Abstract
A genetic algorithm based method to optimize efficiency of a power converter during running process is proposed in this paper. Compared with the conventional PWM, PFM and multi-mode control techniques, both the duty cycle and the switching frequency are regulated by the proposed method. Benefit from this multi-objective optimization, the maximum efficiency of the converter at a specific load can be approached by choosing and evolving the operating points adaptively. Critical issues, such as the input current sensing, the electrical stress limiting of the power devices and the error compensation of the fitness value, are investigated in order to implement the proposed algorithm. A digital controlled Boost converter based on a microcontroller is built to verify the effectiveness of the algorithm. According to the comparison with conventional control techniques, the peak efficiency with genetic algorithm optimization is 2% higher, and the light load efficiency is optimized over 10%.
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