IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v132y2020ics1364032120303713.html
   My bibliography  Save this article

Development and key technologies of pure electric construction machinery

Author

Listed:
  • Lin, Tianliang
  • Lin, Yuanzheng
  • Ren, Haoling
  • Chen, Haibin
  • Chen, Qihuai
  • Li, Zhongshen

Abstract

With global warming and the energy crisis becoming more serious, the emission regulations for construction machinery (CM) are increasingly strict. The pure electric drive system is an inevitable trend for CMs. Although the pure electric drive system is widely used in the industry field and some technologies have been successfully transplanted to the mobile machines, it's not easy for CMs to realize the electrification. Types of pure electric CM (PECM) are discussed firstly to give a glance at PECM. Then the characteristics of a pure electric system for CMs are introduced. Key technologies, like variable speed control of the electric motor (EM), hydroelectric EM driving, new hydroelectric actuator, power supply, and energy recovery, are analyzed in depth. The difficulties of CMs to realize the electrification by comparing the difference between the pure electric power used in CM and the pure electric power used in the other fields. Moreover, the researches and developments in the pure electric drive systems for CMs are introduced. Finally, the challenges that researchers and the CM manufacturers will face are forecasted.

Suggested Citation

  • Lin, Tianliang & Lin, Yuanzheng & Ren, Haoling & Chen, Haibin & Chen, Qihuai & Li, Zhongshen, 2020. "Development and key technologies of pure electric construction machinery," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    • Handle: RePEc:eee:rensus:v:132:y:2020:i:c:s1364032120303713
    DOI: 10.1016/j.rser.2020.110080
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032120303713
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2020.110080?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. Rahman, Imran & Vasant, Pandian M. & Singh, Balbir Singh Mahinder & Abdullah-Al-Wadud, M. & Adnan, Nadia, 2016. "Review of recent trends in optimization techniques for plug-in hybrid, and electric vehicle charging infrastructures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1039-1047.
    2. Zachary P. Cano & Dustin Banham & Siyu Ye & Andreas Hintennach & Jun Lu & Michael Fowler & Zhongwei Chen, 2018. "Batteries and fuel cells for emerging electric vehicle markets," Nature Energy, Nature, vol. 3(4), pages 279-289, April.
    3. Xie, Shaobo & Hu, Xiaosong & Qi, Shanwei & Tang, Xiaolin & Lang, Kun & Xin, Zongke & Brighton, James, 2019. "Model predictive energy management for plug-in hybrid electric vehicles considering optimal battery depth of discharge," Energy, Elsevier, vol. 173(C), pages 667-678.
    4. Lin, Tianliang & Chen, Qiang & Ren, Haoling & Huang, Weiping & Chen, Qihuai & Fu, Shengjie, 2017. "Review of boom potential energy regeneration technology for hydraulic construction machinery," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 358-371.
