data_analyze_platform/USER/SPF/01qixiang/05BatDiag/CBMSBatDiag.py

import pandas as pd
import numpy as np
import datetime
from LIB.MIDDLE.CellStateEstimation.Common.V1_0_1 import BatParam

class BatDiag:
    def __init__(self,sn,celltype,df_bms,df_soh,df_uniform,df_diag_Ram):  #参数初始化

        self.sn=sn
        self.celltype=celltype
        self.param=BatParam.BatParam(celltype)
        self.df_bms=df_bms
        self.df_soh=df_soh
        self.df_uniform=df_uniform
        self.df_diag_ram=df_diag_Ram
        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.bmsfault1=self.df_bms['故障代码']
        # self.bmsfault2=self.df_bms['alarm2'].tolist()
        # self.bmsfault3=self.df_bms['alarm3'].tolist()
        # self.bmsfault4=self.df_bms['fault'].tolist()

        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 diag(self):
        if self.celltype<=50:
            df_res=self._ncm_diag()
            return df_res    
        else:
            df_res=self._ncm_diag()
            return df_res
        

    #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))
    
    #寻找当前行数据的所有温度值...................................................................................
    def _celltemp_get(self,num):   
        celltemp = list(self.df_bms.loc[num,self.celltemp_name])
        return celltemp

    #获取当前行所有电压数据............................................................................................
    def _cellvolt_get(self,num): 
        cellvolt = list(self.df_bms.loc[num,self.cellvolt_name]/1000)
        return cellvolt

    #..........................................三元电池诊断功能..................................................................
    def _ncm_diag(self):

        bmssoc_st=float(self.bms_soc[0])    #SOC卡滞初始参数
        ah_accum=0  #SOC卡滞初始参数
        as_chg=0    #过流诊断初始参数
        as_dis=0    #过流诊断初始参数
        # time1=self.bmstime[0]   #温升速率初始参数
        # temp1=np.array(self._celltemp_get(0))   #温升速率初始参数
        # temprate_cnt=0
        ot_time=0
        ut_time=0
        dt_time=0
        cov_time=0
        cuv_time=0
        cdv_time=0
        pov_time=0
        puv_time=0
        
        end_time='0000-00-00 00:00:00'
            
        for i in range(1,len(self.df_bms)):
            
            #温度诊断功能.............................................................................................................
            celltemp0=self._celltemp_get(i-1)
            celltemp1=self._celltemp_get(i)
            celltempmin0=min(celltemp0)
            celltempmin1=min(celltemp1)
            celltempmax0=max(celltemp0)
            celltempmax1=max(celltemp1)
            #温度有效性判断..........................................................................
            if celltempmax0>self.param.CellTempUpLmt or celltempmin0<self.param.CellTempLwLmt:
                celltempvalid=0
            else:  
                celltempvalid=1
           
            if celltempvalid==1:
                #过温判断.............................................................................................................
                if not 4 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 celltempmax0>self.param.CellTempHighLv2 and celltempmax1>self.param.CellTempHighLv2:    #二级高温进入
                        ot_time=ot_time+(self.bmstime[i]-self.bmstime[i-1]).total_seconds()
                        if ot_time>self.param.temp_time:
                            time=self.bmstime[i]
                            code=4
                            faultlv=3
                            faultinfo='温度{}高温二级'.format(celltemp1.index(celltempmax1)+1)
                            faultadvice='技术介入诊断'
                            self.df_diag_ram.loc[len(self.df_diag_ram)]=[time, end_time, self.sn, code, faultlv, faultinfo, faultadvice]
                        else:
                            pass
                    else:
                        ot_time=0
                else:   #ram当前故障中有该故障，则判断是否退出该故障
                    if celltempmax0<self.param.CellTempHighLv1-5 and celltempmax1<self.param.CellTempHighLv1-5:    #二级高温恢复
                        time=self.bmstime[i]
                        self.df_diag_ram.loc[self.df_diag_ram[self.df_diag_ram['code']==4].index, 'end_time'] = time
                    else:
                        pass
            
