Knowledge Bank

Spatially and temporally resolved one-dimensional transient models for the prediction of performance of lithium-ion batteries have been prevalent in the literature for over a decade. It is generally believed that such models that take into account the detailed mass transfer and electrochemistry within the battery are unsuitable for real-time control of batteries. As a result, several attempts have also been made to develop reduced-order approximate models that are suitable for real-time control. While these reduced models are efficient, they fail in non-linear regimes of operation. In this thesis, it will be shown that full spatial and temporal resolution of the battery with the inclusion of detailed transport phenomena and electrochemistry is possible with faster-than-real-time computing times provided appropriate numerical techniques are employed. The model presented here employs the same governing conservation equations of mass, energy, and charge as employed in previous studies. Only, the numerical procedure and solution algorithms are different. These are presented in some detail. The model was first successfully validated against experimental data for both charge and discharge processes in a — battery. Finally, it was demonstrated for an arbitrary load typical of a hybrid electric vehicle drive cycle. The model was able to predict the cell voltage of a 15-minute drive cycle in less than 9 minutes of compute time on a laptop with a 2.3 GHz Intel i7 processor.