Ultra-fast charging of electric vehicles will soon be available to charge the batteries in less than 15 minutes to 80% state of charge. However, very few studies of batteries under these conditions exist. To design a battery pack with ultra-fast charging in mind, more information about batteries is needed, both electrically and thermally. In this thesis, the performance of three specific commercial lithium-ion batteries during ultra-fast charging is investigated and their thermal behaviour is simulated for use in the battery pack design process. The cells are charged at 1C to 6C current rates, or as high as 10C, and the surface temperature of each cell is measured. The loss calculated from the charging tests are used in a thermal analysis of the three batteries using finite element analysis. The batteries are modeled in a simple cooling apparatus to determine their thermal management requirements in a pack, i.e., how effectively must the heat be removed from the cells to obtain a specific temperature in a pack. Test results show that ultra-fast charging is possible with very little loss; but, it is dependent on the battery. The analysis illustrates important trade-offs between the battery type, charge rate, and the thermal management system. This thesis presents a holistic view to the study of the batteries for eventual use in the design of a battery pack. The thermal performance of the batteries is equally important as their electrical (charge) performance. It also attempts to justify the observed behaviour of the batteries by their underlying chemical behaviour. The work here can be used as a jumping-off point for further work on the ultra-fast charging of batteries or the design of a battery pack. / Thesis / Master of Applied Science (MASc) / Ultra-fast charging of electric vehicles, i.e., fully charging the vehicle in less than 15 minutes, will soon be more available. However, literature on the ultra-fast charging of the batteries used in these vehicles is limited. It is not widely known whether the batteries can effectively achieve ultra-fast charging or how the batteries behave under these conditions. Charging batteries this fast means that the battery cells will heat up. The temperature of the cell greatly impacts its longevity and safety. The thesis attempts to address these questions by studying three commercial lithium-ion batteries, selected for specific characteristics, that show potential for ultra-fast charging. The batteries are charged at different rates to ultra-fast charging levels and the charge performance at each rate is determined. The temperature of the batteries is simulated with different cooling systems to determine how effectively must heat be removed from the batteries to maintain the cells at a specific temperature.

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)