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Integrated Energy and Catalyst Thermal Management for Plug-In Hybrid Electric Vehicles

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  • Yuping Zeng

    (Jiangxi Province Key Laboratory of Precision Drive & Control, Nanchang Institute of Technology, Nanchang 330099, China
    State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing 400044, China)

  • Yang Cai

    (Jiangxi Province Key Laboratory of Precision Drive & Control, Nanchang Institute of Technology, Nanchang 330099, China)

  • Changbao Chu

    (Jiangxi Province Key Laboratory of Precision Drive & Control, Nanchang Institute of Technology, Nanchang 330099, China)

  • Guiyue Kou

    (Jiangxi Province Key Laboratory of Precision Drive & Control, Nanchang Institute of Technology, Nanchang 330099, China)

  • Wei Gao

    (Jiangxi Province Key Laboratory of Precision Drive & Control, Nanchang Institute of Technology, Nanchang 330099, China)

Abstract

With plug-in hybrid electric vehicles (PHEVs), the catalyst temperature is below the light-off temperature due to reduced engine load, extended engine off period, and frequent engine on/off shifting. The conversion efficiency of a three-way catalyst (TWC) and tailpipe emissions were proven to depend heavily on the temperature of the catalyst. The existing energy management strategy (EMS) of the PHEVs focuses on the improvement of fuel efficiency and emissions based on hot engine characteristics, but neglects the effect of catalyst temperature on tailpipe emissions. This paper presents a new EMS that incorporates a catalyst thermal management method. First, an additional cost is established to implement additional constraints on catalyst temperature, and then the global cost function is created using this additional cost and the fuel consumption. Second, we find the global optimal solution using Pontryagin’s minimum principle method, which provides an optimal control policy and state trajectories. Then, based on the analysis of the optimal control policy, an engine on/off filter (eng on/off filter) is introduced to command the engine on/off shifting. This filter plays an important role in adjusting both the energy and catalyst thermal management strategy for PHEVs. Finally, a practical approach based on the eng on/off filter is developed, and a genetic algorithm is applied to optimize the time constants of this filter. Simulation results demonstrate that the proposed approach‘s fuel consumption increased slightly, but the tailpipe emissions of HC (hydrocarbons), CO (carbon monoxide) and NOx (nitrogen oxide) significantly decreased compared with the standard approach.

Suggested Citation

  • Yuping Zeng & Yang Cai & Changbao Chu & Guiyue Kou & Wei Gao, 2018. "Integrated Energy and Catalyst Thermal Management for Plug-In Hybrid Electric Vehicles," Energies, MDPI, vol. 11(7), pages 1-29, July.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:7:p:1761-:d:156188
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    References listed on IDEAS

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    Cited by:

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    2. Ernest Cortez & Manuel Moreno-Eguilaz & Francisco Soriano, 2018. "Advanced Methodology for the Optimal Sizing of the Energy Storage System in a Hybrid Electric Refuse Collector Vehicle Using Real Routes," Energies, MDPI, vol. 11(12), pages 1-17, November.
    3. Wu, Yitao & Zhang, Yuanjian & Li, Guang & Shen, Jiangwei & Chen, Zheng & Liu, Yonggang, 2020. "A predictive energy management strategy for multi-mode plug-in hybrid electric vehicles based on multi neural networks," Energy, Elsevier, vol. 208(C).
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    5. Xuewen Zhang & Xiang Huang & Peiyong Ni & Xiang Li, 2023. "Strategies to Reduce Emissions from Diesel Engines under Cold Start Conditions: A Review," Energies, MDPI, vol. 16(13), pages 1-21, July.
    6. Hamedi, Mohammad Reza & Doustdar, Omid & Tsolakis, Athanasios & Hartland, Jonathan, 2021. "Energy-efficient heating strategies of diesel oxidation catalyst for low emissions vehicles," Energy, Elsevier, vol. 230(C).
    7. Yuping Zeng & Zhikai Huang & Yang Cai & Yonggang Liu & Yue Xiao & Yang Shang, 2018. "A Control Strategy for Driving Mode Switches of Plug-in Hybrid Electric Vehicles," Sustainability, MDPI, vol. 10(11), pages 1-19, November.

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