Maximizing the lifetime of embedded systems powered by fuel cell-battery hybrids

Fuel cells are a viable alternative power source for portable applications. They have higher energy density than traditional Li-ion batteries and can achieve longer lifetime for the same weight or volume. However, because of their limited power density, they can not track fluctuations in the load current fast. A hybrid power source, that consists of a fuel cell and a Li-ion battery, has the advantages of long lifetime and good load following capabilities. In this work, we consider the problem of extending the lifetime of a fuel-cell based hybrid source that is used to provide power to a DVFS processor. We propose a new algorithm that is built on top of an energy based optimization framework. The algorithm simultaneously ad-justs the fuel flow rate (at the producer end), and judiciously scales the load current (at the consumer end) to minimize the energy loss of the hybrid system. Simulations on randomly generated task sets demonstrate the superiority of this algorithm with respect to an algorithm that does not allow adjustment of the fuel flow rate.