Appendix a TABLES of FILTER FUNCTIONS
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The Effects of High Frequency Current Ripple on Electric Vehicle Battery Performance
Original citation: Uddin, Kotub , Moore, Andrew D. , Barai, Anup and Marco, James. (2016) The effects of high frequency current ripple on electric vehicle battery performance. Applied Energy, 178 . pp. 142-154. Permanent WRAP URL: http://wrap.warwick.ac.uk/80006 Copyright and reuse: The Warwick Research Archive Portal (WRAP) makes this work of researchers of the University of Warwick available open access under the following conditions. This article is made available under the Creative Commons Attribution 4.0 International license (CC BY 4.0) and may be reused according to the conditions of the license. For more details see: http://creativecommons.org/licenses/by/4.0/ A note on versions: The version presented in WRAP is the published version, or, version of record, and may be cited as it appears here. For more information, please contact the WRAP Team at: [email protected] warwick.ac.uk/lib-publications Applied Energy 178 (2016) 142–154 Contents lists available at ScienceDirect Applied Energy journal homepage: www.elsevier.com/locate/apenergy The effects of high frequency current ripple on electric vehicle battery performance ⇑ Kotub Uddin , Andrew D. Moore, Anup Barai, James Marco WMG, International Digital Laboratory, The University of Warwick, Coventry CV4 7AL, UK highlights Experimental study into the impact of current ripple on li-ion battery degradation. 15 cells exercised with 1200 cycles coupled AC–DC signals, at 5 frequencies. Results highlight a greater spread of degradation for cells exposed to AC excitation. Implications for BMS control, thermal management and system integration. article info abstract Article history: The power electronic subsystems within electric vehicle (EV) powertrains are required to manage both Received 8 April 2016 the energy flows within the vehicle and the delivery of torque by the electrical machine. -
Emotion Perception and Recognition: an Exploration of Cultural Differences and Similarities
Emotion Perception and Recognition: An Exploration of Cultural Differences and Similarities Vladimir Kurbalija Department of Mathematics and Informatics, Faculty of Sciences, University of Novi Sad Trg Dositeja Obradovića 4, 21000 Novi Sad, Serbia +381 21 4852877, [email protected] Mirjana Ivanović Department of Mathematics and Informatics, Faculty of Sciences, University of Novi Sad Trg Dositeja Obradovića 4, 21000 Novi Sad, Serbia +381 21 4852877, [email protected] Miloš Radovanović Department of Mathematics and Informatics, Faculty of Sciences, University of Novi Sad Trg Dositeja Obradovića 4, 21000 Novi Sad, Serbia +381 21 4852877, [email protected] Zoltan Geler Department of Media Studies, Faculty of Philosophy, University of Novi Sad dr Zorana Đinđića 2, 21000 Novi Sad, Serbia +381 21 4853918, [email protected] Weihui Dai School of Management, Fudan University Shanghai 200433, China [email protected] Weidong Zhao School of Software, Fudan University Shanghai 200433, China [email protected] Corresponding author: Vladimir Kurbalija, tel. +381 64 1810104 ABSTRACT The electroencephalogram (EEG) is a powerful method for investigation of different cognitive processes. Recently, EEG analysis became very popular and important, with classification of these signals standing out as one of the mostly used methodologies. Emotion recognition is one of the most challenging tasks in EEG analysis since not much is known about the representation of different emotions in EEG signals. In addition, inducing of desired emotion is by itself difficult, since various individuals react differently to external stimuli (audio, video, etc.). In this article, we explore the task of emotion recognition from EEG signals using distance-based time-series classification techniques, involving different individuals exposed to audio stimuli. -
Switching-Ripple-Based Current Sharing for Paralleled Power Converters
Switching-ripple-based current sharing for paralleled power converters The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Perreault, D.J., K. Sato, R.L. Selders, and J.G. Kassakian. “Switching-Ripple-Based Current Sharing for Paralleled Power Converters.” IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications 46, no. 10 (1999): 1264–1274. © 1999 IEEE As Published http://dx.doi.org/10.1109/81.795839 Publisher Institute of Electrical and Electronics Engineers (IEEE) Version Final published version Citable link http://hdl.handle.net/1721.1/86985 Terms of Use Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. 1264 IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS—I: FUNDAMENTAL THEORY AND APPLICATIONS, VOL. 46, NO. 10, OCTOBER 1999 Switching-Ripple-Based Current Sharing for Paralleled Power Converters David J. Perreault, Member, IEEE, Kenji Sato, Member, IEEE, Robert L. Selders, Jr., and John G. Kassakian, Fellow, IEEE Abstract— This paper presents the implementation and ex- perimental evaluation of a new current-sharing technique for paralleled power converters. This technique uses information naturally encoded in the switching ripple to achieve current sharing and requires no intercell connections for communicating this information. Practical implementation of the approach is addressed and an experimental evaluation, based on a three-cell prototype system, is also presented. It is shown that accurate and stable load sharing is obtained over a wide load range. Finally, an alternate implementation of this current-sharing technique is described and evaluated. -
