上传三元和磷酸铁锂一致性代码

LIB/MIDDLE/CellStateEstimation/Uniform/V1_0_0/BatParam.py

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+
+#定义电池参数
+from types import CellType
+import sys
+
+class BatParam:
+
+    def __init__(self,celltype):
+
+        # if 'PK500' in sn:
+        #     self.celltype=1 #6040三元电芯
+        # elif 'PK502' in sn:
+        #     self.celltype=2 #4840三元电芯
+        # elif 'PK504' in sn:
+        #     self.celltype=99    #60ah林磷酸铁锂电芯
+        # elif 'MGMLXN750' in sn:
+        #     self.celltype=3 #力信50ah三元电芯
+        # elif 'MGMCLN750' in sn: 
+        #     self.celltype=4 #CATL 50ah三元电芯
+        # else:
+        #     print('未找到对应电池编号！！！')
+        #     sys.exit()
+
+        if celltype==1: #6040
+            self.Capacity = 41
+            self.PackFullChrgVolt=69.99
+            self.CellFullChrgVolt=4.2
+            self.CellVoltNums=17
+            self.CellTempNums=4
+            self.FullChrgSoc=98
+            self.PeakSoc=57
+            self.LookTab_SOC = [0,	    3.5348,	8.3581,	13.181,	18.004,	22.827,	27.651,	32.474,	37.297,	42.120,	46.944,	51.767,	56.590,	61.413,	66.237,	71.060,	75.883,	80.707,	85.530,	90.353,	95.176,	100]
+            self.LookTab_OCV = [3.3159,	3.4384,	3.4774,	3.5156,	3.5478,	3.5748,	3.6058,	3.6238,	3.638,	3.6535,	3.6715,	3.6951,	3.7279,	3.7757,	3.8126,	3.8529,	3.8969,	3.9446,	3.9946,	4.0491,	4.109,	4.183]
+        
+        elif celltype==2: #4840
+            self.Capacity = 41
+            self.PackFullChrgVolt=69.99
+            self.CellFullChrgVolt=4.2
+            self.CellVoltNums=14
+            self.CellTempNums=4
+            self.FullChrgSoc=98
+            self.PeakSoc=57
+            self.LookTab_SOC = [0,	    3.5348,	8.3581,	13.181,	18.004,	22.827,	27.651,	32.474,	37.297,	42.120,	46.944,	51.767,	56.590,	61.413,	66.237,	71.060,	75.883,	80.707,	85.530,	90.353,	95.176,	100]
+            self.LookTab_OCV = [3.3159,	3.4384,	3.4774,	3.5156,	3.5478,	3.5748,	3.6058,	3.6238,	3.638,	3.6535,	3.6715,	3.6951,	3.7279,	3.7757,	3.8126,	3.8529,	3.8969,	3.9446,	3.9946,	4.0491,	4.109,	4.183]
+       
+        elif celltype==99:   #60ah磷酸铁锂电芯
+            self.Capacity = 54
+            self.PackFullChrgVolt=69.99
+            self.CellFullChrgVolt=3.5
+            self.OcvInflexionBelow=3.285
+            self.OcvInflexion2=3.296
+            self.OcvInflexion3=3.328
+            self.OcvInflexionAbove=3.4
+            self.CellVoltNums=20
+            self.CellTempNums=4
+            self.FullChrgSoc=98
+            self.PeakSoc=57
+            self.LookTab_SOC = [0.00, 	2.40, 	6.38, 	10.37, 	14.35, 	18.33, 	22.32, 	26.30, 	30.28, 	35.26, 	40.24, 	45.22, 	50.20, 	54.19, 	58.17, 	60.16, 	65.14, 	70.12, 	75.10, 	80.08, 	84.06, 	88.05, 	92.03, 	96.02, 	100.00]
