Battery Model for Embedded Systems

This paper explores the recovery and rate capacity effect for batteries used in embedded systems. It describes the prominent battery models with their advantages and drawbacks. It then throws new light on the battery recovery behavior, which can help determine optimum discharge profiles and hence result in significant improvement in battery lifetime. Finally it proposes a fast and accurate stochastic model which draws the positives from the earlier models and minimizes the drawbacks. You can also Subscribe to FINAL YEAR PROJECT'S by Email for more such projects and seminar.

The parameters for this model are determined by a pretest, which takes into account the newfound background into recovery and rate capacity hence resulting in higher accuracy. Simulations conducted suggest close correspondence with experimental results and a maximum error of 2.65%.

A battery cell is characterized by the open-circuit potential (VOC), i.e. the initial potential of a fully charged cell. Under no-load conditions, and the cut-off potential (Vcut) at which the cell is considered discharged. Each cell consists of an anode, a cathode and the electrolyte that separates the two electrodes.

Energy-autonomous embedded systems have an attached finite-capacity energy source - a battery that must be relatively small and light for the embedded system to be mobile. Consequently, the system energy budget is severely limited, and efficient energy utilization becomes one of the key problems in the context of battery powered embedded computing.


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