Engineering Commons^™

Control Of Mr Damper Using Anfis And Pid Controller For Optimum Vehicle Ride Comfort, Mohammad Faisal Yakhni, Mohamad Ali, Mohamed El-Gohary

BAU Journal - Science and Technology

Suspension system design is an important challenging duty that facing car manufacturers, so the challenge has become to design the best system in terms of providing ride comfort and handling ability under all driving situations. The goal of this paper is to provide assistance in enhancing the effectiveness of the suspension system. A full car model with eight Degrees Of Freedom (DOF) was developed using MATLAB/Simulink. Validation of the Simulink model was obtained. The model was assumed to travel over a speed hump that has a half sine wave shape and amplitude that changing from 0.01 to 0.2 m. The …

Modeling Intangible Assets Of A Logistic Organization, S. Yadgarov Nomozovich Yadgarov

Acta of Turin Polytechnic University in Tashkent

Abstract—The article presents the results of It will be relevant to fill this gap, presumably arising from insufficient elaboration of ap- proaches to the assessment of scientific knowledge, which, along with managerial knowledge and practical competencies of manage- ment in the field of logistics, generates intangible assets. In other words, it is required to show that the "science intensity" of the lo- gistics business is a capitalized asset.

Efficient End-To-End Autonomous Driving, Hesham Eraqi

Theses and Dissertations

Steering a car through traffic is a complex task that is difficult to cast into algorithms. Therefore, researchers turn to train artificial neural networks from front-facing camera data stream along with the associated steering angles. Nevertheless, most existing solutions consider only the visual camera frames as input, thus ignoring the temporal relationship between frames. In this work, we propose a Convolution Long Short-Term Memory Recurrent Neural Network (C-LSTM), which is end-to-end trainable, to learn both visual and dynamic temporal dependencies of driving. Additionally, We introduce posing the steering angle regression problem as classification while imposing a spatial relationship between the …

Thermoplastic Additive Manufacturing For Composites And Molds, Pritesh S. Yeole

Doctoral Dissertations

Recent inventions in the ability of additive manufacturing (AM) to use carbon fiber (CF) reinforced pellets as a feedstock material to manufacture components has complemented its purpose from prototypes to structural load-bearing parts. In the first part of this research, we investigated the processability, microstructure, and mechanical performance of twin-screw compounded short CF reinforced polyphenylene sulfide (PPS) pellets as a feedstock material for extrusion deposition fabrication-additive manufacturing (EDF-AM) using big area AM (BAAM). The performance of the BAAM components was compared to that of traditional processing methods, namely injection molding (IM) and extrusion-compression molding (ECM). It was found that the …

Intelligent Roadside Unit Deployment In Vehicular Network, Xiangyu Xu

Masters Theses

Intelligent Transportation System (ITS) has been an important research area in building the foundational infrastructures of self-driving vehicles and improving traffic efficiency of future transportation systems. Scientists have been hoping to incorporate intelligence into traditional transportation systems to help reduce the risks, accident rates, traffic congestion, and even environmental emissions.

There are many research works that have been focused on the communication part of ITS, such as vehicular networks, which collect data from vehicles and send it to the cloud for analysis. In the vehicular networks, Roadside Unit (RSU) is a key infrastructure as an intermediate layer between the vehicles …

Towards Sensorimotor Coupling Of A Spiking Neural Network And Deep Reinforcement Learning For Robotics Application, Kashu Yamazaki

Mechanical Engineering Undergraduate Honors Theses

Deep reinforcement learning augments the reinforcement learning framework and utilizes the powerful representation of deep neural networks. Recent works have demonstrated the great achievements of deep reinforcement learning in various domains including finance,medicine, healthcare, video games, robotics and computer vision.Deep neural network was started with multi-layer perceptron (1stgeneration) and developed to deep neural networks (2ndgeneration)and it is moving forward to spiking neural networks which are knownas3rdgeneration of neural networks. Spiking neural networks aim to bridge the gap between neuroscience and machine learning, using biologically-realistic models of neurons to carry out computation. In this thesis, we first provide a comprehensive review …

