热失控预警初版策略

LIB/MIDDLE/CellStateEstimation/BatSafetyWarning/V1_0_1/CBMSBatInterShort.py

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+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+# from pymysql import paramstyle
+from LIB.MIDDLE.CellStateEstimation.Common.V1_0_1 import BatParam
+
+class BatInterShort():
+    def __init__(self,sn,celltype,df_bms,df_soh,df_last,df_last1,df_last2,df_last3,df_lfp):  #参数初始化
+
+        if (not df_lfp.empty) and celltype>50:
+            df_lfp.drop(['sn'],axis=1)
+            df_bms=pd.concat([df_lfp, df_bms], ignore_index=True)
+        else:
+            pass
+
+        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.param.PackCrntDec
+        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')
+
+        self.df_soh=df_soh
+        self.df_last=df_last
+        self.df_last1=df_last1
+        self.df_last2=df_last2
+        self.df_last3=df_last3
+        self.df_lfp=df_lfp
+
+        self.cellvolt_name=['单体电压'+str(x) for x in range(1,self.param.CellVoltNums+1)]
+        self.celltemp_name=['单体温度'+str(x) for x in range(1,self.param.CellTempNums+1)]
+    
+    def intershort(self):
+        if self.celltype<=50:
+            df_res, df_ram_last, df_ram_last1, df_ram_last3=self._ncm_intershort()
+            return df_res, df_ram_last, df_ram_last1,self.df_last2, df_ram_last3,self.df_lfp
+            
+        else:
+            df_res, df_ram_last, df_ram_last1, df_ram_last2, df_ram_last3, df_ram_lfp=self._lfp_intershort()
+            return df_res, df_ram_last, df_ram_last1, df_ram_last2, df_ram_last3, df_ram_lfp
+
+
+    #定义滑动滤波函数....................................................................................
+    def _np_move_avg(self,a, n, mode="same"): 
+        return (np.convolve(a, np.ones((n,)) / n, mode=mode))
+    
+    #寻找当前行数据的最小温度值.............................................................................
+    def _celltemp_weight(self,num):   
+        celltemp = list(self.df_bms.loc[num,self.celltemp_name])
+        celltemp=np.mean(celltemp)
+        self.celltemp=celltemp
+        if self.celltype==99:
+            if celltemp>=25:
+                self.tempweight=1
+                self.StandardStandingTime=3600
+            elif celltemp>=15:
+                self.tempweight=0.6
+                self.StandardStandingTime=7200
+            elif celltemp>=5:
+                self.tempweight=0.
+                self.StandardStandingTime=10800
+            else:
+                self.tempweight=0.1
+                self.StandardStandingTime=10800
+        else:
+            if celltemp>=20:
+                self.tempweight=1
+                self.StandardStandingTime=3600
+            elif celltemp>=10:
+                self.tempweight=0.8
+                self.StandardStandingTime=3600
+            elif celltemp>=5:
+                self.tempweight=0.6
+                self.StandardStandingTime=7200
+            else:
+                self.tempweight=0.2
+                self.StandardStandingTime=10800
+
+    #获取当前行所有电压数据........................................................................................
+    def _cellvolt_get(self,num): 
+        cellvolt = np.array(self.df_bms.loc[num,self.cellvolt_name])/1000
+        return cellvolt
+
+    #获取当前行所有soc差...........................................................................................
+    def _celldeltsoc_get(self,num,dict_baltime,capacity): 
+        cellsoc=[]
+        celldeltsoc=[]
+        for j in range(1, self.param.CellVoltNums+1):   #获取每个电芯电压对应的SOC值
+            cellvolt=self.df_bms.loc[num,'单体电压' + str(j)]/1000
+            ocv_soc=np.interp(cellvolt,self.param.LookTab_OCV,self.param.LookTab_SOC)
+            if j in dict_baltime.keys():
+                ocv_soc=ocv_soc+dict_baltime[j]*self.param.BalCurrent/(capacity*3600)   #补偿均衡电流
+            else:
+                pass
+            cellsoc.append(ocv_soc)
+        
+        if self.celltype==1 or self.celltype==2:
+            consum_num=7
+            cellsoc1=cellsoc[:self.param.CellVoltNums-consum_num]    #切片，将bms耗电的电芯和非耗电的电芯分离开
+            cellsocmean1=(sum(cellsoc1)-max(cellsoc1)-min(cellsoc1))/(len(cellsoc1)-2)
+            cellsoc2=cellsoc[self.param.CellVoltNums-consum_num:]
+            cellsocmean2=(sum(cellsoc2)-max(cellsoc2)-min(cellsoc2))/(len(cellsoc2)-2)
+            
+            for j in range(len(cellsoc)):   #计算每个电芯的soc差
+                if j<self.param.CellVoltNums-consum_num:
+                    celldeltsoc.append(cellsoc[j]-cellsocmean1)
+                else:
+                    celldeltsoc.append(cellsoc[j]-cellsocmean2)
+            return np.array(celldeltsoc)
+
+        else:
+            cellsocmean=(sum(cellsoc)-max(cellsoc)-min(cellsoc))/(len(cellsoc)-2)
+            for j in range(len(cellsoc)):   #计算每个电芯的soc差
+                celldeltsoc.append(cellsoc[j]-cellsocmean)
+            return np.array(celldeltsoc), np.array(cellsoc)
+ 
+    #获取所有电芯的As差
+    def _cellDeltAs_get(self,chrg_st,chrg_end,dict_baltime):
+        cellAs=[]
+        celldeltAs=[]
+        for j in range(1, self.param.CellVoltNums+1):   #获取每个电芯电压>峰值电压的充入As数
+            if j in dict_baltime.keys():    #补偿均衡电流
+                As=-self.param.BalCurrent*dict_baltime[j]
+            else:    
+                As=0
+            As_tatol=0
+            symbol=0
+            for m in range(chrg_st+1,chrg_end):
+                As=As-self.packcrnt[m]*(self.bmstime[m]-self.bmstime[m-1]).total_seconds()
+                if symbol<5:
+                    if self.df_bms.loc[m,'单体电压'+str(j)]/1000>self.param.PeakCellVolt[symbol]:
+                        As_tatol=As_tatol+As
+                        symbol=symbol+1
+                    else:
+                        continue
+                else:
+                    cellAs.append(As_tatol/5)
+                    break
+        
+        if self.celltype==99:
+            consum_num=10
+            cellAs1=cellAs[:self.param.CellVoltNums-consum_num]    #切片，将bms耗电的电芯和非耗电的电芯分离开
+            cellAsmean1=(sum(cellAs1)-max(cellAs1)-min(cellAs1))/(len(cellAs1)-2)
+            cellAs2=cellAs[self.param.CellVoltNums-consum_num:]
+            cellAsmean2=(sum(cellAs2)-max(cellAs2)-min(cellAs2))/(len(cellAs2)-2)
+            
+            for j in range(len(cellAs)):   #计算每个电芯的soc差
+                if j<self.param.CellVoltNums-consum_num:
+                    celldeltAs.append(cellAs[j]-cellAsmean1)
+                else:
+                    celldeltAs.append(cellAs[j]-cellAsmean2)
+        else:
+            cellAsmean=(sum(cellAs)-max(cellAs)-min(cellAs))/(len(cellAs)-2)
+            for j in range(len(cellAs)):   #计算每个电芯的soc差
+                celldeltAs.append(cellAs[j]-cellAsmean)
+            
+        return np.array(celldeltAs)
+
+    #计算每个电芯的均衡时长..........................................................................................................................
