What is he best known for?
The fields of study he is best known for:
- Composite material
- Electrical engineering
- Statistics
Michael Pecht mainly focuses on Reliability engineering, Prognostics, Reliability, Electronics and Battery.
His work investigates the relationship between Reliability engineering and topics such as Physics of failure that intersect with problems in Feature extraction.
In his study, which falls under the umbrella issue of Prognostics, Mahalanobis distance is strongly linked to Condition monitoring.
The study incorporates disciplines such as Field, Forensic engineering and Product in addition to Reliability.
Michael Pecht interconnects Manufacturing engineering and Printed circuit board in the investigation of issues within Electronics.
His work carried out in the field of Battery brings together such families of science as Simulation, Lithium and Voltage.
His most cited work include:
- Prognostics and health management of electronics (669 citations)
- Light emitting diodes reliability review (490 citations)
- Light emitting diodes reliability review (490 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Reliability engineering, Prognostics, Reliability, Electronics and Composite material.
His Reliability engineering study which covers Battery that intersects with Lithium.
Many of his studies on Prognostics involve topics that are commonly interrelated, such as Condition monitoring.
His research on Electronics frequently links to adjacent areas such as Manufacturing engineering.
Michael Pecht works in the field of Composite material, namely Soldering.
He studied Soldering and Printed circuit board that intersect with Electronic engineering.
He most often published in these fields:
- Reliability engineering (26.55%)
- Prognostics (16.58%)
- Reliability (15.36%)
What were the highlights of his more recent work (between 2017-2021)?
- Reliability engineering (26.55%)
- Battery (6.94%)
- Artificial intelligence (5.15%)
In recent papers he was focusing on the following fields of study:
Michael Pecht mainly investigates Reliability engineering, Battery, Artificial intelligence, Electronics and Prognostics.
His Reliability engineering research is multidisciplinary, incorporating perspectives in Reliability and Degradation.
His Battery study integrates concerns from other disciplines, such as Nuclear engineering and Lithium.
His Artificial intelligence research is multidisciplinary, relying on both Fault, Machine learning and Pattern recognition.
His Electronics study often links to related topics such as Reliability.
State of charge is frequently linked to Control theory in his study.
Between 2017 and 2021, his most popular works were:
- Long Short-Term Memory Recurrent Neural Network for Remaining Useful Life Prediction of Lithium-Ion Batteries (203 citations)
- A review of fractional-order techniques applied to lithium-ion batteries, lead-acid batteries, and supercapacitors (152 citations)
- A Double-Scale, Particle-Filtering, Energy State Prediction Algorithm for Lithium-Ion Batteries (110 citations)
In his most recent research, the most cited papers focused on:
- Composite material
- Electrical engineering
- Statistics
Michael Pecht spends much of his time researching Battery, Fault, Lithium, Reliability engineering and State of charge.
Michael Pecht works mostly in the field of Battery, limiting it down to topics relating to Voltage and, in certain cases, Electronic engineering, as a part of the same area of interest.
The Lithium study combines topics in areas such as Particle filter and Automotive engineering.
His study in Reliability engineering focuses on Prognostics in particular.
His Prognostics study combines topics in areas such as Feature extraction, Condition monitoring, Process and Electronics.
As a part of the same scientific study, Michael Pecht usually deals with the State of charge, concentrating on Control theory and frequently concerns with Algorithm.
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