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The series-paralleling technique of dc-dc converters is utilized in various domains of electrical engineering for improved power conversion. Previous studies have proposed and classified the control schemes for the series-paralleled converters. However, they have several restrictions and lack diversity. The purpose of this paper is to propose passivity-based control (PBC) for the diverse output series-parallel connection of dc-dc converters. It is proved that the output series-paralleled converters regulated by PBC are asymptotically stable. The output series-paralleled converters are numerically simulated to confirm the asymptotic stability. PBC is shown to maintain the stability of the output series-paralleled converters with diverse circuit topologies, parameters, and steady-states. The result of this paper theoretically supports the numerical and experimental considerations in the previous studies and justifies the further extension of the series-parallel connection., Comment: 10 pages, accepted for publication in IEEE Transactions on Circuits and Systems I: Regular Papers

In this paper, a converter-based multi-bus DC microgrid (MG) in series is studied, in which the trade-off between voltage recovery and current equalization has been a hot topic of interest. To solve this problem, a distributed learning-based high-order fully actuated (DL-HOFA) secondary control is proposed in this paper, and the simple structure of this control technique facilitates its application in various modern DC MGs with different configurations. Before designing the secondary control protocol, this paper provides a comprehensive description of DC MGs in advance. In the suggested control strategy, the controller design is tightly related to the underlying physical characteristics of the MG, and this prominent feature represents a significant improvement in its adaptability. In addition, the DL-HOFA control obtains fast dynamic and accurate current sharing performance by virtue of the high-order fully actuated DC MG model. The effectiveness of the proposed control method is verified on a real photovoltaic- and battery-based hardware system with maximum power point tracking (MPPT) controller.

In this work, we focus on the three most relevant pseudo-digital ring oscillator circuits for VCO A/D conversion. First, we show that they can be accurately modeled by an equivalent 2-terminal diode-like element. Next, we study the main analog performance figures: the effective oscillation frequency (which affects the quantization noise of a VCO ADC), the input referred noise and the power efficiency both for voltage and current control. We do this both through theoretical modeling as well as through simulations, which are in good agreement with each other. Our study highlights several important independencies: e.g. most performance metrics are independent on the number of VCO stages and the external load capacitance on the VCO nodes. In contrast to these independencies, we identify several important dependencies. In particular, we show that the biasing of the ring has an enormous impact on power efficiency of the ring. This dependency is different for the case of a voltage- or current mode configuration of the ring.

This paper introduces rational polynomial chaos expansions for the stochastic modeling of the frequency-domain responses of linear electrical networks. The proposed method models stochastic network responses as a ratio of polynomial chaos expansions, rather than the standard single polynomial expansion. This approach is motivated by the fact that network responses are best represented by rational functions of both frequency and parameters. In particular, it is proven that the rational stochastic model is exact for lumped networks. The model coefficients are computed via an iterative re-weighted linear least-square regression. Several application examples, concerning both lumped and a distributed systems, illustrate and validate the advocated methodology.

The paper deals with some new results on the averaging theory approach for the analysis of feedback controlled pulsewidth modulation power electronic converters. It develops some considerations regarding the averaging approximation of time-variant differential systems proving an analytical relationship between the accuracy with which the solution of the averaged model converges to the solution of the original time-variant model (i.e., the switched model) and the switching frequency of the converters. This relation is valid both for stable and unstable systems. Moreover, this paper confirms, as corollary, that under suitable conditions (verified during the standard operations of the power electronic converters) the averaged model uniformly converges to the switched model.

We reconsider the black box model by Urbanek of electric-arc in air-blast circuit breakers or in circuit breakers characterized by an electro-negative gas (e.g., SF6) as quenching medium. It has the unique characteristic to account for the dielectric breakdown that possibly reignites the arc. We show some of its main features that have been almost hidden from the first publication of the model in the literature. The conductance in the Urbanek model plays two roles: 1) it effectively represents the conductance of the burning arc when positive and 2) it is a thermodynamic indicator when negative. This thermodynamic indicator is used to eventually trigger a restrike of the arc. We show that this switching behavior can be formally analyzed by considering the model as an hybrid dynamical system. In this paper, we reconsider it and show its main dynamic properties through some case studies.

