The use of solar photovoltaic panels as source of power for Brushless Direct Current (BLDC) motors requires a DC-DC Converter circuit. One application of solar energy is as a power source for Brushless Direct Current (BLDC) motors. The main problem is the voltage fluctuation and low DC voltage generated by the solar panel. This research aims to improve the performance of the DC-DC Boost Converter circuit and minimize voltage fluctuations. The methodology encompasses mathematical modeling of the circuit in the form of transfer functions and optimizing the DC-DC Boost Converter circuit using the Proportional Integral Derivative (PID) controller and the Firefly algorithm. Simulation testing results indicate an improvement in transient response performance of the DC-DC Converter circuit as a driver for the BLDC motor. This is evidenced by an increase in rise time from 499 s to 820 s, a decrease in settling time from 3.33 e+03 s to 2.07e+03 s, and a reduction in overshoot to 0 from previously 11.4 . The utilization of the firefly algorithm in optimization significantly enhances system efficiency, as demonstrated by faster achievement of stability without excessive oscillation and a reduction in the time required for the system to settle. Overall, this study shows that the firefly algorithm is effective in developing DC-DC Boost Converter circuits, improving system efficiency by reducing settling time and eliminating overshoot. These findings provide empirical evidence of the effectiveness of using artificial intelligence algorithms in enhancing the operational efficiency of energy conversion systems. © 2024 The Authors