Automotive Engineering Commons^™

Optimizing Maintenance Routes For Highway Infrastructure Using Leader-Follower Autonomous Vehicles, Qing Tang, Chenxi Chen, Xianbiao Hu, Yuxin Ding, Tianjia Yang

Civil & Environmental Engineering Faculty Publications

The Autonomous Truck Mounted Attenuator (ATMA), a leader–follower style connected and automated vehicle system, enhances safety during transportation infrastructure maintenance in work zones. However, the significantly lower speed of ATMA, compared to regular vehicles, causes moving bottlenecks that reduce roadway capacity and prolong queuing, leading to further delays. Different ATMA routes lead to varying patterns of time-dependent capacity drop, affecting the user equilibrium traffic assignment and resulting in differing system costs. This study aims to optimize ATMA routing within a network to minimize the system cost associated with its slow-moving operation. To this end, a queuing-based traffic assignment approach is …

Machine Learning-Based Lifetime Prediction Of Lithium Batteries: A Comparative Assessment For Electric Vehicle Applications, Abdelilah Hammou, Raffaele Petrone, Demba Diallo, Boubekeur Tala-Ighil, Philippe Makany Boussiengue, Hicham Chaoui, Hamid Gualous

Electrical & Computer Engineering Faculty Publications

This paper evaluates and compares four data-driven methods (Gaussian Process Regression (GPR), echo state network (ESN), gated recurrent unit (GRU), and long short-term memory (LSTM)) for lithium-ion capacity prognostics adapted to electric vehicle conditions. This comparison aims to find the most efficient prognosis method considering two constraints: the limitation of computational power and the unavailability of on-board capacity measurement that requires full charge and discharge conditions. The machine learning models are trained using capacity values estimated under vehicle conditions. The ageing data is collected from cycling tests of two battery chemistries, Lithium Fer Phosphate (LFP) and Nickel Manganese Cobalt (NMC), …

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 …

A Comparative Analysis Of Explainable Ai (Xai) Techniques For Transparent And Reliable Image Classification, Sovon Chakraborty, Shakib Mahmud Dipto, Kevin R. Pilkiewicz, Michael L. Mayo, Pratip Rana

Computer Science Faculty Publications

Evaluating the trustworthiness of black-box machine learning models remains a significant methodological challenge. Their lack of transparency and interpretability limits applicability, because stakeholders often seek transparency before trusting the results of black-box machine learning models. Explainable AI (XAI) methods provide for human-understandable justifications and informed decision-making of these black-box architectures. Therefore, it is imperative to select the proper XAI model tailored to specific tasks. In this research, we focus on examining four XAI techniques: PEEK, LRP, GRAD-CAM, and LIME to understand how they perform against each other for image classification tasks. We evaluate the performance, robustness, generalizability, noise stability, and …

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.