Electric machines (motors and generators) are over actuated systems. In this paper, we show how to exploit this actuation redundancy in order to mitigate machine degradation while simultaneously ensuring that the desired closed loop performance is maintained. We formulate a multiobjective optimization problem with a cost function having terms representing closed loop performance and component degradation for an inverter-fed permanent magnet synchronous motor. Such machines are important as they are widely used as the prime mover of commercial electric vehicles. The resulting optimal control problem is implemented online via a nonlinear model predictive control (NMPC) scheme. The control framework is validated for standard vehicle drive cycles. Results show that the NMPC scheme allows for better closed loop performance and lower degradation than standard industrial controllers, such as the field-oriented control method. Hence, this paper demonstrates how the remaining useful life of a machine can be increased by appropriate controller design without compromising performance.

In the post-CMOS scenario, field coupled nanotechnologies represent an innovative and interesting new direction for electronic nanocomputing. Among these technologies, nanomagnet logic (NML) makes it possible to finally embed logic and memory in the same device. To fully analyze the potential of NML circuits, design tools that mimic the CMOS design-flow should be used for circuit design. We present, in this paper, the latest and improved version of Torino Politecnico Nanotechnology (ToPoliNano), our design and simulation framework for field coupled nanotechnologies. ToPoliNano emulates the top-down design process of CMOS technology. Circuits are described with a VHSIC hardware description language netlist and layout is then automatically generated considering in-plane NML (iNML) technology. The resulting circuits can be simulated and performance can be analyzed. In this paper, we describe several enhancements to the tool itself, like a circuit editor for custom design of field coupled nanodevices, improved algorithms for netlist optimization and new algorithms for the place and route of iNML circuits. We have validated and analyzed the tool by using extensive metrics, both by using standard circuits and ISCAS’85 benchmarks. This contribution highlights the improvements of ToPoliNano, which is now a innovative and complete tool for the development of iNML technology.

This paper proposes a method to include the anisotropic hysteresis characteristics of soft-magnetic laminated steels in the magnetic equivalent circuit (MEC) modeling. The loop-based MEC formulation is improved to handle the nonlinearity of the anisotropic magnetic hysteresis, including the dynamic classical eddy-current and excess fields. The developed MEC model is coupled with both the single-valued B-H curve (SVC) in magnetostatic and the dynamic vector hysteresis model (VHM) in transient analysis. Results with a single elementary MEC element show that an alternating magnetic field in a single direction with a peak value smaller than 300 A/m causes a discrepancy of more than 10% between the magnetic flux densities calculated by the VHM and SVC at 50 and 200 Hz excitation frequencies. Moreover, the proposed modeling technique is verified experimentally using the laminated transformer core of TEAM problem 32. The induced voltage calculated by the MEC model with the VHM demonstrates a good agreement with the measurements, while the MEC model with the SVC calculates inaccurate voltage waveforms. Lastly, the total iron loss dissipated in the transformer's iron core is investigated to verify the proposed technique under different excitation levels and frequencies up to 500 Hz. It is observed that the proposed MEC model with the vector hysteresis characteristics of laminated steels is able to calculate the iron loss accurately, while the conventional single-valued curve method fails to estimate the iron loss.

Spikes and rhythms organize control and communication in the animal world, in contrast to the bits and clocks of digital technology. As continuous-time signals that can be counted, spikes have a mixed nature. This paper reviews ongoing efforts to develop a control theory of spiking systems. The central thesis is that the mixed nature of spiking results from a mixed feedback principle, and that a control theory of mixed feedback can be grounded in the operator theoretic concept of maximal monotonicity. As a nonlinear generalization of passivity, maximal monotonicity acknowledges at once the physics of electrical circuits, the algorithmic tractability of convex optimization, and the feedback control theory of incremental passivity. We discuss the relevance of a theory of spiking control systems in the emerging age of event-based technology.

In this paper, using a minimum number of passive components, i.e., new grounded and floating inductance simulators, grounded capacitance multipliers, and frequency-dependent negative resistors (FDNRs) based on one/two modified current-feedback operational amplifiers (MCFOAs), are proposed. The type of the simulators depends on the passive element selection used in the structure of the circuit without requiring critical active and passive component-matching conditions and/or cancellation constraints. In order to show the flexibility of the proposed MCFOA, a single-input three-output (SITO) voltage-mode (VM) filter, two three-input single-output (TISO) VM filters, and an SITO current-mode (CM) filter employing a single MCFOA are reported. The layout of the proposed MCFOA is also given. A number of simulations using the SPICE program and some experimental tests are performed to exhibit the performance of the introduced structures. © 2008 IEEE.

