IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v312y2024ics0360544224033838.html
   My bibliography  Save this article

Experimental and numerical study on energy flow characteristics of a plug-in hybrid electric vehicle with integrated thermal management system

Author

Listed:
  • Wei, Xiaofei
  • Qian, Yejian
  • Gong, Zhen
  • Yao, Mingyao
  • Meng, Shun
  • Zhang, Yu
  • Xu, Zefei
  • Qian, Duode
  • Zhang, Chao

Abstract

A simulation model was developed and validated to explore the energy flow distribution in plug-in hybrid electric vehicles (PHEVs) with integrated thermal management systems (ITMS), using a genetic algorithm to focus on components, subsystems, and the power system. The influence mechanism of temperature and state of charge (SOC) on the energy consumption of the ITMS was subsequently analyzed throughout the driving cycle. The main findings are: (1) Engines possess significantly greater potential for waste heat utilization compared to motors, with the thermal loss of the engine being 9.6 times greater than that of the motor. (2) Although the ITMS improves the engine energy utilization efficiency, considerable room for improvement remains. At −18 °C, the heat loss of the radiator and the heat used by the ITMS account for 14.6 % and 7.7 %, respectively. (3) A pronounced impact of low temperature and SOC on vehicle energy consumption was identified. Energy consumption increased by a factor of 2.14 as temperature decreased from 48 °C to −18 °C. The total energy consumption at SOC 35 was 1.44 times greater than at SOC 75. These findings offer valuable insights for optimizing energy flow in PHEVs equipped with ITMS.

