Automotive Engineering Commons^™

Speed Measurement On Swri Shell Eco-Marathon Vehicle, Andrew Garza, Benjamin Openshaw, Scott Roelker Murillo

Posters - 2025

Southwest Research Institute (SwRI) operates a fully autonomous electric vehicle known as the Shell Eco-Marathon Vehicle. This platform provides students with the opportunity to develop software, thus gaining hands-on experience in autonomous vehicle systems and advancing their careers. The vehicle competes against other fully autonomous vehicles, testing the performance and reliability of its software in real-world scenarios.

• However, improper handling during shipping damaged the previous speed encoder decoding method. A temporary fix was implemented, but it was limited — it provided accurate readings up to 3MPH but often falsely detected movement when the vehicle was stationary.

• Our project …

Stem Voyager, Alexis Nunez, Jaya Mcgill, Patrick Canez, Fernando Jaime, Pedro Perez, Gianluca Porzio

Posters - 2025

"What do you want to be when you grow up?" This is a question that people are far too familiar with. Many STEM professionals would also say that they are not currently in the career that they initially thought. Somehow there was a moment of inspiration in their life that catalyzed their decision to pursue a STEM degree. This project aims to convert a school bus into a mobile STEM lab that brings hands-on, engaging STEM experiences to middle school students and supports teachers with interactive lessons. The bus will address space and cost challenges by serving as a flexible, …

Techniques For Enabling Advanced Adas Features: Operation In Inclement Weather And Use Of Infrastructure Information, Parth Kadav

Dissertations

Modern vehicles have undergone a transformation with the widespread integration of Advanced Driver Assistance Systems (ADAS) technology becoming the new standard and are set to be mandated by the by the National Highway Traffic Safety Administration (NHTSA) for all passenger vehicles and light trucks. ADAS features have proven to prevent or mitigate crashes by either alerting or assisting the driver. ADAS typically utilizes a forward-facing camera, which comes standard in modern vehicles to provide limited automation features such as Lane Keeping Assist (LKA), and Lane Centering Assist (LCA) to improve driver safety. These systems rely on the assumption that vehicle …

Predicting Battery Efficiency: A Theoretical Approach, Haiti Schafers

SACAD: Scholarly Activities

The Kansas ElectroRally Races continuously demand faster electric vehicles (EV). When designing a vehicle one of the most important components is the battery. This study was designed to find the following; What is the optimal throttle percentage to run a 36V 20Ah (768Wh) LiFePO4 Rechargeable Battery Pack[1].

The optimal throttle percentage was found with methods detailed in a different section. Based on the performance of the older cars this study choose to focus on 50% and 70%, while obtaining other relevant data to further that inference.

Hyperparameter Tuning For Robust Autonomous Vehicle Vision, Nico D. De Ros

Theses and Dissertations

Classification “flickering,” where the classification of an object changes inconsistently between consecutive video frames, remains a persistent issue in modern object classification algorithms. This problem undermines the reliability of autonomous vision systems and poses significant risks in high-stakes applications such as autonomous vehicles. This thesis explores the use of response surface methodology, a statistical design of experiments technique, to optimize hyperparameters across three object classification pipelines. The first pipeline combines YOLOv8 with SORT to establish a benchmark. The second integrates a Bayesian back-end, while the third employs an exponential smoothing back-end. Hyperparameter tuning was conducted using a two-step process: an …

Advances Towards A Robotic Management Vehicle Suited To Nurse Row Crops To More Efficient Outcomes, Adam Mk Gronewold

Dartmouth College Ph.D Dissertations

Enhancing agricultural production while reducing input costs remains a central challenge in modern row-crop management. Recent advances in computation, imagery, and sensors are enabling more efficient practices across various agricultural domains, and automation technologies are increasingly available to manage tasks central to perennial crop development. Automation in row-crop agriculture, by contrast, lags behind. This thesis explores utilizing small, unmanned ground vehicles to transform row cropping through the implementation of unconventional, in-season management strategies. The first focus of this work considers improvements to nitrogen fertilization using small, autonomous vehicles. An agronomy experiment in corn assessed the effects of gradually applying nitrogen …

Adaptive Core Materials For Wireless Power Transfer: Evaluating Mr Fluid In Static And Dynamic Scenarios, Abrer Mohsin Samin, Daniela Wolter Ferreira Touma

