Doutorado em Engenharia Elétrica

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    Primary-side power capability estimation for optimal current distribution in LCC-LCC compensated multi-transmitter lnductive power transfer systems
    (Universidade Federal do Espírito Santo, 2025-08-20) Lacerda, Macklyster Lãnucy Scherre Stofel de; Santos, Walbermark Marques dos ; https://orcid.org/0000-0002-9871-6028; http://lattes.cnpq.br/5558697161842579; https://orcid.org/0000-0002-6673-8716; http://lattes.cnpq.br/0110962438935308; Encarnação, Lucas Frizera; https://orcid.org/0000-0002-6162-7697; http://lattes.cnpq.br/5578918284508758; Antunes, Helio Marcos Andre; https://orcid.org/0000-0001-8247-6448; http://lattes.cnpq.br/7601860538588447; Rech, Cassiano; https://orcid.org/0000-0001-8225-9240; http://lattes.cnpq.br/9375639768929991; Martins, Denizar Cruz; 0000-0002-0806-1831; http://lattes.cnpq.br/6156546664055944
    Inductive Power Transfer (IPT) systems face inherent limitations under misalignment be tween transmitter and receiver coils, leading to reduced magnetic coupling and compromised power capacity and efficiency. Configurations with multiple primary circuits are employed to mitigate these effects. In addition to increased robustness against positional variation, such systems offer improved magnetic field distribution, reduced peak currents, and lower voltage and current stresses on the primary compensation components. Nevertheless, the introduction of multiple primaries creates practical challenges in accurately identifying the power transfer capability of each primary circuit, as this capability is directly influenced by the mutual inductances, which vary dynamically with the spatial position of the secondary coil. To address this challenge, this thesis presents a practical procedure to identify the power transfer capability of each primary circuit in IPT systems with LCC compensa tion topology, based on direct voltage measurements across the primary compensation capacitors. The proposed routine is executed before initiating power transfer, allowing the determination of the power transferable by each primary circuit at specific current levels without requiring knowledge of the secondary coil’s position or complex offline inductance simulations. Based on these results, an optimization problem is formulated to compute the operating currents that minimize conduction losses in the primary inductors, thereby establishing the power distribution among the primary circuits. The proposed method is supported by a mathematical framework initially developed for single-phase LCC IPT systems, where the system is modeled through conductance equations that incorporate the resistive elements of the compensation network. This formulation is then extended to the three-primary, single-secondary configuration. The complete approach—comprising modeling, identification, and optimization—was validated through simulations performed in PSIM for a 1.5 kW IPT system and experimental tests conducted on a 200 W prototype. The system achieved an overall efficiency of approximately 86% in simulations and 64% in experiments. Since the method imposes no mathematical restrictions on power level, it can be applied to IPT systems of any rated power
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    Desenvolvimento e validação experimental do controle preditivo em conversores DAB e ANPC-DAB aplicados a SST
    (Universidade Federal do Espírito Santo, 2025-05-20) Nardoto, Adriano Fazolo; Encarnação, Lucas Frizera; https://orcid.org/0000-0002-6162-7697; http://lattes.cnpq.br/5578918284508758; Bueno Peña, Emilio José; https://orcid.org/0000-0002-0806-1831; Santos, Walbermark Marques dos; https://orcid.org/0000-0002-9871-6028; http://lattes.cnpq.br/5558697161842579; https://orcid.org/0000-0002-5003-698X; http://lattes.cnpq.br/8641259747622403; Simonetti, Domingos Sávio Lyrio; https://orcid.org/0000-0001-5920-2932; http://lattes.cnpq.br/1107005171102255; Coelho, Roberto Francisco; https://orcid.org/0000-0002-4672-0885; http://lattes.cnpq.br/9967005468124403; Martins, Denizar Cruz; https://orcid.org/0000-0002-0806-1831; http://lattes.cnpq.br/6156546664055944; Rech, Cassiano; https://orcid.org/0000-0001-8225-9240; http://lattes.cnpq.br/9375639768929991
    This thesis addresses the development of model predictive control (MPC) strategies for ap plication in DAB (Dual Active Bridge) converters, focusing on high-complexity applications that require real-time processing, particularly in multilevel topologies and systems with a large number of switching states. Two approaches were investigated. The first focused on the modular application of the DAB converter, evaluating power distribution among multiple converters connected in parallel on a low-voltage DC bus (LVDC). This topology was experimentally tested on a test bench developed at the Power Electronics and Electric Drives Laboratory (LEPAC) of the Federal University of Espírito Santo. The second approach aimed to increase the efficiency of the DAB converter through predictive control and advanced modulation techniques, such as triangular and trapezoidal modulations, optimizing the converter’s operation under light load conditions. This technique was experimentally tested on the DAB using the ANPC (Active Neu tral Point Clamped) multilevel topology. The test bench was developed at the Energy, Electrical Systems Engineering, and Smart Grids Group (GEISER) of the University of Alcalá de Henares
