A Systematic Mapping Study on Automatic Control Systems of Multi-Port dc/dc Power Converters

In the ongoing transition to renewable energy sources, power converters have become indispensable. Their prevalence is increasing, enabling efficient energy conversion, enhancing reliability and stability, and optimizing power extraction from renewable sources. Multi-port dc/dc power converters are widely used because they offer advantages in managing multiple sources and loads. However, designing an automatic control system for these converters presents a challenge due to their complexity. Many configurations for multi-port dc/dc power converters have been proposed, featuring diverse combinations of controllers, modulation techniques, and topologies tailored to specific applications. The body of knowledge on these configurations has grown. Yet, papers have been published according to the authors’ areas of specialization, thus generating a scattered and unorganized body of knowledge and making it difficult to discern research trends and open challenges. Previous studies have attempted to organize knowledge about these configurations, but they have not established a systematic mapping process that follows a rigorous and objective methodology. This paper conducts a systematic mapping study on Automatic Control Systems of multi-port dc/dc power converters. Our study analyzed 122 papers from the 777 papers found around the topic to find and organize the body of knowledge on topology, controller, efficiency, number of elements, modulation technique, and practical applications. This systematic mapping provides a foundational framework for researchers, aiming to inspire further exploration and the development of innovative controller systems in multi-port dc/dc power converters. We found the application of machine learning techniques in dc/dc power converters constitutes an open challenge in these devices.