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Cycle time, which is of order of ten weeks for most products in semiconductor wafer fabrication facilities (wafer fabs), must be explicitly considered in production planning models. Cycle times depend nonlinearly on the resource workload in a wafer fab. Different data-driven (DD) production planning formulations are studied in this paper. Such formulations are based on a set of system states representing the congestion behavior of a wafer fab with work in process (WIP) and resulting output levels. Different WIP-output relations in the DD formulations are investigated. In addition, different methods are proposed to gather representative sets of system states. The DD formulations are compared with the Allocated Clearing Function (ACF) formulation with respect to profit and cost values using simulation models of a scaled-down and a large-sized multi-product wafer fab, respectively. The simulation results show that some DD variants are able to outperform the ACF formulation under several experimental conditions. [ABSTRACT FROM AUTHOR]

This paper discusses the back-flashover (BFO) phenomena in a high-voltage (HV) vertical double-circuit transmission line by means of numerical simulations. The single- and multiphase BFOs are analyzed considering 24 cases of AC-voltage angles and nonlinear characteristic of flashovers, taking advantage of the circuit analysis method in time domain. The models used in circuit analysis are the TEM-delay model, which can take into account the non-TEM characteristics of tower and line, and the conventional models. Prior to the BFO analysis, the characteristics of circuit models are compared and discussed with the numerical electromagnetic analysis results. In BFO analysis, it is clarified that the occurrence probability of the multiphase BFO is heavily depending on the bias AC-voltages. The relation of measured BFO phases and AC-voltages are well explained by the TEM-delay model with the valid lightning current magnitude. The conventional circuit models could have underestimated the occurrence of BFOs in HV transmission lines. The analysis and discussions shown in this paper can be utilized for advanced evaluation of lightning performance of transmission lines that considers the seriousness of lightning accidents. [ABSTRACT FROM AUTHOR]

This paper presents a passive lumped model for DC cables and overhead lines, taking into account the frequency dependency of the per-unit-length parameters due to the skin and proximity effects. In comparison to distributed parameter line models, such as the Frequency-Dependent Phase model of PSCAD, the proposed model does not require line propagation delay extraction and does not impose any restrictions on the simulation timestep. As a result, for electrically short lines, the introduced model is more computationally efficient than distributed parameter models as it enables simulation using larger timesteps. The performance of the proposed model is evaluated in comparison with the PI model and the Frequency-Dependent Phase model through time-domain simulations of a DC microgrid and a radial DC distribution feeder. The studies performed in PSCAD focus on fault-induced transients. The results indicate that for electrically short lines the developed model is significantly more accurate compared to the PI model and provides similar accuracy with more computational efficiency compared to the Frequency-Dependent Phase model. [ABSTRACT FROM AUTHOR]

With the widespread application of lithium-ion battery packs, it calls for efficient balancing methods to improve the performance of these battery systems. The relevant research has focused on the design of equalization circuits and control strategies while neglecting quantitative analysis and comparison of battery active equalization structures from the systematic level. In this paper, we propose an improved system-theoretic modeling approach for active equalization structures that takes into account the battery's constraints, including equalization current rate and SOC operation range. Accordingly, the mathematical models of various active equalization structures are derived that can describe their equalization dynamic behavior. Then, the analytical algorithms are developed to estimate the balancing time of active equalization structures online. Finally, extensive numerical simulations are conducted to evaluate and compare the average performance of these equalization systems in term of equalization time. It then comes up with a comprehensive comparison among them. Consequently, the Multicell-to-Multicell (MC2MC) balancing structure benefits the fast balancing speed and the lowest sensitive to initial batteries’ SOCs. The global structure has the lowest implementation cost and the series structure benefits the simplest control. Moreover, the module-based structures have faster balancing speed when each module contains about 4–6 batteries. [ABSTRACT FROM AUTHOR]

Electromagnetic Transient (EMT) simulation tools are typically developed using conventional procedural programming languages. On the other hand, modern high-level and equation-based programming languages, such as Modelica, are currently available. Modelica allows formulating models that are easy to develop, maintain and understand by expressing what needs to be computed without stating how it should be computed. This paper presents a Modelica-based simulator for electromagnetic transients. It is demonstrated that this approach offers significant advantages for developing sophisticated models. Computational performance and accuracy are compared to a conventional EMT-type simulation tool. [ABSTRACT FROM AUTHOR]

