UTILIZING COMPUTATIONAL TECHNIQUES TO DESIGN A HYBRID VEHICLE FOR THE ECOCAR MOBILITY CHALLENGE

Abstract

This thesis documents computational techniques and results used in designing a shared-mobility hybrid electric vehicle developed for the Georgia Tech EcoCAR Team, a collegiate engineering team participating in the EcoCAR Mobility Challenge. The competition challenges 12 university teams, 10 from the United States and 2 from Canada, to hybridize a 2019 Chevrolet Blazer and upfit it to SAE Level 2 autonomous operation, primarily for the Mobility-as-a-Service market. The formation and use of dynamic programming for selecting a hybrid architecture is first detailed. The architecture chosen for the competition is then introduced and a selection of custom components engineered for the vehicle is documented. These include a P4 motor mount using CNC machining and topology optimized weldments, a custom 6061-T6 aluminum fuel tank with topology optimized tabs and multiple revisions, and a high voltage A/C compressor mount made with topology optimized weldments and rubber bushings. These efforts help the Georgia Tech team to quickly make improved design decisions that increase vehicle fuel economy