IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v96y2016icp437-448.html
   My bibliography  Save this article

An optimal structure selection and parameter design approach for a dual-motor-driven system used in an electric bus

Author

Listed:
  • Zhang, Shuo
  • Xiong, Rui
  • Zhang, Chengning
  • Sun, Fengchun

Abstract

A number of driving system topologies have been developed for electric vehicles, but the topology design and optimal sizing always challenge the performance of electric vehicles. This paper attempts to address three aspects. First, two novel topologies were derived from the original dual-motor-driven system, and the efficiency models of the system components were built, including motor efficiency, planet gear system efficiency and drag loss of the wet clutch. Second, a systematic optimal sizing framework was constructed. The feasible region of the design parameters was divided into a certain number of grid points, and each grid point represented different design results. Then, a dynamic programming algorithm was applied to each grid point to locate the optimal control strategy and obtain the best grid points under different power levels. After that, a bi-level optimization method was applied at these selected grid points to find the optimal design parameters. Last, the simulation results showed that, compared with the original design, the new topology with two clutches can reduce energy loss by 12.4%, and the optimal design results for the original topology can reduce energy loss by 3.36%.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:96:y:2016:i:c:p:437-448
    DOI: 10.1016/j.energy.2015.12.089
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S036054421501734X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2015.12.089?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. Hui, Sun & Lifu, Yang & Junqing, Jing, 2010. "Hydraulic/electric synergy system (HESS) design for heavy hybrid vehicles," Energy, Elsevier, vol. 35(12), pages 5328-5335.
    2. McManus, M.C., 2012. "Environmental consequences of the use of batteries in low carbon systems: The impact of battery production," Applied Energy, Elsevier, vol. 93(C), pages 288-295.
    3. Zhang, Shuo & Xiong, Rui & Zhang, Chengning, 2015. "Pontryagin’s Minimum Principle-based power management of a dual-motor-driven electric bus," Applied Energy, Elsevier, vol. 159(C), pages 370-380.
    4. Juul, Nina, 2012. "Battery prices and capacity sensitivity: Electric drive vehicles," Energy, Elsevier, vol. 47(1), pages 403-410.
    5. Amjad, Shaik & Rudramoorthy, R. & Neelakrishnan, S. & Sri Raja Varman, K. & Arjunan, T.V., 2011. "Evaluation of energy requirements for all-electric range of plug-in hybrid electric two-wheeler," Energy, Elsevier, vol. 36(3), pages 1623-1629.
    6. Smith, William J., 2010. "Can EV (electric vehicles) address Ireland’s CO2 emissions from transport?," Energy, Elsevier, vol. 35(12), pages 4514-4521.
    7. Chung, Cheng-Ta & Hung, Yi-Hsuan, 2015. "Performance and energy management of a novel full hybrid electric powertrain system," Energy, Elsevier, vol. 89(C), pages 626-636.
    8. Xu, Liangfei & Ouyang, Minggao & Li, Jianqiu & Yang, Fuyuan & Lu, Languang & Hua, Jianfeng, 2013. "Optimal sizing of plug-in fuel cell electric vehicles using models of vehicle performance and system cost," Applied Energy, Elsevier, vol. 103(C), pages 477-487.
    9. Nunes, Pedro & Farias, Tiago & Brito, Miguel C., 2015. "Enabling solar electricity with electric vehicles smart charging," Energy, Elsevier, vol. 87(C), pages 10-20.
    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. Lei, Fei & Bai, Yingchun & Zhu, Wenhao & Liu, Jinhong, 2019. "A novel approach for electric powertrain optimization considering vehicle power performance, energy consumption and ride comfort," Energy, Elsevier, vol. 167(C), pages 1040-1050.
    2. Zhang, Kaixuan & Ruan, Jiageng & Li, Tongyang & Cui, Hanghang & Wu, Changcheng, 2023. "The effects investigation of data-driven fitting cycle and deep deterministic policy gradient algorithm on energy management strategy of dual-motor electric bus," Energy, Elsevier, vol. 269(C).
    3. Wang, Zhenzhen & Zhou, Jun & Rizzoni, Giorgio, 2022. "A review of architectures and control strategies of dual-motor coupling powertrain systems for battery electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    4. 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).
    5. 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).
    6. Shiwei Xu & Lulu Wei & Xiaopeng Zhang & Zhifeng Bai & Yuan Jiao, 2022. "Research on Multi-Mode Drive Optimization Control Strategy of Four-Wheel-Drive Electric Vehicles with Multiple Motors," Sustainability, MDPI, vol. 14(12), pages 1-17, June.
    7. Liu, Hui & Li, Xunming & Wang, Weida & Han, Lijin & Xiang, Changle, 2018. "Markov velocity predictor and radial basis function neural network-based real-time energy management strategy for plug-in hybrid electric vehicles," Energy, Elsevier, vol. 152(C), pages 427-444.
    8. Lei, Fei & Gu, Ke & Du, Bin & Xie, Xiaoping, 2017. "Comprehensive global optimization of an implicit constrained multi-physics system for electric vehicles with in-wheel motors," Energy, Elsevier, vol. 139(C), pages 523-534.
    9. 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.
    10. 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).
    11. Deping Wang & Changyang Guan & Junnian Wang & Haisheng Wang & Zhenhao Zhang & Dachang Guo & Fang Yang, 2023. "Review of Energy-Saving Technologies for Electric Vehicles, from the Perspective of Driving Energy Management," Sustainability, MDPI, vol. 15(9), pages 1-17, May.
    12. Ma, Shaohua & Wang, Shuli & Zhang, Chengning & Zhang, Shuo, 2017. "A method to improve the efficiency of an electric aircraft propulsion system," Energy, Elsevier, vol. 140(P1), pages 436-443.

