Dr. Bernard Tonderayi Mangara

Central University of Technology
South Arica

Abstract Title: Comparative Analysis of Simplified and Enhanced Detailed Fuel Cell Models for Simulation and Control

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The research evaluates the simplified and detailed PEM fuel cell models in Simulink through their application to energy system simulation and control and optimization. The development of the hydrogen economy and smart grid operations and hybrid energy integration requires precise fuel cell modelling. The simplified model calculates open-circuit voltage, current, and efficiency through algebraic equations that depend on hydrogen pressure, stack temperature and load current. The model is intended for high-level energy flow prediction but does not show dynamic behaviour, or electrochemical loss mechanisms. The detailed model produces hydrogen flow and stack temperature outputs while using transfer functions to model transient dynamics and includes activation, ohmic and concentration losses. The model features enable its use for complex applications such as deterioration analysis, predictive control and hydrogen consumption optimization. The simulation models received identical dynamic input characteristics during their 20-second operational period. The evaluation of essential outputs included stack temperature alongside voltage and current measurements and efficiency ratings and hydrogen flow rates. The simplified model produced a voltage Root Mean Square Error (RMSE) of 0.35552 V because it omitted physical loss mechanisms which resulted in significant differences between the models. The detailed model included hydrogen flow and thermal behavior with current being an imposed input and being the same for both models. The simulation execution time received evaluation. The detailed model executed in 0.6434 seconds, but the simplified model required 1.4262 seconds to run. The simplified model's inefficiencies such as interpreted blocks and algebraic loops caused this outcome. The detailed model delivered superior computing performance together with enhanced physical accuracy. These findings help engineers and researchers choose the right modelling complexity for subsystem design, control development, and system-level feasibility assessments by guiding model selection depending on application context.

Keywords: Fuel Cell Modeling; PEM Fuel Cell; Hydrogen Energy Systems; Simulation and Control; Model-Based Energy Management