A New Method Of Statcom Controlling For Harmonic Mitigation And Power Factor Correction, Doha Jdeed

Journal of the Arab American University مجلة الجامعة العربية الامريكية للبحوث

This paper presents a control algorithm of 3ph STATic synchronous COMpensator (STATCOM). The algorithm depends on the accurate reference currents extraction from only the nonlinear load current spec-trum in frequency domain using Fast Fourier Transfer (FFT). Then the determined harmonics and reactive components of load current are added together to form the compensating reference signals, the PI controllers then generate signals which control the Pulse Width Modulation (PWM) method. The simulation of the study is carried out under MATLAB/Simulink environment to show the usefulness of this control algorithm with nonlin-ear dynamic loads. It determines exactly the phase shift between the …

Non-Conventional Vehicles As A Way Towards Carbon Neutrality In Iceland, Julia Sokolowska

Independent Study Project (ISP) Collection

Paris Agreement’s chief objective is to protect the Earth and its inhabitants from a point of no return, when the effects of climate change will be so intense that they will shift the equilibrium of ecosystems. The distinctiveness of this international environmental treaty is that it does not impose climate change mitigation measures, but rather allows nation states to create their own set of measures, the NDCs, to reach the global warming of ‘well below 2oC’ by the end of the century. Thus, Iceland has submitted its own NDC, the Climate Action Plan 2018-2030, which has an ambitious goal of …

Photovoltaics- And Battery-Based Power Network As Sustainable Source Of Electric Power, Prahaladh Paniyil, Vishwas Powar, Rajendra Singh, Benjamin Hennigan, Pamela Lule, Matthew Allison, John Kimsey, Anthony Carambia, Dhruval Patel, Daniel Carrillo, Zachary Shriber, Truman Bazer, James Farnum, Kushal Jadhav, Dalton Pumputis

Publications

With the rise in the utilization of free fuel energy sources, namely solar and wind, across the globe, it has become necessary to study and implement models of a sustainable power network. This paper focuses on the design of a conceptual power network based on photovoltaics (PV) for power generation and lithium-ion batteries for storage. The power system showcases the various metrics that are involved in a grid-tied PV- and battery-based power network. It also encompasses the various design parameters and sizing considerations to design and conceptualize such a power network. The model focuses on the importance of the conservation …

As The Role Of The Driver Changes With Autonomous Vehicle Technology, So, Too, Must The Law Change, Nanci K. Carr

St. Mary's Law Journal

Getting a driver’s license is a highly anticipated rite of passage for most teenagers. Being alone behind the wheel, in control of a 3,000-pound machine, is an honor, a privilege, and a sign of adult responsibility. How will that change when driver’s licenses become licenses “to cause technology to engage” with the increased use of autonomous cars? Will driver’s education courses, with their focus on safety rules and defensive driving techniques, be eliminated if all a vehicle operator needs to do is push a button and the vehicle does the rest? While arguably autonomous cars are safer, they will not …

Brave New World - Mobility, Rhonda S. Binda

Open Educational Resources

The trifecta of globalization, urbanization and digitization have created new opportunities and challenges across our nation, cities, boroughs and urban centers. Cities are in a unique position at the center of commerce and technology becoming hubs for innovation and practical application of emerging technology. In this rapidly changing 24/7 digitized world, city governments worldwide are leveraging innovation and technology to become more effective, efficient, transparent and to be able to better plan for and anticipate the needs of its citizens, businesses and community organizations. This class will provide the framework for how cities and communities can become smarter and more …

The Impact Of Autonomous Vehicles, Preston Loveland

Marriott Student Review

In this article, Preston Loveland delves into the innovations of autonomous vehicles. He outlines the safety, benefits, and public opinion of self-driving cars while inviting the reader to become part of this innovation.