Shelby Hall Graduate Research Forum Posters

This research introduces the behavior of Magnetorheological (MR) material as a core for Wireless Power Transfer (WPT) and Dynamic Wireless Power Transfer (DWPT) systems. MR fluids are flexible and easily fabricable material, although they offer a lower magnetic permeability compared to conventional Ferrite cores. The main objective of this research is to investigate the potential of MR fluid as a core for static and dynamic WPT system if it improves transfer efficiency, specially under misalignment and movement. MR fluids, known for their ability to rapidly change their rheological properties in response to magnetic fields, support the power transmission between transmitter …

Comparative Evaluation Of Linear Regression, Cross Validation And Regularization Approaches In Multivariate Data Analysis, Ransford Owusu, Felix Yeboah, Francis Effah Boateng

Data Science and Data Mining

This study evaluates linear regression and its enhanced variants incorporating cross-validation and regularization techniques for high-dimensional, multivariate datasets. We address challenges such as multicollinearity and overfitting. Methods including Ridge, LASSO, and Elastic Net are compared against ordinary least squares regression. Empirical analysis using an automobile dataset for fuel efficiency prediction shows that while OLS regression captures basic relationships, its limitations are mitigated through regularization and cross-validation, resulting in improved model interpretability. The findings provide a comprehensive framework for predictive modeling in complex data environments and offer insights into statistical methodology and practical applications in the automobile industry.

Navigating The Future Advancing Autonomous Vehicles Through Robust Target Recognition And Real-Time Avoidance, Mohammed Ahmed Mohammed Hussein

Theses and Dissertations

The problem being tackled by this thesis is a very important one and very relevant to our days and times: it is about making improved target recognition and enhanced real-time response skills in AVs under simulated conditions. Our plan is to put some enhanced sensory capabilities into these vehicles and see if that makes them safer and more reliable. We are using as our base a particular object recognition algorithm (YOLOv7) and a particular simulation environment (CARLA). We utilized the CARLA 0.9.14 simulator on Ubuntu 20.04 as a more stable option than the initially used CARLA 0.9.15 on Ubuntu 22.04, …

Performance And Emissions Characteristics Of Multi-Cylinder Direct Injection Diesel Engine Fuelled With Diesel/Biodiesel And Toluene Additives, Hagar Alm-Eldin Bastawissi, Medhat Elkelawy Prof. Dr. Eng., Mohammed Osama Elsamadony Dr. Eng., Moustafa Ghazaly Eng.

Journal of Engineering Research

This study explores the impact of using a diesel, biodiesel, and toluene additive fuel blend in a multi-cylinder direct injection diesel engine, focusing on both performance and emissions characteristics. Biodiesel, made from renewable sources like vegetable oils, is often added to diesel to reduce reliance on fossil fuels and improve combustion due to its higher oxygen content. In this work, a 45% biodiesel blend (B45) led to significant reductions in particulate matter (PM) emissions by up to 40% compared to conventional diesel. Additionally, carbon monoxide (CO) and hydrocarbon (HC) emissions decreased by up to 30% and 25%, respectively, due to …

Effect Of Dual-Fuelled Cng And Gasoline On Spark Ignition Engine Performance And Emissions Behaviors At Different Loads, Medhat Elkelawy Prof. Dr, Eng., M.M. Bassuoni Prof. Dr., Hagar Alm-Eldin Bastawissi, Saied I. Haiba Eng.

Journal of Engineering Research

Engine emissions are one of numerous factors that have detrimentally affected the environment, such as global warming, which is the result of growing exhaust gases, practically carbon dioxide (CO2). These emissions have substantially influenced researchers to develop strategic initiatives to minimize the carbon contents of fuels. The purpose of this research is to investigate the characteristics of internal combustion (SI) engines fueled by gasoline and compressed natural gas (CNG) blends. The experiments are performed using a HONDA 4-stroke, single-cylinder, and air-cooled SI engine. Five CNG concentrations are evaluated, the concentrations range from 0.5 to 2.5 L/min with a 0.5 L/min …

Dashar: An Implementation Of Augmented Reality Technology For Automotive Applications, Trevor D. Brown

Masters Theses & Specialist Projects

Since the advent of the modern automobile, manufacturers have provided means of tracking various critical data points associated with automobile operation, with the most prominent and standardized method being the instrument cluster. These data points include, but are not limited to, automobile speed, engine speed, fuel level, oil temperature, radiator (water) temperature, and battery charge. While this data is updated in real-time as the automobile is running, traditional instrument clusters cannot be modified or adjusted to the automobile driver’s needs, unless extensive after-market modifications are made. These modifications can be expensive, and require great understanding of the automobile’s assembly.

