Economic factors along with legislation and policies to counter harmful pollution apply specifically to maritime drive research for improved power generation and energy storage. Proton exchange membrane fuel cells are considered among the most promising options for marine applications. Switching converters are the most common interfaces between fuel cells and all types of load in order to provide a stable regulated voltage. In this paper, a method using artificial neural networks（ANNs） is develo... 

【文章來源】：Journal of Marine Science and Application. 2020,19(02)CSCD

【文章頁數(shù)】：20 頁

【文章目錄】：
Article Highlights
1 Introduction
    1.1 Literature Review
    1.2 Marine Application for Fuel Cell Technology
2 Fuel Cell
    2.1 Hydrogen,Oxygen and Air Consumption
3 DC Boost Converter
    3.1 Continuous Conduction Mode
4 Artificial Neural Network
    4.1 Change in Error Due to Output Layer Weights（Self-Learning System）（Galushkin,2007）
    4.2 Weight Adjustments （Self-Learning System）（Galushkin,2007）
5 Steady-State Operation
    5.1 Fuel Cell Generic Model
        5.1.1 Configuration of Fuel Cell Parameters
    5.2 Fuel Cell Model Validation
    5.3 DC/DC Boost Converter Switching Model
        5.3.1 Inductor Selection
        5.3.2 Capacitance Selection
        5.3.3 Selection of the Semiconductor Device （MOSFET （Mohan and Robbins 2003））
        5.3.4 Diode Selection
        5.3.5 Model Implementation
    5.4 ANN configuration for DC/DC boost converter control
        5.4.1 Generation of ANN Data
        5.4.2 ANN Data Parameterization and Separation for Training and Validation
        5.4.3 ANN Implementation and Training
6 Dynamic System Operation
    6.1 Open-Loop Simulation
    6.2 Neural Network Control of Switching DC-DC Boost Converter
    6.3 Neural Network Control of ANN DC/DC Boost Converter Cycle-to-Cycle Equivalent
7 Conclusions



本文編號：3090842