Towards Dynamic Vehicular Clouds, Aida Ghazizadeh

Computer Science Theses & Dissertations

Motivated by the success of the conventional cloud computing, Vehicular Clouds were introduced as a group of vehicles whose corporate computing, sensing, communication, and physical resources can be coordinated and dynamically allocated to authorized users. One of the attributes that set Vehicular Clouds apart from conventional clouds is resource volatility. As vehicles enter and leave the cloud, new computing resources become available while others depart, creating a volatile environment where the task of reasoning about fundamental performance metrics becomes very challenging. The goal of this thesis is to design an architecture and model for a dynamic Vehicular Cloud built on …

Development Of An Improved Arterial Roadway Performance Reliability Methodology, Ernest Tufuor

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

The need for reliable performance measures of urban arterial roadways is increasing because of the rise in traffic congestion and the high value of travel time. Consequently, travel time reliability (TTR), which combines components of measures of central tendency and measures of dispersion of travel times, has recently received considerable research interest.

The basis of all TTR metrics is the travel time distribution (TTD). Estimating and forecasting arterial TTDs for TTR analysis is the focus of this dissertation. This dissertation proposes a new TTR methodology that is a marked improvement on recent TTR estimation and forecasting methodologies including the current …

Performance Testing Of Aero-Naut Camfolding Propellers, Or D. Dantsker, Robert W. Deters, Marco Caccamo, Michael S. Selig

Publications

The increase in popularity of unmanned aerial vehicles (UAVs) has been driven by their use in civilian, education, government, and military applications. However, limited on-board energy storage significantly limits flight time and ultimately usability. The propulsion system plays a critical part in the overall energy consumption of the UAV; therefore, it is necessary to determine the most optimal combination of possible propulsion system components for a given mission profile, i.e. propellers, motors, and electronic speed controllers (ESC). Hundreds of options are available for the different components with little performance specifications available for most of them. By examining a variety of …

Optimized System For On-Route Charging Of Battery Electric Buses And High-Fidelity Modelling And Simulation Of In-Motion Wireless Power Transfer, Yogesh Bappasaheb Jagdale

Masters Theses

Electrifying cars, buses and trucks is an attractive means to reduce energy use and emissions, because it involves minimal restructuring of the transportation network. Transit buses drive fixed routes, minimizing driver range anxiety by properly sizing energy storage system but the major challenge to fully electrifying transit buses, is the amount of energy they consume in a day of driving. To enable a full day of operation, batteries need to be large, which is expensive and heavy. This work utilizes real-world transit bus data fed to a battery electric drive-train model to co-optimize charger locations, charger power levels, and vehicle …

Development Of Catalytic Chromia-Based Aerogels, Fiona Fitzgerald

Honors Theses

Over one billion automobiles are in use around the world, the majority of which employ internal combustion engines. Catalytic converters are used to convert the toxic compounds found in car exhaust -- carbon monoxide, nitrogen oxides (NOx) and hydrocarbons -- to less harmful gases. The typical catalytic converter employs as catalysts expensive raw materials (platinum, palladium and/or rhodium) wash-coated onto an alumina-based ceramic substrate. Aerogel materials have high surface area and thermal stability, properties that make them attractive for catalysis applications. Aerogels made with transition metal oxides are candidates to replace platinum in the catalytic converter. Chromium oxide (chromia) materials …

Conducted And Radiated Emi Measurements Of Parallel Buck Converters Under Varying Spread Spectrum Parameters, Elena Postupalskaya, Nathan Wang

Electrical Engineering

The Conducted and Radiated EMI Measurements with Parallel Buck Converters Under Varying Spread Spectrum Parameters research senior project aims to explore the effects from Spread Spectrum Frequency Modulation (SSFM) on the input electromagnetic interference (EMI) or noise of a switching power supply, specifically with LM53601MAEVM hardware. The input EMI is important as the main input bus needs to be clean to provide a reliable source for other sensitive devices connected to it. SSFM can replace a conventional EMI filter and save weight, space, and cost. This project provides a basis in terms of the impacts of variable SSFM in simulation …

Turbulence Investigations In The Core-Flow Of An Internal Combustion Engine, James R. Macdonald

Dissertations

Turbulence significantly impacts the operation of energy conversion devices. In internal combustion (IC) engines, mixing, heat transfer, and combustion are all strongly dependent on the turbulence inside the cylinder. Consequently, knowledge of the state of turbulence is critical for improving our understanding and modeling of engine processes.