+    def _bal_time(self,dict_bal):
+        dict_baltime={}
+        dict_baltime1={}
+        for key in dict_bal:
+            count=1
+            x=eval(key)
+            while x>0:
+                if x & 1==1:    #判断最后一位是否为1
+                    if count in dict_baltime.keys():
+                        dict_baltime[count] = dict_baltime[count] + dict_bal[key]
+                    else:
+                        dict_baltime[count] = dict_bal[key]
+                else:
+                    pass
+                count += 1
+                x >>= 1    #右移一位
+        
+        dict_baltime=dict(sorted(dict_baltime.items(),key=lambda dict_baltime:dict_baltime[0]))
+        for key in dict_baltime:    #解析均衡的电芯编号
+            if self.celltype==1:    #科易6040
+                if key<14:
+                    dict_baltime1[key]=dict_baltime[key]
+                elif key<18:
+                    dict_baltime1[key-1]=dict_baltime[key]
+                else:
+                    dict_baltime1[key-3]=dict_baltime[key]
+            elif self.celltype==1:    #科易4840
+                if key<4:
+                    dict_baltime1[key-1]=dict_baltime[key]
+                elif key<8:
+                    dict_baltime1[key-1]=dict_baltime[key]
+                elif key<14:
+                    dict_baltime1[key-3]=dict_baltime[key]
+                elif key<18:
+                    dict_baltime1[key-4]=dict_baltime[key]
+                else:
+                    dict_baltime1[key-6]=dict_baltime[key]
+            else:
+                dict_baltime1=dict_baltime
+        return dict_baltime1
+
+    #三元电池的内短路电流计算...........................................................................................................................................................
+    def _ncm_intershort(self):
+        column_name=['time_st', 'time_sp', 'sn', 'method','short_current','baltime']
+        df_res=pd.DataFrame(columns=column_name)
+        df_ram_last=self.df_last
+        df_ram_last1=self.df_last1
+        df_ram_last3=self.df_last3
+
+        #容量初始化
+        if self.df_soh.empty:
+            batsoh=self.df_bms.loc[0,'SOH[%]']
+            capacity=self.param.Capacity*batsoh/100
+        else:
+            batsoh=self.df_soh.loc[len(self.df_soh)-1,'soh']
+            capacity=self.param.Capacity*batsoh/100
+
+        #参数初始化
+        if self.df_last.empty:  
+            firsttime=1
+            dict_bal={}
+        else:
+            deltsoc_last=self.df_last.loc[0,'deltsoc']
+            cellsoc_last=self.df_last.loc[0,'cellsoc']
+            time_last=self.df_last.loc[0,'time']
+            firsttime=0
+            dict_bal={}
+        if self.df_last1.empty:
+            firsttime1=1
+            dict_bal1={}
+        else:
+            deltsoc_last1=self.df_last1.loc[0,'deltsoc1']
+            time_last1=self.df_last1.loc[0,'time1']
+            firsttime1=0
+            dict_bal1={}
+        if self.df_last3.empty:
+            standingtime=0
+            standingtime1=0
+        else:
+            standingtime=self.df_last3.loc[0,'standingtime']
+            standingtime1=self.df_last3.loc[0,'standingtime1']
+            firsttime1=0
+            dict_bal1={}
+
+        for i in range(1,len(self.df_bms)-1):
+
+            if firsttime1==0:   #满电静置算法--计算均衡状态对应的均衡时间
+                try:
+                    balstat=int(self.df_bms.loc[i,'单体均衡状态'])
+                    if balstat>0.5:
+                        bal_step=(self.bmstime[i+1]-self.bmstime[i]).total_seconds()  #均衡步长
+                        bal_step=int(bal_step)
+                        if str(balstat) in dict_bal1.keys():
+                            dict_bal1[str(balstat)]=dict_bal1[str(balstat)]+bal_step
+                        else:
+                            dict_bal1[str(balstat)]=bal_step
+                    else:
+                        pass
+                except:
+                    dict_bal1={}
+            else:
+                pass
+
+            if abs(self.packcrnt[i]) < 0.1 and abs(self.packcrnt[i-1]) < 0.1 and abs(self.packcrnt[i+1]) < 0.1:     
+                delttime=(self.bmstime[i]-self.bmstime[i-1]).total_seconds()
+                standingtime=standingtime+delttime
+                standingtime1=standingtime1+delttime
+                self._celltemp_weight(i)
+
+                #长时间静置法计算内短路-开始.....................................................................................................................................
