Automotive Engineering Commons^™

Crowd Monitoring And Firearm Detection Uas, Arjun Nambiar, Sang-A Lee, Diego Espino, Will Obot Jr, Ethan Encarnacion, Jarrett Usui, Jacob D. Kline

Discovery Day - Daytona Beach

The increasing complexity of public safety operations in urban and high-density environments necessitates intelligent, mobile surveillance systems capable of real-time threat identification and situational awareness. Traditional monitoring approaches, such as fixed CCTV systems and manual observation, are often limited by coverage, scalability, and response latency in complex environments or large-scale events. This project addresses these challenges through the development of a computer vision-enabled Uncrewed Aerial System (UAS) designed for crowd monitoring and firearm detection. The primary objective is to design and validate a modular, Artificial Intelligence (AI)-Machine Learning (ML)-driven model capable of identifying firearms within dynamic environments while supporting real-time …

Modernization Of Deicing Operations Utilizing Uncrewed Aircraft Systems, Christopher Sidor, Hunter Lisle, Zackrey Schraeder

Discovery Day - Daytona Beach

Modernization of Deicing Operations Utilizing Uncrewed Aircraft Systems   The use of Uncrewed Aircraft Systems (UAS), commonly known as drones, has become more apparent in everyday life within the United States (US). The Airport Cooperative Research Program (ACRP) has provided an opportunity to utilize drones to improve quality of life and operational efficiency at airports across the US. Students from Embry-Riddle Aeronautical University under the callsign Team Frostbite, consists of Hunter Lisle, Zakrey Schraeder, and Christopher Sidor. The team provides a potential solution utilizing UAS to measure the efficiency of deicing applications at Patrick Leahy Burlington International Airport (BTV) in Burlington, …

Is Lane Splitting/Lane Filtering Safe Or Dangerous?, Anastacio Doucas Nolas, Sierra Juliano, Shawn De La Osa, Kimberly R. Williamson

Discovery Day - Daytona Beach

This course-based research project examines whether lane splitting and lane filtering are inherently dangerous or whether their safety depends on human factors and traffic conditions. Using published crash, behavioral, and policy literature, the project compares how these motorcycle maneuvers affect riders and other road users across different roadway environments. The analysis distinguishes lane splitting, which occurs between moving lanes of traffic, from lane filtering, which typically occurs at low speeds in stopped or slow traffic queues. Findings suggest that safety cannot be explained by the maneuver alone. Instead, outcomes are shaped by speed differential, driver perception failures, rider workload, intersection …

The Electric Crackdown: Exploring The Human Factors Impacts Of Controls & Displays In Evs Across The Market, Rae Okada, Robin Hanen, Liam Brennan

Discovery Day - Daytona Beach

Title: The Electric Crackdown: Exploring the Human Factors Impacts of Controls & Displays in Electric Vehicles Across the Market   Despite a global adoption of electric vehicles (EVs) with partial driving automation (i.e., advanced driver assistance systems; ADAS), differences exist at societal (i.e., legislation, regulation), individual (i.e., use of), and system (i.e., vehicle-to-vehicle) levels surrounding these vehicles. While these former societal divergences can be considered based on the: (1) mechanisms promoting or limiting EV adoption, (2) number of EVs on the road, and (3) respective incident reports; system differences require investigation for each vehicle based on its make and model. In …

Machine Learning For Predictive Energy And Emissions Modeling Of Vehicles And Power Grids In The United States, S M Tanvir Faysal Alam Chowdhoury

Dissertations

The environmental benefits of electric vehicle (EV) adoption depend on more than replacing internal combustion engine vehicles with electric powertrains. EV adoption reshapes electricity demand, interacts with regional generation mixes, and influences travel behavior and congestion, creating a coupled transportation-energy system in which vehicle and power-plant emissions must be evaluated together. This dissertation develops machine-learning frameworks for predicting energy consumption and emissions from vehicles and power grids under rising EV adoption. The first component forecasts grid emissions from EV charging. Using simulation data from NREL's Cambium database, a Prophet-based time-series framework predicts carbon dioxide, nitrous oxide, and methane emission rates …

Perspectives On Promoting Cultivation Of Intelligent Connected Vehicle Industry For Modern Industrial System, Yu Jiang, Yingxiu Zhang, Feng Chen

Bulletin of Chinese Academy of Sciences (Chinese Version)

