Automotive Engineering Commons^™

Control Strategies For 6-Dof Quadcopter Uavs: Cascade Pid Stabilization In White Noise Conditions, An Vo Van, Hung Ha Duy

Makara Journal of Technology

In this study, a cascade PID control structure is proposed and implemented for a 6-degree-of-freedom (6-DOF) unmanned aerial vehicle (UAV) to enhance stability and trajectory tracking capabilities under both noise and non-noise conditions. The controller was designed based on the Tyreus–Luyben tuning method and was evaluated using quantitative metrics, including rise time, settling time, overshoot, and steady-state error. Simulation results on MATLAB/Simulink show that the controller achieves high performance in angular channels (ϕ, θ, ψ) and altitude (z) with a short rise time (< 2s), slight overshoot (< 1%), and nearly eliminated steady-state error. However, the horizontal position channels (x, y) have a longer settling time (~110s) and are sensitive to white noise. Quantitative comparisons with other control methods show that the cascade PID outperforms the standard PID in terms of accuracy and stability, achieving a performance comparable to LQR under noise-free conditions, but is less robust in the presence of noise than advanced methods like SMC and MPC. These results confirm the feasibility of cascade PID in UAV applications and indicate potential future improvements by integrating nonlinear, adaptive, or intelligent control strategies.

Dem Simulations For Tractive Performance Of Rigid Wheel In Granular Media, Aidan Noah Dickerson

Theses and Dissertations

Accurately predicting vehicle mobility in granular media is essential for evaluating off-road mobility in agriculture, defense, and planetary exploration. Traditional empirical models often fail in capturing complex micromechanics of soil deformation, especially under dynamic conditions such as high slips and maneuvering. This study demonstrates the value of the discrete element method (DEM) in modeling wheel-soil interactions with higher fidelity. Using Altair EDEM and pre-calibrated GEMM materials, simulations were conducted for a range of forward (-5.9% to 54.8%) and side slip angles (3°, 6°, 12°) in dry sand. DEM enabled detailed analysis of sinkage, traction forces, and lateral loads, revealing trends …

Study On The Knock Resistance Offered By Thermally Stratifying Water Injections In A Single Cylinder Spark Ignition Engine, Aditya Datar

All Theses

Stochastic end-gas autoignition in SI engines, commonly called ‘knock’, limits attainable engine efficiencies. Multiple pathways to extend SI engine operation into knock-limited regions have been studied, including direct water injection (DWI). This study employs single-cylinder engine experiments and modeling to investigate the knock resistance offered by compression stroke water injections, which have shown to thermally stratify the cylinder in HCCI. In SI, thermally stratifying injections are expected to forcibly widen the cylinder temperature distribution by preferentially cooling the cylinder periphery. The end-gas is in the cylinder periphery; therefore, a cooler end-gas would result in longer ignition delays, thus providing knock …

Development And Validation Of A Thermal Model For An Electric Vehicle Transmission, Ghazal Rajabikhorasani

Dissertations

This research investigates the thermal behavior of a high-speed electric vehicle (EV) helical gearbox with the goal of improving the prediction accuracy of component temperatures and total power losses under a range of operating conditions. The study focuses on developing a physics-based lumped-parameter thermal network model capable of capturing the main heat generation and dissipation mechanisms within the transmission. The model integrates experimentally validated loss correlations for gears, bearings, seals, and churning, as well as convective and radiative heat transfer paths.

The thermal network model was coded in MATLAB and validated through a series of controlled experiments performed on an …

Power Distribution Controller For Formula Sae Vehicles, Michael Yuen

Electrical Engineering

The Power Distribution Controller (PDC) is designed for low-voltage (12V) automotive applications, specifically Formula SAE vehicles. It aims to replace the current and outdated MOSFET-based system, which suffers from inefficiencies such as lossy current sense resistors and limited configurability. Instead, this new system uses a PROFET-based architecture controlled over the Controller Area Network (CAN) and an updated microcontroller, enabling intelligent power management and data logging.

