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Slippage

ATL-电化学分析软件

1. AECA程序的安装

1.1 直接使用二进制版本

AECA的安装有很多种方法。最简单的方法是直接使用预编译版本的二进制可执行文件。

预编译版本的AECA运行比较可靠,毋须安装任何程序运行环境,开箱即可使用。缺点是由于随程序一起打包了运行所需的python运行时和第三方函数库,因此体积比较大,且只支持window平台。

1.2 使用Python源代码运行

AECA程序是使用python语言进行开发的,从源码运行该程序必须安装Python 3.7x的运行环境。要安装Python运行环境,首先从Python官网下载对应版本和平台的安装包。

安装完python之后,从控制台窗口输入命令

python -V

如果显示Python 3.7.x,则说明python已经安装成功。继续在控制台窗口输入下面的命令

pip --help

执行上述命令后,如果能够看到下面的内容,则说明python的库管理程序pip也安装成功了。如果pip安装不成功,请重新安装python安装包。

Usage:
  pip <command> [options]

Commands:
  install                     Install packages.
  download                    Download packages.
  uninstall                   Uninstall packages.
  freeze                      Output installed packages in requirements 
……

AECA程序依赖于多个第三方库,必须预先安装这些库,才能成功运行程序,第三方函数库的安装通过pip进行,执行如下命令安装AECA所需的库文件

pip install numpy matplotlib pyQt5 pyqtgraph xlrd xlwt chardet

安装完运行所需的函数库之后,双击AeCA.py即可运行程序。

1.3 从Python源代码编译

若需要将源代码打包成二进制文件,也通用需要python的运行环境,具体步骤可以参考上面。打包Python程序,需要先安装pyinstaller,在从控制台窗口输入下面的命令,即可完成安装。

pip install pyinstaller

安装完pyinstaller之后,切换路径到AECA所在文件夹路径,然后执行下面的命令

pyinstaller -i resource/curve.ico -w AECA.py

一段时间后,pyinstaller将程序打包完成,在当前的路径下可以看到新增的dist文件路径,其中的AECA文件夹就是打包的二进制运行程序。

2. AECA程序的功能介绍

AECA程序全称ATL-电化学分析器(ATL-Electrical Chemistry Analysor),该程序使用Python进行开发,并采用pyQt5开发了图形用户界面,其界面主窗口如下图所示

程序默认是英文界面,同时支持英文、简体中文和繁体中文三种语言,点击Language菜单栏可以进行语言的切换。这儿先简单列举一下AECA程序的主要功能。

2.1 数据格式转换功能

  • Excel 格式的数据文件转 CSV格式
  • Excel 格式的数据文件转 TXT格式
  • CSV格式的数据文件转 Excel格式
  • CSV格式的数据文件转 TXT格式
  • TXT格式的数据文件转 Excel格式
  • TXT格式的数据文件转 CSV格式

2.2 数据分析处理功能

  • 自定义间隔对数据采点:将多个数据点平均成一个点,例如原始数据有1000个点,设间隔为5,则每5个点取平均值,处理后的数据有200个点。
  • 自定义间隔对数据微分:和采点不同,间隔微分只会减少尾部的少量数据点,设当前数据集为{(x1,y1),(x2,y2)…(xn,yn)},设间隔为n,则xi处的微分为(yi+n-yi)/( xi+n-xi)。
  • 自定义范围对数据截取:根据用户设定的上下限(xmin,xmax),自动截取数据集中满足xmin ≤ xi ≤ xmax的数据点。
  • 自定义滤波方法对数据进行平滑降噪:程序内置了均值滤波(Simple),中值滤波(Median),SG滤波(Savitzky_Golay),高斯滤波(Gaussian)和三次样条线插值(Spline);前三种滤波方法都是平滑滤波,是低频增强的空间域滤波技术。空间域的平滑滤波一般采用简单平均法进行,就是求邻近点的平均值。邻域的大小与平滑的效果直接相关,邻域越大平滑的效果越好,但邻域过大,平滑会使边缘信息损失的越大,因此需合理选择邻域的大小。平滑窗口=2*邻域的大小+1,因此窗口大小必须设为奇数。程序的默认值是5,可根据需要在用户界面中自行调节。高斯滤波是根据高斯函数的形状来选择权值的线性平滑滤波器。高斯平滑滤波器对于抑制服从正态分布的噪声非常有效。用户可以通过调节sigma值来改变高斯函数的形状,sigma值越大,平滑效果越好,但信息的损失也越大。三次样条线是通过求解三弯矩方程组得出曲线函数,然后预测未知点数值的方法,其噪声因子S≤sum((yi-spl(xi))**2),噪声因子越大,则曲线越平滑,损失的信息也越多。
  • 交换XY轴数据:程序默认的数据形式是电压-容量,微分处理后得到dVdQ-Q数据,对数据交换XY轴即可得到容量-电压数据,微分后即为dQdV-V数据。
  • 数据拟合:根据正极的克容量曲线、负极的克容量曲线以及全电池的测试数据,可以拟合出电池中正极的有效质量、负极的有效质量、以及活性锂的损失,从而达到对电池的失效机理进行定量分析的目的。曲线拟合基于最小二乘法的原理,可以对V-Q数据进行拟合,也可以对dVdQ-Q数据进行拟合。程序会自动基于容量数据进行初猜拟合参数,用户可以按需要对参数进行一定的约束。
  • 数据的缩放和平移:给定拟合参数,可以对选中的正极或负极曲线的数据进行拉伸、压缩和平移。

