Improving charging efficiency with workload scheduling in energy harvesting embedded systems

In energy harvesting embedded systems, if the harvested power is sufficient for the workload, extra power will be stored in the electrical energy storage (EES) bank. How much energy can be stored is affected by many factors including the efficiency of the energy harvesting module, the input/output voltage of the DC-DC converters, the status of the EES elements, and the characteristics of the workload. This paper investigates the impact of workload scheduling of the embedded system on the storage efficiency of the EES bank. We first provide an approximated but accurate power consumption model of the DC-DC converter. Based on this model, we analytically prove that an optimal workload schedule is to always execute high power task first. 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.