Development of Control Systems and State Observers for Efficiency and Durability Improvement in PEM Fuel Cell Based Systems PDF Download

Author: Julio Alberto Luna Pacho
Publisher:
ISBN:
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Languages : en
Pages : 216

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Book Description
Proton exchange membrane (PEM) fuel cells, which use hydrogen as fuel, provide high power densities while operating at lower temperatures, reducing the cost of materials and maintenance. PEM fuel cells are suitable for a broad range of applications, such as stationary, combined heat and power (CHP), portable systems and automotive. Performance and degradation in PEM fuel cell-based systems is greatly influenced by the internal conditions of the fuel cell. In this doctoral thesis, an extensive study of modelling, observation and control strategies of a PEM fuel cell-based system is performed. The objective is to obtain advanced control solutions that aid to enhance the durability and improve the efficiency of fuel cells. These control solutions have to take into account the internal conditions of the fuel cell and use this information to operate the system under conditions that guarantee that the degradation rate of the fuel cell is not increased. At the same time, the controllers have to guarantee that the system achieves high efficiencies, considering the parasitic power consumption of the balance of plant (BoP) ancillaries. The observation and control solutions are evaluated using the New European Driving Cycle (NEDC) profile as a case study. The first part of the thesis introduces the motivation of the present work and the structure of the document. Additionally, the current state of the research regarding modelling, state observers and control strategies for PEM fuel cell-based systems are studied in detail. After the study of the state of the art, the objectives of this doctoral work are presented. The second part of the thesis is focused on the development, implementation and study in a simulation environment of a PEM fuel cell-based system model. The model considers spatial derivatives for the fuel cell in order to represent the internal dynamic behaviour, which affects the efficiency and degradation rate of the system. In this thesis, a special attention is given to the electrochemically active surface area (ECSA). The ECSA in the cathode catalyst layer (CCL) is modelled using a twophase water model at the cathode side of the fuel cell to better represent its effect on the output voltage. The BoP ancillaries are considered as a parasitic power consumption that has to be delivered by the fuel cell. The most relevant parasitic power consumption is that of the compressor, which is modelled to include its dynamic behaviour in the control strategies. Once the model equations are presented, model-based nonlinear distributed parameters observers (NDPO) are developed in the third part of the thesis. First, the partial differential equations (PDE) of the PEM fuel cell-based system are discretised and reformulated to obtain the observation model. Using this model, two novel sliding mode control (SMC) approaches for the observation of the internal conditions of the fuel cell are presented and compared, using the NEDC current profile as the case study for the simulations. The fourth part of the thesis is devoted to model-based predictive control of the PEM fuel cell-based system. In particular, a nonlinear model predictive control (NMPC) strategy is proposed to improve the efficiency and at the same time, enhance the lifetime of the fuel cell. The use of the NDPOs in the control scheme facilitates critical information about the internal conditions of the fuel cell. This allows to design advanced control objectives that would not be achievable if using only the limited measurements that are available in PEM fuel cell-based systems. A multi-objective cost function that can prioritise between the different objectives of the controller during the optimisation procedure is designed. Finally, a discussion of the results obtained comparing different prioritisation between control objectives is provided. The fifth and last part of the thesis is devoted to extract conclusions.