Michael Pecht

Life Cycle Engineering (United States) (US)

Research Areas

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H-index

106

Publications

1545

Citations

53485

i10-index

707

Publications & Citations Over Time

Top Cited Publications

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Title	Year	Citations
Deep Residual Shrinkage Networks for Fault Diagnos...	2019	1362
Long Short-Term Memory Recurrent Neural Network fo...	2018	1254
Battery Lifetime Prognostics	2020	1227
Prognostics of lithium-ion batteries based on Demp...	2011	1042
State of charge estimation of lithium-ion batterie...	2013	943
Prognostics and Health Management of Electronics	2008	839
Light emitting diodes reliability review	2011	750
An ensemble model for predicting the remaining use...	2013	655
Remaining Useful Life Estimation Based on a Nonlin...	2012	645
Machine learning pipeline for battery state-of-hea...	2021	585

Publications

1.
Deep Residual Shrinkage Networks for Fault Diagnosis
Year: 2019Citations: 1362DOI: 10.1109/tii.2019.2943898
2.
Long Short-Term Memory Recurrent Neural Network for Remaining Useful Life Prediction of Lithium-Ion Batteries
Year: 2018Citations: 1254DOI: 10.1109/tvt.2018.2805189
3.
Battery Lifetime Prognostics
Year: 2020Citations: 1227DOI: 10.1016/j.joule.2019.11.018
4.
Prognostics of lithium-ion batteries based on Dempster–Shafer theory and the Bayesian Monte Carlo method
Year: 2011Citations: 1042DOI: 10.1016/j.jpowsour.2011.08.040
5.
State of charge estimation of lithium-ion batteries using the open-circuit voltage at various ambient temperatures
Year: 2013Citations: 943DOI: 10.1016/j.apenergy.2013.07.008
6.
Prognostics and Health Management of Electronics
Year: 2008Citations: 839DOI: 10.1002/9780470385845
7.
Light emitting diodes reliability review
Year: 2011Citations: 750DOI: 10.1016/j.microrel.2011.07.063
8.
An ensemble model for predicting the remaining useful performance of lithium-ion batteries
Year: 2013Citations: 655DOI: 10.1016/j.microrel.2012.12.003
9.
Remaining Useful Life Estimation Based on a Nonlinear Diffusion Degradation Process
Year: 2012Citations: 645DOI: 10.1109/tr.2011.2182221
10.
Machine learning pipeline for battery state-of-health estimation
Year: 2021Citations: 585DOI: 10.1038/s42256-021-00312-3

About Michael Pecht

Michael Pecht is a researcher with 1545 publications and 53485 citations. They are affiliated with Life Cycle Engineering (United States). Their research focuses on . With an h-index of 106, they are among the top researchers in their field.

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