In several cases, substations have become incapable of supporting faults due to short circuit levels increasing. Fault current limiters (FCLs) are a potential solution for this problem. Among several FCL topologies presented in the literature, the saturated Iron-Core Superconducting Fault Current Limiter (SIC-SFCL) has shown promising results in real tests in substations. In this context, this paper presents the impacts of the different kinds of short circuits in the SIC-SFCL device. To reproduce various types of faults, the SIC-SFCL is modeled in a 3D framework considering both ferromagnetic and superconducting non-linearities. Moreover, the proposed 3D FEM model can couple the SIC-SFCL to the electric power system, also representing the electrical grid and the protection systems. For this investigation, the DC-biased superconducting coil's normalized current density and the iron cores' magnetic flux density are examined in light of the different short circuits. The simulations are compared with measurements in a bench prototype, showing a maximum error of 16.5~%. Furthermore, different short circuit types were investigated and compared, which is possible only using a 3D model. The highest limitation occurred in the phase-to-phase short circuit case. In the DC circuit of the SIC-SFCL, the highest transient period has happened in the single-phase short circuit. At last, the phase-to-phase fault presented the highest DC current during the transient.

When RTL designers define the hierarchy of a system, they exploit their knowledge about the conceptual abstractions devised during the design and the functional interactions between the logical components. This valuable information is often lost during physical synthesis. This paper proposes HiDaP, a novel multi-level algorithm that uses RTL information and analytical methods for the macro placement problem of modern designs dominated by multi-cycle connection pipelines. By taking advantage of the hierarchy tree, the netlist is divided into blocks containing macros and standard cells, and their dataflow affinity is inferred considering the register latency and flow width of their interaction. The layout is represented using slicing structures and generated with a top-down algorithm capable of handling blocks with both hard and soft components. An adaptive multi-objective cost function is used to simultaneously minimize wirelength, timing, overlap and distance to preferred locations, which can be user-defined or generated by analytic methods (spectral and force-directed). These techniques have been applied to a set of large industrial circuits and compared against state-of-theart commercial and academic placers, and also to handcrafted floorplans generated by expert back-end engineers. The proposed approach outperforms previous algorithmic methods and can produce solutions with better wirelength and timing than the best handcrafted floorplans. Post-routing layouts are almost brought to timing closure and DRC cleanness with minimal engineer modification, showing that the generated floorplans provide an excellent starting point for the physical design flow and contribute to reduce turn-around time significantly. This work has been partially supported by a grant from Inphi Corporation and funds from the Spanish Ministry for Economy and Competitiveness and the European Union (FEDER funds) under grant TIN2017-86727-C2-1-R, and the Generalitat de Catalunya (2017 SGR 786).

International audience; Electromagnetic Fault Injection (EMFI) has recently gained popularity as a mean to induce faults because of its inherent advantages. Despite this popularity, there is only little information on how EMFI generates faults. Within this context, this paper aims at filling this lack by proposing a complete understanding and modeling of EM induction on Integrated Circuits (IC). The presented model is confronted to experiments to endorse its soundness.

The Switched-Resistor (S-R) approach is gaining popularity among integrated circuits designers because it allows to implement very high equivalent resistances, and thus very large time constants, in CMOS circuits. In this paper, we present an in-depth analysis of the S-R technique and propose a novel detailed model which allows to accurately predict the value of the equivalent resistance even for values of the duty cycle as low as 0.0001% which result in a huge resistance multiplication factor. We show that the conventional model of the S-R technique provides a reasonable accuracy for duty cycle values down to 1%, but its accuracy becomes unacceptable for smaller values of the duty cycle. In the proposed detailed model of the S-R we take into account also the parasitic capacitances of the integrated poly resistors and the non-ideal resistance of the CMOS switches. The modeling strategy is based on the solution of the differential equations for the different switches settings and exploits the Y-matrix to represents the floating S-R. The proposed model has been validated against periodic steady state (PSS) and periodic AC (PAC) simulations referring to a 130nm CMOS technology. Results have shown an average and maximum error lower than 0.53% and 5.15% respectively. As a further validation, a first-order active low-pass filter has been implemented with the same technology with a cutoff frequency tunable from 1.68Hz to 1.46kHz. The average and maximum errors in the estimation of the cutoff frequency have resulted lower than 3.6% and 7% respectively.