Output Ripple Voltage for Buck Switching Regulator (Rev. A)
Application Report SLVA630A–January 2014–Revised October 2014 Output Ripple Voltage for Buck Switching Regulator Surinder P. Singh, Ph.D., Manager, Power Applications Group............................. WEBENCH® Design Center ABSTRACT Switched-mode power supplies (SMPSs) are used to regulate voltage to a certain level. SMPSs have an inherent switching action, which causes the currents and voltages in the circuit to switch and fluctuate. The output voltage also has ripple on top of the regulated steady-state DC value. Designers of power systems consider the output voltage ripple to be both a key parameter for design considerations and a key figure of merit. The online WEBENCH® Power Designer recognizes the key importance of peak-to-peak voltage output ripple voltage—the ripple voltage is calculated and reported in the visualizer [1]. This application report presents a closed-form analytical formulation for the output voltage ripple waveform and the peak-to-peak ripple voltage. This formulation is accurate over all regions of operation and harmonizes the peak-to-peak ripple voltage calculation over all regions of operation. The new analytical formulation presented in this application report gives an accurate evaluation of the output ripple as compared to the simplified linear or root-mean square (RMS) approximations often used. In this application report, the analytical model for output voltage waveform and peak-to-peak ripple voltage for buck is derived. This model is validated against SPICE TINA-TI simulations. This report presents the behavior of ripple peak-to-voltage for various input conditions and choices of output capacitor and compare it against SPICE TINA-TI results. -
T/HIS 15.0 User Manual
For help and support from Oasys Ltd please contact: UK The Arup Campus Blythe Valley Park Solihull B90 8AE United Kingdom Tel: +44 121 213 3399 Email: [email protected] China Arup 39/F-41/F Huaihai Plaza 1045 Huaihai Road (M) Xuhui District Shanghai 200031 China Tel: +86 21 3118 8875 Email: [email protected] India Arup Ananth Info Park Hi-Tec City Madhapur Phase-II Hyderabad 500 081, Telangana India Tel: +91 40 44369797 / 98 Email: [email protected] Web:www.arup.com/dyna or contact your local Oasys Ltd distributor. LS-DYNA, LS-OPT and LS-PrePost are registered trademarks of Livermore Software Technology Corporation User manual Version 15.0, May 2018 T/HIS 0 Preamble 0.1 Text conventions used in this manual 0.1 1 Introduction 1.1 1.1 Program Limits 1.1 1.2 Running T/HIS 1.2 1.3 Command Line Options 1.4 2 Using Screen Menus 2.1 2.1 Basic screen menu layout 2.1 2.2 Mouse and keyboard usage for screen-menu interface 2.2 2.3 Dialogue input in the screen menu interface 2.4 2.4 Window management in the screen interface 2.4 2.5 Dynamic Viewing (Using the mouse to change views). 2.5 2.6 "Tool Bar" Options 2.6 3 Graphs and Pages 3.1 3.1 Creating Graphs 3.1 3.2 Page Size 3.2 3.3 Page Layouts 3.2 3.3.1 Automatic Page Layout 3.2 3.4 Pages 3.6 3.5 Active Graphs 3.6 4 Global Commands and Pages 4.1 4.1 Page Number 4.1 4.2 PLOT (PL) 4.1 4.3 POINT (PT) 4.2 4.4 CLEAR (CL) 4.2 4.5 ZOOM (ZM) 4.2 4.6 AUTOSCALE (AU) 4.2 4.7 CENTRE (CE) 4.2 4.8 MANUAL 4.2 4.9 STOP 4.2 4.10 TIDY 4.2 4.11 Additional Commands 4.3 5 Main Menu 5.1 5.0 Selecting Curves -
Classic Filters There Are 4 Classic Analogue Filter Types: Butterworth, Chebyshev, Elliptic and Bessel. There Is No Ideal Filter
Classic Filters There are 4 classic analogue filter types: Butterworth, Chebyshev, Elliptic and Bessel. There is no ideal filter; each filter is good in some areas but poor in others. • Butterworth: Flattest pass-band but a poor roll-off rate. • Chebyshev: Some pass-band ripple but a better (steeper) roll-off rate. • Elliptic: Some pass- and stop-band ripple but with the steepest roll-off rate. • Bessel: Worst roll-off rate of all four filters but the best phase response. Filters with a poor phase response will react poorly to a change in signal level. Butterworth The first, and probably best-known filter approximation is the Butterworth or maximally-flat response. It exhibits a nearly flat passband with no ripple. The rolloff is smooth and monotonic, with a low-pass or high- pass rolloff rate of 20 dB/decade (6 dB/octave) for every pole. Thus, a 5th-order Butterworth low-pass filter would have an attenuation rate of 100 dB for every factor of ten increase in frequency beyond the cutoff frequency. It has a reasonably good phase response. Figure 1 Butterworth Filter Chebyshev The Chebyshev response is a mathematical strategy for achieving a faster roll-off by allowing ripple in the frequency response. As the ripple increases (bad), the roll-off becomes sharper (good). The Chebyshev response is an optimal trade-off between these two parameters. Chebyshev filters where the ripple is only allowed in the passband are called type 1 filters. Chebyshev filters that have ripple only in the stopband are called type 2 filters , but are are seldom used. -