Turbulence states may be determined through analysis of the Reynolds stress tensor, which can in turn be experimentally quantified using velocity data. In this research, stereoscopic particle image velocimetry (stereo-PIV) experiments were conducted in a single-cylinder, motored engine with optical access to measure the two-dimensional, three-component (2D-3C) velocity fields throughout the compression stroke. …

Evaluating Driving Performance Of A Novel Behavior Planning Model On Connected Autonomous Vehicles, Keyur Shah

Honors Scholar Theses

Many current algorithms and approaches in autonomous driving attempt to solve the "trajectory generation" or "trajectory following” problems: given a target behavior (e.g. stay in the current lane at the speed limit or change lane), what trajectory should the vehicle follow, and what inputs should the driving agent apply to the throttle and brake to achieve this trajectory? In this work, we instead focus on the “behavior planning” problem—specifically, should an autonomous vehicle change lane or keep lane given the current state of the system?

In addition, current theory mainly focuses on single-vehicle systems, where vehicles do not communicate with …

Control And Locomotion Of Inertially And Magnetically Actuated Multi-Scale Robotic Systems, Ehab Al Khatib

Mechanical Engineering Research Theses and Dissertations

In this research, two actuation systems were introduced, inertial and magnetic actuation. In the inertial actuation, the robot used the transfer of momentum to navigate, and this momentum could be generated by spinning masses and wheels. Recent studies in our System Laboratory proved that a wide range of inertially actuated locomotion systems could be generated. This can be achieved by using a family tree approach, starting from a very simple system, and progressively evolving it to more complex ones. The motion diversity of these robots inspired us to extend their locomotion from a macro scale to millimeter and micro scales. …

Hardware Security Of The Controller Area Network (Can Bus), David Satagaj

Senior Honors Theses

The CAN bus is a multi-master network messaging protocol that is a standard across the vehicular industry to provide intra-vehicular communications. Electronics Control Units within vehicles use this network to exchange critical information to operate the car. With the advent of the internet nearly three decades ago, and an increasingly inter-connected world, it is vital that the security of the CAN bus be addressed and built up to withstand physical and non-physical intrusions with malicious intent. Specifically, this paper looks at the concept of node identifiers and how they allow the strengths of the CAN bus to shine while also …

Basic Utilities Vehicle (Buv) Milk Transportation, Brian D. Reynolds, Sean Patrick Bayless Galligar, Emmitt Hanner, Joshua T. Pitts

Scholar Week 2016 - present

In developing countries, a need exists for the transportation of raw foods to communities without spoilage. Traditional methods of transporting goods don’t meet the needs of the consumer, and often times food is wasted due to the harsh climate and time constraints. Food often becomes salvage under the heat, causing a hurt to the profitability of vendors and family needs for fresh produce. In particular milk transportation has become difficult, due to the lack of cold storage in standard transit. As a response to the need for affordable raw food transport, our sponsor Basic Utilities Vehicle (BUV) has tasked us …

Sae Baja Drivetrain, Troy Von Gillern, Kaitlyn Elmer, Nathan Tabor

Scholar Week 2016 - present

A project to optimize the drivetrain on the ONU SAE Baja Team vehicle.

