Research on the tension control method of lithium battery electrode mill based on GA optimized Fuzzy PID

Author:

Xiao Yanjun12,Yu Anqi1,Qi Hao1,Jiang Yunfeng1,Zhou Wei1,Gao Nan1,Liu Weiling1

Affiliation:

1. Department of the State Key Laboratory of Reliability and Intellectual of Electrical Equipment Jointly Constructed by Hebei University of Technology, Tianjin Key Laboratory of Power Transmission and Safety Technology for New Energy Vehicles, School of Mechanical Engineering, Hebei University of Technology, Tianjin, China

2. Career Leader Intelligent Control Automation Company, Suqian, Jiangsu Province, China

Abstract

In the industrial field, the lithium battery industry has a long history and a large market scale. Lithium battery electrode strip rolling mill belongs to the high-end production equipment in the lithium battery industry. However, due to its complex structure, the tension of lithium battery electrode mill is prone to large fluctuation. This will lead to the phenomenon of wrinkle and looseness, which will affect the quality of the electrode strip. At present, the tension control method of lithium battery electrode mill mostly adopts traditional Proportional-Integral-Differential(PID) control. Under this control mode, the production speed and precision of lithium battery electrode mill need to be improved. In this paper, the fuzzy PID tension control method of lithium battery electrode mill based on genetic optimization is studied. Based on fuzzy theory and PID control method, a tension fuzzy PID model is established for experimental verification, and the initial parameters and fuzzy rules of fuzzy PID are optimized by Genetic Algorithm(GA). This method has better stability, can improve the precision of strip tension control, make the tension more stable when the rolling mill is running, and help to improve the quality of electrode strip production.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference15 articles.

1. Research on tension control of winding systems using electronic CAM[J];Peng;Advanced Materials Research,2012

2. Xu Y.X. , Niu L.C. , et al., Optimization of Lithium Battery Pole Piece Thickness Control System Based on GA-BP Neural Network[C]//, of Nanoelectronics and Optoelectronics 14(7) (2019).

3. Stiffness analysis and structure optimization of rolling mill for lithium-ion battery electrode manufacturing[J];Ma;Zhongguo Jixie Gongcheng/China Mechanical Engineering,2015

4. An active dancer roller system for tension control of wire and sheet[J];Kuribayashi;IFAC Proceedings Volumes,1984

5. Optimization of fuzzy PID controller’s parameters[J];Kudinov;Procedia Computer Science,2017

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3