The optimization of the energy management of modern hybrid-electric or fully electric race cars for minimum lap time requires a description of the vehicle dynamics performance envelope, that is, of the tires’ grip limit in corners, braking zones and during acceleration. In this paper, we present a computationally efficient performance envelope model in the form of convex constraints on the achievable longitudinal and lateral acceleration, on the assumption that the path on the track is given. The proposed acceleration limits are modeled velocity-dependent to take into account the effect of aerodynamic downforce present in many circuit race cars. The formulation as linear equality, inequality and second-order cone constraints allows to embed the model in a convex energy management optimization framework. To showcase the approach, we identify the model with data obtained from a state-of-the-art hybrid-electric Formula 1 car and present results for the Silverstone and Spa-Francorchamps circuits. The optimal energy management strategies can be evaluated with a computational time of less than 1 s. The optimal velocity profile subject to the performance envelope constraints is close to the measured one. The good agreement between the optimal solution and the measurement data shows that the proposed model captures the vehicle dynamics accurately enough for the purposes of energy management optimization. [ABSTRACT FROM AUTHOR]

The aim of the paper is to define a limit performance of highly efficient battery electric quadricycles for urban mobility. The vehicle is employed for an energy efficiency competition in which urban concepts compete. A multi-physics (thermo-electro-mechanical) Tank To Wheels (TTW) model has been developed and validated. Given the information on the track route (track map and elevation) and on the throttle input command, the model computes the vehicle power demand and cruising speed. The model is validated by means of both indoor and outdoor experimental tests. The validated model is employed for the optimization of the transmission gear ratio and of the driving strategy to minimize the overall energy consumption on a given track. Design variables are related to the transmission gear ratio and to the throttle command profile. The algorithm aims to minimize the energy consumption, including constraints on the maximum current provided by the battery and on the maximum time available to complete the lap. Comparison with some common driving strategies confirmed the effectiveness of the proposed solution, with a foreseen 9% reduction of the vehicle overall energy demand. The single seater ultra-efficient electric vehicle, compared to other urban quadricycles, has a battery capacity ten times lower and a 50% longer driving range. [ABSTRACT FROM AUTHOR]

This paper proposes an adaptive model of modular multilevel converter (MMC) for electromagnetic transient (EMT) simulations. The model is applicable to MMCs with arbitrary numbers of half-bridge and full-bridge submodules. The proposed design includes average value model, arm equivalent model, and detailed equivalent model. It allows smoothly transitioning from one model to another during time-domain simulations depending on the desired accuracy and execution time constraints. Modifications required in conventional MMC models to achieve smooth transitions are presented in the paper. Time-domain initialization methods are developed for each constituting model, including initialization of the appropriate control system blocks. Validity and effectiveness of the proposed adaptive model is demonstrated using EMT simulations of 401-level MMC-HVDC system. [ABSTRACT FROM AUTHOR]

An important cue for multi-pedestrian tracking in video is the consistent appearance of an individual for quite a while. In this paper, we address multi-pedestrian tracking by learning a robust appearance model from the paradigm of tracking by detection. To separate detections of different pedestrians while assembling detections of the same pedestrian, we take advantage of the cue of consistent appearance and exploit three types of evidence from the recent, past and near-future. Existing online approaches only exploit the detection-to-detection and sequence-to-detection metrics, which focus on the recent and past appearance patterns respectively, while the future pedestrian appearance is simply ignored. This drawback is remedied in this paper by further considering the sequence-to-sequence metric, which resorts to near-future appearance presentation. Adaptive combination weights are learned to fuse these three different metrics. Moreover, we propose a novel Focal Triplet Loss to make the model focus more on hard examples than the easy ones. We demonstrate that this can significantly enhance the discriminating power of the model compared with treating every sample equally. Effectiveness and efficiency of the proposed method is verified by conducting comprehensive ablation studies and comparing with many competitive (offline/online/near-online) counterparts on the MOT16 and MOT17 Challenges. [ABSTRACT FROM AUTHOR]

