Capacity fade experienced by the battery will affect the lifetime of the battery pack as well as the residual value of an electric vehicle. Developing a degradation model that can prognosis state of health for the given operating condition is critical for developing an algorithm to maximize the remaining useful lifetime of the systems. It is known that the electrochemical degradation model has superior predictability to other data-driven models, but still needs improvement in terms of computational efficiency. We reduced the electrochemical degradation model which considers three main aging mechanisms that can predict the state of health at various calendric aging conditions. The parameterization procedure and its prediction capability will be also discussed.