    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. Chen, Zeyu & Xiong, Rui & Cao, Jiayi, 2016. "Particle swarm optimization-based optimal power management of plug-in hybrid electric vehicles considering uncertain driving conditions," Energy, Elsevier, vol. 96(C), pages 197-208.
    2. 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.
    3. Raslavičius, Laurencas & Starevičius, Martynas & Keršys, Artūras & Pilkauskas, Kęstutis & Vilkauskas, Andrius, 2013. "Performance of an all-electric vehicle under UN ECE R101 test conditions: A feasibility study for the city of Kaunas, Lithuania," Energy, Elsevier, vol. 55(C), pages 436-448.
    4. Zhou, Boya & Wu, Ye & Zhou, Bin & Wang, Renjie & Ke, Wenwei & Zhang, Shaojun & Hao, Jiming, 2016. "Real-world performance of battery electric buses and their life-cycle benefits with respect to energy consumption and carbon dioxide emissions," Energy, Elsevier, vol. 96(C), pages 603-613.
    5. Lei, Fei & Du, Bin & Liu, Xin & Xie, Xiaoping & Chai, Tian, 2016. "Optimization of an implicit constrained multi-physics system for motor wheels of electric vehicle," Energy, Elsevier, vol. 113(C), pages 980-990.
    6. Sun, Fengchun & Hu, Xiaosong & Zou, Yuan & Li, Siguang, 2011. "Adaptive unscented Kalman filtering for state of charge estimation of a lithium-ion battery for electric vehicles," Energy, Elsevier, vol. 36(5), pages 3531-3540.
    7. Arslan, Okan & Karasan, Oya Ekin, 2013. "Cost and emission impacts of virtual power plant formation in plug-in hybrid electric vehicle penetrated networks," Energy, Elsevier, vol. 60(C), pages 116-124.
    8. Ramakrishnan, R. & Hiremath, Somashekhar S. & Singaperumal, M., 2014. "Design strategy for improving the energy efficiency in series hydraulic/electric synergy system," Energy, Elsevier, vol. 67(C), pages 422-434.
    9. Østergaard, P.A. & Lund, H. & Thellufsen, J.Z. & Sorknæs, P. & Mathiesen, B.V., 2022. "Review and validation of EnergyPLAN," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    10. He, Hongwen & Xiong, Rui & Zhao, Kai & Liu, Zhentong, 2013. "Energy management strategy research on a hybrid power system by hardware-in-loop experiments," Applied Energy, Elsevier, vol. 112(C), pages 1311-1317.
    11. Hegde, Bharatkumar & Ahmed, Qadeer & Rizzoni, Giorgio, 2020. "Velocity and energy trajectory prediction of electrified powertrain for look ahead control," Applied Energy, Elsevier, vol. 279(C).
    12. Varga, Bogdan Ovidiu, 2013. "Electric vehicles, primary energy sources and CO2 emissions: Romanian case study," Energy, Elsevier, vol. 49(C), pages 61-70.
    13. Masebinu, S.O. & Akinlabi, E.T. & Muzenda, E. & Aboyade, A.O., 2017. "Techno-economics and environmental analysis of energy storage for a student residence under a South African time-of-use tariff rate," Energy, Elsevier, vol. 135(C), pages 413-429.
    14. Biegel, Benjamin & Hansen, Lars Henrik & Stoustrup, Jakob & Andersen, Palle & Harbo, Silas, 2014. "Value of flexible consumption in the electricity markets," Energy, Elsevier, vol. 66(C), pages 354-362.
    15. Louback, Eduardo & Biswas, Atriya & Machado, Fabricio & Emadi, Ali, 2024. "A review of the design process of energy management systems for dual-motor battery electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 193(C).
    16. Fabio Massaro & Maria Luisa Di Silvestre & Marco Ferraro & Francesco Montana & Eleonora Riva Sanseverino & Salvatore Ruffino, 2024. "Energy Hub Model for the Massive Adoption of Hydrogen in Power Systems," Energies, MDPI, vol. 17(17), pages 1-31, September.
    17. 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.
    18. Hernández, J.C. & Ruiz-Rodriguez, F.J. & Jurado, F., 2017. "Modelling and assessment of the combined technical impact of electric vehicles and photovoltaic generation in radial distribution systems," Energy, Elsevier, vol. 141(C), pages 316-332.
    19. Hegazy, Omar & Barrero, Ricardo & Van den Bossche, Peter & El Baghdadi, Mohamed & Smekens, Jelle & Van Mierlo, Joeri & Vriens, Wouter & Bogaerts, Bruno, 2016. "Modeling, analysis and feasibility study of new drivetrain architectures for off-highway vehicles," Energy, Elsevier, vol. 109(C), pages 1056-1074.
    20. Hu, Dingding & Zhou, Kaile & Li, Fangyi & Ma, Dawei, 2022. "Electric vehicle user classification and value discovery based on charging big data," Energy, Elsevier, vol. 249(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:96:y:2016:i:c:p:437-448. 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.