    5. Xiong, Rui & Cao, Jiayi & Yu, Quanqing, 2018. "Reinforcement learning-based real-time power management for hybrid energy storage system in the plug-in hybrid electric vehicle," Applied Energy, Elsevier, vol. 211(C), pages 538-548.
    6. Hannan, M.A. & Hoque, M.M. & Mohamed, A. & Ayob, A., 2017. "Review of energy storage systems for electric vehicle applications: Issues and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 771-789.
    7. Li, Tianyu & Huang, Lingtao & Liu, Huiying, 2019. "Energy management and economic analysis for a fuel cell supercapacitor excavator," Energy, Elsevier, vol. 172(C), pages 840-851.
    8. Ma, Shao-Chao & Fan, Ying & Feng, Lianyong, 2017. "An evaluation of government incentives for new energy vehicles in China focusing on vehicle purchasing restrictions," Energy Policy, Elsevier, vol. 110(C), pages 609-618.
    9. Zhang, Shuo & Hu, Xiaosong & Xie, Shaobo & Song, Ziyou & Hu, Lin & Hou, Cong, 2019. "Adaptively coordinated optimization of battery aging and energy management in plug-in hybrid electric buses," Applied Energy, Elsevier, vol. 256(C).
    10. Mahmoudzadeh Andwari, Amin & Pesiridis, Apostolos & Rajoo, Srithar & Martinez-Botas, Ricardo & Esfahanian, Vahid, 2017. "A review of Battery Electric Vehicle technology and readiness levels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 414-430.
    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. Huang, Xiaohui & Huang, Qi & Cao, Huajun & Wang, Qianyue & Yan, Wanbin & Cao, Le, 2023. "Battery capacity selection for electric construction machinery considering variable operating conditions and multiple interest claims," Energy, Elsevier, vol. 275(C).
    2. 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.
    3. Zhang, Haoxiang & Wang, Feng & Xu, Bing & Fiebig, Wieslaw, 2022. "Extending battery lifetime for electric wheel loaders with electric-hydraulic hybrid powertrain," Energy, Elsevier, vol. 261(PB).
    4. Lin, Tianliang & Lin, Yuanzheng & Ren, Haoling & Chen, Haibin & Li, Zhongshen & Chen, Qihuai, 2021. "A double variable control load sensing system for electric hydraulic excavator," Energy, Elsevier, vol. 223(C).
    5. Lin, Zichang & Lin, Zhenchuan & Wang, Feng & Xu, Bing, 2024. "A series electric hybrid wheel loader powertrain with independent electric load-sensing system," Energy, Elsevier, vol. 286(C).
    6. Daniele Beltrami & Paolo Iora & Laura Tribioli & Stefano Uberti, 2021. "Electrification of Compact Off-Highway Vehicles—Overview of the Current State of the Art and Trends," Energies, MDPI, vol. 14(17), pages 1-30, September.
    7. Huang, Zhenhua & Fan, Hongqin, 2022. "Responsibility-sharing subsidy policy for reducing diesel emissions from in-use off-road construction equipment," Applied Energy, Elsevier, vol. 320(C).
    8. Xuefei Li & Chao Duan & Kun Bai & Zongwei Yao, 2021. "Operating Performance of Pure Electric Loaders with Different Types of Motors Based on Simulation Analysis," Energies, MDPI, vol. 14(3), pages 1-19, January.
    9. Huang, Xiaohui & Huang, Qi & Cao, Huajun & Yan, Wanbin & Cao, Le & Zhang, Qiongzhi, 2023. "Optimal design for improving operation performance of electric construction machinery collaborative system: Method and application," Energy, Elsevier, vol. 263(PA).