Designed with FSAE regulations in mind, the PDC not only enhances the reliability of low-voltage systems but also provides a quickly adaptable solution to fuse boxes. It achieves this by providing firmware-adjustable overcurrent protection, incorporating …

In-Field Tractor Operational Load Profile Generation In Support Of Advanced Tractor Testing In Mixedmode Power, Andrew Donesky

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation addresses the need to better characterize real-world tractor power requirements across drawbar, power take-off (PTO), and hydraulic modes to support more representative tractor testing. Conventional testing protocols, such as OECD Code 2, emphasize steady-state performance under controlled high-load conditions, which do not reflect the mixed and dynamic demands of modern field operations. To address this gap, a Tractor Instrumentation System (TIS) was developed, validated, and deployed to collect high-resolution, mixed-mode power data during planting, anhydrous ammonia application, and grain cart operations. The TIS integrates physical sensors, including custom load pins, hydraulic pressure/flow sensors, and a redesigned PTO torque …

Tradespace Exploration For Multiple Collaborative Vehicles, Mrunal Deshmukh

All Theses

Modern military operations demand systems that adapt to uncertain, rapidly changing missions across diverse terrains. Traditional single-platform vehicle design is insufficient for such complexity. This research introduces a hierarchical tradespace exploration framework for designing and evaluating families of heterogeneous ground vehicles under a System-of-Systems (SoS) architecture. The framework treats vehicle design as a co-optimization problem, where a “parent” vehicle (e.g., a Squad Multipurpose Equipment Transport) coordinates specialized “child” vehicles for reconnaissance, amphibious tasks, terrain traversal, and stealth missions. Unlike conventional approaches that optimize vehicles individually, this study emphasizes collaborative performance, resource sharing, and adaptability at the family level. Central to …

Multi-Modal Data-Efficient Learning For 3d Machine Vision, Zhimin Chen

All Dissertations

The rapid progress of 3D computer vision has enabled a wide range of applications in autonomous driving, robotics, and augmented reality. Despite this growth, training robust 3D perception models remains challenging due to limited labeled data, the complexity of integrating multiple modalities, and the inherently imbalanced and long-tailed nature of 3D datasets. This dissertation addresses these challenges by proposing data-efficient, multi-modal learning frameworks that improve the accuracy, generalization, and scalability of 3D scene understanding.

In the semi-supervised setting, this work presents novel approaches that combine limited annotations with large amounts of unlabeled data to enhance 3D object classification and retrieval. …

Hybrid Learning For Rough Terrain Navigation Of Actively Articulated Wheeled Vehicles, Dhruv Mehta

All Dissertations

Conventional wheeled ground vehicles have been used for rough terrain navigation in the recent years. They consist of a chassis connected to wheels through passive, semi-active, or active suspension systems. However, their fixed configurations limit mobility and maneuverability, constraining their ability to autonomously navigate diverse and rough terrains. Autonomous Ground Vehicles (AGVs) face significant challenges in this regard, including varying terrain roughness, soil hardness, and obstacle crossing.

To address these limitations, Actively Articulated Wheeled Vehicle (AAWV) architectures have recently emerged, offering real-time geometric adaptability. AAWVs have chassis and wheels connected via articulated serial or parallel linkages. However, increased articulation introduces …

Data-Driven Discovery Of Finite-Dimensional Koopman Operator For Modeling And Control Of Uncrewed Ground Vehicles, Ajinkya Joglekar

All Dissertations

This dissertation advances data-driven modeling and adaptive control techniques for Uncrewed Ground Vehicles (UGVs), with a focus on autonomy in mission-critical and safety sensitive environments. UGVs are deployed across a wide spectrum of domains, from structured manufacturing shop floors to unstructured off-road terrains, including planetary exploration, precision agriculture, and disaster response. These platforms, operating in dull, dirty, and dangerous conditions, demand autonomy that is both adaptable and robust. While traditional model-based control methods offer interpretability and robustness, they struggle with unmodeled dynamics, parameter variations, and integration of high-dimensional sensing. Conversely, modern machine learning approaches can directly exploit sensory data but …

Influence On Shot Peening And Blast Polishing For Rotating Bending Fatigue Strength Of Vacuum Carburized Steel With Circumferential Notch, Yuji Kobayashi, Hayato Taniguchi, Kiyotaka Masaki

15th International Conference on Shot Peening

In order to improve fuel efficiency in automobiles, weight reduction is necessary as well as improving engine efficiency. For transmission gears, thickness reduction is necessary for weight reduction. When the thickness is reduced, the cross-sectional area becomes smaller, and the load stress increases. Therefore, higher fatigue strength is required. Most gears carry out carburizing. Shot peening is often used to improve the fatigue strength of carburized heat-treated parts. After shot peening, compressive residual stress is introduced, but at the same time, surface roughness is increased. Therefore, the processing conditions of shot peening are very important. Blast polishing is a processing …

