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@@ -100,6 +100,16 @@ class BatInterShort():
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else:
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cellvolt=pd.DataFrame()
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return cellvolt
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+
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+ #获取单个电压值.................................................................................................
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+ def _singlevolt_get(self,num,series,mode): #mode==1取当前行单体电压值，mode==2取某个单体所有电压值
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+ s=str(series)
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+ if mode==1:
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+ singlevolt=self.df_bms.loc[num,'单体电压' + s]/1000
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+ return singlevolt
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+ else:
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+ singlevolt=self.df_bms['单体电压' + s]/1000
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+ return singlevolt
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#获取当前行所有电压数据........................................................................................
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def _cellvolt_get(self,num):
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@@ -107,11 +117,11 @@ class BatInterShort():
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return cellvolt
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#获取当前行所有soc差...........................................................................................
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- def _celldeltsoc_get(self,num,dict_baltime,capacity):
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+ def _celldeltsoc_get(self,cellvolt_list,dict_baltime,capacity):
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cellsoc=[]
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celldeltsoc=[]
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for j in range(1, self.param.CellVoltNums+1): #获取每个电芯电压对应的SOC值
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- cellvolt=self.df_bms.loc[num,'单体电压' + str(j)]/1000
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+ cellvolt=cellvolt_list[j+1]
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ocv_soc=np.interp(cellvolt,self.param.LookTab_OCV,self.param.LookTab_SOC)
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if j in dict_baltime.keys():
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ocv_soc=ocv_soc+dict_baltime[j]*self.param.BalCurrent/(capacity*3600) #补偿均衡电流
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@@ -194,6 +204,87 @@ class BatInterShort():
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celldeltAs.append(cellAs[j]-cellAsmean)
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return np.array(celldeltAs)
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+
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+ #寻找DVDQ的峰值点，并返回..........................................................................................................................
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+ def _dvdq_peak(self, time, soc, cellvolt, packcrnt):
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+ cellvolt = self._np_move_avg(cellvolt, 3, mode="same")
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+ Soc = 0
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+ Ah = 0
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+ Volt = cellvolt[0]
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+ DV_Volt = []
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+ DQ_Ah = []
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+ DVDQ = []
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+ time1 = []
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+ soc1 = []
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+ soc2 = []
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+ xvolt=[]
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+
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+ for m in range(1, len(time)):
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+ Step = (time[m] - time[m - 1]).total_seconds()
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+ Soc = Soc - packcrnt[m] * Step * 100 / (3600 * self.param.Capacity)
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+ Ah = Ah - packcrnt[m] * Step / 3600
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+ if (cellvolt[m]-Volt)>0.0015 and Ah>0:
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+ DQ_Ah.append(Ah)
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+ DV_Volt.append(cellvolt[m]-Volt)
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+ DVDQ.append((DV_Volt[-1])/Ah)
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+ xvolt.append(cellvolt[m])
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+ Volt=cellvolt[m]
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+ Ah = 0
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+ soc1.append(Soc)
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+ time1.append(time[m])
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+ soc2.append(soc[m])
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+
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+ #切片，去除前后10min的数据
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+ df_Data1 = pd.DataFrame({'time': time1,
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+ 'SOC': soc2,
