A battery life prediction method for hybrid power applications

Abstract

Batteries in hybrid power applications that include intermittent generators, such as wind turbines, experience a very irregular pattern of charge and discharge cycles. Because battery life is dependent on both depth and rate of discharge (and other factors such as temperature, charging strategy, etc.), estimating battery life and optimally sizing batteries for hybrid systems is difficult. Typically, manufacturers give battery life data, if at all, as cycles to failure versus depth of discharge, where all discharge cycles are assumed to be under conditions of constant temperature, current, and depth of discharge. Use of such information directly can lead to gross errors in battery lifetime estimation under actual operating conditions, which may result in either a higher system cost than necessary or an undersized battery bank prone to early failure. Even so, most current battery life estimation algorithms consider only the effect of depth of discharge on cycle life. This paper will discuss a new battery life prediction method, developed to investigate the effects of two primary determinants of battery life in hybrid power applications, varying depths of discharge and varying rates of discharge. A significant feature of the model is that it bases its analysis on battery performance and cyclemore » life data provided by the manufacturer, supplemented by a limited amount of empirical test data, eliminating the need for an electrochemical model of the battery. It performs the analysis for a user-prescribed discharge profile consisting of a series of discharge events of specified average current and duration. Sample analyses are presented to show how the method can be used to select the most economical battery type and size for a given hybrid power system application.« less