Adaptation Of Shot Peen Parameters For Gear Geometry, David J. Breuer, Beth Matlock

15th International Conference on Shot Peening

Shot peening is a well established process for the surface enhancement of gearing. Gearing is a primary example of a high cycle fatigue application that can benefit from residual stress enhancement. Designing shot peening parameters to specific gear geometry based on material, heat treatment, and surface finish is a more precise way to achieve better performance outcomes. One of the best tools to assist in the optimal shot peening is x-ray diffraction (XRD) and its ability to measure small differences that can result in significant performance outcomes. XRD residual stress measurements are a direct measurement of elastic strain. The diffraction …

The E-Strip® As A Tool For Predictive Maintenance To Monitor And Control Shot Peening Processes, Walter A. Beach, Scott Glasier

15th International Conference on Shot Peening

The primary objective of this paper is to demonstrate the E-Strip® is capable of providing real-time feedback to the machine controller for making necessary process adjustments due to external forces, such as machine wear. Adjustments may include regulating air pressure and shot flow within pre-defined tolerances dictated by specification. It is anticipated that this integrated approach will significantly reduce variations in intensity levels observed from part to part and lot to lot.

Application Of Burnishing Process Expected To Frictional Heat To Non-Oriented Electromagnetic Steel Sheet, Yuji Kobayashi, Masato Okada

15th International Conference on Shot Peening

Burnishing is a technology used to improve the surface roughness of metals. On the other hand, it is expected that the metal structure near the surface will change due to strong distortion.

The magnetic properties of electromagnetic steel sheets depend on large crystal grains and fine crystals near the surface[1]. In particular, thinner fine crystal grain layers on the surface are expected to reduce iron loss. In this study, the power generation characteristics of Burnished electromagnetic steel sheets were evaluated.

Electromotive force waveform was evaluated by rotating the laminated electromagnetic steel sheets and using a spindle motor. The electromotive force …

The Effects Of Shot Peening Highly Loaded Compression Springs, David J. Breuer

15th International Conference on Shot Peening

The compression spring in this test study is typical of one used in a demanding off-road vehicle suspension. The cyclic loads applied during fatigue tests were severe enough to cause failure in approximately 11,000 cycles without shot peening.

The objectives of this study were the following: (1) Design a compression spring similar to those used in the off-road recreational industry. (2) Design & manufacture a fatigue test stand that could withstand high loads for months of testing. (3) Generate a matrix of shot peening treatments to produce different amounts of residual compressive stress. (4) Measure the shot peening residual compressive …

Development And Validation Of A Thermal Model For An Electric Vehicle Powertrain, Claudia Fajardo

Waldo Library Student Exhibits

No abstract provided.

Resilient Control Framework For Ev Motor Drive System Subject To Cyber-Physical Security, Ali Arsalan

All Dissertations

The electric drive system (EDS) in electric vehicles (EVs) is one of the key safety-critical components. As IoT-enabled communication infrastructure for modern cyber-physical automotive systems continues to evolve, the importance of securing EDS against cyber threats along with physical faults, has become increasingly prominent. Among physical faults, power switches are particularly vulnerable and exhibit the highest susceptibility to open-circuit faults (OCFs). A compromised EDS, whether due to cyber threats or physical issues, can lead to excessive mechanical vibrations, increased thermal stress, fluctuations in electromagnetic torque, and elevated total harmonic distortion. These factors can substantially undermine traction control stability and jeopardize …

Robustness Investigation, Detection, And Defense Of Deep Learning Models Against False Data Injection, Amirhossein Nazeri

All Dissertations

This dissertation addresses the critical challenge of adversarial robustness in deep learning systems, focusing on two fundamental domains: time-series prediction and object detection. As these AI systems become increasingly deployed in safety-critical applications from power grid management to autonomous vehicles their vulnerability to adversarial attacks poses significant risks to infrastructure and human safety.

