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Energies 2017, 10(11), 1687; doi:10.3390/en10111687

A Novel Multi-Phase Stochastic Model for Lithium-Ion Batteries’ Degradation with Regeneration Phenomena

1
Department of Automation, Xi’an Research Institute of High-Tech, Xi’an 710025, China
2
Department of Automation, Tsinghua University, Beijing 100084, China
3
College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao 266510, China
*
Authors to whom correspondence should be addressed.
Received: 1 October 2017 / Revised: 16 October 2017 / Accepted: 16 October 2017 / Published: 25 October 2017
(This article belongs to the Special Issue 2017 Prognostics and System Health Management Conference)
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Abstract

A lithium-Ion battery is a typical degradation product, and its performance will deteriorate over time. In its degradation process, regeneration phenomena have been frequently encountered, which affect both the degradation state and rate. In this paper, we focus on how to build the degradation model and estimate the lifetime. Toward this end, we first propose a multi-phase stochastic degradation model with random jumps based on the Wiener process, where the multi-phase model and random jumps at the changing point are used to describe the variation of degradation rate and state caused by regeneration phenomena accordingly. Owing to the complex structure and random variables, the traditional Maximum Likelihood Estimation (MLE) is not suitable for the proposed model. In this case, we treat these random variables as latent parameters, and then develop an approach for model identification based on expectation conditional maximum (ECM) algorithm. Moreover, depending on the proposed model, how to estimate the lifetime with fixed changing point is presented via the time-space transformation technique, and the approximate analytical solution is derived. Finally, a numerical simulation and a practical case are provided for illustration. View Full-Text
Keywords: life prognostics; multi-phase degradation; Expectation Conditional Maximization algorithm; regeneration phenomena; Bayesian rule life prognostics; multi-phase degradation; Expectation Conditional Maximization algorithm; regeneration phenomena; Bayesian rule
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Zhang, J.; He, X.; Si, X.; Hu, C.; Zhou, D. A Novel Multi-Phase Stochastic Model for Lithium-Ion Batteries’ Degradation with Regeneration Phenomena. Energies 2017, 10, 1687.

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