Artículos (Ingeniería Electrónica)

URI permanente para esta colecciónhttps://hdl.handle.net/11441/11357

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Predictive Current Control of a Five-Phase Drive Using a Lead-Pursuit Strategy and Virtual Voltage Vectors
(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Barrero, Federico; Bermúdez Guzmán, Mario; Arahal, Manuel R.; González Prieto, Ignacio; Ingeniería Electrónica; Ingeniería Eléctrica; Ingeniería de Sistemas y Automática; Ministerio de Ciencia, Innovación y Universidades (MICIU). España; European Union (UE)
Modern electric machines are attracting the greatest interest from the research community due to their current increasing number of applications, including electric vehicles and wind power generators. Their use requires the development of complex regulators, where predictive controllers appear as interesting and viable alternatives in recent research works. Although these controllers have an easy formulation and high flexibility to incorporate different control objectives in multidimensional systems, they have limitations that require attention and limit their application: a high computational cost and current harmonic content. This work presents a novel controller that focuses on these limitations, where the additional degree of freedom introduced in the predictive controller through the lead-pursuit guidance law concept is combined with the use of virtual voltage vectors to reduce the harmonic content in a controlled drive. The effectiveness of the proposed controller is explored using a five-phase drive and several figures of merit, such as the root mean square error in current tracking, the total harmonic distortion in the stator currents, and the number of switching commutations per cycle. Different predictive controllers are compared with the proposal in terms of speed regulation, stator current control, and steady-state performance, where the results obtained are analyzed to show the interest, improvements, and limitations of the proposal.
On the Usage of Deep Learning Techniques for Unmanned Aerial Vehicle-Based Citrus Crop Health Assessment
(MDPI, 2025-06-30) Gálvez, Ana I.; Afonso, Frederico; Martínez Heredia, Juana María; Universidad de Sevilla. Departamento de Ingeniería Electrónica
This work proposes an end-to-end solution for leaf segmentation, disease detection, and damage quantification, specifically focusing on citrus crops. The primary motivation behind this research is to enable the early detection of phytosanitary problems, which directly impact the productivity and profitability of Spanish and Portuguese agricultural developments, while ensuring environmentally safe management practices. It integrates an onboard computing module for Unmanned Aerial Vehicles (UAVs) using a Raspberry Pi 4 with Global Positioning System (GPS) and camera modules, allowing the real-time geolocation of images in citrus croplands. To address the lack of public data, a comprehensive database was created and manually labelled at the pixel level to provide accurate training data for a deep learning approach. To reduce annotation effort, we developed a custom automation algorithm for pixel-wise labelling in complex natural backgrounds. A SegNet architecture with a Visual Geometry Group 16 (VGG16) backbone was trained for the semantic, pixel-wise segmentation of citrus foliage. The model was successfully integrated as a modular component within a broader system architecture and was tested with UAV-acquired images, demonstrating accurate disease detection and quantification, even under varied conditions. The developed system provides a robust tool for the efficient monitoring of citrus crops in precision agriculture.
Integrated Bragg Grating Spectra
(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Praena, José Ángel; Carballar Rincón, Alejandro; Universidad de Sevilla. Departamento de Ingeniería Electrónica
In this paper, we present a general methodology suitable for analyzing any IBG (Integrated Bragg Grating) as a linear time-invariant (LTI) system using the effective refractive index (ERI) and transfer matrix method (TMM). This approach is based on the translation of the IBG’s physical structure into a matrix of effective refractive indexes, neff, which is wavelength-dependent and describes the behavior of light in the IBG while avoiding the use of approximations like Coupled Mode Theory does. This procedure allows to obtain very accurate reflection and transmission spectra, regardless of the perturbation complexity of the grating. Using this methodology, different apodization and chirp methods are revised and compared. Its generality is considered by analyzing two distinct technological platforms, silicon-on-insulator (SOI) and aluminum oxide (Al2O3).