    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. Ashleigh Townsend & Rupert Gouws, 2022. "A Comparative Review of Lead-Acid, Lithium-Ion and Ultra-Capacitor Technologies and Their Degradation Mechanisms," Energies, MDPI, vol. 15(13), pages 1-29, July.
    2. Xiaoli Sun & Zhengguo Li & Xiaolin Wang & Chengjiang Li, 2019. "Technology Development of Electric Vehicles: A Review," Energies, MDPI, vol. 13(1), pages 1-29, December.
    3. Jiansong Li & Jiyun Zhao & Xiaochun Zhang, 2020. "A Novel Energy Recovery System Integrating Flywheel and Flow Regeneration for a Hydraulic Excavator Boom System," Energies, MDPI, vol. 13(2), pages 1-25, January.
    4. Zhang, Wei & Wang, Jixin & Liu, Yong & Gao, Guangzong & Liang, Siwen & Ma, Hongfeng, 2020. "Reinforcement learning-based intelligent energy management architecture for hybrid construction machinery," Applied Energy, Elsevier, vol. 275(C).
    5. Rahman, Syed & Khan, Irfan Ahmed & Khan, Ashraf Ali & Mallik, Ayan & Nadeem, Muhammad Faisal, 2022. "Comprehensive review & impact analysis of integrating projected electric vehicle charging load to the existing low voltage distribution system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    6. Chen, Jiaxin & Shu, Hong & Tang, Xiaolin & Liu, Teng & Wang, Weida, 2022. "Deep reinforcement learning-based multi-objective control of hybrid power system combined with road recognition under time-varying environment," Energy, Elsevier, vol. 239(PC).
    7. Ou, Shiqi & Hao, Xu & Lin, Zhenhong & Wang, Hewu & Bouchard, Jessey & He, Xin & Przesmitzki, Steven & Wu, Zhixin & Zheng, Jihu & Lv, Renzhi & Qi, Liang & LaClair, Tim J., 2019. "Light-duty plug-in electric vehicles in China: An overview on the market and its comparisons to the United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 747-761.
    8. Shi, Wenzhuo & Huangfu, Yigeng & Xu, Liangcai & Pang, Shengzhao, 2022. "Online energy management strategy considering fuel cell fault for multi-stack fuel cell hybrid vehicle based on multi-agent reinforcement learning," Applied Energy, Elsevier, vol. 328(C).
    9. Macias, A. & Kandidayeni, M. & Boulon, L. & Trovão, J.P., 2021. "Fuel cell-supercapacitor topologies benchmark for a three-wheel electric vehicle powertrain," Energy, Elsevier, vol. 224(C).
    10. Xiao, B. & Ruan, J. & Yang, W. & Walker, P.D. & Zhang, N., 2021. "A review of pivotal energy management strategies for extended range electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    11. Marouane Adnane & Ahmed Khoumsi & João Pedro F. Trovão, 2023. "Efficient Management of Energy Consumption of Electric Vehicles Using Machine Learning—A Systematic and Comprehensive Survey," Energies, MDPI, vol. 16(13), pages 1-39, June.
    12. Gaizka Saldaña & Jose Ignacio San Martin & Inmaculada Zamora & Francisco Javier Asensio & Oier Oñederra, 2019. "Electric Vehicle into the Grid: Charging Methodologies Aimed at Providing Ancillary Services Considering Battery Degradation," Energies, MDPI, vol. 12(12), pages 1-37, June.
    13. Zhang, Shuo & Hu, Xiaosong & Xie, Shaobo & Song, Ziyou & Hu, Lin & Hou, Cong, 2019. "Adaptively coordinated optimization of battery aging and energy management in plug-in hybrid electric buses," Applied Energy, Elsevier, vol. 256(C).
    14. Cong Zhang & Dai Wang & Bin Wang & Fan Tong, 2020. "Battery Degradation Minimization-Oriented Hybrid Energy Storage System for Electric Vehicles," Energies, MDPI, vol. 13(1), pages 1-21, January.
    15. Ioan-Sorin Sorlei & Nicu Bizon & Phatiphat Thounthong & Mihai Varlam & Elena Carcadea & Mihai Culcer & Mariana Iliescu & Mircea Raceanu, 2021. "Fuel Cell Electric Vehicles—A Brief Review of Current Topologies and Energy Management Strategies," Energies, MDPI, vol. 14(1), pages 1-29, January.
    16. Wu, Yitao & Zhang, Yuanjian & Li, Guang & Shen, Jiangwei & Chen, Zheng & Liu, Yonggang, 2020. "A predictive energy management strategy for multi-mode plug-in hybrid electric vehicles based on multi neural networks," Energy, Elsevier, vol. 208(C).
    17. Erika Pierri & Valentina Cirillo & Thomas Vietor & Marco Sorrentino, 2021. "Adopting a Conversion Design Approach to Maximize the Energy Density of Battery Packs in Electric Vehicles," Energies, MDPI, vol. 14(7), pages 1-24, March.
    18. Balali, Yasaman & Stegen, Sascha, 2021. "Review of energy storage systems for vehicles based on technology, environmental impacts, and costs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    19. Mahmoudzadeh Andwari, Amin & Pesiridis, Apostolos & Rajoo, Srithar & Martinez-Botas, Ricardo & Esfahanian, Vahid, 2017. "A review of Battery Electric Vehicle technology and readiness levels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 414-430.
    20. Bumin Meng & Yaonan Wang & Jianxu Mao & Jianwen Liu & Guochang Xu & Jian Dai, 2018. "Using SoC Online Correction Method Based on Parameter Identification to Optimize the Operation Range of NI-MH Battery for Electric Boat," Energies, MDPI, vol. 11(3), pages 1-20, March.

    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:rensus:v:132:y:2020:i:c:s1364032120303713. 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/600126/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.