The first contribution introduces a novel stealthy black-box False Data Injection (FDI) attack specifically designed for quasi-periodic time-series data. Unlike existing attacks that produce easily detectable anomalies, our method generates adversarial perturbations that preserve the underlying periodicity and statistical properties of the data, effectively bypassing traditional anomaly …

Secure Control And Trust Evaluation Framework For Autonomous Transportation Systems, Grace Muriithi

All Dissertations

This dissertation advances the cybersecurity of hybrid tracked vehicles (HTVs) and ship power systems (SPSs) by developing innovative cyber-attack models and corresponding defence frameworks. First, we formulate stealthy false-data-injection attacks (FDIAs) on HTV energy-management systems as a partially observable Markov decision process (POMDP) solved via deep reinforcement learning. A novel sniffing-based reward function guides the attacker to covertly degrade battery capacity and energy efficiency, which we evaluate using custom stealth–impact metrics and a sliding-window anomaly detector (Isolation Forest with Dynamic Time Warping). Additionally, we model sophisticated control-layer attacks in HTVs, including reinforcement-learning-optimised replay attacks and denial-of-service (DoS) attacks targeting generator-speed …

Decision Field Theory For Human-Multi-Robot Collaboration: Human-Centric Decision-Making For Multi-Robot Systems, Ryan Mbagna Nanko

All Theses

At first glance, choosing between an apple and an orange appears to be a straightforward matter of personal taste; however, this seemingly simple preference opens a window into the multifaceted world of decision-making, revealing the complex interplay of cognitive processes, psychological, and behavioral-economic principles that guide our choices \cite{bandyopadhyayRoleAffectDecision2013}. By unpacking these nuanced perspectives, we uncover insights that can drive more effective human-robot interaction and collaboration.

Modeling human cognition requires understanding the evolution of choice utility and the influence of emotions. Decision Field Theory (DFT) stands out by capturing the fluctuating nature in human preferences over time, explaining why choices …

Advancing Life Cycle Assessment For Environmental Sustainability Of Carbon Fiber-Reinforced Polymer Composites (Cfrps)), Hao Chen

All Dissertations

Carbon fiber-reinforced polymer composites (CFRPs) have emerged as promising materials, particularly for lightweight applications, with the potential to reduce environmental impacts across multiple sectors, including automotive, aerospace, and renewable energy. However, fully realizing their sustainability potential requires a more comprehensive and context-specific understanding of their environmental performance throughout the entire life cycle—from raw material production to end-of-life management.

This dissertation advances life cycle assessment (LCA) practices for CFRPs by addressing key challenges across multiple phases of the CFRP life cycle. First, I conducted a critical review and meta-analysis of carbon fiber manufacturing, revealing substantial variability in reported data on energy …

Algorithms For Combined Regular Synthesis Of Controller Parameters In Control Systems For Dynamic Objects, Khusan Zakirovich Igamberdiev, Latafat Abbas Gizi Gardashova, Yulduz Mukhtarkhodjayevna Abdurakhmanova, Uktam Farkhodovich Mamirov

Technical science and innovation

Nonlinear control system that includes m-dimensional input control signal and extended (n+s) - dimensional state vector, the last s components of which form a vector of unknown parameters θ satisfying a general difference equation is being considered. The quality criterion is determined by the loss function. The optimal control must satisfy the Bellman equation with respect to the optimal loss function. To be defined an approximate solution that preserves an active use of information. For this purpose, the system is linearized in accordance to the nominal trajectory. This problem is seen as incorrectly stated. The values of the preliminary data …

Comparative Analysis Of Gas And Mechanical Emissions From Electric Cars And Internal Combustion Engine Vehicles, Bakhtiyor Akhmatjonovich Kosimov

Technical science and innovation

This article analyzes the environmental impact of modern cars, in particular the amount of harmful substances emitted into the environment by electric cars and internal combustion engine cars, and provides scientific information on the substances that are released from cars in the form of not only gaseous emissions, but also dust particles generated by the mechanical wear of the brake system and tires. At the same time, this article also takes a scientific approach to the wear rates of brake pads and tires, their impact on environmental safety, and the level of dispersion of the microdust generated. Comparative tables have …

A Comprehensive Review Of Natural Gas-Diesel Dual-Fuel Engines: Efficiency, Emissions, And Engine Performance, Medhat Elkelawy Prof. Dr, Eng., E. A. El Shenawy Prof. Dr., Hagar Alm-Eldin Bastawissi Prof. Dr. Eng., Mohamed Mostafa Shafey Eng

Journal of Engineering Research

Natural gas (NG) diesel dual-fuel systems have emerged as a promising advancement in internal combustion engine (ICE) technology, offering significant potential for reducing emissions, while maintaining high fuel efficiency and performance standards. This review critically examines the combustion characteristics, operational performance, emissions mitigation potential, and the engineering challenges associated with engine modifications and fuel system compatibility. Furthermore, the role of dual-fuel technology within broader global climate change mitigation strategies is explored. Extensive evidence from the literature confirms that NG-diesel dual-fuel engines can achieve substantial reductions in nitrogen oxides (NOₓ) emissions up to 53% particulate matter (PM) by over 60%, and …

Experimental Investigation On The Effect Of Using Gasoline With Commercial Additives On Spark Ignition Engines Performance And Emissions Characteristic, Medhat Elkelawy Prof. Dr, Eng., E. A. El Shenawy Prof. Dr., Hagar Alm-Eldin Bastawissi, Emad Mostafa Eng.

