Li-ion battery failure becomes one of major challenges for reliable battery applications, as it could cause catastrophic consequences. Compared with capacity fading resulted from calendar effects, Li-plating induced battery failures are more difficult to identify, as they causes sudden capacity loss leaving limited time for failure diagnosis. This paper presents a new internal state variable (ISV) mapping approach to identify values of immeasurable battery ISVs considering changes of inherent parameters of battery system dynamics for Li-plating diagnosis. Employing the developed ISV mapping approach, an explicit functional relationship model between measurable battery signals and immeasurable battery ISVs can be developed. The developed model can then be used to identify ISVs from an online battery system for the occurrence identification of Li-plating. Employing multiphysics based simulation of Li-plating using COMSOL, the proposed Li-plating diagnosis approach is implemented under different conditions in the case studies to demonstrate its efficacy in diagnosis of Li-plating onset timings.