Portable and wearable computers can be powered by different combinations of two or more battery packs to give the user the possibility of choosing an optimal compromise between lifetime and weight/size. Recent work on battery-driven power management has demonstrated that sequential discharge is suboptimal in multibattery systems and lifetime can be maximized by distributing (steering) the current load on the available batteries, thereby discharging them in a partially concurrent fashion. Based on these observations, we formulate multibattery lifetime maximization as a continuous, constrained optimization problem, which can be efficiently solved by nonlinear optimizers. We show that significant lifetime extensions can be obtained with respect to standard sequential discharge (up to 160 percent), as well to previously proposed battery scheduling algorithms (up to 12 percent).

Discharge Current Steering for Battery Lifetime Optimization / Benini, L.; Bruni, D.; Macii, Alberto; Macii, Enrico; Poncino, M.. - In: IEEE TRANSACTIONS ON COMPUTERS. - ISSN 0018-9340. - 52:(2003), pp. 985-995. [10.1109/TC.2003.1223633]

Discharge Current Steering for Battery Lifetime Optimization

MACII, Alberto;MACII, Enrico;PONCINO M.
2003

Abstract

Portable and wearable computers can be powered by different combinations of two or more battery packs to give the user the possibility of choosing an optimal compromise between lifetime and weight/size. Recent work on battery-driven power management has demonstrated that sequential discharge is suboptimal in multibattery systems and lifetime can be maximized by distributing (steering) the current load on the available batteries, thereby discharging them in a partially concurrent fashion. Based on these observations, we formulate multibattery lifetime maximization as a continuous, constrained optimization problem, which can be efficiently solved by nonlinear optimizers. We show that significant lifetime extensions can be obtained with respect to standard sequential discharge (up to 160 percent), as well to previously proposed battery scheduling algorithms (up to 12 percent).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/1402075
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