SIMPLIS efficiency model for a synchronous multiphase buck converter

In this master’s thesis, an efficiency model was developed for the synchronous multiphase buck converters of the TPS6594x-Q1 integrated circuit using SIMPLIS simulator. The model includes internal losses occurring in power stage transistors, power stage drivers and bondwires. Modeled external losses include printed circuit board resistance and inductance, inductor direct and alternating current characteristics as well as capacitor nonidealities. Internal loss modeling was mostly based on Cadence simulations. Power stage transistors especially were thoroughly modeled. The capacitances of the power stage transistors were extracted by integrating gate and drain currents during the transistor on and off transitions. Charging of the parasitic capacitances followed the theory in turn-off and turn-on transitions and therefore the capacitance extraction was fairly simple. Nonlinearities of the parasitic capacitors were modeled in SIMPLIS with multiple linear approximations. Transistor gate drivers were very rough approximations of the real drivers but good enough for the simulation model. Drivers were modeled to match the gate currents simulated in Cadence, which were then combined the accurate switching transistor models in order to accurately model the switching characteristics. External loss models were based on measurements and simulations. Printed circuit board losses were based on Ansys simulations in which the printed circuit board inductances and resistances were solved from the geometry of the printed circuit board. Inductors were modeled to match the datasheet impedance and resistance graphs and the model was verified against the measurements done in the laboratory. An automated measurement testbench was done for the inductor measurements using LabVIEW and the results were parsed using Matlab. A ladder topology with resistances and inductances was used in the final inductor model to model the frequency characteristics of the inductor. The effect of direct current on inductance was also investigated but the inductance reduction did not have any significant impact on efficiency. Other external components such as capacitors also cause some external losses and they were modeled based on the capacitor datasheets. The simulation model was compared against single- and two-phase efficiency measurements with multiple different input and output voltages which were chosen to match the most common use cases. Efficiency curves were drawn for each configuration using the implemented simulation model and over 300 different comparison points were compared in total. A post processing script that was launched after a simulation completes had to be written with the programming language SIMPLIS supports to draw the efficiency graph from the simulated data. Using the script allowed to run the efficiency simulation without any additional licenses other than the SIMPLIS license. The final model achieved an average error of under 1 % between all the measured and simulated efficiency curves. The most accurate results were obtained with lower switching frequency and larger inductance. Apart from accuracy, the simulator had to be practical and therefore the simulation time had to be considered. Simulation time was attempted to be kept at minimum by simplifying the schematic in as many ways as possible without losing accuracy. For example, reducing the point of the linear approximations in the power stage transistors from 79 points to 17 points saved nearly 50 seconds in single-phase simulations without significant changes in simulation accuracy

18th IEEE Workshop on Nonlinear Dynamics of Electronic Systems: Proceedings

Proceedings of the 18th IEEE Workshop on Nonlinear Dynamics of Electronic Systems, which took place in Dresden, Germany, 26 – 28 May 2010.:Welcome Address ........................ Page I Table of Contents ........................ Page III Symposium Committees .............. Page IV Special Thanks ............................. Page V Conference program (incl. page numbers of papers) ................... Page VI Conference papers Invited talks ................................ Page 1 Regular Papers ........................... Page 14 Wednesday, May 26th, 2010 ......... Page 15 Thursday, May 27th, 2010 .......... Page 110 Friday, May 28th, 2010 ............... Page 210 Author index ............................... Page XII

