data_analyze_platform/USER/SPF/alibaba/04BatSoc/CBMSBatSoc.py

import pandas as pd
import numpy as np
from scipy.interpolate import interp2d
import BatParam
import datetime

class BatSoc():
    def __init__(self,sn,celltype,df_bms,df_soh,df_ram_sn,df_socdiff):  #参数初始化

        self.sn=sn
        self.celltype=celltype
        self.param=BatParam.BatParam(celltype)
        self.df_soh=df_soh
        self.df_socdiff=df_socdiff
        self.df_ram_sn=df_ram_sn
        df_bms['time']=pd.to_datetime(df_bms['time'], format='%Y-%m-%d %H:%M:%S')
        self.df_bms=df_bms

        if not self.df_ram_sn.empty:
            self.df_bms=self.df_bms[self.df_bms['time'] > self.df_ram_sn.iloc[-1]['time']]    #滤除原始数据中的重复数据
            self.df_bms.reset_index(inplace=True,drop=True)     #重置索引
        self.packcrnt=df_bms['PackCrnt']*self.param.PackCrntDec
        self.bms_soc=df_bms['PackSOC']
        self.bms_soh=df_bms['PackSOH']
        self.bmstime= pd.to_datetime(df_bms['time'], format='%Y-%m-%d %H:%M:%S')

        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 batsoc(self):
        if self.celltype<50:
            if not self.df_bms.empty:
                df_res, df_ram=self._ncm_soc()
                return df_res, df_ram
            else:
                return pd.DataFrame(), pd.DataFrame()

        elif self.celltype>50:
            if not self.df_bms.empty:
                df_res, df_ram=self._lfp_soc()
                return df_res, df_ram
            else:
                return pd.DataFrame(), pd.DataFrame()

        else:
            return pd.DataFrame()

    #........................................................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=18000
        else:
            if celltemp>=20:
                self.tempweight=1
                self.StandardStandingTime=1800
            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])
        return cellvolt

    #......................................................判断单体电压离散度,并返回OCV值....................................................................................
    def _ocv_dispersion(self):

        cellvolt=self.df_bms[self.cellvolt_name]
        cellocv=cellvolt.mean(axis=0)
        cellocv_std=cellvolt.std(axis=0)
        cellocv_std=cellocv_std.fillna(0)
        if max(cellocv_std)<0.002:
            return np.array(cellocv)
        else:
            return [0]

    #...........................................................三元电池的soc计算...............................................................................................
    def _ncm_soc(self):
        column_name=['time', 'sn', 'bms_soc', 'packsoc', 'socdsp', 'cellsocmin', 'cellsocmax','socmin_num','socmax_num','cellsoc_diff','cellsoc','ocvweight','socstep']
        df_res=pd.DataFrame(columns=column_name)
        df_bms_len=len(self.df_bms)
        rampackcrnt=self.packcrnt[df_bms_len-1]
        ocvweight=0

        #获取电池包SOH................................................................................................
        if self.df_soh.empty:
            batsoh=self.bms_soh[0]
            if batsoh>30:
                capacity=self.param.Capacity*batsoh/100
            else:
                capacity=self.param.Capacity
        else:
            batsoh=eval(self.df_soh.loc[0,'cellsoh'])
            batsoh=np.array(batsoh)
            capacity=self.param.Capacity*batsoh/100

        #计算静置时间和累计As量..................................................................................................
        if not self.df_ram_sn.empty:
            standingtime=self.df_ram_sn.iloc[-1]['standingtime']
            as_accum=0
            for i in range(df_bms_len):
                if i==0:
                    step=(self.bmstime[i]-self.df_ram_sn.iloc[-1]['time']).total_seconds()
                    if abs(self.packcrnt[i])<0.1 and abs(self.df_ram_sn.iloc[-1]['rampackcrnt'])<0.1:
                        standingtime=standingtime+step
                    else:
                        standingtime=0
                        if step<120:
                            as_accum=as_accum-self.packcrnt[i]*step
                        else:
                            as_accum=as_accum+((self.bms_soc[i]-self.df_ram_sn.iloc[-1]['bms_soc'])*capacity*3600/100)
                else:
                    step=(self.bmstime[i]-self.bmstime[i-1]).total_seconds()
                    if abs(self.packcrnt[i])<0.1 and abs(self.packcrnt[i-1])<0.1:
                        standingtime=standingtime+step
                        as_accum=as_accum-self.packcrnt[i]*step
                    else:
                        standingtime=0
                        as_accum=as_accum-self.packcrnt[i]*step
        else:
            standingtime=0
            as_accum=0
            for i in range(df_bms_len):
                if i==0:
                    pass
                else:
                    step=(self.bmstime[i]-self.bmstime[i-1]).total_seconds()
                    if abs(self.packcrnt[i])<0.1 and abs(self.packcrnt[i-1])<0.1:
                        standingtime=standingtime+step
                        as_accum=as_accum-self.packcrnt[i]*step
                    else:
                        standingtime=0
                        as_accum=as_accum-self.packcrnt[i]*step