+            self.LookTab_OCV = [2.7151,	3.0298,	3.1935,	3.2009,	3.2167,	3.2393,	3.2561,	3.2703,	3.2843,	3.2871,	3.2874,	3.2868,	3.2896,	3.2917,	3.2967,	3.3128,	3.3283,	3.3286,	3.3287,	3.3288,	3.3289,	3.3296,	3.3302,	3.3314,	3.3429]
+        
+        elif celltype==3:
+            self.Capacity = 51
+            self.PackFullChrgVolt=80
+            self.CellFullChrgVolt=4.2
+            self.CellVoltNums=20
+            self.CellTempNums=4
+            self.FullChrgSoc=98
+            self.PeakSoc=57
+            self.LookTab_SOC = [0,	    5,	    10,	    15,	    20,	    25,	    30,	    35,	    40,	    45,	    50,	    55,	    60,	    65,	    70,	    75,	    80,	    85,	    90,	    95,	    100]
+            self.LookTab_OCV = [3.357, 	3.455, 	3.493, 	3.540, 	3.577, 	3.605, 	3.622, 	3.638, 	3.655, 	3.677, 	3.707, 	3.757, 	3.815, 	3.866, 	3.920, 	3.976, 	4.036, 	4.099, 	4.166, 	4.237, 	4.325]
+        
+        else:
+            print('未找到对应电池编号！！！')
+            sys.exit()
+

LIB/MIDDLE/CellStateEstimation/Uniform/V1_0_0/CBMSBatUniform.py

@@ -0,0 +1,358 @@
+import pandas as pd
+import numpy as np
+import datetime
+import bisect
+import matplotlib.pyplot as plt
+import BatParam
+
+class BatUniform:
+    def __init__(self,sn,celltype,df_bms):  #参数初始化
+
+        self.sn=sn
+        self.celltype=celltype
+        self.param=BatParam.BatParam(celltype)
+        self.df_bms=df_bms
+        self.packcrnt=df_bms['总电流[A]']
+        self.packvolt=df_bms['总电压[V]']
+        self.bms_soc=df_bms['SOC[%]']
+        self.bmstime= pd.to_datetime(df_bms['时间戳'], format='%Y-%m-%d %H:%M:%S')
+
+    def batuniform(self):
+        if self.celltype==1 or self.celltype==2:
+            df_res=self._ncm_uniform()
+            return df_res
+            
+        elif self.celltype==99:
+            df_res=self._lfp_uniform()
+            return df_res
+    
+    def _np_move_avg(self,a, n, mode="same"): #定义滑动滤波函数
+        return (np.convolve(a, np.ones((n,)) / n, mode=mode))
+    
+    def _celltemp_weight(self,num):   #寻找当前行数据的最小温度值
+        celltemp = []
+        for j in range(1, self.param.CellTempNums+1):
+            s = str(j)
+            celltemp.append(self.df_bms.loc[num,'单体温度' + s])
+        celltemp.remove(min(celltemp))
+        if self.celltype==99:
+            if min(celltemp)>=20:
+                self.tempweight=1
+                self.StandardStandingTime=600
+            elif min(celltemp)>=10:
+                self.tempweight=0.6
+                self.StandardStandingTime=900
+            elif min(celltemp)>=5:
+                self.tempweight=0.
