Lithium-ion Battery Rate-of-Degradation Modeling for Real-Time Battery Degradation Control during EV Drive Cycle

This work investigates an approach to modeling lithium-ion battery (LIB) rate-of-degradation (ROD) that can be used for real-time active control of battery degradation. This physics-based model extends from electrochemical LIB degradation modeling in the literature to LIB ROD modeling by estimating the solid-electrolyte-interphase (SEI) layer growth rate on the graphite anode. To enable the real-time control capability, the complexity of conventional electrochemical degradation models is reduced by eliminating all of the associated partial differential equations (PDEs) via regression and estimation algorithms. The proposed reduced-order ROD model can accurately predict the aging progression of batteries cycled with dynamic profiles. The dynamic ROD estimation can be integrated into a dynamic battery current (power) limiting control. Experimental results show that battery degradation reduction can be achieved during drive cycles with the ROD control enabled.