Advancements in batteries, microprocessors as well as an extra emphasis being put on the environment has pushed electric vehicles to the forefront of today. Despite the many benefits of electric vehicles, range anxiety and long charge times are hurdles to overcome. These shortfalls are a result of the current battery technology regardless of the many breakthroughs over the last decade. Lithium-ion Batteries and other modern chemistries pose a number of challenges in testing and research when compared to the traditional lead acid batteries. Current test systems fall short in providing a complete testing solution with. The focus of this thesis is to develop a complete software framework for battery characterization: testing, modelling and characterization to accompany battery testing hardware developed by D&V Electronics. The first step in battery characterization, involves battery testing in order to obtain data. This required development of the test software and a number of battery tests, including: Charge and discharge, state of charge vs. open circuit voltage curve generation, Electro-Impedance Spectroscopy, and capacity test. Research was done in order to ensure developed test procedures lined up with that of other publications. All data from the testing data is logged to a central database, allowing for the second major development, the model framework. The model framework is composed of seven different battery models that can be parameterized with the touch of a button, using data collected from the tester. It is a software framework that is meant to be expandable by abstracting the details of a model from the tester. This allows for new models and parameterization techniques to be integrated into the software without the need of new software development. Lastly, all development was used to do a battery characterization of a prismatic battery cell. All tests were conducted on a battery over two hundred cycles, followed by battery parameterization using the mode framework. The battery models were then used to simulate a US06 drive profile and compared to the same profile with measurements taken from the tester. With an average root mean square error of 8 millivolts, the battery characterization using the framework proved to be a success. / Thesis / Master of Applied Science (MASc)