gyung & Kim, Dae-Kee & Park, Min-Ro & Lim, Myung-Seop, 2022. "Sizing and optimization process of hybrid electric propulsion system for heavy-duty vehicle based on Gaussian process modeling considering traction motor characteristics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    3. Miranda, Matheus H.R. & Silva, Fabrício L. & Lourenço, Maria A.M. & Eckert, Jony J. & Silva, Ludmila C.A., 2022. "Electric vehicle powertrain and fuzzy controller optimization using a planar dynamics simulation based on a real-world driving cycle," Energy, Elsevier, vol. 238(PC).
    4. Kwon, Kihan & Lee, Jung-Hwan & Lim, Sang-Kil, 2023. "Optimization of multi-speed transmission for electric vehicles based on electrical and mechanical efficiency analysis," Applied Energy, Elsevier, vol. 342(C).
    5. Chi T. P. Nguyen & Bảo-Huy Nguyễn & Minh C. Ta & João Pedro F. Trovão, 2023. "Dual-Motor Dual-Source High Performance EV: A Comprehensive Review," Energies, MDPI, vol. 16(20), pages 1-28, October.
    6. Stefano De Pinto & Pablo Camocardi & Christoforos Chatzikomis & Aldo Sorniotti & Francesco Bottiglione & Giacomo Mantriota & Pietro Perlo, 2020. "On the Comparison of 2- and 4-Wheel-Drive Electric Vehicle Layouts with Central Motors and Single- and 2-Speed Transmission Systems," Energies, MDPI, vol. 13(13), pages 1-24, June.
    7. Rodriguez, Mauricio & Arcos-Aviles, Diego & Guinjoan, Francesc, 2024. "Simple fuzzy logic-based energy management for power exchange in isolated multi-microgrid systems: A case study in a remote community in the Amazon region of Ecuador," Applied Energy, Elsevier, vol. 357(C).
    8. Matteo Acquarone & Claudio Maino & Daniela Misul & Ezio Spessa & Antonio Mastropietro & Luca Sorrentino & Enrico Busto, 2023. "Influence of the Reward Function on the Selection of Reinforcement Learning Agents for Hybrid Electric Vehicles Real-Time Control," Energies, MDPI, vol. 16(6), pages 1-22, March.
    9. Youssef Amry & Elhoussin Elbouchikhi & Franck Le Gall & Mounir Ghogho & Soumia El Hani, 2022. "Electric Vehicle Traction Drives and Charging Station Power Electronics: Current Status and Challenges," Energies, MDPI, vol. 15(16), pages 1-30, August.
    10. Zhu, Tao & Wills, Richard G.A. & Lot, Roberto & Ruan, Haijun & Jiang, Zhihao, 2021. "Adaptive energy management of a battery-supercapacitor energy storage system for electric vehicles based on flexible perception and neural network fitting," Applied Energy, Elsevier, vol. 292(C).
    11. 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).
    12. Tang, Yanyan & Zhang, Qi & Li, Yaoming & Li, Hailong & Pan, Xunzhang & Mclellan, Benjamin, 2019. "The social-economic-environmental impacts of recycling retired EV batteries under reward-penalty mechanism," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    13. Wenjian Yang & Changping Li, 2022. "Symmetry Detection and Topological Synthesis of Mechanisms of Powertrains," Energies, MDPI, vol. 15(13), pages 1-22, June.
    14. Md Ragib Ahssan & Mehran Ektesabi & Saman Gorji, 2023. "Evaluation of a Three-Parameter Gearshift Strategy for a Two-Speed Transmission System in Electric Vehicles," Energies, MDPI, vol. 16(5), pages 1-28, March.
    15. Massimiliano Passalacqua & Mauro Carpita & Serge Gavin & Mario Marchesoni & Matteo Repetto & Luis Vaccaro & Sébastien Wasterlain, 2019. "Supercapacitor Storage Sizing Analysis for a Series Hybrid Vehicle," Energies, MDPI, vol. 12(9), pages 1-15, May.
    16. Zheng Shi & Lu Yan & Yingying Hu & Yao Wang & Wenping Qin & Yan Liang & Haibo Zhao & Yongming Jing & Jiaojiao Deng & Zhi Zhang, 2024. "Optimization of Operation Strategy of Multi-Islanding Microgrid Based on Double-Layer Objective," Energies, MDPI, vol. 17(18), pages 1-20, September.
    17. Xiaotao Fei & Yunwu Han & Shaw Voon Wong & Muhammad Amin Azman & Wenlong Shen, 2024. "Design and Testing of Innovative Type of Dual-Motor Drive Electric Wheel Loader," Energies, MDPI, vol. 17(7), pages 1-28, March.
    18. Huang, Ruchen & He, Hongwen & Zhao, Xuyang & Wang, Yunlong & Li, Menglin, 2022. "Battery health-aware and naturalistic data-driven energy management for hybrid electric bus based on TD3 deep reinforcement learning algorithm," Applied Energy, Elsevier, vol. 321(C).
    19. Tian, Yang & Zhang, Yahui & Li, Hongmin & Gao, Jinwu & Swen, Austin & Wen, Guilin, 2023. "Optimal sizing and energy management of a novel dual-motor powertrain for electric vehicles," Energy, Elsevier, vol. 275(C).
    20. Hong, Xianqian & Wu, Jinglai & Zhang, Nong & Wang, Bing, 2022. "Energy efficiency optimization of Simpson planetary gearset based dual-motor powertrains for electric vehicles," Energy, Elsevier, vol. 259(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:eee:energy:v:296:y:2024:i:c:s0360544224008272. 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.journals.elsevier.com/energy .

    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.