TY - GEN
T1 - Maximizing the lifetime of embedded systems powered by fuel cell-battery hybrids
AU - Zhuo, Jianli
AU - Chakrabarti, Chaitali
AU - Chang, Naehyuck
AU - Vrudhula, Sarma
PY - 2006
Y1 - 2006
N2 - 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 adjusts 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.
AB - 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 adjusts 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.
KW - Battery
KW - DVFS system
KW - Fuel cell
KW - Hybrid systems
KW - Task scaling
UR - http://www.scopus.com/inward/record.url?scp=34247250734&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=34247250734&partnerID=8YFLogxK
U2 - 10.1145/1165573.1165676
DO - 10.1145/1165573.1165676
M3 - Conference contribution
AN - SCOPUS:34247250734
SN - 1595934626
SN - 9781595934628
T3 - Proceedings of the International Symposium on Low Power Electronics and Design
SP - 424
EP - 429
BT - ISLPED'06 - Proceedings of the 2006 International Symposium on Low Power Electronics and Design
T2 - ISLPED'06 - 11th ACM/IEEE International Symposium on Low Power Electronics and Design
Y2 - 4 October 2006 through 6 October 2006
ER -