Search Results (259)

Induction motors piloted by voltage source inverters constitute a major source of acoustic noise in industry. The discrete tonal bands generated by induction motor stator current spectra controlled by the fixed Pulse Width Modulation (PWM) technique have damaging effects on the electronic noise source. Nowadays, the investigation of new advanced control techniques for variable speed drives has developed a potential investigation field. Finite state model predictive control has recently become a very popular research focus for power electronic converter control. The flexibility of this control shows that the switching times are generated using all the information on the drive status. Predictive Torque Control (PTC), space vector PWM and random PWM are investigated in this paper in terms of acoustic noise emitted by an induction machine fed by a three-phase two-level inverter. A comparative study based on electrical and mechanical magnitudes, as well as harmonic analysis of the stator current, is presented and discussed. An experimental test bench is also developed to examine the effect of the proposed PTC and PWM techniques on the acoustic noise of an induction motor fed by a three-phase two-level voltage source converter. Full article

A three-phase inverter generates non-sinusoidal voltages, contains high order harmonics, and concentrates on switching frequency multiples. Supplying an induction machine (IM) with a voltage source inverter (VSI) increases the acoustic noise content which becomes unbearable, particularly for systems needing a moderate level of electric traction. The discrete tonal bands produced by the IM stator current spectrum controlled by the fixed pulse width modulation (PWM) technique have damaging effects on the electronic noise source. Moreover, it has been factually proven that the noise content is strongly associated with the harmonics of the source feeding electric machine. Thus, the harmonic content is influenced by the control strategy VSI to produce pulse width modulation (PWM). Currently, the investigation of new advanced control techniques for variable speed drives has developed into a potential investigation file. Two fundamental topologies for a three-phase inverter have been suggested in the literature, namely two- and three-level topologies. Therefore, this paper investigated the effect of variable and fixed PWM strategies, such as random PWM (RPWM) and space vector PWM (SVPWM), on the noise generated by an IM, powered with a two- or three-level inverter. Simulation results showed the validity and efficiency of the proposed variable RPWM strategy in reducing sideband harmonics for both the two and three levels at different switching frequencies and modulation indexes. The proposed PWM strategies were further evaluated by the results of equivalent experiments on an IM fed by a two-level VSI. The experimental measurements of harmonic current and noise spectra demonstrate that the acoustic noise is reduced and dispersed totally for the RPWM strategy. Full article

This paper presents an improved structure of an asymmetrical single-phase multilevel inverter topology with reduced device count. The proposed topology achieves 19 voltage levels at the output using only 12 power switches and 3 DC sources. The topology can be easily extended, resulting in a modular topology with more voltage levels at higher voltages. Moreover, the reliability analysis of the proposed converter results in a higher mean time to fault. The simulation is performed in MATLAB/Simulink, and a hardware prototype is developed to validate the circuit’s performance. A low-frequency Nearest Level Control PWM technique is implemented to generate switching signals and achieves 4.30% THD in output voltage. The PLECS software is used for power loss and efficiency analysis, resulting in a maximum efficiency of 99.08%. The proposed converter has been compared with other MLI topologies to demonstrate its superiority. The results indicate that the proposed topology has proven superior and outperformed other topologies in various parameters, making it suitable for renewable energy applications. Full article

Background/Objectives: The ability to drive is closely linked to participation in daily activities and quality of life in people living with neurological disorders. Cognitive deficits in people with multiple sclerosis (pwMS) are known to hinder this ability, yet concrete fitness-to-drive criteria remain elusive and assessment guidelines lack uniformity. A plethora of cognitive tests have provided associations with various aspects of driving performance and on-road behavior; however, several studies reveal limitations and inconsistencies in most tests’ sensitivity and predictive effect. Novel and resurfaced modalities for cognitive assessment, in the form of advanced imaging techniques and electrophysiological studies, may offer improved sensitivity in driving-related abilities in earlier and milder stages. Their application in addition to evaluations in driving simulators may aid future research and enhance the quality of evidence to inform decision-making. Methods: We searched for the relevant literature in the PubMed database and synthesized the available findings for the applications of currently clinically used cognitive tests, markers derived from functional magnetic resonance imaging (fMRI) and diffuse tensor imaging (DTI), as well as event-related potentials (ERP). Results: Advanced imaging modalities and ERP studies may better capture neurobiological changes that lead to driving impairment in pwMS, and they may also be applied to detect cognitive alterations earlier and with greater precision, helping to predict driving difficulties in this population. Conclusions: Novel tools and driving simulator settings could improve our understanding of the relation between cognition and driving in pwMS, enhance protocol homogeneity in driving studies, and aid in the formation of guidelines. The evidence in this review supports an increase in their application in future studies. Full article