+                self.StandardStandingTime=1800
+            else:
+                self.tempweight=0.1
+                self.StandardStandingTime=3600
+        else:
+            if min(celltemp)>=20:
+                self.tempweight=1
+                self.StandardStandingTime=300
+            elif min(celltemp)>=10:
+                self.tempweight=0.8
+                self.StandardStandingTime=600
+            elif min(celltemp)>=5:
+                self.tempweight=0.6
+                self.StandardStandingTime=1800
+            else:
+                self.tempweight=0.2
+                self.StandardStandingTime=3600
+
+    def _cellvolt_get(self,num): #获取当前行所有电压数据
+        cellvolt=[]
+        for j in range(1, self.param.CellVoltNums+1): 
+            s = str(j)
+            cellvolt.append(self.df_bms.loc[num,'单体电压' + s]/1000)
+        return(cellvolt)
+
+    def _dvdq_peak(self, time, soc, cellvolt, packcrnt):    #寻找DVDQ的峰值点，并返回
+        cellvolt1 = self._np_move_avg(cellvolt, 5, mode="same")
+        Soc = 0
+        Ah = 0
+        Volt = cellvolt1[0]
+        DV_Volt = []
+        DQ_Ah = []
+        DVDQ = []
+        time1 = []
+        soc1 = []
+        soc2 = []
+        xvolt=[]
+
+        for m in range(1, len(time)):
+            Step = (time[m] - time[m - 1]).total_seconds()
+            Soc = Soc - packcrnt[m] * Step * 100 / (3600 * self.param.Capacity)
+            Ah = Ah - packcrnt[m] * Step / 3600
+            if (cellvolt[m]-Volt)>0.99 and Ah>0:
+                DQ_Ah.append(Ah)
+                DV_Volt.append(cellvolt[m]-Volt)
+                DVDQ.append((DV_Volt[-1])/DQ_Ah[-1])
+                xvolt.append(cellvolt[m]/1000)
+                Volt=cellvolt[m]
+                Ah = 0
+                soc1.append(Soc)
+                time1.append(time[m])
+                soc2.append(soc[m])
+
+        #切片，去除前后10min的数据
+        df_Data1 = pd.DataFrame({'time': time1,
+                                'SOC': soc2,
+                                'DVDQ': DVDQ,
+                                'AhSoc': soc1,
+                                'DQ_Ah':DQ_Ah,
+                                'DV_Volt':DV_Volt,
+                                'XVOLT':xvolt})
+        start_time=df_Data1.loc[0,'time']
+        start_time=start_time+datetime.timedelta(seconds=600)
+        end_time=df_Data1.loc[len(time1)-1,'time']
+        end_time=end_time-datetime.timedelta(seconds=1200)
+        if soc2[0]<40 and soc2[-1]>93:
+            df_Data1=df_Data1[(df_Data1['SOC']>44) & (df_Data1['SOC']<90)]
+        elif soc2[0]<40 and soc2[-1]<=93:
+            df_Data1=df_Data1[(df_Data1['SOC']>44) & (df_Data1['time']<end_time)]
+        elif soc2[0]>=40 and soc2[-1]>93:
+            df_Data1=df_Data1[(df_Data1['time']>start_time) & (df_Data1['SOC']<90)]
+        else:
+            df_Data1=df_Data1[(df_Data1['time']>start_time) & (df_Data1['time']<end_time)]
+
+        ax1 = plt.subplot(3, 1, 1)
+        plt.plot(df_Data1['XVOLT'],df_Data1['DVDQ'],'r*-')
+        plt.xlabel('Volt/V')
+        plt.ylabel('DV/DQ')
+        plt.legend()
+        ax1 = plt.subplot(3, 1, 2)
+        plt.plot(df_Data1['SOC'],df_Data1['XVOLT'],'y*-')
+        plt.xlabel('SOC/%')
+        plt.ylabel('Volt/V')
+        plt.legend()
+        ax1 = plt.subplot(3, 1, 3)
+        plt.plot(df_Data1['SOC'], df_Data1['DVDQ'], 'r*-')
+        plt.xlabel('SOC/%')
+        plt.ylabel('DV/DQ')
+        plt.legend()
+        plt.show()
+
+        if len(df_Data1)>2:     #寻找峰值点，且峰值点个数>2
+            PeakIndex = df_Data1['DVDQ'].idxmax()
