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Critical review on structural architecture, energy control strategies and development process towards optimal energy management in hybrid vehicles

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  • Saiteja, Pemmareddy
  • Ashok, B.

Abstract

Hybrid Electric Vehicles (HEVs) are facing difficulties in the aspect of splitting the demand power between various drivetrain components. To negate this issue an efficient energy management system (EMS) is required, EMS is used to split the demand power between drivetrain components. However, it is a difficult task because of the computation complexity and various functionalities associated with the vehicle. In this context to develop an efficient EMS, the various structural architectures, and energy optimization strategies are considered to review in this work. This work presents an overview of key control modules in the EMS such as torque control module, driving mode control, power-split control, and output power sources. Also describes various aspects of energy optimization strategies such as fuzzy, dynamic program, model predictive, neural network, intelligent and connected vehicle technologies to enhance the performance and emissions of the vehicle. These strategies are employed to optimize the fuel economy and energy consumption without compromising the performance of the vehicle. Further, this article provides knowledge on real-time development process of EMS and its calibration parameters such as SOC, vehicle speed, power-split, etc, which are used to enhance the vehicle output characteristics. This research explores a holistic approach to developing the control architecture of EMS with various control strategies. Also, challenges and difficulties on EMS advancements are adequately highlighted, along with a short idea and discussion for the development of future EMS research. Finally, an interpretative study on real-time EMS for HEV with various control strategies disclosed its significance and possible outcomes.

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  • Saiteja, Pemmareddy & Ashok, B., 2022. "Critical review on structural architecture, energy control strategies and development process towards optimal energy management in hybrid vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    • Handle: RePEc:eee:rensus:v:157:y:2022:i:c:s1364032121013009
    DOI: 10.1016/j.rser.2021.112038
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    Cited by:

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    2. Dong, Peng & Zhao, Junwei & Liu, Xuewu & Wu, Jian & Xu, Xiangyang & Liu, Yanfang & Wang, Shuhan & Guo, Wei, 2022. "Practical application of energy management strategy for hybrid electric vehicles based on intelligent and connected technologies: Development stages, challenges, and future trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    3. Hu, Dong & Xie, Hui & Song, Kang & Zhang, Yuanyuan & Yan, Long, 2023. "An apprenticeship-reinforcement learning scheme based on expert demonstrations for energy management strategy of hybrid electric vehicles," Applied Energy, Elsevier, vol. 342(C).
    4. Tang, Wenbin & Wang, Yaqian & Jiao, Xiaohong & Ren, Lina, 2023. "Hierarchical energy management strategy based on adaptive dynamic programming for hybrid electric vehicles in car-following scenarios," Energy, Elsevier, vol. 265(C).

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