In this paper, we propose a circuit yield prediction method to improve the efficiency of circuit yield prediction. Both traditional Monte Carlo simulation and the current popular machine learning for yield prediction require a large number of circuit simulation results, which increases production costs. This method finds the data boundary points through high-dimensional kernel density estimation, and performs simulation calculations on these boundary values instead of the overall simulation. Experiments show that, compared with machine learning and Monte Carlo methods, the proposed algorithm can efficiently predict the yield of circuits. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surface (IRS) has been regarded as a promising and revolutionary technology for future wireless communication systems owing to its capability of tailoring signal propagation environment in an energy/spectrum/ hardware-efficient manner. However, most existing studies on IRS optimizations are based on a simple and ideal reflection model that is impractical in hardware implementation, which thus leads to severe performance loss in realistic wideband/multi-band systems. To deal with this problem, in this paper we first propose a more practical and more tractable IRS reflection model that describes the difference of reflection responses for signals at different frequencies. Then, we investigate the joint transmit beamforming and IRS reflection beamforming design for an IRS-assisted multi-cell multi-band system. Both power minimization and sum-rate maximization problems are solved by exploiting popular second-order cone programming (SOCP), Riemannian manifold, minimization-majorization (MM), weighted minimum mean square error (WMMSE), and block coordinate descent (BCD) methods. Simulation results illustrate the significant performance improvement of our proposed joint transmit beamforming and reflection design algorithms based on the practical reflection model in terms of power saving and rate enhancement. [ABSTRACT FROM AUTHOR]

Modular multilevel converters have become the technology of choice in high voltage direct current systems. They are composed of a large number of submodules, which poses significant computational challenges to electromagnetic transient simulations. To address this issue, scholars proposed several approaches that are a trade-off between simulation accuracy and computational burden, which mainly achieve numerical efficiency by adopting reduced and simplified models of the converter arm submodules. This paper proposes a different simulation paradigm based on sub-circuit isomorphism. It is suited for the analysis of intrinsically modular electronic circuits, as it exploits the common behavior of structurally identical submodules by clustering them together. This method does not require any simplification of the submodule electrical model and minimizes the number of equations to be solved at each time step of the time domain analysis, thereby significantly reducing the computational effort. Thus, this method is suitable for thorough simulations of ac/dc networks, which may require the implementation of detailed transistor-level representations of the converter submodules. [ABSTRACT FROM AUTHOR]

The Hidden Weighted Bit function plays an important role in the study of classical models of computation. A common belief is that this function is exponentially hard to implement using reversible ancilla-free circuits, even though introducing a small number of ancillae allows a very efficient implementation. In this paper, we refute the exponential hardness conjecture by developing a polynomial-size reversible ancilla-free circuit computing the Hidden Weighted Bit function. Our circuit has size $O(n^{6.42})$ O (n 6. 42) , where $n$ n is the number of input bits. We also show that the Hidden Weighted Bit function can be computed by a quantum ancilla-free circuit of size $O(n^2)$ O (n 2) . The technical tools employed come from a combination of Theoretical Computer Science (Barrington's theorem) and Physics (simulation of fermionic Hamiltonians) techniques. [ABSTRACT FROM AUTHOR]

A logic diagnosis procedure provides information about the defects that are present in a faulty unit as a set of candidate faults. To obtain smaller, and more accurate, sets of candidate faults, a diagnostic test generation procedure produces a test set that distinguishes fault pairs. This paper observes that large sets of candidate faults are obtained when multiple defects are present in a faulty unit, even if a diagnostic test set is used for logic diagnosis. This points to the possibility that fault pairs do not provide a complete set of targets for diagnostic test generation. This paper analyzes the conditions that cause a large set of candidate faults to be formed under a particular logic diagnosis procedure and suggests new targets for diagnostic test generation. The experimental results for benchmark circuits demonstrate that a diagnostic test set can be improved by adding diagnostic tests for the new targets. [ABSTRACT FROM AUTHOR]

This paper addresses theoretical aspects of arithmetic circuit verification based on algebraic rewriting. Its goal is to advance the understanding of algebraic techniques for arithmetic circuit verification in the context of symbolic computer algebra. The paper offers a new insight into the arithmetic circuit verification problem, by viewing the computation performed by the circuit as the flow of digital data. In the proposed bit-flow model, the circuit is modeled as a network of logic components satisfying a bit-flow conservation law. We prove that the value of the flow of data in the circuit is invariant throughout the circuit and use this to prove soundness and completeness of the rewriting technique, independently from the computer algebra arguments. The efficiency of the method is illustrated with impressive results for large integer multipliers. The verification system and benchmarks are offered in an open source software environment. [ABSTRACT FROM AUTHOR]

