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Adaptive Rule-Based Energy Management Strategy for a Parallel HEV

Author

Listed:
  • Rishikesh Mahesh Bagwe

    (Department of Electrical and Computer Engineering, Indiana University—Purdue University Indianapolis (IUPUI), Indianapolis, IN 46202, USA)

  • Andy Byerly

    (Allison Transmission, Inc., One Allison Way, Indianapolis, IN 46222, USA)

  • Euzeli Cipriano dos Santos

    (Department of Electrical and Computer Engineering, Indiana University—Purdue University Indianapolis (IUPUI), Indianapolis, IN 46202, USA)

  • Zina Ben-Miled

    (Department of Electrical and Computer Engineering, Indiana University—Purdue University Indianapolis (IUPUI), Indianapolis, IN 46202, USA)

Abstract

This paper proposes an Adaptive Rule-Based Energy Management Strategy (ARBS EMS) for a parallel hybrid electric vehicle (HEV). The aim of the strategy is to facilitate the aftermarket hybridization of medium- and heavy-duty vehicles. ARBS can be deployed online to optimize fuel consumption without any detailed knowledge of the engine efficiency map of the vehicle or the entire duty cycle. The proposed strategy improves upon the established Preliminary Rule-Based Strategy (PRBS), which has been adopted in commercial vehicles, by dynamically adjusting the regions of operations of the engine and the motor. It prevents the engine from operating in highly inefficient regions while reducing the total equivalent fuel consumption of the vehicle. Using an HEV model developed in Simulink ® , both the proposed ARBS and the established PRBS strategies are compared over an extended duty cycle consisting of both urban and highway segments. The results show that ARBS can achieve high MPGe with different thresholds for the boundary between the motor region and the engine region. In contrast, PRBS can achieve high MPGe only if this boundary is carefully established from the engine efficiency map. This difference between the two strategies makes the ARBS particularly suitable for aftermarket hybridization where full knowledge of the engine efficiency map may not be available.

Suggested Citation

  • Rishikesh Mahesh Bagwe & Andy Byerly & Euzeli Cipriano dos Santos & Zina Ben-Miled, 2019. "Adaptive Rule-Based Energy Management Strategy for a Parallel HEV," Energies, MDPI, vol. 12(23), pages 1-17, November.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:23:p:4472-:d:290330
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    References listed on IDEAS

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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.
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    Cited by:

    1. Aaron Shmaryahu & Nissim Amar & Alexander Ivanov & Ilan Aharon, 2021. "Sizing Procedure for System Hybridization Based on Experimental Source Modeling for Electric Vehicles," Energies, MDPI, vol. 14(17), pages 1-21, August.
    2. Lyu, Chenghao & Zhang, Yuchen & Bai, Yilin & Yang, Kun & Song, Zhengxiang & Ma, Yuhang & Meng, Jinhao, 2024. "Inner-outer layer co-optimization of sizing and energy management for renewable energy microgrid with storage," Applied Energy, Elsevier, vol. 363(C).
    3. Yavuz Eray Altun & Osman Akın Kutlar, 2024. "Energy Management Systems’ Modeling and Optimization in Hybrid Electric Vehicles," Energies, MDPI, vol. 17(7), pages 1-39, April.
    4. Wei, Changyin & Chen, Yong & Li, Xiaoyu & Lin, Xiaozhe, 2022. "Integrating intelligent driving pattern recognition with adaptive energy management strategy for extender range electric logistics vehicle," Energy, Elsevier, vol. 247(C).
    5. Chun-Hsin Chang & Hsuan-Yung Chang & Yi-Hsuan Hung & Chien-Hsun Wu & Ji-Jia Xu, 2020. "System Designs and Experimental Assessment of a Seven-Mode Vehicle-Oriented Hybrid Powertrain Platform," Energies, MDPI, vol. 13(8), pages 1-20, April.
    6. Wei, Changyin & Sun, Xiuxiu & Chen, Yong & Zang, Libin & Bai, Shujie, 2021. "Comparison of architecture and adaptive energy management strategy for plug-in hybrid electric logistics vehicle," Energy, Elsevier, vol. 230(C).
    7. Li, Cheng & Xu, Xiangyang & Zhu, Helong & Gan, Jiongpeng & Chen, Zhige & Tang, Xiaolin, 2024. "Research on car-following control and energy management strategy of hybrid electric vehicles in connected scene," Energy, Elsevier, vol. 293(C).

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