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Developing Equivalent Consumption Minimization Strategy for Advanced Hybrid System-II Electric Vehicles

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  • Hsiu-Ying Hwang

    (Department of Vehicle Engineering, National Taipei University of Technology, Taipei 10608, Taiwan)

Abstract

Compared with conventional vehicles, hybrid electric vehicles (HEVs) have the advantage of high-energy conversion efficiency, which can have better fuel economy and lower emissions. The main issue of HEVs is how to develop an energy management strategy to achieve significantly better fuel efficiency. In this research, the Equivalent Consumption Minimization Strategy (ECMS) was applied to optimize the performance of fuel consumption in the Advanced Hybrid System-II (AHS-II). Based on FTP-75 Test Procedure defined by the U.S. Environmental Protection Agency (EPA), a backward simulation module was established. The baseline simulation module with the rule-based control strategy was validated with the original fuel consumption data. Then, the module with ECMS followed the same control rules of engine on/off and mode selection, and the fuel consumption of ECMS was compared with the simulation results of the baseline model. The fuel economy improvements of ECMS in urban, highway driving pattern, and composite fuel economy were up to 8.5%, 7.7%, and 8.1%, respectively. The simulation results showed that the difference of motors’ working efficiency was only 1.2% between ECMS and baseline rule-based control strategies. The main reason of fuel consumption improvement was the engine operation chosen by ECMS, which provided better power distribution.

Suggested Citation

  • Hsiu-Ying Hwang, 2020. "Developing Equivalent Consumption Minimization Strategy for Advanced Hybrid System-II Electric Vehicles," Energies, MDPI, vol. 13(8), pages 1-19, April.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:8:p:2033-:d:347646
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    References listed on IDEAS

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    1. 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.
    2. Zou Yuan & Liu Teng & Sun Fengchun & Huei Peng, 2013. "Comparative Study of Dynamic Programming and Pontryagin’s Minimum Principle on Energy Management for a Parallel Hybrid Electric Vehicle," Energies, MDPI, vol. 6(4), pages 1-14, April.
    3. Bedatri Moulik & Dirk Söffker, 2015. "Optimal Rule-Based Power Management for Online, Real-Time Applications in HEVs with Multiple Sources and Objectives: A Review," Energies, MDPI, vol. 8(9), pages 1-15, August.
    4. Peng, Jiankun & He, Hongwen & Xiong, Rui, 2017. "Rule based energy management strategy for a series–parallel plug-in hybrid electric bus optimized by dynamic programming," Applied Energy, Elsevier, vol. 185(P2), pages 1633-1643.
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    Cited by:

    1. Laeun Kwon & Dae-Seung Cho & Changsun Ahn, 2021. "Degradation-Conscious Equivalent Consumption Minimization Strategy for a Fuel Cell Hybrid System," Energies, MDPI, vol. 14(13), pages 1-14, June.
    2. Alberto Broatch & Pablo Olmeda & Benjamín Plá & Amin Dreif, 2022. "Novel Energy Management Control Strategy for Improving Efficiency in Hybrid Powertrains," Energies, MDPI, vol. 16(1), pages 1-21, December.

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