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    A novel framework for Covid-19 detection and clinical triage using multimodal physiological signals on a portable medical assistant
    (Universidade Federal do Espírito Santo, 2025-08-15) Silva, Leticia Araújo; Krishnan, Sridhar; https://orcid.org/0000-0002-0321-9273; Bastos Filho, Teodiano Freire; https://orcid.org/0000-0002-1185-2773; http://lattes.cnpq.br/3761585497791105; https://orcid.org/0000-0002-1534-0708; http://lattes.cnpq.br/2690656852231539; Caldeira, Eliete Maria de Oliveira; https://orcid.org/0000-0002-3742-0952; http://lattes.cnpq.br/8508979665054143 ; Andrade, Adriano de Oliveira; https://orcid.org/0000-0002-5689-6606; http://lattes.cnpq.br/1229329519982110; Naves, Eduardo Lazaro Martins; https://orcid.org/0000-0003-4175-723X; http://lattes.cnpq.br/5450557733379720; Rodríguez, Denis Delisle; https://orcid.org/0000-0002-8937-031X; http://lattes.cnpq.br/7140331839822423; Villa Parra, Ana Cecilia; https://orcid.org/0000-0002-7588-9372; http://lattes.cnpq.br/7385634502540480
    Emergency and urgent care systems face growing challenges in providing timely and accurate triage, especially in resource-constrained environments where subjectivity, lack of infrastructure, and high patient volumes compromise clinical decisions. These limitations became even more evident during the Coronavirus Disease 2019 (COVID-19) pandemic, which exposed critical gaps in diagnostic capacity and highlighted the absence of scalable, non-invasive tools for autonomous assessment. This research investigates whether multimodal physiological signals — cough, speech, breath, and vital signs — collected through a portable equipment called Integrated Portable Medical Assistant (IPMA) may support intelligent triage and COVID-19 inference via Machine Learning (ML) models. To address this, a two-part experimental design was conducted. The first part focused on COVID-19 detection using public datasets and real-world data collected with the IPMA. Mel-spectrograms were extracted from audio signals, followed by texture-based feature extraction using Local Binary Pattern (LBP) and Local Ternary Pattern (LTP). LBP consistently outperformed LTP across classification tasks, with speech showing the highest discriminative power, and SpO2 and temperature emerging as the most informative physiological indicators. Although trained on public datasets, models achieved moderate generalization to IPMA data, particularly for speech and breath signals. The second part evaluated clinical risk classification based on the Manchester Triage System through a structured approach that included data preprocessing, comparison of ML and Deep Learning (DL) models, and usability assessment. Using a public pediatric dataset, ensemble classifiers such as XGBoost and Stacking achieved F1-scores above 0.99 when trained on comprehensive clinical features. Additionally, promising results were obtained using primarily vital signs and low-subjectivity variables, with models reaching F1-scores around 0.74, demonstrating the potential of objective data for low-bias risk stratification in autonomous systems. However, when tested on adult data collected with IPMA, the models showed limited performance, indicating challenges in generalizing across different populations and clinical contexts. Usability was also a central component of this study. Standardized evaluations using the System Usability Scale (SUS) (and Post-Study System Usability Questionnaire — PSSUQ — for the COVID-19 task) indicated high user acceptance of the IPMA by both patients and healthcare professionals. Reported scores reflect the system’s ease of use and perceived integration into clinical workflows, reinforcing its potential for deployment in real-world triage and screening scenarios.
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    Limitação das correntes de curto-circuito para minimizar o impacto da elevada integração de geração distribuída na proteção de alimentadores em média tensão
    (Universidade Federal do Espírito Santo, 2024-09-13) Rocha Junior, Edmilson Bermudes; Simonetti, Domingos Sávio Lyrio ; https://orcid.org/0000-0001-5920-2932; http://lattes.cnpq.br/1107005171102255; Batista, Oureste Elias ; http://orcid.org/0000-0003-4719-4132; http://lattes.cnpq.br/3717606765861586; http://orcid.org/0000-0001-8956-8548; http://lattes.cnpq.br/8631253817692368; Fardin, Jussara Farias; https://orcid.org/0000-0003-4785-556X; http://lattes.cnpq.br/1912113095988528; Santos, Walbermark Marques dos; https://orcid.org/0000-0002-9871-6028; http://lattes.cnpq.br/5558697161842579; Lopes, Felipe Vigolvino; https://orcid.org/0000-0001-6465-8045; http://lattes.cnpq.br/3155646870666658; Araújo, Marcel Ayres de ; https://orcid.org/0000-0002-3403-4650; http://lattes.cnpq.br/0669410110930611