+            df_Data2 = df_Data1[(df_Data1['SOC'] > (df_Data1['SOC'][PeakIndex] - 0.5)) & (df_Data1['SOC'] < (df_Data1['SOC'][PeakIndex] + 0.5))]
+            if len(df_Data2) > 2:
+                return df_Data1['AhSoc'][PeakIndex]
+            else:
+                df_Data1 = df_Data1.drop([PeakIndex])
+                PeakIndex = df_Data1['DVDQ'].idxmax()
+                df_Data2 = df_Data1[(df_Data1['SOC'] > (df_Data1['SOC'][PeakIndex] - 0.5)) & (df_Data1['SOC'] < (df_Data1['SOC'][PeakIndex] + 0.5))]
+                if len(df_Data2) > 2:
+                    return df_Data1['AhSoc'][PeakIndex]
+                else:
+                    return 0
+        else:
+            return 0
+ 
+    def _ncm_uniform(self):
+        column_name=['time','sn','cellsoc_diff','cellvolt_diff','cellmin_num','cellmax_num']
+        df_res=pd.DataFrame(columns=column_name)
+        standingtime=0
+
+        for i in range(1,len(self.df_bms)-2):
+
+            if abs(self.packcrnt[i]) < 0.3:     #电流为0
+                delttime=(self.bmstime[i+1]-self.bmstime[i]).total_seconds()
+                standingtime=standingtime+delttime
+                self._celltemp_weight(i)     #获取不同温度对应的静置时间
+
+                if standingtime>self.StandardStandingTime:      #静置时间满足要求
+                    if abs(self.packcrnt[i+2]) >= 0.3:
+                        standingtime=0                    
+                        cellvolt_now=self._cellvolt_get(i)     #获取当前行电压数据
+                        cellvolt_min=min(cellvolt_now)
+                        cellvolt_max=max(cellvolt_now)
+                        cellmin_num=cellvolt_now.index(cellvolt_min)+1
+                        cellmax_num=cellvolt_now.index(cellvolt_max)+1
+                        cellsoc_min=np.interp(cellvolt_min,self.param.LookTab_OCV,self.param.LookTab_SOC)
+                        cellsoc_max=np.interp(cellvolt_max,self.param.LookTab_OCV,self.param.LookTab_SOC)
+                        cellvolt_diff=(cellvolt_max-cellvolt_min)*1000
+                        cellsoc_diff=cellsoc_max-cellsoc_min
+                        cellsoc_diff=format(cellsoc_diff,'.1f')
+                        cellvolt_diff=format(cellvolt_diff,'.0f')
+                        df_res.loc[len(df_res)]=[self.bmstime[i], self.sn, cellsoc_diff, cellvolt_diff, cellmin_num, cellmax_num]
+                    elif standingtime>3600*12:
+                        standingtime=0                    
+                        cellvolt_now=self._cellvolt_get(i)     #获取当前行电压数据
+                        cellvolt_min=min(cellvolt_now)
+                        cellvolt_max=max(cellvolt_now)
+                        cellmin_num=cellvolt_now.index(cellvolt_min)+1
+                        cellmax_num=cellvolt_now.index(cellvolt_max)+1
+                        cellsoc_min=np.interp(cellvolt_min,self.param.LookTab_OCV,self.param.LookTab_SOC)
+                        cellsoc_max=np.interp(cellvolt_max,self.param.LookTab_OCV,self.param.LookTab_SOC)
+                        cellvolt_diff=(cellvolt_max-cellvolt_min)*1000
+                        cellsoc_diff=cellsoc_max-cellsoc_min
+                        cellsoc_diff=format(cellsoc_diff,'.1f')
+                        cellvolt_diff=format(cellvolt_diff,'.0f')
+                        df_res.loc[len(df_res)]=[self.bmstime[i], self.sn, cellsoc_diff, cellvolt_diff, cellmin_num, cellmax_num]
+                    elif i>=len(self.df_bms)-4:
+                        standingtime=0
+                        cellvolt_now=self._cellvolt_get(i)     #获取当前行电压数据