Electrical impedance tomography (EIT) has the potential to be an alternative technique to microscopy for many biological applications. It is a novel approach to monitor cell viability, proliferation, or drug response with high temporal resolution in a label-free, non-toxic, and non-destructive way. To limit measurement errors, only time-difference EIT is currently used for biological imaging. Still, the need for constant background reference limits its uses in long-term imaging. A novel equivalent circuit model was developed to analyze the errors in frequency-difference EIT (FDEIT) measurements. Based on the circuit model, the calibrated FDEIT (CFDEIT) method has been derived to compensate the measurement errors. The simulation results show that the voltage variations introduced by the leakage current are correctly modeled by the equivalent circuit. Significant improvements in the image quality are observed in both simulation and experimental results after the application of CFDEIT. It indicates that this paper improves the accuracy of FDEIT and makes it feasible for 3D tissue culture monitoring.

It is commonly believed that weak light-matter interactions in low-mobility graphene dramatically limits tunability of graphene-based optoelectronic devices, such as tunable absorbers or switches. In this paper, we develop and use a simple circuit model to understand absorption in graphene sheets. In particular, we show that light interacts weakly also with very high-mobility graphene sheets and propose systematic design means to overcome these problems. The results have allowed us to demonstrate in the terahertz band that perfect absorption with excellent electrical tunability can be achieved within a wide span of mobility values which almost covers the whole range of ever reported room-temperature mobilities. Remarkably, concentrating on the most practical low-mobility graphene devices, we exemplify our theory with two cases: frequency-tunable and switchable absorbers with near 100% modulation efficiencies. Our work provides systematic and instructive insights into the design of highly tunable absorbers, without restrictions on graphene mobility. The design strategy and the developed analytical model can, in principle, be generalized to other wavelength regions from microwave to mid-infrared range, and other two-dimensional materials such as transition metal dichalcogenides (TMDs) and black phosphorus., 11 pages and 12 figures

This paper presents a novel step-up dc to ac converter with only one power supply. These types of converters are suitable for renewable and sustainable energy applications with low input dc sources. The proposed topology has the ability of self-voltage balancing and does not apply end side H-bridge to produce a bipolar staircase waveform. Consequently, switching losses and voltage stress of semiconductor components are reduced to a great extent. A small dc voltage source can be used to achieve a high voltage high quality ac waveform through switching the precharged capacitors in series and in parallel. Circuit configuration and its operation principle, capacitors’ charging process, thermal model, capacitances, and losses calculations are discussed in details. Moreover, the comparison of the proposed circuit with the other single source multilevel converters shows that the proposed topology reduces the number of circuit elements. Finally, a laboratory nine-level prototype is built to verify the theoretical analyses and feasibility of the proposed topology. The experimental results show that the converter efficiency at 1 KW output power is 92.75%.

Hydraulic cylinders and motors are commonly used in actuator systems of mobile machines and industrial applications. Hydraulic actuators have the ability to offer large amounts of energy density. To analyze the dynamic behavior of a hydraulic actuator system, the hydraulic circuit is generally divided into volumes in which pressure is assumed to be equally distributed. The pressure within these volumes can be predicted by employing first-order differential equations. To achieve an accurate numerical presentation of a hydraulic circuit, pressures within very small volumes must often be calculated. The small volumes involved in the hydraulic circuits make the models numerically stiff, and consequently, a very small integration time-step is required. In this paper, the singular perturbation theory, which can be applied to problems in which a small value appears with singularity effects, is implemented as a computationally efficient method for modeling hydraulic circuits. The implementation is performed in two stages, i.e., the derivation of the perturbed equations and the modification of their effects. It is shown that the usage of a perturbation theory based approach alleviates problems associated with small volumes in hydraulic system modeling and substantially enhances computational efficiency, thus facilitating real-time simulation. Post-print / Final draft

CLCL resonant converters represent an interesting and emerging high-order resonant converter topology. In this paper, some modeling methods have been introduced and analyzed in detail, with special emphasis on their frequency characteristics. Hence, a small-signal model has been set up and a control to output transfer function has been obtained by using the state-space method. Also, frequency characteristics related to different component parameters is investigated and a systematic modeling approach for derivative topologies with higher order resonant tanks is proposed. The relevance of the obtained results are further demonstrated through experimental tests.

