Search Results (308)

This paper presents a novel design for precise vertical landing of drones based on the detection of three phase shifts in the range of ±180°. The design has three inputs to which the signal transmitted from an oscillator located at the landing point arrives with different delays. The circuit increases the aerial tracking volume relative to that achieved by detectors with theoretical unambiguous detection ranges of ±90°. The phase shift measurement circuit uses an analog phase detector (mixer), detecting a maximum range of ±90°and a double multiplication of the input signals, in phase and phase-shifted, without the need to fulfill the quadrature condition. The calibration procedure, phase detector curve modeling, and calculation of the input signal phase shift are significantly simplified by the use of an automatic gain control on each branch, dwhich keeps input amplitudes to the analog phase detectors constant. A simple program to determine phase shifts and guidance instructions is proposed, which could be integrated into the same flight control platform, thus avoiding the need to add additional processing components. A prototype has been manufactured in C band to explain the details of the procedure design. The circuit uses commercial circuits and microstrip technology, avoiding the crossing of lines by means of switches, which allows the design topology to be extrapolated to much higher frequencies. Calibration and measurements at 5.3 GHz show a dynamic range greater than 50 dB and a non-ambiguous detection range of ±180°. These specifications would allow one to track the drone during the landing maneuver in an inverted cone formed by a surface with an 11 m radius at 10 m high and the landing point, when 4 cm between RF inputs is considered. The errors of the phase shifts used in the landing maneuver are less than ±3°, which translates into 1.7% losses over the detector theoretical range in the worst case. The circuit has a frequency bandwidth of 4.8 GHz to 5.6 GHz, considering a 3 dB variation in the input power when the AGC is limiting the output signal to 0 dBm at the circuit reference point of each branch. In addition, the evolution of phases in the landing maneuver is shown by means of a small simulation program in which the drone trajectory is inside and outside the tracking range of ±180°. Full article

This paper presents a complete workflow for the evaluation of GaN transistors in voltage source inverters. With the associated high switching speed of transistors based on GaN, it is important to consider some critical points in the design phase as well as in the measurement setup in order to be able to utilise and verify the advantages of GaN properly. For this reason, the presented circuit board’s design focuses on a minimised power loop inductance. Simulation models, an analytical approach and measurement results with the aim of determining this inductance are compared with each other. A good compliance results between the presented methods. Additionally, the description of a test bench is given, which enables the performance of the opposition method. This setup allows the measurement of the designed H-bridge’s arising losses and the GaN-transistor’s switching behaviour. In comparison to the conventional double pulse method, this approach enables results that are more accurate for determining losses. Full article

This paper presents an accurate analysis of the power losses of an interior permanent magnet synchronous motor fed by a cascaded H-bridge multilevel inverter. The main goal of this study is to investigate the impact of the cascaded h-bridge inverter, multicarrier PWM strategies, and inverter switching frequency on the synchronous motor power losses. With this aim in mind, a detailed frequency domain power analysis was carried out on motor power losses at different operating points in the frequency–torque plane. Motor power losses were further categorized into fundamental and harmonic power losses. This evaluation involved driving the power converter using six distinct multicarrier PWM strategies at four different switching frequencies. Additionally, a comparison was conducted with a conventional two-level PWM inverter to quantify the reduction in motor power losses. The experimental results show that the cascaded h-bridge inverter guarantees a notable increase in the motor efficiency, up to 7%, and losses in segregation at the fundamental frequency, if compared to the standard two-level PWM inverter, especially at low speed and with partial-load conditions. Such results mark out the cascaded H-bridge inverter as a valuable choice, also with regard to low-voltage drive applications. Full article