Reducing Output Ripple and Noise Using the LMZ34002
Application Report SNVA698–September 2013 Reducing Output Ripple and Noise using the LMZ34002 Jason Arrigo ...................................................................................................... SVA - Simple Switcher ABSTRACT Analog circuits that need a negative output voltage, such as high-speed data converters, power amplifiers, and sensors are sensitive to noise. This application report examines different techniques to minimize the output ripple and noise with the LMZ34002 negative output voltage power module. Other modules in the LMZ3 family can also implement these noise-reducing techniques, such as adding additional output capacitance, a pi-filter, or a low noise low drop-out regulator. Contents 1 Introduction .................................................................................................................. 2 2 LMZ34002 with Standard Filtering ........................................................................................ 2 3 LMZ34002 with Additional Ceramic Output Capacitance .............................................................. 3 4 LMZ34002 Filtering for Noise Sensitive Applications .................................................................. 4 5 Summary ..................................................................................................................... 6 List of Figures 1 Diagram of the LMZ34002 with Standard Filtering ..................................................................... 2 2 Output Ripple Waveform with Standard Filtering ...................................................................... -
Aluminum Electrolytic Capacitors Power Application Capabilities
VISHAY INTERTECHNOLOGY, INC. aluMinuM electrolYtic capacitors Power Application Capabilities Aluminum Electrolytic Capacitors in Power Applications POWER APPLICATIONS • Motor Drives • Solar Inverters • Traction in trains or rolling stock • Uninterruptible Power Supply (UPS) • Pulsed Power RESOURCES • For technical questions contact [email protected] • Sales Contacts: http://www.vishay.com/doc?99914 A WORLD OF SOLUTIONS CAPABILITIES 1/11 VMN-PL0453-1610 THIS DOCUMENT IS SUBJECT TO CHANGE WITHOUT NOTICE. THE PRODUCTS DESCRIBED HEREIN AND THIS DOCUMENT ARE SUBJECT TO SPECIFIC DISCLAIMERS, SET FORTH AT www.vishay.com/doc?91000 www.vishay.com VISHAY INTERTECHNOLOGY, INC. aluMinuM electrolYtic capacitors for Motor Drives Introduction to the Application Motor drives are used to control the speed of various motors in all kinds of systems, from the small pumps and motors in household washing machines and central heating and air-conditioning systems to the large motors found in industrial machinery. Selecting the Best Capacitor for Your Motor Drive Application Aluminum capacitors are often used as DC link capacitors in motor drives, both in 1-phase and 3-phase designs. The aluminum capacitor is used as an energy buffer to ensure stable operation of the switch mode inverter driving the motor. The aluminum capacitor also functions as a filter to prevent high-frequency components from the switch mode inverter from polluting the mains voltage. The key selection criterion for the aluminum capacitor is the required ripple current. The ripple current consists of two components, a low-frequency ripple (50 Hz to 200 Hz) from the input and a high-frequency component from the inverter, typically 8 kHz to 20 kHz. -
Measuring and Understanding the Output Voltage Ripple of a Boost Converter
www.ti.com Table of Contents Application Report Measuring and Understanding the Output Voltage Ripple of a Boost Converter Jasper Li ABSTRACT The output ripple waveform of a boost converter is normally larger than the calculation result because of the voltage spike. Such behavior is related to the measurement method, the operating principle and the non-ideal characteristics of the boost circuit. The application note analyzes the root cause of the spike in the output ripple and proposes a simple solutions to solve the problem. Table of Contents 1 Introduction.............................................................................................................................................................................2 2 Observation in Bench Test.....................................................................................................................................................3 3 Root Cause Analysis.............................................................................................................................................................. 5 4 A Simple Solution................................................................................................................................................................... 8 5 Summary............................................................................................................................................................................... 10 List of Figures Figure 1-1. Simplified Schematic of TPS61022.......................................................................................................................... -