A novel method for semantic action recognition through learning a pose lexicon is presented in this paper. A pose lexicon comprises a set of semantic poses, a set of visual poses, and a probabilistic mapping between the visual and semantic poses. This paper assumes that both the visual poses and mapping are hidden and proposes a method to simultaneously learn a visual pose model that estimates the likelihood of an observed video frame being generated from hidden visual poses, and a pose lexicon model establishes the probabilistic mapping between the hidden visual poses and the semantic poses parsed from textual instructions. Specifically, the proposed method consists of two-level hidden Markov models. One level represents the alignment between the visual poses and semantic poses. The other level represents a visual pose sequence, and each visual pose is modeled as a Gaussian mixture. An expectation-maximization algorithm is developed to train a pose lexicon. With the learned lexicon, action classification is formulated as a problem of finding the maximum posterior probability of a given sequence of video frames that follows a given sequence of semantic poses, constrained by the most likely visual pose and the alignment sequences. The proposed method was evaluated on MSRC-12, WorkoutSU-10, WorkoutUOW-18, Combined-15, Combined-17, and Combined-50 action datasets using cross-subject, cross-dataset, zero-shot, and seen/unseen protocols. [ABSTRACT FROM AUTHOR]

This paper proposes a detailed equivalent model for electromagnetic transient simulation of a modular multilevel converter with embedded battery energy storage in its submodules. The model offers an accuracy identical to that of a detailed switching model (DSM), while it markedly reduces the computational complexity of simulations. This is achieved by modeling each multivalve as a Thevenin equivalent considering the full dynamics of each constituent submodule, which results in a significant reduction in the number of switchable nodes in the converter model and hence the dimensions of the system's admittance matrix. The paper presents the mathematical development of the model and validates it against detailed switching models through several case studies. Experimental results from a scaled-down laboratory setup are also presented for further verification. [ABSTRACT FROM AUTHOR]

Partial shading condition drastically reduces the maximum power output of photovoltaic array. Partial shading occurs due to several factors, such as flying birds, trees, and passing clouds. Many ways can be mitigated partial shading problems in photovoltaic (PV) array. One among the way is reconfiguration techniques, namely reconfigure the location of PV modules in PV array based on irradiance levels in order to distribute shading effects and increasing maximum power. This paper proposed an optimal SuDoKu reconfiguration pattern for $9\times 9$ total-cross-tied (TCT) PV array to improve maximum power under partial shading conditions. In this approach, the physical location of PV modules in TCT array are rearranged based on optimal SuDoKu style without altering the electrical connections, so that the shading effects can distribute over the array. Further, the performance of proposed pattern investigated with existing SuDoKu pattern under different shading conditions by comparing the global maximum power point, mismatch losses, fill-factor, and efficiency using MATLAB-Simulink. Based on the results of this paper, it concluded that the proposed optimal SuDoKu reconfiguration arrangement is reducing the wiring arrangement and increasing the shading distribution over the array as compared to SuDoKu arrangement. [ABSTRACT FROM AUTHOR]

This paper deals with stabilization of an ideal transformer model (ITM) circuit, used as an interfacing algorithm for hardware-in-the-loop simulations. The ITM allows for the distribution of simulation model computations over multiple processors or can be used in power hardware-in-the-loop simulations. When specific impedance conditions of the partitioned circuit are not met, this interfacing algorithm becomes unstable. This paper first presents a new theoretical approach for representing the ITM interfacing algorithm that is based on delay differential equations. With a stability analysis of the obtained time-delay system, a stabilization method is proposed, which increases the stability boundaries of the ITM algorithm. Simulation examples, including the scenario of a two-level inverter system, are provided. [ABSTRACT FROM AUTHOR]

