IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v239y2022ipds0360544221025391.html
   My bibliography  Save this article

Novel design of compound coupled hydro-mechanical transmission on heavy-duty vehicle for energy recycling

Author

Listed:
  • Yu, Jin
  • Song, Yurun
  • Zhang, Huasen
  • Dong, Xiaohan

Abstract

How to efficiently transmit power and reuse/recover energy has been the subjects of heated discussion in the high-power transmission field. Regarding heavy-duty vehicles, they used to be equipped with a gearbox as a typical type of high-power transmission to deliver power to the wheel. However, a gearbox transmission has quite complex mechanical structure for realizing a large speed-regulating range, and it has an inevitable drawback of weighing too much. In addition, it cannot reuse/recover energy. In this study, a novel design of a compound coupled hydro-mechanical transmission (CCHMT) is proposed to realize energy reuse/recovery on heavy-duty vehicles. The CCHMT has an optimal structure coupled with hydraulic and mechanical components, which makes its speed change continuously and keep the engine running with a high fuel economy. Moreover, compared with both hybrid and battery electric vehicles, vehicle with CCHMT has higher power density. To validate the transmission's feasibility and operational efficiency, simulation modeling and experiments are conducted. The CCHMT can transform unstable energy under a wide speed-regulation range, reuse/recover a vehicle's excess energy at an efficiency of 82.30%/62.94%, and provide a stable driving torque with a high efficiency of 76%, which shows a good energy management performance on heavy-duty vehicle's hydraulic system.

