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基于预测PI的电极面密度控制系统

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为解决锂离子电池极片面密度在复杂工业环境下变参数、大干扰、超大时滞的控制难题,设计基于预测PI的面密度控制系统.首先基于电极涂覆工作原理建立其数学模型并设计控制方案,然后在传统粒子群算法的基础上引入交叉变异因子实现预测PI算法的参数整定.实际应用表明:该控制系统能够实现横向(TD)面密度和纵向(MD)面密度双闭环控制,面密度变异系数CV由0.192%降至0.115%,面密度过程能力指数CPK由1.212提升至2.324,锂离子电池极片面密度的一致性和稳定性得到了极大改善.
The Control System for Electrode Areal Density Based on Predictive PI
For purpose of solving the control problem of Li-ion electrode areal density in complex industrial environments with variant parameters,large disturbances and large time-delay,the areal density control system based on predictive PI was designed.Firstly,having a mathematical model established based on the working principle of electrode coating and its control scheme designed;then,having the traditional particle swarm optimization algorithm based to introduce into the cross mutation factor so as to achieve parameter tuning of the predictive PI algorithm.The application result shows that,the control system proposed can achieve closed-loop control of areal densities in the transverse direction(TD)and the machine direction(MD).The coefficient of variation(CV)of the areal density can decrease from 0.192%to 0.115%,and the process capability index(CPK)of the areal density increase from 1.212 to 2.324.The consistency and sta-bility of the areal density of lithium-ion batteries have been greatly improved.

predictive PIgenetic particle swarm optimizationLi-ion batteryareal-densityuncertain system

唐为庆、任正云

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东华大学信息科学与技术学院

预测PI 遗传粒子群算法 锂离子电池 面密度 不确定系统

2025

化工自动化及仪表
天华化工机械及自动化研究设计院有限公司

化工自动化及仪表

影响因子:0.355
ISSN:1000-3932
年,卷(期):2025.52(1)