Barrett

Barrett, The Honors College at Arizona State University proudly showcases the work of undergraduate honors students by sharing this collection exclusively with the ASU community.

Barrett accepts high performing, academically engaged undergraduate students and works with them in collaboration with all of the other academic units at Arizona State University. All Barrett students complete a thesis or creative project which is an opportunity to explore an intellectual interest and produce an original piece of scholarly research. The thesis or creative project is supervised and defended in front of a faculty committee. Students are able to engage with professors who are nationally recognized in their fields and committed to working with honors students. Completing a Barrett thesis or creative project is an opportunity for undergraduate honors students to contribute to the ASU academic community in a meaningful way.

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Investigation and Integration of Communication Technologies for Multiple Connected and Automated Vehicle (CAV) Prototypes

Description
With the growing popularity and advancements in automation technology, Connected and Automated Vehicles (CAVs) have become the pinnacle of ground-vehicle transportation. Connectivity has the potential to allow all vehicles—new or old, automated or non-automated—to communicate with each other at all times and greatly reduce the possibility of a multi-vehicle collision.…

With the growing popularity and advancements in automation technology, Connected and Automated Vehicles (CAVs) have become the pinnacle of ground-vehicle transportation. Connectivity has the potential to allow all vehicles—new or old, automated or non-automated—to communicate with each other at all times and greatly reduce the possibility of a multi-vehicle collision. This project sought to achieve a better understanding of CAV communication technologies by attempting to design, integrate, test, and validate a vehicular ad-hoc network (VANET) amongst three automated ground-vehicle prototypes. The end goal was to determine what current technology best satisfies Vehicle-to-Vehicle (V2V) communication with a real-time physical demonstration. Although different technologies, such as dedicated short-range communication (DSRC) and cellular vehicle to everything (C-V2X) were initially investigated, due to time and budget constraints, a FreeWave ZumLink Z9-PE DEVKIT (900 MHz radio) was used to create a wireless network amongst the ground-vehicle prototypes. The initial testing to create a wireless network was successful and demonstrated but creating a true VANET was unsuccessful as the radios communicate strictly peer to peer. Future work needed to complete the simulated VANET includes programming the ZumLink radios to send and receive data using message queuing telemetry transport (MQTT) protocol to share data amongst multiple vehicles, as well as programming the vehicle controller to send and receive data utilizing terminal control protocol (TCP) to ensure no data loss and all data is communicated in correct sequence.
ContributorsDunn, Brandon (Author) / Chen, Yan (Thesis director) / Wishart, Jeffrey (Committee member) / Engineering Programs (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05

Model Predictive Control For Energy Management Strategies in Electric Vehicles

Description
Model Predictive Control (MPC) is a fairly recent development in control optimization theory with high potential for use in the automotive industry, specifically in electric vehicle energy management systems. Because model predictive control is a particularly young concept and due to the MPC’s high computational load, it is overlooked when…

Model Predictive Control (MPC) is a fairly recent development in control optimization theory with high potential for use in the automotive industry, specifically in electric vehicle energy management systems. Because model predictive control is a particularly young concept and due to the MPC’s high computational load, it is overlooked when compared to conventional control methods such as Proportional Integral Derivative (PID) controllers. Among recent advancements in computing technology in electric vehicles, model predictive controllers have become a viable solution in electric vehicle (EV) Energy Management Systems (EMS). The distinction between MPCs and other EMS control methods can be summarized by MPC’s ability to optimize outputs in systems where multiple constraints and state-space variables are introduced where conventional methods cannot. The MPC achieves this by using predictive modeling, allowing it system states based on information provided through a feedback loop. Feasibility for the use of MPCs in EV EMSs will be supported by using a simulated dual-motor electric vehicle in SIMULINKs Virtual Vehicle Composer (VVC) application. Findings from repeated simulations have proven model predictive control to be an effective alternative optimization strategy for electric vehicle energy management systems.
ContributorsWild, Trevor (Author) / Chen, Yan (Thesis director) / Zhao, Junfeng (Committee member) / Barrett, The Honors College (Contributor) / Engineering Programs (Contributor)
Created2024-05