Automatic and Versatile Test Bench for Data Collection on Battery Cells
(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Marsal Pederzani, Esteban; Martínez Cantero, Nicolás; Pérez Vega-Leal, Alfredo; Barrero, Federico; Hamdan, Mohamad; Garrido Satué, Manuel; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Ministerio de Ciencia e Innovación (MICIN). España; European Union (UE)
Rechargeable batteries are a key component of sustainable future systems, as their performance directly affects energy efficiency, maintenance costs, and system reliability. Assessing performance requires evaluating parameters such as the state of health (SoH) of the battery, which necessitates developing a system capable of efficiently gathering large amounts of data. This article presents a safe, simple, versatile, and automated system designed to test and characterize various types of battery cells. The system is conceived as a practical tool capable of automatically collecting the required data for analysis, thus enabling the determination of the performance parameters of a battery cell. The proposed system incorporates an innovative approach based on the concatenation of charge/discharge data, allowing for a more reliable evaluation of battery performance. Experimental tests show the interest and performance behavior of the proposed system.
A Review of Techniques to Enhance an Amplifier’s Performance Using Resistive Local Common Mode Feedback
(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Ramírez Angulo, Jaime; López Martín, Antonio J.; González Carvajal, Ramón; Torralba Silgado, Antonio Jesús; Huerta Chua, Jesús; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Agencia Estatal de Investigación. España; Junta de Andalucía
A review of some of the most common applications of the resistive local common mode feedback technique to enhance amplifier’s performance is presented. It is shown that this simple technique offers essential improvement in open loop gain, gain-bandwidth product, slew rate, common mode rejection ratio, power supply rejection ratio, etc. This is achieved without increasing power dissipation or supply voltage requirements and with small additional silicon area and circuit complexity. It is also shown that it is especially appropriate to improve amplifiers’ performance in current fine-line submicrometer CMOS technology. Some of the applications discussed are GB enhanced, class AB and super class AB operational amplifiers, gain boosted op-amps, bulk-driven circuits, sample and hold circuits and power management circuits, among others.
Structural assessment of the medieval city wall of Seville (Spain) using low-cost accelerometers
(Elsevier, 2025-06) Serrano Chacón, Álvaro Rubén; Mascort-Albea, Emilio J.; Romero Hernández, Rocío; Canivell, Jacinto; Muñoz Chavero, Fernando; Hidalgo Fort, Eduardo; Jaramillo Morilla, Antonio; Universidad de Sevilla. Departamento de Ingeniería del Diseño; Universidad de Sevilla. Departamento de Estructuras de Edificación e Ingeniería del Terreno; Universidad de Sevilla. Departamento de Construcciones Arquitectónicas II (ETSIE); Universidad de Sevilla. Departamento de Ingeniería Electrónica; Ministerio de Educación, Cultura y Deporte (MECD). España; Universidad de Sevilla. TEP018: Ingeniería del Terreno; Universidad de Sevilla. TEP211: Conservación Preventiva del Patrimonio Construido; Universidad de Sevilla. TIC192: Ingeniería Electrónica
The remains of fortifications are commonly found embedded in the contemporary urban fabric of historic cities. Due to their typological nature, these heritage assets are usually elements of great size and impact on the urban landscape. Their location within cities exposes them to very specific risks, such as pollution, vibration, biodegradation, and anthropic factors, which must be taken into account for the proper conservation and maintenance of such remains. The case of the medieval wall of Seville (Spain), built on rammed earth, shows specific factors of vulnerability, degradation, and erosion which prompt the need for non-destructive techniques (NDT). In the present research, vibration-based inspection is used and, specifically, when subjected to ambient vibrations. The collection of accelerations, which covered a period of nine months, was conducted in different parts of the structure under study by using mainly high-resolution accelerographs. These data allowed to perform an exhaustive dynamic characterisation of this defensive structure. Among other findings, it was determined that the filling of cracks and voids in the walls increased the fundamental frequency by about 2 %. In addition, no serious damage to the structure was found. Knowledge of the historic buildings' condition is essential in order to determine the most appropriate intervention. To this end, a protocol for the global structural diagnosis of these buildings has been proposed. It is based on the recording of accelerations with low-cost accelerographs. Besides being an inexpensive protocol, it allows a quick decision making, since the dynamic characterization of the structure is performed by means of the fast Fourier transform. Basically, the designed protocol is based on the variation of the fundamental frequency of the structure between two time instants. These values are used for the calculation of a damage index. By means of an exhaustive review of conventional masonry buildings tested in the laboratory, the damage index has been correlated with the state of the structure prior to collapse. Specifically, this threshold, which ranges from DS4 to DS5 according to the criteria of the European Macroseismic Scale 1998 (EMS-98), provides a valuable reference point for the structural assessment of historical box-shaped constructions with conventional masonry load-bearing walls. This simplified procedure for structural diagnosis was applied in its initial phase at the White Tower. It was found that this protocol is able to identify the fundamental frequency of the structure with an error of <0.65 % in comparison to the results obtained through operational modal analysis methods.
