Accurate information on battery state-of-charge, expected battery lifetime, and expected battery cycle life is essential for many practical applications. In this paper, we develop a nonchemically based partially linearized (in battery power) input-output battery model, initially developed for lead-acid batteries in a hybrid electric vehicle. We show that with properly tuned parameter values, the model can be extended to different battery types, such as lithium-ion, nickel-metal hydride, and alkaline. The validation results of the model against measured data in terms of power and efficiency at different temperatures are then presented. The model is incorporated with the recovery effect for accurate lifetime estimation. The obtained lifetime estimation results using the proposed model are similar to the ones predicted by the Rakhmatov and Virudhula battery model on a given set of typical loads at room temperature. A possible incorporation of the cycling effect, which determines the battery cycle life, in terms of the maximum available energy approximated at charge/discharge nominal power level is also suggested. The usage of the proposed model is computationally inexpensive, hence implementable in many applications, such as low-power system design, real-time energy management in distributed sensor network, etc.