2.3 绘图功能

  • 原始读取的数据,以及后续处理得到的数据可以进行作图,只需勾选对应的数据即可显示在绘图框中。
  • 可以设定绘图的方式(散点图或折线图)、曲线的颜色、散点的形状、散点的大小、曲线的线宽等等。
  • 图像的缩放、拉伸、局部放大、平移显示等等。
  • 将所有绘图的数据导出为一个数据文件。
  • 将所绘的曲线导出为图片(支持svg、png、jpg、tif等等)。
  • 将曲线数据用matplotlib显示。

3. AECA程序的操作说明

3.1 数据读取

如下图所示,点击菜单栏的 文件 菜单,在下拉菜单中选择 打开 ,在二级下拉菜单中会显示三个菜单选项: 正极参考数据负极参考数据测试数据 。用户根据自己的需要选择不同的菜单。

首先载入正极的参考数据,按下快捷键( Atl+P )或点击菜单栏 文件-打开-正极参考数据 ,程序会弹出文件选择窗口如下:

程序支持 ExcelCSVTXT 三种数据格式,用户根据自己的实际情况选择数据类型,文件选择窗口会自动过滤出复合条件的数据文件,选择需要读取的文件,然后点击 打开 按钮,或按下 Enter键 。程序会读取文件的数据,并根据文件名显示在数据列表、正极列表和曲线列表三个位置,如下图红框标注所示。

类似地载入负极的参考数据,和测试数据,最终的界面如下图所示。在 数据列表曲线列表 里面列出了所有载入的数据,在 正极列表负极列表全电池列表 里面则分别列出了对应的数据。

3.2数据的预处理

3.2.1数据的采点压缩

当数据点非常密集的时候,可以通过设置间隔采点对数据进行压缩,间隔的值必须是正整数。软件默认间隔为1,也即不对数据进行任何处理;当间隔为n,且n大于1的时候,则将每n个数据点平均成一个数据点。若原始数据点有1000个,设置间隔为5进行采点之后数据量会压缩成200个点。

对于等时间间隔的(也即等容量间隔,按时间进行数据采集)数据,设置一定的间隔进行采点,等效于一种低通线性滤波,可以在一定程度上对数据进行平滑。经采点处理后得到的新数据默认以 当前数据名称+"_S" 进行保存,用户可以在编辑菜单中对数据进行 重命名对于非等间隔的数据,不建议进行采点处理!

3.2.2数据的微分

对散点数据的曲线,由于没有固定的数学表达式,因此曲线的微分通过数据方法,也即差分法计算得到:某点(xi,yi)处的微分dy/dx近似等于(yi+n-yi-n)/( xi+n-xi-n),公式中的n即为微分间隔。程序默认为1,也即(dy/dx)i=(yi+1-yi-1)/( xi+1-xi-1)。微分处理后的数据相比原始数据会减少头尾各n个数据点。经微分处理后得到的新数据默认以 当前数据名称+"_D" 进行保存,用户也可以在编辑菜单中对数据进行重命名。对与微分后的数据,也可以继续做微分处理,等于对原始数据进行二阶微分,以此类推。

    类似的微分后的数据也可以做采点、切割、平滑等其他处理,用户可以通过各种操作的任意组合得到自己需要的数据。

3.2.3数据的切割

对于任意选中的数据集,程序会自动读取x轴的最大值和最小值,并显示在输入框中,也即数据切割的 上下限 。用户可以对数据切割范围进行调整,获得自己所需范围内的数据点。经微分处理后得到的新数据默认以 当前数据名称+"_C" 进行保存,用户也可以在编辑菜单中对数据进行重命名。对于某些测试数据,在起始或者结束位置的,会有少量的几个点数据存在异常,可以通过这种方式删去。需要注意的是,在用半电池数据拟合全电池数据的时候,必须保证半电池的数据段能够覆盖全电池的数据段,因此对数据切割需要用户自己根据曲线来判断范围。

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