Journal of Engineering Research

Gasoline is the primary source of energy in combustion engines, despite some drawbacks, such as knocking inside the engine, incomplete combustion, and the production of high emissions. The main trend has been toward the use of chemical additives as improvers, including oxidizing additives and aromatic hydrocarbon compounds. Both additives have an effect on the combustion process. Oxidizing additives improve the combustion process inside the chamber by adding additional oxygen to the fuel, which helps accelerate flame propagation, such as ethanol and oleo-octane plus. On the other hand, aromatic additives are used to increase the octane number, which in turn enhances …

Enhancing Autonomous Vehicle Resilience Through Engineering Requirements And Snow-Adaptive Lane Detection, Alexandra Marie Masterson

Masters Theses

This thesis investigates two distinct but interrelated challenges in the development of resilient autonomous vehicle (AV) systems: the formalization of engineering requirements for AV perception subsystems and the enhancement of visual lane detection under snow-covered road conditions. In the first study, field experiments were conducted using a campus-deployed autonomous research vehicle to evaluate the impacts of perception related failures including GPS outages, HD map inconsistencies, and weather interference—on vehicle operation. These findings were used to develop a set of qualitative engineering requirements that promote AV resilience through proactive design. In the second study, a custom snow-focused lane detection dataset was …

Effect Of Using Machine Learning To Improve Active Suspension Control For Vehicle Stability, David A. Butz

Masters Theses

This study demonstrates that it is possible to use road surface classification as a means of informing active suspension systems in order to limit their activity. An approach was taken to improve the response of an active suspension control system by classifying road surfaces in near real time. A control system model was developed to represent a full-body vehicle, and an AI was used to analyze road vibration noise. The model was adapted to allow the AI to select from multiple control signals based on the AI’s analysis of road vibration noise. The objective of the study was to demonstrate …

Algorithms & Design Behind Autonomous Uavs And Ugvs Coordinated System, Aashish Dhakal

Honors Theses

Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs), when coordinated effectively, offer substantial potential for automating large-scale tasks—from search and rescue operations to precision agriculture. However, synchronizing these autonomous systems remains challenging, especially in time-sensitive missions requiring precision. This thesis investigates the design and algorithmic coordination of autonomous UAVs and UGVs, examining both single-vehicle scenarios and multi-agent (swarming) approaches. Using the Robot Operating System (ROS) as a communication backbone, I integrate GPS positioning with computer vision techniques through OpenCV, enabling accurate localization and object detection. During the development phase, I validate my methods using ArduPilot Software-in-the-Loop (SITL) simulations within …

Training Safety Control Filters Using High-Dimensional And Un-Labeled Data, Yuxuan Yang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Synthesizing control policies that preserve the safety of autonomous systems is a challenge that remains to be solved. Towards that goal, control barrier functions (CBFs) have been developed as mathematical constructs that can be used in real-time to correct safety-violating nominal actions to ones which preserve the safety of control systems. However, synthesizing CBFs using correct-by-construction methods has not been scalable. Instead, recent research has proposed data-driven approaches for learning CBFs in the form of neural networks. Two main challenges face such approaches: (1) labeling states as unsafe or safe ones requires the knowledge of the states in the backward …

Development Of A Cost-Effective Daq For Measuring Brake Performance In Race Cars, Adrin Alias

2025 Spring Honors Capstone Projects - Archive

This project explores the feasibility of creating a cost-effective data acquisition (DAQ) system for high-speed, real-time brake performance testing of Formula SAE racecars. The research addresses the limitations of the current MoTeC DAQ system currently employed by the team, which is costly and time-consuming to set up for on-car testing. The team will use a brake dynamometer for steady-state comparisons of different brake pad compounds (senior design project), but evaluating real-world performance requires on-car testing. By systematically comparing various hardware platforms, sensors, communication protocols, and storage solutions, this project aims to balance cost-efficiency with reliability and performance. The research evaluates …