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Environmental Impact Assessment and Classification of 48 V Plug-in Hybrids with Real-Driving Use Case Simulations

Author

Listed:
  • Tobias Frambach

    (Robert Bosch GmbH, Robert-Bosch-Straße 2, 71701 Schwieberdingen, Germany
    Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen University, Jägerstraße 17-19, 52066 Aachen, Germany)

  • Ralf Kleisch

    (Institute of Automotive Engineering (IFS), University of Stuttgart, Pfaffenwaldring 12, 70569 Stuttgart, Germany)

  • Ralf Liedtke

    (Robert Bosch GmbH, Robert-Bosch-Straße 2, 71701 Schwieberdingen, Germany)

  • Jochen Schwarzer

    (Robert Bosch GmbH, Robert-Bosch-Straße 2, 71701 Schwieberdingen, Germany)

  • Egbert Figgemeier

    (Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen University, Jägerstraße 17-19, 52066 Aachen, Germany
    Helmholtz Institute Münster (HI MS), IEK-12, Forschungszentrum Jülich, Corrensstraße 46, 48149 Münster, Germany)

Abstract

Plug-in hybrid electric vehicles (PHEVs) are commonly operated with high-voltage (HV) components due to their higher power availability compared to 48 V-systems. On the contrary, HV-powertrain components are more expensive and require additional safety measures. Additionally, the HV system can only be repaired and maintained with special equipment and protective gear, which is not available in all workshops. PHEVs based on a 48 V-system level can offer a reasonable compromise between the greenhouse gas (GHG) emission-saving potential and cost-effectiveness in small- and medium-sized electrified vehicles. In our study, the lifecycle emissions of the proposed 48 V PHEV system were compared to a conventional vehicle, 48 V HEV, and HV PHEV for individual driving use cases. To ensure a holistic evaluation, the analysis was based on measured real-driving cycles including Global Position System (GPS) map-matched slope profiles for a parallel hybrid. Optimal PHEV battery capacities were derived for the individual driving use cases. The analysis was based on lifecycle emissions for 2020 and 2030 in Europe. The impact analysis revealed that 48 V PHEVs can significantly reduce GHG emissions compared to vehicles with no charging opportunity for all use cases. Furthermore, the findings were verified for two vehicle segments and two energy mix scenarios. The 48 V PHEVs can therefore complement existing powertrain portfolios and contribute to reaching future GHG emission targets.

Suggested Citation

  • Tobias Frambach & Ralf Kleisch & Ralf Liedtke & Jochen Schwarzer & Egbert Figgemeier, 2022. "Environmental Impact Assessment and Classification of 48 V Plug-in Hybrids with Real-Driving Use Case Simulations," Energies, MDPI, vol. 15(7), pages 1-21, March.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:7:p:2403-:d:779077
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    References listed on IDEAS

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    1. Shaobo, Xie & Qiankun, Zhang & Xiaosong, Hu & Yonggang, Liu & Xianke, Lin, 2021. "Battery sizing for plug-in hybrid electric buses considering variable route lengths," Energy, Elsevier, vol. 226(C).
    2. Patrick Plötz & Simon Árpád Funke & Patrick Jochem, 2018. "Empirical Fuel Consumption and CO2 Emissions of Plug‐In Hybrid Electric Vehicles," Journal of Industrial Ecology, Yale University, vol. 22(4), pages 773-784, August.
    3. Song, Ziyou & Zhang, Xiaobin & Li, Jianqiu & Hofmann, Heath & Ouyang, Minggao & Du, Jiuyu, 2018. "Component sizing optimization of plug-in hybrid electric vehicles with the hybrid energy storage system," Energy, Elsevier, vol. 144(C), pages 393-403.
    4. Paffumi, Elena & De Gennaro, Michele & Martini, Giorgio, 2018. "Alternative utility factor versus the SAE J2841 standard method for PHEV and BEV applications," Transport Policy, Elsevier, vol. 68(C), pages 80-97.
    5. Yuping Zeng & Yang Cai & Guiyue Kou & Wei Gao & Datong Qin, 2018. "Energy Management for Plug-In Hybrid Electric Vehicle Based on Adaptive Simplified-ECMS," Sustainability, MDPI, vol. 10(6), pages 1-24, June.
    6. Cai, Y. & Ouyang, M.G. & Yang, F., 2017. "Impact of power split configurations on fuel consumption and battery degradation in plug-in hybrid electric city buses," Applied Energy, Elsevier, vol. 188(C), pages 257-269.
    7. Enang, Wisdom & Bannister, Chris, 2017. "Modelling and control of hybrid electric vehicles (A comprehensive review)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 1210-1239.
    8. Huang, Yanjun & Wang, Hong & Khajepour, Amir & Li, Bin & Ji, Jie & Zhao, Kegang & Hu, Chuan, 2018. "A review of power management strategies and component sizing methods for hybrid vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 132-144.
    9. Ahmed M. Ali & Dirk Söffker, 2018. "Towards Optimal Power Management of Hybrid Electric Vehicles in Real-Time: A Review on Methods, Challenges, and State-Of-The-Art Solutions," Energies, MDPI, vol. 11(3), pages 1-24, February.
    10. Mahmoodi-k, Mehdi & Montazeri, Morteza & Madanipour, Vahid, 2021. "Simultaneous multi-objective optimization of a PHEV power management system and component sizing in real world traffic condition," Energy, Elsevier, vol. 233(C).
    11. Andersson, Öivind & Börjesson, Pål, 2021. "The greenhouse gas emissions of an electrified vehicle combined with renewable fuels: Life cycle assessment and policy implications," Applied Energy, Elsevier, vol. 289(C).
    12. Ximing Wang & Hongwen He & Fengchun Sun & Jieli Zhang, 2015. "Application Study on the Dynamic Programming Algorithm for Energy Management of Plug-in Hybrid Electric Vehicles," Energies, MDPI, vol. 8(4), pages 1-20, April.
    13. Piotr Wróblewski & Jerzy Kupiec & Wojciech Drożdż & Wojciech Lewicki & Jarosław Jaworski, 2021. "The Economic Aspect of Using Different Plug-In Hybrid Driving Techniques in Urban Conditions," Energies, MDPI, vol. 14(12), pages 1-17, June.
    14. Du, Jiuyu & Zhang, Xiaobin & Wang, Tianze & Song, Ziyou & Yang, Xueqing & Wang, Hewu & Ouyang, Minggao & Wu, Xiaogang, 2018. "Battery degradation minimization oriented energy management strategy for plug-in hybrid electric bus with multi-energy storage system," Energy, Elsevier, vol. 165(PA), pages 153-163.
    15. Onat, Nuri Cihat & Kucukvar, Murat & Tatari, Omer, 2015. "Conventional, hybrid, plug-in hybrid or electric vehicles? State-based comparative carbon and energy footprint analysis in the United States," Applied Energy, Elsevier, vol. 150(C), pages 36-49.
    16. Zhang, LiPeng & Liu, Wei & Qi, BingNan, 2020. "Energy optimization of multi-mode coupling drive plug-in hybrid electric vehicles based on speed prediction," Energy, Elsevier, vol. 206(C).
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