Nonlinear Least Squares 3-D Geolocation Solutions Using Time Differences Of Arrival, Michael V. Bredemann

Mathematics & Statistics ETDs

This thesis uses a geometric approach to derive and solve nonlinear least squares minimization problems to geolocate a signal source in three dimensions using time differences of arrival at multiple sensor locations. There is no restriction on the maximum number of sensors used. Residual errors reach the numerical limits of machine precision. Symmetric sensor orientations are found that prevent closed form solutions of source locations lying within the null space. Maximum uncertainties in relative sensor positions and time difference of arrivals, required to locate a source within a maximum specified error, are found from these results. Examples illustrate potential requirements …

Fluid Power Vehicle Challenge, Jacob Torrey, Kayla Londono, Bryson Chan, Aaron Trujillo

Mechanical Engineering

The FPVC combines mechanical engineering disciplines to design and manufacture a vehicle that utilizes hydraulic power. The FDR covers the final manufacturing process and verification processes developed during the front end of research and analysis built upon the Critical Design Review (CDR) and the PDR (Preliminary Design Review). This report showcases the design decisions and extensive research that supports the continuing efforts by the Team Pump My Ride, to build upon the accomplishments of Cal Poly’s previous team, The Incompressibles. The FDR presents how Team Pump My Ride produced the design changes from the CDR and PDR to achieve improvements …

Vehicle Velocity Prediction Using Artificial Neural Networks And Effect Of Real-World Signals On Prediction Window, Tushar Dnyaneshwar Gaikwad

Masters Theses

Prediction of vehicle velocity is essential since it can realize improvements in the fuel economy/energy efficiency, drivability, and safety. Many publications address velocity prediction problems, yet there is a need for the understanding effect of different signals for the prediction. There are numerous new sensor and signal technologies like vehicle-to-vehicle and vehicle-to-infrastructure communication that can be used to obtain comprehensive datasets. Several references considered deterministic and stochastic approaches that use the datasets as input to determine future operation predictions. These approaches include different traffic models and artificial neural networks such as Markov chain, nonlinear autoregressive model, Gaussian function, and recurrent …

Comparison Of Optimal Energy Management Strategies Using Dynamic Programming, Model Predictive Control, And Constant Velocity Prediction, Amol Arvind Patil

Masters Theses

Due to the recent advancements in autonomous vehicle technology, future vehicle velocity predictions are becoming more robust which allows fuel economy (FE) improvements in hybrid electric vehicles through optimal energy management strategies (EMS). A real-world highway drive cycle (DC) and a controls-oriented 2017 Toyota Prius Prime model are used to study potential FE improvements. We proposed three important metrics for comparison: (1) perfect full drive cycle prediction using dynamic programming, (2) 10-second prediction horizon model predictive control (MPC), and (3) 10-second constant velocity prediction. These different velocity predictions are put into an optimal EMS derivation algorithm to derive optimal engine …

Vehicle Performance Analysis Of An Autonomous Electric Shuttle Modified For Wheelchair Accessibility, Johan Fanas Rojas

Masters Theses

Autonomous vehicles (AV) have the potential to vastly improve independent, safe, and cost-effective mobility options for individuals with disabilities. However, accessibility considerations are often overlooked in the early stages of design, resulting in AVs that are inaccessible to people with disabilities. The needs of wheeled mobility device users can cause significant vehicle design changes due to requirements for stepless ingress/egress and increased space for onboard circulation and securement. Vehicles serving people with disabilities typically require costly aftermarket modifications for accessibility, which may have unforeseen impacts on vehicle performance and safety, particularly in the case of automated vehicles. In this research, …

The Future State Of Mobility, Jerome Quandt

Purdue Road School

Formed in 2018, the Illinois Autonomous Vehicles Association (ILAVA) is a privately funded non-for-profit organization focused on establishing thought leadership in the state of Illinois, by identifying and addressing the current and emerging opportunities related to the inevitable growth of CAV technologies throughout the transportation network. Through the deployment of scalable and sustainable business solutions, facilitating industry education and establishing thought leadership, ILAVA is creating an ecosystem that defines Illinois as #TheFutureStateofMobility.