A Score Function for Optimizing the Cycle-Life of Battery-Powered Embedded Systems

Erik Ramsgaard Wognsen; Boudewijn R.H.M. Haverkort; M.R. Jongerden; René Rydhof Hansen; K.G. Larsen; Sriram Sankaranarayanan; Enrico Vicario

doi:10.1007/978-3-319-22975-1_20

A Score Function for Optimizing the Cycle-Life of Battery-Powered Embedded Systems

Erik Ramsgaard Wognsen, Boudewijn R.H.M. Haverkort, M.R. Jongerden, René Rydhof Hansen, K.G. Larsen, Sriram Sankaranarayanan (Editor), Enrico Vicario (Editor)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

20 Citations (Scopus)

Abstract

An ever increasing share of embedded systems is powered by rechargeable batteries. These batteries deteriorate with the number of charge/discharge cycles they are subjected to, the so-called cycle life. In this paper, we propose the wear score function to compare and evaluate the relative impact of usage (charge and discharge) profiles on cycle life. The wear score function can not only be used to rank different usage profiles, these rankings can also be used as a criterion for optimizing the overall lifetime of a battery-powered system. We perform such an optimization on a nano-satellite case study provided by the company GomSpace. The scheduling of the system is modelled as a network of (stochastic) weighted timed games. In a stochastic setting, exact optimization is very expensive. However, the recently introduced Uppaal Stratego tool combines symbolic synthesis with statistical model checking and reinforcement learning to synthesize near-optimal scheduling strategies subject to possible hard timing-constaints. We use this to study the trade-off between optimal short-term dynamic payload selection and the operational life of the satellite.

Original language	English
Title of host publication	Proceedings of the 13th International Conference on Formal Modeling and Analysis of Timed Systems, FORMATS 2015
Editors	Sriram Sankaranarayanan, Enrico Vicario
Place of Publication	London
Publisher	Springer Verlag
Pages	305-320
Number of pages	16
ISBN (Print)	9783319229744
DOIs	https://doi.org/10.1007/978-3-319-22975-1_20
Publication status	Published - Sept 2015
Externally published	Yes
Event	International Conference on Formal Modeling and Analysis of Timed Systems 2015 - Madried, Spain Duration: 2 Sept 2015 → 4 Sept 2015 Conference number: 13 http://formats2015.unifi.it/

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer Verlag
Volume	9268
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Formal Modeling and Analysis of Timed Systems 2015
Abbreviated title	FORMATS 2015
Country/Territory	Spain
City	Madried
Period	2/09/15 → 4/09/15
Internet address	http://formats2015.unifi.it/

Keywords

EC Grant Agreement nr.: FP7/318490
EWI-26287
cycle-life battery
METIS-314963
EC Grant Agreement nr.: FP7/2007-2013
Uppaal Stratego
IR-98150
battery aging

Access to Document

10.1007/978-3-319-22975-1_20

Cite this

Wognsen, E. R., Haverkort, B. R. H. M., Jongerden, M. R., Hansen, R. R., Larsen, K. G., Sankaranarayanan, S. (Ed.), & Vicario, E. (Ed.) (2015). A Score Function for Optimizing the Cycle-Life of Battery-Powered Embedded Systems. In S. Sankaranarayanan, & E. Vicario (Eds.), Proceedings of the 13th International Conference on Formal Modeling and Analysis of Timed Systems, FORMATS 2015 (pp. 305-320). (Lecture Notes in Computer Science; Vol. 9268). Springer Verlag. https://doi.org/10.1007/978-3-319-22975-1_20

Wognsen, Erik Ramsgaard ; Haverkort, Boudewijn R.H.M. ; Jongerden, M.R. et al. / A Score Function for Optimizing the Cycle-Life of Battery-Powered Embedded Systems. Proceedings of the 13th International Conference on Formal Modeling and Analysis of Timed Systems, FORMATS 2015. editor / Sriram Sankaranarayanan ; Enrico Vicario. London : Springer Verlag, 2015. pp. 305-320 (Lecture Notes in Computer Science).