Promoting the development of intelligent connected vehicles (ICVs) has strategic significance for China to consolidate and expand its leadership in the new energy vehicle industry, accelerate the construction of a strong country in science and technology as well as transportation, and build a modern industry system with international competitiveness. Starting from the progressiveness and safety characteristics of the modern industrial system, and combining the three key requirements of “strategic guidance”, “innovation driven”, and “risk regulation” in the cultivation of emerging industries, this study reviews the innovation practices of major countries in the world to promote the development of the ICV …

Adaptive – Compositional Method For Coordinating Subsystems At Different Levels In Hierarchical Control Systems, Husan Zakirovich Igamberdiyev, Uktam Farxodovich Mamirov Mr, Inomjon Ilxom Ugli Abdukaxxarov Mr

Technical science and innovation

This paper examines the problem of synthesizing algorithms for the composition of subsystems at various levels within complex hierarchical control systems under conditions of uncertainty and resource constraints. It is demonstrated that classical composition algorithms, which rely on the intersection of admissible sets and the use of local optimality criteria, suffer from several significant drawbacks. These include a combinatorial increase in complexity, dependence on the expert selection of parameters, and limited applicability in dynamic environments. To overcome these shortcomings, an adaptive-compositional method is proposed. This method is based on the dynamic recalculation of coordination parameters, the integration of model predictive …

Calculation Of The Basic Parameters Of The Hybrid Power Plant (Hpu) On The Spark Car, Rustam Raximovich Tillahodjaev, Jamoliddin Pardaboy Ugli Turdiev

Technical science and innovation

This article presents one of the effective ways to improve fuel efficiency and reduce emissions of toxic substances, the use of internal combustion engines with the use of an electric drive in their designs. In recent years, two directions in the development of cars with electromechanical drives have been clearly identified, the first is the creation of a pure electric car, the second is the development of an electromechanical drive with a combined (hybrid) power plant. Due to the lack of efficient energy storage available for mass production, pure electric vehicles have relatively low mileage on a single charge. This …

Upholding Long-Termism In Basic Research To Shape Leading Advantage Of Automotive Industry, Yubo Lian

Bulletin of Chinese Academy of Sciences (Chinese Version)

General Secretary Xi Jinping has pointed out that basic research is the origin of the entire scientific system and the master switch for all technological issues, emphasizing that it must be advanced with greater efforts and more concrete measures. Upholding long-termism in basic research means placing it at the foundation of the innovation chain and maintaining continuous investment with strategic patience characterized by a long-term horizon and high tolerance for failure. Drawing on the author’s industrial practice, this study systematically reviews the characteristics and roles of basic research throughout the development of China’s new energy vehicle industry. In light of …

A Comparative Study Of Model Predictive Control And The Stanley Method For Vehicle Path Tracking Applications, Noah S. Fitzgerald

Master's Theses

This thesis compares a model predictive controller (MPC) and a lateral Stanley controller for vehicle path-tracking applications under simulation-based and perception-driven operating conditions. Both controllers were evaluated in simulation using a nonlinear dynamic bicycle model executing single and double lane change maneuvers. Following simulation-based evaluation, both controllers were implemented on hardware within a perception-driven steering-control pipeline. This pipeline utilized recorded sensor data from the MXcarkit 1/8^th-scale autonomous vehicle platform, incorporating lane instance segmentation and homography-based roadway estimation.

Under idealized simulation conditions, the MPC demonstrated improved trajectory-tracking performance during aggressive maneuvers while requiring greater steering activity and computational effort …

Trim-Transfer: A Transfer Learning Approach For Cross-Trim Level Can Intrusion Detection, Baylor J. Whitehead

Master's Theses

Modern vehicles contain many Electronic Control Units (ECUs) that communicate through CAN. While CAN enables efficient data communication, it lacks built in authentication and encryption, allowing adversarial actors to inject malicious CAN messages. This limitation has motivated the development of CAN intrusion detection systems (IDS). However, deploying IDS across a vehicle lineup requires collecting large labeled datasets and retraining models, increasing development cost and limiting scalability.

This thesis investigates the use of transfer learning with LSTM-based deep neural networks to reduce retraining cost while maintaining model detection performance. A baseline LSTM model is trained using CAN data from a base …

Comprehensive Analysis Of Spray Development And Low Temperature Combustion Characteristics In A Cvcc With Nvh Of Renewable Aerospace Fuels: Hefa & Ft Synthetic Kerosene (S8) Compared To Jet-A & Ulsd, Coleman Norton