Alongside …

Integration Of Agile Approach Into The Implementation Of The Iso/Sae 21434 On Top Of The V-Model To Enable Continuous Secure-By-Design Automotive Cybersecurity Development, Pooja Patil

Master's Theses and Doctoral Dissertations

The rapid evolution of technology is revolutionizing the automotive industry, with connected and autonomous vehicles at the forefront. These vehicles rely on complex digital ecosystems to enhance safety and efficiency but are increasingly vulnerable to cybersecurity threats. Addressing these challenges requires following robust development methodologies, while complying with cybersecurity standards. This study introduces a framework that merges the widely used agile methodology practices with the ISO/SAE 21434 standard to support secure-by-design automotive product development. Traditional development approaches like the V-model provide structured and linear project phases, but they often lack the flexibility and the ability to adapt to evolving security …

Computational Investigation Of Underbody Slant Angle Variation Effect On A Hatchback Vehicle, Nufile Uddin Ahmed

College of Graduate Studies: Theses & Dissertations

Electric Vehicles, despite many advantages over their gasoline-powered counterparts, have the following main challenges towards mass adoption – the charging infrastructure and the range of the vehicle. Among the myriads of factors affecting the range, the coefficient of drag and the required power to overcome it are noteworthy. This study aims to investigate the effect of rear underbody slant angle on a common, simplified hatchback-shaped Electric Vehicle. The rear underbody slant angles (upward) assessed were 0°, 5°, 10°, and 15° and they were subjected to three freestream velocities representative of urban (16 m/s), highway (25 m/s) and interstate (40 m/s) …

Influence Of Time Pressure And Flood Information Type On Flood Alert Effectiveness In Driving, Katherine R. Garcia, Scott Mishler, Jing Chen

Psychology Faculty Publications

Flood alerts are a means of risk communication that alerts the public to potential floods. The purpose of this research was to investigate factors that affected drivers' understanding and actions given a flood presented through a mobile navigation application. Two experiments were conducted to examine the effects of time pressure and type of flood information on drivers' planned actions when faced with potential flooding. Participants were asked about their planned actions given one type of flood information in a driving scenario either with or without time pressure. Our results indicated significant differences in participants' behaviors across the different flood information …

Intelligent Systems For Synergistic Optimization Of Vehicle Dynamics And Energy Consumption In Connected And Automated Vehicles, Aman Poovalappil

Dissertations, Master's Theses and Master's Reports

This dissertation focuses on the development and validation of on-board, real-time estimation algorithms and the investigation of energy-saving strategies for modern light-duty vehicles, including connected and automated vehicles (CAVs). The accurate estimation of key vehicle parameters is critical for enhancing energy efficiency, enabling advanced driver-assistance systems (ADAS), and optimizing vehicle performance and energy efficiency. First, this research introduces a novel real-time algorithm to dynamically learn vehicle mass using readily available sensor data. Based on longitudinal vehicle dynamics, a sensitivity analysis was conducted to identify the conditions under which mass estimation is most robust. The algorithm was extensively validated through on-road …

ต้นแบบระบบตรวจจับ คัดแยก และป้องกันภัยจากอากาศยานไร้คนขับขนาดเล็ก, รักษ์ตะวัน พูลสุวรรณ

Chulalongkorn University Theses and Dissertations (Chula ETD)

