Unlocking the full potential of electric vehicle fast-charging over lifetime through model-based aging adaptation
Kareem Abo Gamra, Philip Bilfinger, Markus Schreiber, Thomas Kröger, Christian Allgäuer, Markus Lienkamp
Abstract
Fast-charging within 15 min is increasingly demanded in electric vehicles to reduce downtime and increase customer acceptance. To ensure this, battery models depicting internal states can be used to safely operate along the batteries’ physical boundaries. This, however, poses an increasing risk of model error as the battery degrades over its lifetime, requiring aging-based derating and model updating. Conventional model-updating strategies based on capacity measurements are inaccurate, as they neglect the individual degradation paths of the electrodes and lithium inventory. In this study, we utilize half-cell open circuit potential measurements to update an electrochemical battery model using electrode and lithium inventory aging information over lifetime, showing that conventional methods may underestimate fast-charging potential. The average model error can be reduced by 66 % for a publically available aging dataset compared to no model updating and by 33 % compared to full cell capacity derating. Furthermore, we predict that charging speeds can be increased by up to 34 % for strongly aged cells compared to full cell derating, as the latter neglects the loss of lithium inventory, which reduces the risk of critical anode potentials causing lithium plating. • Overview of the state-of-the-art of aging adaptation strategies in fast-charge applications. • Increased charging speeds over lifetime using degradation mode aging adaptation compared to state-of-the-art methods. • Lowest model error over lifetime using an aging dataset under diverse operating conditions. • Quantification of the impact of different degradation mode compositions on fast-charging capability.