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Energy management strategy to reduce pollutant emissions during the catalyst light-off of parallel hybrid vehicles

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  • Guille des Buttes, Alice
  • Jeanneret, Bruno
  • Kéromnès, Alan
  • Le Moyne, Luis
  • Pélissier, Serge

Abstract

The transportation sector is a major contributor to both air pollution and greenhouse gas emissions. Hybrid electric vehicles can reduce fuel consumption and CO2 emissions by optimizing the energy management of the powertrain. The purpose of this study is to examine the trade-off between regulated pollutant emissions and hybrid powertrain efficiency. The thermal dynamics of the three-way catalyst are taken into account in order to optimize the light-off. Experimental campaigns are conducted on a spark-ignition engine to introduce simplified models for emissions, exhaust gas temperature, catalyst heat transfers and efficiency. These models are used to determine the optimal distribution of a power request between the thermal engine and the electric motor with three-dimensional dynamic programming and a weighted objective function. A pollution-centered scenario is compared with a consumption-centered scenario for various driving cycles. The optimal torque distribution for the emissions-centered scenario on the world harmonized light-duty vehicles test cycle shows an 8–33% decrease in pollutant emissions while the consumption remains stable (0.1% increase). The consistency of the results is analyzed with respect to the discretization parameters, driving cycle, electric motor and battery sizing, as well as emission and catalyst models. The control strategies are promising but will have to be adapted to online engine control where the driving cycle and the catalyst efficiency are uncertain.

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  • 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).
  • Handle: RePEc:eee:appene:v:266:y:2020:i:c:s0306261920303780
    DOI: 10.1016/j.apenergy.2020.114866
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    1. Zhang, Pei & Yan, Fuwu & Du, Changqing, 2015. "A comprehensive analysis of energy management strategies for hybrid electric vehicles based on bibliometrics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 88-104.
    2. Li, Ji & Zhou, Quan & He, Yinglong & Shuai, Bin & Li, Ziyang & Williams, Huw & Xu, Hongming, 2019. "Dual-loop online intelligent programming for driver-oriented predict energy management of plug-in hybrid electric vehicles," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    3. Zhang, Shaojun & Wu, Ye & Hu, Jingnan & Huang, Ruikun & Zhou, Yu & Bao, Xiaofeng & Fu, Lixin & Hao, Jiming, 2014. "Can Euro V heavy-duty diesel engines, diesel hybrid and alternative fuel technologies mitigate NOX emissions? New evidence from on-road tests of buses in China," Applied Energy, Elsevier, vol. 132(C), pages 118-126.
    4. Zhang, Shuo & Hu, Xiaosong & Xie, Shaobo & Song, Ziyou & Hu, Lin & Hou, Cong, 2019. "Adaptively coordinated optimization of battery aging and energy management in plug-in hybrid electric buses," Applied Energy, Elsevier, vol. 256(C).
    5. Sinha Majumdar, Sreshtha & Pihl, Josh A. & Toops, Todd J., 2019. "Reactivity of novel high-performance fuels on commercial three-way catalysts for control of emissions from spark-ignition engines," Applied Energy, Elsevier, vol. 255(C).
    6. 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).
    7. Raffael Hedinger & Philipp Elbert & Christopher Onder, 2017. "Optimal Cold-Start Control of a Gasoline Engine," Energies, MDPI, vol. 10(10), pages 1-17, October.
    8. Wu, Yuankai & Tan, Huachun & Peng, Jiankun & Zhang, Hailong & He, Hongwen, 2019. "Deep reinforcement learning of energy management with continuous control strategy and traffic information for a series-parallel plug-in hybrid electric bus," Applied Energy, Elsevier, vol. 247(C), pages 454-466.
    9. Dardiotis, Christos & Martini, Giorgio & Marotta, Alessandro & Manfredi, Urbano, 2013. "Low-temperature cold-start gaseous emissions of late technology passenger cars," Applied Energy, Elsevier, vol. 111(C), pages 468-478.
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    11. 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).
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