Monitoring the peak junction hotspot temperature in IGBT modules is critical for ensuring the reliability of high-power industrial multilevel inverters, particularly when operating under extreme thermal conditions, such as in traction applications. This study presents a comprehensive chip-level analytical loss and thermal model for estimation of the peak junction hotspot temperature in a three-level T-type neutral-point-clamped (TNPC) IGBT module. The developed model includes a detailed analytical assessment of conduction and switching losses, along with transient thermal network modeling, based on the actual electrical and thermal characteristics of the IGBT module. Additionally, a hybrid thermal–electrical stress experimental setup, designed to replicate real operating conditions, was implemented for a balanced three-phase inverter circuit utilizing a Semikron three-level IGBT module, with testing currents reaching 100 A and a critical case temperature of 125 °C. The analytically estimated module losses and peak junction hotspot temperatures were validated through direct experimental measurements. Furthermore, thermal simulations were conducted with Semikron’s SemiSel benchmark tool to cross-validate the accuracy of the thermo-electrical model. The outcomes show a relative estimation error of less than 1% when compared to experimental data and approximately 1.15% for the analytical model. These findings confirm the model’s accuracy and enhance the reliability evaluation of TNPC-IGBT modules in extreme thermal environments. Full article

Micro gas turbines serve small-scale generation where swift response and low emissions are highly valued, and they are commonly fuelled by natural gas. True to their ‘micro’ designation, their size is indeed compact; however, a noteworthy portion of the enclosure is devoted to power electronics components. This article considers whether these components can be made even smaller by substituting their conventional silicon switches with switches fashioned from silicon carbide. The wider bandgap of silicon carbide permits stronger electric fields and reliable operation at higher temperatures, which together promise lower switching losses, less heat, and simpler cooling arrangements. This study rests on a simple volumetric model. Two data sets feed the model. First come the manufacturer specifications for a pair of converter modules (one silicon, the other silicon carbide) with identical operation ratings. Second are the operating data and dimensions of a commercial 100 kW micro gas turbine. The model splits the converter into two parts: the semiconductor package and its cooling hardware. It then applies scaling factors that capture the higher density of silicon carbide and its lower switching losses. Lower switching losses reduce generated heat, so heatsinks, fans, or coolant channels can be slimmer. Together these effects shrink the cooling section and, therefore, the entire converter. The findings show that a micro gas turbine inverter built with silicon carbide occupies about one fifth less space and delivers more than a quarter higher power density than its silicon counterpart. Full article

This research presents a method for improving the regenerative efficiency of interior permanent magnet synchronous motors (IPMSMs) used in traction applications such as electric vehicles. In conventional powertrain control, the maximum torque per ampere (MTPA) strategy is commonly applied in the constant-torque region. However, this approach does not account for the combined losses of both the motor and inverter. In this study, overall system efficiency is investigated, and an improved current combination is proposed to minimize total losses. The single switching method is employed in the inverter due to its simplicity and its ability to reduce inverter losses. Simulations incorporating both motor and inverter losses were performed for two driving conditions around the MTPA current point. The results show that the optimal current combination slightly deviates from the MTPA point and leads to a slight improvement in efficiency. Experimental results under the two steady-state driving torque and angular velocity conditions confirm that the optimized current combination enhances system efficiency. Furthermore, simulations based on the Urban Dynamometer Driving Schedule predict an increase in recovered energy of approximately 1%. The proposed control strategy is simple, easy to implement, and enables the powertrain to operate with highly efficient current references. Full article

The increasing integration of renewable energy, electric vehicles, and industrial applications demands efficient power converter control strategies that reduce switching losses while maintaining high waveform quality. This paper presents a Finite-Control-Set Model Predictive Control (FCS-MPC) strategy for three-phase, two-level voltage source inverters (VSIs), incorporating a secondary objective for switching frequency minimization. Unlike conventional MPC approaches, the proposed method optimally balances control performance and efficiency trade-offs by adjusting the weighting factor (${\lambda }_{min}$). Real-time implementation using the OPAL-RT platform validates the effectiveness of the approach under both linear and non-linear load conditions. Results demonstrate a significant reduction in switching losses, accompanied by improved waveform tracking; however, trade-offs in distortion are observed under non-linear load scenarios. These findings provide insights into the practical implementation of real-time predictive control strategies for high-performance power converters. Full article