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abstract = "An ever increasing share of embedded systems is powered by rechargeable batteries. These batteries deteriorate with the number of charge/discharge cycles they are subjected to, the so-called cycle life. In this paper, we propose the wear score function to compare and evaluate the relative impact of usage (charge and discharge) profiles on cycle life. The wear score function can not only be used to rank different usage profiles, these rankings can also be used as a criterion for optimizing the overall lifetime of a battery-powered system. We perform such an optimization on a nano-satellite case study provided by the company GomSpace. The scheduling of the system is modelled as a network of (stochastic) weighted timed games. In a stochastic setting, exact optimization is very expensive. However, the recently introduced Uppaal Stratego tool combines symbolic synthesis with statistical model checking and reinforcement learning to synthesize near-optimal scheduling strategies subject to possible hard timing-constaints. We use this to study the trade-off between optimal short-term dynamic payload selection and the operational life of the satellite.",

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Wognsen, ER, Haverkort, BRHM, Jongerden, MR, Hansen, RR, Larsen, KG, Sankaranarayanan, S (ed.) & Vicario, E (ed.) 2015, A Score Function for Optimizing the Cycle-Life of Battery-Powered Embedded Systems. in S Sankaranarayanan & E Vicario (eds), Proceedings of the 13th International Conference on Formal Modeling and Analysis of Timed Systems, FORMATS 2015. Lecture Notes in Computer Science, vol. 9268, Springer Verlag, London, pp. 305-320, International Conference on Formal Modeling and Analysis of Timed Systems 2015, Madried, Spain, 2/09/15. https://doi.org/10.1007/978-3-319-22975-1_20

A Score Function for Optimizing the Cycle-Life of Battery-Powered Embedded Systems. / Wognsen, Erik Ramsgaard; Haverkort, Boudewijn R.H.M.; Jongerden, M.R. et al.
Proceedings of the 13th International Conference on Formal Modeling and Analysis of Timed Systems, FORMATS 2015. ed. / Sriram Sankaranarayanan; Enrico Vicario. London: Springer Verlag, 2015. p. 305-320 (Lecture Notes in Computer Science; Vol. 9268).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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AU - Wognsen, Erik Ramsgaard

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AU - Jongerden, M.R.

AU - Hansen, René Rydhof

AU - Larsen, K.G.

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N2 - An ever increasing share of embedded systems is powered by rechargeable batteries. These batteries deteriorate with the number of charge/discharge cycles they are subjected to, the so-called cycle life. In this paper, we propose the wear score function to compare and evaluate the relative impact of usage (charge and discharge) profiles on cycle life. The wear score function can not only be used to rank different usage profiles, these rankings can also be used as a criterion for optimizing the overall lifetime of a battery-powered system. We perform such an optimization on a nano-satellite case study provided by the company GomSpace. The scheduling of the system is modelled as a network of (stochastic) weighted timed games. In a stochastic setting, exact optimization is very expensive. However, the recently introduced Uppaal Stratego tool combines symbolic synthesis with statistical model checking and reinforcement learning to synthesize near-optimal scheduling strategies subject to possible hard timing-constaints. We use this to study the trade-off between optimal short-term dynamic payload selection and the operational life of the satellite.

AB - An ever increasing share of embedded systems is powered by rechargeable batteries. These batteries deteriorate with the number of charge/discharge cycles they are subjected to, the so-called cycle life. In this paper, we propose the wear score function to compare and evaluate the relative impact of usage (charge and discharge) profiles on cycle life. The wear score function can not only be used to rank different usage profiles, these rankings can also be used as a criterion for optimizing the overall lifetime of a battery-powered system. We perform such an optimization on a nano-satellite case study provided by the company GomSpace. The scheduling of the system is modelled as a network of (stochastic) weighted timed games. In a stochastic setting, exact optimization is very expensive. However, the recently introduced Uppaal Stratego tool combines symbolic synthesis with statistical model checking and reinforcement learning to synthesize near-optimal scheduling strategies subject to possible hard timing-constaints. We use this to study the trade-off between optimal short-term dynamic payload selection and the operational life of the satellite.

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KW - METIS-314963

KW - EC Grant Agreement nr.: FP7/2007-2013

KW - Uppaal Stratego

KW - IR-98150

KW - battery aging

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BT - Proceedings of the 13th International Conference on Formal Modeling and Analysis of Timed Systems, FORMATS 2015

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Wognsen ER, Haverkort BRHM, Jongerden MR, Hansen RR, Larsen KG, Sankaranarayanan S, (ed.) et al. A Score Function for Optimizing the Cycle-Life of Battery-Powered Embedded Systems. In Sankaranarayanan S, Vicario E, editors, Proceedings of the 13th International Conference on Formal Modeling and Analysis of Timed Systems, FORMATS 2015. London: Springer Verlag. 2015. p. 305-320. (Lecture Notes in Computer Science). doi: 10.1007/978-3-319-22975-1_20

A Score Function for Optimizing the Cycle-Life of Battery-Powered Embedded Systems

Abstract

Publication series

Conference

Keywords

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