The rapid evolution of modern power systems, driven by the large-scale integration of renewable energy sources and the emergence of smart grids, presents new challenges in maintaining grid stability, power quality, and control reliability. As critical interfacing elements, three-phase pulse width modulation (PWM) converters must now ensure resilient and efficient operation under increasingly adverse and dynamic grid conditions. This paper proposes an adaptive neural network-based virtual flux (VF) estimator for sensorless predictive direct power control (PDPC) of PWM converters under nonideal grid voltage conditions. The proposed estimator is realized using an adaptive linear neuron (ADALINE) configured as a quadrature signal generator, offering robustness against grid voltage disturbances such as voltage unbalance, DC offset and harmonic distortion. In parallel, a PDPC scheme based on the extended pq theory is developed to reject active-power oscillations and to maintain near-sinusoidal grid currents under unbalanced conditions. The resulting VF-based PDPC (VF-PDPC) strategy is validated via real-time simulations on the OPAL-RT platform. Comparative analysis confirms that the ADALINE-based estimator surpasses conventional VF estimation techniques. Moreover, the VF-PDPC achieves superior performance over conventional PDPC and extended pq theory-based PDPC strategies, both of which rely on physical voltage sensors, confirming its robustness and effectiveness under non-ideal grid conditions. Full article

As robotic systems advance in autonomy and sophistication while being used in uncertain environments, the challenge of building reliable and robust electric motors that are embedded into robotic systems has never been a more important engineering problem. Thermal distress caused by extended operation or excessive loading can negatively affect a motor’s performance and efficiency and lead to catastrophic hardware failure. This paper proposes a novel intelligent control framework that includes real-time thermal feedback for hybrid electric motors that are embedded into robotic systems. The framework relies on adaptive control techniques and lightweight machine learning techniques to estimate internal motor temperatures and dynamically change operational parameters. Unlike traditional reactive methods, this framework provides a spacious active/predictive method of heat management, while preserving efficiency and allowing for responsive control. Simulations, experimental validations, and preliminary trials that deployed real robotic systems demonstrated that our framework allows for reductions in peak temperatures by up to 18% and extends motor lifetime by 22%, while retaining control stability and a range of variations in PWM adjustments of ±12% across disparate workloads. These results demonstrate the efficacy of intelligent and thermally aware motor control architectures and processes to improve the reliability of autonomous robotic systems and open the door for next-generation embedded controllers that will allow robotic platforms to self-manage thermal effects in resilient, adaptable robots. Full article

This paper proposes a design and control methodology for a Quasi-Y-Source impedance source inverter (QS-YSI) as a power electronics interface for Vehicle-to-Grid (V2G) and Grid-to-Vehicle (G2V) applications in the context of virtual power plants (VPPs). The work presents an analysis of bidirectional power transfer using Electric Vehicles (EVs) to supply power to the utility grid, businesses, and homes, thereby acting as distributed energy resources. The proposed QS-YSI topology supports both V2G and G2V operation while providing reactive power compensation and enabling the decoupled tracking of active power (P) and reactive power (Q), demonstrating the capability of EVs to return energy to the grid and to provide ancillary services such as power factor correction. The key contributions are a detailed control design methodology that includes pulsating DC-link voltage regulation, inverter output current reference tracking in the synchronous $dq$ reference frame considering DC-link voltage dynamics, and a modified Pulse Width Modulation (PWM) technique for effective decoupling of DC link and inverter output current control. Finally, the feasibility and validity of the proposed approach are demonstrated through simulations of the complete system under nominal conditions and experiments conducted considering a small-scale prototype. Full article

