IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v292y2024ics036054422400313x.html
   My bibliography  Save this article

Experiment and simulation study on energy flow characteristics of a battery electric vehicle throughout the entire driving range in low-temperature conditions

Author

Listed:
  • Sun, Xilei
  • Zhou, Feng
  • Fu, Jianqin
  • Liu, Jingping

Abstract

To comprehensively investigate the energy distribution and performance of a battery electric vehicle (BEV), an integrated simulation model based on energy flow test data was developed and validated, and the energy flow characteristics of the BEV throughout the entire driving range in low-temperature conditions were studied. The results show that the battery heat loss and motor energy loss first increase and then decrease with an increment in cycle number, while the transmission loss first decreases and then remains constant. The energy recovery efficiency demonstrates an incremental trend with the number of cycles post-battery charging, while the energy utilization efficiency experiences a decline due to escalating energy losses within the power distribution unit (PDU). The energy flow characteristics of the BEV exhibit a pronounced connection with the speed properties inherent in the driving cycle. The battery charge energy is maximal under Urban Dynamometer Driving Schedule (UDDS), whereas the electricity consumption per 100 km is minimized under China light-duty vehicle test cycle-passenger (CLTC-P). Conversely, the energy utilization and recovery efficiency are the highest under Worldwide Light-duty Test Cycle (WLTC). These findings provide directional insights, theoretical support and data basis for rational performance evaluation and optimal energy distribution of BEVs.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:energy:v:292:y:2024:i:c:s036054422400313x
    DOI: 10.1016/j.energy.2024.130542
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S036054422400313X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2024.130542?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. Al-Wreikat, Yazan & Serrano, Clara & Sodré, José Ricardo, 2022. "Effects of ambient temperature and trip characteristics on the energy consumption of an electric vehicle," Energy, Elsevier, vol. 238(PC).
    2. 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).
    3. Shi, Zhicheng & Lee, Chia-fon & Wu, Han & Wu, Yang & Zhang, Lu & Liu, Fushui, 2019. "Optical diagnostics of low-temperature ignition and combustion characteristics of diesel/kerosene blends under cold-start conditions," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    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. Ding, Xiaofeng & Zhang, Donghuai & Cheng, Jiawei & Wang, Binbin & Luk, Patrick Chi Kwong, 2019. "An improved Thevenin model of lithium-ion battery with high accuracy for electric vehicles," Applied Energy, Elsevier, vol. 254(C).
    8. Fiori, Chiara & Ahn, Kyoungho & Rakha, Hesham A., 2016. "Power-based electric vehicle energy consumption model: Model development and validation," Applied Energy, Elsevier, vol. 168(C), pages 257-268.
    9. Yao, Zhi-Min & Qian, Zuo-Qin & Li, Rong & Hu, Eric, 2019. "Energy efficiency analysis of marine high-powered medium-speed diesel engine base on energy balance and exergy," Energy, Elsevier, vol. 176(C), pages 991-1006.
    10. 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).
    11. Ma, Yan & Ding, Hao & Liu, Yongqin & Gao, Jinwu, 2022. "Battery thermal management of intelligent-connected electric vehicles at low temperature based on NMPC," Energy, Elsevier, vol. 244(PA).
    12. 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).
    13. Shi, Zhicheng & Lee, Chia-fon & Wu, Han & Li, Haiying & Wu, Yang & Zhang, Lu & Bo, Yaqing & Liu, Fushui, 2020. "Effect of injection pressure on the impinging spray and ignition characteristics of the heavy-duty diesel engine under low-temperature conditions," Applied Energy, Elsevier, vol. 262(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 & 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).
