Ant Colony Optimization Tuned Fuzzy Control for PV Battery and Super Capacitor Powered Electric Vehicle


  • Ankita Maurya, Jaya Shukla


Ant colony Optimization, Fuzzy, PV, Battery, EV.


This study presents a control plan for a photovoltaic (PV) battery and supercapacitor-powered electric vehicle (EV) using ant colony optimization (ACO) tuned fuzzy control. The proposed approach utilizes the ACO algorithm to optimize the parameters of the fuzzy controller, which is designed to manage the power flow between the electric motor, supercapacitor, and PV battery. The fuzzy control system takes into account the vehicle's speed, battery and supercapacitor voltages, and the power demand from the motor to decide the optimal power delivery among the energy storage devices. The results obtained by Simulation show that the proposed ACO tuned fuzzy control approach effectively advances the vehicle's performance and achieves better energy management. The optimization of the proposed Ant colony optimization based Fuzzy control was examined and its performance investigated through MATLAB/Simulink.


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How to Cite

Ankita Maurya. (2024). Ant Colony Optimization Tuned Fuzzy Control for PV Battery and Super Capacitor Powered Electric Vehicle. International Journal of Intelligent Systems and Applications in Engineering, 12(22s), 99 –. Retrieved from



Research Article