The following article aims to implement a hybrid modulation methodology based on the Selective Harmonic Elimination Pulse Width Modulation (SHE-PWM) technique to work with the fundamental frequency of the system and find the optimal firing angles using the PSO optimization algorithm, capable of reducing the voltage THDv present in the output signals of three-phase multilevel inverters. To develop this approach, three case studies are proposed, developed in MATLAB/Simulink software, which feature three-phase inverters with five, seven, and nine levels, respectively, of the CHB topology. The impact of adequate modulation is assessed, resulting in a voltage output signal with reduced distortion. The national regulation ARCERNNR 002/20 will be used as a reference point to evaluate the results before and after implementing the methodology. It was verified that the developed methodology can effectively eliminate the selected harmonics, especially those of lower order (3rd, 5th, 7th, 9th, 11th, 13th, and 15th), achieving an improvement of up to 17.93% in the voltage THDv concerning the standard S-PWM modulation present in the CHB-MLI. Full article

This study investigates the thermal performance of induction motors powered by multilevel H-bridge inverters using a novel pulse-width phase shift triangle modulation (PSTM-PWM) technique. Conventional PWM methods introduce significant harmonic distortion, increasing copper and iron losses and causing overheating and reduced motor lifespan. Through experimental testing and comparison with standard PWM techniques (LS-PWM and PS-PWM), the proposed PSTM-PWM reduces harmonic distortion by up to 64% compared to the worst one and internal motor losses by up to 5.5%. A first-order thermal model is used to predict motor temperature, validated with direct thermocouple measurements and infrared thermography. The results also indicate that the PSTM-PWM technique improves thermal performance, particularly at a triangular waveform peak value of 3.5 V, reducing temperature by around 6% and offering a practical and simple solution for industrial motor drive applications. The modulation order was set to M = 7 to reduce both the losses in the power inverter and to prevent the generation of very high voltage pulses (high dV/dt), which can deteriorate the insulation of the induction motor windings over time. Full article

This paper presents a microcontroller-based technique for accurately measuring resistive sensors over a wide dynamic range using an adaptive constant current source. Unlike conventional voltage dividers or fixed-current methods—often limited by reduced resolution and saturation when sensor resistance varies across several decades—the proposed system dynamically adjusts the excitation current to maintain optimal Analog-to-Digital Converter (ADC) input conditions. The measurement circuit employs a fixed reference resistor and an inverting amplifier configuration, where the excitation current is generated by one or more pulse-width modulated (PWM) signals filtered through low-pass RC networks. A microcontroller selects the appropriate PWM channel to ensure that the output voltage remains within the ADC’s linear range. To support multiple sensors, an analog switch enables sequential measurements using the same dual-PWM current source. The full experimental implementation uses four op-amps to support modularity, buffering, and dual-range operation. Experimental results show accurate measurement of resistances from 1 kΩ to 100 kΩ, with maximum relative errors of 0.15% in the 1–10 kΩ range and 0.33% in the 10–100 kΩ range. The method provides a low-cost, scalable, and digitally controlled solution suitable for embedded resistive sensing applications without the need for high-resolution ADCs or programmable gain amplifiers. Full article

The stable operation of micromachine systems relies on reliable power management, where DC-DC converters provide energy with high efficiency to extend operational endurance. However, these converters also constitute significant electromagnetic interference (EMI) sources that may interfere with the normal functioning of micro-electromechanical systems. This paper proposes a boost converter utilizing Pulse Width Modulation (PWM) with peak current mode control to address the EMI issues inherent in the switching operation of DC-DC converters. The converter incorporates a Hybrid Spread Spectrum (HSS) technique to effectively mitigate EMI noise. The HSS combines a 1.2 MHz pseudo-random spread spectrum with a 9.4 kHz triangular periodic spread spectrum. At a standard switching frequency of 2 MHz, the spread spectrum range is set to ±7.8%. Simulations conducted using a 0.5 μm Bipolar Complementary Metal-Oxide-Semiconductor Double-diffused Metal-Oxide-Semiconductor (BCD) process demonstrate that the HSS technique reduces EMI around the switching frequency by 12.29 dBμV, while the converter’s efficiency decreases by less than 1%. Full article