        if standingtime>3600*24*30:
            standingtime=3600*24*30
        else:
            pass

        #计算单体SOC.............................................................................................................................
        if not self.df_ram_sn.empty:
            self._celltemp_weight(0)
            ramcellvolt=self.df_ram_sn.iloc[-1]['ramcellvolt']
            ramcellsoc=self.df_ram_sn.iloc[-1]['cellsoc']
            ocvweight_2dlook=interp2d(self.param.OcvWeight_StandingTime, self.param.OcvWeight_Temp, self.param.OcvWeight, kind = 'linear')
            ocvweight=ocvweight_2dlook(standingtime, self.celltemp)
            ocvweight=ocvweight[0]

            if self.bmstime[0]>datetime.datetime.strptime('2021-10-22 19:49:20','%Y-%m-%d %H:%M:%S'):
                pass


            if ocvweight>0.01:
                cellocv=self._ocv_dispersion()

                if df_bms_len>1:      #数据字段长度≥2
                    if 2<max(cellocv)<4.5 and 2<min(cellocv)<4.5:
                        ocvsoc=np.array(list(map(lambda x:np.interp(x,self.param.LookTab_OCV,self.param.LookTab_SOC),cellocv)))
                        cellsoc=ocvsoc*ocvweight+ramcellsoc*(1-ocvweight)
                        socstep=0
                    else:
                        cellsoc=ramcellsoc
                        socstep=1
                else:       #数据字段长度==1
                    if 2<max(cellocv)<4.5 and 2<min(cellocv)<4.5 and max(abs(ramcellvolt-np.array(cellocv)))<0.004:
                        ocvsoc=np.array(list(map(lambda x:np.interp(x,self.param.LookTab_OCV,self.param.LookTab_SOC),cellocv)))
                        cellsoc=ocvsoc*ocvweight+ramcellsoc*(1-ocvweight)
                        socstep=2
                    else:
                        cellsoc=ramcellsoc
                        socstep=3

            else:
                cellsoc=ramcellsoc+(as_accum*100)/(3600*capacity)
                socstep=4


        else:
            cellsoc= np.array([self.bms_soc[df_bms_len-1]])+np.random.rand(self.param.CellVoltNums)
            socstep=5

        #更新ram电芯电压
        ramcellvolt=self._cellvolt_get(df_bms_len-1)

        #单体Soc满充修正........................................................................................................................................................................
        cellvoltall=self.df_bms[self.cellvolt_name] #筛选所有单体电压
        cellvoltall_min=cellvoltall.min(axis=0) #每一个单体电芯的最小值
        if self.param.CellFullChrgVolt<max(cellvoltall_min)<5 and self.param.CellFullChrgVolt<max(cellvoltall_min)<5 and min(self.packcrnt)>self.param.CellFullChrgCrnt and max(self.packcrnt)<-0.5:
            deltsoc=self.param.FullChrgSoc-max(cellsoc)
            cellsoc=cellsoc+deltsoc
        else:
            pass

        #计算电池包packsoc和最大最小SOC..................................................................................................................................................................................
        cellsoc[cellsoc>100]=100    #限值最大值100
        cellsoc[cellsoc<0]=0    #限值最小值0
        cellsoc1=list(map(lambda x:float(format(x,'.1f')), cellsoc))

        cellsocmin=min(cellsoc1)
        cellsocmax=max(cellsoc1)
        cellsoc_diff=cellsocmax-cellsocmin
        socmin_num=cellsoc1.index(cellsocmin)+1
        socmax_num=cellsoc1.index(cellsocmax)+1
        alpha=(cellsocmin+cellsocmax)*0.02-2    #blending系数计算
        if cellsocmax>90 or alpha>1:
            alpha=1
        elif cellsocmin<10 or alpha<-1:
            alpha=-1
        else:
            pass
        packsoc=(cellsocmin+cellsocmax)*0.5+(cellsocmax-cellsocmin)*0.5*alpha
        packsoc=eval(format(packsoc,'.1f'))
        socdsp=packsoc