+                if firsttime==1:    
+                    if standingtime>self.StandardStandingTime*2:      #静置时间满足要求
+                        standingtime=0
+                        cellvolt_now=self._cellvolt_get(i)
+                        cellvolt_min=min(cellvolt_now)
+                        cellvolt_max=max(cellvolt_now)
+                        cellvolt_last=self._cellvolt_get(i-1)
+                        deltvolt=max(abs(cellvolt_now-cellvolt_last))
+
+                        if 2<cellvolt_min<4.5 and 2<cellvolt_max<4.5 and deltvolt<0.005: 
+                            dict_baltime={}   #获取每个电芯的均衡时间
+                            deltsoc_last, cellsoc_last=self._celldeltsoc_get(i,dict_baltime,capacity)
+                            time_last=self.bmstime[i]
+                            firsttime=0
+                            df_ram_last.loc[0]=[self.sn,time_last,deltsoc_last,cellsoc_last]   #更新RAM信息
+                    else:
+                        pass                
+                elif standingtime>3600*10:
+                    standingtime=0
+                    cellvolt_now=self._cellvolt_get(i)
+                    cellvolt_min=min(cellvolt_now)
+                    cellvolt_max=max(cellvolt_now)
+                    cellvolt_last=self._cellvolt_get(i-1)
+                    deltvolt=max(abs(cellvolt_now-cellvolt_last))
+                    
+                    if 2<cellvolt_min<4.5 and 2<cellvolt_max<4.5 and deltvolt<0.005:
+                        dict_baltime=self._bal_time(dict_bal)   #获取每个电芯的均衡时间
+                        deltsoc_now, cellsoc_now=self._celldeltsoc_get(i,dict_baltime,capacity)
+                        time_now=self.bmstime[i]
+                        if -5<max(cellsoc_now-cellsoc_last)<5:
+                            df_ram_last.loc[0]=[self.sn,time_now,deltsoc_now,cellsoc_now] #更新RAM信息
+                            
+                            list_sub=deltsoc_now-deltsoc_last
+                            list_pud=(0.01*capacity*3600*1000)/(time_now-time_last).total_seconds()
+                            leak_current=list_sub*list_pud
+                            # leak_current=np.array(leak_current)
+                            leak_current=np.round(leak_current,3)
+                            leak_current=list(leak_current)
+                            
+                            df_res.loc[len(df_res)]=[time_last,time_now,self.sn,1,str(leak_current),str(dict_baltime)]  #计算结果存入Dataframe
+                            time_last=time_now  #更新时间
+                            deltsoc_last=deltsoc_now    #更新soc差
+                            dict_bal={}
+                        else:
+                            firsttime=1
+                else: 
+                    try:  
+                        balstat=int(self.df_bms.loc[i,'单体均衡状态'])
+                        if balstat>0.5:
+                            bal_step=(self.bmstime[i+1]-self.bmstime[i]).total_seconds()  #均衡步长
+                            bal_step=int(bal_step)
+                            if str(balstat) in dict_bal.keys():
+                                dict_bal[str(balstat)]=dict_bal[str(balstat)]+bal_step
+                            else:
+                                dict_bal[str(balstat)]=bal_step
+                        else:
+                            pass
+                    except:
+                        dict_bal={}
+
+                #满电静置法计算内短路-开始.....................................................................................................................................................
+                if self.StandardStandingTime<standingtime1:  
+                    standingtime1=0
+                    cellvolt_now1=self._cellvolt_get(i)
+                    cellvolt_max1=max(cellvolt_now1)
+                    cellvolt_min1=min(cellvolt_now1)
+                    cellvolt_last1=self._cellvolt_get(i-1)
+                    deltvolt1=max(abs(cellvolt_now1-cellvolt_last1))
+                    cellsoc_now1=np.interp(cellvolt_max1,self.param.LookTab_OCV,self.param.LookTab_SOC)
+
+                    if cellsoc_now1>=self.param.FullChrgSoc-10 and 2<cellvolt_min1<4.5 and 2<cellvolt_max1<4.5 and deltvolt1<0.005:
+                        if firsttime1==1:
+                            dict_baltime1={}   #获取每个电芯的均衡时间
+                            deltsoc_last1, cellsoc_last1=self._celldeltsoc_get(i,dict_baltime1,capacity)
+                            time_last1=self.bmstime[i]
+                            firsttime1=0
+                            df_ram_last1.loc[0]=[self.sn,time_last1,deltsoc_last1]    #更新RAM信息
+                        else:
+                            dict_baltime1=self._bal_time(dict_bal1)   #获取每个电芯的均衡时间
+                            time_now1=self.bmstime[i]
+                            if (time_now1-time_last1).total_seconds()>3600*12:
+                                deltsoc_now1, cellsoc_now1=self._celldeltsoc_get(i,dict_baltime1,capacity)
+                                df_ram_last1.loc[0]=[self.sn,time_now1,deltsoc_now1] #更新RAM信息
+
+                                list_sub1=deltsoc_now1-deltsoc_last1
+                                list_pud1=(0.01*capacity*3600*1000)/(time_now1-time_last1).total_seconds()
+                                leak_current1=list_sub1*list_pud1
+                                # leak_current1=np.array(leak_current1)
+                                leak_current1=np.round(leak_current1,3)
+                                leak_current1=list(leak_current1)
+                                
+                                df_res.loc[len(df_res)]=[time_last1,time_now1,self.sn,2,str(leak_current1),str(dict_baltime1)]  #计算结果存入Dataframe
+                                time_last1=time_now1  #更新时间
+                                deltsoc_last1=deltsoc_now1    #更新soc差
+                                dict_bal1={}
+                            else:
+                                pass
+                    else:
+                        pass
+                else:   
+                    pass
+
+            else:
+                df_ram_last=pd.DataFrame(columns=['sn','time','deltsoc','cellsoc'])   #电流>0,清空上次静置的SOC差
+                dict_bal={} 
+                firsttime=1
+                standingtime=0
+                standingtime1=0
+                pass
+        
+        #更新RAM的standingtime
+        df_ram_last3.loc[0]=[self.sn,standingtime,standingtime1]
+
+        #返回计算结果
+        if df_res.empty:    
+            return pd.DataFrame(), df_ram_last, df_ram_last1, df_ram_last3
+        else:
+            return df_res, df_ram_last, df_ram_last1, df_ram_last3
+
+    #磷酸铁锂电池内短路计算程序.............................................................................................................................