Decoupling Patrolling Tasks for Water Quality Monitoring: A Multi-Agent Deep Reinforcement Learning Approach
(IEEE, 2024) Seck Diop, Dame; Yanes Luis, Samuel; Perales Esteve, Manuel Ángel; Toral, S. L.; Gutiérrez Reina, Daniel; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Ministerio de Ciencia e Innovación (MICIN). España; European Union (UE)
This study proposes the use of an Autonomous Surface Vehicle (ASV) fleet with water quality sensors for efficient patrolling to monitor water resource pollution. This is formulated as a Patrolling Problem, which consists of planning and executing efficient routes to continuously monitor a given area. When patrolling Lake Ypacaraí with ASVs, the scenario transforms into a Partially Observable Markov Game (POMG) due to unknown pollution levels. Given the computational complexity, a Multi-Agent Deep Reinforcement Learning (MADRL) approach is adopted, with a common policy for homogeneous agents. A consensus algorithm assists in collision avoidance and coordination. The work introduces exploration and reinforcement phases to the patrolling problem. The Exploration Phase aims at homogeneous map coverage, while the Intensification Phase prioritizes high polluted areas. The innovative introduction of a transition variable, ν, efficiently controls the transition from exploration to intensification. Results demonstrate the superiority of the method, which outperforms a Single-Phase (trained on a single task) Deep Q-Network (DQN) by an average of 17% on the intensification task. The proposed multitask learning approach with parameter sharing, coupled with DQN training, outperforms Task-Specific DQN (two DQNs trained on separate tasks) by 6% in exploration and 13% in intensification. It also outperforms the heuristic-based Lawn Mower Path Planner (LMPP) and Random Wanderer Path Planner (RWPP) algorithms, by 35% and 20% on average respectively. Additionally, it outperforms a Particle Swarm Optimization-based Path Planner (PSOPP) by an average of 26%. The algorithm demonstrates adaptability in unforeseen scenarios, giving users flexibility in configuration.
Variational model-based Deep Reinforcement Learning for Non-Homogeneous Patrolling aquatic environments with multiple unmanned surface vehicles
(Elsevier, 2025-04-25) Yanes Luis, Samuel; Basilico, Nicola; Antonazzi, Michele; Gutiérrez Reina, Daniel; Toral, S. L.; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Universidad de Sevilla. TIC201: ACE-TI
This paper addresses the challenge of Non-Homogeneous Patrolling for Autonomous Surface Vehicles in non-homogeneous importance water environments with a dissimilar biological monitorization criterion. Traditional monitoring methods fail, especially in expansive areas such as Lake Ypacaraíin Paraguay. The proposed solution employs a cooperative Deep Reinforcement Learning framework, specifically a multi-agent version of the Double Deep Q-Learning algorithm based on safe-consensus decision making. This framework optimizes adaptive policies for such vehicles by simultaneously modeling the environment and patrolling high-importance zones. The incorporation of a Variational Auto-Encoder based on the U-Network architecture directly addresses the non-observability of the environment by predicting biological importance from partial observations. The methodology is validated in a realistic algae bloom contamination scenario, demonstrating superior performance and computational efficiency compared to traditional approaches like Gaussian Processes and K-Nearest-Neighbors. The Deep Reinforcement Learning framework, coupled with the Variational Auto-Encoder model, showcases flexibility and efficiency in addressing multi-agent cooperation and long-term objective optimization for water quality monitoring. The results reveal significant improvements, with the proposed model exceeding well-founded approaches with a 30% faster minimization of the patrolling score compared to these methods.
