This study is devoted to a proper modeling and estimation method of battery capacity fading under the widely adopted exponential decay model, in view of an efficient lifetime assessment of battery. The method is based upon recursive online Bayes estimation of capacity fading. It is also shown how a degradation-based modeling of battery reliability can be adopted, leading to a Bernstein lifetime distribution. The performances of the proposed method are successfully evaluated by means of extensive Monte Carlo simulations based upon available literature and experimental data. A brief account is also given of a robustness analysis of the proposed methodology with respect to departures from the assumption of Gaussian noise.

On line Bayes Estimation of Capacity Fading for Battery Lifetime Assessment

Andrenacci N.
2019

Abstract

This study is devoted to a proper modeling and estimation method of battery capacity fading under the widely adopted exponential decay model, in view of an efficient lifetime assessment of battery. The method is based upon recursive online Bayes estimation of capacity fading. It is also shown how a degradation-based modeling of battery reliability can be adopted, leading to a Bernstein lifetime distribution. The performances of the proposed method are successfully evaluated by means of extensive Monte Carlo simulations based upon available literature and experimental data. A brief account is also given of a robustness analysis of the proposed methodology with respect to departures from the assumption of Gaussian noise.
978-1-7281-1356-2
Battery; Bayes Estimation; Bernstein Distribution; capacity prediction; Kalman filter; Reliability
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12079/54255
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