+    def _lfp_intershort(self):
+        column_name=['time_st', 'time_sp', 'sn', 'method','short_current','baltime']
+        df_res=pd.DataFrame(columns=column_name)
+        df_ram_last=self.df_last
+        df_ram_last1=self.df_last1
+        df_ram_last2=self.df_last2
+        df_ram_last3=self.df_last3
+        df_ram_lfp=pd.DataFrame(columns=self.df_bms.columns.tolist())
+
+        #容量初始化
+        if self.df_soh.empty:
+            batsoh=self.df_bms.loc[0,'SOH[%]']
+            capacity=self.param.Capacity*batsoh/100
+        else:
+            batsoh=self.df_soh.loc[len(self.df_soh)-1,'soh']
+            capacity=self.param.Capacity*batsoh/100
+        #参数初始化
+        if self.df_last.empty:  
+            firsttime=1
+            dict_bal={}
+        else:
+            deltsoc_last=self.df_last.loc[0,'deltsoc']
+            cellsoc_last=self.df_last.loc[0,'cellsoc']
+            time_last=self.df_last.loc[0,'time']
+            firsttime=0
+            dict_bal={}
+        if self.df_last1.empty:
+            firsttime1=1
+            dict_bal1={}
+        else:
+            deltsoc_last1=self.df_last1.loc[0,'deltsoc1']
+            time_last1=self.df_last1.loc[0,'time1']
+            firsttime1=0
+            dict_bal1={}
+        if self.df_last2.empty:
+            firsttime2=1
+            charging=0
+            dict_bal2={}
+        else:
+            deltAs_last2=self.df_last2.loc[0,'deltAs2']
+            time_last2=self.df_last2.loc[0,'time2']
+            firsttime2=0
+            charging=0
+            dict_bal2={}
+        if self.df_last3.empty:
+            standingtime=0
+            standingtime1=0
+        else:
+            standingtime=self.df_last3.loc[0,'standingtime']
+            standingtime1=self.df_last3.loc[0,'standingtime1']
+            dict_bal1={}
+
+        for i in range(1,len(self.df_bms)-1):
+
+            #静置法计算内短路..........................................................................................................................
+            if firsttime1==0:   #满电静置算法--计算均衡状态对应的均衡时间
+                try:
+                    balstat=int(self.df_bms.loc[i,'单体均衡状态'])
+                    if balstat>0.5:
+                        bal_step=(self.bmstime[i+1]-self.bmstime[i]).total_seconds()  #均衡步长
+                        bal_step=int(bal_step)
+                        if str(balstat) in dict_bal1.keys():
+                            dict_bal1[str(balstat)]=dict_bal1[str(balstat)]+bal_step
+                        else:
+                            dict_bal1[str(balstat)]=bal_step
+                    else:
+                        pass
+                except:
+                    dict_bal1={}
+            else:
+                pass
+
+            if abs(self.packcrnt[i]) < 0.1 and abs(self.packcrnt[i-1]) < 0.1 and abs(self.packcrnt[i+1]) < 0.1:     
+                delttime=(self.bmstime[i]-self.bmstime[i-1]).total_seconds()
+                standingtime=standingtime+delttime
+                standingtime1=standingtime1+delttime
+                self._celltemp_weight(i)
+
+                #长时间静置法计算内短路-开始.....................................................................................................................................
+                if firsttime==1:    
+                    if standingtime>self.StandardStandingTime:      #静置时间满足要求
+                        standingtime=0
+                        cellvolt_now=self._cellvolt_get(i)
+                        cellvolt_min=min(cellvolt_now)
+                        cellvolt_max=max(cellvolt_now)
+                        cellvolt_last=self._cellvolt_get(i-1)
+                        deltvolt=max(abs(cellvolt_now-cellvolt_last))
+
+                        if 2<cellvolt_max<self.param.OcvInflexionBelow-0.002 and 2<cellvolt_min<4.5 and abs(deltvolt)<0.003:
+                            dict_baltime={}  #获取每个电芯的均衡时间
+                            deltsoc_last, cellsoc_last=self._celldeltsoc_get(i,dict_baltime,capacity)
+                            time_last=self.bmstime[i]
+                            firsttime=0
+                            df_ram_last.loc[0]=[self.sn,time_last,deltsoc_last,cellsoc_last]   #更新RAM信息
+                        else:
+                            pass
+                    else:
+                        pass                
+                elif standingtime>3600*10:
+                    standingtime=0
+                    cellvolt_now=np.array(self._cellvolt_get(i))
+                    cellvolt_min=min(cellvolt_now)
+                    cellvolt_max=max(cellvolt_now)
+                    cellvolt_last=np.array(self._cellvolt_get(i-1))
+                    deltvolt=max(abs(cellvolt_now-cellvolt_last))
+
+                    if 2<cellvolt_max<self.param.OcvInflexionBelow-0.002 and 2<cellvolt_min<4.5  and abs(deltvolt)<0.003:
+                        dict_baltime=self._bal_time(dict_bal)   #获取每个电芯的均衡时间
+                        deltsoc_now, cellsoc_now=self._celldeltsoc_get(i, dict_baltime,capacity)    #获取每个电芯的SOC差
+                        time_now=self.bmstime[i]
+                        if -5<max(cellsoc_now-cellsoc_last)<5:
+                            df_ram_last.loc[0]=[self.sn,time_now,deltsoc_now,cellsoc_now]   #更新RAM信息
+
+                            list_sub=deltsoc_now-deltsoc_last
+                            list_pud=(0.01*capacity*3600*1000)/(time_now-time_last).total_seconds()
+                            leak_current=list_sub*list_pud
+                            # leak_current=np.array(leak_current)
+                            leak_current=np.round(leak_current,3)
+                            leak_current=list(leak_current)
+                            
+                            df_res.loc[len(df_res)]=[time_last,time_now,self.sn,1,str(leak_current),str(dict_baltime)]  #计算结果存入Dataframe
+                            time_last=time_now  #更新时间
+                            deltsoc_last=deltsoc_now    #更新soc差
+                            dict_bal={}
+                        else:
+                            firsttime=1
+                    else:
+                        pass
+                else: 
+                    try:  
+                        balstat=int(self.df_bms.loc[i,'单体均衡状态'])
+                        if balstat>0.5:
+                            bal_step=(self.bmstime[i+1]-self.bmstime[i]).total_seconds()  #均衡步长
+                            bal_step=int(bal_step)
+                            if str(balstat) in dict_bal.keys():
+                                dict_bal[str(balstat)]=dict_bal[str(balstat)]+bal_step
+                            else:
+                                dict_bal[str(balstat)]=bal_step
+                        else:
+                            pass
+                    except:
+                        dict_bal={}
+
+                #非平台区间静置法计算内短路-开始.....................................................................................................................................................
