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Abstract A new adaptive‐linear‐neuron‐ (ADALINE‐) based dead‐time compensation method is presented for permanent magnet synchronous motor (PMSM) drives. It is proposed to suppress the sixth current harmonics adaptively in the synchronous reference frame due to dead‐time effects. In order to extract the sixth current harmonics, two ADALINE‐based extractors are used without taking into account the electrical lead angle. An improved ADALINE algorithm is used to calculate compensation voltages, taking into account the phase shift of impedance. The proposed method is capable of operating not only at low speed but also at medium and rated speeds in contrast to the traditional compensation method of ADALINE only at low speed. The new method is effective in steady, load dynamic and speed dynamic states with no needs for any extra hardware to detect phase current polarity. The effectiveness of the proposed compensation method is verified on a 780 W PMSM drive through experiments.

This paper proposes a method for compensation of dead-time effects for a fivephase inverter. In the proposed method an additional control subsystem was added to the field-oriented control (FOC) scheme in the coordinate system mapped to the third harmonic. The additional control loop operates in the fixed, orthogonal reference frame ( α - β coordinates) without the need for additional Park transformations. The purpose of this method is to minimize the dead-time effects by third harmonic injection in two modes of operation of the FOC control system: with sinusoidal supply and with trapezoidal supply. The effectiveness of the proposed control method was verified experimentally on a laboratory setup with a prototype five-phase interior permanent magnet synchronous machine (IPMSM). All experimental results were presented and discussed in the following paper.

The demeanour of many chemical and non-chemical processes resemble that of an integrating process. Developing a control plan for an integrating process is complicated, and the difficulty becomes even more when dead time is present. Internal Model Control (IMC) is enthralling in the creation of control strategies because it can derive the controller in the framework of a Proportional-Integral-Derivative controller (PID). It has been noted that when a filter is added to a controller, its performance improves, and various researchers have proposed PID with filter. The current work presents a comprehensive review of existing IMC-PID controllers for controlling integrating processes with dead time. The filter postulation in IMC is discussed, which is responsible for generating several forms of PID for the same process. Performance is measured using a variety of conventional performance indices. This article provides an overview of IMC filter topologies used in IMC-PID tuning for various integrating processes, including tuning relations and time delay approximations. The paper has also highlighted the guidelines for the selection of IMC filter and different structures of IMC filters from conventional to fractional order.

Although Gallium Nitride (GaN) Field Effect Transistor (FET) devices have found extensive application in DC-DC converters, their utilization in inverter motor drives remains an evolving area of study. In particular, the intricacies of reverse conduction operation during the dead time, specific to GaN FETs, require in-depth exploration for inverters supplying AC currents to electrical motors. Therefore, this paper undertakes an assessment of reverse conduction during the dead time intervals in low-voltage GaN FETs employed in motor drives applications. This analysis provides correlations between device technology attributes and the variations in AC phase current. To facilitate this investigation, a dedicated numerical tool is developed to evaluate the reverse conduction characteristics of GaN FET and associated power losses. Furthermore, this study includes a comparative analysis of the reverse conduction behavior of GaN FET devices with their low-voltage MOSFET counterparts, taking into account their differing static and dynamic characteristics. As a result, the main contribution of this work is to provide to the inverter designers a comprehensive understanding of dead-time effects in GaN-based inverters, along with guidance on selecting and optimizing dead time intervals within inverter legs for motor control applications employing the latest generation of GaN FET devices.

Although the dead-time optimization design of resonant converters has been widely researched, classical design methods focus more on achieving zero-voltage switching (ZVS) operation. The body diode loss is always ignored, which results in low-efficiency of the converter, especially, in energy router (ER). To deal with this problem, this paper proposes an adaptive deadtime modulation scheme for bidirectional LLC resonant converters in ER. First, the power loss of the MOSFET is analyzed based on the dead-time. Then, a novel dead-time optimization modulation principle is proposed. It can eliminate the body diode loss of MOSFET compared with existing literature. Based on the optimization modulation principle, this paper proposes an adaptive dead-time modulation scheme. To this end, the converter adopting the scheme no longer needs to calculate dead-time, which simplifies the parameter design process. Meanwhile, this scheme enables dead-time to dynamically change with working conditions according to the dead-time optimization modulation principle. With these effects, the ZVS operation is achieved, and the body diode loss of MOSFET is also eliminated. Furthermore, a digital implementation method is designed to make the proposed modulation scheme have fast-transient response. Finally, experimental results show that the proposed dead-time modulation scheme enables converters to achieve ZVS operation in all working conditions, and has higher efficiency than classical dead-time design methods.