                #欠温判断.................................................................................................................
                if not 6 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 celltempmin0<self.param.CellTempLowLv2 and celltempmin1<self.param.CellTempLowLv2:  #二级低温进入
                        ut_time=ut_time+(self.bmstime[i]-self.bmstime[i-1]).total_seconds()
                        if ut_time>self.param.temp_time:
                            time=self.bmstime[i]
                            code=6
                            faultlv=3
                            faultinfo='温度{}低温二级'.format(celltemp1.index(celltempmin1)+1)
                            faultadvice='技术介入诊断'
                            self.df_diag_ram.loc[len(self.df_diag_ram)]=[time, end_time, self.sn, code, faultlv, faultinfo, faultadvice]
                        else:
                            pass
                    else:
                        ut_time=0
                else:   #ram当前故障中有该故障，则判断是否退出该故障
                    if celltempmax0>self.param.CellTempLowLv1+2 and celltempmax1>self.param.CellTempLowLv1+2:    #二级高温恢复
                        time=self.bmstime[i]
                        self.df_diag_ram.loc[self.df_diag_ram[self.df_diag_ram['code']==6].index, 'end_time'] = time
                    else:
                        pass
              
                #温差判断.............................................................................................................................
                if not 8 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 (celltempmax0-celltempmin0)>self.param.CellTempDiffLv2 and (celltempmax1-celltempmin1)>self.param.CellTempDiffLv2:  #二级温差进入
                        dt_time=dt_time+(self.bmstime[i]-self.bmstime[i-1]).total_seconds()
                        if dt_time>self.param.temp_time:
                            time=self.bmstime[i]
                            code=8
                            faultlv=3
                            faultinfo='温度{}和{}温差大二级'.format(celltemp1.index(celltempmax1)+1,celltemp1.index(celltempmin1)+1)
                            faultadvice='技术介入诊断'
                            self.df_diag_ram.loc[len(self.df_diag_ram)]=[time, end_time, self.sn, code, faultlv, faultinfo, faultadvice]
                        else:
                            pass
                    else:
                        dt_time=0
                else:   #ram当前故障中有该故障，则判断是否退出该故障
                    if (celltempmax0-celltempmin0)<self.param.CellTempDiffLv1-2 and (celltempmax1-celltempmax0)>self.param.CellTempDiffLv1-2:  #二级温差恢复
                        time=self.bmstime[i]
                        self.df_diag_ram.loc[self.df_diag_ram[self.df_diag_ram['code']==8].index, 'end_time'] = time
                    else:
                        pass

            #     #温升判断
            #     time2=self.bmstime[i]
            #     delttime=(time2-time1).total_seconds()
            #     if delttime>20:
            #         temp2=np.array(self._celltemp_get(i))
            #         celltemp_rate=round((max(temp2-temp1)*60)/delttime,2)    #计算最大温升速率
            #         temp1=temp2 #更新初始温度
            #         time1=time2 #更新初始时间
            #         if not 9 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 celltemp_rate>self.param.CellTempRate:
            #                 temprate_cnt=temprate_cnt+1
            #                 if temprate_cnt>2:  #温升故障进入
            #                     time=self.bmstime[i]
            #                     code=9
            #                     faultlv=3
            #                     faultinfo='温升速率过快：{}℃/min'.format(celltemp_rate)
            #                     faultadvice='技术介入诊断'
            #                     self.df_diag_ram.loc[len(self.df_diag_ram)]=[time, end_time, self.sn, code, faultlv, faultinfo, faultadvice]
            #                 else:
            #                     pass
            #             else:   #ram当前故障中有该故障，则判断是否退出该故障
            #                pass
            #         else:
            #             if celltemp_rate<self.param.CellTempRate-1: #温升故障恢复
            #                 time=self.bmstime[i]
            #                 self.df_diag_ram.loc[self.df_diag_ram[self.df_diag_ram['code']==9].index, 'end_time'] = time
            #     else:
            #         pass
            
            else:
                ot_time=0
                ut_time=0
                dt_time=0
                    
