The electrification of transportation is gradually becoming more prominent as it is more efficient and sustainable than conventional transportation alternatives found today. At the centre of this growth is battery testing and research, as they are the primary energy storage devices used to power electric vehicles. With the growing complexity of battery systems, testing and monitoring their performance relies on highly specialized and precise equipment. Furthermore, the use of battery models helps researchers improve their research while reducing the time and costs involved in testing. As such, accurate battery modelling is a critical component in predicting how a battery will behave in specific applications and under various conditions. In this research, a lithium-ion cell is tested extensively, and its performance is characterized across a wide range of operating conditions including temperature, current rates and state of charge (SOC) values. An equivalent circuit model for impedance modelling is proposed, which utilizes constant phase elements represented in the time domain to improve fitting accuracy. This is done concurrently with the development of a state of the art, fully automated battery test system which is showcased throughout the course of the research. In addition to this, an analysis is conducted on the low frequency impedance data used during research, as well as its effect on model accuracy. To provide significance behind the results and relevance to real-world applications, all of the impedance modelling is experimentally validated using temporal drive cycle data. This research was able to demonstrate that the use of a ZARC element can improve the mid-frequency fitting of impedance data relative to a conventionally used modelling approach. It also showcases how the use of low frequency electrochemical impedance spectroscopy (EIS) data can negatively impact the accuracy of impedance modelling. / Thesis / Master of Applied Science (MASc)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/25476 |
| Date | January 2020 |
| Creators | Tawakol, Abdel Rahman |
| Contributors | Habibi, Saeid, Mechanical Engineering |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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