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<p>In recent years, utilization of electric vehicles has increased rapidly due to extensive development of environmental circumstances and environmental disintegration which includes lack of fossil fuels as well as economic crisis. It is essential to ensure bidirectional power flow to accommodate the operational requirements of a hybrid energy system. Photovoltaic power is considered a stunning power to generate electricity due to its high scalability, as well as low maintenance. However, due to power dependencies arising from fluctuations in temperature, sunlight intensity, and unforeseen shading conditions, photovoltaic systems often experience variability that diminishes overall system efficiency. To address this limitation, it is necessary to integrate an additional reliable energy source, which can ensure consistent power delivery under dynamic environmental conditions. In this study, a bidirectional DC–DC converter is employed alongside a novel fuzzy logic controller (FLC) enhanced with the Fire Hawk Search (FHS) algorithm. The fuzzy logic controller dynamically adjusts the duty cycle of the bidirectional switches based on system states, while the FHS algorithm optimizes these duty cycles to maintain the output voltage within a specified range and maximize conversion efficiency. This integrated control strategy is implemented in MATLAB using the Simscape Electrical library to ensure accurate modeling and simulation. The proposed FLC–FHS approach is rigorously evaluated using key performance metrics, including duty cycle, efficiency, output power, and power loss. The simulation results demonstrate that the proposed technique significantly outperforms conventional methods, achieving a high efficiency of 98.57%, minimal power loss of 1W, an output power of 97W, and a duty cycle of 0.9 validating its effectiveness for hybrid energy systems in electric vehicle applications. The results demonstrate that the proposed fuzzy logic controller integrated with the Fire Hawk Search algorithm model outperforms other methods. Therefore, the fuzzy logic controller integrated with the Fire Hawk Search algorithm method attains better results in electric vehicles.</p>

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Optimized Bidirectional Power Flow in Hybrid Systems Using Fuzzy Logic and Fire Hawk Search: An Electric Vehicle Perspective

  • 期刊论文

  • 发表日期：

    2025年7月28日

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  • S. Chitra Devi,
  • A. Ramkumar,
  • K. Rajesh

摘要

In recent years, utilization of electric vehicles has increased rapidly due to extensive development of environmental circumstances and environmental disintegration which includes lack of fossil fuels as well as economic crisis. It is essential to ensure bidirectional power flow to accommodate the operational requirements of a hybrid energy system. Photovoltaic power is considered a stunning power to generate electricity due to its high scalability, as well as low maintenance. However, due to power dependencies arising from fluctuations in temperature, sunlight intensity, and unforeseen shading conditions, photovoltaic systems often experience variability that diminishes overall system efficiency. To address this limitation, it is necessary to integrate an additional reliable energy source, which can ensure consistent power delivery under dynamic environmental conditions. In this study, a bidirectional DC–DC converter is employed alongside a novel fuzzy logic controller (FLC) enhanced with the Fire Hawk Search (FHS) algorithm. The fuzzy logic controller dynamically adjusts the duty cycle of the bidirectional switches based on system states, while the FHS algorithm optimizes these duty cycles to maintain the output voltage within a specified range and maximize conversion efficiency. This integrated control strategy is implemented in MATLAB using the Simscape Electrical library to ensure accurate modeling and simulation. The proposed FLC–FHS approach is rigorously evaluated using key performance metrics, including duty cycle, efficiency, output power, and power loss. The simulation results demonstrate that the proposed technique significantly outperforms conventional methods, achieving a high efficiency of 98.57%, minimal power loss of 1W, an output power of 97W, and a duty cycle of 0.9 validating its effectiveness for hybrid energy systems in electric vehicle applications. The results demonstrate that the proposed fuzzy logic controller integrated with the Fire Hawk Search algorithm model outperforms other methods. Therefore, the fuzzy logic controller integrated with the Fire Hawk Search algorithm method attains better results in electric vehicles.