    2. 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).
    3. 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.
    4. Andrea Di Martino & Seyed Mahdi Miraftabzadeh & Michela Longo, 2022. "Strategies for the Modelisation of Electric Vehicle Energy Consumption: A Review," Energies, MDPI, vol. 15(21), pages 1-20, October.
    5. David Watling & Patrícia Baptista & Gonçalo Duarte & Jianbing Gao & Haibo Chen, 2022. "Systematic Method for Developing Reference Driving Cycles Appropriate to Electric L-Category Vehicles," Energies, MDPI, vol. 15(9), pages 1-28, May.
    6. 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).
    7. Nan, Sirui & Tu, Ran & Li, Tiezhu & Sun, Jian & Chen, Haibo, 2022. "From driving behavior to energy consumption: A novel method to predict the energy consumption of electric bus," Energy, Elsevier, vol. 261(PA).
    8. Djati Wibowo Djamari & Muhammad Idris & Permana Andi Paristiawan & Muhammad Mujtaba Abbas & Olusegun David Samuel & Manzoore Elahi M. Soudagar & Safarudin Gazali Herawan & Davannendran Chandran & Abdu, 2022. "Diesel Spray: Development of Spray in Diesel Engine," Sustainability, MDPI, vol. 14(23), pages 1-22, November.
    9. Polychronis Spanoudakis & Gerasimos Moschopoulos & Theodoros Stefanoulis & Nikolaos Sarantinoudis & Eftichios Papadokokolakis & Ioannis Ioannou & Savvas Piperidis & Lefteris Doitsidis & Nikolaos C. Ts, 2020. "Efficient Gear Ratio Selection of a Single-Speed Drivetrain for Improved Electric Vehicle Energy Consumption," Sustainability, MDPI, vol. 12(21), pages 1-19, November.
    10. Chengqun, Qiu & Wan, Xinshan & Wang, Na & Cao, Sunjia & Ji, Xinchen & Wu, Kun & Hu, Yaoyu & Meng, Mingyu, 2023. "A novel regenerative braking energy recuperation system for electric vehicles based on driving style," Energy, Elsevier, vol. 283(C).
    11. Chen, Haiyan & Shi, Zhongjie & Liu, Fushui & Wu, Yue & Li, Yikai, 2022. "Non-monotonic change of ignition delay with injection pressure under low ambient temperature for the diesel spray combustion," Energy, Elsevier, vol. 243(C).
    12. Maksymilian Mądziel, 2024. "Energy Modeling for Electric Vehicles Based on Real Driving Cycles: An Artificial Intelligence Approach for Microscale Analyses," Energies, MDPI, vol. 17(5), pages 1-22, February.
    13. Jiang, Junyu & Yu, Yuanbin & Min, Haitao & Cao, Qiming & Sun, Weiyi & Zhang, Zhaopu & Luo, Chunqi, 2023. "Trip-level energy consumption prediction model for electric bus combining Markov-based speed profile generation and Gaussian processing regression," Energy, Elsevier, vol. 263(PD).
    14. 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).
    15. Li, Yikai & Wang, Dongfang & Shi, Zhongjie & Chen, Haiyan & Liu, Fushui, 2021. "Environment-adaptive method to control intake preheating for diesel engines at cold-start conditions," Energy, Elsevier, vol. 227(C).
    16. Zhao, Yang & Wang, Zhenpo & Shen, Zuo-Jun Max & Zhang, Lei & Dorrell, David G. & Sun, Fengchun, 2022. "Big data-driven decoupling framework enabling quantitative assessments of electric vehicle performance degradation," Applied Energy, Elsevier, vol. 327(C).
    17. Atiquzzaman Khan Ankur & Stefan Kraus & Thomas Grube & Rui Castro & Detlef Stolten, 2022. "A Versatile Model for Estimating the Fuel Consumption of a Wide Range of Transport Modes," Energies, MDPI, vol. 15(6), pages 1-24, March.
    18. Zhou, Xinyi & Li, Tie & Yi, Ping, 2021. "The similarity ratio effects in design of scaled model experiments for marine diesel engines," Energy, Elsevier, vol. 231(C).
    19. 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).
    20. Themistoklis Stamadianos & Nikolaos A. Kyriakakis & Magdalene Marinaki & Yannis Marinakis, 2023. "Routing Problems with Electric and Autonomous Vehicles: Review and Potential for Future Research," SN Operations Research Forum, Springer, vol. 4(2), pages 1-34, June.

    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:292:y:2024:i:c:s036054422400313x. 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.