Theses and Dissertations
Issuing Body
Mississippi State University
Advisor
Hwang, Joonsik
Committee Member
Jones, Bryan
Committee Member
Mohsen, Azimi
Date of Degree
12-8-2023
Original embargo terms
Campus Access Only 1 Year
Document Type
Graduate Thesis - Campus Access Only
Major
Mechanical Engineering
Degree Name
Master of Science (M.S.)
College
James Worth Bagley College of Engineering
Department
Department of Mechanical Engineering
Abstract
Electric and hybrid-electric vehicles lean heavily on intricate control algorithms to provide smooth, reliable, and secure operations under any driving conditions. Three distinct supervisory control strategies have been developed, each aiming to improve reliability and vehicle performance of a dual-motor electric vehicle equipped with an all-wheel-drive, fully electric powertrain. These algorithms are adept at dynamically modulating and constraining the torque provided to the wheels, leveraging two autonomous permanent magnet electric drive units. This study utilizes a vehicle model jointly provided by MathWorks and General Motors in partnership with industry sponsors. The these strategies were implemented in the model and enhanced the performance, vehicle range, energy consumption, regenerated energy using specific EDUs provided by sponsors. Adhering to a systematic engineering iterative method, the emphasis was heavily placed on simulation and modeling during the development and validation of these strategies. Simulations ensured robust testing before field implementation, emphasizing software modeling's vital role.
Recommended Citation
Hidara, Aymane, "Adaptive traction, Power and Torque Control strategies and optimization in an all-electric powertrain" (2023). Theses and Dissertations. 5992.
https://scholarsjunction.msstate.edu/td/5992