TY  - JOUR
A1  - Fayyazi, Mojgan
A1  - Sardar, Paramjotsingh
A1  - Thomas, Sumit Infent
A1  - Daghigh, Roonak
A1  - Jamali, Ali
A1  - Esch, Thomas
A1  - Kemper, Hans
A1  - Langari, Reza
A1  - Khayyam, Hamid
T1  - Artificial intelligence/machine learning in energy management systems, control, and optimization of hydrogen fuel cell vehicles
N2  - Environmental emissions, global warming, and energy-related concerns have accelerated the advancements in conventional vehicles that primarily use internal combustion engines. Among the existing technologies, hydrogen fuel cell electric vehicles and fuel cell hybrid electric vehicles may have minimal contributions to greenhouse gas emissions and thus are the prime choices for environmental concerns. However, energy management in fuel cell electric vehicles and fuel cell hybrid electric vehicles is a major challenge. Appropriate control strategies should be used for effective energy management in these vehicles. On the other hand, there has been significant progress in artificial intelligence, machine learning, and designing data-driven intelligent controllers. These techniques have found much attention within the community, and state-of-the-art energy management technologies have been developed based on them. This manuscript reviews the application of machine learning and intelligent controllers for prediction, control, energy management, and vehicle to everything (V2X) in hydrogen fuel cell vehicles. The effectiveness of data-driven control and optimization systems are investigated to evolve, classify, and compare, and future trends and directions for sustainability are discussed.
KW  - optimization system
KW  - intelligent control
KW  - fuel cell vehicle
KW  - machine learning
KW  - artificial intelligence
KW  - intelligent energy management
Y1  - 2023
U6  - https://doi.org/10.3390/su15065249
N1  - This article belongs to the Special Issue "Circular Economy and Artificial Intelligence"
VL  - 15
IS  - 6
SP  - 38
PB  - MDPI
CY  - Basel
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TY  - JOUR
A1  - Schöning, Michael Josef
A1  - Turek, M.
A1  - Heiden, W.
A1  - Riesen, A.
A1  - Chhabda, T. A.
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A1  - Krüger, P.
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T1  - Artificial intelligence/fuzzy logic method for analysis of combined signals from heavy metal chemical sensors
JF  - Electrochimica Acta. 54 (2009), H. 25 Sp. Iss. SI
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PB  - Elsevier
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A1  - Raptis, Y. S.
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A1  - Quernheim, Ulrich
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Y1  - 1990
SN  - 0444888721
N1  - International Federation for Information Processing ; COMNET ; (1990, Budapest)
PB  - Elsevier
CY  - New York, N.Y.
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A1  - Bergmann, Ole
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A1  - Machado, Patricia
A1  - Morrison, Audry
A1  - Page, Henry
A1  - Pluta, Emil
A1  - Stübing, Felix
A1  - Küpper, Thomas
T1  - Are small airplanes safe with regards to COVID-19 transmission?
JF  - Journal of Travel Medicine
Y1  - 2021
U6  - https://doi.org/10.1093/jtm/taab105
SN  - 1708-8305
VL  - 28
IS  - 7
PB  - Oxford University Press
CY  - Oxford
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A1  - Wilke, Thomas
T1  - Architekturzeichnung als Instrument der Theoriebildung. Lineamenta vs. Portraicture – Architekturdarstellung zwischen Wissenschaft und Öffentlichkeit. Tagung des DFG-Netzwerks-Schnittstelle Bild in Zusammenarbeit mit dem Lehrstuhl für Kunstgeschichte der Universität Regensburg, 28.4.2012.
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