Test generation procedures target a variety of fault models in order to produce test sets that are effective for defect detection. This paper considers the likely scenario where two-cycle skewed-load tests are generated to detect single transition faults, and the test set is complemented with tests for single stuck-at faults that are not detected by the transition fault test set. For this scenario, this paper makes several unique observations that can be utilized to produce a single compact test set that consists only of two-cycle skewed-load tests for both fault models. The first observation is that a single-cycle test for a stuck-at fault can be transformed into a skewed-load test that is guaranteed to detect the stuck-at fault without performing logic or fault simulation. The second observation is that skewed-load tests, which are transformed from single-cycle tests for stuck-at faults, sometimes detect more transition and stuck-at faults than tests that were generated for transition faults. The third observation is that a static test compaction procedure, which is based on the modification and removal of tests, is effective in this context because it allows tests for stuck-at faults to detect more transition faults and vice versa. This paper describes a test compaction procedure based on these observations and presents experimental results for benchmark circuits to demonstrate the effectiveness of the procedure. [ABSTRACT FROM AUTHOR]

This paper introduces a novel modeling approach that allows to obtain fast simulations of pulsewidth-modulated dc–dc switched-mode power supplies (SMPS). The proposed methodology combines the use of precise switched models during transient evolutions and averaged models during steady-state or slowly varying conditions. In that way, the resulting mixed modeling approach enables to obtain the detailed switching behavior of SMPS in the context of long-term simulations. The commutation between models is automatically performed in runtime by an algorithm that detects the transient or slowly varying condition according to the evolution of some model variables. When the precise switched model is used, the mentioned algorithm also adjusts the averaged model parameters so that its results are accurate irrespective of the operating point. This paper also describes the implementation of the methodology in the Modelica language and reports simulation experiments showing that the results are as accurate as those obtained using precise switched models, but several times faster. [ABSTRACT FROM AUTHOR]

State of charge (SOC) estimation of lithium-ion batteries has been extensively studied and the estimation accuracy was mainly investigated through the development of various battery models and dynamic estimation algorithms. All battery models, however, contain inherent model bias due to the simplifications and assumptions, which cannot be effectively addressed through the development of various algorithms such as Kalman filtering (KF) or particle filtering (PF). Consequently, as observed in some study, battery SOC estimation using a typical extended KF in fact is not very accurate where the error could range from 5% to 10% or even more depending on the battery characteristics. This paper proposes bias characterization of the battery model, so that accuracy of the baseline model could be significantly improved and eventually SOC estimation could be much more accurate than the one only using the baseline model. This paper reports great potential for improving battery SOC estimation with the bias characterization and proposes two methods for actual bias modeling. In particular, the polynomial regression model and the Gaussian process regression model are proposed to examine the effects of the two methods on bias modeling and SOC estimation using a typical battery circuit model. Results are demonstrated in both simulation and lab testing using three battery charging/discharging profiles with the cross-validation technique. [ABSTRACT FROM AUTHOR]

This paper introduces a fully automated greedy algorithm for the construction of parameterized behavioral models of electromagnetic structures, targeting at the same time uniform model stability and passivity. The proposed algorithm is able to determine a small set of parameter configurations for which an external solver provides on-the-fly the sampled scattering parameters of the structure over a predetermined frequency band. These samples are subjected to a multivariate rational/polynomial fitting process, which iteratively leads to a parameterized descriptor realization of the model. The main novel contribution in this paper is the adoption of a model-based approach for the adaptive augmentation of an initially small set of frequency responses, each corresponding to a randomly selected parameter configuration. In particular, the locations of the in-band passivity violations of intermediate macromodels constructed at each iteration are used as a proxy for the model-data error in those regions where input data are not available. This physics-based consistency check, which is enabled by recent developments in multivariate passivity characterization based on Skew-Hamiltonian–Hamiltonian (SHH) spectra, is combined with standard space exploration metrics to obtain a small-size and automatically determined distribution of points in the parameter space, leading to the construction of an accurate macromodel with a very limited number of external field solver runs. The embedded passivity check and enforcement process guarantees that either the final model is passive throughout the parameter space or the residual violations, if present, are negligible for practical purposes. Several examples validate the proposed approach for up to three concurrent parameters. [ABSTRACT FROM AUTHOR]