+                        cellvolt_min=min(cellvolt_now)
+                        cellvolt_max=max(cellvolt_now)
+                        cellmin_num=cellvolt_now.index(cellvolt_min)+1
+                        cellmax_num=cellvolt_now.index(cellvolt_max)+1
+                        cellsoc_min=np.interp(cellvolt_min,self.param.LookTab_OCV,self.param.LookTab_SOC)
+                        cellsoc_max=np.interp(cellvolt_max,self.param.LookTab_OCV,self.param.LookTab_SOC)
+                        cellvolt_diff=(cellvolt_max-cellvolt_min)*1000
+                        cellsoc_diff=cellsoc_max-cellsoc_min
+                        cellsoc_diff=format(cellsoc_diff,'.1f')
+                        cellvolt_diff=format(cellvolt_diff,'.0f')
+                        df_res.loc[len(df_res)]=[self.bmstime[i], self.sn, cellsoc_diff, cellvolt_diff, cellmin_num, cellmax_num]
+                        break
+                    else:
+                        continue
+                else:
+                    continue
+            else:
+                standingtime=0
+                continue
+
+        if df_res.empty:    #返回计算结果
+            return pd.DataFrame()
+        else:
+            return df_res
+
+    def _lfp_uniform(self):
+        column_name=['time','sn','cellsoc_diff','cellvolt_diff','cellmin_num','cellmax_num']
+        df_res=pd.DataFrame(columns=column_name)
+        standingtime=0
+        chrg_start=[]
+        chrg_end=[]
+        charging=0
+
+        for i in range(3,len(self.df_bms)-3):
+
+            #静置电压法计算电芯一致性
+            if abs(self.packcrnt[i]) < 0.2:     #电流为0
+                delttime=(self.bmstime[i+1]-self.bmstime[i]).total_seconds()
+                standingtime=standingtime+delttime
+                self._celltemp_weight(i)     #获取不同温度对应的静置时间
+
+                if standingtime>self.StandardStandingTime:      #静置时间满足要求
+                    cellvolt_now=self._cellvolt_get(i)     #获取当前行电压数据
+                    cellvolt_min=min(cellvolt_now)
+                    cellvolt_max=max(cellvolt_now)
+                    if abs(self.packcrnt[i+2]) >= 0.2 and cellvolt_max < self.param.OcvInflexionBelow:     
+                        standingtime=0                   
+                        cellmin_num=cellvolt_now.index(cellvolt_min)+1
+                        cellmax_num=cellvolt_now.index(cellvolt_max)+1
+                        cellsoc_min=np.interp(cellvolt_min,self.param.LookTab_OCV,self.param.LookTab_SOC)
+                        cellsoc_max=np.interp(cellvolt_max,self.param.LookTab_OCV,self.param.LookTab_SOC)
+                        cellvolt_diff=(cellvolt_max-cellvolt_min)*1000
+                        cellsoc_diff=cellsoc_max-cellsoc_min
+                        cellsoc_diff=format(cellsoc_diff,'.1f')
+                        cellvolt_diff=format(cellvolt_diff,'.0f')
+                        df_res.loc[len(df_res)]=[self.bmstime[i], self.sn, cellsoc_diff, cellvolt_diff, cellmin_num, cellmax_num]
+                    elif i>=len(self.df_bms)-4 and cellvolt_max < self.param.OcvInflexionBelow:
+                        standingtime=0
+                        cellmin_num=cellvolt_now.index(cellvolt_min)+1
+                        cellmax_num=cellvolt_now.index(cellvolt_max)+1
+                        cellsoc_min=np.interp(cellvolt_min,self.param.LookTab_OCV,self.param.LookTab_SOC)
+                        cellsoc_max=np.interp(cellvolt_max,self.param.LookTab_OCV,self.param.LookTab_SOC)
+                        cellvolt_diff=(cellvolt_max-cellvolt_min)*1000
