Neural Networks Control of the Ni-MH Power Battery Positive Mill Thickness

Guang Jun Ma; Shuo Wu; Guang Qi Cai

doi:10.4028/www.scientific.net/AMM.411-414.1855

Paper Titles

Analysis and Design of Spherical Aerial Vehicle's Motion Modes
p.1836

Programming Applications of Computer Aided Design and Layout of the Complex Solar Panels
p.1840

The Development and Application of Digital Mine Ventilation System
p.1844

A New Type of Proportion Cycle Temperature Control Algorithm
p.1851

Neural Networks Control of the Ni-MH Power Battery Positive Mill Thickness
p.1855

Scale Effect on Dynamic Analysis of Electrostatically Actuated Nano Beams Using the Nonlocal-Gradient Elasticity Theory
p.1859

Evaluation Method Research on Trunk Highway Traffic Safety Based on AHP
p.1865

Algorithm Evolution from Traveling Salesman Problem to Vehicle Routing Problem
p.1872

D-S Algorithm Based on SCO for Matching Fragments
p.1876

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 411-414Neural Networks Control of the Ni-MH Power Battery...

Neural Networks Control of the Ni-MH Power Battery Positive Mill Thickness

Abstract:

This paper analyzes the process and control of nanohydrogen storage alloy strip rolling. We design a nonlinear model of rolling mill, use the neural network control scheme, and we adopt the rolling process of mathematical modeling, and use the model of the mathematical method in quantitative analysis. Finally, we use the system of computer simulation, at the end we draw the following conclusions. In strip rolling process, using a neural network system for control, far superior to the introduction of PI control, not only solved the rolling process with variable delay and variable gain and other shortcomings, and that the hydrogen storage alloy electrochemical performance was improved, the production process to ensure the high quality of hydrogen storage alloy, reducing energy consumption, saving raw materials, reduce the labor intensity of operating staff is of great significance.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 411-414)

Pages:

1855-1858

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.411-414.1855

Citation:

Cite this paper

Online since:

September 2013

Authors:

Guang Jun Ma, Shuo Wu, Guang Qi Cai

Keywords:

Nanohydrogen Storage Materials, Neural Network Control, Nickel Metals Hydrogen Power Battery, Strip

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Li Ming, Zhou Zhen, Li Ya Fei, Shen Pan Wen . Research and design of Nano structured materials for hydrogen storage calculation [J], China Science 09, (2009).

Google Scholar

[2] Li Lan Lan, Cheng Fang Yi. First principles calculation of hydrogen storage materials research progress, applied Chemistry, 09, (2010).

Google Scholar

[3] Fan Mei Qiang, Liao Wei Lin. NH-Ni battery consistency somewhat separation technology [J], Power supply technology, 29(6), 2005, 361.

Google Scholar

[4] Pan Wei dong. Using artificial neural network technology to realize the intelligent control[J], Computing technology and automation, 12(2), 1993, 6-11.

Google Scholar

[5] Xiao Fang Ming, Lu Qi Yun, Tang Ren Heng. High performance nano crystalline hydrogen storage alloy preparation [J], Rare metal materials and Engineering, 07, (2004).

Google Scholar