Cascade Control of Grid-Connected NPC Converters Via Sliding Mode Technique
(Institute of Electrical and Electronics Engineers, 2023-02) Shen, Xiaoning; Liu, Jianxing; Lin, Hao; Yin, Yunfei; Márquez Alcaide, Abraham; León Galván, José Ignacio; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Universidad de Sevilla. TIC109: Tecnología
This paper proposes a two-stage control strategy including an adaptive sliding mode control (ASMC) and a nonlinear high-gain observer (HGO) for the three-level neutral-point-clamped (NPC) converter in dc microgrids. In the outer loop, an ASMC is utilized to regulate the dc-link voltage. By introducing an adapted gain, the tradeoff between the chattering and dynamic performance of the classic sliding mode control is overcome, thus the transient response of the NPC converter can be further enhanced without increasing the chattering. In addition, a nonlinear HGO is cooperated with the ASMC method to reject exogenous disturbance for the NPC converter, which not only assures a high disturbance rejection capacity but also accommodates the inevitable measurement noise in the actual applications. For the inner loop, in consideration of the parameter uncertainty, a high-gain observer-based second-order sliding mode (SOSM) control is adopted to assure the steady state performance and the robustness of the NPC converter. Finally, a set of comparative experimental results confirm the effectiveness and superiority of the proposed control scheme implemented in the NPC converter. Additionally, the robustness under parameter variation of the proposed method is also validated.
Towards a Retrieval-Augmented Generation Framework for Originality Evaluation in Projects-Based Learning Classrooms
(MDPI, 2025-06) Yanes Luis, Samuel; Gutiérrez Reina, Daniel; Toral, S. L.; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Junta de Andalucía; Universidad de Sevilla. TIC201: ACE-TI
Project-Based Learning is central to modern engineering education, but assessing the originality of student work poses significant challenges, particularly when previous project repositories are accessible. This paper addresses the issue by proposing a framework based on Retrieval-Augmented Generation and Large Language Models to evaluate the originality of project proposals in the context of a master’s course in Electronic Engineering. The system processes and summarizes prior work—including reports, code, and presentations—creating a semantically indexed knowledge base. Upon receiving a new proposal, the RAG system compares it to this base, identifies the most similar previous works, and generates an originality assessment. Results show the effectiveness of the approach, with a strong correlation (coefficient of 0.87) between the originality scores assigned by the system and those given by expert instructors in a blind evaluation. The proposed RAG system demonstrates its ability to systematically detect similarities and potential lack of originality that might be overlooked by human evaluators due to the volume of prior work. This framework provides an objective and efficient tool to support originality assessment, benefiting both instructors and students by promoting genuine innovation in PBL settings.
Computational Analysis of the Long Horizon FCS-MPC Problem for Power Converters
(Institute of Electrical and Electronics Engineers, 2024-06) Zafra, Eduardo; Vázquez Pérez, Sergio; Geyer, Tobías; Aguilera, Ricardo P.; Freire Macías, Emilio; García Franquelo, Leopoldo; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Universidad de Sevilla. Departamento de Matemática Aplicada II (ETSI); Ministerio de Ciencia e Innovación (MICIN). España; Universidad de Sevilla. TIC109: Tecnología
Long prediction horizon finite control set model predictive control (LPH-FCS-MPC) for power converters can be reformulated as a box-constrained integer-least squares (ILS) problem to find the optimal control action without requiring an exhaustive search. Instead, the solution can be found by means of a sphere decoding method that still presents several intricacies regarding its complexity and its variable computational cost. This article provides a study of the computational behavior of this approach. Special emphasis is placed on how the generator matrix is calculated, either as a lower or an upper triangular structure. This choice decides whether the switching sequences are explored forward- or backward-in-time during the optimization process. In this work, it is explained how this selection holds a great impact on the computational burden of the algorithm. Similarly, it is also analyzed how the tuning of the FCS-MPC and system parameters also drastically impacts the computational cost.
