Improving energy efficiency for energy harvesting embedded systems

While the energy harvesting system (EHS) supplies green energy to the embedded system, it also suffers from uncertainty and large variation in harvesting rate. This constraint can be remedied by using efficient energy storage. Hybrid Electrical Energy Storage (HEES) system is proposed recently as a cost effective approach with high power conversion efficiency and low self-discharge. In this paper, we propose a fast heuristic algorithm to improve the efficiency of charge allocation and replacement in an EHS/HEES equipped embedded system. The goal of our algorithm is to minimize the energy overhead on the DC-DC converter while satisfying the task deadline constraints of the embedded workload and maximizing the energy stored in the HEES system. We first provide an approximated but accurate power consumption model of the DC-DC converter. Based on this model, the optimal operating point of the system can be analytically solved. Integrated with the dynamic reconfiguration of the HEES bank, our algorithm provides energy efficiency improvement and runtime overhead reduction compared to previous approaches.