Thermal characterisation and performance of cylindrical lithium-ion batteries

Lithium-ion cells are a key piece of technology in the world today, used in a variety of applications from electric vehicles to mobile phones. Most applications use multiple cells in a battery pack. Choosing the right cell for a given application can be critical to achieving an optimised battery pack. However, a lack of information from cell datasheets makes choosing an optimum cell a challenge. This thesis aims to assess potential methods of making the comparison of cells easier. The Cell Cooling Coefficient (CCC) is a thermal metric designed to define the heat rejection capability of lithium-ion cells. Experiments presented in this thesis successfully measure the CCC value for base cooled cylindrical cells. While modelling work, highlighted potential issues caused by the heat generation profile of the cell, making the CCC non-constant, with the impact of real experimental losses impacting the measurement of the CCC, resulting in the application of the CCC being restricted to use as a standardised comparison for cell thermal performance. Following this, a study benchmarking the performance of six cylindrical cells has been performed aiming to assess the viability of selecting cells based on standardised conditions. Through a series of tests covering a range of electrical loads and different cooling systems, it is demonstrated that the conditions of testing can impact percentile-based ranking by over 20%, proving that cells must be tested under application-specific conditions to enable the correct choice of cell. Finally, an experimental lifetime study is performed on two commercial cells, comparing base cooling, side cooling and standardised conditions, under automotive-relevant cycles. It is found that side cooling is the better cooling system for both beginning and end of life, with standardised conditions being unrepresentative of either. Concluding that cells should be tested for life performance under application-relevant conditions, to choose the best cell.