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+ 'DVDQ': DVDQ,
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+ 'AhSoc': soc1,
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+ 'DQ_Ah':DQ_Ah,
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+ 'DV_Volt':DV_Volt,
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+ 'XVOLT':xvolt})
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+ start_time=df_Data1.loc[0,'time']
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+ start_time=start_time+datetime.timedelta(seconds=900)
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+ end_time=df_Data1.loc[len(time1)-1,'time']
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+ end_time=end_time-datetime.timedelta(seconds=1200)
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+ if soc2[0]<36:
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+ df_Data1=df_Data1[(df_Data1['SOC']>40) & (df_Data1['SOC']<80)]
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+ else:
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+ df_Data1=df_Data1[(df_Data1['time']>start_time) & (df_Data1['SOC']<80)]
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+ df_Data1=df_Data1[(df_Data1['XVOLT']>self.param.PeakVoltLowLmt) & (df_Data1['XVOLT']<self.param.PeakVoltUpLmt)]
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+
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+ # print(packcrnt[int(len(time)/2)], min(self.celltemp))
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+ # ax1 = plt.subplot(3, 1, 1)
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+ # plt.plot(df_Data1['SOC'],df_Data1['DQ_Ah'],'g*-')
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+ # plt.xlabel('SOC/%')
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+ # plt.ylabel('DQ_Ah')
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+ # plt.legend()
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+ # ax1 = plt.subplot(3, 1, 2)
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+ # plt.plot(df_Data1['SOC'],df_Data1['XVOLT'],'y*-')
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+ # plt.xlabel('SOC/%')
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+ # plt.ylabel('Volt/V')
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+ # plt.legend()
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+ # ax1 = plt.subplot(3, 1, 3)
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+ # plt.plot(df_Data1['SOC'], df_Data1['DVDQ'], 'r*-')
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+ # plt.xlabel('SOC/%')
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+ # plt.ylabel('DV/DQ')
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+ # plt.legend()
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+ # # plt.show()
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+
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+ if len(df_Data1)>2: #寻找峰值点，且峰值点个数>2
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+ PeakIndex = df_Data1['DVDQ'].idxmax()
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+ df_Data2 = df_Data1[(df_Data1['SOC'] > (df_Data1['SOC'][PeakIndex] - 0.5)) & (df_Data1['SOC'] < (df_Data1['SOC'][PeakIndex] + 0.5))]
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+ if len(df_Data2) > 1 and df_Data1.loc[PeakIndex,'XVOLT']<self.param.PeakVoltUpLmt-0.015:
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+ return df_Data1['AhSoc'][PeakIndex]
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+ else:
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+ df_Data1 = df_Data1.drop([PeakIndex])
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+ PeakIndex = df_Data1['DVDQ'].idxmax()
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+ df_Data2 = df_Data1[(df_Data1['SOC'] > (df_Data1['SOC'][PeakIndex] - 0.5)) & (df_Data1['SOC'] < (df_Data1['SOC'][PeakIndex] + 0.5))]
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+ if len(df_Data2) > 1 and df_Data1.loc[PeakIndex,'XVOLT']<self.param.PeakVoltUpLmt-0.015:
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+ return df_Data1['AhSoc'][PeakIndex]
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+ else:
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+ return 0
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+ else:
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+ return 0
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#计算每个电芯的均衡时长..........................................................................................................................
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def _bal_time(self,dict_bal):
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@@ -325,7 +416,7 @@ class BatInterShort():
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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):
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dict_baltime={} #获取每个电芯的均衡时间
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- deltsoc_last, cellsoc_last=self._celldeltsoc_get(i,dict_baltime,capacity)
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+ deltsoc_last, cellsoc_last=self._celldeltsoc_get(cellvolt_now,dict_baltime,capacity)
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time_last=self.bmstime[i]
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firsttime=0
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df_ram_last.loc[0]=[self.sn,time_last,deltsoc_last,cellsoc_last] #更新RAM信息
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@@ -344,7 +435,7 @@ class BatInterShort():
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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):
