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Model predictive control (MPC) strategies for PEM fuel cell systems – A comparative experimental demonstration
- Source :
- Chemical Engineering Research and Design. 131:656-670
- Publication Year :
- 2018
- Publisher :
- Elsevier BV, 2018.
-
Abstract
- The aim of this work is to demonstrate the response of advanced model-based predictive control (MPC) strategies for Polymer Electrolyte Membrane Fuel cell (PEMFC) systems. PEMFC are considered as an interesting alternative to conventional power generation and can be used in a wide range of stationary and mobile applications. An integrated and modular computer-aided Energy Management Framework (EMF) is developed and deployed online to an industrial automation system for monitoring and operation of a PEMFC testing unit at CERTH/CPERI. The operation objectives are to deliver the demanded power while operating at a safe region, avoiding starvation, and concurrently minimize the fuel consumption at stable temperature conditions. A dynamic model is utilized and different MPC strategies are online deployed (Nonlinear MPC, multiparametric MPC and explicit Nonlinear MPC). The response of the MPC strategies is assessed through a set of comparative experimental studies, illustrating that the control objectives are achieved and the fuel cell system operates economically and at a stable environment regardless of the varying operating conditions.
- Subjects :
- Energy management
business.industry
Computer science
020209 energy
General Chemical Engineering
Proton exchange membrane fuel cell
02 engineering and technology
General Chemistry
Modular design
Automation
Automotive engineering
Model predictive control
Electricity generation
020401 chemical engineering
Range (aeronautics)
0202 electrical engineering, electronic engineering, information engineering
Fuel efficiency
0204 chemical engineering
business
Subjects
Details
- ISSN :
- 02638762
- Volume :
- 131
- Database :
- OpenAIRE
- Journal :
- Chemical Engineering Research and Design
- Accession number :
- edsair.doi...........37a7cca2db0cbdcc82e6c1be10dcbdda
- Full Text :
- https://doi.org/10.1016/j.cherd.2018.01.024