Date of Award

5-2011

Document Type

Thesis

Degree Name

Master of Science (MS)

Legacy Department

Mechanical Engineering

Advisor

Fadel, Dr. Georges M

Committee Member

Thompson , Dr. Lonny L

Committee Member

Li , Dr. Gang

Abstract

Improving vehicle performance and passenger comfort has been a prime engineering concern and focus of research for many years in automotive design. Turning to high-performance components in an effort to improve vehicle performance alone is often not enough and their placement and interactions with other components should also be an integral part of the improvement process. With the advancement in hybrid electric vehicle technology, the packing of components under the hood is ever more essential and challenging. Under hood packing is a multi-objective optimization problem with many, and mostly conflicting objectives. A non-deterministic multi-objective evolutionary algorithm needs to be integrated with the packing algorithm to obtain solutions. However, it is almost impossible to find optimal solutions in a limited amount of time due to the computationally intensive algorithm. Therefore, a new and efficient approach needs to be developed.
This study applies an agent-based approach to the under hood vehicle packing problem with three objectives, namely: center of gravity, survivability, and maintainability subject to no overlap among components and with the enclosure, and minimum ground clearance. As per the weak notion of agency, a layered architecture is built with an agent on top of object model. A non-deterministic evolutionary multi-objective algorithm (AMGA-2) is used to identify non-dominated solutions, speed up the convergence to a non-dominated set and prevents unpredictability in the agent system. The developed agent-based model is applied to a passenger car but, it can also address large packing problems for SUVs and Trucks (FMTV). This work demonstrates the applicability and benefits of an agent-based approach to the packing problem.

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