+                if standingtime1>self.StandardStandingTime: 
+                    standingtime1=0
+                    cellvolt_now1=self._cellvolt_get(i)
+                    cellvolt_max1=max(cellvolt_now1)
+                    cellvolt_min1=min(cellvolt_now1)
+                    cellvolt_last1=self._cellvolt_get(i-1)
+                    deltvolt1=max(abs(cellvolt_now1-cellvolt_last1))
+                
+                    if 2<cellvolt_max1<self.param.OcvInflexionBelow-0.002 and 2<cellvolt_min1<4.5 and deltvolt1<0.005:
+                        if firsttime1==1:
+                            dict_baltime1=self._bal_time(dict_bal1)   #获取每个电芯的均衡时间
+                            deltsoc_last1, cellsoc_last1=self._celldeltsoc_get(i,dict_baltime1,capacity)
+                            time_last1=self.bmstime[i]
+                            firsttime1=0
+                            df_ram_last1.loc[0]=[self.sn,time_last1,deltsoc_last1]    #更新RAM信息
+                        else:
+                            dict_baltime1=self._bal_time(dict_bal1)   #获取每个电芯的均衡时间
+                            deltsoc_now1, cellsoc_now1=self._celldeltsoc_get(i,dict_baltime1,capacity)
+                            time_now1=self.bmstime[i]
+                            df_ram_last1.loc[0]=[self.sn,time_now1,deltsoc_now1]    #更新RAM信息
+
+                            if (time_now1-time_last1).total_seconds()>3600*12:
+                                list_sub1=deltsoc_now1-deltsoc_last1
+                                list_pud1=(0.01*capacity*3600*1000)/(time_now1-time_last1).total_seconds()
+                                leak_current1=list_sub1*list_pud1
+                                # leak_current1=np.array(leak_current1)
+                                leak_current1=np.round(leak_current1,3)
+                                leak_current1=list(leak_current1)
+                                
+                                df_res.loc[len(df_res)]=[time_last1,time_now1,self.sn,2,str(leak_current1),str(dict_baltime1)]  #计算结果存入Dataframe
+                                time_last1=time_now1  #更新时间
+                                deltsoc_last1=deltsoc_now1    #更新soc差
+                                dict_bal1={}
+                            else:
+                                pass
+                    else:
+                        pass
+                else:   
+                    pass
+
+            else:
+                df_ram_last=pd.DataFrame(columns=['sn','time','deltsoc','cellsoc'])   #电流>0,清空上次静置的SOC差
+                dict_bal={} 
+                firsttime=1
+                standingtime=0
+                standingtime1=0
+                pass
+
+            #获取充电数据——开始..............................................................................................................
+            try:
+                balstat=int(self.df_bms.loc[i,'单体均衡状态'])  #统计均衡状态
+                if balstat>0.5:
+                    bal_step=(self.bmstime[i+1]-self.bmstime[i]).total_seconds()  #均衡步长
+                    bal_step=int(bal_step)
+                    if str(balstat) in dict_bal2.keys():
+                        dict_bal2[str(balstat)]=dict_bal2[str(balstat)]+bal_step
+                    else:
+                        dict_bal2[str(balstat)]=bal_step
+                else:
+                    pass
+            except:
+                dict_bal2={}
+
+            #判断充电状态
+            if self.packcrnt[i]<=-1 and self.packcrnt[i+1]<=-1 and self.packcrnt[i-1]<=-1:
+                if charging==0:
+                    if self.bms_soc[i]<40:
+                        cellvolt_now=self._cellvolt_get(i)
+                        if min(cellvolt_now)<self.param.CellFullChrgVolt-0.15:
+                            charging=1
+                            chrg_start=i
+                        else:
+                            pass
+                    else:
+                        pass
+
+                else: #充电中
+                    cellvolt_now=self._cellvolt_get(i)
+                    if (self.bmstime[i+1]-self.bmstime[i]).total_seconds()>180 or (self.packcrnt[i]>self.param.Capacity/3 and self.packcrnt[i+1]>self.param.Capacity/3):  #如果充电过程中时间间隔>180s，则舍弃该次充电
+                        charging=0
+                        continue
+                    elif min(cellvolt_now)>self.param.CellFullChrgVolt-0.13:   #电压>满充电压-0.13V，即3.37V
+                        self._celltemp_weight(i)
+                        if i-chrg_start>10 and self.celltemp>10:
+                            chrg_end=i+1
+                            charging=0
+
+                            #计算漏电流值...................................................................
