Open Access. Powered by Scholars. Published by Universities.®

Operations Research, Systems Engineering and Industrial Engineering Commons™

Open Access. Powered by Scholars. Published by Universities.®

Electrical and Computer Engineering

Series

2017

Articles 1 - 6 of 6

Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering

Application Of Real Field Connected Vehicle Data For Aggressive Driving Identification On Horizontal Curves, Arash Jahangiri, Vincent Berardi, Sahar Ghanipoor Machiani Dec 2017

Application Of Real Field Connected Vehicle Data For Aggressive Driving Identification On Horizontal Curves, Arash Jahangiri, Vincent Berardi, Sahar Ghanipoor Machiani

Psychology Faculty Articles and Research

The emerging technology of connected vehicles generates a vast amount of data that could be used to enhance roadway safety. In this paper, we focused on safety applications of a real field connected vehicle data on a horizontal curve. The database contains connected vehicle data that were collected on public roads in Ann Arbor, Michigan with instrumented vehicles. Horizontal curve negotiations are associated with a great number of accidents, which are mainly attributed to driving errors. Aggressive/risky driving is a contributing factor to the high rate of crashes on horizontal curves. Using basic safety message data in connected vehicle data …

Go to article

Modeling And Simulation Of Microgrid, Ahmad Alzahrani, Mehdi Ferdowsi, Pourya Shamsi, Cihan H. Dagli Nov 2017

Modeling And Simulation Of Microgrid, Ahmad Alzahrani, Mehdi Ferdowsi, Pourya Shamsi, Cihan H. Dagli

Electrical and Computer Engineering Faculty Research & Creative Works

Complex computer systems and electric power grids share many properties of how they behave and how they are structured. A microgrid is a smaller electric grid that contains several homes, energy storage units, and distributed generators. The main idea behind microgrids is the ability to work even if the main grid is not supplying power. That is, the energy storage unit and distributed generation will supply power in that case, and if there is excess in power production from renewable energy sources, it will go to the energy storage unit. Therefore, the electric grid becomes decentralized in terms of control …

Go to article

Chaotic Behavior In High-Gain Interleaved Dc-Dc Converters, Ahmad Alzahrani, Pourya Shamsi, Mehdi Ferdowsi, Cihan H. Dagli Nov 2017

Chaotic Behavior In High-Gain Interleaved Dc-Dc Converters, Ahmad Alzahrani, Pourya Shamsi, Mehdi Ferdowsi, Cihan H. Dagli

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, chaotic behavior in high gain dc-dc converters with current mode control is explored. The dc-dc converters exhibit some chaotic behavior because they contain switches. Moreover, in power electronics (circuits with more passive elements), the dynamics become rich in nonlinearity and become difficult to capture with linear analytical models. Therefore, studying modeling approaches and analysis methods is required. Most of the high-gain dc-dc boost converters cannot be controlled with only voltage mode control due to the presence of right half plane zero that narrows down the stability region. Therefore, the need of current mode control is necessary to …

Go to article

Solar Irradiance Forecasting Using Deep Neural Networks, Ahmad Alzahrani, Pourya Shamsi, Cihan H. Dagli, Mehdi Ferdowsi Nov 2017

Solar Irradiance Forecasting Using Deep Neural Networks, Ahmad Alzahrani, Pourya Shamsi, Cihan H. Dagli, Mehdi Ferdowsi

Electrical and Computer Engineering Faculty Research & Creative Works

Predicting solar irradiance has been an important topic in renewable energy generation. Prediction improves the planning and operation of photovoltaic systems and yields many economic advantages for electric utilities. The irradiance can be predicted using statistical methods such as artificial neural networks (ANN), support vector machines (SVM), or autoregressive moving average (ARMA). However, they either lack accuracy because they cannot capture long-term dependency or cannot be used with big data because of the scalability. This paper presents a method to predict the solar irradiance using deep neural networks. Deep recurrent neural networks (DRNNs) add complexity to the model without specifying …

Go to article

Quantitative Analysis Of Regenerative Energy In Electric Rail Traction Systems, Mahmoud Saleh, Oindrilla Dutta, Yusef Esa, Ahmed Mohamed Oct 2017

Quantitative Analysis Of Regenerative Energy In Electric Rail Traction Systems, Mahmoud Saleh, Oindrilla Dutta, Yusef Esa, Ahmed Mohamed

Publications and Research

This paper aims at determining the influential factors affecting regenerative braking energy in DC rail transit systems. This has been achieved by quantitatively evaluating the dependence of regenerative energy on various parameters, such as vehicle dynamics, train scheduling, ground inclination and efficiency of the electrical devices. The recuperated power and energy have been presented by a mathematical model, comprising of a set of empirical forms, which allows for thorough analysis. A detailed simulation model of a typical DC-traction system has been developed to validate the developed empirical forms. The results verified the validity of the proposed mathematical model, and demonstrated …

Go to article

Sensitivity Analysis Method To Address User Disparities In The Analytic Hierarchy Process, Marie Ivanco, Gene Hou, Jennifer Michaeli Jan 2017

Sensitivity Analysis Method To Address User Disparities In The Analytic Hierarchy Process, Marie Ivanco, Gene Hou, Jennifer Michaeli

Mechanical & Aerospace Engineering Faculty Publications

Decision makers often face complex problems, which can seldom be addressed well without the use of structured analytical models. Mathematical models have been developed to streamline and facilitate decision making activities, and among these, the Analytic Hierarchy Process (AHP) constitutes one of the most utilized multi-criteria decision analysis methods. While AHP has been thoroughly researched and applied, the method still shows limitations in terms of addressing user profile disparities. A novel sensitivity analysis method based on local partial derivatives is presented here to address these limitations. This new methodology informs AHP users of which pairwise comparisons most impact the derived …

Go to article