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ENGR2022ANDERSON30447 ENGR

Bidirectional DCDC Conversion for Supercapacitor Implementation in Electric Vehicles

Type: Undergraduate
Author(s): Corban Anderson Engineering Sam Rajnarayanan Engineering Steve Rivas Engineering
Advisor(s): Stephen Weis Engineering
Location: Basement, Table 9, Position 2, 1:45-3:45

DC to DC Conversion is important in modern electronics, and to the automotive industry. It is the process of converting a direct current (i.e constant) signal into another form of direct current (DC). A small-scale example of this is a car adapter, which converts the 12 volts provided by a car outlet into the 5 volts a cell phone needs to charge, known as a ‘step down’ converter. The main objective of the project is to design and test a bidirectional DC to DC conversion system. Most DCDC converters available on the market are unidirectional, i.e., either ‘step down’ or ‘step up’ the DC signal. Those that can switch are called bidirectional converters, but many available cannot handle the higher requirements of an electric motor. A system that can switch directions based on specific system parameters allows for situational flexibility, and the use of new devices for more efficient energy use. The supercapacitor is one such device. They provide power more efficiently than batteries but can only store a small amount of energy. They must be recharged often, which requires a step-down conversion from a power source (much like the car adapter example). Supplying the motor from supercapacitors requires a step-up conversion. So, to use, and reap the most benefit from these supercapacitors, switching from step up to step down based on their charge is a requirement. Ultimately, this would allow for the use of supercapacitors in an EV as part of a future project.

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ENGR2022GILLY10381 ENGR

Ground Truth Mapping

Type: Undergraduate
Author(s): Nathaniel Gilly Engineering Kate Harris Engineering Brent Hewitt Engineering Carson Maher Engineering
Advisor(s): Sue Gong Engineering
Location: Third Floor, Table 3, Position 1, 1:45-3:45

In this presentation, the process of creating a map of an area using ground truth data will be explained. The overall objective of this research project is to be able to capture a remote image of a land mass and be able to discern what sections within that image are a certain material. This is done through the matching of spectral signatures, which are unique for every physical material found on earth. A demonstration of spectral signature matching will be shown to understand the basic idea of how the mapping is done. A model expanding on this idea with the use of ground truth data will be shown with results showing how the map will be made.

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ENGR2022HEWITT52353 ENGR

Hydrodynamic Analysis of Surfboard Fin Performance

Type: Undergraduate
Author(s): Brent Hewitt Engineering
Advisor(s): Robert Bittle Engineering
Location: Second Floor, Table 7, Position 1, 1:45-3:45

Hydrodynamic Analysis of Surfboard Fin Performance set out to analyze how the outline and size of a surfboard fin can impact performance. Performance analysis involved running images from the manufacturer’s website through a MATLAB code that would process the image to determine an appropriate, numerical method, based on fluid dynamics, to explain categorical differences between fins. After testing for differences between categories for the following performance metrics: the vertical line of action, the horizontal line of action, the ratio between the tip area and the rest of the fin, and the resulting angle created by comparing the vertical and horizontal lines of action, the angle was found to be the most statistically significant factor for determining fin categories. Moving forward, users can input an image, along with the fin dimensions, to determine the performance characteristics of a fin, without having to purchase a fin. This project explains the underlying equations that are utilized, the fundamental assumptions that are made, how the results are generated, and how users can interpret the results.

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ENGR2022KANG39306 ENGR

RC/Semi-Autonomous Quadcopter

Type: Undergraduate
Author(s): HyunMyung Kang Engineering Omar Hussein Engineering Rose Ibarra Engineering Nhu Le Engineering Emmanuel Matthews Engineering Natalia Perez Engineering
Advisor(s): Morgan Kiani Engineering
Location: Basement, Table 11, Position 1, 11:30-1:30

Autonomous drones have been commercially available for decades. The integration of sensors has allowed robots to interact with their environment and resulting in autonomy. This quadcopter team takes on the challenge of creating an autonomous quadcopter using a frame, motors, electronic speed controllers, propellers, a Raspberry Pi, and an RPLidar. The team achieved remote control flight of the drone through pre-installed software—QGroundControl. The onboard computer will collect data using the RPLidar sensor and then send the data to the flight controller. Setting the robot (talker) and the virtual machine (listener) as nodes, they can communicate with each other through the ROS master.

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ENGR2022NOLAN36467 ENGR

Generative Design for Manufacture

Type: Undergraduate
Author(s): Connor Nolan Engineering Corban Anderson Engineering Antonio Malvar Gonzalez Engineering Jose Miranda Engineering
Advisor(s): Robert Bittle Engineering
Location: Second Floor, Table 6, Position 2, 11:30-1:30

Generative design implementation in this project had the goal of replacing sheet metal structures previously used to hold relays and electromechanic switches with 3D printed structures. The generative design software has the benefit of minimizing the mass of the structure, while keeping its structural integrity. The software does this by iterating through designs solving for stresses at each step, deciding where it is better to place a structure and then cutting mass at points where the structural integrity would not be compromised. Although the software creates a design on its own the user must define certain parameters: the preserve geometry (fundamental geometry for operation), obstacle geometry (sections that the software should leave without obstruction), the expected load case, manufacturing method, and material to be used. The end result is that the computer creates most efficient parts, allowing for a plastic 3D printed part to be able to safely replace one made of metal.

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