cited By 0; International audience; Energy harvesting from various ambient energy sources keeps gaining interest to deal with the challenges arising from more and more widespread Internet of Things applications in consumer electronics and industrial applications such as remote sensing. However, available energy is scarce and designers must comply with small size package and thermal dissipation that inevitably lead to compromises. This paper presents a transformer-free and self-powered oscillator that can be directly powered from a very low dc voltage source such as a thermoelectric module and able to deliver dc bias output. Using off-the-shelves parts, such a design is less cumbersome and gives more freedom to designers while tailoring their circuits with respect to their applications. The oscillator consists of a modified Hartley oscillator including a supplementary capacitor that provides a bias voltage in its output. Theoretical analysis is validated through experimental measurements showing that the proposed solution could be deployed in buildings and/or wearable devices as small and cheap complete microgenerators using for example thermoelectric elements or microbial fuel cells. © 1982-2012 IEEE.

Employing bipolar dc distribution systems introduces the possibility of imbalance in the system. To analyze these systems it is important to create novel modelling techniques. Therefore, this paper presents a method to decompose dc distribution systems into symmetrical components. The presented method simplifies the analysis of balanced, unbalanced, and fault conditions of bipolar dc distribution systems. Furthermore, equivalent circuits for several network components in the symmetrical domain are derived and are shown to be independent under symmetrical conditions. Additionally, a dynamic analysis is performed in the symmetrical domain showing that the method simplifies the analysis of dc distribution systems. Finally, the symmetrical domain equivalent circuits of several fault conditions are derived.

International audience; 1-D compound metallic grating (CMG) is a periodic structure with more than one slit in each period. When CMG is combined with a graphene sheet as its cover, the incident light is effectively coupled to the plasmons in graphene which in turn can result in strong manipulation of light for both major polarizations. We show that tunable phase resonance and perfect absorption of the incident light are interesting outcomes of this manipulation. In this paper, we demonstrate that fano-like phase resonances which can be observed in CMGs under transverse magnetic polarized incident wave are tuned by changing the Fermi level of graphene. It is shown that while the spectral position of the phase resonances can be shifted up to several gigahertzes, their peak to peak amplitudes are tuned from ~0.9 to ~0.1. On the other hand, we design a graphene-covered CMG, which is able to perfectly absorb both major polarizations of incident wave in two separate bands; hence, providing the opportunity for designing multi-band/wide-band absorbers. We have developed a circuit model for the analysis of the structure. Parameters of the model are derived explicitly and analytically for both major polarizations. Our results are verified through comparison against results of the full-wave simulations.

This paper deals with the intrasystem electromagnetic interference (EMI) in a pacemaker equipped with a wireless power transfer (WPT) charging system. The WPT application to pacemakers is very new, and no results are yet published on possible EMI effects produced by the WPT coil currents in the pacemaker pacing leads. To this aim, an efficient and original co-simulation circuit/field method is proposed to predict the induced voltages on a pacing lead. In the numerical calculation, the pacemaker with WPT secondary coil and a pacing lead is implanted in a sophisticated human body model. The numerical results are validated by measurements showing a good agreement. The proposed approach would be a useful tool for pacemaker EMI compliance tests and safety assessment evaluations.

Timely detection and identification of faults in railway track circuits are crucial for the safety and availability of railway networks. In this paper, the use of the long-short-term memory (LSTM) recurrent neural network is proposed to accomplish these tasks based on the commonly available measurement signals. By considering the signals from multiple track circuits in a geographic area, faults are diagnosed from their spatial and temporal dependences. A generative model is used to show that the LSTM network can learn these dependences directly from the data. The network correctly classifies 99.7% of the test input sequences, with no false positive fault detections. In addition, the t-Distributed Stochastic Neighbor Embedding (t-SNE) method is used to examine the resulting network, further showing that it has learned the relevant dependences in the data. Finally, we compare our LSTM network with a convolutional network trained on the same task. From this comparison, we conclude that the LSTM network architecture is better suited for the railway track circuit fault detection and identification tasks than the convolutional network.

Autonomous systems must be able to adapt to a constantly-changing environment. This adaptability requires significant computational resources devoted to learning, and current artificial systems are lacking in these resources when compared to humans and animals. We aim to produce VLSI spiking neural networks which feature learning structures similar to those in biology, with the goal of achieving the performance and efficiency of natural systems. The neuroscience literature suggests that calcium ions play a key role in explaining long-term synaptic plasticity’s dependence on multiple factors, such as spike timing and stimulus frequency. Here we present a novel VLSI implementation of a calcium-based synaptic plasticity model, comparisons between the model and circuit simulations, and measurements of the fabricated circuit.

