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Experimental Study on Heuristics Energy Management Strategy for Hybrid Energy Storage System

Author

Listed:
  • Alok Ranjan

    (Department of Electrical Engineering, Shri Ramdeobaba College of Engineering and Management, Nagpur 440013, India)

  • Sanjay Bodkhe

    (Department of Electrical Engineering, Shri Ramdeobaba College of Engineering and Management, Nagpur 440013, India)

  • Gaurav Goyal

    (Department of Electrical Engineering, Shri Ramdeobaba College of Engineering and Management, Nagpur 440013, India)

  • Archana Belge

    (Department of Mechanical and Mechatronics Engineering, Thakur College of Engineering and Technology, Mumbai 400101, India)

  • Sneha Tibude

    (Department of Electrical Engineering, Shri Ramdeobaba College of Engineering and Management, Nagpur 440013, India)

Abstract

The energy management strategy (EMS) is a decision-making algorithm for effective power allocation between storage devices in a hybrid energy storage system (HESS). Source voltages, state of charge (SOC), the terminal voltage of the load, and the rate of change in the battery current must be considered while implementing the EMS and, hence, they are termed as performance indicators. This research work focuses on the development of an EMS, designed to manage the performance indicators of the sources (terminal voltage and battery current rate) and ensure efficient power distribution through a shared bus topology. A shared bus topology employs individual converters for each source, offering efficient control over these sources. Rule-based fuzzy logic control ensures efficient power distribution between batteries and ultracapacitors. Additionally, hardware has been developed to validate the power allocation strategy and regulate the DC-link voltage in the energy management system (EMS). dSPACE MicroLabBox is utilized for the implementation of real-time control strategies. A battery and an ultracapacitor bank are utilized in a hybrid energy storage system. The simulation outcomes have been corroborated by experimental data, affirming the efficacy of the proposed energy management strategy. The proposed EMS achieves a 2.1% battery energy saving compared to a conventional battery electric vehicle over a 25 s duration under the same load conditions.

Suggested Citation

  • Alok Ranjan & Sanjay Bodkhe & Gaurav Goyal & Archana Belge & Sneha Tibude, 2024. "Experimental Study on Heuristics Energy Management Strategy for Hybrid Energy Storage System," Energies, MDPI, vol. 17(23), pages 1-15, November.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:23:p:5850-:d:1526791
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    References listed on IDEAS

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    1. Dogga Raveendhra & Rajana Poojitha & Beeramangalla Lakshminarasaiah Narasimharaju & Alexander Domyshev & Aliona Dreglea & Minh Hien Dao & Mukesh Pathak & Fang Liu & Denis Sidorov, 2023. "Part II: State-of-the-Art Technologies of Solar-Powered DC Microgrid with Hybrid Energy Storage Systems: Converter Topologies," Energies, MDPI, vol. 16(17), pages 1-34, August.
    2. Xuan Meng & Jian Mei & Xingwang Tang & Jinhai Jiang & Chuanyu Sun & Kai Song, 2024. "The Degradation Prediction of Proton Exchange Membrane Fuel Cell Performance Based on a Transformer Model," Energies, MDPI, vol. 17(12), pages 1-13, June.
    3. Tang, Xingwang & Zhang, Yujia & Xu, Sichuan, 2023. "Experimental study of PEM fuel cell temperature characteristic and corresponding automated optimal temperature calibration model," Energy, Elsevier, vol. 283(C).
    4. Li, Heng & Liu, Zheng & Yang, Yingze & Yang, Huihui & Shu, Boyu & Liu, Weirong, 2024. "A proactive energy management strategy for battery-powered autonomous systems," Applied Energy, Elsevier, vol. 363(C).
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