Electric Vehicle Energy Harvesting Using a Meta-heuristic MPPT Controller Based on DM Optimization

Rajesh Kannan, Venkatesan Sundharajan, Selvaperumal Sundaramoorthy, Nirmala Rajendran

Abstract


In this paper, a novel Maximum Power Point Tracking (MPPT) control scheme for electric vehicles (EVs) powered by Proton Exchange Membrane Fuel Cells (PEMFCs), using the Dwarf Mongoose Optimization Algorithm (DMOA). The proposed algorithm enhances energy extraction by dynamically adapting to operating conditions with reduced computational complexity. The system integrates an interleaved SEPIC converter and a three-phase inverter for Brushless DC (BLDC) motor drive, achieving 500 W output at 400 V and 2000 rpm with low THD (<5%). Compared to conventional MPPT methods, DMOA demonstrates faster convergence, smoother performance, and higher efficiency under varying temperature.


Keywords


Energy

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References


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DOI (PDF): https://doi.org/10.20508/ijsmartgrid.v9i4.435.g410

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