Suggested Citation

  • Yu, Jin & Song, Yurun & Zhang, Huasen & Dong, Xiaohan, 2022. "Novel design of compound coupled hydro-mechanical transmission on heavy-duty vehicle for energy recycling," Energy, Elsevier, vol. 239(PD).
    • Handle: RePEc:eee:energy:v:239:y:2022:i:pd:s0360544221025391
    DOI: 10.1016/j.energy.2021.122291
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544221025391
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2021.122291?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. Zhao, Xueyong & Maißer, Peter, 2003. "A novel power splitting drive train for variable speed wind power generators," Renewable Energy, Elsevier, vol. 28(13), pages 2001-2011.
    2. Xie, Shaobo & Hu, Xiaosong & Xin, Zongke & Brighton, James, 2019. "Pontryagin’s Minimum Principle based model predictive control of energy management for a plug-in hybrid electric bus," Applied Energy, Elsevier, vol. 236(C), pages 893-905.
    3. Li, Junqiu & Wang, Yihe & Chen, Jianwen & Zhang, Xiaopeng, 2017. "Study on energy management strategy and dynamic modeling for auxiliary power units in range-extended electric vehicles," Applied Energy, Elsevier, vol. 194(C), pages 363-375.
    4. Liu, Hongwei & Lin, Yonggang & Shi, Maoshun & Li, Wei & Gu, Haigang & Xu, Quankun & Tu, Le, 2015. "A novel hydraulic-mechanical hybrid transmission in tidal current turbines," Renewable Energy, Elsevier, vol. 81(C), pages 31-42.
    5. Bravo, Rafael Rivelino Silva & De Negri, Victor Juliano & Oliveira, Amir Antonio Martins, 2018. "Design and analysis of a parallel hydraulic – pneumatic regenerative braking system for heavy-duty hybrid vehicles," Applied Energy, Elsevier, vol. 225(C), pages 60-77.
    6. Qi, Chunyang & Song, Chuanxue & Xiao, Feng & Song, Shixin, 2022. "Generalization ability of hybrid electric vehicle energy management strategy based on reinforcement learning method," Energy, Elsevier, vol. 250(C).
    7. Van de Ven, James D., 2013. "Constant pressure hydraulic energy storage through a variable area piston hydraulic accumulator," Applied Energy, Elsevier, vol. 105(C), pages 262-270.
    8. Li, Shuangqi & He, Hongwen & Zhao, Pengfei, 2021. "Energy management for hybrid energy storage system in electric vehicle: A cyber-physical system perspective," Energy, Elsevier, vol. 230(C).
    9. Abdelkareem, Mohamed A.A. & Xu, Lin & Ali, Mohamed Kamal Ahmed & Elagouz, Ahmed & Mi, Jia & Guo, Sijing & Liu, Yilun & Zuo, Lei, 2018. "Vibration energy harvesting in automotive suspension system: A detailed review," Applied Energy, Elsevier, vol. 229(C), pages 672-699.
    10. Ruan, Jiageng & Walker, Paul & Zhang, Nong, 2016. "A comparative study energy consumption and costs of battery electric vehicle transmissions," Applied Energy, Elsevier, vol. 165(C), pages 119-134.
    11. Wang, Rong-Jie & Gerber, Stiaan, 2014. "Magnetically geared wind generator technologies: Opportunities and challenges," Applied Energy, Elsevier, vol. 136(C), pages 817-826.
    12. Du, Jiuyu & Chen, Jingfu & Song, Ziyou & Gao, Mingming & Ouyang, Minggao, 2017. "Design method of a power management strategy for variable battery capacities range-extended electric vehicles to improve energy efficiency and cost-effectiveness," Energy, Elsevier, vol. 121(C), pages 32-42.
    13. Karásek, Jiří & Pojar, Jan & Kaločai, Ladislav & Heralová, Renáta Schneiderová, 2018. "Cost optimum calculation of energy efficiency measures in the Czech Republic," Energy Policy, Elsevier, vol. 123(C), pages 155-166.
    14. Crippa, Paola & Alifa, Mariana & Bolster, Diogo & Genton, Marc G. & Castruccio, Stefano, 2021. "A temporal model for vertical extrapolation of wind speed and wind energy assessment," Applied Energy, Elsevier, vol. 301(C).
    15. Pugi, L. & Pagliai, M. & Nocentini, A. & Lutzemberger, G. & Pretto, A., 2017. "Design of a hydraulic servo-actuation fed by a regenerative braking system," Applied Energy, Elsevier, vol. 187(C), pages 96-115.
    16. Tao Liu & Jincheng Zheng & Yongmao Su & Jinghui Zhao, 2013. "A Study on Control Strategy of Regenerative Braking in the Hydraulic Hybrid Vehicle Based on ECE Regulations," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-9, November.
    17. Kwon, Hyukjoon & Sprengel, Michael & Ivantysynova, Monika, 2016. "Thermal modeling of a hydraulic hybrid vehicle transmission based on thermodynamic analysis," Energy, Elsevier, vol. 116(P1), pages 650-660.
    18. Clauser, Christoph & Ewert, Markus, 2018. "The renewables cost challenge: Levelized cost of geothermal electric energy compared to other sources of primary energy – Review and case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3683-3693.
    19. Qi, Chunyang & Zhu, Yiwen & Song, Chuanxue & Yan, Guangfu & Xiao, Feng & Da wang, & Zhang, Xu & Cao, Jingwei & Song, Shixin, 2022. "Hierarchical reinforcement learning based energy management strategy for hybrid electric vehicle," Energy, Elsevier, vol. 238(PA).
    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. Ouyang, Tiancheng & Jin, Song & Lu, Yucai & Peng, Weijie & Li, Yanzhou, 2024. "Improved energy utilization in heavy-duty automatic transmission: Advanced modeling and multi-objective optimization," Energy, Elsevier, vol. 303(C).
    2. Yu, Jin & Dong, Xiaohan & Song, Yurun & Zhang, Yangguang & Zhang, Huasen & Yang, Xianshen & Xu, Zhongjie & Liu, Yupeng, 2022. "Energy efficiency optimization of a compound coupled hydro-mechanical transmission for heavy-duty vehicles," Energy, Elsevier, vol. 252(C).

