School of Automotive Studies,Tongji University

固体氧化物燃料电池(SOFC)运行过程中存在对流、扩散、表面反应、电荷转移反应等复杂物理化学现象,耦合反应动力学模型的电极仿真模型可以实现对SOFC性能的预测。相较于Bulter-Volmer方程,使用多步基元反应模型可以更准确地描述实际电极反应动力学。但目前多步基元反应模型的参数取值误差较大,对模型预测准确性影响显著。为降低模型预测不确定性,首先,为以加湿氢气(H2/H2O)为燃料的SOFC系统构建了阳极模型,并计算其极化曲线;其次,对模型动力学与热力学参数开展敏感性分析,成功识别出11个敏感参数;最后,对模型分别开展正向与反向不确定性分析,并基于不确定性分析结果优化了模型预测性能。结果表明:开发的阳极优化模型对1023.15K与1123.15K两个温度下的极化曲线预测误差分别由原来的33.12%、34.51%降低到8.61%、15.47%,预测准确性得到提高。

During the operation of solid oxide fuel cell (SOFC),complex physicochemical phenomenas such as convection,diffusion,surface reactions,and charge transfer reactions will occur. Coupling the reaction kinetics model with electrode simulation model canpredict the performance of SOFC. Compared to the Butler-Volmer equation,the multi-step elementary reaction model can better describethe actual electrode kinetics. However,parameters of multi-step elementary reaction model usually contain significant uncertainties,whichaffects the accuracy of model predictions. To reduce model prediction uncertainty,an anode model for SOFC using humidified hydrogengas (H2/H2O) as fuel is eatablished in this study,and polarization curve of the anode is calculated. Sensitivity analysis is conducted onthe kinetic and thermodynamic parameters,with 11 sensitive parameters being identified. Forward and reverse uncertainty analysis areperformed on the anode model separately,and the model prediction performance is optimized based on the results of uncertainty analysis.The results show that the optimized anode model reduces the prediction errors of the polarization curves at temperatures of 1 023.15 K and1 123.15 K from original 33.12% and 34.51% to 8.61% and 15.47% respectively,the model prediction accuracy is improved.

国家自然科学基金面上基金资助项目(52276133);上海市科学技术委员会科研计划资助项目(23160711900)

刘姣,杨建飞,蔡黎明.固体氧化物燃料电池(SOFC)阳极模型预测性能不确定性研究[J].洁净煤技术,2025,31(1):111−120.

LIU Jiao,YANG Jianfei,CAI Liming. Uncertainty analysis for prediction performance of solid oxide fuel cell (SOFC)anode model[J].Clean Coal Technology,2025,31(1):111−120.