Modeling and simulation of magnetic components in electric circuits

This thesis demonstrates how by using a variety of model constructions and parameter extraction techniques, a range of magnetic component models can be developed for a wide range of application areas, with different levels of accuracy appropriate for the simulation required. Novel parameter extraction and model optimization methods are developed, including the innovative use of Genetic Algorithms and Metrics, to ensure the accuracy of the material models used. Multiple domain modeling, including the magnetic, thermal and magnetic aspects are applied in integrated simulations to ensure correct and complete dynamic behaviour under a range of environmental conditions. Improvements to the original Jiles-Atherton theory to more accurately model loop closure and dynamic thermal behaviour are proposed, developed and tested against measured results. Magnetic Component modeling techniques are reviewed and applied in practical examples to evaluate the effectiveness of lumped models, 1D and 2D Finite Element Analysis models and coupling Finite Element Analysis with Circuit Simulation. An original approach, linking SPICE with a Finite Element Analysis solver is presented and evaluated. Practical test cases illustrate the effectiveness of the models used in a variety of contexts. A Passive Fault Current Limiter (FCL) was investigated using a saturable inductor with a magnet offset, and the comparison between measured and simulated results allows accurate prediction of the behaviour of the device. A series of broadband hybrid transformers for ADSL were built, tested, modeled and simulated. Results show clearly how the Total Harmonic Distortion (THD), Inter Modulation Distortion (IMD) and Insertion Loss (IL) can be accurately predicted using simulation.A new implementation of ADSL transformers using a planar magnetic structure is presented, with results presented that compare favourably with current wire wound techniques. The inclusion of transformer models in complete ADSL hybrid simulations demonstrate the effectiveness of the models in the context of a complete electrical system in predicting the overall circuit performance

Design of robust ultra-low power platform for in-silicon machine learning

The rapid development of machine learning plays a key role in enabling next generation computing systems with enhanced intelligence. Present day machine learning systems adopt an "intelligence in the cloud" paradigm, resulting in heavy energy cost despite state-of-the-art performance. It is therefore of great interest to design embedded ultra-low power (ULP) platforms with in-silicon machine learning capability. A self-contained ULP platform consists of the energy delivery, sensing and information processing subsystems. This dissertation proposes techniques to design and optimize the ULP platform for in-silicon machine learning by exploring a trade-off that exists between energy-efficiency and robustness. This trade-off arises when the information processing functionality is integrated into the energy delivery, sensing, or emerging stochastic fabrics (e.g., CMOS operating in near-threshold voltage or voltage overscaling, and beyond CMOS devices). This dissertation presents the Compute VRM (C-VRM) to embed the information processing into the energy delivery subsystem. The C-VRM employs multiple voltage domain stacking and core swapping to achieve high total system energy efficiency in near/sub-threshold region. A prototype IC of the C-VRM is implemented in a 1.2 V, 130 nm CMOS process. Measured results indicate that the C-VRM has up to 44.8% savings in system-level energy per operation compared to the conventional system, and an efficiency ranging from 79% to 83% over an output voltage range of 0.52 V to 0.6 V. This dissertation further proposes the Compute Sensor approach to embed information processing into the sensing subsystem. The Compute Sensor eliminates both the traditional sensor-processor interface, and the high-SNR/high-energy digital processing by moving feature extraction and classification functions into the analog domain. Simulation results in 65 nm CMOS show that the proposed Compute Sensor can achieve a detection accuracy greater than 94.7% using the Caltech101 dataset, which is within 0.5% of that achieved by an ideal digital implementation. The performance is achieved with 7x to 17x lower energy than the conventional architecture for the same level of accuracy. To further explore the energy-efficiency vs. robustness trade-off, this dissertation explores the use of highly energy efficient but unreliable stochastic fabrics to implement in-silicon machine learning kernels. In order to perform reliable computation on the stochastic fabrics, this dissertation proposes to employ statistical error compensation (SEC) as an effective error compensation technique. This dissertation makes a contribution to the portfolio of SEC by proposing embedded algorithmic noise tolerance (E-ANT) for low overhead error compensation. E-ANT operates by reusing part of the main block as estimator and thus embedding the estimator into the main block. System level simulation results in a commercial 45 nm CMOS process show that E-ANT achieves up to 38% error tolerance and up to 51% energy savings compared with an uncompensated system. This dissertation makes a contribution to the theoretical understanding of stochastic fabrics by proposing a class of probabilistic error models that can accurately model the hardware errors on the stochastic fabrics. The models are validated in a commercial 45 nm CMOS process and employed to evaluate the performance of machine learning kernels in the presence of hardware errors. Performance prediction of a support vector machine (SVM) based classifier using these models indicates that the probability of detection P_{det} estimated using the proposed model is within 3% for timing errors due to voltage overscaling when the error rate p_η ≤ 80%, within 5% for timing errors due to process variation in near threshold-voltage (NTV) region (0.3 V-0.7 V) and within 2% for defect errors when the defect rate p_{saf} is between 10^{-3} and 20%, compared with HDL simulation results. Employing the proposed error model and evaluation methodology, this dissertation explores the use of distributed machine learning architectures, named classifier ensemble, to enhance the robustness of in-silicon machine learning kernels. Comparative study of distributed architectures (i.e., random forest (RF)) and centralized architectures (i.e., SVM) is performed in a commercial 45 nm CMOS process. Employing the UCI machine learning repository as input, it is determined that RF-based architectures are significantly more robust than SVM architectures in presence of timing errors in the NTV region (0.3 V- 0.7 V). Additionally, an error weighted voting technique that incorporates the timing error statistics of the NTV circuit fabric is proposed to further enhance the robustness of RF architectures. Simulation results confirm that the error weighted voting technique achieves a P_{det} that varies by only 1.4%, which is 12x lower compared to centralized architectures