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This paper presents the development of a linear dynamic model of a MOS Cross Coupled Charge Pump (CC-CP) suitable for low voltage energy harvesting systems in the form of a Discrete-Time State-Space set of equations considering the resistive behavior of transistor switches. The dynamic model, easily extendable to a CC-CP of an arbitrary number of stages, includes parasitic elements without loss of generality. The validity of the dynamic model is evaluated through the comparison of Matlab simulations of the model to circuit simulations of an ideal CC-CP.

This paper performs a comprehensive nonlinear modeling of a Bulk Acoustic Wave (BAW) duplexer operating at the band 7 of the LTE wireless communication standard. The modeling starts by an accurate characterization of the resonators forming the filters by performing measurements of the second harmonic (H2). The modeling of individual resonators has then been used to predict second order nonlinear manifestations occurring in a real duplexer. These are H2, second order intermodulation products (IMD2), for the case where a jamming signal is set to low frequencies (IMD2-Low) and when the jamming signal is set to high frequencies (IMD2-High). Predicted results are then validated with real measurements. The authors would like to thank Qorvo Inc. for providing the on-wafer measurements that appear in this article. Work supported in part through grants TEC2017-84817-C2-2-R, TEC2017-88343-C4-2-R and 2017 SGR 813

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Stochastic Resonance (SR) is a nonlinear system specific phenomenon, which was demonstrated to lead to system unexpected (counter-intuitive) performance improvements under certain noise conditions. Memristor, on the other hand, is a fundamentally nonlinear circuit element, thus susceptible to benefit from SR, which recently came in the spotlight of the emerging technologies potential candidates. However, at this time, the variability exhibited by manufactured memristor devices within the same array constitutes the main hurdle in the road towards the commercialisation of memristor-based memories and/or computing units. Thus, in this paper, memristor SR effects are explored, assuming various memristor models, and SR-based memristance range enhancement, tolerant to device-to-device variability, is demonstrated. Our experiments reveal that SR can induce significant R MAX /R MIN ratio increase under up to 60% variability, getting as high as 3.4× for 29 dBm noise power.

Antennas are a critical component of an internet of things device and are typically modelled using full-wave electromagnetic (EM) solvers for their optimal design. In this paper, we investigate and compare the impact, accuracy and limitations of three, four and five element equivalent circuit models from the literature to estimate the impedance characteristics of a center-fed linear wire dipole antenna at 2.45 GHz. All the circuit model results are compared against the finite element model. It was found that the three element model is inaccurate in estimating the input impedance of a dipole antenna at the resonant frequency. In comparison to the finite element model, the four element model estimates the input impedance with an error of 3.75 j2.54 Ohms at 2.45 GHz. For the five element model the error−in the input impedance was −6.21+j1.68 Ohms. The input impedance for the both, the four and five element models are in good agreement with the EM model. This approach is shown to enable efficient analysis of antenna impedance for wireless communication systems.

International audience; This paper deals with a new method of metamodel construction for electromagnetic compatibility (EMC) simulation of power electronic converters. The proposed method uses a compressed wavelet coefficients vector of a time-domain signal and a learning method [support vector regression (SVR)]. This can be applied for a black box approach of modeling of complex systems such as power converters. This allows the study of EMC behavior, the impact of the uncertainties and their propagations inside the model or the design of EMC filters.

As research and development of renewable and clean energy based systems is advancing rapidly, the nonlinear source emulator (NSE) is becoming very essential for testing of maximum power point trackers or downstream converters. Renewable and clean energy sources play important roles in both terrestrial and nonterrestrial applications. However, most existing NSEs have only been concerned with simulating energy sources in terrestrial applications, which may not be fast enough for testing of nonterrestrial applications. In this paper, a high-bandwidth NSE is developed that is able to simulate the behaviors of a typical nonlinear source under different critical conditions that can happen during their operations. The proposed 200-W NSE, which consists of a fourth-order output filter buck converter and a novel nonlinear small-signal reference generator, can quickly react not only to an instantaneous change in the input source but also to a load step between nominal and open circuit. Moreover, all of these operation modes have a very fast settling time of only 10 $\mu$ s, which is hundreds of times faster than that of existing works. This attribute allows for higher speed and a more efficient maximum power point tracking algorithm. The proposed NSE, therefore, offers a superior dynamic performance among devices of the same kind.

