Date of Award
Open Access Master's Thesis
Master of Science in Mechanical Engineering (MS)
Administrative Home Department
Department of Mechanical Engineering-Engineering Mechanics
Committee Member 1
The technical report discusses the high fidelity modelling of the powertrain of Chevy Volt Gen II Hybrid Vehicle in the Electric Mode. The overall objective of the powertrain model was to predict total energy consumed within 5% of experimental data for different drive cycles in Charge Depleting Mode. The following powertrain elements were modelled in Matlab and Simulink using parameters and performance maps provided by General Motors: battery, E-Motor, TPIM power electronics, transmission auxiliary pumps and spin losses.
An electric circuit based dynamic model of the Li-ion battery was developed. Static models of the E Motor, TPIM inverter, transmission auxiliary pump and spin losses based on performance maps were developed. The report discusses the development of each of the powertrain components. Further, the methodology behind the development of simplified EV supervisory controller which determines the EV modes,motor torque and speeds from the vehicle speeds is discussed. To generate the motor torques the existing rule based EV mode selection and torque blending logic implemented in Chevy Volt were extracted using analysis of ANL experimental data. The vehicle dynamics and transmission models were developed which generates the actual vehicle velocity and the controller acts on the error between actual speed and target speed for mode selection and commanding motor torque.
The overall powertrain model was validated for three drive cycles in Charge Depleting (EV) mode i.e. HWFET, UDDS, US06 based on test data provided by Argonne National Lab. The model estimates the total energy consumption of battery over the drive cycle beyond 95 % accuracy of the ANL experimental data i.e. with errors less than 5%.
Surresh, Kaushik, "Modelling and Analysis of Chevy Volt Gen II Hybrid Vehicle in Electric Mode", Open Access Master's Thesis, Michigan Technological University, 2018.