+                        cellsoc_diff=cellsoc_max-cellsoc_min
+                        cellsoc_diff=format(cellsoc_diff,'.1f')
+                        cellvolt_diff=format(cellvolt_diff,'.0f')
+                        df_res.loc[len(df_res)]=[self.bmstime[i], self.sn, cellsoc_diff, cellvolt_diff, cellmin_num, cellmax_num]
+                    else:
+                        pass
+                else:
+                    pass
+            else:
+                standingtime=0
+                pass   
+
+            #获取DVDQ算法所需数据——开始
+            if i==3 and self.packcrnt[1]<=-1 and self.packcrnt[2]<=-1 and self.packcrnt[3]<=-1:
+                chrg_start.append(i)
+                charging=1
+            elif self.packcrnt[i-1]>-1 and self.packcrnt[i]<=-1 and self.packcrnt[i+1]<=-1 and self.packcrnt[i+2]<=-1:     #判断充电开始
+                if self.bms_soc[i]<45:
+                    charging=1
+                    if len(chrg_start)>len(chrg_end):
+                        chrg_start[-1]=i
+                    else:
+                        chrg_start.append(i)
+                else:
+                    pass
+            else:
+                pass
+
+            if charging==1: #充电中
+                if (self.bmstime[i+1]-self.bmstime[i]).total_seconds()>180:  #如果充电过程中时间间隔>180s，则舍弃该次充电
+                    chrg_start.remove(chrg_start[-1])
+                    charging=0
+                    continue
+                elif self.packcrnt[i]<=-1 and self.packcrnt[i+1]<=-1 and  self.packcrnt[i+2]>-1:  #判断电流波动时刻
+                    cellvolt_now=self._cellvolt_get(i+1)
+                    if max(cellvolt_now)>self.param.CellFullChrgVolt:   #电压>满充电压
+                        chrg_end.append(i+1)
+                        charging=0
+                        continue
+                    else:
+                        pass
+                elif self.packcrnt[i+1]>-0.1 and self.packcrnt[i+2]>-0.1 and self.packcrnt[i+3]>-0.1:   #判断充电结束
+                    charging=0
+                    if len(chrg_start)>len(chrg_end):
+                        if self.bms_soc[i]>90:
+                            chrg_end.append(i)
+                        else:
+                            chrg_start.remove(chrg_start[-1])
+                            continue
+                    else:
+                        continue
+                elif i==len(self.packcrnt)-4 and self.packcrnt[i+1]<-1 and self.packcrnt[i+2]<-1:
+                    charging=0
+                    if len(chrg_start)>len(chrg_end):
+                        if self.bms_soc[i]>90:   #soc>90
+                            chrg_end.append(i)
+                            continue
+                        else:
+                            chrg_start.remove(chrg_start[-1])
+                            continue
+                    else:
+                        continue   
+            else:
+                pass
+            #获取DVDQ算法所需数据——结束
+
+        if chrg_end:    #DVDQ方法计算soc差
+            peaksoc_list=[]
+            for i in range(len(chrg_end)):
+                peaksoc_list = []
+                for j in range(1, self.param.CellVoltNums + 1):
+                    s = str(j)
+                    cellvolt = self.df_bms['单体电压' + s]
+                    cellvolt = list(cellvolt[chrg_start[i]:chrg_end[i]])
+                    time = list(self.bmstime[chrg_start[i]:chrg_end[i]])
+                    packcrnt = list(self.packcrnt[chrg_start[i]:chrg_end[i]])
+                    soc = list(self.bms_soc[chrg_start[i]:chrg_end[i]])
+                    peaksoc = self._dvdq_peak(time, soc, cellvolt, packcrnt)
