Model-based diagnosis through Structural Analysis and Causal Computation for automotive Polymer Electrolyte Membrane Fuel Cell systems

JOURNAL OF POWER SOURCES

卷:357

Article

Polverino, Pierpaolo¹  Frisk, Erik²  Jung, Daniel²  Krysander, Mattias²  Pianese, Cesare¹ 

[1] Univ Salerno, Dept Ind Engn, Via Giovanni Paolo 2 132, I-84084 Fisciano, SA, Italy

[2] Linkoping Univ, Dept Elect Engn, S-5183 Linkoping, Sweden

关键词: Polymer Electrolyte Membrane Fuel Cell;    Model-based diagnosis;    Fault detection;    Fault isolation;    Residual generation;    Algorithm design;   

DOI  :  10.1016/j.jpowsour.2017.04.089

来源: Elsevier

【 摘 要 】

The present paper proposes an advanced approach for Polymer Electrolyte Membrane Fuel Cell (PEMFC) systems fault detection and isolation through a model-based diagnostic algorithm. The considered algorithm is developed upon a lumped parameter model simulating a whole PEMFC system oriented towards automotive applications. This model is inspired by other models available in the literature, with further attention to stack thermal dynamics and water management. The developed model is analysed by means of Structural Analysis, to identify the correlations among involved physical variables, defined equations and a set of faults which may occur in the system (related to both auxiliary components malfunctions and stack degradation phenomena). Residual generators are designed by means of Causal Computation analysis and the maximum theoretical fault isolability, achievable with a minimal number of installed sensors, is investigated. The achieved results proved the capability of the algorithm to theoretically detect and isolate almost all faults with the only use of stack voltage and temperature sensors, with significant advantages from an industrial point of view. The effective fault isolability is proved through fault simulations at a specific fault magnitude with an advanced residual evaluation technique, to consider quantitative residual deviations from normal conditions and achieve univocal fault isolation. (C) 2017 Elsevier B.V. All rights reserved.

【 授权许可】

Free