This paper proposes a new fast chargingstrategy for lithium-ion (Li-ion) batteries. The approach relies on an experimentally validated high-fidelity model describing battery electrochemical and thermal dynamics that determine the fast charging capability. Such a high-dimensional nonlinear dynamic model can be intractable to compute in real-time if it is fused with the extended Kalman filter or the unscented Kalman filter that is commonly used in the community of battery management. To significantly save computational efforts and achieve rapid convergence, the ensemble transform Kalman filter (ETKF) is selected and tailored to estimate the nonuniform Li-ion battery states. Then, a health- and safety-aware charging protocol is proposed based on successively applied proportional-integral (PI) control actions. The controller regulates charging rates using online battery state information and the imposed constraints, in which each PI control action automatically comes into play when its corresponding constraint is triggered. The proposed physical constraint-triggered PI charging control strategy with the ETKF is evaluated and compared with several prevalent alternatives. It shows that the derived controller can achieve close to the optimal solution in terms of charging time and trajectory, as determined by a nonlinear model predictive controller, but at a drastically reduced computational cost. [ABSTRACT FROM AUTHOR]

This paper presents the modeling of some protective relays commonly used in generation and transmission systems, and their integration in three-phase RMS dynamic simulation tool. The three-phase models of the network and the power apparatuses, utilizing phase frame representation, enlarges the possibility to better represent the protection systems, since the relays involving ground and neutral circuitry can be modeled. The network can be modeled with a node-breaker topology representation, facilitating the integration of protecting relays and the switchgear. The relay modeling framework can also be used in positive-sequence RMS dynamic simulation tools with few adjustments in the measured quantities. Simulation results in realistic small and large-scale systems showing the performance of the proposed relay modeling framework and a comparison with an EMT tool are presented. [ABSTRACT FROM AUTHOR]

The design of squirrel-cage induction motors (IMs) entails the capability to predict the motor efficiency map with high accuracy over an operating range. In particular, modeling harmonic rotor bar currents becomes important for loss analysis. In theory, it is possible to analyze an induction motor using time-stepping finite element analysis (TS-FEA); however, this is not viable due to computational limitations. To bridge this gap, we set forth a computationally efficient method that couples magnetostatic FEA with a qd-circuit model of the cage. The proposed IM model includes the effects of saturation, winding and slot harmonics, as well as nonuniform current density distribution in the rotor bars. The model is presented in two parts. Part I focuses on the formulation of a qd cage circuit model with segmented bars. Part II is a companion paper that proposes an FEA-based parameter estimation and a solution method. [ABSTRACT FROM AUTHOR]

Adiabatic logic is an energy-efficient technique, however, the time required in the design, validation, and debugging increases manifold for large-scale adiabatic system designs. In this endeavor, we present a hardware description language (HDL)-based modeling approach for 4-phase adiabatic logic design. The paper highlights the drawbacks of the existing approaches and proposes a new approach that captures the timing errors and detects the circuit’s invalid operation due to mutually exclusive inputs being violated. We develop a model library containing the function of the four periods used in the trapezoidal power-clock and the adiabatic logic gates. The validation and verification of the proposed approach were done on the ISO-14443 standard benchmark circuit, a 16-bit cyclic redundancy check (CRC) circuit. The system modeled using HDL shows the timing agreement with the transistor-level SPICE simulations. The novel use of the four periods of a power-clock improves the robustness and reliability for the design and verification of large adiabatic systems. [ABSTRACT FROM AUTHOR]

Large-scale circuit simulation poses a challenge to most simulation tools because of its high computational complexity. This paper presents an efficient method, which decouples the circuit topology and components’ characteristics in computation so as to make it suitable for large-scale circuit simulation. The proposed method is based on a circuit lemma, which indicates the relationship of branch voltages and currents. The proving process of this lemma is provided in this paper. The working principle of the proposed method is elaborated and its numerical stability is also analyzed. This method achieves nearly linear computational complexity and is very suitable for hierarchical and zonal computation. The proposed method is verified by real-time application on the more electric aircraft microgrid. Hardware-in-the-loop testing of this study case on Xilinx Virtex Ultrascale+ field programmable gate array (FPGA) board is achieved and the results are compared with PSCAD/EMTDC. The resulting waveforms from these two simulation tools show very good agreement on both normal and fault operation test scenarios, which demonstrates that the proposed method has very good performance on computational accuracy and efficiency. [ABSTRACT FROM AUTHOR]

