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通过递归过来降低噪声,以更准确地识别电化学源和接口的参数

Mitar Simić¹, Milan Medić¹, Milan Radovanović²

¹Faculty of Electrical Engineering, University of Banja Luka, 78000 Banja Luka, Bosnia and Herzegovina.

Sensors (Basel, Switzerland)

|June 27, 2025

概括

精确的电化学阻抗光谱 (EIS) 分析需要降低噪声. 本研究引入了用于Randles电路参数识别的递归过器,提高了无需用户输入的准确性.

科学领域:

电化学电化学电化学
电气工程电气工程
数据分析数据分析

背景情况:

电化学阻抗光谱 (EIS) 对于研究电化学系统至关重要.
在EIS数据中的测量噪声阻碍了准确的参数识别和解释.
兰德尔等效电路通常用于模拟电化学接口.

研究的目的:

为EIS数据开发一种降噪方法.
为了能够准确地识别兰德尔电路的参数.
呈现一个自动和自调的过和估计程序.

主要方法:

递归过用于用于降低噪音的EIS数据.
序列电阻,电荷转移电阻和双层电容的参数估计是使用闭式方程进行的.
通过搜索方法自调一个最佳的递归波器权重因子.

主要成果:

拟议的递归波器在随机噪声的情况下显著提高了估计准确性.
该方法成功处理了来自离子电池的合成和实验EIS数据.
基于PC和基于微控制器的系统都证明了这种方法的有效性.

结论:

提出的方法提供了一个自动化和独立于用户的方法来减少噪音和EIS中的参数识别.
这种技术提高了电化学模型参数估计的可靠性.
这些发现适用于各种电化学系统,包括电池研究.

关键词:

电池阻抗分析电池阻抗分析相当于电路的同等电路.阻抗分析阻抗分析参数识别参数识别

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