This paper is concerned with the problem of maximizing capacity utilization of the battery power source in a portable electronic system under latency and loss rate constraints. First, a detailed stochastic model of a power-managed, battery-powered electronic system is presented. The model, which is based on the theories of continuous-time Markovian decision processes and stochastic networks, captures two important characteristics of today's rechargeable battery cells, i.e., the current rate-capacity characteristic and the relaxation-induced recovery. Next, the battery-aware dynamic power management problem is formulated as a policy optimization problem and solved exactly by using a linear programming approach. Experimental results show that the proposed method outperforms existing heuristic methods for battery management by as much as 17% in terms of the average energy delivered per unit weight of battery cells. 0-7803-7607-2/02/$17.00 ©2002 IEEE
Rong et al. presented a stochastic model for a power-managed, battery-powered electronic system, and formulated a policy optimization problem to maximize the capacity utilization of the battery powered systems REF .
Battery-aware power management based on Markovian decision processes
ICCAD 2002
Computer Science