Error modeling, self-calibration and design of pipelined analog to digital converters

Typescript (photocopy).As the field of signal processing accelerates toward the use of high performance digital techniques, there is a growing need for increasingly fast and accurate analog to digital converters. Three highly visible examples of this trend originated in the last decade. The advent of the compact disc revolutionized the way high-fidelity audio is stored, reproduced, recorded and processed. Digital communication links, fiber optic cables and in the near future ISDN networks (Integrated Services Digital Network) are steadily replacing major portions of telephone systems. Finally, video-conferencing, multi-media computing and currently emerging high definition television (HDTV) systems rely more and more on real-time digital data compression and image enhancing techniques. All these applications rely on analog to digital conversion. In the field of digital audio, the required conversion accuracy is high, but the conversion speed limited (16 bits, 2 x 20 kHz signal bandwidth). In the field of image processing, the required accuracy is less, but the data conversion speed high (8-10 bits, 5-20MHz bandwidth). New applications keep pushing for increasing conversion rates and simultaneously higher accuracies. This dissertation discusses new analog to digital converter architectures that could accomplish this. As a consequence of the trend towards digital processing, prominent analog designers throughout the world have engaged in very active research on the topic of data conversion. Unfortunately, literature has not always kept up. At the time of this writing, it seemed rather difficult to find detailed fundamental publications about analog to digital converter design. This dissertation represents a modest attempt to remedy this situation. It is hoped that anyone with a back-ground in analog design could go through this work and pick up the fundamentals of converter operation, as well as a number of more advanced design techniques

Cutting Edge Nanotechnology

The main purpose of this book is to describe important issues in various types of devices ranging from conventional transistors (opening chapters of the book) to molecular electronic devices whose fabrication and operation is discussed in the last few chapters of the book. As such, this book can serve as a guide for identifications of important areas of research in micro, nano and molecular electronics. We deeply acknowledge valuable contributions that each of the authors made in writing these excellent chapters

Engineering Education and Research Using MATLAB

MATLAB is a software package used primarily in the field of engineering for signal processing, numerical data analysis, modeling, programming, simulation, and computer graphic visualization. In the last few years, it has become widely accepted as an efficient tool, and, therefore, its use has significantly increased in scientific communities and academic institutions. This book consists of 20 chapters presenting research works using MATLAB tools. Chapters include techniques for programming and developing Graphical User Interfaces (GUIs), dynamic systems, electric machines, signal and image processing, power electronics, mixed signal circuits, genetic programming, digital watermarking, control systems, time-series regression modeling, and artificial neural networks

Analysis and modeling methods for predicting functional robustness of integrated circuits during fast transient events

