%0 Journal Article %A Mao, Lei %A Jackson, Lisa %D 2016 %T Comparative study on prediction of fuel cell performance using machine learning approaches %U https://repository.lboro.ac.uk/articles/journal_contribution/Comparative_study_on_prediction_of_fuel_cell_performance_using_machine_learning_approaches/9222638 %2 https://repository.lboro.ac.uk/ndownloader/files/16801973 %K Fuel cell %K Prognostics %K Machine learning technique %K Neural network %K Adaptive neuro-fuzzy inference system %K Particle filtering approach %K Engineering not elsewhere classified %X This paper provides a comparative study to evaluate the effectiveness of machine learning techniques in predicting fuel cell performance. Several methods applied in fuel cell prognostics are selected, including a neural network, an adaptive neuro-fuzzy inference system, and a particle filtering approach. Test data from a fuel cell system is used for the evaluation. From the results, the advantages and disadvantages of these approaches are compared, which can provide a general framework for the selection of the necessary algorithms for fuel cell prognostics under different conditions. %I Loughborough University