Development of a battery runtime prediction algorithm and a method for determining its accuracy

Johnson Controls Battery Group, Inc. (JCBGI) has developed a battery performance algorithm which provides an accurate runtime prediction via continuous battery monitoring. The Energy Eye algorithm is based on a mathematical model that describes the batteries´ relative state-of-charge as a function of voltage and discharge rate. Each battery design used with the algorithm has a unique set of mathematical constants derived from a comprehensive testing regime. The algorithm provides an accurate runtime prediction with stable output under constant and dynamic loads. It is compatible with continuous monitoring and updates battery performance using readily monitorable battery information. The algorithm also possesses a learning capacity to provide improved predictive capability, with an accurate and conservative prediction in the critical time frame near the end-of-discharge