1. Controller design for polymer electrolyte membrane fuel cell systems for automotive applications
- Author
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Juan Carlos Carracedo Gomez, Attila Husar, Maria Pina Serra, Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya. Departament de Mecànica de Fluids, Universitat Politècnica de Catalunya. SAC - Sistemes Avançats de Control, Universitat Politècnica de Catalunya. GReCEF- Grup de Recerca en Ciència i Enginyeria de Fluids, Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), European Commission, Ministerio de Economía y Competitividad (España), and Fuel Cells and Hydrogen 2 Joint Undertaking
- Subjects
Non-linear model predictive control ,Informàtica::Automàtica i control [Àrees temàtiques de la UPC] ,Electric vehicles ,Fuel cell system ,Computer science ,Automotive application ,Automotive industry ,Energy Engineering and Power Technology ,Proton exchange membrane fuel cell ,Time horizon ,02 engineering and technology ,010402 general chemistry ,01 natural sciences ,7. Clean energy ,Transport control ,Piles de combustible ,Fuel cells ,Zero emission ,Renewable Energy, Sustainability and the Environment ,business.industry ,Control engineering ,Efficiency optimization ,021001 nanoscience & nanotechnology ,Condensed Matter Physics ,Power system control ,0104 chemical sciences ,Model predictive control ,Fuel Technology ,Vehicles elèctrics ,Cascade ,Control system ,Control structure ,0210 nano-technology ,business ,Driving cycle - Abstract
Continuous developments in Proton Exchange Membrane Fuel Cells (PEMFC) make them a promising technology to achieve zero emissions in multiple applications including mobility. Incremental advancements in fuel cells materials and manufacture processes make them now suitable for commercialization. However, the complex operation of fuel cell systems in automotive applications has some open issues yet. This work develops and compares three different controllers for PEMFC systems in automotive applications. All the controllers have a cascade control structure, where a generator of setpoints sends references to the subsystems controllers with the objective to maximize operational efficiency. To develop the setpoints generators, two techniques are evaluated: off-line optimization and Model Predictive Control (MPC). With the first technique, the optimal setpoints are given by a map, obtained off-line, of the optimal steady state conditions and corresponding setpoints. With the second technique, the setpoints time profiles that maximize the efficiency in an incoming time horizon are continuously computed. The proposed MPC architecture divides the fast and slow dynamics in order to reduce the computational cost. Two different MPC solutions have been implemented to deal with this fast/slow dynamics separation. After the integration of the setpoints generators with the subsystems controllers, the different control systems are tested and compared using a dynamic detailed model of the automotive system in the INN-BALANCE project running under the New European Driving Cycle., This work was supported in part by the Spanish national project DOVELAR (RTI2018-096001-B-C32, MINECO/FEDER) also in part by the Spanish State Research Agency through the María de Maeztu Seal of Excellence to IRI (MDM-2016-0656), and finally in part by the Fuel Cells and Hydrogen 2 Joint Undertaking under Grant INN-BALANCE 735969. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation program and Hydrogen Europe and N. ERGHY.
- Published
- 2021