        #输出ram结果....................................................................................................................................................................
        list_ram=[self.bmstime[df_bms_len-1], self.sn, self.bms_soc[df_bms_len-1], packsoc, cellsoc, standingtime, rampackcrnt, ramcellvolt,0,0,ocvweight,as_accum,socstep]
        df_ram=pd.DataFrame(columns=self.df_ram_sn.columns)
        df_ram.loc[0]=list_ram

        #输出计算结果........................................................................................................................................................................
        df_res.loc[0]=[self.bmstime[df_bms_len-1], self.sn, self.bms_soc[df_bms_len-1], packsoc, socdsp, cellsocmin, cellsocmax,socmin_num,socmax_num,cellsoc_diff,str(cellsoc1),ocvweight,socstep]
        return df_res, df_ram

    #...........................................................磷酸铁锂电池的soc计算...............................................................................................
    def _lfp_soc(self):
        column_name=['time', 'sn', 'bms_soc', 'packsoc', 'socdsp', 'cellsocmin', 'cellsocmax','socmin_num','socmax_num','cellsoc_diff','cellsoc','ocvweight','socstep']
        df_res=pd.DataFrame(columns=column_name)
        df_bms_len=len(self.df_bms)
        rampackcrnt=self.packcrnt[df_bms_len-1]
        if not self.df_socdiff.empty:
            cellsoc_diff=self.df_socdiff.iloc[-1]['cellsoc_diff']
        else:
            cellsoc_diff=2

        #获取电池包SOH................................................................................................
        if self.df_soh.empty:
            batsoh=self.bms_soh[0]
            capacity=self.param.Capacity*batsoh/100
        else:
            batsoh=self.df_soh.loc[0,'soh']
            capacity=self.param.Capacity*batsoh/100

        #计算静置时间和累计As量以及OCV权重值..................................................................................................
        if not self.df_ram_sn.empty:
            standingtime=self.df_ram_sn.iloc[-1]['standingtime']
            ocvweight=self.df_ram_sn.iloc[-1]['ocvweight']
            as_accum=0
            for i in range(df_bms_len):
                if i==0:
                    step=(self.bmstime[i]-self.df_ram_sn.iloc[-1]['time']).total_seconds()
                    if abs(self.packcrnt[i])<0.1 and abs(self.df_ram_sn.iloc[-1]['rampackcrnt'])<0.1:
                        standingtime=standingtime+step
                    else:
                        standingtime=0
                        if step<120:
                            as_accum=as_accum-self.packcrnt[i]*step
                        else:
                            as_accum=as_accum+((self.bms_soc[i]-self.df_ram_sn.iloc[-1]['bms_soc'])*capacity*3600/100)
                else:
                    step=(self.bmstime[i]-self.bmstime[i-1]).total_seconds()
                    if abs(self.packcrnt[i])<0.1 and abs(self.packcrnt[i-1])<0.1:
                        standingtime=standingtime+step
                        as_accum=as_accum-self.packcrnt[i]*step
                    else:
                        standingtime=0
                        as_accum=as_accum-self.packcrnt[i]*step

        else:
            standingtime=0
            ocvweight=0.5
            as_accum=0
            for i in range(df_bms_len):
                if i==0:
                    pass
                else:
                    step=(self.bmstime[i]-self.bmstime[i-1]).total_seconds()
                    if abs(self.packcrnt[i])<0.1 and abs(self.packcrnt[i-1])<0.1:
                        standingtime=standingtime+step
                        as_accum=as_accum-self.packcrnt[i]*step
                    else:
                        standingtime=0
                        as_accum=as_accum-self.packcrnt[i]*step

        #静置时间限值..............................................
        if standingtime>3600*24*30:
            standingtime=3600*24*30
        else:
            pass

        #权重值计算.................................................
        ocvweight=ocvweight-as_accum*10/(capacity*3600)
        if ocvweight>1:
            ocvweight=1
        elif ocvweight<0:
            ocvweight=0
        else:
            pass
        ocvweight=eval(format(ocvweight,'.2f'))

