All Outputs (65)

Model Predictive Control of a Modular Multilevel Converter with Reduced Computational Burden (2024)
Journal Article
Kadhum, H., Watson, A. J., Rivera, M., Zanchetta, P., & Wheeler, P. (2024). Model Predictive Control of a Modular Multilevel Converter with Reduced Computational Burden. Energies, 17(11), Article 2519. https://doi.org/10.3390/en17112519

Recent advances in high-power applications employing voltage source converters have been primarily fuelled by the emergence of the modular multilevel converter (MMC) and its derivatives. Model predictive control (MPC) has emerged as an effective way... Read More about Model Predictive Control of a Modular Multilevel Converter with Reduced Computational Burden.

Reduced Computational Burden of Modulated Model-Predictive Control for Synchronous Reluctance Motor Drive Applications (2023)
Presentation / Conference Contribution
Riccio, J., Karamanakos, P., Degano, M., Gerada, C., & Zanchetta, P. (2023). Reduced Computational Burden of Modulated Model-Predictive Control for Synchronous Reluctance Motor Drive Applications. In 2023 IEEE Energy Conversion Congress and Exposition (ECCE) (4995-5002). https://doi.org/10.1109/ECCE53617.2023.10362110

This paper introduces a novel geometric approach to significantly reduce the computational burden of modulated predictive controllers while maintaining the same steady-state performance and satisfactory dynamic behavior. The proposed geometric method... Read More about Reduced Computational Burden of Modulated Model-Predictive Control for Synchronous Reluctance Motor Drive Applications.

Artificial Intelligence Techniques for Enhancing the Performance of Controllers in Power Converter-Based Systems—An Overview (2023)
Journal Article
Gao, Y., Wang, S., Dragicevic, T., Wheeler, P., & Zanchetta, P. (2023). Artificial Intelligence Techniques for Enhancing the Performance of Controllers in Power Converter-Based Systems—An Overview. IEEE Open Journal of Industry Applications, 4, 366-375. https://doi.org/10.1109/OJIA.2023.3338534

The integration of artificial intelligence (AI) techniques in power converter-based systems has the potential to revolutionize the way these systems are optimized and controlled. With the rapid advancements in AI and machine learning technologies, th... Read More about Artificial Intelligence Techniques for Enhancing the Performance of Controllers in Power Converter-Based Systems—An Overview.

A Reconfigurable Cascaded Multilevel Converter for EV Powertrain (2023)
Journal Article
Tresca, G., Formentini, A., Riccio, J., Anglani, N., & Zanchetta, P. (2024). A Reconfigurable Cascaded Multilevel Converter for EV Powertrain. IEEE Transactions on Industry Applications, 60(2), 3332-3344. https://doi.org/10.1109/TIA.2023.3337763

This paper presents a new topology for EV powertrain, called Reconfigurable Cascaded Multilevel Converter, able to simultaneously implement power conversion and active battery system management. The latter feature is performed through the Reconfigura... Read More about A Reconfigurable Cascaded Multilevel Converter for EV Powertrain.

Encoderless Predictive Speed and Torque Control of an Induction Motor (2023)
Presentation / Conference Contribution
Zerdali, E., Rivera, M., Zanchetta, P., Wheeler, P., & Ristić, L. (2023). Encoderless Predictive Speed and Torque Control of an Induction Motor. In 2023 22nd International Symposium on Power Electronics (Ee). https://doi.org/10.1109/ee59906.2023.10346148

Recently, model predictive control (MPC) has gained popularity in the control of power converters and electric drives. In this paper, the advantages of two MPC strategies are combined, and a cascaded encoderless predictive speed and torque control (P... Read More about Encoderless Predictive Speed and Torque Control of an Induction Motor.

Model Predictive Control of Modular Multilevel Converter with High Number of Submodules (2023)
Presentation / Conference Contribution
Kadhum, H., Alan, W., Saleh, B. M., Marco, R., Pericle, Z., & Patrick, W. (2023). Model Predictive Control of Modular Multilevel Converter with High Number of Submodules. In 2023 25th European Conference on Power Electronics and Applications (EPE'23 ECCE Europe). https://doi.org/10.23919/epe23ecceeurope58414.2023.10264447

This paper proposes a Level Model Predictive Control strategy combined with a pre-processing sorting algorithm to address the processing time issue of predictive control for Modular Multilevel Converters (MMCs) with hundreds of submodules. Five contr... Read More about Model Predictive Control of Modular Multilevel Converter with High Number of Submodules.

A Study on Molecular Dynamics of High Voltage Pulsed Electrolysis (2023)
Presentation / Conference Contribution
Albornoz, M., Rivera, M., Wheeler, P., & Zanchetta, P. (2023). A Study on Molecular Dynamics of High Voltage Pulsed Electrolysis. In 2023 11th International Conference on Power Electronics and ECCE Asia (ICPE 2023 - ECCE Asia) (3430-3437). https://doi.org/10.23919/ICPE2023-ECCEAsia54778.2023.10213763

Electrolysis has been considered to be an interesting research topic in recent decades. With the important advances in controllable solid-state semiconductor devices, it has become relatively simple to design power converters with high voltage and hi... Read More about A Study on Molecular Dynamics of High Voltage Pulsed Electrolysis.

