Approach to Proton Exchange Membrane Fuel Cell Modeling Based on Dynamic Neural Networks

CAO Zheng-cai; LI Bo; LIU Min; ZHANG Jie

doi:10.3969/j.issn.0372-2112.2014.01.016

您当前的位置：

首页 >

文章列表页 >

Approach to Proton Exchange Membrane Fuel Cell Modeling Based on Dynamic Neural Networks

更新时间：2025-07-16

- Approach to Proton Exchange Membrane Fuel Cell Modeling Based on Dynamic Neural Networks
- Acta Electronica Sinica Vol. 42, Issue 1, Pages: 102-106(2014)
- 作者机构：
  
  1. 北京化工大学信息科学与技术学院,北京,100029
  2. 东南大学复杂工程系统测量与控制教育部重点实验室,江苏,南京,210096
  3. 中国科学院理化技术研究所,北京,100190
  4. 清华大学自动化系,北京,100084
  5. 北京化工大学信息科学与技术学院,北京,100029
  6. 东南大学复杂工程系统测量与控制教育部重点实验室,江苏,南京,210096
  7. 中国科学院理化技术研究所,北京,100190
  8. 清华大学自动化系,北京,100084
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2014.01.016
  CLC： TP183
- Published：2014
- 稿件说明：
移动端阅览
CAO Zheng-cai, LI Bo, LIU Min, et al. Approach to Proton Exchange Membrane Fuel Cell Modeling Based on Dynamic Neural Networks[J]. Acta Electronica Sinica, 2014, 42(1): 102-106.
DOI：

CAO Zheng-cai, LI Bo, LIU Min, et al. Approach to Proton Exchange Membrane Fuel Cell Modeling Based on Dynamic Neural Networks[J]. Acta Electronica Sinica, 2014, 42(1): 102-106. DOI： 10.3969/j.issn.0372-2112.2014.01.016.

摘要

针对现有质子交换膜燃料电池（Proton Exchange Membrane Fuel Cell，PEMFC）模型逼近能力不足、自适应性差的问题，提出一种基于动态神经网络的PEMFC建模方法.该方法引入神经网络输出敏感度作为隐含层结构合理性判别依据，根据敏感度分析结果选择采用相应的神经元修改算法调整隐含层结构，使隐含层神经元数目根据燃料电池数据处理需求动态变化，实现模型结构与参数的双重优化.以某型双系统燃料电池测试平台实际运行数据为例进行验证，结果表明构建的PEMFC动态神经网络模型比传统模型的网络规模小、拟合精度高、收敛速度快，适用于工程化仿真应用.

Abstract

An innovative approach of proton exchange membrane fuel cell (PEMFC) modeling based on dynamic neural networks is proposed to improve approximating and self-adaptive ability of the existing PEMFC models.To evaluate the rationality of networks structure

sensitivity analysis (SA) of the model output was introduced.The hidden nodes were pruned or inserted according to the result of SA to optimize the networks structure and parameters

so that the networks could adapt the PEMFC data processing automatically.The approach was validated using operation data from a commercial dual-system fuel cell test platform.The result shows the proposed PEMFC model with more compact structure

higher accuracy and faster convergence rate compared with the common models

have the capability to be applied to engineering simulation applications.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Dynamic Neural Network for Incremental Learning with Task Extended: Research Progress and Prospect

A Tiny Target Feature Enhancement Algorithm for Semantic Segmentation

A Supply Chain Modeling Technology Based on RFID Discovery Service

Petri-Net and GA-Based Approach to Modeling and Optimize for Semiconductor Wafer Fabrication

Mixed-Signal Modeling and Simulation for a Digital RF Charge Sampling Mixer Based on Verilog-AMS

Related Author

CHEN Qing-kui

CAO Jian

MA Quan-yi

ZHAO Hai-yan

LIU Qiong

REN Sha-sha

FONT

WANG Li-fu

Related Institution

School of Optical-Electrical & Computer Engineering， University of Shanghai for Science and Technology

Department of Computer Science and Technology， Shanghai Jiaotong University

School of Software Engineering, South China University of Technology

北京大学信息科学技术学院软件研究所高可信软件技术教育部重点实验室

1.北京大学信息科学技术学院

⁰