Microgrids are an active research field due to their integration of renewable and non-renewable energy sources alongside energy storage systems to supply both DC and AC loads. While existing studies extensively explore hierarchical control structures, focusing on algorithm design and optimization, practical implementation remains challenging due to system complexity. This paper presents the development of a low-power microgrid hardware platform based on power converters and controllers, enabling experimental validation of the second and third levels of hierarchical control. The platform enables real-time energy management using FPPT algorithms while providing an intuitive graphical interface for data visualization and system monitoring. Experimental results confirm the system’s capability of dynamically managing energy flows, ensuring stable operation under varying load conditions. The system demonstrates reliable operation handling loads of up to 100 W, with scalability to 200 W, providing an effective tool for testing and research in microgrid control strategies.

According to the literature, battery ripple current is one of the phenomena that most significantly affect the state of health of batteries. Therefore, this paper presents a methodology to design a digital control in order to reduce such ripple current, which is injected by means of converters that process the charge and discharge energy. The strategy was designed for and implemented in an interlaced converter. The implemented methodology is presented in four stages: (i) modelling the battery-converter-charge system; (ii) designing the digital control based on the model; (iii) designing the practical implementation, where the instrumentation and implementation stage is presented using an embedded device; and (iv) practical validation of the operation of the strategy and the reduction of battery ripple current. The methodology presented here produced a correct performance of the digital control, fulfilling the design parameters of different operation modes and reducing the ripple current in the battery between 50 and 65%. This reduction protects the battery’s useful life and the sources or loads connected to the system. Additionally, it allows the state-of-charge and health estimation algorithms to increase their accuracy, which leads to an improvement in maintenance protocols and the planning of element replacement.

Contexto: El modelado de baterías es una actividad que puede ser compleja si se utilizan técnicas basadas en el comportamiento químico, para facilitar esto se han utilizado estrategias de modelo inverso que se basan en curvas experimentales y ajustes de modelos circuitales. Para la parametrización se utilizan diferentes técnicas que radican en su complejidad, exactitud y tiempo de convergencia. Método: En este trabajo se utiliza un algoritmo de optimización por enjambre de partículas para la parametrización de un modelo de polarización dual para una celda de ion litio de tipo 18650. La metodología propuesta divide el problema en diferentes casos de optimización y propone una estrategia de búsqueda localizada basada en la experiencia del caso anterior. Resultados: El algoritmo PSO permite ajustar los parámetros del modelo para cada uno de los casos analizados. La división del problema por casos permite mejorar la precisión global del problema y a su vez disminuir los tiempos de convergencia del algoritmo. A partir de los posibles casos se puede encontrar la dinámica de cada uno de los parámetros en función del estado de carga. Conclusiones: La metodología propuesta permite reducir los tiempos de parametrización del modelo de polarización dual. Debido a la aproximación generada por las experiencias anteriores, es posible disminuir el número de la población del enjambre y disminuir aún más el tiempo de convergencia del proceso. Adicionalmente, la metodología puede ser utilizada con diferentes algoritmos de optimización.

This work presents an integrated methodology for modeling, parameter tuning, and experimental emulation of Dual Active Bridge (DAB) converters aimed at detailed simulation, control design, and real-time emulation. This is needed to bridge the gap between theoretical modeling and practical implementation, enabling accurate prediction of converter behavior under realistic operating conditions and facilitating the development of control strategies. The study begins with the derivation of a nonlinear model including parasitic elements and transformer characteristics, enabling accurate representation of the converter’s dynamics across operating conditions. To address deviations caused by component tolerances, the model parameters are calibrated using a multi-algorithm optimization framework based on Particle Swarm Optimization, Grey Wolf Optimizer, Secretary Bird Optimization, and Whale Optimization, where the error between predicted and experimental waveforms is minimized. The comparative analysis allows selecting the most suitable optimization strategy based on statistical analyses. The model is also discretized and implemented on a Hardware-in-the-Loop (HIL) platform based on a high-performance microcontroller, enabling real-time emulation of the converter as a digital twin. Moreover, a control-oriented version of the model is presented and used to design a voltage controller, which is subsequently tested in both the HIL environment and on a real DAB converter prototype. Experimental results report differences between HIL and real prototype below 3.9% for currents and 4.45% for voltages in multiple operation conditions, demonstrating an accurate representation of the real power system. This methodology ensures low errors between theoretical, simulated, and experimental behavior, providing a framework for accurate modeling and controller design of DAB converters.

This paper presents a comprehensive analysis of the design and simulation of an integrated electric propulsion system for small boats, with the purpose of optimizing river transport from an environmental and energy perspective. The research proposes a propulsion system that combines an electric motor, a lithium-ion battery-based storage system and a three-phase charger designed for in-port recharging processes. The system components were modeled and simulated using Matlab/Simulink, incorporating real operational data and navigation profiles adapted to typical Colombian river conditions, specifically in the Atrato River. The vessel operating profiles were defined in three main modes: maneuvering (5 knots), economic (12 knots) and maximum speed (27 knots). For each mode, critical variables such as required power, energy autonomy and the frequency of recharges needed on the river route were simulated. The results indicate that operating at low speeds maximizes energy autonomy, reduces the number of refueling stops and allows a shorter cumulative operating time, highlighting higher energy efficiency compared to higher speeds. The article highlights the importance of simulation in the preliminary design of electric propulsion systems, facilitating the optimization of configurations and parameter tuning prior to implementation.

This work presents a cost-effective, versatile hardware-in-the-loop (HIL) system for non-isolated DC/DC converter emulation. The system emulates five types of converters (Buck, Boost, Buck-Boost, Cuk, and SEPIC) and targets educational and research applications. The hardware uses an ARM Cortex M7 microcontroller to perform real-time calculations and produce analog signals that emulate the behavior of the converters. Its economical, compact, and modular design is optimized to facilitate use in educational environments and research projects with limited resources. Additionally, the system includes software that enables automatic configuration of the code necessary for emulation, offering flexibility while reducing costs and complexity