Master of Science in Engineering, Youngstown State University, 2025, Department of Mechanical, Industrial and Manufacturing Engineering

A continuously variable transmission (CVT) is a type of transmission used commonly in small engine racing such as snowmobiling, go-karting, or in Society of Automotive Engineers (SAE) Baja racing. These transmissions allow for a constantly varying gear ratio while driving, without requiring the driver to shift gears manually. The continually changing ratio adapts well to varying course conditions such as frequent stops and starts, turns, and jumps. CVTs must be properly installed and tuned to reach their highest level of performance, which is a common difficulty for these complex systems. A MATLAB code has been developed that characterizes the torque, horsepower, and shift profile of a Gaged GX9 CVT. This predictive model may be used to select a tune for a vehicle and evaluate its performance without requiring extensive test time on a track. Multiple setups of the primary and secondary were analyzed, including different primary and secondary springs, flyweights, and ramps. The numerical characterization of torque, horsepower, shift curve, and acceleration has been validated experimentally, through the use of an inertia dynamometer, Kohler CH440Pro 14HP engine, and DynoMiteTM analysis software. Theoretical comparison was completed using free body and kinetic diagrams of the forces acting in the system, which were entered into a MATLAB code.   A new inertia dynamometer system has been installed within Youngstown State University's (YSU) engine laboratory, providing a hands-on application of methods learned in the classroom for students. The new installation has been used by several student groups to date. An operator's manual for the system focusing on safety and proper machine operation has been developed to aid in correct usage of the dynamometer. The new installation and numerical modeling completed has also been used to develop a laboratory for mechanical engineering students in the Dynamic Systems Modeling (DSM) class. Within the lab students will learn t (open full item for complete abstract)

Committee: C. Virgil Solomon PhD (Advisor); Hazel Marie PhD (Committee Member); Fred Persi PhD (Committee Member) Subjects: Applied Mathematics; Automotive Engineering; Mechanical Engineering

Master of Science, The Ohio State University, 2023, Industrial and Systems Engineering

Injection molding is one of the most common and effective manufacturing processes used to produce plastic products and impacts industries around the world. However, injection molding is a complex process that requires careful consideration of several key control variables. These variables and how they are utilized have a great effect on the resulting parts of any particular molding operation. It is vital that the bounds of each control process variable or CPV be analyzed and defined to ensure manufacturing success and produce injected molded parts efficiently and effectively. One such method in which the key CPV of an injection molding operation can be optimized is through the development of a process window. Once developed, operating CPV at values within the boundaries of the window or region will allow a molder to consistently produce parts that comply with the desired performance measures, promoting a stable manufacturing process. Through the use of experimental research, not only was an injection molding process window for one particular molding operation developed but a methodology in which similar windows could be created for other molding operations is also presented. The use of the suggested strategies may allow other molders to develop process windows of their own in a more standardized way and allow them to mold with higher quality standards at increased consistency.

Committee: Jose Castro (Advisor); Allen Yi (Committee Member); Rachmat Mulyana (Advisor) Subjects: Engineering; Industrial Engineering

Master of Science, The Ohio State University, 2019, Mechanical Engineering

The Ohio State University has participated in Advanced Vehicle Technology Competitions (AVTCs) for over 21 years. These competitions challenge universities throughout North American to reengineer a vehicle with technologies advancing the automotive market. This work explores the use of systems engineering practices during the eleventh iteration of the AVTC program, the EcoCAR 3 competition. The document presents the systems engineering process and two case studies implementing the process. The systems engineering process presented is a simplification of the “Vee” and “Agile” systems engineering processes applicable to a high-cost, long-term, prototype program. The process is broken into five stages: Concept Creation and Refinement, Architecture and Metric Creation, Development, Verification, and Assessment and Validation. The two case studies present uses of the process at a low-level applied to a software algorithm and at a high-level applied to an entire project. The first case study reviews the development of a diagnostic algorithm for the automated manual transmission used in the EcoCAR 3 competition vehicle. The team automated a manual transmission and needed an algorithm to detect and isolate failures to components of the transmission system. The concept and requirements for this algorithm are detailed in Chapter 1 before continuing to discussion of development and testing. Testing of the algorithm utilizes a model-based environment. The second case study reviews the construction and execution of a behavioral study project evaluating driver performance during a vehicle to driver transition of an SAE Level 3 partially automated vehicle. Research was conducted in a model-based environment, simulating an autonomous vehicle by utilizing a driving simulator. The project requirements are derived from the applicable parent requirements, implemented, and tested.