Dual Maximum Power Point Tracking (MPPT) inverters are essential in residential and small commercial solar power systems, optimizing power extraction from two independent solar panel arrays to enhance efficiency and energy harvesting. On the other hand, the Three-Level T-Type Voltage Source Inverter (3L T-Type VSI) is known for its reduced switching losses, improved harmonic distortion, and reduced part count in comparison to other three-level topologies. In this paper, a novel architecture is proposed to integrate the dual MPPT structure directly to each DC-side split capacitor of the 3L T-Type VSI, taking advantage of the intrinsic characteristics of the inverter’s topology. Further performance enhancement is achieved by integrating a classical MPPT strategy to the control framework to make it feasible for a real-case grid integration. The combination of these methods ensures faster and stable tracking under dynamic irradiance conditions. Considering that strategies dedicated to balancing the DC-link capacitor’s voltage slightly affect the AC-side current waveform, an enhanced sliding mode control (SMC) strategy tailored for dual MPPT and 3L T-Type VSI is deployed, combining the simplicity of conventional PI controllers used in the independent MPPT-based DC-DC converters with the superior robustness and dynamic performance of SMC. Real-time results obtained using the OPAL-RT Hardware-in-the-Loop platform validated the performance of the proposed control strategy under realistic test scenarios. The current THD was maintained below 4.8% even under highly distorted grid conditions, and the controller achieved a steady state within approximately 15 ms following perturbations in the DC-link voltage, sudden irradiance variations, and voltage sags and swells. Additionally, the power factor remained unitary, enhancing power transfer from the renewable source to the grid. The proposed system was able to achieve efficient power extraction while maintaining high power quality (PQ) standards for the output, positioning it as a practical and flexible solution for advanced solar PV systems. Full article

This paper introduces a non-isolated ultra-high voltage gain topology using the combination of the coupled-inductor-based inverting buck-boost converter (IBB) and voltage multiplier (VM) structure. In the proposed converter, an ultra-high step-up voltage gain can be achieved with a small duty cycle thanks to a coupled inductor and VMs. The voltage stress and the losses of the switches in the proposed converter are even less than other conventional topologies. Unlike other coupled-inductor topologies, a large voltage spike caused by the leakage inductance of the coupled inductor is smoothed by the capacitor in the voltage multiplier. In addition, zero-voltage switching (ZVS) turn-on for the switches and zero-current switching (ZCS) turn-off for the diodes can be achieved with the energy stored in the leakage inductance. A 360 W (40 V/380 V) prototype converter is implemented to prove the advantages of the proposed converter, with a maximum efficiency of 98.4%. Full article

Traditional multilevel inverter topologies, such FC, NPC, and CHB, have a few significant disadvantages. They need a great number of parts, which raises the complexity, expense, and switching losses. Furthermore, their intricate control schemes make voltage balancing and synchronization challenging. Lastly, under some circumstances, they experience severe harmonic distortion, necessitating the inclusion of expensive filters to enhance signal quality. This paper proposes a novel multilevel converter topology that uses the phase-disposition PWM (PD-PWM) technique to control a 19-level output. This new configuration maintains performance comparable to the CHB-MLI reference while using fewer switches, simplifying control, and reducing costs. Our approach is based on extensive simulations conducted in the MATLAB Simulink environment, with results compared to the CHB-MLI. A low-pass filter is added to improve the output voltage quality, reducing the THD% to 1.33%. This strategy offers several advantages, including simpler control, lower costs, increased reliability, and higher-quality output. The system was replicated using MATLAB Simulink and validated through hardware-in-the-loop (HIL) testing. The HIL method ensures real-world testing without causing damage to the hardware. The integrated system includes sensors and necessary hardware for a comprehensive energy management solution. Full article

Full waveform inversion (FWI) is an established precise velocity estimation tool for seismic exploration. Machine learning-based FWI could plausibly circumvent the long-standing cycle-skipping problem of traditional model-driven methods. The physics-guided self-supervised FWI is appealing in that it avoids having to make tedious efforts in terms of label generation for supervised methods. One way is to employ an inversion network to convert the seismic shot gathers into a velocity model. The objective function is to minimize the difference between the recorded seismic data and the synthetic data by solving the wave equation using the inverted velocity model. To further improve the efficiency, we propose a two-stage training strategy for the self-supervised learning FWI. The first stage is to pretrain the inversion network using a simultaneous source for a large-scale velocity model with high efficiency. The second stage is switched to modeling the separate shot gathers for an accurate measurement of the seismic data to invert the velocity model details. The inversion network is a partial convolution attention modified UNet (PCAMUNet), which combines local feature extraction with global information integration to achieve high-resolution velocity model estimation from seismic shot gathers. The time-domain 2D acoustic wave equation serves as the physical constraint in this self-supervised framework. Different loss functions are used for the two stages, that is, the waveform loss with time weighting for the first stage (simultaneous source) and the hybrid waveform with time weighting and logarithmic envelope loss for the second stage (separate source). Comparative experiments demonstrate that the proposed approach improves both inversion accuracy and efficiency on the Marmousi2 model, Overthrust model, and BP model tests. Moreover, the method exhibits excellent noise resistance and stability when low-frequency data component is missing. Full article

