Automotive Engineering Commons^™

Estimation Of Unmeasurable External Disturbances Of A Dynamic Object Based On A Robust Adaptive Kalman Filter, Bunyod Mamurjon Ugli Buronov

Technical science and innovation

This article considers the problem of directly estimating unmeasurable external disturbances acting on a dynamic object under the condition that the state vector of the object is available for measurement. In the considered case, the problem is reduced to the estimation of an unknown input of a dynamic system. It is shown that when the system state is measurable, both a direct inversion scheme based on the object’s dynamic equation and filtering methods that eliminate the need for coarse numerical differentiation can be applied. For slowly varying disturbances, a random walk model with a small process noise covariance is proposed, …

Reducing Drag Of Vehicles With Half-Stepped Cylinder Surfaces Part I: Numerical Optimization, Ryan Moffit, Hamid Rahai, Komal Gada

Mineta Transportation Institute

Aerodynamic drag is a major source of energy loss for vehicles, increasing fuel consumption, reducing the driving range of electric vehicles, and contributing to greenhouse gas emissions. For a vehicle, the major components of its drag are pressure and viscous drag. Engineers have developed a variety of strategies to reduce drag, including streamlined vehicle designs, surface modifications, and devices that alter airflow around the vehicle. This research focuses on reducing the viscous drag. Specifically, this study investigates whether microscopic surface features called half-stepped cylinder arrays can reduce skin friction by altering the turbulent boundary layer and promoting smoother airflow near …

Empirical Study Of Impact Of National Science And Technology Program On Development Of New Energy Vehicle Industry, Dan Du, Xiaoyong Shi, Yong Cao, Yang Yang, Yao Yang

Bulletin of Chinese Academy of Sciences (Chinese Version)

The national science and technology program serves as the primary instrument for the government to support scientific and technological innovation through financial funding. This study employs impact assessment methods to conduct an empirical study on the path of technological development in the field of new energy vehicles and its economic impact supported by the national science and technology program, and explores the role of scientific and technological support in forming new quality productive forces. It was found that the task layout of the national science and technology program has expanded from the midstream of the industrial chain to both upstream …

Project-Based Conversion Versus Prototype-Based Instruction In Automotive Teacher Education, Ramdhani Ramdhani, Sriyono Sriyono, Wahid Munawar, Raafi Rizki Maulana, Apriyansah Bahrudin

Jurnal Pendidikan: Teori, Penelitian, dan Pengembangan

The transition to electric and hydrogen mobility is reshaping the competencies that automotive vocational teaching requires, yet institutions with limited equipment must choose between authentic learning designs without evidence of what each produces. Indonesian research to date has built substitute learning media and reported feasibility ratings rather than measured learning. This study asks what cognitive and psychomotor gains two contrasting designs produce and how those gains compare. Two pre-experimental studies were conducted in one automotive teacher education programme in Indonesia. Study A used a time-series design across three project cycles of 200 minutes in which 15 undergraduates converted a combustion …

Performance Evaluation Of Controllers Using Fuzzy Delphi And Ahp Techniques, Kamala. R. Aliyeva, Nihad Mehdiyev, Shamil Mehdi

Chemical Technology, Control and Management

This study introduces an enhanced decision-support framework that integrates the Fuzzy Delphi method with the Analytic Hierarchy Process (AHP) to improve controller tuning and performance evaluation in uncertain environments. Traditional tuning techniques typically depend on crisp expert judgments and deterministic performance indices; however, industrial control systems are characterized by nonlinear behaviors, uncertain parameter variations, and subjective expert evaluations that are often vague or inconsistent. The Fuzzy Delphi procedure is applied to systematically gather, filter, and consolidate expert insights, enabling a refined set of performance criteria such as stability margins, robustness to disturbances, settling time, overshoot, control effort, and energy consumption …

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 …

Optimal Management Of Electric Vehicle Fast Charging Stations Via Lyapunov Optimization And Reinforcement Learning, Mohammad Hossein Abbasi

All Dissertations

The transportation sector is responsible for 28% of global energy-related emissions, with road transport accounting for most of these emissions. While electric vehicles (EVs) are essential for decarbonizing transportation, widespread adoption depends on fast, efficient charging. Fast charging reduces charging time but accelerates battery degradation, whereas slow charging increases range anxiety. In addition, fast charging stations (FCSs) impose significant stress on distribution grids, making their operation a critical challenge. Optimizing FCS operation can conflict with EV fast-charging objectives, yet existing research largely treats these problems independently despite their strong interdependence.

Current fast-charging methods focus on individual cells or small battery …

Smart Process Planning For Automated Fiber Placement, Matthew J. Godbold

All Dissertations

Automated Fiber Placement (AFP) is a preeminent manufacturing technology for producing high-performance composite structures, offering precise material placement, reduced waste, and the potential for highly optimized lightweight designs. While AFP has been widely adopted in aerospace applications, its broader use across industries such as automotive, wind energy, maritime, and sporting goods remains limited. A key barrier to wider adoption is the traditional separation of design, manufacturing, and inspection processes, which drives up cost and results in inefficiencies, sub-optimal designs, and limited feedback between lifecycle stages. In current practice, manufacturing is treated as an isolated process, disconnected from early-stage design decisions …

Integrated Power, Energy, And Thermal Management For Autonomous Hybrid Off-Road Vehicles: Multi-Timescale Modeling, Predictive Control, And Resilient Thermal Design, Anirudh Sundar

All Dissertations

Electrification and autonomy are increasingly important for off-road vehicles operating in construction, agriculture, mining, defense, and other demanding environments. These platforms must deliver high tractive power under unstructured terrain, harsh ambient conditions, low-speed operation, and large auxiliary loads. While hybrid and electrified powertrains offer improved efficiency, mobility, and auxiliary power capability, they also introduce significant challenges in managing tightly coupled power, energy, and thermal subsystems. In particular, lithium-ion batteries, power electronics, electric machines, and internal combustion engine-generator systems operate across different temperature limits and timescales, requiring coordinated management to ensure efficiency, durability, and safe operation. This dissertation develops modeling, planning, …

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 …

Modeling And Generating Crash Avoidance Behaviors In Safety-Critical Vehicle–Pedestrian Interactions Using Deep Reinforcement Learning, Qingwen Pu

Civil & Environmental Engineering Theses & Dissertations

Traffic crashes between vehicles and pedestrians arise from complex, split-second interactions in which both parties make rapid evasive decisions. Four fundamental gaps persist in existing research. Surrogate safety measures assume linear trajectories, failing to capture the curved movements of turning vehicles and crossing pedestrians at intersections. Single-agent modeling treats one party as a fixed obstacle, ignoring the joint decision-making that governs near-miss outcomes. The effect of vehicle type on pedestrian avoidance behavior—whether pedestrians respond differently to automated vehicles (AVs) than to human-driven vehicles (HDVs)—remains poorly understood. Finally, automated driving system development is hampered by a severe scarcity of large-scale, behaviorally …

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 …

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 …

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 …