Committee: Shawn Midlam-Mohler Ph.D. (Advisor); Giorgio Rizzoni Ph.D. (Advisor); Lisa Fiorentini Ph.D. (Committee Member); Sandra Metzler Ph.D. (Committee Member) Subjects: Electrical Engineering; Engineering; Mechanical Engineering

Master of Science, The Ohio State University, 2016, Mechanical Engineering

The Ohio State University is participating in EcoCAR 3, which is a four-year long competition amongst 16 North American university teams to redesign the 2016 Chevrolet Camaro to reduce its environmental impact, while maintaining the muscle and performance expected from the iconic American car. To effectively assess and increase overall product quality and readiness of Ohio State's vehicle, this work defines and deploys a state of the art Model-Based Systems Engineering (MBSE) approach for managing engineering complexity as it relates to requirements management, traceability, and fulfillment. To demonstrate the effectiveness of the implemented approach, this work presents system safety development activities that have been conducted during the first two years of the competition. As EcoCAR 3 transitions into year-three, this work has already contributed to over a dozen awards by increasing overall documentation, traceability and workflow management as part of the overall engineering development process.

Committee: Shawm Midlam-Mohler (Advisor); Giorgio Rizzoni (Committee Member) Subjects: Automotive Engineering; Mechanical Engineering

Master of Science, The Ohio State University, 2024, Computer Science and Engineering

With the rise of car infotainment systems, the integration of smartphones with in-car displays has become increasingly prevalent. CarPlay, as one of the popular systems, is highly favored by users and is equipped in many vehicles. The Magic Brand Magic Box is an innovative Android-based device designed to interface with a car's CarPlay-enabled USB port, enabling the projection of its own user interface onto the car's display. However, this capability raises significant safety concerns, as it allows activities typically restricted while driving, such as watching videos on car screens. This thesis aims to reverse engineer the Magic Box to understand the mechanisms by which it communicates through the CarPlay interface. By analyzing the device's hardware and software, as well as referencing partial CarPlay protocol documents found online, we seek to uncover the principles behind its functionality and explore potential vulnerabilities in the Apple CarPlay system that may have been exploited. We aim to provide a detailed insight into the process of Android reverse engineering, offering valuable knowledge for researchers and practitioners interested in similar endeavors.

Committee: Keith Redmill (Advisor); Zhiqiang Lin (Advisor) Subjects: Computer Engineering; Computer Science

Master of Science in Cyber Security (M.S.C.S.), Wright State University, 2019, Computer Engineering

In the growing world of cybersecurity, being able to map and analyze how software and hardware interact is key to understanding and protecting critical embedded systems like the Engine Control Unit (ECU). The aim of our research is to use our understanding of the ECU's control flow attained through manual analysis to automatically map and identify sensor functions found within the ECU. We seek to do this by generating unique sets of feature vectors for every function within the binary file of a car ECU, and then using those feature sets to locate functions within each binary similar to their corresponding control function. This feature algorithm is used to locate candidate functions that utilize a sensor, and then examine the structure of each of these candidate functions to approximate the memory-mapped IO address of each sensor. This method was able to successfully locate 95\% of all candidate functions and was able to successfully recover 100\% of likely sensor addresses within each of those functions.

Committee: Junjie Zhang Ph.D. (Advisor); Jack Jean Ph.D. (Committee Member); Meilin Liu Ph.D. (Committee Member) Subjects: Computer Engineering; Computer Science

Master of Science, The Ohio State University, 2016, Mechanical Engineering

An automotive wire harness is an organized set of individual electrical wires, terminals and connectors that run throughout the entire vehicle transmitting information and electric power. Wire harnesses may be exposed to tensile, bending and torsion loads during and after being assembled in cars, causing stress and strain in the individual electrical wires without accurate validation from CAE tools. The lack of accurate CAE tools for wire harnesses has been generating extra costs to automotive OEMs for many years due to issues like rattling and interference with other parts. Present CAE software packages are not developed specifically for wire harness simulation and oversimplified models have been used such as elasticity behavior as well as ignoring taping and contact forces. To be able to develop an accurate CAE tool to simulate wire harnesses, the mechanical properties of harnesses and harness components must be fully characterized. However, due to the complexity, flexibility and high variation in wire harnesses and individual electrical wires, their mechanical properties have not been studied systematically and thoroughly in previous studies. In addition, no standards and very few experimental methods for mechanical testing of single electrical wires and wire harnesses have been developed, which led to few empirical data for CAE simulation resulting in inaccurate models. In this study, mechanical experiments have been categorized, developed and conducted on individual electrical wires and wire bundles under different loading conditions to identify key mechanical properties and behaviors. FEA researchers utilized these empirical data to create computational models for electrical wires and wire bundles. The experiments for individual electrical wires were categorized into tensile, bending and torsion tests. From tensile tests, stress-strain curves of three different wires were obtained, and elastic modulus, yield strength, elongation as well as ultimate tensile (open full item for complete abstract)

Committee: Marcelo Dapino (Advisor); Soheil Soghrati (Committee Member) Subjects: Mechanical Engineering