DC electric power distribution is becoming popular due to the proliferation of renewable sources and storage elements in applications such as electric vehicles, ships, aircrafts, microgrids, etc. These systems are characterized by a high integration of power electronic converters. From a system-level perspective, it would be desirable to design this kind of systems using commercial-off-the shelf converters. However, in general, the manufacturers do not provide a behavioral model of the devices in order to analyze the dynamic behavior of the interconnected system before the actual implementation. In the literature, several blackbox modeling techniques have been proposed to overcome this lack of information. This paper proposes the integration of dynamic weighting functions to the polytopic model in order to improve the accuracy of the behavioral models when the input variables change sharply. A boost converter is used as case study and the performance of the proposed model is compared with the most relevant techniques that can be found in the literature. INDEX TERMS Blackbox models, dc microgrids, dc-dc converters, dynamic interactions, electronic power distribution, modeling, system identification, nonlinear models. AIRÁN FRANCÉS (GS'16-M'18) received the M.Sc. and Ph.D. degrees in electrical engineering from the Universidad Politécnica de Madrid (UPM), Spain, in 2012 and 2018, respectively. He is currently an Assistant Professor with the Department of Electrical Engineering, UPM. He participated for two years in the European Project XFEL, where he collaborated in the design and development of dc-dc power supplies for superconducting magnets. His current research interests include modeling, control and stability assessment of electronic power distribution systems, and smart grids.