Fabien, BrianJain, Yug Mukesh2021-03-192021-03-192021-03-192020Jain_washington_0250O_22417.pdfhttp://hdl.handle.net/1773/46841Thesis (Master's)--University of Washington, 2020This work evaluates two control strategies for Adaptive Cruise Control (ACC), classical control (PID control), and Model Predictive Control (MPC) with linear-piecewise approximated engine fuel map as a part of cost function to penalize fuel consumption, both applied to UW EcoCAR vehicle model. The ACC system with MPC consists of hierarchical control architecture, a lower-level controller to track the acceleration command, and a higher-level ACC control. The control algorithms are tested on Model-In-Loop (MIL) using Simulink. The real-time Hardware-In-Loop (HIL) performance testing is done using the dSpace simulator which runs the vehicle model and the dSpace MicroAutoBox II which serves as a controller platform. A comparison of miles per gallon of fuel, average acceleration, and average jerk is provided for drive cycle runs by ACC PID and MPC.application/pdfen-USCC BYMechanical engineeringMechanical engineeringThesis