Rosas-Caro, Julio
Main Affiliation
Preferred name
Rosas-Caro, Julio
Official Name
Rosas Caro, Julio César
ORCID
0000-0003-0161-0575
Researcher ID
R-6224-2018
Scopus Author ID
57191227591
145 results
Now showing 1 - 10 of 145
- Some of the metrics are blocked by yourconsent settings
Item type:Publication, Series-Capacitor Boost Converter as Power Conditioner for Fuel Cell Electric Vehicles(2022); 2 13Scopus© Citations 3 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Quadratic Boost Converter with Reduced Input Current Ripple(MDPI AG, 2025-10-08); ; Silva-Vera, Edgar D.19 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Output feedback dynamic tracking excitation control of synchronous generators(2016); Scopus© Citations 6 1 10 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, On-line speed control of the shunt-connected DC motor via a neurocontroller(2014); 2 43 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Different Switching Strategy for a Quadratic Boost Converter Based on Non-Series Energy Transfer (QBC-NSET)(MDPI AG, 2026-04-02); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A Low-Cost Jamming Detection Approach Using Performance Metrics in Cluster-Based Wireless Sensor Networks(2021); ; Alberto F. Martínez-Herrera<jats:p>Wireless Sensor Networks constitute an important part of the Internet of Things, and in a similar way to other wireless technologies, seek competitiveness concerning savings in energy consumption and information availability. These devices (sensors) are typically battery operated and distributed throughout a scenario of particular interest. However, they are prone to interference attacks which we know as jamming. The detection of anomalous behavior in the network is a subject of study where the routing protocol and the nodes increase power consumption, which is detrimental to the network’s performance. In this work, a simple jamming detection algorithm is proposed based on an exhaustive study of performance metrics related to the routing protocol and a significant impact on node energy. With this approach, the proposed algorithm detects areas of affected nodes with minimal energy expenditure. Detection is evaluated for four known cluster-based protocols: PEGASIS, TEEN, LEACH, and HPAR. The experiments analyze the protocols’ performance through the metrics chosen for a jamming detection algorithm. Finally, we conducted real experimentation with the best performing wireless protocols currently used, such as Zigbee and LoRa.</jats:p>Scopus© Citations 14 1 9 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Novel Current-Fed Bidirectional DC-DC Converter for Battery Charging in Electric Vehicle Applications with Reduced Spikes(2024)14Scopus© Citations 5 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Fault-Tolerant Control Implemented for Sustainable Active and Reactive Regulation of a Wind Energy Generation System(2024)13 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Sliding Mode Speed Control in Synchronous Motors for Agriculture Machinery: A Chattering Suppression Approach(MDPI, 2024)14Scopus© Citations 7 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Inertia in Converter-Dominated Microgrids: Control Strategies and Estimation Techniques<jats:p>This scoping review analyzes the role of inertia in converter-dominated microgrids, with an emphasis on hybrid AC/DC architectures. Following the PRISMA-ScR methodology, 54 studies published between 2015 and 2025 were identified, screened, and synthesized. The review addresses two key aspects, inertia estimation methods and control strategies for emulating inertia via power converters, emphasizing the role of the interlinking converter (ILC) as a bidirectional interface for inertia support between the AC and DC subsystems. This work addresses several limitations of prior reviews: their narrow scope, often overlooking advanced data-driven approaches such as machine learning; the lack of systematic classifications, hindering a comprehensive overview of existing methods; and the absence of practical guidance on selecting appropriate techniques for specific conditions. The findings show that conventional estimation methods are insufficient for low-inertia grids, necessitating adaptive and data-driven approaches. Virtual inertia emulation strategies—such as Virtual Synchronous Machines, Virtual Synchronous Generators, Synchronverters, and ILC-based controls—offer strong potential to enhance frequency stability but remain challenged by scalability, adaptability, and robustness. The review highlights critical research gaps and future directions to guide the development of resilient hybrid microgrid control strategies.</jats:p>34