System identification is fundamental in many recent state-of-the-art developments in power electronic such as modeling, parameter tracking, estimation, self-tuning and adaptive control, health monitoring, and fault detection. Therefore, this paper presents a comprehensive review of parametric, non-parametric, and dual hybrid system identification for dc–dc switch mode power converter (SMPC) applications. The paper outlines the key challenges inherent with system identification for power electronic applications; speed of estimation, computational complexity, estimation accuracy, tracking capability, and robustness to disturbances and time-varying systems. Based on the literature in the field, modern solutions to these challenges are discussed in detail. Furthermore, this paper reviews and discusses the various applications of system identification for SMPCs; including health monitoring and fault detection. [ABSTRACT FROM AUTHOR]

This paper presents a novel circuit model for eddy-current effects for multi-winding transformers. It presents the theoretical framework to model eddy currents applicable to layer or disk windings with n-layers for two-dimensional (2-D) transformer arrangements. The new white-box model is physical, dual, and leakage reversible. Additionally, it does not have mutually coupled elements or negative inductors. The paper presents a complete circuit for transformer windings (including capacitances) and core. The model accurately predicts the variation of resistance (dc component, skin, and proximity effects) and leakage inductance of windings from dc to hundreds of kilohertz. Being derived from the principle of duality, the circuit elements can be physically related one-to-one to the distribution of flux and current in the winding geometry. A practical winding discretization, based on field penetration depth for the given frequency, allows estimating the parameters using very simple formulae requiring only geometrical information and properties of materials. Model verification is done using finite element simulations. It is shown that the circuit model matches very well with 2-D FEM simulations. The circuit can be easily implemented in any circuit simulation software like EMTP-RV, PSCAD, ATP, etc., by simply dragging and dropping elements. [ABSTRACT FROM AUTHOR]

A diagnostic test generation procedure targets fault pairs in a set of target faults with the goal of distinguishing all the fault pairs. When a fault pair cannot be distinguished, it prevents the diagnostic test set from providing information about the faults, and consequently, about defects whose diagnosis would have benefited from a diagnostic test for the indistinguishable fault pair. This is referred to in this paper as a diagnostic hole. This paper observes that it is possible to address diagnostic holes by targeting different but related fault pairs, possibly from a different fault model. As an example, this paper considers the case where diagnostic test generation is carried out for single stuck-at faults, and related bridging faults are used for addressing diagnostic holes. Considering fault detection, an undetectable single stuck-at fault implies that certain related bridging faults are undetectable. This paper observes that, even if a pair of single stuck-at faults is indistinguishable, a related pair of bridging faults may be distinguishable. Based on this observation, diagnostic tests for pairs of bridging faults are added to a diagnostic test set when the related single stuck-at faults are indistinguishable. Experimental results of defect diagnosis for defects that do not involve bridging faults demonstrate the importance of eliminating diagnostic holes. [ABSTRACT FROM AUTHOR]

Two challenges are combined when compressed tests are computed for path delay faults: 1) path delay faults that are important to detect are associated with long paths, and many of these faults are undetectable and 2) it may not be possible to compress a given test for a path delay fault. This paper addresses these challenges in the context of test data compression methods that are based on a linear-feedback shift-register (LFSR). The basic approach that this paper uses modifies initially random seeds for the LFSR into seeds that produce tests for detecting target faults. This approach can find seeds even if the available tests cannot be compressed into seeds. In addition, the procedure described in this paper also selects detectable path delay faults to address the presence of undetectable path delay faults in the set of target faults. For this purpose it uses a metric that measures the similarity between target and detected path delay faults, and attempts to compute seeds that increase the values of this metric. Experimental results are presented to demonstrate the ability of the procedure to detect path delay faults in benchmark circuits. [ABSTRACT FROM AUTHOR]

To investigate and quantify the radiation emission of an electronic package model, the partial element equivalent circuit method combined with the field equivalence principle is developed in this paper and used for the near-field radiation prediction. Furthermore, this paper presents a novel electromagnetic bandgap (EBG) design to suppress the electromagnetic radiation. The simulation results obtained by the proposed method have been validated against the measurement; moreover, the simulation and measurement results demonstrate the noise suppression ability of the new designed EBG structure, which can be used to reduce the electromagnetic radiation of the package. [ABSTRACT FROM AUTHOR]