+                    if peaksoc>1:
+                        peaksoc_list.append(peaksoc)    #计算到达峰值点的累计Soc
+                    else:
+                        pass
+                if len(peaksoc_list)>11:
+                    peaksoc_max=max(peaksoc_list)
+                    peaksoc_min=min(peaksoc_list)
+                    peaksoc_maxnum=peaksoc_list.index(peaksoc_min)+1
+                    peaksoc_minnum=peaksoc_list.index(peaksoc_max)+1
+                    cellsoc_diff=peaksoc_max-peaksoc_min
+                    cellsoc_diff=format(cellsoc_diff,'.1f')
+                    df_res.loc[len(df_res)]=[self.bmstime[chrg_start[i]], self.sn, cellsoc_diff, 0, peaksoc_minnum, peaksoc_maxnum]
+                else:
+                    pass
+
+        if df_res.empty:
+            return pd.DataFrame()
+        else:
+            df_res.sort_values(by='time', ascending=True, inplace=True)
+            return df_res

LIB/MIDDLE/CellStateEstimation/Uniform/V1_0_0/log.py

@@ -0,0 +1,24 @@
+import logging
+import traceback
+
+class Mylog:
+
+    def __init__(self,log_name,log_level):
+        self.name=log_name
+        self.level=log_level
+    
+    def logcfg(self):
+        if len(self.level) > 0:
+            if self.level == 'debug':
+                Level=logging.DEBUG
+            elif self.level == 'info':
+                Level=logging.INFO
+            elif self.level == 'warning':
+                Level=logging.WARNING
+            else:
+                Level=logging.ERROR
+        logging.basicConfig(filename=self.name, level=Level,format='%(asctime)s - %(levelname)s - %(message)s')
+
+    def logopt(self,*info):
+        logging.error(info)
+        logging.error(traceback.format_exc())

LIB/MIDDLE/CellStateEstimation/Uniform/V1_0_0/main.py

@@ -0,0 +1,73 @@
+import CBMSBatUniform
+import log
+
+#coding=utf-8
+import os
+import sys
+import datetime
+import pandas as pd
+from LIB.BACKEND import DBManager, Log
+# from LIB.MIDDLE import SignalMonitor
+from sqlalchemy import create_engine
+from sqlalchemy.orm import sessionmaker
+import time, datetime
+from LIB.MIDDLE.soh import NCMSoh_20210716 as NCMSoh
+from LIB.MIDDLE.soh import LFPSoh_20210711 as LFPSoh
+from urllib import parse
+
+dbManager = DBManager.DBManager()
+if __name__ == "__main__":
+    SNdata_6040 = pd.read_excel('骑享资产梳理-20210621.xlsx', sheet_name='6040骑享')
+    SNdata_6060 = pd.read_excel('骑享资产梳理-20210621.xlsx', sheet_name='6060')
+    SNdata_4840 = pd.read_excel('骑享资产梳理-20210621.xlsx', sheet_name='4840骑享')
+    SNdata_7250 = pd.read_excel('骑享资产梳理-20210621.xlsx', sheet_name='7250')
+    SNnums_6060=SNdata_6060['SN号']
+    SNnums_6040=SNdata_6040['SN号']
+    SNnums_4840=SNdata_4840['SN号']
+    SNnums_7250=SNdata_7250['SN号']
+
+    SNnums=SNnums_6040.tolist()+SNnums_6060.tolist()+SNnums_4840.tolist()+SNnums_7250.tolist()
+    now_time=datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')
+    now_time=datetime.datetime.strptime(now_time,'%Y-%m-%d %H:%M:%S')
+    start_time=now_time-datetime.timedelta(days=5)
+    end_time=str(now_time)
+    start_time=str(start_time)
+
+    #log信息配置
+    mylog=log.Mylog('log.txt','error')
+    mylog.logcfg()
+
+    for sn in SNnums:
+        try:
+            if 'PK500' in sn:
+                celltype=1 #6040三元电芯
+            elif 'PK502' in sn:
+                celltype=2 #4840三元电芯
+            elif 'PK504' in sn:
+                celltype=99    #60ah林磷酸铁锂电芯
+            elif 'MGMLXN750' in sn:
+                celltype=3 #力信50ah三元电芯
