Fuel Cell Characteristic Curve Approximation Using the Bézier Curve Technique

• Main Authors: Mohamed Louzazni, Sameer Al-Dahidi, Marco Mussetta
• Format: Article
• Language: English
• Published: MDPI AG 2020-10-01
• Series: Sustainability
• Subjects: fuel cell; characteristics curve; computer graphic technique; approximation; Bézier curve
• Online Access: https://www.mdpi.com/2071-1050/12/19/8127

Accurate modelling of the fuel cell characteristics curve is essential for the simulation analysis, control management, performance evaluation, and fault detection of fuel cell power systems. However, the big challenge in fuel cell modelling is the multi-variable complexity of the characteristic curves. In this paper, we propose the implementation of a computer graphic technique called Bézier curve to approximate the characteristics curves of the fuel cell. Four different case studies are examined as follows: Ballard Systems, Horizon H-12 W stack, NedStackPS6, and 250 W proton exchange membrane fuel cells (PEMFC). The main objective is to minimize the absolute errors between experimental and calculated data by using the control points of the Bernstein–Bézier function and de Casteljau’s algorithm. The application of this technique entails subdividing the fuel cell curve to some segments, where each segment is approximated by a Bézier curve so that the approximation error is minimized. Further, the performance and accuracy of the proposed techniques are compared with recent results obtained by different metaheuristic algorithms and analytical methods. The comparison is carried out in terms of various statistical error indicators, such as Individual Absolute Error (<i>IAE</i>), Relative Error (<i>RE</i>), Root Mean Square Error (<i>RMSE</i>), Mean Bias Errors (<i>MBE</i>), and Autocorrelation Function (<i>ACF</i>). The results obtained by the Bézier curve technique show an excellent agreement with experimental data and are more accurate than those obtained by other comparative techniques.