IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v14y2024i9p1551-d1473561.html
   My bibliography  Save this article

Design and Experimental Testing of Extended-Range Power Supply System for 15 Horsepower Electric Tractor

Author

Listed:
  • Baochao Wang

    (Collaborative Innovation Center for Shandong’s Main Crop Production Equipment and Mechanization, Qingdao Agricultural University, Qingdao 266109, China)

  • Yanshi Lv

    (Collaborative Innovation Center for Shandong’s Main Crop Production Equipment and Mechanization, Qingdao Agricultural University, Qingdao 266109, China)

  • Xianggang Chu

    (Weichai Lovol Intelligent Agricultural Technology Co., Ltd., Weifang 261200, China)

  • Dongwei Wang

    (Collaborative Innovation Center for Shandong’s Main Crop Production Equipment and Mechanization, Qingdao Agricultural University, Qingdao 266109, China)

  • Shuqi Shang

    (Collaborative Innovation Center for Shandong’s Main Crop Production Equipment and Mechanization, Qingdao Agricultural University, Qingdao 266109, China)

Abstract

Electric tractors have many advantages, including high torque, excellent controllability, energy efficiency, a simple structure, and an electric interface for expansion. However, a significant limitation lies in their endurance. This study presents the design of an extended-range power supply system to ensure continuous endurance for an electric tractor. The objective is to provide a continuous power source for our self-developed electric tractor while preserving the benefits of electric propulsion. Extended-range power systems utilize a primary mover, typically an oil-fueled internal combustion engine, to drive the generator for electricity generation, and the generated AC-form electricity is subsequently converted into stable DC bus voltage by a power electronic converter. The hardware and control design of an extended-range power supply system are finalized and validated through experimental trials. The results demonstrate the system’s capability to sustain stable DC bus voltage amidst disruptions such as sudden load shifts and fluctuations in the prime mover’s speed. Even with a 50% sudden load change, the voltage drop is within 12% and can recover to ±3% within 4 s. The extended-range can be used alone without a battery to power the electric tractor, or it can used in parallel with other extended ranges or batteries for power sharing thanks to the droop control ability.

