Browsing by Subject "Performance Model"
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Item Open Access State aggregation-based model of asynchronous multi-fiber optical switching with shared wavelength converters(Elsevier, 2013) Akar, N.; Raffaelli, C.; Savi, M.This paper proposes new analytical models to study optical packet switching architectures with multi-fiber interfaces and shared wavelength converters. The multi-fiber extension of the recently proposed Shared-Per-Input-Wavelength (SPIW) scheme is compared against the multi-fiber Shared-Per-Node (SPN) scheme in terms of cost and performance for asynchronous traffic. In addition to using Markov chains and fixed-point iterations for modeling the mono-fiber case, a novel state aggregation technique is proposed to evaluate the packet loss in asynchronous multi-fiber scenario. The accuracy of the performance models is validated by comparison with simulations in a wide variety of scenarios with both balanced and imbalanced input traffic. The proposed analytical models are shown to remarkably capture the actual system behavior in all scenarios we tested. The adoption of multi-fiber interfaces is shown to achieve remarkable savings in the number of wavelength converters employed and their range. In addition, the SPIW solution allows to save, in particular conditions, a significant number of optical gates compared to the SPN solution. Indeed, SPIW allows, if properly dimensioned, potential complexity and cost reduction compared to SPN, while providing similar performance.Item Open Access Zero-free-parameter modeling approach to predict the voltage of batteries of different chemistries and supercapacitors under arbitrary load(Electrochemical Society, Inc., 2017) Özdemir, E.; Uzundal, C. B.; Ulgut, B.Performance modeling of electrochemical energy storage systems is gathering increasingly higher attention in recent years. With the ever increasing power demand of mobile applications, predicting voltage behavior under different load profiles is of utmost importance for communications, automotive and consumer electronics. The ideal modelling approach needs not only to accurately predict the response of the battery, but also be robust, easy to implement and have low computational complexity. We will present a new algorithm that is algebraically straightforward, that has no adjustable parameters and that can accurately predict the voltage response of batteries and supercapacitors. The approach works well in a variety of discharge profiles ranging from simple long DC discharge/charge profiles to pulse schemes based on drive schedules published by regulatory bodies. Our approach is based on Electrochemical Impedance Spectroscopy measurements done on the system to be predicted. The spectrum is used in the frequency domain without any further processing to predict the fast moving portion of the voltage in the frequency domain. DC response is added in through a straightforward lookup table. This widely applicable approach can predict the voltage of with less than 1% error, without any adjustable parameters to a large variety of discharge profiles.