A novel P systems based optimization algorithm for parameter estimation of proton exchange membrane fuel cell model
- 作者：Shipin Yang ; Ning Wang ; nwang@iipc.zju.edu.cn ; nwang126@126.com
- 关键词：PEM fuel cells ; Modeling ; Optimization ; P systems ; Parameter estimation
- 刊名：International Journal of Hydrogen Energy
- 出版年：2012
- 期刊代码：42_03603199
- 类别：ch
- 出版时间：May, 2012
- 卷：37
- 期：10
- 页码：8465-8476
- 文件大小：1314 K
摘要
Accurate kinetic models are of great significance for the simulation and analysis for hydrogen fuel cells. The proton exchange membrane (PEM) fuel cell is a complex nonlinear, multi-variable system. The mathematical modeling of PEM fuel cell usually leads to nonlinear parameter estimation problems which often contain more than one minimum. In this paper, a novel bio-inspired P systems based optimization algorithm, named BIPOA, is proposed to solve PEM fuel cell model parameter estimation problems. In BIPOA, the nested membrane structure and new rules such as adaptive mutation rule, partial migration rule and autophagy rule are combined to improve the algorithm's global search capacities and convergence accuracy. Studies on some benchmark test functions indicate that the BIPOA outperforms the other two methods (PSOPS and GAs) in both convergence speed and accuracy. In addition, experimental results reveal that the model predictive outputs are in better agreement with the actual experimental data. Therefore, the BIPOA is a helpful and reliable technique for estimating the PEM fuel cell model parameters and is available to other complex parameter estimation problems of fuel cell models.