Date of Award


Publication Type


Degree Name



Mechanical, Automotive, and Materials Engineering


Battery Electric Vehicles;Hybrid Electric Vehicles;Lithium-ion Batteries;Thermal Degradation;Thermal Modeling;Vehicle and Exhaust Modeling


Ofelia Jianu



Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.


One of the major challenges with the implementation of lithium-ion batteries in electric and hybrid vehicles (EVs and HEVs) is effective thermal management. Inherently, lithium-ion batteries are thermally sensitive which causes a reduction in vehicle performance and thermal degradation when operated outside of the recommended temperature range. However, the lithium-ion battery thermal management can be difficult in full-vehicle systems, due to the highly transient conditions demanded by the driver. Therefore, accurate full-vehicle and battery thermal models are required in order to predict the battery temperature throughout various driving conditions. This thesis begins with the development of a plug-in hybrid vehicle (PHEV) full-vehicle transient thermal model in Virtual Time-Temperature Analysis software in order to predict the battery surface temperature. The full-vehicle thermal model consists of a full exhaust piping system, a high-voltage lithium-ion battery pack system, and a liquid closed-loop battery coolant system. All modes of heat transfer including conduction, forced and natural convection, radiation, battery cooling, and battery internal heat generation are considered in the model. The full-vehicle model is simulated under various vehicle conditions to represent four standard customer drive cycles. The simulated battery surface temperature at specified points along the battery module surfaces is compared to experimental vehicle test-cell data to provide model validation. The second part of this thesis focuses on the implementation of a thermal degradation model using time-temperature analysis. Time-temperature analysis predicts the thermal degradation over the entire life cycle of the vehicle. The analysis utilizes the thermal history results of the full-vehicle model, historical regional weather data, battery material properties, and several temperature goals to predict the amount of thermal degradation in the form of equivalent temperature exposure times.

Available for download on Thursday, September 26, 2024