Abstract
A model is an input–output mapping that suitably explains the behavior of a system. Model helps to analyze the functionality of the system and to design suitable controllers. System identification builds model from experimental data obtained by exciting the process with an input and observing its response at regular interval (Wibowo et al. in System identification of an interacting series process for real-time model predictive control, American Control Conference, pp. 4384–4389, 2009). Fuel cells (FC) systems are a potentially good clean energy conversion technology, and they have wide range of power generation applications. Classification of fuel cells is based on the fuel and the electrolyte type used. The proton exchange membrane fuel cells (PEMFC) are portable devices with superior performance and longer life. They act as a good source for ground vehicle applications. They also possess high power density and fast start-up time. In this work, mathematical model of a real-time PEMFC is obtained and its quality is assessed using various validation techniques. The model is obtained using system identification tool in MATLAB, and validation procedures like recursive least square algorithm, ARX and ARMAX were employed to assess the model. Controllers such as PI and PID were employed in order to achieve the desired load current by controlling the hydrogen flow rate. The values of the gain constant, integral time and derivative time were obtained using Cohen-Coon method. PI and PID control schemes were implemented using SIMULINK in MATLAB environment, and the system response was observed.
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References
Wibowo, T.C.S., Saad, N., Karsiti, M.N.: System identification of an interacting series process for real-time model predictive control, American Control Conference, pp. 4384–4389 (2009)
Spiegel, C.: PEM fuel cell modeling and simulation using MATLAB. Academic Press, London (2011)
Ljung, L.: System identification—theory for the user, 2nd edn. Prentice-Hall, New Jersey (1999)
Astrom, K.J., Wittenmark, B.: Adaptive control, 2nd edn. Dover Publications, New York (2008)
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Arun Kumar, P., Geetha, M., Chandran, K., Sanjeevikumar, P. (2018). PEM Fuel Cell System Identification and Control. In: SenGupta, S., Zobaa, A., Sherpa, K., Bhoi, A. (eds) Advances in Smart Grid and Renewable Energy. Lecture Notes in Electrical Engineering, vol 435. Springer, Singapore. https://doi.org/10.1007/978-981-10-4286-7_44
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DOI: https://doi.org/10.1007/978-981-10-4286-7_44
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