Performance of Cuk Converter Based on EHO Model for Improving the Conversion Efficiency Levels

Abstract

The performance of Cuk converter is heavily dependent on circuit parameter ratings, which assist in optimizing capacitor values, inductor values, duty cycles, etc. for optimum conversion efficiency. To perform this task, various researchers have proposed multiple models that allow for dynamic selection of these ratings under real-time use-cases. But most of these models have higher complexity, and their values cannot be used for general-purpose circuit deployments. To overcome this limitation, a novel Elephant Herding Optimization (EHO) based model for the selection of Cuk converter parameters for improving conversion efficiency levels is proposed and discussed in this paper. The proposed model uses an EHO method for estimating circuit ratings under ON and OFF states. These values are validated for different converter configurations and are incrementally tuned by the EHO model for general-purpose applicability. These values include ratings of the parallel diode, switching duty cycle, and ratings for series inductors and capacitors under different conditions. Due to the optimum selection of these ratings, the underlying model is capable of low power, and high-efficiency operations. The proposed model is evaluated under different real-time applications including solar power conversion, battery power conversion, wind power conversion, etc., and its power efficiency and total harmonic distortion (THD) levels are compared with various state-of-the-art models. Based on this comparison it is observed that the proposed model showcased 8.5% lower THD, with 4.9% better power efficiency when compared with these models, which makes the proposed model highly useful for large-scale conversion applications.