Dead time is necessary for the coupled power switches to prevent shoot-through, especially in the modular multilevel converters (MMCs) with a large number of power switches. This paper proposes a dead-time effect suppression strategy for MMCs with nearest level modulation. The operational principles of MMCs are first analyzed. According to the operational features of MMCs, the method that removes a switching signal from the coupled switches and the reduced switching frequency voltage balancing algorithms (RSFVBAs) are mixed in the proposed method. In the intervals that are furthest away from the zero-crossing points (ZCP) of arm currents, the single switching signal method can completely eliminate the dead-time effect (DTE). Alternatively, the DTE is suppressed by the RSFVBA in intervals that are close to the ZCP. By the combination of the two methods, the dependence of the DTE suppression method on currents is reduced and the influences of ZCP are also released without degrading the normal operation performance of MMCs. Moreover, the output performance of MMCs is improved and the voltage stress on the arm inductor dramatically decreases. Finally, the validation of the method is verified by the simulation results with the professional tool Matlab/Simulink.

Abstract Dual active bridge (DAB) is an isolated DC‐DC converter gaining wider attention in power electronics applications. The high frequency (HF) transformer is an integral part of the DAB which is prone to saturation. Silicon carbide (SiC) based DAB are generally preferred for highly efficient power conversions, calling for an extremely low DC resistance of the transformer. This aggravates the DC bias issue significantly. The DC bias current generally flows due to the mismatch in static and transient switching of active devices, leading to eventual saturation of the transformer. This paper proposes an active method to precisely control the dead time of the devices (8–100 ns) without sacrificing the voltage utilization of the converter. This method does not require a sophisticated DC offset current measurement technique. The field programmable gate array (FPGA) based control platform on the gate driver side executes the proposed algorithm. The proposed control is experimentally verified in a 5 kW SiC based converter. The control implementation methodology is discussed with the support of necessary experimental results.

This paper proposes a new adaptive dead time compensation method for dual three-phase permanent magnet synchronous motors with two sets of three-phase windings spatially shifted by 30 electrical degrees. The stator resistance and leakage inductance are the only 5th and 7th harmonic impedances in the dual three-phase motor, which leads to a more pronounced current distortion due to dead time in the dual three-phase motor than in the three-phase motor. Therefore, dead-time compensation has significant implications for the application of dual three-phase motors. In this paper, the minimum value tracking algorithm is used to adjust the compensation voltage amplitude adaptively, and the compensation voltages are added to the output reference voltage in stationary frames. The proposed computation method has some significant advantages, such as simple implementation without additional hardware, easy mathematical computations, and no offline experimental measurements. Simulation results are provided to validate the performance of the proposed method.

Background The response of heart rate to changes in exercise intensity is comprised of several dynamic modes with differing magnitudes and temporal characteristics. Investigations of empirical identification of dynamic models of heart rate showed that second-order models gave substantially and significantly better model fidelity compared to the first order case. In the present work, we aimed to reanalyse data from previous studies to more closely consider the effect of including a zero and a pure delay in the model. Methods This is a retrospective analysis of 22 treadmill (TM) and 54 cycle ergometer (CE) data sets from a total of 38 healthy participants. A linear, time-invariant plant model structure with up to two poles, a zero and a dead time is considered. Empirical estimation of the free parameters was performed using least-squares optimisation. The primary outcome measure is model fit, which is a normalised root-mean-square model error. Results A model comprising parallel connection of two first-order transfer functions, one with a dead time and one without, was found to give the highest fit (56.7 % for TM, 54.3 % for CE), whereby the non-delayed component appeared to merely capture initial transients in the data and the part with dead time likely represented the true dynamic response of heart rate to the excitation. In comparison, a simple first-order model without dead time gave substantially lower fit than the parallel model (50.2 % for TM, 47.9 % for CE). Conclusions This preliminary analysis points to a linear first-order system with dead time as being an appropriate model for heart rate response to exercise using treadmill and cycle ergometer modalities. In order to avoid biased estimates, it is vitally important that, prior to parameter estimation and validation, careful attention is paid to data preprocessing in order to eliminate transients and trends.

This paper investigates the commutation transients of MOSFET and GaN FET devices in motor drive applications during hard-switching and soft-switching commutations at dead time operation. This study compares the switching behaviors of MOSFETs and GaN FETs, focusing on their performance during dead time in inverter legs for voltage source inverters. Experimental tests at various phase current levels reveal distinct switching characteristics and energy dissipation patterns. A validated simulation model estimates the experimental energy exchanged and dissipated during switching transients. The results demonstrate that GaN FETs exhibit lower overall losses at shorter dead times compared to MOSFETs, despite higher reverse conduction voltage drops. The study provides a quantitative framework for selecting optimal dead times to minimize energy losses, enhancing the efficiency of GaN FET-based inverters in low-voltage motor drive applications. Finally, a dead time optimization strategy is proposed and described.

