Description

The portable devices for battery health and charge monitoring are always a challenge for engineers. This work is coin for development of micro-controller based smart instruments to indicate status of battery. It aims to develop an artificial intelligence based battery monitoring instrument which indicates the charge status of the battery. The instrument uses a Neuro-Fuzzy approach coupled with on line sensing of parameters to map the battery behaviour. The battery behaviour shows non-linear characteristics due to complex physical and chemical process and is hard to predict. This behaviour is understood by modelling the physical parameters. The soft computing techniques (artificial neural network and fuzzy logic) have been used to model the battery behaviour using easily measurable five parameters viz. voltage, current, internal resistance, temperature and consumption time. The developed instrument predicts battery status on line and indicates the battery status in terms of state of charge that results in timely detection of faulty state of the battery which is very essential for reliability and safety of all instruments.

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