Honors College Theses

A comprehensive analysis was conducted to research the viability of Hydroprocessed Esters and Fatty Acids (HEFA) and S8 Synthetic Kerosene fuels as a drop-in replacement for conventional petroleum-based fuels, Jet-A and ULSD (Ultra Low Sulfur Diesel). Global transportation remains heavily dependent on liquid fossil fuels, while renewable aerospace fuels offer a promising pathway to reducing life cycle greenhouse gas emissions and pollution. However, the combustion performance and long-term feasibility of these fuels remain insufficiently characterized. This study performed a thorough assessment of each fuel's thermophysical and combustion properties. Thermophysical characterization encompassed viscosity, freezing point, energy density, spray atomization, and volatility. …

Design Optimization Of Active-Stabilizing Canards For High-Powered Rockets, Simon Babcock

Senior Honors Theses

Rocket canards are a common means of stabilizing a high-powered rocket in flight by producing aerodynamic forces to correct the rocket's trajectory. The size, shape, and position of the canards relative to the rocket body determine their control effectiveness and aerodynamic efficiency – two objectives of canard design with an inverse relationship to each other. By integrating automated iterative rocket trajectory simulation with adaptive surrogate modelling, this research optimized the canard planform geometry for a high-powered rocket to maximize the canards’ control effectiveness and aerodynamic efficiency through multi-variable, multi-objective design optimization. The canard design was first parameterized into four design …

Bayesian Assembly Tool For Intelligent Digital Twin Selection, Shishir Sharma

All Theses

Digital twins can be used for system performance optimization, health monitoring, predictive maintenance, and investigating system anomalies. A ground vehicle digital twin may be assembled using representations of the subsystem models (tires, suspension system, powertrain, etc.) of different fidelity. Lower fidelity Digital Twins have relatively simpler design and physics, hence are generally computationally less expensive, but may not represent the physical system accurately. On the contrary, higher fidelity Digital Twins are generally more precise in their ability to represent the physical system, but due to complexity, are usually computationally more demanding. This thesis describes the application of Bayesian Classification within …

Safe Control Design For Quadruped Locomotion In Unstructured Environments Using Linear Transfer Operators, Sriram Sundar Krishnamoorthy Shankara Narayanan

All Dissertations

Deploying quadruped robots in unstructured, obstacle-rich environments requires control and planning methods that remain safe and reliable despite complex terrain geometry, limited sensing, and inevitable modeling errors. This thesis develops operator-theoretic tools for safe control design of robotic systems using linear transfer operators, with a focus on quadruped locomotion in unstructured environments. The central goal is to develop a unified operator-theoretic framework for safe control design based on the Perron–Frobenius (P–F) and Koopman operators. In particular, the thesis leverages \emph{density functions} to develop safe navigation frameworks in the dual space of densities. In the operator-theoretic perspective, the P–F operator governs …

Development Of A Mixing-Controlled Combustion Model For 0d Engine Modeling: Using High-Order Models To Guide The Formulation Of Reduced-Order Models, James Gohn

All Dissertations

Vehicles are becoming increasingly complex to comply with the increasingly stringent regulations placed on all market sectors while still maintaining performance requirements. This increased complexity leads to increases in the cost and time it takes to develop and produce these next generation vehicles. To meet demand therefore, it becomes necessary to evaluate numerous design iterations using computer models. There are multiple levels of models that may be necessary for different purposes or use cases. All levels of modeling for virtual prototyping, however, require a level of validation and predictive ability to be useful. To this end, the following thesis presents …

Increasing The Number Of Injections Per Cycle In A Gasoline Compression Ignition Strategy: An Experimental Study, Joshua Murray

All Theses

Gasoline Compression Ignition (GCI) is an advanced compression ignition strategy which utilizes the high octane number of gasoline to improve diesel soot and NOx emissions by enabling partially premixed injections of fuel. GCI work in the literature typically uses single, double, or triple injection strategies, with higher numbers of injections noted for their ability to achieve low MPRRs, improved soot and NOx emissions, and higher efficiency. Thus, this study extends the literature by evaluating quadruple and quintuple injection strategies for continued improvement in engine efficiency and emissions.

The experiments in this work are conducted on a heavy-duty Detroit Diesel DD13 …

Optimizing Controller Speed And Torque To Reduce Drivetrain Stress, Selene J. Welch

SACAD: Scholarly Activities

This project investigates how torque delivery from the motor controller affects mechanical stress on the rear freewheel ratchet mechanism of a three-wheel electric race car. Excessive initial torque has caused accelerated wear and tear on the ratchet mechanism, reducing drivetrain reliability during Kansas ElectroRally competitions. Preliminary testing showed that slower, gradual acceleration prevented malfunction and allowed the vehicle to maintain top speed reliably. Prior research shows that torque-control strategies strongly influence electric-drive performance. Current research focuses on optimizing the controller’s torque and speed using the Alltrax Software ToolKit to reduce drivetrain tension while preserving the car’s performance capabilities.