+                            if firsttime2==1:
+                                dict_baltime={}
+                                deltAs_last2=self._cellDeltAs_get(chrg_start,chrg_end,dict_baltime)
+                                time_last2=self.bmstime[chrg_end]
+                                df_ram_last2.loc[0]=[self.sn,time_last2,deltAs_last2]    #更新RAM信息
+                            else:
+                                dict_baltime=self._bal_time(dict_bal2)   #获取每个电芯的均衡时间
+                                deltAs_now2=self._cellDeltAs_get(chrg_start,chrg_end,dict_baltime)  #获取每个电芯的As差
+                                time_now2=self.bmstime[chrg_end]
+                                df_ram_last2.loc[0]=[self.sn,time_now2,deltAs_now2]    #更新RAM信息
+
+                                list_sub2=deltAs_now2-deltAs_last2
+                                list_pud2=-1000/(time_now2-time_last2).total_seconds()
+                                leak_current2=list_sub2*list_pud2
+                                # leak_current=np.array(leak_current)
+                                leak_current2=np.round(leak_current2,3)
+                                leak_current2=list(leak_current2)
+
+                                df_res.loc[len(df_res)]=[time_last2,time_now2,self.sn,3,str(leak_current2),str(dict_baltime)]  #计算结果存入Dataframe
+                                deltAs_last2=deltAs_now2
+                                time_last2=time_now2
+                                dict_bal2={}
+
+                        else:
+                            charging=0
+                            continue
+                    elif i==len(self.df_bms)-2:  #数据中断后仍在充电，将前段充电数据写入RAM
+                        df_ram_lfp=self.df_bms.iloc[chrg_start:]
+                        df_ram_lfp['sn']=self.sn
+                    else:
+                        pass
+            else:
+                pass
+
+    
+        #更新RAM
+        df_ram_last3.loc[0]=[self.sn,standingtime,standingtime1]
+
+        #返回结果
+        if df_res.empty:    
+            return pd.DataFrame(), df_ram_last, df_ram_last1, df_ram_last2, df_ram_last3,df_ram_lfp
+        else:
+            return df_res, df_ram_last, df_ram_last1, df_ram_last2, df_ram_last3, df_ram_lfp

LIB/MIDDLE/CellStateEstimation/BatSafetyWarning/V1_0_1/CBMSSafetyWarning.py

@@ -0,0 +1,96 @@
+import pandas as pd
+import numpy as np
+import datetime
+from LIB.MIDDLE.CellStateEstimation.Common.V1_0_1 import BatParam
+
+class SafetyWarning:
+    def __init__(self,sn,celltype,df_short,df_liplated,df_uniform,df_diag_ram):  #参数初始化
+
+        self.sn=sn
+        self.celltype=celltype
+        self.param=BatParam.BatParam(celltype)
+        self.df_short=df_short
+        self.df_liplated=df_liplated
+        self.df_uniform=df_uniform
+        self.df_diag_ram=df_diag_ram
+
+    
+    def diag(self):
+        if self.celltype<=50:
+            df_res=self._warning_diag()
+            return df_res    
+        else:
+            df_res=self._warning_diag()
+            return df_res
+        
+
+    #电池热安全预警诊断功能.................................................................................................
+    def _warning_diag(self):
+
+        df_res=pd.DataFrame(columns=['start_time', 'end_time', 'product_id', 'code', 'level', 'info','advice'])
+
+        time=datetime.datetime.now()
+        time_sp='0000-00-00 00:00:00'
+
+        #参数初始化
+        shortfault=0
+        liplatedfault=0
+        uniformfault=0
+
+        for i in range(self.param.CellVoltNums):
+
+            #漏电流故障判断...........................................................................
+            if not self.df_short.empty:
+                short_current=self.df_short['short_current']
+                short_current=short_current.str.replace("[", '')
+                short_current=short_current.str.replace("]", '')
+                self.df_short['cellshort'+str(i+1)]=short_current.map(lambda x:eval(x.split(',')[i]))
+
+                cellshort=self.df_short['cellshort'+str(i+1)]
+                index_list=cellshort[cellshort>self.param.LeakCurrentLv2].index
+                if len(index_list)==2 and (index_list[1]-index_list[0])==1:
+                    shortfault=1
+                elif len(index_list)>2:
+                    shortfault=1
+                else:
+                    shortfault=0
+            
+            #析锂故障判断...............................................................................
+            if not self.df_liplated.empty:
+                liplated=self.df_liplated['liplated']
+                liplated=liplated.str.replace("[", '')
+                liplated=liplated.str.replace("]", '')
+                self.df_liplated['liplated'+str(i+1)]=liplated.map(lambda x:eval(x.split(',')[i]))
+
+                if max(self.df_liplated['liplated'+str(i+1)])>0.5:
+                    liplatedfault=1
+                else:
+                    liplatedfault=0
+            else:
+                liplatedfault=0
+
+            #电芯SOC排名判断.............................................................................
+            if not self.df_uniform.empty:
+                if (i+1) in self.df_uniform['cellmin_num'].tolist():
+                    uniformfault=1
+                else:
+                    uniformfault=0
+            else:
+                uniformfault=0
+            
+            #电池热安全预警
+            if not 110 in list(self.df_diag_ram['code']):  #当前故障中没有该故障，则判断是否发生该故障
+                if shortfault==1 and (liplatedfault==1 or uniformfault==1):
+                    faultcode=110
+                    faultlv=4
+                    faultinfo='电芯{}热失控安全预警'.format(i+1)
+                    faultadvice='联系用户远离电池，立刻召回电池'
+                    self.df_diag_ram.loc[len(self.df_diag_ram)]=[time, time_sp, self.sn, faultcode, faultlv, faultinfo, faultadvice]
+                else:
+                    pass
+            else:
+                if shortfault==0 and liplatedfault==0:
+                    time=self.bmstime[i]
+                    self.df_diag_ram[self.df_diag_ram[self.df_diag_ram['faultcode']==110].index, 'time_sp'] = time
+            
+        return self.df_diag_ram

LIB/MIDDLE/CellStateEstimation/BatSafetyWarning/main.py

@@ -0,0 +1,210 @@
+import pandas as pd
+import pymysql
+from LIB.BACKEND import DBManager, Log
+from apscheduler.schedulers.blocking import BlockingScheduler
+import time, datetime
+from LIB.MIDDLE.CellStateEstimation.Common.V1_0_1 import DBDownload
+from LIB.MIDDLE.CellStateEstimation.Common.V1_0_1 import log
+import CBMSBatInterShort
+import CBMSSafetyWarning
+
+#电池热安全预警核心算法函数......................................................................................................................