An Adaptive Data-Driven Iterative Feedforward Tuning Approach Based on Fast Recursive Algorithm: With Application to A Linear Motor (2022)
Journal Article
Fu, X., Yang, X., Zanchetta, P., Tang, M., Liu, Y., & Chen, Z. (2023). An Adaptive Data-Driven Iterative Feedforward Tuning Approach Based on Fast Recursive Algorithm: With Application to A Linear Motor. IEEE Transactions on Industrial Informatics, 19(4), 6160-6169. https://doi.org/10.1109/tii.2022.3202818

The feedforward control can effectively improve the servo performance in applications with high requirements of velocity and acceleration. The iterative feedforward tuning method (IFFT) enables the possibility of both removing the need for prior know... Read More about An Adaptive Data-Driven Iterative Feedforward Tuning Approach Based on Fast Recursive Algorithm: With Application to A Linear Motor.

Power Electronics Converters for the Internet of Energy: A Review (2022)
Journal Article
Granata, S., Di Benedetto, M., Terlizzi, C., Leuzzi, R., Bifaretti, S., & Zanchetta, P. (2022). Power Electronics Converters for the Internet of Energy: A Review. Energies, 15(7), Article 2604. https://doi.org/10.3390/en15072604

This paper presents a comprehensive review of multi-port power electronics converters used for application in AC, DC, or hybrid distribution systems in an Internet of Energy scenario. In particular, multi-port solid-state transformer (SST) topologies... Read More about Power Electronics Converters for the Internet of Energy: A Review.

Reconfigurable Cascaded Multilevel Converter design for Battery Energy System Storage (2022)
Presentation / Conference Contribution
Tresca, G., Formentini, A., Di Salvo, S., Leuzzi, R., Anglani, N., & Zanchetta, P. (2022). Reconfigurable Cascaded Multilevel Converter design for Battery Energy System Storage. . https://doi.org/10.1109/SPEEDAM53979.2022.9842134

This paper presents the Reconfigurable Cascaded Multilevel converter employed for battery energy storage systems. The main advantage lies on the possibility to fully control each battery cell, improving the overall performances of the storage system.... Read More about Reconfigurable Cascaded Multilevel Converter design for Battery Energy System Storage.

Effect of model parameter errors in model predictive control applications (2021)
Presentation / Conference Contribution
Rojas, D., Rivera, M., Munoz, J., Wheeler, P., Zanchetta, P., & Mirzaeva, G. (2021). Effect of model parameter errors in model predictive control applications. . https://doi.org/10.1109/CHILECON54041.2021.9702942

When implementing predictive control strategies for power electronic converters a good model of the system is needed because this model determines the quality of the resulting controller. In this paper a study of the model parameter error effects in... Read More about Effect of model parameter errors in model predictive control applications.

Model predictive Control of a Double Stage AC-DC Converter for Grid-Interface of Vanadium Flow Batteries (2021)
Presentation / Conference Contribution
Di Salvo, S. R., Bulzi, M., Riccio, J., Leuzzi, R., Zanchetta, P., & Anglani, N. (2021). Model predictive Control of a Double Stage AC-DC Converter for Grid-Interface of Vanadium Flow Batteries. In 2021 IEEE Energy Conversion Congress and Exposition (ECCE) (1895-1901). https://doi.org/10.1109/ECCE47101.2021.9595483

This paper presents a multi-objective model predictive control algorithm to implement the control of a bidirectional double stage ac-dc power conversion system, used to interface a Vanadium redox flow battery with a power grid. The converter topology... Read More about Model predictive Control of a Double Stage AC-DC Converter for Grid-Interface of Vanadium Flow Batteries.

A Fixed Frequency Full-Bridge Three-Level DC-DC LCL-Type Series Resonant Converter for Large Scale Solar PV Plants Applications (2021)
Presentation / Conference Contribution
Omar, A. A., Wheeler, P., Zanchetta, P., & Burgos-Mellado, C. (2021). A Fixed Frequency Full-Bridge Three-Level DC-DC LCL-Type Series Resonant Converter for Large Scale Solar PV Plants Applications. In 2021 23rd European Conference on Power Electronics and Applications (EPE'21 ECCE Europe). https://doi.org/10.23919/EPE21ECCEEurope50061.2021.9570707

Large scale solar PV plants are typically connected into medium voltage AC grids using line frequency transformers, which are bulky. In application where size and/or weight are important an attractive alternative is the use of multilevel inverter con... Read More about A Fixed Frequency Full-Bridge Three-Level DC-DC LCL-Type Series Resonant Converter for Large Scale Solar PV Plants Applications.

