Hussain Attia, American University of Ras Al Khaimah, UAE

This paper presents a new design of a unity power factor corrector for DC-DC converter applications based on an Artificial Neural Network algorithm. The controller firstly calculates the system power factor by measuring the phase shift between the grid voltage and the grid current. Secondly, the controller receives the absolute value of the grid voltage and the measured phase shift through the designed ANN, which predicts the duty cycle of the pulse width modulation (PWM) drive pulses, these PWM pulses are used to drive the Boost DC-DC converter to enforce the drawn current to be fully in phase with the grid voltage as well as to improve the level of Total Harmonics Distortion (THD) of the grid current. MATLAB/Simulink software is adopted to simulate the presented design. The analysis of the simulation results indicates the high performance of the proposed controller in terms of correcting the power factor, and improving the grid current THD.

Power factor corrector, artificial neural network, Boost DC-DC converter, Total Harmonic Distortion, MATLAB/Simulink.