Optimized Direct Torque Control of Switched Reluctance Motors Using Bio-Geography Based Firefly Optimization for Torque Ripple Reduction
DOI:
https://doi.org/10.53799/m1s5qx94Keywords:
Switched Reluctance Motor (SRM), , Torque Ripple Control, Bio-geography Based Firefly Optimization (BBFO), MATLAB/SimulinkAbstract
Switched Reluctance Motor (SRM) continues to grow because of its cost-effectiveness and its straightforward construction alongside excellent performance. This work establishes reduction of acoustic noise from Switched Reluctance Motors (SRMs) as its central goal by developing effective torque ripple control methods. The research introduces an optimized Direct Torque Control (DTC) method through the application of Bio-geography Firefly Optimization (BBFO). SRM model implementation in MATLAB/Simulink functions through its combined electrical, magnetic and mechanical dynamic elements. The Optimization Process utilizes Bio-geography Based Firefly Optimization (BBFO) within MATLAB and Simulink to model and simulate while considering Load torque (Nm), Ripple current (A), Motor speed (rpm), Ripple torque (Nm), flux and Motor average power (kW) as criteria. Because of its accurate optimization capability BBFO-based DTC reduces torque ripple and noise effectively and thus suits high-performance applications that depend on these parameters.
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