In this paper, a stabilized reduced-order model based on the gappy proper orthogonal decomposition (POD) technique is applied to an eddy-current problem with the non-linear material property. A classical magnetodynamic finite element formulation based on the magnetic vector potential is used as reference and starting point to build up the reduced models. The computational complexity of the non-linear problem might be reduced by the discrete empirical interpolation method-POD technique, but the eddy current effects may make this method unstable. In this paper, we propose an approach which is similar to the gappy method to successfully overcome this instability problem, while keeping the computational cost (time and memory) low. [ABSTRACT FROM AUTHOR]

In this paper, an enhanced compact model of multiwalled carbon nanotube (MWCNT) interconnects while considering defects and contact resistance is proposed. Based on the atomistic-level simulations, we have found that defect densities impact MWCNT resistance and ultimately their electrical performance. Furthermore, we have computed by atomistic-level simulations, the end-contact resistance between single-wall carbon nanotube and palladium (Pd) electrode to mimic the Pd–CNT end-contact resistance of each CNT shell in MWCNT. We have developed an advanced shell-by-shell model to include various parameters, such as shell diameter, shell chirality, defects on each shell, and connectivity of each shell to end contacts. We run Monte Carlo simulations to perform variability studies on each of these parameters to understand the electrical performance variation on MWCNT interconnects. We present the simulation results to convey the critical impact of variations. The impact of doping on MWCNT variability in the form of Fermi level shift will be addressed in Part II of this paper. [ABSTRACT FROM AUTHOR]

The nonlinearities and memory effects of power amplifiers (PAs) can be compensated by multistage cascaded digital predistortion with low complexity. Compared with full multistage models, sparse multistage models may have the same linearization performances while their complexities are even lower. However, the choice of the model structure is very difficult, especially for the sparse models. For instance, if there are $(K+1)(L+1)$ full models, then $2^{K+L-2}$ different corresponding sparse models exist. An algorithm with the optimal search space definition is proposed in this paper to search for the optimal cascaded sparse model structure. The search criterion represents tradeoff between the modeling accuracy and identification complexity with a weight coefficient. A method to determine the value of the weight coefficient is proposed in this paper. The sparse model solution found by the proposed algorithm is evaluated with a three-way Doherty PA using a long term evolution-advanced signal. It is also compared with the solution of full model structure search. [ABSTRACT FROM AUTHOR]

With the increasing penetration of renewable energies in modern power grids, large amounts of voltage source converters (VSCs) have been installed, resulting in many new transient issues. Electromagnetic transient (EMT) simulation plays an essential role in investigating and solving the issues. However, simulation efficiency plunges when object grids contain multiple VSCs, because each switching event incurs modification or re-decomposition of the network matrix in traditional EMT programs, which is very time-consuming. Thus, this paper proposes a VSC model represented by pulse voltage-current source pairs. Accordingly, a unidirectional loosely-coupled solving algorithm is designed. Synthetically, the authors propose a novel EMT simulation approach adaptive to systems with multiple VSCs. The proposed approach keeps the computational network invariable while sufficiently considers detailed switching events, thereby significantly improving the simulation efficiency of the EMTP program without precision loss. [ABSTRACT FROM AUTHOR]

In comparison to single-model based trackers, the model-ensembled tracking strategy has shown a substantial adaptivity in handling various tracking challenges. As the performance of the tracker has been improved by combining different model outputs linearly, the insufficient consideration of each ensemble member’s contribution still limits the tracking performance to be further enhanced. As the performance of the tracker has been improved by combining different model outputs linearly, the insufficient consideration of each ensemble member’s contribution still limits the tracking performance to be further enhanced. In this paper, a tracking strategy based on multiple instance models regression (MIMRT) is proposed with a unified ensembling scheme. By formulating the tracking initialization with an instance model, the encoding process for an object’s specific detail is performed corresponding to the samples in each frame. The advantage of this operation is to guarantee the model frame-wise discrimination of short-term training, as well as to evaluate the reliability of each instance model by utilizing the long-lifetime samples obtained throughout the whole tracking procedure. To finalize the proposed tracking, all the independent instance models attached to the learned regression coefficients are ensembled with respect to the long-lifetime samples. This also effectively bridges the instance model as a latent variable to investigate a semantic association between the tracking model and the overall samples. A comprehensive experiment has shown that the proposed tracker is able to achieve superior performances compared to the state-of-art tracking approaches on both short-term datasets (e.g., OTB2013, OTB100, VOT2016, UAV123) and long-term dataset (UAV20L). [ABSTRACT FROM AUTHOR]