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Impact of the hybrid electric architecture on the performance and emissions of a delivery truck with a dual-fuel RCCI engine

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  • García, Antonio
  • Monsalve-Serrano, Javier
  • Martinez-Boggio, Santiago
  • Gaillard, Patrick

Abstract

Reactivity controlled compression ignition combustion showed great advantages in terms of NOx and soot emissions reduction, leading to virtually zero emissions. However, the average brake thermal efficiency of this concept is like that found with conventional diesel operation. The powertrain electrification using electric motors and battery packages appears as a potential solution to reduce the CO2 emissions. For this reason, several solutions for the powertrain electrification can be found currently in the market as the parallel, series and power split powertrain architectures. The aim of this work is to evaluate the hybrid architecture impact on the fuel consumption and emissions of a delivery truck (Volvo-FL) intended for urban and urban–rural applications. The truck equipped with a reactivity-controlled compression ignition diesel-gasoline engine is evaluated and compared against the conventional diesel case. In addition, to evaluate the impact of new e-fuels on the well-to-wheel CO2 emissions, a synthetic gasoline coming from carbon capture and green electricity is evaluated. The results show that hybridization allows reducing the tank-to-wheel CO2 emissions above 15% with the parallel hybrid set-up. The series and power split architectures show CO2 benefits of 12% with respect to the baseline diesel non-hybrid case. Using synthetic gasoline as low reactivity fuel allows to achieve a 50% well-to-wheel CO2 reduction in the P2 and 70% well-to-wheel CO2 reduction for the series and power split cases due to the higher average gasoline fraction used in the driving cycle.

Suggested Citation

  • García, Antonio & Monsalve-Serrano, Javier & Martinez-Boggio, Santiago & Gaillard, Patrick, 2021. "Impact of the hybrid electric architecture on the performance and emissions of a delivery truck with a dual-fuel RCCI engine," Applied Energy, Elsevier, vol. 301(C).
    • Handle: RePEc:eee:appene:v:301:y:2021:i:c:s0306261921008801
    DOI: 10.1016/j.apenergy.2021.117494
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    as
    1. Xu, Bin & Rathod, Dhruvang & Zhang, Darui & Yebi, Adamu & Zhang, Xueyu & Li, Xiaoya & Filipi, Zoran, 2020. "Parametric study on reinforcement learning optimized energy management strategy for a hybrid electric vehicle," Applied Energy, Elsevier, vol. 259(C).
    2. Millo, Federico & Rolando, Luciano & Fuso, Rocco & Zhao, Jianning, 2015. "Development of a new hybrid bus for urban public transportation," Applied Energy, Elsevier, vol. 157(C), pages 583-594.
    3. He, Yinglong & Wang, Chongming & Zhou, Quan & Li, Ji & Makridis, Michail & Williams, Huw & Lu, Guoxiang & Xu, Hongming, 2020. "Multiobjective component sizing of a hybrid ethanol-electric vehicle propulsion system," Applied Energy, Elsevier, vol. 266(C).
    4. Helgeson, Broghan & Peter, Jakob, 2020. "The role of electricity in decarbonizing European road transport – Development and assessment of an integrated multi-sectoral model," Applied Energy, Elsevier, vol. 262(C).
    5. Li, Zilong & Zhang, Yaoyuan & Huang, Guan & Zhao, Wenbin & He, Zhuoyao & Qian, Yong & Lu, Xingcai, 2020. "Control of intake boundary conditions for enabling clean combustion in variable engine conditions under intelligent charge compression ignition (ICCI) mode," Applied Energy, Elsevier, vol. 274(C).
    6. Zhang, Bo & Zhang, Jiangyan & Xu, Fuguo & Shen, Tielong, 2020. "Optimal control of power-split hybrid electric powertrains with minimization of energy consumption," Applied Energy, Elsevier, vol. 266(C).
    7. Forrest, Kate & Mac Kinnon, Michael & Tarroja, Brian & Samuelsen, Scott, 2020. "Estimating the technical feasibility of fuel cell and battery electric vehicles for the medium and heavy duty sectors in California," Applied Energy, Elsevier, vol. 276(C).
    8. Vora, Ashish P. & Jin, Xing & Hoshing, Vaidehi & Saha, Tridib & Shaver, Gregory & Varigonda, Subbarao & Wasynczuk, Oleg & Tyner, Wallace E., 2017. "Design-space exploration of series plug-in hybrid electric vehicles for medium-duty truck applications in a total cost-of-ownership framework," Applied Energy, Elsevier, vol. 202(C), pages 662-672.
    9. Shiyu Gan & Daniela Chrenko & Alan Kéromnès & Luis Le Moyne, 2018. "Development of a Multi-Architecture and Multi-Application Hybrid Vehicle Design and Management Tool," Energies, MDPI, vol. 11(11), pages 1-19, November.
    10. Guille des Buttes, Alice & Jeanneret, Bruno & Kéromnès, Alan & Le Moyne, Luis & Pélissier, Serge, 2020. "Energy management strategy to reduce pollutant emissions during the catalyst light-off of parallel hybrid vehicles," Applied Energy, Elsevier, vol. 266(C).
    11. Zhuang, Weichao & Li (Eben), Shengbo & Zhang, Xiaowu & Kum, Dongsuk & Song, Ziyou & Yin, Guodong & Ju, Fei, 2020. "A survey of powertrain configuration studies on hybrid electric vehicles," Applied Energy, Elsevier, vol. 262(C).
    12. Li, Yuecheng & He, Hongwen & Khajepour, Amir & Wang, Hong & Peng, Jiankun, 2019. "Energy management for a power-split hybrid electric bus via deep reinforcement learning with terrain information," Applied Energy, Elsevier, vol. 255(C).
    Full references (including those not matched with items on IDEAS)

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    8. Navid Balazadeh Meresht & Sina Moghadasi & Sandeep Munshi & Mahdi Shahbakhti & Gordon McTaggart-Cowan, 2023. "Advances in Vehicle and Powertrain Efficiency of Long-Haul Commercial Vehicles: A Review," Energies, MDPI, vol. 16(19), pages 1-37, September.
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