        #计算单体最大最小SOC.............................................................................................................................
        cellocv=self._ocv_dispersion()  #获取每一列电压的平均值
        if not self.df_ram_sn.empty:
            self._celltemp_weight(0)
            kocellvoltmin=self.df_ram_sn.iloc[-1]['kocellvoltmin']
            kocellvoltmax=self.df_ram_sn.iloc[-1]['kocellvoltmax']
            ramcellsoc=self.df_ram_sn.iloc[-1]['cellsoc']
            #满足静置时间
            if standingtime>self.StandardStandingTime:
                #数据字段长度≥2...............................................................................................................
                if df_bms_len>1:
                    ocvsocmin=np.interp(min(cellocv),self.param.LookTab_OCV,self.param.LookTab_SOC)
                    ocvsocmax=np.interp(max(cellocv),self.param.LookTab_OCV,self.param.LookTab_SOC)
                    if 2<min(cellocv)<self.param.OcvInflexionBelow and 2<max(cellocv)<self.param.OcvInflexionBelow and ocvsocmax<self.param.SocInflexion1:
                        cellsocmin=ocvsocmin
                        cellsocmax=ocvsocmax
                        socstep=0
                    elif 2<min(cellocv)<self.param.OcvInflexionBelow and max(cellocv)>=self.param.OcvInflexionBelow and ocvsocmin<self.param.SocInflexion1:
                        cellsocmin=ocvsocmin
                        cellsocmax=ocvsocmin+cellsoc_diff
                        socstep=1
                    else:
                        #第一平台向第二平台修正
                        if ocvsocmax>self.param.SocInflexion3+5 and max(ramcellsoc)<self.param.SocInflexion2-5:
                            if  ocvsocmin>self.param.SocInflexion3+5 and min(ramcellsoc)<self.param.SocInflexion2-5:
                                cellsocmin=self.param.SocInflexion3
                                cellsocmax=cellsocmin+cellsoc_diff
                                socstep=2
                            else:
                                cellsocmax=self.param.SocInflexion3
                                cellsocmin=cellsocmax-cellsoc_diff
                                socstep=3
                        #第一非平台区向第一平台区修正
                        elif ocvsocmax>self.param.SocInflexion1+5 and max(ramcellsoc)<self.param.SocInflexion1-2:
                            if ocvsocmin>self.param.SocInflexion1+5 and min(ramcellsoc)<self.param.SocInflexion1-2:
                                cellsocmin=self.param.SocInflexion1
                                cellsocmax=cellsocmin+cellsoc_diff
                                socstep=4
                            else:
                                cellsocmax=self.param.SocInflexion1
                                cellsocmin=cellsocmax-cellsoc_diff
                                socstep=5
                        #第二平台区向第一平台区修正
                        elif ocvsocmin<self.param.SocInflexion2-5 and min(ramcellsoc)>self.param.SocInflexion3+5:
                            if ocvsocmax<self.param.SocInflexion2-5 and max(ramcellsoc)>self.param.SocInflexion3+5:
                                cellsocmax=self.param.SocInflexion2
                                cellsocmin=cellsocmax-cellsoc_diff
                                socstep=6
                            else:
                                cellsocmin=self.param.SocInflexion2
                                cellsocmax=cellsocmin+cellsoc_diff
                                socstep=7
                        else:
                            cellsoc=ramcellsoc
                            socstep=8
                #数据字段长度==1..............................................................................................
                else:
                    cellvolt0=self._cellvolt_get(0)
                    ramcellvolt=self.df_ram_sn.iloc[-1]['ramcellvolt']
                    if max(abs(cellvolt0-ramcellvolt))<0.004:
                        ocvmax=max(cellvolt0)
                        ocvmin=min(cellvolt0)
                        ocvsocmin=np.interp(ocvmin,self.param.LookTab_OCV,self.param.LookTab_SOC)
                        ocvsocmax=np.interp(ocvmax,self.param.LookTab_OCV,self.param.LookTab_SOC)
                        if 2<ocvmin<self.param.OcvInflexionBelow and 2<ocvmax<self.param.OcvInflexionBelow and ocvsocmax<self.param.SocInflexion1:
                            cellsocmin=ocvsocmin
                            cellsocmax=ocvsocmax
                            socstep=9
                        elif 2<ocvmin<self.param.OcvInflexionBelow and ocvmax>=self.param.OcvInflexionBelow and ocvsocmin<self.param.SocInflexion1:
                            cellsocmin=ocvsocmin
                            cellsocmax=ocvsocmin+cellsoc_diff
                            socstep=10
                        else:
                            #第一平台向第二平台修正
                            if ocvsocmax>self.param.SocInflexion3+5 and max(ramcellsoc)<self.param.SocInflexion2-5:
