1,721,003 research outputs found
Real Time Li-ion Battery Bank Parameters Estimation for Electric Vehicle Traction System
No full textA Master of Science thesis in Electrical Engineering by Hafiz Muhammad Usman Butt entitled, “Real Time Li-ion Battery Bank Parameters Estimation for Electric Vehicle Traction System”, submitted in May 2019. Thesis advisor is Dr. Shayok Mukhopadhyay and thesis co-advisor is Dr. Habibur Rehman. Soft and hard copy available.This work focuses on accurate and efficient real-time estimation of Li-ion battery model parameters for electric vehicle (EV) traction systems. The contributions made by this thesis are: accurate estimation of Li-ion battery parameters using a two-stage adaptive optimization strategy, which minimizes the need of offline processing, and enables efficient real-time estimation of Li-ion battery model parameters for EV traction systems. In the first part of this thesis, a two-stage universal adaptive stabilizer (UAS) based optimization technique is proposed for estimation of Li-ion battery model parameters. The first stage utilizes a UAS based APE technique to acquire an initial estimate of battery parameters. The second stage utilizes one of the three different optimization techniques, i.e., fmincon, particle swarm optimization (PSO), and hybrid PSO to improve the accuracy of battery model parameters obtained by the APE. The parameters estimated by the APE help in reducing the search space interval required by the optimization technique, thus reducing the computation time for the optimization process. This thesis presents detailed comparison of experimental results using the proposed approach, and other well-known optimization techniques from the literature. In the second part of this thesis, a modification to the existing UAS based APE strategy is proposed. The existing UAS based APE strategy requires a small amount of prior offline experimentation and some post-processing to determine some of the battery parameters. However, the proposed modified APE strategy estimates all battery parameters in a single experimental run. Mathematical proofs, simulation and experimental results supporting the proposed modified APE strategy are also presented. In the third part of this thesis, the modified APE strategy is employed for real-time parameters estimation of a 400 V, 6.6 Ah Li-ion battery bank, which supplies power to a field-oriented control based EV drive system. Some of the distinct features of the modified APE strategy, such as simple real-time implementation, fast convergence, and minimal experimental effort, show the effectiveness of the modified APE strategy developed in this work for real-time Li-ion battery model parameters estimation of EV traction systems.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
The Macroeconomic Determinants and Market Efficiency of Precious Metals: An Empirical Evidence of International Markets
No full textThis empirical study extends market efficiency application to precious metals. Literature suggests that prices of four precious metals (i.e., Gold, Silver, Platinum, and Palladium) fluctuate due to instability of macroeconomic factors globally. Moreover, the impact of macroeconomic factors causes uncertainty in the prices of metals which affects the investors’ return. To test the robustness of the precious metals price efficiency, this thesis is divided into three separate empirical studies that measure market efficiency and analyse the impact of macroeconomic factors on pricing in developed and emerging economies.
Chapter 2 (Paper 1) examines weak-form efficiency in the precious metal market using the Automatic Portmanteau, Automatic Variance Ratio, Autoboot Variance Ratio, and Generalized Spectral Shape tests. The findings demonstrate that market efficiency for four precious metals in developed and emerging economies changes over time. Market efficiency may vary due to technical changes, economic booms and busts. The other reason could be that markets are fragmented due to restrictions, lunar cycles, market complexity, and other challenges.
Chapter 3 (Paper 2) investigates the relationship between macroeconomic
factors and precious metals prices across developed and emerging markets from 1979 to 2020 using multiple time series techniques – Johansen Cointegration, VECM, VAR, ARDL model, and Wald tests. The findings revealed the long-run and short -run relationships between precious metals prices and macroeconomic factors vary depending on the country of the study. In the long run, cointegrating relationships are unstable and differ significantly between developed and emerging economies. The causality test results between four precious metals and major macroeconomic indicators vary depending on the country and the sample length of the frequency distributions used.
Chapter 4 (Paper 3) examined how macroeconomic factors collectively impact gold, silver, and platinum prices in developed and emerging economies using the panel data unit root test and dynamic panel data model. The findings demonstrate that macroeconomic factors affect precious metal prices in developed and emerging economies
Energy Management Strategies for Residential Distribution System Using Smart Meter Data
No full textEnergy management (EM) strategies for a power distribution system have attracted attention in the past few decades. EM within smart residential distribution systems is a long-standing challenge that involves effective scheduling of electric vehicle charging and discharging while utilizing available photovoltaic resources and efficiently drawing power from the electric grid to meet household energy demands. This dissertation introduces four important research problems that provide the power distribution system operator with crucial cybersecurity insights. These insights facilitate real-time monitoring of the Distribution Transformer (DT) kVA load, prediction of its end of remaining-useful life, and disaggregation of behind-the-meter solar generation — all using just smart meter data from residential customers processed at the electric utility’s server.
