An efficient state of charge prediction model for solar harvesting WSN platforms

Harvesting energy from the environment has the potential to enable near-perpetual system operation. This comes at the cost of an increased complexity of both the hardware and software that respectively provide and use those features. In this paper we characterize a solar energy harvesting WSN platform using a high level and global approach. The harvesting transducer, the capacity of the battery, the platform load and the application behavior are modeled. We also propose a generic model for the prediction of the State of Charge (SoC) of the battery and we extract high level parameters that can be exploited by a power manager.