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Power Management for Controlling Event Detection Probability of Supercapacitor Powered Sensor Networks

In this paper, the power management method of supercapacitor powered systems is developed for a complex sensor network system wherein the sensor footprint depends on the available energy of supercapacitor. With a radar sensor network as an example, it is proved that the event detection probability of the sensor network can be decoupled as the quality of service of each node. Accordingly, the problem of maintaining the event detection probability is formulated as a problem of tracking a reference quality of service value for each sensor node. In this problem formulation, the supercapacitor model and the in-network processing model are used as two of the constraints of the optimization problem, wherein the supercapacitor model captures both the self-discharge and charge-redistribution phenomena to achieve the full potential of the stored energy. Model predictive control is employed to solve the optimization problem with particle swarm optimization, and the simulation results demonstrate that the developed method can track the required quality of service while satisfying the system constraints and ensuring the terminal voltage of the supercapacitor to be within the normal working range.