Suggested Citation

  • Baochao Wang & Yanshi Lv & Xianggang Chu & Dongwei Wang & Shuqi Shang, 2024. "Design and Experimental Testing of Extended-Range Power Supply System for 15 Horsepower Electric Tractor," Agriculture, MDPI, vol. 14(9), pages 1-16, September.
    • Handle: RePEc:gam:jagris:v:14:y:2024:i:9:p:1551-:d:1473561
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/14/9/1551/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/14/9/1551/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhang, Xiongwen & Tan, Siew-Chong & Li, Guojun & Li, Jun & Feng, Zhenping, 2013. "Components sizing of hybrid energy systems via the optimization of power dispatch simulations," Energy, Elsevier, vol. 52(C), pages 165-172.
    2. Li, Maobing & Xu, Hui & Li, Weimin & Liu, Yin & Li, Fade & Hu, Yue & Liu, Li, 2016. "The structure and control method of hybrid power source for electric vehicle," Energy, Elsevier, vol. 112(C), pages 1273-1285.
    3. Kafeel Ahmed & Irfan Hussain & Mehdi Seyedmahmoudian & Alex Stojcevski & Saad Mekhilef, 2023. "Voltage Stability and Power Sharing Control of Distributed Generation Units in DC Microgrids," Energies, MDPI, vol. 16(20), pages 1-17, October.
    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. Ji-Won Lee & Mun-Kyeom Kim & Hyung-Joon Kim, 2021. "A Multi-Agent Based Optimization Model for Microgrid Operation with Hybrid Method Using Game Theory Strategy," Energies, MDPI, vol. 14(3), pages 1-21, January.
    2. Sachs, Julia & Sawodny, Oliver, 2016. "Multi-objective three stage design optimization for island microgrids," Applied Energy, Elsevier, vol. 165(C), pages 789-800.
    3. Chauhan, Anurag & Saini, R.P., 2015. "Renewable energy based off-grid rural electrification in Uttarakhand state of India: Technology options, modelling method, barriers and recommendations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 662-681.
    4. Pavković, D. & Hoić, M. & Deur, J. & Petrić, J., 2014. "Energy storage systems sizing study for a high-altitude wind energy application," Energy, Elsevier, vol. 76(C), pages 91-103.
    5. da Silva, Samuel Filgueira & Eckert, Jony Javorski & Corrêa, Fernanda Cristina & Silva, Fabrício Leonardo & Silva, Ludmila C.A. & Dedini, Franco Giuseppe, 2022. "Dual HESS electric vehicle powertrain design and fuzzy control based on multi-objective optimization to increase driving range and battery life cycle," Applied Energy, Elsevier, vol. 324(C).
    6. Caballero, F. & Sauma, E. & Yanine, F., 2013. "Business optimal design of a grid-connected hybrid PV (photovoltaic)-wind energy system without energy storage for an Easter Island's block," Energy, Elsevier, vol. 61(C), pages 248-261.
    7. Chauhan, Anurag & Saini, R.P., 2016. "Techno-economic optimization based approach for energy management of a stand-alone integrated renewable energy system for remote areas of India," Energy, Elsevier, vol. 94(C), pages 138-156.
    8. Zhichao Zhao & Lu Li & Yang Ou & Yi Wang & Shaoyang Wang & Jing Yu & Renhua Feng, 2023. "A Comparative Study on the Energy Flow of Electric Vehicle Batteries among Different Environmental Temperatures," Energies, MDPI, vol. 16(14), pages 1-15, July.
    9. Rigo-Mariani, Rémy & Chea Wae, Sean Ooi & Mazzoni, Stefano & Romagnoli, Alessandro, 2020. "Comparison of optimization frameworks for the design of a multi-energy microgrid," Applied Energy, Elsevier, vol. 257(C).
    10. Jamila Snoussi & Seifeddine Ben Elghali & Mohamed Benbouzid & Mohamed Faouzi Mimouni, 2018. "Auto-Adaptive Filtering-Based Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles," Energies, MDPI, vol. 11(8), pages 1-20, August.
    11. Forough, Atefeh Behzadi & Roshandel, Ramin, 2018. "Lifetime optimization framework for a hybrid renewable energy system based on receding horizon optimization," Energy, Elsevier, vol. 150(C), pages 617-630.
    12. Chen, Zhang & Yiliang, Xie & Hongxia, Zhang & Yujie, Gu & Xiongwen, Zhang, 2023. "Optimal design and performance assessment for a solar powered electricity, heating and hydrogen integrated energy system," Energy, Elsevier, vol. 262(PA).
    13. Chen, Syuan-Yi & Wu, Chien-Hsun & Hung, Yi-Hsuan & Chung, Cheng-Ta, 2018. "Optimal strategies of energy management integrated with transmission control for a hybrid electric vehicle using dynamic particle swarm optimization," Energy, Elsevier, vol. 160(C), pages 154-170.
    14. Sukumar, Shivashankar & Mokhlis, Hazlie & Mekhilef, Saad & Naidu, Kanendra & Karimi, Mazaher, 2017. "Mix-mode energy management strategy and battery sizing for economic operation of grid-tied microgrid," Energy, Elsevier, vol. 118(C), pages 1322-1333.
    15. Belqasem Aljafari & Subramanian Vasantharaj & Vairavasundaram Indragandhi & Rhanganath Vaibhav, 2022. "Optimization of DC, AC, and Hybrid AC/DC Microgrid-Based IoT Systems: A Review," Energies, MDPI, vol. 15(18), pages 1-30, September.
    16. Wakui, Tetsuya & Kawayoshi, Hiroki & Yokoyama, Ryohei, 2016. "Optimal structural design of residential power and heat supply devices in consideration of operational and capital recovery constraints," Applied Energy, Elsevier, vol. 163(C), pages 118-133.
    17. Peng, Hui & Wang, Junzheng & Shen, Wei & Shi, Dawei & Huang, Yuan, 2019. "Compound control for energy management of the hybrid ultracapacitor-battery electric drive systems," Energy, Elsevier, vol. 175(C), pages 309-319.
    18. Yin, Cong & Gao, Yan & Guo, Shaoyun & Tang, Hao, 2014. "A coupled three dimensional model of vanadium redox flow battery for flow field designs," Energy, Elsevier, vol. 74(C), pages 886-895.
    19. Hua, Lin & Junjie, Xia & Xiang, Gao & Lei, Zheng & Dengwei, Jing & Zhang, Xiongwen & Liejin, Guo, 2024. "Scenario-based stochastic optimization on the variability of solar and wind for component sizing of integrated energy systems," Renewable Energy, Elsevier, vol. 237(PA).
    20. Cai, Wei & Li, Xing & Maleki, Akbar & Pourfayaz, Fathollah & Rosen, Marc A. & Alhuyi Nazari, Mohammad & Bui, Dieu Tien, 2020. "Optimal sizing and location based on economic parameters for an off-grid application of a hybrid system with photovoltaic, battery and diesel technology," Energy, Elsevier, vol. 201(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:jagris:v:14:y:2024:i:9:p:1551-:d:1473561. 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.