Lithium ion batteries are one of the most commercially used batteries. Though they are widely used in mobile phones, laptops and other consumer electronics, concerns related to their safety and efficient operation still persists. One of the major issues in Li-ion batteries is the capacity degradation with aging due to various mechanisms such as solid electrolyte interphase (SEI) formation and dissolution, thermal runaway, and Li-plating. In this work, we describe a capacity fade minimizing model predictive control approach for identification and realization of optimal charge-discharge cycles for Li-ion batteries. Optimum charging profiles are obtained such that the reduction in charge carrying capacity with cycling is minimized, while still obtaining required charging. We expect the proposed strategy to improve battery capacity and prolong lifespan. Examples that demonstrate the significance of the proposed framework by comparing battery performance with and without the presence of controller are discussed. Extensions to this work in terms of addressing various battery failure mechanisms, on-line identification of failure mechanisms, and designs for on-line implementation in real battery systems are also outlined. © 2017 Elsevier B.V.