data_analyze_platform/USER/SPF/alibaba/07BatSafetyWarning/CBMSBatInterShort.py

import pandas as pd
import numpy as np
import datetime
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_bms=pd.concat([df_lfp, df_bms], ignore_index=True)
            df_bms.reset_index(inplace=True,drop=True) 
        else:
            pass

        self.sn=sn
        self.celltype=celltype
        self.param=BatParam.BatParam(celltype)
        self.packcrnt=df_bms['PackCrnt']*self.param.PackCrntDec
        self.packvolt=df_bms['PackVolt']
        self.bms_soc=df_bms['PackSOC']
        df_bms['time']=pd.to_datetime(df_bms['time'], format='%Y-%m-%d %H:%M:%S')
        self.bmstime= df_bms['time']

        self.df_bms=df_bms
        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=['CellVolt'+str(x) for x in range(1,self.param.CellVoltNums+1)]
        self.celltemp_name=['CellTemp'+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=min(celltemp)
        self.celltemp=celltemp
        if self.celltype>50:
            if celltemp>=25:
                self.tempweight=1
                self.StandardStandingTime=4500
            elif celltemp>=15:
                self.tempweight=0.6
                self.StandardStandingTime=7200
            elif celltemp>=5:
                self.tempweight=0.2
                self.StandardStandingTime=10800
            else:
                self.tempweight=0.1
                self.StandardStandingTime=10800
        else:
            if celltemp>=25:
                self.tempweight=1
                self.StandardStandingTime=3600
            elif celltemp>=15:
                self.tempweight=0.8
                self.StandardStandingTime=5400
            elif celltemp>=5:
                self.tempweight=0.6
                self.StandardStandingTime=7200
            else:
                self.tempweight=0.2
                self.StandardStandingTime=10800

    #获取前5min每个电压的平均值........................................................................................
    def _avgvolt_get(self,num):
        time_now=self.df_bms.loc[num, 'time']
        time_last=time_now-datetime.timedelta(seconds=300)
        df_volt=self.df_bms[(self.df_bms['time']>=time_last) & (self.df_bms['time']<=time_now)]
        df_volt=df_volt[self.cellvolt_name]
        df_volt=df_volt[(df_volt>2) & (df_volt<4.5)]
        df_volt=df_volt.dropna()
        cellvolt_std=df_volt.std(axis=0)
        if len(df_volt)>2 and max(cellvolt_std)<0.005:
            cellvolt_sum=df_volt.sum(0)-df_volt.max(0)-df_volt.min(0)
            cellvolt_mean=cellvolt_sum/(len(df_volt)-2)
            cellvolt=cellvolt_mean
        elif len(df_volt)==2:
            # df_volt=pd.DataFrame(df_volt,dtype=np.float)
            if max(abs(df_volt.iloc[1]-df_volt.iloc[0]))<0.003:
                cellvolt=df_volt.mean(0)
            else:
                cellvolt=pd.DataFrame()
        elif len(df_volt)==1:
            cellvolt=df_volt.iloc[0]
        else:
            cellvolt=pd.DataFrame()
        return cellvolt

    #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])
        return cellvolt

    #获取当前行所有soc差...........................................................................................
    def _celldeltsoc_get(self,cellvolt_list,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=cellvolt_list[j-1]
            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)

        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,'CellVolt'+str(j)]>self.param.PeakCellVolt[symbol]:
                        As_tatol=As_tatol+As
                        symbol=symbol+1
                    else:
                        continue
                else:
                    cellAs.append(As_tatol/5)
                    break
        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):
        df_res=pd.DataFrame(columns=['time_st', 'time_sp', 'sn', 'method','short_current','baltime'])
        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,'PackSOH']
            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 df_ram_last.empty:
            firsttime=1
            dict_bal={}
        else:
            deltsoc_last=df_ram_last.loc[0,'deltsoc']
            cellsoc_last=df_ram_last.loc[0,'cellsoc']
            time_last=df_ram_last.loc[0,'time']
            firsttime=0
            dict_bal={}
        if df_ram_last1.empty:
            firsttime1=1
            dict_bal1={}
        else:
            deltsoc_last1=df_ram_last1.loc[0,'deltsoc1']
            time_last1=df_ram_last1.loc[0,'time1']
            firsttime1=0
            dict_bal1={}
        if df_ram_last3.empty:
            standingtime=0
            standingtime1=0
            standingtime2=0
        else:
            standingtime=df_ram_last3.loc[0,'standingtime']
            standingtime1=df_ram_last3.loc[0,'standingtime1']
            standingtime2=df_ram_last3.loc[0,'standingtime2']
            dict_bal1={}
            if abs(self.packcrnt[0])<0.01 and standingtime>1 and standingtime1>1:
                standingtime=standingtime+(self.bmstime[0]-df_ram_last3.loc[0,'time3']).total_seconds()
                standingtime1=standingtime1+(self.bmstime[0]-df_ram_last3.loc[0,'time3']).total_seconds()
            else:
                pass