La miniaturisation des circuits intégrés se poursuit de nos jours avec le développement de technologies toujours plus fines et denses. Elle permet une intégration des circuits toujours plus massive, avec des performances plus élevées et une réduction des coûts de production. La réduction de taille des circuits s'accompagne aussi d'une augmentation de leur sensibilité électrique. L'électronique automobile est un acteur majeur dans la nouvelle tendance des véhicules autonomes. Ce type d'application a besoin d'analyser des données et d'appliquer des actions sur le véhicule en temps réel. L'objectif à terme est d'améliorer la sécurité des usagers. Il est donc vital de garantir que ces modules électroniques pourront effectuer leurs tâches correctement malgré toutes les perturbations auxquelles ils seront exposés. Néanmoins, l'environnement automobile est particulièrement sévère pour l'électronique. Parmi tous les stress rencontrés, les décharges électrostatiques (ESD - Electrostatic Discharge) sont une importante source d'agression électrique. Ce type d'évènement très bref est suffisamment violent pour détruire des composants électroniques ou les perturber pendant leur fonctionnement. Les recherches présentées ici se concentrent sur l'analyse des défaillances fonctionnelles. À cause des ESD, des fonctions électroniques peuvent cesser temporairement d'être opérantes. Des méthodes d'analyse et de prédiction sont requises au niveau-circuit intégré afin de détecter des points de faiblesses susceptibles de générer des fautes fonctionnelles pendant l'exposition à un stress électrostatique. Différentes approches ont été proposées dans ce but. Une méthode hiérarchique de modélisation a été mise au point afin d'être capable de reproduire la forme d'onde ESD jusqu'à l'entrée du circuit intégré. Avec cette approche, chaque élément du système est modélisé individuellement puis son modèle ajouté au schéma complet. Un cas d'étude réaliste de défaillance fonctionnelle d'un circuit intégré a été analysé à l'aide d'outils de simulation. Afin d'obtenir plus de données sur cette faute, une puce de test a été développée, contenant des structures de surveillance et de mesure directement intégrées dans la puce. La dernière partie de ce travail de recherche est concentrée sur le développement de méthodes d'analyse dans le but d'identifier efficacement des fautes par simulation. Une des techniques développées consiste à modéliser chaque bloc d'une fonction individuellement puis permet de chaîner ces modèles afin de déterminer la robustesse de la fonction complète. La deuxième méthode tente de construire un modèle équivalent dit boite-noire d'une fonction de haut-niveau d'un circuit intégré. Ces travaux de recherche ont mené à la mise au point de prototypes matériels et logiciels et à la mise en évidence de points bloquants qui pourront constituer une base pour de futurs travaux.Miniaturization of electronic circuits continues nowadays with the more recent technology nodes being applied to diverse fields of application such as automotive. Very dense and small integrated circuits are interesting for economic reasons, because they are cheaper to manufacture in mass and can pack more functionalities with elevated performances. The counterpart of size reduction is integrated circuits becoming more fragile electrically. In the automotive world, the new trend of fully autonomous driving is seeing tremendous progress recently. Autonomous vehicles must take decisions and perform critical actions such as braking or steering the wheel. Those decisions are taken by electronic modules, that have now very high responsibilities with regards of our safety. It is important to ensure that those modules will operate no matter the kind of disturbances they can be exposed to. The automotive world is a quite harsh environment for electronic systems. A major source of electrical stress is called the Electrostatic Discharge (ESD). It is a very sudden flow of electricity of large amplitude capable of destroying electronic components, or disturb them during their normal operation. This research focuses on functional failures where functionality can be temporarily lost after an ESD with various impact on the vehicle. To guarantee before manufacturing that a module and its components will perform their duty correctly, new analysis and prediction methods are required against soft-failures caused by electrostatic discharges. In this research, different approaches have been explored and proposed towards that goal. First, a modelling method for reproducing the ESD waveforms from the test generator up to the integrated circuit input is presented. It is based on a hierarchical approach where each element of the system is modelled individually, then added to the complete setup model. A practical case of functional failure at silicon-level is analyzed using simulation tools. To acquire more data on this fault, a testchip has been designed. It contains on-chip monitoring structures to measure voltage and current, and monitor function behavior directly at silicon-level. The last part of this research details different analysis methods developed for identifying efficiently functional weaknesses. The methods rely heavily on simulation tools, and prototypes have been implemented to prove the initial concepts. The first method models each function inside the chip individually, using behavioral models, then enables to connect the models together to deduce the full function's robustness. It enables hierarchical analysis of complex integrated circuit designs, to identify potential weak spots inside the circuit that could require more shielding or protection. The second method is focused on constructing equivalent electrical black box models of integrated circuit functions. The goal is to model the IC with a behavioral, black-box model capable of reproducing waveforms in powered conditions during the ESD. In summary, this research work has led to the development of several hardware and software prototypes. It has also highlighted important modelling challenges to solve in future works to achieve better functional robustness against electrostatic discharges