+            elif 'MGMCLN750' in sn: 
+                celltype=4 #CATL 50ah三元电芯
+            else:
+                print('未找到对应电池编号！！！')
+                sys.exit()
+            
+            # sn='PK50001A100000035'
+            # start_time='2021-08-10 9:49:37'
+            # end_time='2021-08-29 19:49:37'
+
+            dbManager = DBManager.DBManager()
+            df_data = dbManager.get_data(sn=sn, start_time=start_time, end_time=end_time, data_groups=['bms'])
+            df_bms = df_data['bms']
+            # df_bms.to_csv('BMS_'+sn+'.csv',encoding='GB18030')
+
+            BatUniform=CBMSBatUniform.BatUniform(sn,celltype,df_bms)
+            df_res=BatUniform.batuniform()
+            df_res.to_csv('CBMS_Uniform_'+sn+'.csv',encoding='GB18030')
+        
+        
+        except IndexError as e:
+            print(repr(e))
+            mylog.logopt(sn,e)
+            pass

LIB/MIDDLE/CellStateEstimation/Uniform/main.py

@@ -0,0 +1,73 @@
+import CBMSBatUniform
+import log
+
+#coding=utf-8
+import os
+import sys
+import datetime
+import pandas as pd
+from LIB.BACKEND import DBManager, Log
+# from LIB.MIDDLE import SignalMonitor
+from sqlalchemy import create_engine
+from sqlalchemy.orm import sessionmaker
+import time, datetime
+from LIB.MIDDLE.soh import NCMSoh_20210716 as NCMSoh
+from LIB.MIDDLE.soh import LFPSoh_20210711 as LFPSoh
+from urllib import parse
+
+dbManager = DBManager.DBManager()
+if __name__ == "__main__":
+    SNdata_6040 = pd.read_excel('骑享资产梳理-20210621.xlsx', sheet_name='6040骑享')
+    SNdata_6060 = pd.read_excel('骑享资产梳理-20210621.xlsx', sheet_name='6060')
+    SNdata_4840 = pd.read_excel('骑享资产梳理-20210621.xlsx', sheet_name='4840骑享')
+    SNdata_7250 = pd.read_excel('骑享资产梳理-20210621.xlsx', sheet_name='7250')
+    SNnums_6060=SNdata_6060['SN号']
+    SNnums_6040=SNdata_6040['SN号']
+    SNnums_4840=SNdata_4840['SN号']
+    SNnums_7250=SNdata_7250['SN号']
+
+    SNnums=SNnums_6040.tolist()+SNnums_6060.tolist()+SNnums_4840.tolist()+SNnums_7250.tolist()
+    now_time=datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')
+    now_time=datetime.datetime.strptime(now_time,'%Y-%m-%d %H:%M:%S')
+    start_time=now_time-datetime.timedelta(days=5)
+    end_time=str(now_time)
+    start_time=str(start_time)
+
+    #log信息配置
+    mylog=log.Mylog('log.txt','error')
+    mylog.logcfg()
+
+    for sn in SNnums:
+        try:
+            if 'PK500' in sn:
+                celltype=1 #6040三元电芯
+            elif 'PK502' in sn:
+                celltype=2 #4840三元电芯
+            elif 'PK504' in sn:
+                celltype=99    #60ah林磷酸铁锂电芯
+            elif 'MGMLXN750' in sn:
+                celltype=3 #力信50ah三元电芯
+            elif 'MGMCLN750' in sn: 
+                celltype=4 #CATL 50ah三元电芯
+            else:
+                print('未找到对应电池编号！！！')
+                sys.exit()
+            
+            # sn='PK50001A100000035'
+            # start_time='2021-08-10 9:49:37'
+            # end_time='2021-08-29 19:49:37'
+
+            dbManager = DBManager.DBManager()
+            df_data = dbManager.get_data(sn=sn, start_time=start_time, end_time=end_time, data_groups=['bms'])
+            df_bms = df_data['bms']
+            # df_bms.to_csv('BMS_'+sn+'.csv',encoding='GB18030')
+
+            BatUniform=CBMSBatUniform.BatUniform(sn,celltype,df_bms)
+            df_res=BatUniform.batuniform()
+            df_res.to_csv('CBMS_Uniform_'+sn+'.csv',encoding='GB18030')
+        
+        
+        except IndexError as e:
+            print(repr(e))
+            mylog.logopt(sn,e)
+            pass