Li-ion battery performance degrades with aging and usage, and the degradation highly depends on how the cell is operated. As such, models used for system design and optimization should ideally capture the impact of those effects, and battery management system should take degradation into consideration and control cell operation carefully. Physics-based electrochemical models have shown the capability of predicting cell performance and degradation, but are computationally time consuming, often precluding its use in control-oriented design/optimization. Based on the constitutive laws which are widely adopted in the electrochemical models, a control-oriented reduced-order degradation model for a commercial LiNiMnCoO2/graphite cell is derived to improve computational efficiency without sacrificing model fidelity. Three primary degradation mechanisms that occur in a typical Li-ion cell are captured: 1) Solid Electrolyte Interface (SEI) layer growth, 2) SEI layer fracture and re-healing, and 3) Active Material loss. The extensive validation against a wide range of experimental data illustrates the ability of the model to accurately predict the capacity loss.