What is he best known for?
The fields of study he is best known for:
- Electrical engineering
- Mechanical engineering
- Artificial intelligence
His primary scientific interests are in Proton exchange membrane fuel cell, Stack, Reliability engineering, Prognostics and Control engineering.
Proton exchange membrane fuel cell is a subfield of Fuel cells that Marie-Cécile Péra tackles.
His research integrates issues of Power loss and Fault detection and isolation in his study of Reliability engineering.
His work carried out in the field of Control engineering brings together such families of science as Electricity generation, Artificial neural network, Fuzzy logic and Nonlinear system.
He interconnects Behavioral modeling, Automotive engineering, Computer simulation and Electrical engineering in the investigation of issues within Artificial neural network.
Marie-Cécile Péra focuses mostly in the field of Nonlinear system, narrowing it down to topics relating to Control system and, in certain cases, Energy management and MATLAB.
His most cited work include:
- A review on model-based diagnosis methodologies for PEMFCs (171 citations)
- Review of characterization methods for supercapacitor modelling (153 citations)
- A Review on solid oxide fuel cell models (139 citations)
What are the main themes of his work throughout his whole career to date?
Marie-Cécile Péra mostly deals with Proton exchange membrane fuel cell, Stack, Automotive engineering, Control engineering and Energy management.
His Proton exchange membrane fuel cell research is under the purview of Fuel cells.
System model is closely connected to Gas compressor in his research, which is encompassed under the umbrella topic of Automotive engineering.
His Control engineering research is multidisciplinary, relying on both Artificial neural network, Electricity generation, Fuzzy logic, Fault and MATLAB.
His study looks at the intersection of Energy management and topics like Battery with Electrical network.
His Prognostics research is multidisciplinary, incorporating elements of Simulation and State of health.
He most often published in these fields:
- Proton exchange membrane fuel cell (53.19%)
- Stack (29.79%)
- Automotive engineering (26.60%)
What were the highlights of his more recent work (between 2016-2021)?
- Energy management (22.34%)
- Battery (10.64%)
- Automotive engineering (26.60%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Energy management, Battery, Automotive engineering, Reliability engineering and Proton exchange membrane fuel cell.
His research investigates the connection with Energy management and areas like Benchmark which intersect with concerns in Fuzzy logic and Range.
The Automotive engineering study combines topics in areas such as Hydrogen station and Electricity.
The concepts of his Reliability engineering study are interwoven with issues in Recurrent neural network, Echo state network, Scheduling and Voltage.
His Proton exchange membrane fuel cell study combines topics in areas such as Prognostics, Wear and tear and State of health.
Many of his studies involve connections with topics such as Fuel cells and Prognostics.
Between 2016 and 2021, his most popular works were:
- A survey on driving prediction techniques for predictive energy management of plug-in hybrid electric vehicles (66 citations)
- A review of fault tolerant control strategies applied to proton exchange membrane fuel cell systems (39 citations)
- Optimization of Electrical Energy Storage System Sizing for an Accurate Energy Management in an Aircraft (25 citations)
In his most recent research, the most cited papers focused on:
- Electrical engineering
- Mechanical engineering
- Control theory
Marie-Cécile Péra spends much of his time researching Energy management, Control engineering, Control theory, Fault and Identification.
His work focuses on many connections between Energy management and other disciplines, such as Battery, that overlap with his field of interest in Quality, Prediction algorithms and Reliability engineering.
His Control engineering study frequently draws connections between adjacent fields such as Electricity generation.
He has researched Electricity generation in several fields, including Electrical network, Automotive engineering and Filter.
His Fault study combines topics from a wide range of disciplines, such as Artificial neural network, Reservoir computing and Stability.
His research in Identification intersects with topics in Optimal control, Fault tolerance, Isolation, Proton exchange membrane fuel cell and Operating point.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
