Journal of Energy and Power Technology (JEPT) is an international peer-reviewed Open Access journal published quarterly online by LIDSEN Publishing Inc. This periodical is dedicated to providing a unique, peer-reviewed, multi-disciplinary platform for researchers, scientists and engineers in academia, research institutions, government agencies and industry. The journal is also of interest to technology developers, planners, policy makers and technical, economic and policy advisers to present their research results and findings.
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Modeling and Control of Fuel Cell Systems
Submission Deadline: July 31, 2020 (Closed) Submit Now
Ramon Costa-Castello, PhD
Associate Professor, Department d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial (ESAII), Universitat Politècnica de Catalunya (UPC), Barcelona, Spain
Research Interests: fuel cell systems modeling and control; energy management, control systems design; automatic control education
About This Topic
Fuel cells are very efficient electrical and thermal energy generation elements. In recent times a lot of research has been done in this area both in the field of materials and structures. Another important area is the obtaining of modeling and calibration methods, as well as the design of the control systems or the integration of fuel cells in larger energy systems.
In this issue, we describe the main contributions in the field of modeling, control and energy management of fuel cell systems.
Fuel cell; PEMFC; SOFC; Control systems; Optimal control; Efficiency; Observer design
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Received: 31 July 2020; Published: 18 January 2021; doi: 10.21926/jept.2101004
This report is an account of research and development activities undertaken by the Centre for Process Systems Computations, Department of Chemical Engineering at Curtin University, Western Australia in the area of solid oxide fuel cells. The focus of work of the group included 1)effect of cell macrostructure and microstructure on electrochemic [...]
Online State of Charge Prediction in Next Generation Vehicle Batteries Using Deep Recurrent Neural Networks and Continuous Model Size Control
Received: 31 July 2020; Published: 12 January 2021; doi: 10.21926/jept.2101003
This investigation presents a data-driven Long-short Term Memory battery model for predicting State of Charge for lithium-ion batteries LiFePO4 for next-generation vehicle operations. Our modified algorithm builds and updates a model using multivariate inputs that include physical properties, voltage, current, and ambient temperature during [...]
Received: 03 June 2020; Published: 24 July 2020; doi: 10.21926/jept.2003011
The fluctuations in the cost of energy coupled with the gradual decrease in natural resources (i.e., oil, natural gas, coal) and the environmental issues caused by the extensive use of fossil fuels, demand the urgent need for the development of advanced and clean energy systems. The European Union has requested new measures to target climate [...]