Fast computational framework for optimal life management of lithium ion batteries

Fast computational framework for optimal life management of lithium ion batteries The determination of optimal charging profiles over cycle life of a lithium ion battery is a challenging problem that is extremely important for commercial applications. It is a difficult problem to solve owing to the complex degradation processes occurring inside the battery. Further, modeling of a realistic battery operation, let alone the degradation mechanisms, results in computationally expensive mathematical models. In the present study, a framework is developed towards addressing this problem by (1) developing a method to formulate extremely fast and accurate algebraic models that capture essential features such as charging time and aging characteristics described by battery models and (2) utilizing these algebraic models in an optimization framework involving genetic algorithms for determining the optimal charging profiles over the cycle life of the battery. The utility of the present framework in determining the optimal charging solutions is illustrated with various real‐life usage scenarios such as fast charging and extension of cycle life. The proposed solution can be utilized onboard for generating the optimal charging profiles over cycle life of the battery. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Energy Research Wiley

Fast computational framework for optimal life management of lithium ion batteries

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Publisher
Wiley Subscription Services, Inc., A Wiley Company
Copyright
Copyright © 2018 John Wiley & Sons, Ltd.
ISSN
0363-907X
eISSN
1099-114X
D.O.I.
10.1002/er.3996
Publisher site
See Article on Publisher Site

Abstract

The determination of optimal charging profiles over cycle life of a lithium ion battery is a challenging problem that is extremely important for commercial applications. It is a difficult problem to solve owing to the complex degradation processes occurring inside the battery. Further, modeling of a realistic battery operation, let alone the degradation mechanisms, results in computationally expensive mathematical models. In the present study, a framework is developed towards addressing this problem by (1) developing a method to formulate extremely fast and accurate algebraic models that capture essential features such as charging time and aging characteristics described by battery models and (2) utilizing these algebraic models in an optimization framework involving genetic algorithms for determining the optimal charging profiles over the cycle life of the battery. The utility of the present framework in determining the optimal charging solutions is illustrated with various real‐life usage scenarios such as fast charging and extension of cycle life. The proposed solution can be utilized onboard for generating the optimal charging profiles over cycle life of the battery.

Journal

International Journal of Energy ResearchWiley

Published: Jan 1, 2018

Keywords: ; ; ; ; ;

References

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