        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._avgvolt_get(i)
                        if not cellvolt_now.empty:
                            cellvolt_min=min(cellvolt_now)
                            cellvolt_max=max(cellvolt_now)
                            # cellvolt_last=self._avgvolt_get(i-1)
                            # deltvolt=max(abs(cellvolt_now-cellvolt_last))
                            cellsoc_max=np.interp(cellvolt_max,self.param.LookTab_OCV,self.param.LookTab_SOC)
                            cellsoc_min=np.interp(cellvolt_min,self.param.LookTab_OCV,self.param.LookTab_SOC)

                            if 2<cellvolt_min<4.5 and 2<cellvolt_max<4.5 and (45<cellsoc_max or cellsoc_max<30) and (45<cellsoc_min or cellsoc_min<30):
                                dict_baltime={}   #获取每个电芯的均衡时间
                                deltsoc_last, cellsoc_last=self._celldeltsoc_get(cellvolt_now,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*12:
                    standingtime=0
                    cellvolt_now=self._avgvolt_get(i)
                    if not cellvolt_now.empty:
                        cellvolt_min=min(cellvolt_now)
                        cellvolt_max=max(cellvolt_now)
                        # cellvolt_last=self._avgvolt_get(i-1)
                        # deltvolt=max(abs(cellvolt_now-cellvolt_last))
                        cellsoc_max=np.interp(cellvolt_max,self.param.LookTab_OCV,self.param.LookTab_SOC)
                        cellsoc_min=np.interp(cellvolt_min,self.param.LookTab_OCV,self.param.LookTab_SOC)

                        if 2<cellvolt_min<4.5 and 2<cellvolt_max<4.5 and (45<cellsoc_max or cellsoc_max<30) and (45<cellsoc_min or cellsoc_min<30):
                            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(cellvolt_now,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._avgvolt_get(i)
                    if not cellvolt_now1.empty:
                        cellvolt_max1=max(cellvolt_now1)
                        cellvolt_min1=min(cellvolt_now1)
                        # cellvolt_last1=self._avgvolt_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:
                            if firsttime1==1:
                                dict_baltime1={}   #获取每个电芯的均衡时间
                                deltsoc_last1, cellsoc_last1=self._celldeltsoc_get(cellvolt_now1,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*20:
                                    deltsoc_now1, cellsoc_now1=self._celldeltsoc_get(cellvolt_now1,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,self.bmstime[len(self.bmstime)-1],standingtime,standingtime1,standingtime2]

        #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,'PackSOH']
            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 df_ram_last.empty:
            firsttime=1
            dict_bal={}
        else:
            deltsoc_last=df_ram_last.loc[0,'deltsoc']
            cellsoc_last=df_ram_last.loc[0,'cellsoc']
            time_last=df_ram_last.loc[0,'time']
            firsttime=0
            dict_bal={}
        if df_ram_last1.empty:
            firsttime1=1
            dict_bal1={}
        else:
            deltsoc_last1=df_ram_last1.loc[0,'deltsoc1']
            time_last1=df_ram_last1.loc[0,'time1']
            firsttime1=0
            dict_bal1={}
        if df_ram_last2.empty:
            firsttime2=1
            charging=0
            dict_bal2={}
        else:
            deltAs_last2=df_ram_last2.loc[0,'deltAs2']
            time_last2=df_ram_last2.loc[0,'time2']
            firsttime2=0
            charging=0
            dict_bal2={}
        if df_ram_last3.empty:
            standingtime=0
            standingtime1=0
            standingtime2=0
        else:
            standingtime=df_ram_last3.loc[0,'standingtime']
            standingtime1=df_ram_last3.loc[0,'standingtime1']
            standingtime2=df_ram_last3.loc[0,'standingtime2']
            dict_bal1={}
            if abs(self.packcrnt[0])<0.01 and standingtime>1 and standingtime1>1:
                standingtime=standingtime+(self.bmstime[0]-df_ram_last3.loc[0,'time3']).total_seconds()
                standingtime1=standingtime1+(self.bmstime[0]-df_ram_last3.loc[0,'time3']).total_seconds()
            else:
                pass