            #电压诊断功能.................................................................................................
            cellvolt0=self._cellvolt_get(i-1)
            cellvolt1=self._cellvolt_get(i)
            cellvoltmin0=min(cellvolt0)
            cellvoltmax0=max(cellvolt0)
            cellvoltmin1=min(cellvolt1)
            cellvoltmax1=max(cellvolt1)
            #电压断线诊断...................................................................................................
            if (cellvoltmin0<2 and cellvoltmax0>4.5) or cellvoltmin0<0.1 or cellvoltmax0>5:
                cellvoltvalid=0
            else:
                cellvoltvalid=1
            
            if cellvoltvalid==1:
                #过压诊断.............................................................................................................
                if not 12 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 cellvoltmax0>self.param.CellOvLv2 and cellvoltmax1>self.param.CellOvLv2:  #二级过压进入
                        cov_time=cov_time+(self.bmstime[i]-self.bmstime[i-1]).total_seconds()
                        if cov_time>self.param.volt_time:
                            time=self.bmstime[i]
                            code=12
                            faultlv=4
                            faultinfo='电芯{}过压二级'.format(cellvolt1.index(cellvoltmax1)+1)
                            faultadvice='联系用户询问用车场景，技术介入诊断'
                            self.df_diag_ram.loc[len(self.df_diag_ram)]=[time, end_time, self.sn, code, faultlv, faultinfo, faultadvice]
                        else:
                            pass
                    else:
                        cov_time=0
                else:   #ram当前故障中有该故障，则判断是否退出该故障
                    if cellvoltmax0<self.param.CellOvLv1-0.05 and cellvoltmax1<self.param.CellOvLv1-0.05:   #二级过压故障恢复
                        time=self.bmstime[i]
                        self.df_diag_ram.loc[self.df_diag_ram[self.df_diag_ram['code']==12].index, 'end_time'] = time
                    else:
                        pass
              

                #欠压诊断.................................................................................................................
                if not 14 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 cellvoltmin0<self.param.CellUvLv2 and cellvoltmin1<self.param.CellUvLv2:  #二级欠压
                        cuv_time=cuv_time+(self.bmstime[i]-self.bmstime[i-1]).total_seconds()
                        if cuv_time>self.param.volt_time:
                            time=self.bmstime[i]
                            code=14
                            faultlv=3
                            faultinfo='电芯{}欠压二级'.format(cellvolt1.index(cellvoltmin1)+1)
                            faultadvice='联系用户询问用车场景，技术介入诊断'
                            self.df_diag_ram.loc[len(self.df_diag_ram)]=[time, end_time, self.sn, code, faultlv, faultinfo, faultadvice]
                        else:
                            pass
                    else:
                        cuv_time=0
                else:
                    if cellvoltmin0>self.param.CellUvLv1+0.1 and cellvoltmin1>self.param.CellUvLv1+0.1:
                        time=self.bmstime[i]
                        self.df_diag_ram.loc[self.df_diag_ram[self.df_diag_ram['code']==14].index, 'end_time'] = time
                    else:
                        pass
             
                #电芯压差大.....................................................................................................................................................
                if not 16 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 (cellvoltmax0-cellvoltmin0)>self.param.CellVoltDiffLv2 and (cellvoltmax1-cellvoltmin1)>self.param.CellVoltDiffLv2:  #二级电芯压差
                        cdv_time=cdv_time+(self.bmstime[i]-self.bmstime[i-1]).total_seconds()
                        if cdv_time>self.param.volt_time:
                            time=self.bmstime[i]
                            code=16
                            faultlv=3
                            faultinfo='电芯{}和{}压差大二级'.format(cellvolt1.index(cellvoltmax1)+1,cellvolt1.index(cellvoltmin1)+1)
                            faultadvice='技术介入诊断'
                            self.df_diag_ram.loc[len(self.df_diag_ram)]=[time, end_time, self.sn, code, faultlv, faultinfo, faultadvice]
                        else:
                            pass
                    else:
                        cdv_time=0
                else:
                    if (cellvoltmax0-cellvoltmin0)<self.param.CellVoltDiffLv1-0.05 and (cellvoltmax1-cellvoltmin1)<self.param.CellVoltDiffLv1-0.05: #二级欠压恢复
                        time=self.bmstime[i]
                        self.df_diag_ram.loc[self.df_diag_ram[self.df_diag_ram['code']==16].index, 'end_time'] = time
                    else:
                        pass
            else:
                cov_time=0
                cuv_time=0
                cdv_time=0
                
