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Samuel Yacinthe

Undergraduate Major: Mechanical Engineering

Future Plans: PhD in Mechanical Engineering at Ohio State University

Samuel Yacinthe

Samuel Yacinthe was born in Haiti and moved to Florida at the age of two. While growing up in South Florida, he became interested in engineering when receiving his first Lego-set in elementary school. Samuel has proven his passion for engineering outreach through participation in projects including ICubed (National Science Foundation funded research project) as he continues to positively impact the community. In addition to being a contributing member in the Society of Automotive Engineers (SAE), Samuel pursues his leadership development by holding executive board positions in both Pi Tau Sigma and the National Society of Black Engineers (NSBE). Samuel is pursuing his undergraduate degree in Mechanical Engineering, and his research interests include human-machine systems, bio-inspired control, and automotive control systems.

Sam was among 60 college and university undergraduate students nationwide selected to participate in the 18th annual Posters on the Hill event taking place April 28-29 in Washington, D.C. Sam's application was selected based on a review of over 600 application.

Hybrid Vehicle Sensitivity Analysis for Optimization of Efficiency and Performance

Conducted at The Ohio State University as part of the Summer Research Opportunities Program and the McNair Scholars Program

Awards: Selected by the Council on Undergraduate Research (CUR) to present his research at the 18th Annual Posters on the Hill.
1st Place, Technical Research Exhibition Award at the 2013 National Society of Black Engineers Fall Regional Conference.

Mentor: Dr. Shawn Midlam-Mohler, Assistant Professor – Clinical, Department of Mechanical and Aerospace Engineering, The Ohio State University.

Abstract: EcoCAR2 is an Advanced Vehicle Technology Competition (AVTC) sponsored by the U.S. Department of Energy (DOE) and General Motors (GM). This three-year student project explores electric vehicle technology with primary goals of maximizing energy efficiency and minimizing vehicle emissions, while maintaining consumer acceptability and safety. As the competition transitions into its third year, the goal is to refine and optimize the vehicle in this final stage of competition. This research study utilizes design of experiment (DoE) techniques to conduct a parametric analysis that identifies which vehicle parameters are most influential on the system efficiency. We simulate a model of the plug-in hybrid electric vehicle (PHEV) via Matlab/Simulink software, as this is a cost effective experimentation approach to considering all factors simultaneously. A cost model is also developed to determine associated resource cost for improving each parameter. With combinations of cost and parametric sensitivity, we find that the most effective approach for refinements is that given the amount of resources, efforts should focus on improving mass, then auxiliary load, followed by improvements in rolling resistance and aerodynamic drag. Hence, by establishing the relative importance of each vehicle parameter with an associated cost model, this study can guide the focus of areas that will be most beneficial in improving efficiency and performance of The Ohio State University's EcoCAR2.

Dynamic Model Validation of a Differential Drive Robot

Conducted at University of Central Florida as part of the ICubed National Science Foundation funded research project.

Mentor: Suhada Jayasuriya, Ph.D., PE, Department of Mechanical, Materials, and Aerospace Engineering (MMAE), University of Central Florida

Abstract: For control purposes, in order to improve a wheeled mobile robot's (WMR) navigation on realistic terrains, the interactions between the robot and its surroundings need to be studied and implemented into the dynamic model of the system. Slip is a common condition that accounts for ground and tire interaction, and the aim of this work is to study a newly proposed dynamic model that accounts for multi-directional slipping characteristics. Now, the type of WMR being studied is differentially driven, and is characterized by the independent control of each wheel's velocity for the two-wheeled vehicle. The newly developed model will first be simulated for various cases and verified by face validity to ensure that the model behaves correctly. Then, for similar cases the method of predictive validation will be implemented to investigate how well theoretical data correlates with experimental results. Due to important applications of high speed WMR's, such a dynamic model becomes useful when predicting slip. This can lead to improvements in predictive control of these systems, as the use of traditional models may lead to inaccuracies in position estimation.