Comparison of a Low-Frequency Butterworth Filter with a Symmetric SE-Filter
Comparison of a low-frequency Butterworth filter with a symmetric SE-filter K S Medvedeva1 1Saratov State University, Astrakhanskaya Street 83, Saratov, Russia, 410012 Abstract. The article compares two filters: a Butterworth filter and an asymmetric SE- filter.The experimental studydetermines their advantages and disadvantages.Also,experiments based on the peak signal-to-noise ratio(PSNR) metricshowvisual evaluation. The results of experimentsshow that a symmetric filter better restores images usinga small set of continuous function parametersthatare distorted by a low-frequency Gaussian filter. 1. Introduction Due to the imperfection of forming and recording systems, images recorded by systemsare distorted (fuzzy) copiesof the original images. The main causes of distortions that resultindegradation of clarity includethe limited resolution of the forming system, refocusing, the presence of a distorting medium (for example, the atmosphere), and movement of the camera on the object being registered. Eliminating or reducing distortion for clarity is the task of image recovery. Automatic control systems, measuring equipment, signal processing systems, and various filters with different characteristics are used to filter signalsin telecommunications. Depending on the frequency band associated with the bandwidth and the suppression band, there are odd, band, high- frequency, and low-frequency filters. Also, all-pass filters have a constant amplitude-frequency response in the required frequency range, and their phase-frequency response is a given frequency function [1]. The simplest way to restoreimage clarity is to process the observed image in the spatial frequency domain with an inverse filter [2].The drawbacks of this filter are the occurrence of edge effects, which take the form of an oscillating hindrance of high power that completely masksthe reconstructed image. -
Introduction to Signals & Systems
A very Brief Introduction to Signals & Systems Outline • Signals & Systems • Continuous and discrete time signals • Properties of Systems • Input- Output relation : Convolution • Frequency domain representation of signals & systems • Analog to digital Conversion • Sampling – Nyquist Sampling Theorem • Basic Filter Theory • Types of filters • Designing practical filters in Labview and Matlab • What is a signal? – A signal is a function defined on the continuum of time values • What is a system ? – a system is a black box that “takes in” one or more input signals and “produces” one or more output signals Continuous time Vs Discrete time Signals • Most of the modern day systems are discrete time systems. E.g., A computer. • A computer can’t directly process a continuous time signal but instead it needs a stream of numbers, which is a discrete time signal. • Discrete time signals are obtain by sampling the continuous time signals • How fast should we sample the signal? Examples • Signals – Unit Step function – Continuous time impulse function – Discrete time • Systems – A simple circuit Basic System Properties • Linearity – System is linear if the principle of superposition holds • Time- Invariance – The system does not change with time Convolution • Linear & Time invariant (LTI) sytems are characterized by their impulse response • Impulse response is the output of the system when the input to the system is an impulse function • For Continuous time signals • For Discrete time signals Frequency domain representation of signals • In most of -
Filters Matthew Spencer Harvey Mudd College E157 – Radio Frequency Circuit Design
Department of Engineering Lecture 09: Filters Matthew Spencer Harvey Mudd College E157 – Radio Frequency Circuit Design 1 1 Department of Engineering Filter Specifications and the Filter Prototype Function Matthew Spencer Harvey Mudd College E157 – Radio Frequency Circuit Design 2 In this video we’re going to start talking about filters by defining a language that we use to describe them. 2 Department of Engineering Filters are Like Extended Matching Networks Vout Vout Vout + + + Vin Vin Vin - - - Absorbs power Absorbs power at one Absorbs power at one ω ω, but can pick Q in a range of ω 푉 푗휔 퐻 푗휔 = 푉 푗휔 ω ω ω 3 Filters are a natural follow on after talking about matching networks because you can think of them as an extension of the same idea. We showed that an L-match lets us absorb energy at one frequency (which is resonance) and reflect it at every other frequency, so we could think of an L match as a type of filter. That’s particularly obvious if we define a transfer function across an L match network from Vin to Vout, which would look like a narrow resonant peak. Adding more components in a pi match allowed us to control the shape of that peak and smear it out over more frequencies. So it stands to reason that by adding even more components to our matching network, we could control whether a signal is passed or reflected over a wider frequency. That turns out to be true, and the type of circuit that achieves this frequency response is referred to as an LC ladder filter.