            #电池包诊断.....................................................................................................................................
            if self.packvolt[i-1]<2*self.param.CellVoltNums and self.packvolt[i]>4.5*self.param.CellVoltNums:   #电池包电压有效性
                packvoltvalid=0
            else:
                packvoltvalid=1

            if packvoltvalid==1:
                if not 18 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 self.packvolt[i-1]>self.param.PackVoltOvLv2 and self.packvolt[i]>self.param.PackVoltOvLv2:   #电池包过压二级进入
                        pov_time=pov_time+(self.bmstime[i]-self.bmstime[i-1]).total_seconds()
                        if pov_time>self.param.volt_time:
                            time=self.bmstime[i]
                            code=18
                            faultlv=4
                            faultinfo='电池包过压二级'
                            faultadvice='联系用户询问用车场景，技术介入诊断'
                            self.df_diag_ram.loc[len(self.df_diag_ram)]=[time, end_time, self.sn, code, faultlv, faultinfo, faultadvice]
                        else:
                            pass
                    else:
                        pov_time=0
                else:
                    if self.packvolt[i-1]<self.param.PackVoltOvLv1-0.05*self.param.CellVoltNums and self.packvolt[i]<self.param.PackVoltOvLv1-0.05*self.param.CellVoltNums: #电池包过压二级恢复
                        time=self.bmstime[i]
                        self.df_diag_ram.loc[self.df_diag_ram[self.df_diag_ram['code']==18].index, 'end_time'] = time
                    else:
                        pass
          
                if not 20 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 self.packvolt[i-1]<self.param.PackVoltUvLv2 and self.packvolt[i]<self.param.PackVoltUvLv2:   #电池包二级欠压进入
                        puv_time=puv_time+(self.bmstime[i]-self.bmstime[i-1]).total_seconds()
                        if puv_time>self.param.volt_time:
                            time=self.bmstime[i]
                            code=20
                            faultlv=3
                            faultinfo='电池包欠压二级'
                            faultadvice='联系用户询问用车场景，技术介入诊断'
                            self.df_diag_ram.loc[len(self.df_diag_ram)]=[time, end_time, self.sn, code, faultlv, faultinfo, faultadvice]
                        else:
                            pass
                    else:
                        puv_time=0
                else:
                    if self.packvolt[i-1]>self.param.PackVoltUvLv1+0.1*self.param.CellVoltNums and self.packvolt[i]>self.param.PackVoltUvLv1+0.1*self.param.CellVoltNums:   #电池包二级欠压恢复
                        time=self.bmstime[i]
                        self.df_diag_ram.loc[self.df_diag_ram[self.df_diag_ram['code']==20].index, 'end_time'] = time
                    else:
                        pass
            else:
                pov_time=0
                puv_time=0 
            
            #电流过流诊断.......................................................................................................................
            step=(self.bmstime[i]-self.bmstime[i-1]).total_seconds()
            if step<120 and self.packcrnt[i]>self.param.PackDisOc and self.packcrnt[i-1]>self.param.PackDisOc:
                as_dis=as_dis+(self.packcrnt[i]-self.param.PackDisOc)*step    #ah累计
            elif step<120 and self.packcrnt[i]<self.param.PackChgOc and self.packcrnt[i-1]<self.param.PackChgOc:
                as_chg=as_chg+(self.param.PackDisOc-self.packcrnt[i])*step    #ah累计
            else:
                as_dis=0
                as_chg=0
            
            if not 22 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 as_dis>100:
                    time=self.bmstime[i]
                    code=22
                    faultlv=3
                    faultinfo='电池包放电过流'
                    faultadvice='联系用户询问用车场景，技术介入诊断'
                    self.df_diag_ram.loc[len(self.df_diag_ram)]=[time, end_time, self.sn, code, faultlv, faultinfo, faultadvice]
                else:
                    pass
            else:
                if self.packcrnt[i]<self.param.PackDisOc-10:
                    time=self.bmstime[i]
                    self.df_diag_ram.loc[self.df_diag_ram[self.df_diag_ram['code']==22].index, 'end_time'] = time
                else:
                    pass
            
            if not 21 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 as_chg>100:
                    time=self.bmstime[i]
                    code=21
                    faultlv=3
                    faultinfo='电池包充电过流'
                    faultadvice='联系用户询问用车场景，技术介入诊断'
                    self.df_diag_ram.loc[len(self.df_diag_ram)]=[time, end_time, self.sn, code, faultlv, faultinfo, faultadvice]
                else:
                    pass
            else:
                if self.packcrnt[i]>self.param.PackChgOc+10:
                    time=self.bmstime[i]
                    self.df_diag_ram.loc[self.df_diag_ram[self.df_diag_ram['code']==21].index, 'end_time'] = time
                else:
                    pass