Common DC-link Capacitor Lifetime Extension in Modular dc/dc Converters for Electric Vehicle Fast Chargers via Variable-Angle Interleaved Operation
(Institute of Electrical and Electronics Engineers, 2022-12) Márquez Alcaide, Abraham; Guenter, Sandro; León Galván, José Ignacio; Buticchi, Giampaolo; Kouro, Samir; García Franquelo, Leopoldo; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Ministerio de Ciencia e Innovación (MICIN). España; Junta de Andalucía; Universidad de Sevilla. TIC109: Tecnología
The global shift toward the electrified transportation as a means of achieving decarbonized economy has led to an increase in the demand of electric vehicles. In order to enhance the transition, there is a need to develop fast and ultrafast charging substations. Hence, power converters play an inherently vital role in the mass adoption of electric vehicles. However, the reliability and active maintenance scheduling of these converters are becoming prominent issues for manufacturers and operators. As a result, optimization of the operation of an interleaved dc/dc converter present in the charging poles plays a significant role. This article proposes an alternative modulation technique for interleaved dc/dc power converters of fast chargers aiming to improve the harmonic performance of the common dc-link capacitor current. This technique leads to an extension of lifetime of the capacitor, which is one of the most critical component of the power system. Experimental results are shown in order to validate the effectiveness of the proposed method.
Capacitor Lifetime Extension of Interleaved dc-dc Converters for Multi-String PV Systems
(Institute of Electrical and Electronics Engineers, 2022-07) Márquez Alcaide, Abraham; Ko, Youngjong; Andresen, Markus; León Galván, José Ignacio; Vázquez Pérez, Sergio; Monopoli, Vito Giuseppe; Buticchi, Giampaolo; Liserre, Marco; García Franquelo, Leopoldo; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Ministerio de Ciencia e Innovación (MICIN). España; Junta de Andalucía; Universidad de Sevilla. TIC109: Tecnología
Interleaved dc–dc converters are being vastly applied for a wide range of applications. Inherent power sharing between the power modules and reduction of the output waveforms ripple are the main advantages of these power systems. However, in some cases, such as the multistring photovoltaic converters, each power module manages different power, leading to an unbalanced operation of the interleaved converters. In this case, the harmonic response of the conventional interleaving operation is degraded. This fact affects directly the expected lifetime of the dc-link capacitor of the power converter, which is one critical components of the system. In this article, a variable-angle phase displacement angle is proposed in order to mitigate this problem, achieving an extension of the converter lifetime.
Generalized Multi-Carrier PWM Technique for Two-level Voltage Source Inverters
(Institute of Electrical and Electronics Engineers, 2022-07) Márquez Alcaide, Abraham; Monopoli, Vito Giuseppe; Zafra, Eduardo; Buticchi, Giampaolo; León, Galván, José Ignacio; Vázquez Pérez, Sergio; Liserre, Marco; García Franquelo, Leopoldo; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Ministerio de Ciencia e Innovación (MICIN). España; Junta de Andalucía; Ministerio de Ciencias, Innovación y Universidades; Universidad de Sevilla. TIC109: Tecnología
Two-level voltage source inverters are the mainstream solution for many power applications. The conventional modulation method of such inverters is the single-carrier pulsewidth modulation (PWM) technique. In this article, the usage of a generalized PWM method with three independent carriers is analyzed. The carrier phase-displacement angles are evaluated in order to reduce the common-mode voltage (CMV) total harmonic distortion (THD), the dc-link capacitor current THD, and the phase currents THD. These targets are difficult to be met at the same time and a cost function is deployed in order to look for a suitable solution that develops a tradeoff between all the targets. The proposed method has been tested in a laboratory prototype demonstrating its superior performance.
