Date of Award

9-27-2023

Publication Type

Thesis

Degree Name

M.A.Sc.

Department

Mechanical, Automotive, and Materials Engineering

Keywords

Electrochemical;Genetic Algorithm;Heat generation;Lithium-ion

Supervisor

Ofelia Jianu

Rights

info:eu-repo/semantics/embargoedAccess

Creative Commons License

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

Abstract

One of the many current significant challenges of lithium-ion battery use is keeping the thermal limits of the boundaries within a reasonable range. This applies equally to hybrid electric vehicles and to full-battery electric vehicles. To accomplish this, an accurate understanding of the thermal behavior of the battery is necessary, and consequently, accurate thermal models are required. To achieve this accuracy, the model's parameters must be well-predicted to reduce the behavior difference between simulated and experimental temperatures. These models should also describe the voltage behavior of the battery adequately to encapsulate the system's design requirements fully. To estimate the parameters of the model, a hybrid pulse power characteristic profile was performed at multiple temperatures and multiple discharge rates, and the battery's voltage and temperature response were measured at ambient conditions. A one-dimensional electrochemical model was developed, and a genetic algorithm minimizing the root mean squared error between modeled and experimental voltages was completed. Current loads representing the loading conditions of the standard world harmonized light-duty cycle (WLTC), environmental protection agency driving cycle (EPA), China light-duty cycle (CLTC), and Nuremberg ring cycle (NR) were applied to the battery cell model. The battery cell model's simulated voltages were compared to the experimental voltages of the above driving cycles. These initial simulations show that parameter estimation can accurately simulate the voltage behavior of the battery. A heat generation model was developed, including reversible and irreversible heat generation terms. The thermal behavior of the battery, such as the maximum, minimum, and mean temperatures, was investigated for the aforementioned drive cycles at ambient conditions, at both the modular and cellular levels.

Available for download on Thursday, September 26, 2024

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