Metaheuristic-Based Power Loss Optimization for Boost Converter Design

Le Anh Duc; Huy-Hoang Nguyen; Xuan Thanh Pham

doi:10.48084/etasr.18539

Authors

Le Anh Duc School of Information and Communications Technology, Hanoi University of Industry, Hanoi, Vietnam
Huy-Hoang Nguyen School of Electrical and Electronic Engineering, Hanoi University of Industry, Hanoi, Vietnam
Xuan Thanh Pham School of Electrical and Electronic Engineering, Hanoi University of Industry, Hanoi, Vietnam

Volume: 16 | Issue: 3 | Pages: 35311-35316 | June 2026 | https://doi.org/10.48084/etasr.18539

Received: 5 March 2026 | Revised: 18 March 2026 | Accepted: 29 March 2026 | Online: 6 June 2026

Corresponding author: Xuan Thanh Pham

Abstract

This article presents a design for a DC-DC Boost Converter (BoC), which is widely used in many power electronic systems. The objective of the optimization problem is to minimize power loss in circuit components to enhance the efficiency of the BoC while considering three variables: inductance, capacitance, and switching frequency. Leveraging nature-inspired metaheuristics, including a Bat Algorithm (BA) and a Differential Evolution (DE), enables the attainment of optimal solutions to the nonconvex problem. In numerous scenarios, the two proposed approaches outperform the two benchmarks: Geometric Programming (GP) and Particle Swarm Optimization (PSO). Additionally, the optimized BoCs successfully operate in PSIM, a circuit simulation software, thereby further validating the effectiveness of the design.

Keywords:

bat algorithm, DC-DC boost converters, differential evolution, nature-inspired metaheuristics

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