A new adaptive‐linear‐neuron‐ (ADALINE‐) based dead‐time compensation method is presented for permanent magnet synchronous motor (PMSM) drives. It is proposed to suppress the sixth current harmonics adaptively in the synchronous reference frame due to dead‐time effects. In order to extract the sixth current harmonics, two ADALINE‐based extractors are used without taking into account the electrical lead angle. An improved ADALINE algorithm is used to calculate compensation voltages, taking into account the phase shift of impedance. The proposed method is capable of operating not only at low speed but also at medium and rated speeds in contrast to the traditional compensation method of ADALINE only at low speed. The new method is effective in steady, load dynamic and speed dynamic states with no needs for any extra hardware to detect phase current polarity. The effectiveness of the proposed compensation method is verified on a 780 W PMSM drive through experiments. [ABSTRACT FROM AUTHOR]

Background The response of heart rate to changes in exercise intensity is comprised of several dynamic modes with differing magnitudes and temporal characteristics. Investigations of empirical identification of dynamic models of heart rate showed that second-order models gave substantially and significantly better model fidelity compared to the first order case. In the present work, we aimed to reanalyse data from previous studies to more closely consider the effect of including a zero and a pure delay in the model. Methods This is a retrospective analysis of 22 treadmill (TM) and 54 cycle ergometer (CE) data sets from a total of 38 healthy participants. A linear, time-invariant plant model structure with up to two poles, a zero and a dead time is considered. Empirical estimation of the free parameters was performed using least-squares optimisation. The primary outcome measure is model fit, which is a normalised root-mean-square model error. Results A model comprising parallel connection of two first-order transfer functions, one with a dead time and one without, was found to give the highest fit (56.7 % for TM, 54.3 % for CE), whereby the non-delayed component appeared to merely capture initial transients in the data and the part with dead time likely represented the true dynamic response of heart rate to the excitation. In comparison, a simple first-order model without dead time gave substantially lower fit than the parallel model (50.2 % for TM, 47.9 % for CE). Conclusions This preliminary analysis points to a linear first-order system with dead time as being an appropriate model for heart rate response to exercise using treadmill and cycle ergometer modalities. In order to avoid biased estimates, it is vitally important that, prior to parameter estimation and validation, careful attention is paid to data preprocessing in order to eliminate transients and trends.

Abstract The number of neutrons emitted from a nuclear reaction plays a crucial role in various fields, including nuclear theory, nuclear nonproliferation, nuclear energy and nuclear criticality safety. Accurate determination of neutron multiplicities requires the application of several corrections, with dead-time correction and background subtraction being particularly significant. These corrections become more challenging for neutron detectors with time-dependent neutron capture. In this work, we perform a comprehensive study of three existing methods used for dead-time correction and background subtraction in neutron detectors with time-dependent neutron capture. The methods were tested for dead-times in the range from 0 to 1 μs using a Monte Carlo model simulating the dead-time and background effects in the standard neutron multiplicity probability distribution of $$^{252}$$ 252 Cf. The previous methods showed larger than desired uncertainty or systematic trade off. Those uncertainties prompted the development of a novel approach using neural networks trained with data from Monte Carlo simulations. The Neural Network method enabled the correction of neutron multiplicity probabilities more accurately than the other methods with fractional errors smaller than 3% for multiplicities around the peak of $$^{252}$$ 252 Cf. A similar approach using neural networks could be applied to problems where the system being studied can be accurately simulated without having an accurate analytical description available. The neural network method presented in this paper can be easily expanded if multiplicities greater than 10 are expected.

Background The response of heart rate to changes in exercise intensity is comprised of several dynamic modes with differing magnitudes and temporal characteristics. Investigations of empirical identification of dynamic models of heart rate showed that second-order models gave substantially and significantly better model fidelity compared to the first order case. In the present work, we aimed to reanalyse data from previous studies to more closely consider the effect of including a zero and a pure delay in the model. Methods This is a retrospective analysis of 22 treadmill (TM) and 54 cycle ergometer (CE) data sets from a total of 38 healthy participants. A linear, time-invariant plant model structure with up to two poles, a zero and a dead time is considered. Empirical estimation of the free parameters was performed using least-squares optimisation. The primary outcome measure is model fit, which is a normalised root-mean-square model error. Results A model comprising parallel connection of two first-order transfer functions, one with a dead time and one without, was found to give the highest fit (56.7 % for TM, 54.3 % for CE), whereby the non-delayed component appeared to merely capture initial transients in the data and the part with dead time likely represented the true dynamic response of heart rate to the excitation. In comparison, a simple first-order model without dead time gave substantially lower fit than the parallel model (50.2 % for TM, 47.9 % for CE). Conclusions This preliminary analysis points to a linear first-order system with dead time as being an appropriate model for heart rate response to exercise using treadmill and cycle ergometer modalities. In order to avoid biased estimates, it is vitally important that, prior to parameter estimation and validation, careful attention is paid to data preprocessing in order to eliminate transients and trends.

The inverter dead time effect is non-negligible for the control performance of sensorless synchronous reluctance motor (SynRM) drives at low speeds. In this paper, a reduced-order observer-based sensorless control method for SynRM drives combined with the adaptive linear neurons (ADALINE)-based dead-time compensation is proposed. The reduced-order observer-based sensorless control method is presented, for which is parameter tuning is easy. On this basis, the dead-time compensation strategy using ADALINE filters is proposed to reduce the voltage harmonics effect on the estimation performance of the reduced-order observer. With ADALINE filters, the sixth current harmonic can be successfully filtered out by compensating the voltage directly or fitting the current to compensate the voltage. In this way, the low-speed estimation performance of the reduced-order observer is improved. The effectiveness of the proposed method is verified on a 3 kW SynRM experimental platform.