Authors:
B. Gunapriya, N. Samanvitha, S. Venkatasubramanian, M. Arunadevi Thirumalraj, Bhopendra Singh
Addresses:
Department of Electrical and Electronics Engineering, New Horizon College of Engineering, Bengaluru, Karnataka, India. Department of Electrical and Electronics Engineering, Nitte Meenakshi Institute of Technology (NMIT), Bengaluru, Karnataka, India. Department of Computer Science and Business Systems, Saranathan College of Engineering, Tiruchirappalli, Tamil Nadu, India. Department of Computer Science and Engineering, Karunya Institute of Technology and Science, Coimbatore, Tamil Nadu, India. Department of Computer Science and Business Management, Saranathan College of Engineering, Tiruchirappalli, Tamil Nadu, India. Department of Engineering, Amity University Dubai, Dubai, United Arab Emirates.
As the use of renewable energy increases, the electrical energy storage system must overcome several challenges. As battery technology improves, the range of electric cars (EVs) increases, driving rising demand for these vehicles. An efficient electrical energy storage expedient is required to address the issue of low-range EVs. Conventional electric cars rely on a single power source, which is inadequate for meeting the EV's varying energy needs. To accommodate the high energy density of EV loads, a novel storage medium is required. Fuel efficiency in a HEV is directly related to the PMS employed. In this research, the researchers propose a hybrid power management strategy that combines an SFC with the equivalent consumption minimisation approach (ECMS), with the SFC's hyperparameters tuned using Improved Sand Cat Swarm Optimisation (ISCSO). AI has been a game-changer in coordinating the needs of sources. The supply is a green technology that combines a PEMFC with batteries and ultracapacitors for additional energy storage. The model is developed using MATLAB/Simulink. The simulation-projection scheme meets the power demand of a typical cycle, while other PMS have been evaluated based on hydrogen consumption, overall efficiency, base, and DC bus stability.
Keywords: Power Management Strategy (PMS); Sugeno Fuzzy Controller (SFC); Electrical Energy Storage System; Artificial Intelligence (AI); MATLAB/Simulink; State Machine Control; Proton Exchange Membrane Fuel Cell (PEMFC).
Received on: 17/06/2024, Revised on: 28/07/2024, Accepted on: 18/10/2024, Published on: 09/06/2025
DOI: 10.64091/ATIAS.2025.000178
AVE Trends in Intelligent Applied Sciences, 2025 Vol. 1 No. 2, Pages: 76-95