                                if  ocvsocmin>self.param.SocInflexion3+5 and min(ramcellsoc)<self.param.SocInflexion2-5:
                                    cellsocmin=self.param.SocInflexion3
                                    cellsocmax=cellsocmin+cellsoc_diff
                                    socstep=11
                                else:
                                    cellsocmax=self.param.SocInflexion3
                                    cellsocmin=cellsocmax-cellsoc_diff
                                    socstep=12
                            #第一非平台区向第一平台区修正
                            elif ocvsocmax>self.param.SocInflexion1+5 and max(ramcellsoc)<self.param.SocInflexion1-2:
                                if ocvsocmin>self.param.SocInflexion1+5 and min(ramcellsoc)<self.param.SocInflexion1-2:
                                    cellsocmin=self.param.SocInflexion1
                                    cellsocmax=cellsocmin+cellsoc_diff
                                    socstep=13
                                else:
                                    cellsocmax=self.param.SocInflexion1
                                    cellsocmin=cellsocmax-cellsoc_diff
                                    socstep=14
                            #第二平台区向第一平台区修正
                            elif ocvsocmin<self.param.SocInflexion2-5 and min(ramcellsoc)>self.param.SocInflexion3+5:
                                if ocvsocmax<self.param.SocInflexion2-5 and max(ramcellsoc)>self.param.SocInflexion3+5:
                                    cellsocmax=self.param.SocInflexion2
                                    cellsocmin=cellsocmax-cellsoc_diff
                                    socstep=15
                                else:
                                    cellsocmin=self.param.SocInflexion2
                                    cellsocmax=cellsocmin+cellsoc_diff
                                    socstep=16
                            else:
                                cellsoc=ramcellsoc
                                socstep=17
                    else:
                        cellsoc=ramcellsoc
                        socstep=17
            #不满足静置时间，判断电压回弹方向
            elif standingtime>130 and 2<kocellvoltmax<4.5 and 2<kocellvoltmin<4.5:
                cellvoltmin=min(cellocv)
                cellvoltmax=max(cellocv)
                ocvsocmin1=np.interp(cellvoltmin,self.param.LookTab_OCV,self.param.LookTab_SOC)
                ocvsocmax1=np.interp(cellvoltmax,self.param.LookTab_OCV,self.param.LookTab_SOC)
                #最大最小电压向上回弹
                if 2<cellvoltmin<4.5 and cellvoltmin>kocellvoltmin+0.005 and ocvsocmin1>min(ramcellsoc):
                    if 2<cellvoltmax<4.5 and cellvoltmax>kocellvoltmax+0.005 and ocvsocmax1>max(ramcellsoc):
                        #最大最小电压均在非平台区
                        if ocvsocmax1<self.param.SocInflexion1:
                            cellsocmin=ocvsocmin1
                            cellsocmax=ocvsocmax1
                            socstep=18
                        #最小电压均在非平台区，最大电压在平台区
                        elif ocvsocmin1<self.param.SocInflexion1:
                            cellsocmin=ocvsocmin1
                            cellsocmax=cellsocmin+cellsoc_diff
                            socstep=19
                        #最大最小电压均在平台区，ramsoc在非平台区
                        elif ocvsocmin1>self.param.SocInflexion1+5 and max(ramcellsoc)<self.param.SocInflexion1 and min(ramcellsoc)<self.param.SocInflexion1:
                            cellsocmin=self.param.SocInflexion1
                            cellsocmax=cellsocmin+cellsoc_diff
                            socstep=20
                        else:
                            cellsoc=ramcellsoc
                            socstep=21
                    else:
                        cellsoc=ramcellsoc
                        socstep=22
                #最大最小电压向下回弹
                elif 2<cellvoltmin<4.5 and cellvoltmin<kocellvoltmin-0.005 and ocvsocmin1<min(ramcellsoc):
                    if 2<cellvoltmax<4.5 and cellvoltmax<kocellvoltmax-0.005 and ocvsocmax1>max(ramcellsoc):
                        #最大最小电压均在非平台区
                        if ocvsocmax1<self.param.SocInflexion1:
                            cellsocmin=ocvsocmin1
                            cellsocmax=ocvsocmax1
                            socstep=23
                        #最小电压在非平台区，最大电压在平台区
                        elif ocvsocmin1<self.param.SocInflexion1:
                            cellsocmin=ocvsocmin1
                            cellsocmax=cellsocmin+cellsoc_diff
                            socstep=24
                        else:
                            cellsoc=ramcellsoc
                            socstep=25
                    else:
                        cellsoc=ramcellsoc
                        socstep=26
                #电压回弹方向一致
                else:
                    cellsoc=ramcellsoc
                    socstep=27