Performance Analysis Of A Converted Electric Underbone Motorcycle: A Combined Dynamometer And Road Test Approach, Dhimas Oki Permata Aji, Sigit Suwarto, Yunus Ari Rokhim

Journal of Mechanical Engineering Science and Technology (JMEST)

In developing countries, converting traditional underbone motorcycles to electric vehicles transforms sustainable transportation from a theoretical concept to a practical implementation. This paper describes the design and operational performance evaluation of an electric underbone motorcycle conversion system that integrates a 2.0 kW, 72 V BLDC motor and a 72 V, 20 Ah lithium-ion battery pack. Compared to previous studies, this paper combines, for the first time, both dynamometer and road tests as the basis for a comprehensive performance assessment of low-cost motorcycle conversion. The dynamometer test was conducted under laboratory conditions to evaluate the test system for torque, power output, …

Plasmoid Vortex System Retrofit A Sustainability And Efficiency Study On Internal Combustion Engines, Walker Hall

Doctoral Dissertations and Master's Theses

The thesis addresses the persistent inefficiency and environmental degradation caused by internal combustion engines in modern vehicles, a major issue as the automotive industry faces increasing pressure to reduce fuel consumption and greenhouse gas emissions. Internal combustion engines, which power most cars today, convert only about 20-30% of fuel energy into useful work, with the remainder lost as heat and exhaust waste, including carbon monoxide (CO), carbon dioxide (CO₂), hydrocarbons (HC), and nitrogen oxides (NOx). This inefficiency contributes to global carbon emissions, with transportation accounting for approximately 29% of U.S. greenhouse gases in 2021 [1]. As regulatory standards tighten (e.g., …

Markov-Modulated Queueing Network For Mobile Traffic Aggregation With Threshold-Controlled Buffers, Anton A. Esin, Elmira Yu. Kalimulina

Mathematical Modelling and Numerical Simulation with Applications

We study the problem of data transmission from mobile platforms operating in high-speed transit between cellular base stations, under conditions of unstable and intermittent connectivity. Conventional queueing and connectivity models often fail to capture the combined effects of rapidly changing signal conditions, finite buffer capacity, and dynamic topology. We aim to develop a tractable yet expressive model that integrates stochastic link availability, queue dynamics, and buffer control. We propose a mathematical framework based on queues whose service intensities are modulated by a continuous-time Markov chain (CTMC) representing signal conditions along a high-speed trajectory. The core subsystem is a two-stage (aggregation …

Scenarioxp: A Complete Scenario–Based Testing Framework For The Exploration And Exploitation Of Autonomous Vehicle Validation Scenarios, Quentin Goss

Student Research Symposium (SRS)

Today is an age of exiting emerging technology where cutting-edge research in autonomous vehicles (AVs) reduces the active human participation in driving and extends awareness beyond human limitations of perception and reaction, improving driving safety and quality of the user experience as a result. The ever-increasing complexity of these autonomous systems poses many challenges towards the validation and verification (V\&V) of these complex systems under time and resource constraints, as the use of artificial intelligence and also the intricacy of the operating environment means that these systems are also black-box and non-deterministic. Scenario-based V\&V testing of such systems, which involves …

A Data-Driven Framework For Modeling Car-Following Behavior Using Conditional Transfer Entropy And Dynamic Mode Decomposition, Poorendra Ramlall

Student Research Symposium (SRS)

Accurate modeling of car-following behavior is essential for understanding traffic dynamics and enabling predictive control in intelligent transportation systems. This study presents a novel data-driven framework that combines information-theoretic input selection via conditional transfer entropy (CTE) with dynamic mode decomposition with control (DMDc) for identifying and forecasting car-following dynamics. In the first step, CTE is employed to identify the specific vehicles that exert directional influence on a given subject vehicle, thereby systematically determining the relevant control inputs for modeling its behavior. In the second step, DMDc is applied to estimate and predict the dynamics by reconstructing the closed-form expression of …

Rm Sotheby’S Construction Of Value In The High-End Car Market, Pablo Mijares Musi

MA Theses

The purpose of my thesis is to tell and enlighten any readers how the most prestigious and iconic auction house in the world, RM Sotheby’s sells more than just cars from the high-end car market and how the auction house adds value to through storytelling and provenance from each vehicle.  In today’s luxury market economics, we see somewhat of a radical shift. The high-end car market has moved into a very refined area where these beautiful machines are no longer seen and appraised just for their aesthetic design and mechanical engineering, now we see new value drivers for these works …