Cogging Force Identification Based on Self-Adaptive Hybrid Self-Learning TLBO Trained RBF Neural Network for Linear Motors (2021)
Presentation / Conference Contribution
Fu, X., Ding, C., Zanchetta, P., Yang, X., Tang, M., & Liu, Y. (2021). Cogging Force Identification Based on Self-Adaptive Hybrid Self-Learning TLBO Trained RBF Neural Network for Linear Motors. . https://doi.org/10.1109/LDIA49489.2021.9505810

The cogging force arising due to the strong attraction forces between the iron core and the permanent magnets, is a common inherent property of the linear motors, which significantly affects the control performance. Therefore, significant research ef... Read More about Cogging Force Identification Based on Self-Adaptive Hybrid Self-Learning TLBO Trained RBF Neural Network for Linear Motors.

Common-Mode Voltage Reduction in a VSI Inverter Applying Sequential Predictive Control (2021)
Presentation / Conference Contribution
Murillo-Yarce, D., Rivera, M., Restrepo, C., Munoz, J., Baier, C., Rodriguez, R., …Mirzaeva, G. (2021). Common-Mode Voltage Reduction in a VSI Inverter Applying Sequential Predictive Control. In 2021 IEEE International Conference on Automation/XXIV Congress of the Chilean Association of Automatic Control (ICA-ACCA). https://doi.org/10.1109/icaacca51523.2021.9465321

In the classical predictive control (CPC) implementation a cost function designed in terms of the control objectives and constants known as weighting factors must be minimized. Weighting factors are usually obtained by trial and error since there is... Read More about Common-Mode Voltage Reduction in a VSI Inverter Applying Sequential Predictive Control.

A Study of Cost Function Selection in Model Predictive Control Applications (2021)
Presentation / Conference Contribution
Rojas, D., Rivera, M., Wheeler, P., Zanchetta, P., Mirzaeva, G., & Rohten, J. (2021). A Study of Cost Function Selection in Model Predictive Control Applications. In 2021 IEEE International Conference on Automation/XXIV Congress of the Chilean Association of Automatic Control (ICA-ACCA). https://doi.org/10.1109/icaacca51523.2021.9465326

The cost function selection is considered one of the most relevant aspects for the implementation of Model Predictive Control strategies. In this paper a study of the most common cost functions used for the control of a two level voltage source inver... Read More about A Study of Cost Function Selection in Model Predictive Control Applications.

Optimal and automated decentralised converter control design in more electrical aircraft power electronics embedded grids (2021)
Journal Article
Dewar, D., Formentini, A., Li, K., Zanchetta, P., & Wheeler, P. (2021). Optimal and automated decentralised converter control design in more electrical aircraft power electronics embedded grids. IET Power Electronics, 14(3), 690-705. https://doi.org/10.1049/pel2.12056

In modern power systems, the proliferation of power electronics converters, and distributed generation raises important issues concerning inter-connected switching units in terms of performance, stability and robustness. Such phenomenon are more prom... Read More about Optimal and automated decentralised converter control design in more electrical aircraft power electronics embedded grids.

Sequential Predictive Current Control of a VSI with Common-Mode Voltage Reduction (2020)
Presentation / Conference Contribution
Murillo-Yarce, D., Rivera, M., Restrepo, C., Rodríguez, R., Wheeler, P. W., Zanchetta, P., & Mirzaeva, G. (2020). Sequential Predictive Current Control of a VSI with Common-Mode Voltage Reduction. In The 10th International Conference on Power Electronics, Machines and Drives (PEMD 2020) (651-656). https://doi.org/10.1049/icp.2021.1196

The voltage source inverter (VSI) is a classic topology widely used for ac conversion. In this paper sequential predictive control (SPC) is applied to a VSI converter that supplies a RL load. The objective is to demonstrate the potential of this new... Read More about Sequential Predictive Current Control of a VSI with Common-Mode Voltage Reduction.

Control of a Dual Fed Open End Winding SPMSM with a Floating Capacitor (2020)
Presentation / Conference Contribution
Minaglia, D., Rovere, L., Formentini, A., Leuzzi, R., Pipolo, S., Marchesoni, M., & Zanchetta, P. (2020). Control of a Dual Fed Open End Winding SPMSM with a Floating Capacitor. In 2020 IEEE Energy Conversion Congress and Exposition (ECCE) (4036-4043). https://doi.org/10.1109/ecce44975.2020.9235937

Surface Permanent Magnet Synchronous Motor (SPMSM) are not the first choice when a motor drive is required to operate over a wide speed range with an extended Constant Power Speed Range (CPSR). Nevertheless, SPMSMs offer high torque density, high eff... Read More about Control of a Dual Fed Open End Winding SPMSM with a Floating Capacitor.

AC-DC Isolated Matrix Converter Charger: Topology and Modulation (2020)
Presentation / Conference Contribution
Rovere, L., Pipolo, S., Formentini, A., & Zanchetta, P. (2020). AC-DC Isolated Matrix Converter Charger: Topology and Modulation. In 2020 IEEE Energy Conversion Congress and Exposition (ECCE) (1583-1588). https://doi.org/10.1109/ecce44975.2020.9235696

This paper presents the modulation strategy for the 25 kW AC-DC isolated Matrix Charger three-phase rectifier (MCharger). The proposed topology allows current and voltage regulation for energy storage devices such as EVs batteries. Compared to a stan... Read More about AC-DC Isolated Matrix Converter Charger: Topology and Modulation.