Improving Charging Efficiency in Energy Harvesting Embedded Systems with Workload Scheduling

The limited lifetime of the Electrical Energy Storage system (EES) & the unstableness of the Energy Harvesting (EH) system can be overcome by combining these two together to an energy harvesting embedded system and making them work cooperatively. In this system external energy is harvested to power the embedded systems. If harvested energy is enough to carry workload, extra power will be stored in electrical storage bank. Amount of energy storage is affected by various factors such as workload characteristics, efficiency of the energy harvesting module, the input/output voltage of the DC-DC converters & EES elements status. Aim is to store maximum energy in EES banks. This paper investigates how the storage efficiency of EES bank is affected by the workload scheduling of the embedded system. A DC-DC converter power consumption model is introduced and based on this model our analysis proves that in workload scheduling execution of high power task should be prioritized. Experimental results confirm that proposed scheduling strategy outperforms all other possible scheduling and increases the amount of stored energy by up to 10.41% in average.