Multivariate degradation modeling using generalized cauchy process and application in life prediction of dye-sensitized solar cells
Asgari, Ali Si, Wujun Wei, Wei Krishnan, Krishna K. Liu, Kunpeng
Asgari, Ali
Si, Wujun
Wei, Wei
Krishnan, Krishna K.
Liu, Kunpeng
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2025-03
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Article
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Generalized cauchy process,Lifetime prediction,Local irregularity,Long memory,Solar cell
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Ali Asgari, Wujun Si, Wei Wei, Krishna Krishnan, Kunpeng Liu, Multivariate degradation modeling using generalized cauchy process and application in life prediction of dye-sensitized solar cells, Reliability Engineering & System Safety, Volume 255, 2025, 110651, ISSN 0951-8320, https://doi.org/10.1016/j.ress.2024.110651.
Abstract
Recently, the Generalized Cauchy (GC) process has been applied to capture a Long Memory (LM) phenomenon in product degradation modeling and life prediction. Compared with the traditional fractional Brownian motion that captures the LM using a single Hurst parameter, the GC process has two free parameters (Hurst and fractal dimension parameters) that flexibly capture both global LM and local irregularity. However, all existing GC-based degradation models are for a single Degradation Characteristic (DC). In this article, motivated by a real degradation problem of dye-sensitized solar cells that jointly exhibits multiple DCs, global LM, local irregularity and DC-wise cross-correlation, we propose a novel GC-based Multivariate Degradation Model (GC-MDM) to simultaneously capture the aforementioned effects. A maximum likelihood estimation approach is developed to estimate parameters of the GC-MDM. Subsequently, product life prediction based on the GC-MDM is developed. The proposed GC-MDM is validated through a simulation study and a physical experiment of dye-sensitized solar cells. Results show that the proposed GC-MDM fundamentally improves the life prediction accuracy in comparison with conventional degradation models which significantly misestimate the uncertainty of product life. © 2024 Elsevier Ltd
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Elsevier Ltd
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Reliability Engineering and System Safety
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09518320