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dict_baltime=self._bal_time(dict_bal) #获取每个电芯的均衡时间
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- deltsoc_now, cellsoc_now=self._celldeltsoc_get(i,dict_baltime,capacity)
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+ deltsoc_now, cellsoc_now=self._celldeltsoc_get(cellvolt_now,dict_baltime,capacity)
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time_now=self.bmstime[i]
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if -5<max(cellsoc_now-cellsoc_last)<5:
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df_ram_last.loc[0]=[self.sn,time_now,deltsoc_now,cellsoc_now] #更新RAM信息
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@@ -388,10 +479,10 @@ class BatInterShort():
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# deltvolt1=max(abs(cellvolt_now1-cellvolt_last1))
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cellsoc_now1=np.interp(cellvolt_max1,self.param.LookTab_OCV,self.param.LookTab_SOC)
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- if cellsoc_now1>=self.param.FullChrgSoc-10 and 2<cellvolt_min1<4.5 and 2<cellvolt_max1<4.5:
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+ if cellsoc_now1>self.param.FullChrgSoc-10 and 2<cellvolt_min1<4.5 and 2<cellvolt_max1<4.5:
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if firsttime1==1:
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dict_baltime1={} #获取每个电芯的均衡时间
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- deltsoc_last1, cellsoc_last1=self._celldeltsoc_get(i,dict_baltime1,capacity)
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+ deltsoc_last1, cellsoc_last1=self._celldeltsoc_get(cellvolt_now1,dict_baltime1,capacity)
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time_last1=self.bmstime[i]
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firsttime1=0
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df_ram_last1.loc[0]=[self.sn,time_last1,deltsoc_last1] #更新RAM信息
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@@ -399,7 +490,7 @@ class BatInterShort():
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dict_baltime1=self._bal_time(dict_bal1) #获取每个电芯的均衡时间
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time_now1=self.bmstime[i]
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if (time_now1-time_last1).total_seconds()>3600*20:
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- deltsoc_now1, cellsoc_now1=self._celldeltsoc_get(i,dict_baltime1,capacity)
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+ deltsoc_now1, cellsoc_now1=self._celldeltsoc_get(cellvolt_now1,dict_baltime1,capacity)
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df_ram_last1.loc[0]=[self.sn,time_now1,deltsoc_now1] #更新RAM信息
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list_sub1=deltsoc_now1-deltsoc_last1
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@@ -538,7 +629,7 @@ class BatInterShort():
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if cellsoc_max<self.param.SocInflexion1-2 and 12<cellsoc_min:
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dict_baltime={} #获取每个电芯的均衡时间
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- deltsoc_last, cellsoc_last=self._celldeltsoc_get(i,dict_baltime,capacity)
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+ deltsoc_last, cellsoc_last=self._celldeltsoc_get(cellvolt_now,dict_baltime,capacity)
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time_last=self.bmstime[i]
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firsttime=0
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df_ram_last.loc[0]=[self.sn,time_last,deltsoc_last,cellsoc_last] #更新RAM信息
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@@ -559,7 +650,7 @@ class BatInterShort():
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if cellsoc_max<self.param.SocInflexion1-2 and 12<cellsoc_min:
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dict_baltime=self._bal_time(dict_bal) #获取每个电芯的均衡时间
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- deltsoc_now, cellsoc_now=self._celldeltsoc_get(i, dict_baltime,capacity) #获取每个电芯的SOC差
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+ deltsoc_now, cellsoc_now=self._celldeltsoc_get(cellvolt_now, dict_baltime,capacity) #获取每个电芯的SOC差
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time_now=self.bmstime[i]
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if -5<max(cellsoc_now-cellsoc_last)<5:
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df_ram_last.loc[0]=[self.sn,time_now,deltsoc_now,cellsoc_now] #更新RAM信息
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@@ -609,13 +700,13 @@ class BatInterShort():
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if cellsoc_max1<self.param.SocInflexion1-2 and 12<cellsoc_min1:
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if firsttime1==1:
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dict_baltime1=self._bal_time(dict_bal1) #获取每个电芯的均衡时间
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- deltsoc_last1, cellsoc_last1=self._celldeltsoc_get(i,dict_baltime1,capacity)
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+ deltsoc_last1, cellsoc_last1=self._celldeltsoc_get(cellvolt_now1,dict_baltime1,capacity)
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time_last1=self.bmstime[i]
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firsttime1=0
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df_ram_last1.loc[0]=[self.sn,time_last1,deltsoc_last1] #更新RAM信息
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else:
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dict_baltime1=self._bal_time(dict_bal1) #获取每个电芯的均衡时间