    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. Zhou, Jianhao & Xue, Yuan & Xu, Da & Li, Chaoxiong & Zhao, Wanzhong, 2022. "Self-learning energy management strategy for hybrid electric vehicle via curiosity-inspired asynchronous deep reinforcement learning," Energy, Elsevier, vol. 242(C).
    2. 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).
    3. Hyukjoon Kwon & Monika Ivantysynova, 2020. "System Characteristics Analysis for Energy Management of Power-Split Hydraulic Hybrids," Energies, MDPI, vol. 13(7), pages 1-23, April.
    4. Xiaodong Liu & Hongqiang Guo & Xingqun Cheng & Juan Du & Jian Ma, 2022. "A Robust Design of the Model-Free-Adaptive-Control-Based Energy Management for Plug-In Hybrid Electric Vehicle," Energies, MDPI, vol. 15(20), pages 1-24, October.
    5. 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).
    6. Hou, Daizheng & Sun, Qun & Bao, Chunjiang & Cheng, Xingqun & Guo, Hongqiang & Zhao, Ying, 2019. "An all-in-one design method for plug-in hybrid electric buses considering uncertain factor of driving cycles," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    7. Najafi, Arsalan & Jasiński, Michał & Leonowicz, Zbigniew, 2022. "A hybrid distributed framework for optimal coordination of electric vehicle aggregators problem," Energy, Elsevier, vol. 249(C).
    8. Chen, Dongfang & Pei, Pucheng & Meng, Yining & Ren, Peng & Li, Yuehua & Wang, Mingkai & Wang, Xizhong, 2022. "Novel extraction method of working condition spectrum for the lifetime prediction and energy management strategy evaluation of automotive fuel cells," Energy, Elsevier, vol. 255(C).
    9. 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).
    10. Gye-Seong Lee & Dong-Hyun Kim & Jong-Ho Han & Myeong-Hwan Hwang & Hyun-Rok Cha, 2019. "Optimal Operating Point Determination Method Design for Range-Extended Electric Vehicles Based on Real Driving Tests," Energies, MDPI, vol. 12(5), pages 1-17, March.
    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. Wang, Yaxin & Lou, Diming & Xu, Ning & Fang, Liang & Tan, Piqiang, 2021. "Energy management and emission control for range extended electric vehicles," Energy, Elsevier, vol. 236(C).
    13. Paweł Krawczyk & Artur Kopczyński & Jakub Lasocki, 2022. "Modeling and Simulation of Extended-Range Electric Vehicle with Control Strategy to Assess Fuel Consumption and CO 2 Emission for the Expected Driving Range," Energies, MDPI, vol. 15(12), pages 1-41, June.
    14. Donglai Zhao & Wenjie Ge & Xiaojuan Mo & Bo Liu & Dianbiao Dong, 2019. "Design of A New Hydraulic Accumulator for Transient Large Flow Compensation," Energies, MDPI, vol. 12(16), pages 1-17, August.
    15. Yang, Chao & Du, Xuelong & Wang, Weida & Yuan, Lijuan & Yang, Liuquan, 2024. "Variable optimization domain-based cooperative energy management strategy for connected plug-in hybrid electric vehicles," Energy, Elsevier, vol. 290(C).
    16. Song, Ke & Wang, Xiaodi & Li, Feiqiang & Sorrentino, Marco & Zheng, Bailin, 2020. "Pontryagin’s minimum principle-based real-time energy management strategy for fuel cell hybrid electric vehicle considering both fuel economy and power source durability," Energy, Elsevier, vol. 205(C).
    17. Wilberforce, Tabbi & Anser, Afaaq & Swamy, Jangam Aishwarya & Opoku, Richard, 2023. "An investigation into hybrid energy storage system control and power distribution for hybrid electric vehicles," Energy, Elsevier, vol. 279(C).
    18. Liu, Huanlong & Jiang, Yue & Li, Shun, 2019. "Design and downhill speed control of an electric-hydrostatic hydraulic hybrid powertrain in battery-powered rail vehicles," Energy, Elsevier, vol. 187(C).
    19. Huixin Song & Mingming Dong & Liang Gu, 2024. "Research on Efficient Suspension Vibration Reduction Configuration for Effectively Reducing Energy Consumption," Sustainability, MDPI, vol. 16(10), pages 1-19, May.
    20. Liu, Yonggang & Wu, Yitao & Wang, Xiangyu & Li, Liang & Zhang, Yuanjian & Chen, Zheng, 2023. "Energy management for hybrid electric vehicles based on imitation reinforcement learning," Energy, Elsevier, vol. 263(PC).

    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:239:y:2022:i:pd:s0360544221025391. 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.