+def saftywarning_cal():
+    global SNnums
+    global df_warning_ram
+    global df_warning_ram1
+    global df_warning_ram2
+    global df_warning_ram3
+    global df_lfp_ram
+    global now_time
+    
+    start=time.time()
+    # now_time=datetime.datetime.now()
+    # start_time=now_time-datetime.timedelta(hours=12)
+    # start_time1=now_time-datetime.timedelta(days=7)
+    # start_time2=now_time-datetime.timedelta(days=90)
+    # start_time=start_time.strftime('%Y-%m-%d %H:%M:%S')
+    # start_time1=start_time1.strftime('%Y-%m-%d %H:%M:%S')
+    # end_time=now_time.strftime('%Y-%m-%d %H:%M:%S')
+
+    now_time=now_time+datetime.timedelta(hours=12)
+    start_time=now_time-datetime.timedelta(hours=12)
+    start_time1=now_time-datetime.timedelta(days=7)
+    start_time2=now_time-datetime.timedelta(days=90)
+    start_time=start_time.strftime('%Y-%m-%d %H:%M:%S')
+    start_time1=start_time1.strftime('%Y-%m-%d %H:%M:%S')
+    end_time=now_time.strftime('%Y-%m-%d %H:%M:%S')
+
+    #数据库配置
+    host='rm-bp10j10qy42bzy0q77o.mysql.rds.aliyuncs.com'
+    port=3306
+    user='qx_read'
+    password='Qx@123456'
+
+    #读取故障结果库中code==110且end_time='0000-00-00 00:00:00'...............................
+    db='safety_platform'
+    mysql = pymysql.connect (host=host, user=user, password=password, port=port, database=db)
+    cursor = mysql.cursor()
+    param='start_time,end_time,product_id,code,level,info,advice'
+    tablename='all_fault_info'
+    sql =  "select %s from %s where code=110 and end_time='0000-00-00 00:00:00'" %(param,tablename)
+    cursor.execute(sql)
+    res = cursor.fetchall()
+    df_fault_ram= pd.DataFrame(res,columns=param.split(','))
+    cursor.close()
+    mysql.close()
+
+    for sn in SNnums:
+        if 'PK500' in sn:
+            celltype=1 #6040三元电芯
+        elif 'PK502' in sn:
+            celltype=2 #4840三元电芯
+        elif 'K504B' 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' or 'UD' in sn: 
+            celltype=4 #CATL 50ah三元电芯
+        else:
+            print('SN：{}，未找到对应电池类型！！！'.format(sn))
+            continue
+            # sys.exit()
+
+        #读取原始数据库数据........................................................................................................................................................
+        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']
+        # tim=start_time.replace(':','_')
+        # df_bms.to_csv(r'D:\Platform\platform_python\data_analyze_platform\USER\spf\01qixiang\98Download\\'+sn+'_BMS_'+tim+'.csv',encoding='GB18030')
+
+        #读取结果数据库数据........................................................................................................................................................
+        db='qx_cas'
+        mode=1
+        tablename='cellstateestimation_soh'
+        DBRead=DBDownload.DBDownload(host, port, db, user, password,mode)
+        with DBRead as DBRead:
+            df_soh=DBRead.getdata('time_st,sn,soh,cellsoh', tablename=tablename, sn=sn, timename='time_sp', st=start_time, sp=end_time)
+
+        if not df_bms.empty:
+            #电池内短路计算................................................................................................................................................................
+            df_warning_ram_sn=df_warning_ram[df_warning_ram['sn']==sn]
+            df_warning_ram_sn1=df_warning_ram1[df_warning_ram1['sn']==sn]
+            df_warning_ram_sn2=df_warning_ram2[df_warning_ram2['sn']==sn]
+            df_warning_ram_sn3=df_warning_ram3[df_warning_ram3['sn']==sn]
+            df_warning_ram_sn.reset_index(inplace=True,drop=True)     #重置索引
+            df_warning_ram_sn1.reset_index(inplace=True,drop=True)     #重置索引
+            df_warning_ram_sn2.reset_index(inplace=True,drop=True)     #重置索引
+            df_warning_ram_sn3.reset_index(inplace=True,drop=True)     #重置索引
+            if celltype>50:
+                df_lfp_ram=df_lfp_ram.reindex(columns=df_bms.columns.tolist()+['sn'])
+                df_lfp_ram_sn=df_lfp_ram[df_lfp_ram['sn']==sn]
+                df_lfp_ram_sn.reset_index(inplace=True,drop=True)     #重置索引
+            else:
+                df_lfp_ram_sn=pd.DataFrame()
+
+            BatShort=CBMSBatInterShort.BatInterShort(sn,celltype,df_bms,df_soh,df_warning_ram_sn,df_warning_ram_sn1,df_warning_ram_sn2,df_warning_ram_sn3,df_lfp_ram_sn)
+            df_short_res, df_ram_res, df_ram_res1, df_ram_res2, df_ram_res3, df_ram_res4=BatShort.intershort() 
+
+            if not df_short_res.empty:
+                with open(r'D:\Platform\platform_python\data_analyze_platform\USER\spf\01qixiang\07BatSafetyWarning\内短路.txt','a') as file:
+                    file.write(str(df_short_res)+'\n')
+
+            #内短路ram处理.........................................................