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- deltsoc_now1, cellsoc_now1=self._celldeltsoc_get(i,dict_baltime1,capacity)
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+ deltsoc_now1, cellsoc_now1=self._celldeltsoc_get(cellvolt_now1,dict_baltime1,capacity)
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time_now1=self.bmstime[i]
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df_ram_last1.loc[0]=[self.sn,time_now1,deltsoc_now1] #更新RAM信息
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@@ -664,7 +755,7 @@ class BatInterShort():
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#判断充电状态
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if self.packcrnt[i]<=-1 and self.packcrnt[i+1]<=-1 and self.packcrnt[i-1]<=-1:
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if charging==0:
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- if self.bms_soc[i]<40:
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+ if self.bms_soc[i]<41:
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cellvolt_now=self._cellvolt_get(i)
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if min(cellvolt_now)<self.param.CellFullChrgVolt-0.15:
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charging=1
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@@ -676,42 +767,125 @@ class BatInterShort():
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else: #充电中
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cellvolt_now=self._cellvolt_get(i)
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- 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
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+ if (self.bmstime[i+1]-self.bmstime[i]).total_seconds()>180 or (self.packcrnt[i]>self.param.Capacity/2 and self.packcrnt[i+1]>self.param.Capacity/2): #如果充电过程中时间间隔>180s，则舍弃该次充电
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charging=0
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continue
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- elif min(cellvolt_now)>self.param.CellFullChrgVolt-0.13: #电压>满充电压-0.13V，即3.37V
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+ # elif min(cellvolt_now)>self.param.CellFullChrgVolt-0.13: #电压>满充电压-0.13V，即3.37V
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+ # self._celltemp_weight(i)
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+ # if i-chrg_start>10 and self.celltemp>20:
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+ # chrg_end=i+1
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+ # charging=0
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+
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+ # #计算漏电流值...................................................................
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+ # if firsttime2==1:
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+ # dict_baltime={}
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+ # deltAs_last2=self._cellDeltAs_get(chrg_start,chrg_end,dict_baltime)
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+ # time_last2=self.bmstime[chrg_end]
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+ # df_ram_last2.loc[0]=[self.sn,time_last2,deltAs_last2] #更新RAM信息
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+ # else:
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+ # dict_baltime=self._bal_time(dict_bal2) #获取每个电芯的均衡时间
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+ # deltAs_now2=self._cellDeltAs_get(chrg_start,chrg_end,dict_baltime) #获取每个电芯的As差
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+ # time_now2=self.bmstime[chrg_end]
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+ # df_ram_last2.loc[0]=[self.sn,time_now2,deltAs_now2] #更新RAM信息
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+
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+ # list_sub2=deltAs_now2-deltAs_last2
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+ # list_pud2=-1000/(time_now2-time_last2).total_seconds()
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+ # leak_current2=list_sub2*list_pud2
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+ # # leak_current=np.array(leak_current)
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+ # leak_current2=np.round(leak_current2,3)
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+ # leak_current2=list(leak_current2)
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+
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+ # 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
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+ # deltAs_last2=deltAs_now2
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+ # time_last2=time_now2
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+ # dict_bal2={}
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+
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+ # else:
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+ # charging=0
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+ # continue
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+ elif min(cellvolt_now)>self.param.CellFullChrgVolt-0.1: #电压>满充电压
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self._celltemp_weight(i)
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- if i-chrg_start>10 and self.celltemp>20:
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+ if i-chrg_start>10 and self.celltemp>10:
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chrg_end=i+1
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charging=0
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#计算漏电流值...................................................................
