IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i14p5253-d1189839.html
   My bibliography  Save this article

A Comparative Study on the Energy Flow of Electric Vehicle Batteries among Different Environmental Temperatures

Author

Listed:
  • Zhichao Zhao

    (China Automotive Engineering Research Institute Co., Ltd., Chongqing 401122, China
    New Energy Technology of CAERI Co., Ltd., Chongqing 401122, China)

  • Lu Li

    (China Automotive Engineering Research Institute Co., Ltd., Chongqing 401122, China
    New Energy Technology of CAERI Co., Ltd., Chongqing 401122, China)

  • Yang Ou

    (China Automotive Engineering Research Institute Co., Ltd., Chongqing 401122, China
    New Energy Technology of CAERI Co., Ltd., Chongqing 401122, China)

  • Yi Wang

    (China Automotive Engineering Research Institute Co., Ltd., Chongqing 401122, China
    New Energy Technology of CAERI Co., Ltd., Chongqing 401122, China)

  • Shaoyang Wang

    (Vehicle Engineering Institute, Chongqing University of Technology, Chongqing 400054, China)

  • Jing Yu

    (Vehicle Engineering Institute, Chongqing University of Technology, Chongqing 400054, China)

  • Renhua Feng

    (Vehicle Engineering Institute, Chongqing University of Technology, Chongqing 400054, China
    Zongshen Industrial Group Co., Ltd., Chongqing 401320, China)