Lifetime Extension Approach Based on Levenberg-Marquardt Neural Network and Power Routing of DC-DC Converters
(Institute of Electrical and Electronics Engineers, 2023-05) Zhang, Jiusi; Tian, Jilun; Marquez Alcaide, Abraham; León Galván, José Ignacio; Vázquez Pérez, Sergio; García Franquelo, Leopoldo; Luo, Hao; Yin, Shen; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Universidad de Sevilla. TIC109: Tecnología
The power conversion system based on the modular connection has widespread applications in various power electronic systems. To accurately estimate the state of health without recognizing the systematic mathematical model and to extend the lifetime, this article proposes a lifetime extension approach based on the Levenberg–Marquardt back propagation neural network (LM-BPNN) and power routing of interleaved dc–dc boost conversion systems. The LM-BPNN model is constructed based on the voltage, current, and temperature data generated by the system. On the basis of the trained LM-BPNN, the real-time cumulated damage estimation of each power cell in the conversion system can be accomplished. Applying the power routing concept, the dc–dc boost conversion system allocates different power to the cells according to the cumulated damage of each cell, thereby delaying the failure of cells with higher cumulated damage. Numerical simulation results show that the proposed lifetime extension approach can extend the overall system lifetime. Furthermore, an experimental setup of the interleaved dc–dc boost conversion is constructed to verify the proposed approach, which is of great significance for predictive maintenance in the industrial system.
An Artificial Intelligence Approach for Real-Time Tuning of Weighting Factors in FCS-MPC for Power Converters
(Institute of Electrical and Electronics Engineers, 2021-12) Vázquez Pérez, Sergio; Marino, Daniel; Zafra, Eduardo; Valdés Peña, María Dolores; Rodríguez-Andina, Juan J.; García Franquelo, Leopoldo; Manic, Milos; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Ministerio de Ciencia e Innovación (MICIN). España; Universidad de Sevilla. TIC109: Tecnología
In this paper a finite control set model predic- tive control is used to track a current reference in a power converter connected to an RL load. An artificial intelligence (AI) approach is presented for real-time determination of the weighting factor that regulates the average switching frequency, independently of the operating point. The paper focuses on the design, training, and digital implementation of an artificial neural network (ANN) that can be developed in a low-cost control platform. It is presented a sampling and offline ANN training procedure, together with a low- cost hardware implementation based on integer quantiza- tion of the ANN. The above approach provides a standalone application, serving as a framework for development of ANN applications for power-converters. The main advan- tage of the presented approach is that the ANN inference is executed in real-time. In this way, the weighting factor is automatically updated in real-time, allowing the system to quickly adapt to any reference step changes, and conse- quently provide the desired behavior. Executing the setup in laboratory prototype confirmed the theoretical analysis and successful tracking of the reference frequency
Period Control Approach FCS-MPC Switching Phase Control for Interleaved DC/DC Converters
(Institute of Electrical and Electronics Engineers, 2023-11) Aguirre, Matías; Vázquez Pérez, Sergio; Márquez Alcaide, Abraham; Portillo Guisado, Ramón Carlos; Kouro, Samir; León Galván, José Ignacio; García Franquelo, Leopoldo; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Ministerio de Ciencia e Innovación (MICIN). España; Universidad de Sevilla. TIC109: Tecnología
The control of interleaved converters is commonly implemented through pulsewith modulation (PWM) techniques. A common element in these implementations is the use of phase shift between carriers to improve the system performance. When working with a balanced system, this phase shift is equally distributed between modules, but for an unbalanced system, this is no longer the best alternative. Changing the phase shift in these controllers requires the implementation of new capabilities in the control platforms, and for the controller to manage more variables of different nature. On the other hand, finite control set model predictive control (FCS-MPC) has shown to be a promising control strategy, especially when managing multiple control objectives of different natures or dynamics. In general, FCS-MPC does not present a fixed switching pattern, but this issue has been recently addressed with the so called period control approach (PCA). This article expands on the PCA-FCS-MPC to achieve the switching phase regulation for interleaved dc/dc power converters. A switching pattern similar to that of PWM techniques is achieved, while keeping the advantages of FCS-MPC and achieving the phase shift required for interleaved operation. Simulation and experimental results confirm the effectiveness of the proposed method.
