An effective method for state-of-charge estimation in wireless sensor networks

This poster shows the work-in-progress results of an effective method for predicting the residual battery energy in WSN nodes including the battery behavior. This method uses a hybrid approach consisting of a deterministic part by counting credit points for any operation of the sensor node and a model-based State-of-Charge (SoC) estimation based on battery voltage and temperature. It is applied for Li-Ion accumulators on modified Tmote Sky motes. For demonstration purposes the method is used for cluster head selection in a cluster-based topology formation algorithm to ensure equal distribution of the cluster head role among the network nodes based on the residual energy.