Abstract

In the present research, the energy flow of electric vehicle batteries under different environmental temperatures was experimentally examined in a climate chamber. The energy flow characteristics, energy loss conditions, and the critical components’ operating conditions and working efficiency under different environmental temperatures were comparatively analyzed. The test results show that the environmental temperature has a profound impact on an electric vehicle’s performance and the critical components’ working conditions. The driving mileage of the tested vehicle at −7 °C, 23 °C, and 35 °C was found to be 162.89 km, 256.09 km, and 198.69 km, respectively. The environmental temperature does not have much effect on the loss of the motor and motor control unit under driving conditions, and the proportion of those at different temperatures is in all cases about 18%. The battery-recycled energy at 23 °C under braking conditions is much higher than that at −7 °C and 35 °C, leading to a longer driving range. The power battery pack thermal transfer loss at −7 °C is much greater than that at 23 °C and 35 °C due to the low charging and discharging efficiency and the high energy consumption required to warm up the battery at a low environmental temperature. The compressor energy consumption accounts for a large proportion in both braking and driving conditions at 35 °C, and the proportions are 15.25% and 12.41%, respectively. The battery state-of-charge drops the fastest at −7 °C, followed by 35 °C, due to the differences in the power demands of air conditioning, warm air positive temperature coefficient (PTC), and battery PTC in high- and low-temperature environments. The working condition of the front motor under driving conditions at 35 °C is the most severe and leads to the lowest working efficiency.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:14:p:5253-:d:1189839
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/14/5253/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/14/5253/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Apostolaki-Iosifidou, Elpiniki & Codani, Paul & Kempton, Willett, 2017. "Measurement of power loss during electric vehicle charging and discharging," Energy, Elsevier, vol. 127(C), pages 730-742.
    2. Han, Seungyun & Kobla Tagayi, Roland & Kim, Jaewon & Kim, Jonghoon, 2022. "Adaptive deterministic approach for optimized sizing of high-energy battery system applied in electric-powered application," Applied Energy, Elsevier, vol. 309(C).
    3. Guo, Qingbo & Zhang, Chengming & Li, Liyi & Gerada, David & Zhang, Jiangpeng & Wang, Mingyi, 2017. "Design and implementation of a loss optimization control for electric vehicle in-wheel permanent-magnet synchronous motor direct drive system," Applied Energy, Elsevier, vol. 204(C), pages 1317-1332.
    4. Myeong Hyeon Park & Sung Chul Kim, 2019. "Heating Performance Enhancement of High Capacity PTC Heater with Modified Louver Fin for Electric Vehicles," Energies, MDPI, vol. 12(15), pages 1-14, July.
    5. 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).
    6. 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).
    7. Yan, Dongxiang & Lu, Languang & Li, Zhe & Feng, Xuning & Ouyang, Minggao & Jiang, Fachao, 2016. "Durability comparison of four different types of high-power batteries in HEV and their degradation mechanism analysis," Applied Energy, Elsevier, vol. 179(C), pages 1123-1130.
    8. Wang, Haibing & Zheng, Tianhang & Sun, Weiqing & Khan, Muhammad Qasim, 2023. "Research on the pricing strategy of park electric vehicle agent considering carbon trading," Applied Energy, Elsevier, vol. 340(C).
    9. Kwon, Kihan & Lee, Jung-Hwan & Lim, Sang-Kil, 2023. "Optimization of multi-speed transmission for electric vehicles based on electrical and mechanical efficiency analysis," Applied Energy, Elsevier, vol. 342(C).
    10. Li, Maobing & Xu, Hui & Li, Weimin & Liu, Yin & Li, Fade & Hu, Yue & Liu, Li, 2016. "The structure and control method of hybrid power source for electric vehicle," Energy, Elsevier, vol. 112(C), pages 1273-1285.
    11. Al-Wreikat, Yazan & Serrano, Clara & Sodré, José Ricardo, 2021. "Driving behaviour and trip condition effects on the energy consumption of an electric vehicle under real-world driving," Applied Energy, Elsevier, vol. 297(C).
    12. 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).
    13. Li, Shicheng & Xu, Lin & Du, Xiaofang & Wang, Nian & Lin, Feng & Abdelkareem, Mohamed A.A., 2023. "Combined single-pedal and low adhesion control systems for enhanced energy regeneration in electric vehicles: Modeling, simulation, and on-field test," Energy, Elsevier, vol. 269(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. "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).
    2. 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).
    3. Sørensen, Åse Lekang & Ludvigsen, Bjørn & Andresen, Inger, 2023. "Grid-connected cabin preheating of Electric Vehicles in cold climates – A non-flexible share of the EV energy use," Applied Energy, Elsevier, vol. 341(C).
    4. 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).
    5. Li, Shicheng & Xu, Lin & Du, Xiaofang & Wang, Nian & Lin, Feng & Abdelkareem, Mohamed A.A., 2023. "Combined single-pedal and low adhesion control systems for enhanced energy regeneration in electric vehicles: Modeling, simulation, and on-field test," Energy, Elsevier, vol. 269(C).
    6. Zhou, Xiaochuan & Wu, Gang & Wang, Chunyan & Zhang, Ruijun & Shi, Shuaipeng & Zhao, Wanzhong, 2024. "Cooperative optimization of energy recovery and braking feel based on vehicle speed prediction under downshifting conditions," Energy, Elsevier, vol. 301(C).
    7. 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.
    8. Maria Cieśla & Piotr Nowakowski & Mariusz Wala, 2024. "The Impact of Variable Ambient Temperatures on the Energy Efficiency and Performance of Electric Vehicles during Waste Collection," Energies, MDPI, vol. 17(17), pages 1-21, August.
    9. 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).
    10. 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).
    11. 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.
    12. Amir Ansari & Hamidreza Abediasl & Mahdi Shahbakhti, 2024. "Ambient Temperature Effects on Energy Consumption and CO 2 Emissions of a Plug-in Hybrid Electric Vehicle," Energies, MDPI, vol. 17(14), pages 1-21, July.
    13. 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).
    14. Meryem Abid & Mohamed Tabaa & Hanaa Hachimi, 2024. "Electric Vehicle Routing Problem with an Enhanced Vehicle Dispatching Approach Considering Real-Life Data," Energies, MDPI, vol. 17(7), pages 1-27, March.
    15. He, Qiang & Yang, Yang & Luo, Chang & Zhai, Jun & Luo, Ronghua & Fu, Chunyun, 2022. "Energy recovery strategy optimization of dual-motor drive electric vehicle based on braking safety and efficient recovery," Energy, Elsevier, vol. 248(C).
    16. Ghotge, Rishabh & van Wijk, Ad & Lukszo, Zofia, 2021. "Off-grid solar charging of electric vehicles at long-term parking locations," Energy, Elsevier, vol. 227(C).
    17. Lane, Blake & Kinnon, Michael Mac & Shaffer, Brendan & Samuelsen, Scott, 2022. "Deployment planning tool for environmentally sensitive heavy-duty vehicles and fueling infrastructure," Energy Policy, Elsevier, vol. 171(C).
    18. Olivian Chiver & Ioan Radu Sugar & Liviu Neamt, 2024. "Study on the Selection of Electric Motor/Engine on the Performance of Hybrid Vehicles," Energies, MDPI, vol. 17(14), pages 1-14, July.
    19. Daniel Rasbash & Kevin Joseph Dillman & Jukka Heinonen & Eyjólfur Ingi Ásgeirsson, 2023. "A National and Regional Greenhouse Gas Breakeven Assessment of EVs across North America," Sustainability, MDPI, vol. 15(3), pages 1-26, January.
    20. 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).

    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:gam:jeners:v:16:y:2023:i:14:p:5253-:d:1189839. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.