งานวิจัยนี้ได้นำเสนอการออกแบบและความเป็นไปได้ของระบบกระบวนการหลายขั้นตอนแบบครบวงจรสำหรับการตอบโต้โดรน (UAV) โดยใช้แพลตฟอร์ม Software-Defined Radio (SDR) ในกระบวนการแรก การตรวจจับใช้วิดีโอเรดาร์แบบคลื่นต่อเนื่องปรับความถี่ (FMCW) ที่มีความถี่พาหะ 2.4GHz สำหรับการตรวจจับและติดตามเป้าหมายทางอากาศ ระบบย่อยนี้ได้รับการออกแบบมาเพื่อระบุระยะทางและความเร็วของวัตถุที่เข้ามา ขั้นตอนที่สองเกี่ยวข้องกับการจำแนกสัญญาณคลื่นความถี่วิทยุ (RF) โดยใช้โครงข่ายประสาทเทียมแบบคอนโวลูชัน (CNN) เพื่อวิเคราะห์สัญญาณควบคุมและการถ่ายโอนข้อมูลที่ส่งระหว่างโดรนและผู้ควบคุมภายในย่านความถี่ ISM (2.4GHz) ขั้นตอนสุดท้ายคือการทำให้ภัยคุกคามที่ได้รับการยืนยันเป็นกลางโดยใช้เทคนิคการตอบโต้ทางอิเล็กทรอนิกส์สองวิธี วิธีแรกคือการปล่อยสัญญาณรบกวนเพื่อขัดขวางการเชื่อมโยงคำสั่งและการควบคุมในย่านความถี่ ISM (2.4GHz) เพื่อแยกโดรนออกจากผู้ควบคุมได้อย่างมีประสิทธิภาพ ในขณะเดียวกัน ระบบจะทำการหลอก GPS ภายในย่านความถี่ L1 โดยการส่งสัญญาณ GPS L1 จำลองในย่านความถี่ 1.575GHz เพื่อทำให้ตำแหน่งของโดรนสับสน ระบบนี้ได้ทดสอบกับโดรน DJI Mini 4K ที่มีพื้นที่หน้าตัดเรดาร์ 0.01 ตารางเมตร โดยมีผลลัพธ์คือระยะการตรวจจับ 20 เมตร และระยะการรบกวนและการหลอก GPS ที่ 50 เมตร ภายใต้ข้อจำกัดกำลังส่งที่ 20 dB ตามข้อจำกัดของย่านความถี่ ISM

Development And Verification Of Testing Platform For Torque Vectoring Controller, Nicholas Petersen

Dissertations, Master's Theses and Master's Reports

A foremost concept in the automotive industry in recent years has been that of a vehicle “digital twin”. A digital twin is an accurate simulation of a dynamic system for the use of rapid development. These digital twins have a critical advantage over physical testing, which have dominated vehicle development up to now. As the cost of physical testing continues to rise, simulation can deliver rapid system development in a low-cost format. No simulation environment is a perfect representation of reality, however, and physical testing is still necessary to validate systems for use in the real world. This is especially …

Numerical Modelling And Co-Optimization Of Gasoline Fuels For Gasoline Compression Ignition Using Multi Component Approach, Ashwin Karthik Purushothaman

Dissertations, Master's Theses and Master's Reports

Future mobility is expected to rely on a broad spectrum of powertrain technologies, including battery electric vehicles (BEVs), hybrid electric vehicles (HEVs), fuel cell electric vehicles (FCEVs) and traditional internal combustion engine (ICE) vehicles. Despite the shift toward electrification, internal combustion engines are projected to remain a key component of future powertrains, either as the primary power source or as range extenders to generate electricity in hybrid systems. As such, significant research efforts continue to focus on enhancing the efficiency and reducing the emissions of ICEs to meet increasingly stringent regulatory and environmental targets. Gasoline compression ignition (GCI) has been …

Tl-Convlstm: A Transfer-Learning-Based Convolutional Lstm To Identify And Forecast Traffic In The Nextg Environments, Bikash Chandra Singh, Peter Foytik, Rafael Diaz, Sachin Shetty

School of Cybersecurity Faculty Publications

Forecasting and categorizing cellular traffic flows and their types are essential functions in intelligent network systems to ensure efficient network optimization. The ever-evolving nature of 5G networks results in fluctuations in traffic patterns over time, leading to a phenomenon known as model drift. Consequently, accurately predicting and identifying cellular traffic patterns becomes a complex task. To tackle this challenge, this article introduces an innovative approach called TL-ConvLSTM, which combines transfer learning with convolutional long short-term memory (ConvLSTM) to effectively combat model drift and provide precise forecasting and recognition of cellular traffic within the network. To accomplish this, we initiate the …