            #SOC卡滞、跳变诊断................................................................................................
            step=(self.bmstime[i]-self.bmstime[i-1]).total_seconds()
            if step<120:
                ah_accum=ah_accum-self.packcrnt[i]*step/3600    #ah累计
            else:
                pass
            #SOC卡滞............................................................................................................
            if abs(ah_accum)>self.param.Capacity*0.1:   
                bmssoc_now=float(self.bms_soc[i])
                if not 27 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 abs(bmssoc_now-bmssoc_st)<self.param.SocClamp:   #SOC卡滞故障进入
                        time=self.bmstime[i]
                        code=27
                        faultlv=1
                        faultinfo='电池SOC卡滞'
                        faultadvice='技术介入诊断，检修电池BMS软件'
                        self.df_diag_ram.loc[len(self.df_diag_ram)]=[time, end_time, self.sn, code, faultlv, faultinfo, faultadvice]
                    else:
                        pass
                else:
                    if abs(bmssoc_now-bmssoc_st)>self.param.SocClamp:   #SOC卡滞故障退出
                        time=self.bmstime[i]
                        self.df_diag_ram.loc[self.df_diag_ram[self.df_diag_ram['code']==27].index, 'end_time'] = time
                    else:
                        pass
                bmssoc_st=bmssoc_now
                ah_accum=0
            else:
                pass

            #SOC跳变....................................................................................................................
            bmssoc_last=float(self.bms_soc[i-1])
            bmssoc_now=float(self.bms_soc[i])
            if not 28 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 step<30 and abs(bmssoc_now-bmssoc_last)>self.param.SocJump:  #SOC跳变进入
                    time=self.bmstime[i]
                    code=28
                    faultlv=1
                    faultinfo='电池SOC跳变'
                    faultadvice='技术介入诊断，检修电池BMS软件'
                    self.df_diag_ram.loc[len(self.df_diag_ram)]=[time, end_time, self.sn, code, faultlv, faultinfo, faultadvice]
                else:
                    pass
            else:
                if abs(bmssoc_now-bmssoc_st)<self.param.SocJump:    #SOC跳变故障退出
                    time=self.bmstime[i]
                    self.df_diag_ram.loc[self.df_diag_ram[self.df_diag_ram['code']==28].index, 'end_time'] = time
                else:
                    pass

            # #SOC过低故障报警............................................................................................................
            # if not 26 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 self.bms_soc[i-1]<self.param.SocLow and self.bms_soc[i]<self.param.SocLow:   #SOC过低故障进入
            #         time=self.bmstime[i]
            #         code=26
            #         faultlv=1
            #         faultinfo='电池包电量过低'
            #         faultadvice='联系用户，请立刻充电'
            #         self.df_diag_ram.loc[len(self.df_diag_ram)]=[time, end_time, self.sn, code, faultlv, faultinfo, faultadvice]
            #     else:
            #         pass
            # else:   
            #     if self.bms_soc[i-1]>self.param.SocLow and self.bms_soc[i]>self.param.SocLow:   #SOC过低故障退出
            #         time=self.bmstime[i]
            #         self.df_diag_ram.loc[self.df_diag_ram[self.df_diag_ram['code']==26].index, 'end_time'] = time
            #     else:
            #         pass

            # #BMS故障报警........................................................................................................
            # if not 1 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 self.bmsfault1[i-1] is None or self.bmsfault1[i] is None:
            #         self.bmsfault1[i-1]=0
            #         self.bmsfault1[i]=0
            #     if self.bmsfault1[i-1]>0 or self.bmsfault1[i]>0:   #BMS故障进入
            #         time=self.bmstime[0]
            #         code=1
            #         faultlv=2
            #         faultinfo='BMS故障报警：{}'.format(self.bmsfault1[i-1])
            #         faultadvice='技术介入诊断'
            #         self.df_diag_ram.loc[len(self.df_diag_ram)]=[time, end_time, self.sn, code, faultlv, faultinfo, faultadvice]
            #     else:
            #         pass
            # else:
            #     if self.bmsfault1[i-1]==0 and self.bmsfault1[i]==0:   #BMS故恢复
            #         time=self.bmstime[i]
            #         self.df_diag_ram.loc[self.df_diag_ram[self.df_diag_ram['code']==1].index, 'end_time'] = time
        
