Lithium-ion battery state of health estimation

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Electric vehicles (EVs) play a key role in decreasing the carbon footprint of the mobility sector. Their high upfront cost, limited range and slow charging speed are however a barrier to increased EV uptake. Reducing the cost and improving the EV Lithium-ion (Li-ion) battery could reduce these barriers. There is, however, limited knowledge in the safe operation and degradation rate of Li-ion batteries. This is largely due to the complex electrochemical mechanisms not being well understood. Furthermore, the large operating envelope (temperature, charging speed etc.) over its lifetime require resource intensive testing to parameterize semi-empirical models. The battery is therefore operated very conservatively, resulting in oversizing the battery and sub-optimal operating conditions resulting in inefficiencies and higher costs.This PhD aims to provide optimal testing strategies and accurate modelling of Li-ion batteries in order to provide information to facilitate more efficient operating strategies (e.g. fast charging). This will be achieved by a combination of advanced design of experiments (DOE), modelling and machine learning. The core of the PhD, will focus on methods to estimate the state of health of the battery cells over various operating ranges. The initial part of the PhD will focus on building a model structure which is based on a data driven neural network. The accuracy of this model will then be assessed using existing battery data in literature and data provided by the industrial partner. An experimental test campaign will then be designed and implemented, in an attempt to efficiently parameterize the battery models. The resultant battery models would then provide important information to improve the safe operation range of the battery.More efficient testing methods and accurate modelling of battery degradation will speed up development time in the design phase of the Electric Vehicle production. It will also facilitate development of new battery architectures and more efficient operating schemes (e.g. improved fast charging strategies). Both of these developments would decrease the overall cost of batteries in EVs. This could decrease overall EV cost and accelerate their uptake by consumers, thereby reducing the overall carbon impact of the mobility sector.