Piezoelectric energy harvester lifetime prognostics by novel Gaidai multi-modal reliability scheme

Abstract

Green Energy Harvesters (EH) are nowadays quite an important component of the contemporary green energy sector; thus, experimental data is required for their robust design validation. Existing reliability concepts are not applicable to dynamic systems possessing dimensionality above bivariate, except Monte Carlo-based methods, which are not applicable to measured data, or FORM, SORM methods that require prior knowledge of the underlying distribution. Existing system reliability methods are not always well suited to treat the latter problems, especially given the high-dimensional spatiotemporal nature of the nonlinearity of both system and environmental loadings. Presented case study proposes generic, state-of-the-art multivariate reliability methodology, assessing complex nonlinear system’s lifetime distribution, based on even a limited underlying dataset, extracted from an empirically recorded dynamic system time history. A comprehensive state-of-the-art multivariate reliability assessment along with methodological benchmarking was carried out. Methodology advocated in this study is not only applicable to energy harvesting devices; it can also be utilized for a range of engineering complex sustainable systems, subjected to environmental loads during designed service life. Novelty: presented case study benchmarks state-of-the-art, Gaidai multivariate reliability approach for evaluating an energy system’s operational lifetime, that is especially well suited for complex engineering systems, possessing high dimensionality, accompanied by complex inter-correlations between system primary dimensions or components.