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Abstract: Battery models are of great importance to develop portable computing systems, for whether the design of low power hardware architecture or the design of battery-aware scheduling policies. In this paper, we present a physically justified iterative computing method to illustrate the discharge, recovery and charge process of Li/Li-ion batteries. The discharge and recovery processes correspond well to an existing accurate analytical battery model: R-V-W’s analytical model, and thus interpret this model algorithmically. Our method can also extend R-V-W’s model easily to accommodate the charge process. The work will help the system designers to grasp the characteristics of R-V-W’s battery model and also, enable to predict the battery behavior in the charge process in a uniform way as the discharge process and the recovery process. Experiments are performed to show the accuracy of the extended model by comparing the predicted charge times with those derived from the DUALFOIL simulations. Various profiles with different combinations of battery modes were tested. The experimental results show that the extended battery model preserves high accuracy in predicting the charge behavior.

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