+            df_warning_ram=df_warning_ram.drop(df_warning_ram[df_warning_ram.sn==sn].index)
+            df_warning_ram1=df_warning_ram1.drop(df_warning_ram1[df_warning_ram1.sn==sn].index)
+            df_warning_ram2=df_warning_ram2.drop(df_warning_ram2[df_warning_ram2.sn==sn].index)
+            df_warning_ram3=df_warning_ram3.drop(df_warning_ram3[df_warning_ram3.sn==sn].index)
+
+            df_warning_ram=pd.concat([df_warning_ram,df_ram_res],ignore_index=True)
+            df_warning_ram1=pd.concat([df_warning_ram1,df_ram_res1],ignore_index=True)
+            df_warning_ram2=pd.concat([df_warning_ram2,df_ram_res2],ignore_index=True)
+            df_warning_ram3=pd.concat([df_warning_ram3,df_ram_res3],ignore_index=True)
+            
+            if celltype>50:
+                df_lfp_ram=df_lfp_ram.drop(df_lfp_ram[df_lfp_ram.sn==sn].index)
+                df_lfp_ram=pd.concat([df_lfp_ram,df_ram_res4],ignore_index=True)
+            
+
+        #电池热安全预警..............................................................................................................................................................
+        #读取内短路、析锂和一致性结果数据库数据
+        db='qx_cas'
+        mode=2
+        tablename1='cellstateestimation_intershort'
+        tablename2=''   #析锂表单
+        tablename3='cellstateestimation_uniform_socvoltdiff'
+        DBRead=DBDownload.DBDownload(host, port, db, user, password,mode)
+        with DBRead as DBRead:
+            df_short=DBRead.getdata('time_sp,sn,short_current', tablename=tablename1, sn=sn, timename='time_sp', st=start_time1, sp=end_time)
+            # df_liplated=DBRead.getdata('time,sn,liplated,lipltd_amount', tablename=tablename2, sn=sn, timename='time_sp', st=start_time2, sp=end_time)
+            df_uniform=DBRead.getdata('time,sn,cellsoc_diff,cellmin_num', tablename=tablename3, sn=sn, timename='time', st=start_time1, sp=end_time)
+            df_liplated=pd.DataFrame()
+        
+        #获取sn的故障RAM
+        df_fault_ram_sn=df_fault_ram[df_fault_ram['product_id']==sn]
+        
+        #热安全预警
+        BatWarning=CBMSSafetyWarning.SafetyWarning(sn,celltype,df_short,df_liplated,df_uniform,df_fault_ram_sn)
+        df_warning_res=BatWarning.diag()
+
+        df_warning_end=df_warning_res[df_warning_res['end_time'] != '0000-00-00 00:00:00']
+        if not df_warning_end.empty:    #df_warning_end历史故障筛选并更改数据库故障结束时间
+            pass   
+        elif df_fault_ram_sn.empty and (not df_warning_res.empty):
+            with open(r'D:\Platform\platform_python\data_analyze_platform\USER\spf\01qixiang\07BatSafetyWarning\热失控预警.txt','a') as file:
+                file.write(str(tuple(df_warning_res.iloc[-1]))+'\n')
+        else:
+            pass
+
+        
+        print(df_warning_ram)
+        print(df_warning_ram1)
+        print(df_warning_ram2)
+        print(df_warning_ram3)
+        print(df_lfp_ram)
+
+        end=time.time()
+        print(end-start)
+        # print(df_soh)
+
+#...............................................主函数起定时作用.......................................................................................................................
+if __name__ == "__main__":
+    
+    excelpath=r'D:\Platform\platform_python\data_analyze_platform\USER\spf\01qixiang\sn-20210903.xlsx'
+    SNdata_6060 = pd.read_excel(excelpath, sheet_name='科易6060')
+    SNdata_6040 = pd.read_excel(excelpath, sheet_name='科易6040')
+    SNdata_4840 = pd.read_excel(excelpath, sheet_name='科易4840')
+    SNdata_L7255 = pd.read_excel(excelpath, sheet_name='格林美-力信7255')
+    SNdata_C7255 = pd.read_excel(excelpath, sheet_name='格林美-CATL7255')
+    SNdata_U7255 = pd.read_excel(excelpath, sheet_name='优旦7255')
+    SNnums_6060=SNdata_6060['SN号'].tolist()
+    SNnums_6040=SNdata_6040['SN号'].tolist()
+    SNnums_4840=SNdata_4840['SN号'].tolist()
+    SNnums_L7255=SNdata_L7255['SN号'].tolist()
+    SNnums_C7255=SNdata_C7255['SN号'].tolist()
+    SNnums_U7255=SNdata_U7255['SN号'].tolist()
+    SNnums=SNnums_L7255 + SNnums_C7255 + SNnums_U7255, SNnums_6040 + SNnums_4840 + SNnums_6060
+    SNnums=['MGMCLN750N215N099','PK504B10100004425']
+    
+    mylog=log.Mylog('log_warning.txt','error')
+    mylog.logcfg()
+
+    #............................模块运行前，先读取数据库中所有结束时间为0的数据，需要从数据库中读取...................................
+    df_warning_ram=pd.DataFrame(columns=['sn','time','deltsoc','cellsoc'])
+    df_warning_ram1=pd.DataFrame(columns=['sn','time1','deltsoc1'])
+    df_warning_ram2=pd.DataFrame(columns=['sn','time2','deltAs2'])
+    df_warning_ram3=pd.DataFrame(columns=['sn','standingtime','standingtime1'])
+    df_lfp_ram=pd.DataFrame()
+
+    now_time='2021-10-16 00:00:00'
+    now_time=datetime.datetime.strptime(now_time,'%Y-%m-%d %H:%M:%S')
+
+    #定时任务.......................................................................................................................................................................
+    scheduler = BlockingScheduler()
+    scheduler.add_job(saftywarning_cal, 'interval', seconds=5)
+
+    try:  
+        scheduler.start()
+    except Exception as e:
+        scheduler.shutdown()
+        print(repr(e))
+        mylog.logopt(e)