Electric propulsion ships have garnered significant attention for addressing the environmental impact associated with conventional shipping vessels. Their performance critically depends on the inverters that control propulsion motors. This study aims to enhance inverter control by addressing the limitations of conventional model predictive control (MPC), particularly its high current errors and total harmonic distortion (THD) owing to the limited switching frequency. Herein, a discontinuous MPC is proposed that is capable of reducing the switching losses by implementing discontinuous switching during high current periods. This approach employs zero-voltage vectors that are selected based on the polarity of the offset voltage to prevent unnecessary switching losses. Experimental results indicate that the proposed approach reduces the current error by up to 45%, THD by up to 30%, and switching losses by 15–25%. Therefore, this study demonstrates the potential of the proposed control strategy to improve the efficiency and reliability of electric propulsion systems, thereby contributing to the advancement of inverter control technology and development of eco-friendly shipping vessels. Full article

The Shunt Active Filter (SAF) is an effective solution for mitigating electrical perturbations in power networks. SAFs usually consist of a voltage source inverter (VSI) with lossy transistors and bulky inductors. In this context, this article proposes analytical models to evaluate the losses and efficiency of a SAF. The models include conduction and switching losses in the transistors and diodes and are valid for both IGBT and SiC MOSFET transistors. The methodology consists of analysing the current waveform to separate the portion flowing through the transistor or diode. IGBT and SiC MOSFET are compared in two cases: firstly, the classic SAF operation with harmonic and reactive power compensation and, secondly, in the case of power injection by a photovoltaic panel or batteries, in addition to the classic SAF operation. The results are validated with real manufacturer data. A step-by-step comparison shows a good accuracy of the model. Therefore, the developed methodology is useful for a SAF designer to select relevant components for the converter and to estimate the efficiency of the system accurately and quickly. Full article

In this study, we propose an active junction temperature control method specifically tailored for traction inverters based on active neutral point-clamped (ANPC) three-level topology. This approach not only enables real-time junction temperature equalization across switching devices, but also minimizes switching losses while preserving synchronous modulation. The methodology begins with a detailed formulation of the loss quantification model for ANPC inverters, establishing the relationship between predicted losses and switching vectors. Building on this foundation, we develop a loss equalization modulation control strategy featuring closed-loop loss control. The effectiveness and practicality of the proposed control method are rigorously validated using simulations and low-power experimental testing, demonstrating its potential to enhance both the reliability and efficiency of traction inverters. Full article

The early detection of faults in photovoltaic (PV) systems is crucial for ensuring efficiency, minimizing energy losses, and extending operational lifespan. This study evaluates and compares multiple machine-learning models for fault diagnosis in PV systems, analyzing their performance across different fault types and operational modes. A dataset comprising 2.2 million measurements from a laboratory-based PV model, covering seven fault categories—including inverter failures, partial shading, and sensor faults—is used for training and validation. Models are assessed under both Maximum Power Point Tracking (MPPT) and Limited Power Point Tracking (LPPT) conditions to determine their adaptability. The results indicate that the ensemble bagged tree classifier achieves the highest accuracy (92.2%) across all fault scenarios, while neural network-based models perform better under MPPT conditions. Additionally, the study highlights variations in model performance based on power mode, suggesting the potential for adaptive diagnostic approaches. The findings reinforce the feasibility of machine learning for predictive maintenance in PV systems, offering a cost-effective, sensor-free method for real-time fault detection. Future research should explore hybrid models that dynamically switch between classifiers based on system conditions, as well as validation using real-world PV installations. Full article