    With the increasing number of distributed generators connected to distribution systems, which traditionally had centralized generation, networks are now configured to allow bidirectional energy flow. This scenario has significant impacts on short-circuit currents, not only altering their magnitude but also their direction, directly affecting the effectiveness of overcurrent protections. The complexity is compounded by the fact that algorithms used by protection device manufacturers are not publicly disclosed, hindering advancements in the field of protection. This study investigates the behavior of short-circuit currents in a context of high penetration of distributed generation, considering different types of faults at specific locations on a medium-voltage distribution feeder. The technique adopted for short-circuit current detection involves defining a reference current value, reading instantaneous current values in each phase, comparing them with the reference value, and calculating the derivative using the Euler method. This approach was implemented alongside a solid-state current limiter on the IEEE 13 NTF test feeder with varying levels of power injected by distributed generators. Simulation results indicate an average detection time of approximately 250 ms. Regarding current limitation, significant variations in short-circuit current magnitudes were observed. The highest average variations were 85.01% for single-phase faults, 87.60% for two-phase faults, and 94.09% for three-phase faults
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    AI-based strategies for handover enhancement in visible light communication systems
    (Universidade Federal do Espírito Santo, 2025-03-21) Camporez, Higor Araújo Fim; Silva, Jair Adriano Lima; https://orcid.org/; http://lattes.cnpq.br/3099010533644898; Wortche, Heinrich; https://orcid.org/0000-0003-2263-0495; http://lattes.cnpq.br/4357799865954315; Rocha, Helder Roberto de Oliveira; https://orcid.org/0000-0001-6215-664X; http://lattes.cnpq.br/8801325729735529; https://orcid.org/0000-0003-2197-8588; http://lattes.cnpq.br/5910374743077555; Pohl, Alexandre de Almeida Prado; https://orcid.org/0000-0003-1300-4679; http://lattes.cnpq.br/9118815178885363; Zanotelli, Tiago; https://orcid.org/0000-0001-9467-2710; http://lattes.cnpq.br/7490836346926791; Pontes, Maria José; https://orcid.org/0000-0002-9009-2425; http://lattes.cnpq.br/4148956242627659; Ciarelli, Patrick Marques; https://orcid.org/0000-0003-3177-4028; http://lattes.cnpq.br/1267950518719423
    The Internet of Things (IoT) growth, particularly applications involving wireless devices, has significantly increased the demand for signal bandwidth. However, Radio Frequency (RF) wire less systems presented a limited spectrum to support massive device connections and suscepti bility to electromagnetic interference. These challenges have increased the interest in exploring alternative solutions to face RF issues while maintaining high data rates, low latency, reliability, and cost efficiency. Advancements in Light Emitting Diode (LED) technology have introduced highly energy-efficient lighting capable of high-speed modulation of light intensity. Thus, these characteristics have driven research into Visible Light Communication (VLC), which can uti lize existing lighting infrastructures for data transmission using a broad and unregulated optical spectrum (≈ 400 THz). Additionally, VLC can also provide physical layer security, low power consumption, high transmission speeds, and immunity to RF electromagnetic interference. Spectral efficiency and high data rates are critical for VLC systems, with Orthogonal Fre quency Division Multiplexing (OFDM) emerging as a robust and spectrally efficient modulation technique for indoor applications. However, nonlinearities introduced by multicarrier signals in LED-based systems can degrade performance. To address these issues, techniques such as Constant-Envelope OFDM (CE-OFDM) have been developed to mitigate Peak-to-Average Power Ratio (PAPR), improving power efficiency and reducing distortions, particularly in high power transmission scenarios. Additionally, VLC faces several challenges, including signal blockage by opaque objects, confinement of signals, and limited Access Point (AP) coverage. Addressing these limitations often requires deploying ultra-dense networks to ensure reliable connectivity across large areas. However, such dense deployments can lead to frequent han dovers, increasing infrastructure costs and complexity. This thesis evaluates the application of larger signal amplitudes despite the LED-nonlinearities to enable data transmission over long distances, evaluating the conventional and constant envelope OFDMperformances. Furthermore, it proposes a ModifiedGeneticAlgorithm(MGA) optimization procedure combined with time series Machine Learning (ML) classifiers to min imize handovers in both a digital twin-based simulation system and experimental VLC setups. The proposed handover scheme considers receiver trajectory information to reduce handover frequency while maintaining system performance within the forward error correction limit. Results demonstrate that a 9.51 Mb/s CE-OFDM system with 16-QAM subcarrier map ping in a 5MHz bandwidth outperformed a conventional OFDM system in terms of efficiency. The application of the CE-OFDM scheme in a 6m VLC link reduced the EVM from 17.5%to 10%, an improvement of approximately 43%. Additionally, the CE-OFDM-based VLC system demonstrated satisfactory performance in an 8 m link when using 4-QAM subcarrier mapping. The proposed handover scheme outperforms a power-based approach, achieving han dover reductions of 42.47% in a MISO simulation environment and up to 48.61% in a MIMO environment. In experimental scenarios with three and four transmitters, the scheme achieved reductions of 46.43% and 45.45%, respectively. These results confirm that the integration of MGAwithMLmodelseffectively minimizes handovers and improves overall VLC system per formance