        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:
                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
                        cellvolt_now=self._avgvolt_get(i)
                        if not cellvolt_now.empty:
                            standingtime=0
                            cellvolt_min=min(cellvolt_now)
                            cellvolt_max=max(cellvolt_now)
                            # cellvolt_last=self._avgvolt_get(i-1)
                            # deltvolt=max(abs(cellvolt_now-cellvolt_last))
                            cellsoc_max=np.interp(cellvolt_max,self.param.LookTab_OCV,self.param.LookTab_SOC)
                            cellsoc_min=np.interp(cellvolt_min,self.param.LookTab_OCV,self.param.LookTab_SOC)

                            if cellsoc_max<self.param.SocInflexion1-2 and 12<cellsoc_min:
                                dict_baltime={}  #获取每个电芯的均衡时间
                                deltsoc_last, cellsoc_last=self._celldeltsoc_get(cellvolt_now,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*12:
                    cellvolt_now=np.array(self._avgvolt_get(i))
                    if not cellvolt_now.empty:
                        standingtime=0
                        cellvolt_min=min(cellvolt_now)
                        cellvolt_max=max(cellvolt_now)
                        # cellvolt_last=np.array(self._avgvolt_get(i-1))
                        # deltvolt=max(abs(cellvolt_now-cellvolt_last))
                        cellsoc_max=np.interp(cellvolt_max,self.param.LookTab_OCV,self.param.LookTab_SOC)
                        cellsoc_min=np.interp(cellvolt_min,self.param.LookTab_OCV,self.param.LookTab_SOC)

                        if cellsoc_max<self.param.SocInflexion1-2 and 12<cellsoc_min:
                            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(cellvolt_now, 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:
                    cellvolt_now1=self._avgvolt_get(i)
                    if not cellvolt_now1.empty:
                        standingtime1=0
                        cellvolt_max1=max(cellvolt_now1)
                        cellvolt_min1=min(cellvolt_now1)
                        # cellvolt_last1=self._avgvolt_get(i-1)
                        # deltvolt1=max(abs(cellvolt_now1-cellvolt_last1))
                        cellsoc_max1=np.interp(cellvolt_max1,self.param.LookTab_OCV,self.param.LookTab_SOC)
                        cellsoc_min1=np.interp(cellvolt_min1,self.param.LookTab_OCV,self.param.LookTab_SOC)

                        if cellsoc_max1<self.param.SocInflexion1-2 and 1<cellsoc_min1:
                            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(cellvolt_now1,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(cellvolt_now1,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*24:
                                    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

            if i==len(self.df_bms)-2 and abs(self.packcrnt[i+1]) < 0.1:  #数据中断后仍在静置，将最后一条数据写入RAM
                df_ram_lfp.loc[0]=self.df_bms.iloc[-1]
            else:
                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 charging==0:
                if self.packcrnt[i]<=-1 and self.packcrnt[i+1]<=-1 and self.packcrnt[i-1]<=-1:
                    if self.bms_soc[i]<40:
                        cellvolt_now=self._cellvolt_get(i)
                        if min(cellvolt_now)<self.param.CellFullChrgVolt-0.17:
                            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]>-0.1 and self.packcrnt[i-1]>-0.1) or (self.packcrnt[i]<-self.param.Capacity and self.packcrnt[i+1]<-self.param.Capacity):  #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-0.1:   
                    self._celltemp_weight(i)
                    if i-chrg_start>10 and self.celltemp>20:
                        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


        #更新RAM
        df_ram_last3.loc[0]=[self.sn,self.bmstime[len(self.bmstime)-1],standingtime,standingtime1,standingtime2]

        #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