Accurate predictions of degradation and lifetime of lithium-ion batteries are essential for reliability, safety and key to remanufacturing and repurposing. Cycle life is a key performance metric to understand how changes in the cell design or chemistry will impact system cost and durability. Physics-based models can be used to evaluate battery degradation mechanisms, which is useful when the product lifetime is expected to be 10-20 years and experimental validation is infeasible. The complete lifetime simulation can take hours corresponding to thousands of charge and discharge cycles. An adaptive inter-cycle extrapolation algorithm allows us to rapidly simulate the entire lifetime of the battery and enable the use of optimization algorithms to tune model parameters. We demonstrate the efficacy of the proposed parameter tuning approach using the single particle model with two degradation mechanisms, solid electrolyte interphase growth and active material loss due to mechanical failure. The model can explain the observed trends in capacity fade, loss of lithium inventory and individual electrode capacities from both cycling and calendering experiments. The model agrees well with the data in all outputs, even in cases that were withheld from parameter tuning. The accelerated simulations also agree well with full simulations.