Uncertainty-Aware Estimation, Planning, And Control For Tracking Multiple Drifting Patches In Flow Fields, Daniel O. Akanji, Krishnanand N. Kaipa, Cong Wei

Mechanical & Aerospace Engineering Faculty Publications

In this study, we present a replay-based framework for uncertainty-aware persistent tracking of multiple advected surface patches using an autonomous marine vehicle operating in spatiotemporal-varying currents. The method combines three components: local flow estimation, covariance-aware patch-boundary propagation with intermittent boundary fusion, and mission-level scheduling over multiple patches. Each patch is represented by a polygonal boundary, whose vertices are propagated through the estimated flow field while carrying per-vertex covariance, thereby quantifying uncertainty growth during advection. A flow-aware gain-scheduled linear quadratic regulator (LQR) was designed to shape the desired surge speed to take advantage of favorable currents. When the vehicle services a …

Development Of Stronger, More Extrudable 6xxx Series Alloys For Automotive Applications, Eli A. Harma

Dissertations, Master's Theses and Master's Reports

6xxx alloys are widely used in automotive extrusion structures for their high specific strength and formability. Advanced designs require greater formability and strength, creating an opportunity for high-strength, formable alloys. The 6xxx series forms β”-Mg₅Si₆ precipitates during age hardening and develops a fibrous microstructure during extrusion, both strengthening the alloy. Increasing Mg and Si to form more β” decreases formability. Thus, modifying texture can increase strength without reducing formability. Current alloys like 6005A add Mn and Cr to form dispersoids that inhibit recrystallization and promote strengthening textures; however, high Mn and Cr concentrations reduce formability. Replacing Mn …

Investigation Of The Impact Of The Shape Of The Wings On Formula E Racing Car Performance: Enhancements For Optimal Aerodynamics, Ednie Marthe Adlaikah Jozil

Honors Undergraduate Theses

The aerodynamic performance of a Formula E chassis significantly dictates its overall race efficiency, directly impacting crucial parameters such as battery range and thermal management. This thesis investigates the external aerodynamics of the baseline Gen 2 Formula E car and evaluates the performance gains of two novel aerodynamic packages: a "Fully Modified" configuration and a "Flat Rear Wing" design. Computational Fluid Dynamics (CFD) simulations were conducted to analyze drag coefficients (Cd), downforce generation, and vehicle wake structures at race-relevant free-stream velocities (e.g., 37 m/s and 89 m/s). To ensure numerical robustness, the computational setup was validated using a smooth sphere …

The Efficacy Of Hybrid Manufacturing For High Stress Automotive Parts, Logan Trimmer

Harrisburg University Other Works

Presentation covering the broad strokes of the project. The goal was to prove the viability of hybrid/additive manufacturing for high stress automotive applications. This project focused on recreating a piston from an old engine to examine if hybrid manufacturing could be used for such applications. On a small scale, hybrid manufacturing was able to be more cost effective if the costs of the equipment and electricity were ignored. The decision to ignore those costs came from the inability to find accurate prices for industrial casting.

The Efficacy Of Hybrid Manufacturing For High Stress Automotive Components, Logan Trimmer

Harrisburg University Other Works

The goal of this research was to establish the viability of using hybrid manufacturing for automotive applications. By verifying that high-stress components can be created, it can be assumed that any other lower stress part could be made to match the strength requirements. A limiting factor of adoption for hybrid manufacturing is how new the technology is. Studies on time and cost were performed allowing for comparisons with traditional manufacturing technologies (casting, forging, milling) used in automotive applications. This research utilized a Haas Automation UMC750 5-axis CNC mill with a Meltio laser wire direct energy deposition attachment. Fusion 360 was …

Multi-Level Energy Optimization For Connected And Automated Vehicles: From Cooperative Multi-Vehicle Control To Individual Powertrain Management, Pruthwiraj Santhosh

Dissertations, Master's Theses and Master's Reports

The transportation sector currently accounts for nearly 30% of global energy consumption, necessitating urgent advancements in vehicle efficiency to meet Net Zero targets. Leveraging connectivity and automation, this dissertation proposes and validates methodologies to reduce the energy consumption of light-duty vehicles at both fleet and individual levels.

First, a validation framework is developed to bridge the “simulation-to-real world” gap in Cooperative Automated Vehicle (CAV) research. Moving beyond virtual simulations, the study establishes a methodology for physically validating centralized control architectures via a custom Cellular V2X network. By synchronizing vehicle-powertrain models with physical test vehicles, the framework successfully orchestrates complex arterial …