        
        #SOC一致性故障报警..........................................................................................................
        if not self.df_uniform.empty:
            cellsoc_diff=self.df_uniform.loc[0,'cellsoc_diff']
            if not 25 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 cellsoc_diff>self.param.SocDiff: #SOC一致性差故障进入
                    time=self.bmstime[0]
                    code=25
                    faultlv=1
                    faultinfo='电芯{}和{}SOC差过大:{}'.format(self.df_uniform.loc[0,'cellmin_num'],self.df_uniform.loc[0,'cellmax_num'],cellsoc_diff)
                    faultadvice='技术介入诊断'
                    self.df_diag_ram.loc[len(self.df_diag_ram)]=[time, end_time, self.sn, code, faultlv, faultinfo, faultadvice]
                else:
                    pass
            else:
                if cellsoc_diff<self.param.SocDiff: #SOC一致性差故障恢复
                    time=self.bmstime[0]
                    self.df_diag_ram.loc[self.df_diag_ram[self.df_diag_ram['code']==25].index, 'end_time'] = time
        else:
            cellsoc_diff=3

        #容量过低和一致性故障报警................................................................................................
        if not self.df_soh.empty:
            soh=self.df_soh.loc[0,'soh']
            cellsoh=eval(self.df_soh.loc[0,'cellsoh'])
            cellsoh=np.array(cellsoh)
            cellsoh_lowindex=np.argwhere(cellsoh<self.param.SohLow)
            cellsoh_lowindex=cellsoh_lowindex+1
            if self.celltype==1 or self.celltype==2 or self.celltype==3 or self.celltype==4: 
                cellsoh_diff=np.max(cellsoh)-np.min(cellsoh)
                if not 23 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 soh<self.param.SohLow:   #soh过低故障进入
                        time=self.bmstime[0]
                        code=23
                        faultlv=1
                        faultinfo='电池包容量过低：电芯{}'.format(cellsoh_lowindex)
                        faultadvice='检修电池，更换容量过低的电芯或模组'
                        self.df_diag_ram.loc[len(self.df_diag_ram)]=[time, end_time, self.sn, code, faultlv, faultinfo, faultadvice]
                    else:
                        pass
                else:
                    if soh>self.param.SohLow+2:   #soh过低故障恢复
                        time=self.bmstime[0]
                        self.df_diag_ram.loc[self.df_diag_ram[self.df_diag_ram['code']==23].index, 'end_time'] = time
                    else:
                        pass

                if not 24 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 cellsoh_diff>self.param.SohDiff:
                        time=self.bmstime[0]
                        code=24
                        faultlv=1
                        faultinfo='电池包容量一致性差：电芯{}'.format(cellsoh_lowindex)
                        faultadvice='检修电池，更换容量过低的电芯或模组'
                        self.df_diag_ram.loc[len(self.df_diag_ram)]=[time, end_time, self.sn, code, faultlv, faultinfo, faultadvice]
                    else:
                        pass
                else:
                    if cellsoh_diff<self.param.SohDiff-2:
                        time=self.bmstime[0]
                        self.df_diag_ram.loc[self.df_diag_ram[self.df_diag_ram['code']==24].index, 'end_time'] = time
                    else:
                        pass
            else:
                pass
        else:
            cellsoh_diff=5
        
        # #电池健康度评分.....................................................................................................
        # health_state=soh*0.6+(100-cellsoh_diff)*0.2+(100-cellsoc_diff)*0.2
        # if health_state>100:
        #     health_state=100
        # elif health_state<0:
        #     health_state=0
        # else:
        #     pass
        # health_state=eval(format(health_state,'.1f'))

        #返回诊断结果...........................................................................................................
        df_res=self.df_diag_ram
        if not df_res.empty:
            return df_res
        else:
            return pd.DataFrame()