The first research proposes a novel non-intrusive approach based on the Universal Adaptive Stabilization (UAS) algorithm for real-time assessment of behind-the-meter (BTM) solar generation using smart meter data from residential customers. This approach is characterized by its simplicity, robustness, and unsupervised operation, eliminating the need for complex system dynamics. The accuracy and convergence of the proposed method are mathematically justified and evaluated against advanced algorithms using publicly available datasets.
The second research presents a hardware-free strategy for DT kVA load estimation using smart meter data from residential customers. The proposed DT kVA load estimation algorithm operates at the utility server level without requiring a fixed power factor assumption or reactive power load information across residential customers. The proposed strategy provides a simple, effective fixed-point iteration-based formulation for a balanced secondary distribution network, that is extended for an unbalanced three-phase underground secondary distribution network. Theoretical analysis on convergence and stability
of the proposed DT kVA load estimation method is also provided.
Building up on the second research work, the third research proposes a four-layer framework that utilizes the DT kVA load estimation algorithm for assessing the remaining useful life (RUL) of a DT. The first layer stores residential smart meter data used for DT kVA load estimation in the second layer. In the third layer, two powerful forecasting tools, Time Series Decomposition and Hidden Markov Model, are compared. The historical and forecast data, along with the DT’s thermal parameters, are employed to assess its RUL. Numerical validation is conducted using real-world data from fifteen households in London, Ontario, Canada.
The three aforementioned research problems are seamlessly integrated into the fourth, presenting a fuzzy logic-based real-time energy management control system, from the perspective of an electric utility. The primary objectives of the fourth research work are to utilize available energy resources in a smart residential distribution system, optimize grid power consumption, minimize electricity costs for both the utility and customers, ensure reliable power grid operation, and mitigate DT overloading.
This dissertation aims to propose a fast, efficient, and real-time energy management strategy for smart residential distribution systems. The three integrated research problems offer precise estimation of real-time BTM solar generation, ensuring system reliability while providing accurate DT kVA load estimation to mitigate DT overloading. As a result, the proposed real-time energy management control strategy with its integrated parts makes a valuable contribution to the advancement of smart grid technologies and various distribution automation applications
The Macroeconomic Determinants and Market Efficiency of Precious Metals: An Empirical Evidence of International Markets
Full text linkThis empirical study extends market efficiency application to precious metals. Literature suggests that prices of four precious metals (i.e., Gold, Silver, Platinum, and Palladium) fluctuate due to instability of macroeconomic factors globally. Moreover, the impact of macroeconomic factors causes uncertainty in the prices of metals which affects the investors’ return. To test the robustness of the precious metals price efficiency, this thesis is divided into three separate empirical studies that measure market efficiency and analyse the impact of macroeconomic factors on pricing in developed and emerging economies.
Chapter 2 (Paper 1) examines weak-form efficiency in the precious metal market using the Automatic Portmanteau, Automatic Variance Ratio, Autoboot Variance Ratio, and Generalized Spectral Shape tests. The findings demonstrate that market efficiency for four precious metals in developed and emerging economies changes over time. Market efficiency may vary due to technical changes, economic booms and busts. The other reason could be that markets are fragmented due to restrictions, lunar cycles, market complexity, and other challenges.
Chapter 3 (Paper 2) investigates the relationship between macroeconomic
factors and precious metals prices across developed and emerging markets from 1979 to 2020 using multiple time series techniques – Johansen Cointegration, VECM, VAR, ARDL model, and Wald tests. The findings revealed the long-run and short -run relationships between precious metals prices and macroeconomic factors vary depending on the country of the study. In the long run, cointegrating relationships are unstable and differ significantly between developed and emerging economies. The causality test results between four precious metals and major macroeconomic indicators vary depending on the country and the sample length of the frequency distributions used.
Chapter 4 (Paper 3) examined how macroeconomic factors collectively impact gold, silver, and platinum prices in developed and emerging economies using the panel data unit root test and dynamic panel data model. The findings demonstrate that macroeconomic factors affect precious metal prices in developed and emerging economies
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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