Gain-cell embedded DRAM (GC-eDRAM) is an interesting alternative to SRAM for reasons such as high density, low bitcell leakage, logic compatibility, and suitability for 2-port memories. The major drawbacks of GC-eDRAMs are their limited data retention times (RTs) and the large spread of RT across an array, which degrade energy-efficiency due to refresh cycles. While the array refresh rate can be determined according to circuit simulation or post-manufacturing calibration, there is a lack of analytical and statistical RT models for GC-eDRAM that could unveil the limiters and circuit parameters that lead to the large observed RT spreads. In this work, we derive the first comprehensive analytical model for the statistical distribution of the per-cell retention time of 2T-bitcell GC-eDRAMs, which is found to follow a log-normal distribution. The accuracy of the proposed retention time model is verified by extensive Monte Carlo and worst case distance circuit simulations and silicon measurements of an 0.18 $\mu{\mathrm{m}}$ test chip. Furthermore, a sensitivity analysis unveils the circuit parameters that have the highest impact on the RT spread. Interestingly, the variability of the threshold voltage of the write access transistor has a much higher impact on the RT spread than the variability of any other circuit parameter, including the storage node capacitor. This holds true under process scaling, for nodes as advanced as 28 nm, as shown through simulation. The insights gained from the retention time model help circuit designers achieve better GC-eDRAMs with longer RTs and sharper RT distributions. In addition, the herein presented model can be used as a basis to study the reliability/energy trade-off for GC-eDRAM usage in fault-tolerant VLSI systems.

International audience; Modern Signal and Power Integrity (SI/PI) verification flows rely on accurate models for complex I/O-buffers that drive and receive electrical signals on high-speed channels. The sheer density of modern integrated circuits makes detailed transistor-level descriptions computationally cumbersome to the point where they become unusable for system-level simulations. Fortunately, transistor-level descriptions may be replaced with more compact representations that approximate the input/output buffers behavior with considerable accuracy while providing a simulation speedup of several orders of magnitude. Known as behavioral models, surrogate models or macromodels, these computationally efficient equivalents have become a de-facto industry standard in SI/PI simulations. This paper presents an overview of the state-of-the-art in I/O-buffer behavioral modeling, introducing the main features of both standard and emerging solutions. Open issues and future research directions are also discussed.

This paper delivers a considerable improvement in the framework of the statistical simulation of highly nonlinear devices via polynomial chaos-based circuit equivalents. Specifically, a far more efficient and "black-box" approach is proposed that reduces the model complexity for nonlinear components. Based on recent literature, the "stochastic testing" method is used in place of a Galerkin approach to find the pertinent circuit equivalents. The technique is demonstrated via the statistical analysis of a low-noise power amplifier and its features in terms of accuracy and efficiency are highlighted.

This paper proposes a simple method to detect and diagnose short circuits and open circuits faults in photovoltaic (PV) systems based on the evaluation of three coefficients. The proposed method consists fundamentally on two steps: an offline step based on a simulated model and an online step in which a comparison of the real measured coefficients against those obtained in the offline step is performed. The simulated model of the PV array has been validated using a real experimental data of a daily profile from a 3 kWp grid connected system installed at Algiers. The effectiveness of the proposed method has been evaluated based on PSIM™/Matlab™ Co-simulation approach of four operating cases: healthy operating case, one short circuit module in a string operating case, five short circuits modules in a string operating case, and finally a completely disconnected string operating case. Simulation results have demonstrated the ability of the proposed method to detect and diagnose short circuits and open circuits faulty operation under any meteorological conditions.

In this paper, a new methodology for designing an electrical machine is proposed. Preliminary physical dimensions for the machine to be designed are obtained with the use of analytical equations. Then, the machine is realized by a Magnetic Equivalent Circuit (MEC) for accurate analysis. Thus, with the aid of MEC, quick convergence to the optimal machine design on different fronts like losses, cost, weight, etc. becomes feasible. Such design procedures are preferred in electric vehicle applications. The MEC topology considered in this work accounts for the saturation of the core material and the movement of rotor. As a result, the solutions obtained would be accurate. Further, with the aid of finite element analysis tool, the machine design can be validated. The proposed methodology is demonstrated for the design of switched reluctance motor., by K. Ragavan, J. Prathamesh and Arava Pavan Kishore