Suggested Citation

  • Wei, Xiaofei & Qian, Yejian & Gong, Zhen & Yao, Mingyao & Meng, Shun & Zhang, Yu & Xu, Zefei & Qian, Duode & Zhang, Chao, 2024. "Experimental and numerical study on energy flow characteristics of a plug-in hybrid electric vehicle with integrated thermal management system," Energy, Elsevier, vol. 312(C).
    • Handle: RePEc:eee:energy:v:312:y:2024:i:c:s0360544224033838
    DOI: 10.1016/j.energy.2024.133605
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544224033838
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2024.133605?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. Ma, Jing & Sun, Yongfei & Zhang, Shiang, 2023. "Experimental investigation on energy consumption of power battery integrated thermal management system," Energy, Elsevier, vol. 270(C).
    2. Fu, Jianqin & Li, Hao & Sun, Xilei & Zhang, Guanjie, 2024. "Many-objective optimization for overall performance of an electric sport utility vehicle under multiple temperature conditions based on natural gradient boosting model," Energy, Elsevier, vol. 304(C).
    3. M. Sabri, M.F. & Danapalasingam, K.A. & Rahmat, M.F., 2016. "A review on hybrid electric vehicles architecture and energy management strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 1433-1442.
    4. Sun, Xilei & Fu, Jianqin & Yang, Huiyong & Xie, Mingke & Liu, Jingping, 2023. "An energy management strategy for plug-in hybrid electric vehicles based on deep learning and improved model predictive control," Energy, Elsevier, vol. 269(C).
    5. Oh, Tick Hui & Hasanuzzaman, Md & Selvaraj, Jeyraj & Teo, Siew Chein & Chua, Shing Chyi, 2018. "Energy policy and alternative energy in Malaysia: Issues and challenges for sustainable growth – An update," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 3021-3031.
    6. Luin, Blaž & Petelin, Stojan & Al-Mansour, Fouad, 2019. "Microsimulation of electric vehicle energy consumption," Energy, Elsevier, vol. 174(C), pages 24-32.
    7. Hemmati, S. & Doshi, N. & Hanover, D. & Morgan, C. & Shahbakhti, M., 2021. "Integrated cabin heating and powertrain thermal energy management for a connected hybrid electric vehicle," Applied Energy, Elsevier, vol. 283(C).
    8. Sun, Xilei & Zhou, Feng & Fu, Jianqin & Liu, Jingping, 2024. "Experiment and simulation study on energy flow characteristics of a battery electric vehicle throughout the entire driving range in low-temperature conditions," Energy, Elsevier, vol. 292(C).
    9. Zhang, LiPeng & Liu, Wei & Qi, Bingnan, 2019. "Innovation design and optimization management of a new drive system for plug-in hybrid electric vehicles," Energy, Elsevier, vol. 186(C).
    10. 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).
    11. Sun, Xilei & Fu, Jianqin, 2024. "Many-objective optimization of BEV design parameters based on gradient boosting decision tree models and the NSGA-III algorithm considering the ambient temperature," Energy, Elsevier, vol. 288(C).
    12. Qiao, Junhao & Chen, Fan & Liu, Jingping & Guan, Jinhuan & Wang, Shuqian & Li, Yangyang, 2024. "Numerical study on the performance, combustion characteristics and energy flow distribution of gasoline-powered vehicle under synthetic actual driving test cycle," Energy, Elsevier, vol. 293(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. Sun, Xilei & Zhou, Feng & Fu, Jianqin & Liu, Jingping, 2024. "Experiment and simulation study on energy flow characteristics of a battery electric vehicle throughout the entire driving range in low-temperature conditions," Energy, Elsevier, vol. 292(C).
    2. Sun, Xilei & Fu, Jianqin, 2024. "Experiment investigation for interconnected effects of driving cycle and ambient temperature on bidirectional energy flows in an electric sport utility vehicle," Energy, Elsevier, vol. 300(C).
    3. Sun, Xilei & Fu, Jianqin, 2024. "Many-objective optimization of BEV design parameters based on gradient boosting decision tree models and the NSGA-III algorithm considering the ambient temperature," Energy, Elsevier, vol. 288(C).
    4. Ma, Jing & Sun, Yongfei & Zhang, Shiang, 2023. "Experimental investigation on energy consumption of power battery integrated thermal management system," Energy, Elsevier, vol. 270(C).
    5. Reddi Khasim, Shaik & Dhanamjayulu, C., 2021. "Selection parameters and synthesis of multi-input converters for electric vehicles: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    6. Fu, Jianqin & Wang, Huailin & Sun, Xilei & Bao, Huanhuan & Wang, Xun & Liu, Jingping, 2024. "Multi-objective optimization for impeller structure parameters of fuel cell air compressor using linear-based boosting model and reference vector guided evolutionary algorithm," Applied Energy, Elsevier, vol. 363(C).
    7. Fu, Jianqin & Li, Hao & Sun, Xilei & Zhang, Guanjie, 2024. "Many-objective optimization for overall performance of an electric sport utility vehicle under multiple temperature conditions based on natural gradient boosting model," Energy, Elsevier, vol. 304(C).
    8. Ibrahim, Amier & Jiang, Fangming, 2021. "The electric vehicle energy management: An overview of the energy system and related modeling and simulation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    9. Xie, Yunkun & Li, Yangyang & Zhao, Zhichao & Dong, Hao & Wang, Shuqian & Liu, Jingping & Guan, Jinhuan & Duan, Xiongbo, 2020. "Microsimulation of electric vehicle energy consumption and driving range," Applied Energy, Elsevier, vol. 267(C).
    10. Das, Himadry Shekhar & Tan, Chee Wei & Yatim, A.H.M., 2017. "Fuel cell hybrid electric vehicles: A review on power conditioning units and topologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 268-291.
    11. 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.
    12. Du, Guodong & Zou, Yuan & Zhang, Xudong & Kong, Zehui & Wu, Jinlong & He, Dingbo, 2019. "Intelligent energy management for hybrid electric tracked vehicles using online reinforcement learning," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    13. Du, Guodong & Zou, Yuan & Zhang, Xudong & Liu, Teng & Wu, Jinlong & He, Dingbo, 2020. "Deep reinforcement learning based energy management for a hybrid electric vehicle," Energy, Elsevier, vol. 201(C).
    14. Alexander Wahl & Christoph Wellmann & Björn Krautwig & Patrick Manns & Bicheng Chen & Christof Schernus & Jakob Andert, 2022. "Efficiency Increase through Model Predictive Thermal Control of Electric Vehicle Powertrains," Energies, MDPI, vol. 15(4), pages 1-21, February.
    15. Zhao, Yang & Jiang, Ziyue & Chen, Xinyu & Liu, Peng & Peng, Tianduo & Shu, Zhan, 2023. "Toward environmental sustainability: data-driven analysis of energy use patterns and load profiles for urban electric vehicle fleets," Energy, Elsevier, vol. 285(C).
    16. Ifaei, Pouya & Tayerani Charmchi, Amir Saman & Loy-Benitez, Jorge & Yang, Rebecca Jing & Yoo, ChangKyoo, 2022. "A data-driven analytical roadmap to a sustainable 2030 in South Korea based on optimal renewable microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    17. 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).
    18. 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).
    19. Wei, Changyin & Sun, Xiuxiu & Chen, Yong & Zang, Libin & Bai, Shujie, 2021. "Comparison of architecture and adaptive energy management strategy for plug-in hybrid electric logistics vehicle," Energy, Elsevier, vol. 230(C).
    20. Zhang, Hao & Lei, Nuo & Chen, Boli & Li, Bingbing & Li, Rulong & Wang, Zhi, 2024. "Modeling and control system optimization for electrified vehicles: A data-driven approach," Energy, Elsevier, vol. 310(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:312:y:2024:i:c:s0360544224033838. 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.