            #更新ko电压
            elif 70<standingtime<=130:
                cellsoc=ramcellsoc
                socstep=28
                cellvolt=self._cellvolt_get(df_bms_len-1)
                kocellvoltmin=min(cellvolt)
                kocellvoltmax=max(cellvolt)

            else:
                cellsoc=ramcellsoc+(as_accum*100)/(3600*capacity)
                socstep=29
                #更新ko电芯电压
                kocellvoltmin=0
                kocellvoltmax=0

        else:
            cellsocmin= self.bms_soc[df_bms_len-1]-cellsoc_diff/2
            cellsocmax= self.bms_soc[df_bms_len-1]+cellsoc_diff/2
            socstep=30
            #更新ko电芯电压
            kocellvoltmin=0
            kocellvoltmax=0

        #更新Ram电压.................
        ramcellvolt=self._cellvolt_get(df_bms_len-1)

        #单体Soc满充修正........................................................................................................................................................................
        cellvoltall=self.df_bms[self.cellvolt_name] #筛选所有单体电压
        cellvoltall_min=cellvoltall.min(axis=0) #每一个单体电芯的最小值
        if self.param.CellFullChrgVolt<max(cellvoltall_min)<5 and self.param.CellFullChrgVolt<max(cellvoltall_min)<5 and min(self.packcrnt)>self.param.CellFullChrgCrnt and max(self.packcrnt)<-0.5:
            deltsoc=self.param.FullChrgSoc-max(cellsoc)
            cellsoc=cellsoc+deltsoc
        else:
            pass

        #计算所有电芯SOC...........................................................................................
        if not socstep in [8,17,21,22,25,26,27,28,29]:
            looktab_ocv=[min(cellocv),max(cellocv)]
            looktab_soc=[cellsocmin,cellsocmax]
            cellsoc=np.array(list(map(lambda x:np.interp(x,looktab_ocv,looktab_soc),cellocv)))
        else:
            pass

        #计算电池包packsoc和最大最小SOC..................................................................................................................................................................................
        cellsoc[cellsoc>100]=100    #限值最大值100
        cellsoc[cellsoc<0]=0    #限值最小值0
        cellsoc1=list(map(lambda x:eval(format(x,'.1f')), cellsoc))

        cellsocmin=min(cellsoc1)
        cellsocmax=max(cellsoc1)
        cellsoc_diff=cellsocmax-cellsocmin
        socmin_num=cellsoc1.index(cellsocmin)+1
        socmax_num=cellsoc1.index(cellsocmax)+1

        alpha=(cellsocmin+cellsocmax)*0.02-2    #blending系数计算
        if cellsocmax>90 or alpha>1:
            alpha=1
        elif cellsocmin<10 or alpha<-1:
            alpha=-1
        else:
            pass
        packsoc=(cellsocmin+cellsocmax)*0.5+(cellsocmax-cellsocmin)*0.5*alpha
        packsoc=eval(format(packsoc,'.1f'))
        socdsp=packsoc

        #输出ram结果....................................................................................................................................................................
        list_ram=[self.bmstime[df_bms_len-1], self.sn, self.bms_soc[df_bms_len-1], packsoc, cellsoc, standingtime, rampackcrnt, ramcellvolt,kocellvoltmin,kocellvoltmax,ocvweight,as_accum,socstep]
        df_ram=pd.DataFrame(columns=self.df_ram_sn.columns)
        df_ram.loc[0]=list_ram

        #输出计算结果........................................................................................................................................................................
        df_res.loc[0]=[self.bmstime[df_bms_len-1], self.sn, self.bms_soc[df_bms_len-1], packsoc, socdsp, cellsocmin, cellsocmax,socmin_num,socmax_num,cellsoc_diff,str(cellsoc1),ocvweight,socstep]
        return df_res, df_ram