Coronary artery disease (CAD) is the third leading cause of disability and death globally. Intravascular ultrasound (IVUS) is the most commonly used imaging modality for the characterization of vulnerable plaques. The development of novel intravascular imaging and therapy devices requires dedicated open systems (e.g., for pulse sequences for imaging or thrombolysis), which are not currently available. This paper presents the development of a novel multifunctional FPGA-based pulser/receiver system for intravascular ultrasound imaging and therapy research. The open platform consists of a host PC with a Matlab-based software interface, an FPGA board, and a proprietary analog front-end board with state-of-the-art electronics for highly flexible transmission and reception schemes. The main features of the system include the capability to convert arbitrary waveforms into tristate bipolar pulses by using the PWM technique and by the direct acquisition of raw radiofrequency (RF) echo data. The results of a multicycle excitation pulse applied to a custom 550 kHz therapy transducer for acoustic characterization and a pulse-echo experiment conducted with a high-voltage, short-pulse excitation for a 19.48 MHz transducer are reported. Testing results show that the proposed system can be easily controlled to match the frequency and bandwidth required for different IVUS transducers across a broad class of applications. Full article

The failure of power semiconductors due to variations in junction temperature represents an important factor in determining the reliability of a power converter. This work presents a comparative assessment of the thermal performance of IGBT power semiconductors within a two-level voltage source converter, specifically the average junction temperature and the variation of this value over a given period. The evaluation was carried out using different continuous and discontinuous carrier-based pulse width modulation (CB-PWM) techniques. The use of discontinuous PWM allows for a decrease in switching losses and therefore in average junction temperatures, but the variation in junction temperature is largely and non-linearly dependent on several factors, including the power factor of the three-phase load. Among the discontinuous PWM techniques, this analysis focuses on those that allow for a symmetric thermal load. The aforementioned comparisons have been tested in a laboratory setup, whee we directly measured the junction temperature through a high-end infrared thermal camera. Full article

This manuscript investigates the applicability and behavior of the Generalized Extreme Value (GEV) distribution in flood frequency analysis, comparing it with the Pearson III and Wakeby distributions. Traditional approaches often rely on a limited set of statistical distributions and estimation techniques, which may not adequately capture the behavior of extreme events. The study focuses on four hydrometric stations in Romania, analyzing maximum discharges associated with rare and very rare events. The research employs seven parameter estimation methods: the method of ordinary moments (MOM), the maximum likelihood estimation (MLE), the L-moments, the LH-moments, the probability-weighted moments (PWMs), the least squares method (LSM), and the weighted least squares method (WLSM). Results indicate that the GEV distribution, particularly when using L-moments, consistently provides more reliable predictions for extreme events, reducing biases compared to MOM. Compared to the Wakeby distribution for an extreme event (T = 10,000 years), the GEV distribution produced smaller deviations than the Pearson III distribution, namely +7.7% (for the Danube River, Giurgiu station), +4.9% (for the Danube River, Drobeta station), and +35.3% (for the Ialomita River). In the case of the Siret River, the Pearson III distribution generated values closer to those obtained by the Wakeby distribution, being 36.7% lower than those produced by the GEV distribution. These results support the use of L-moments in national hydrological guidelines for critical infrastructure design and highlight the need for further investigation into non-stationary models and regionalization techniques. Full article

This study evaluates six parameter estimation methods for the generalized extreme value (GEV) distribution: maximum likelihood estimation (MLE), two probability-weighted moments (PWM-UE and PWM-PP), and three robust two-stage order statistics estimators (TSOS-ME, TSOS-LMS, and TSOS-LTS). Their performance was assessed using simulation experiments under varying tail behaviors, represented by three types of GEV distributions: Weibull (short-tailed), Gumbel (light-tailed), and Fréchet (heavy-tailed) distributions, based on the mean squared error (MSE) and mean absolute percentage error (MAPE). The results showed that TSOS-LTS consistently achieved the lowest MSE and MAPE, indicating high robustness and forecasting accuracy, particularly for short-tailed distributions. Notably, PWM-PP performed well for the light-tailed distribution, providing accurate and efficient estimates in this specific setting. For heavy-tailed distributions, TSOS-LTS exhibited superior estimation accuracy, while PWM-PP showed a better predictive performance in terms of MAPE. The methods were further applied to real-world monthly maximum PM2.5 data from three air quality stations in Bangkok. TSOS-LTS again demonstrated superior performance, especially at Thon Buri station. This research highlights the importance of tailoring estimation techniques to the distribution’s tail behavior and supports the use of robust approaches for modeling environmental extremes. Full article