Hybrid Sphere Decoder for Long Prediction Horizon FCS-MPC
(Institute of Electrical and Electronics Engineers, 2022-08) Zafra, Eduardo; Vázquez Pérez, Sergio; Márquez Alcaide, Abraham; Pérez Martín, Emilia; García Franquelo, Leopoldo; León Galván, José Ignacio; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Ministerio de Ciencia e Innovación (MICIN). España; Universidad de Sevilla. TIC109: Tecnología
In finite control set model predictive control strategies, extending the prediction horizon length provides important closed-loop performance improvements. However, the computational costs are increased in exponential fashion. Transforming the problem to an equivalent box-constrained integer least-squares formulation enables the usage of sphere decoding algorithms (SDA) that can efficiently solve this problem. Recently, a K-best sphere decoder was proposed and designed for hardware platforms. This algorithm follows a breadth-first strategy different to the conventional SDA. In this work, a hybrid SDA that combines the merits of both the K-best SDA and the conventional SDA is proposed with the objective of increasing optimality likelihood and improve control performance. In particular, it is proposed that a K-best sphere decoder delivers a preliminary optimal solution. Then, a conventional SDA uses the available calculation time to search for a better solution. Simulation and experimental results confirm the validity of the proposal in terms of performance and computational efficiency.
A Furtherance of High-Power Adjustable Speed Drive System
(Institute of Electrical and Electronics Engineers, 2022-11) Deng, Fujin; Hou, Jiehua; Zhang, Yue; Cheng, Ming; Hu, Yihua; Vázquez Pérez, Sergio; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Universidad de Sevilla. TIC109: Tecnología
The high-power machine drive system is the power heart of the modern power industry, which has been used in a broad range of industry applications. Extensive research and development efforts have been carried out on the design and implementation of high-power machine drive systems. In this article, various converter topologies and research progress for high-power machine drive systems are reviewed. And a novel medium-frequency ac link powered machine drive system is analyzed and discussed for a furtherance of high-power adjustable speed drive systems. In addition, some prospects for future research are highlighted to provide a feasible reference for practitioner
Discontinuous PWM Technique with Reduced Low-order Harmonic Distortion for High-Power Applications
(Institute of Electrical and Electronics Engineers, 2023-10) Balenciaga, Jon Xabier; Márquez Alcaide, Abraham; León Galván, José Ignacio; Aldazabal, Eritz; Madariaga, Danel; Legarra, Iraitz; García Franquelo, Leopoldo; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Ministerio de Ciencia e Innovación (MICIN). España; Universidad de Sevilla. TIC109: Tecnología
The modulation techniques used in high power applications have to generate high quality waveforms with reduced switching losses. As an attractive alternative, discontinuous PWM (DPWM) techniques present lower device switching frequencies than conventional continuous PWM methods lowering the converter switching loss. Considering the same cooling system, this allows to increase the carrier frequency of DPWM methods displacing the main switching harmonics to higher frequencies. As a main drawback, when low carrier to fundamental ratios are used, DPWM methods present some undesired low-order harmonics that are required to be filtered. This article presents a low-order harmonic minimization method for synchronous DPWM methods by modifying the conventional modulating reference to limit low order harmonics amplitude, while keeping the same effective switching frequency and thus limited switching losses.

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