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if firsttime2==1:
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dict_baltime={}
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- deltAs_last2=self._cellDeltAs_get(chrg_start,chrg_end,dict_baltime)
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- time_last2=self.bmstime[chrg_end]
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- df_ram_last2.loc[0]=[self.sn,time_last2,deltAs_last2] #更新RAM信息
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+ peaksoc_list=[]
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+ for j in range(1, self.param.CellVoltNums + 1):
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+ cellvolt = self._singlevolt_get(i,j,2) #取单体电压j的所有电压值
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+ cellvolt = list(cellvolt[chrg_start:chrg_end])
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+ time = list(self.bmstime[chrg_start:chrg_end])
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+ packcrnt = list(self.packcrnt[chrg_start:chrg_end])
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+ soc = list(self.bms_soc[chrg_start:chrg_end])
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+ peaksoc = self._dvdq_peak(time, soc, cellvolt, packcrnt)
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+ if peaksoc>1:
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+ peaksoc_list.append(peaksoc)
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+ else:
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+ break
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+ if len(peaksoc_list)==self.param.CellVoltNums:
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+ celldeltsoc=[]
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+ consum_num=10
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+ cellsoc1=peaksoc_list[:self.param.CellVoltNums-consum_num] #切片，将bms耗电的电芯和非耗电的电芯分离开
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+ cellsocmean1=(sum(cellsoc1)-max(cellsoc1)-min(cellsoc1))/(len(cellsoc1)-2)
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+ cellsoc2=peaksoc_list[self.param.CellVoltNums-consum_num:]
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+ cellsocmean2=(sum(cellsoc2)-max(cellsoc2)-min(cellsoc2))/(len(cellsoc2)-2)
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+
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+ for j in range(len(peaksoc_list)): #计算每个电芯的soc差
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+ if j<self.param.CellVoltNums-consum_num:
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+ celldeltsoc.append(peaksoc_list[j]-cellsocmean1)
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|
|
+ else:
|
|
|
+ celldeltsoc.append(peaksoc_list[j]-cellsocmean2)
|
|
|
+ deltsoc_last2=celldeltsoc
|
|
|
+ time_last2=self.bmstime[chrg_end]
|
|
|
+ df_ram_last2.loc[0]=[self.sn,time_last2,deltsoc_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={}
|
|
|
-
|
|
|
+ peaksoc_list=[]
|
|
|
+ for j in range(1, self.param.CellVoltNums + 1):
|
|
|
+ cellvolt = self._singlevolt_get(i,j,2) #取单体电压j的所有电压值
|
|
|
+ cellvolt = list(cellvolt[chrg_start:chrg_end])
|
|
|
+ time = list(self.bmstime[chrg_start:chrg_end])
|
|
|
+ packcrnt = list(self.packcrnt[chrg_start:chrg_end])
|
|
|
+ soc = list(self.bms_soc[chrg_start:chrg_end])
|
|
|
+ peaksoc = self._dvdq_peak(time, soc, cellvolt, packcrnt)
|
|
|
+ if peaksoc>1:
|
|
|
+ peaksoc_list.append(peaksoc)
|
|
|
+ else:
|
|
|
+ break
|
|
|
+ if len(peaksoc_list)==self.param.CellVoltNums:
|
|
|
+ celldeltsoc=[]
|
|
|
+ consum_num=10
|
|
|
+ cellsoc1=peaksoc_list[: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=peaksoc_list[self.param.CellVoltNums-consum_num:]
|
|
|
+ cellsocmean2=(sum(cellsoc2)-max(cellsoc2)-min(cellsoc2))/(len(cellsoc2)-2)
|
|
|
+
|
|
|
+ for j in range(len(peaksoc_list)): #计算每个电芯的soc差
|
|
|
+ if j<self.param.CellVoltNums-consum_num:
|
|
|
+ celldeltsoc.append(peaksoc_list[j]-cellsocmean1)
|
|
|
+ else:
|
|
|
+ celldeltsoc.append(peaksoc_list[j]-cellsocmean2)
|
|
|
+ deltsoc_now2=celldeltsoc
|
|
|
+ time_now2=self.bmstime[chrg_end]
|
|
|
+ df_ram_last2.loc[0]=[self.sn,time_now2,deltsoc_now2] #更新RAM信息
|
|
|
+
|
|
|
+ list_sub2=deltsoc_now2-deltsoc_last2
|
|
|
+ list_pud2=(0.01*capacity*3600*1000)/(time_now2-time_last2).total_seconds()
|
|
|
+ leak_current2=list_sub2*list_pud2
|
|
|
+ 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
|
|
|
+ deltsoc_last2=deltsoc_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
|
