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@@ -1,906 +0,0 @@
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-import pandas as pd
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-import numpy as np
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-import matplotlib.pyplot as plt
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-import datetime
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-# from pymysql import paramstyle
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-from LIB.MIDDLE.CellStateEstimation.Common.V1_0_1 import BatParam
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-
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-class BatInterShort():
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- def __init__(self,sn,celltype,df_bms,df_soh,df_last,df_last1,df_last2,df_last3,df_lfp): #参数初始化
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-
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- if (not df_lfp.empty) and celltype>50:
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- df_lfp.drop(['sn'],axis=1)
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- df_bms=pd.concat([df_lfp, df_bms], ignore_index=True)
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- else:
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- pass
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-
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- self.sn=sn
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- self.celltype=celltype
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- self.param=BatParam.BatParam(celltype)
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- self.packcrnt=df_bms['总电流[A]']*self.param.PackCrntDec
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- self.packvolt=df_bms['总电压[V]']
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- self.bms_soc=df_bms['SOC[%]']
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- df_bms['time']=pd.to_datetime(df_bms['时间戳'], format='%Y-%m-%d %H:%M:%S')
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- self.bmstime= df_bms['time']
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-
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- self.df_bms=df_bms
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- self.df_soh=df_soh
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- self.df_last=df_last
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- self.df_last1=df_last1
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- self.df_last2=df_last2
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- self.df_last3=df_last3
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- self.df_lfp=df_lfp
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-
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- self.cellvolt_name=['单体电压'+str(x) for x in range(1,self.param.CellVoltNums+1)]
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- self.celltemp_name=['单体温度'+str(x) for x in range(1,self.param.CellTempNums+1)]
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-
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- def intershort(self):
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- if self.celltype<=50:
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- df_res, df_ram_last, df_ram_last1, df_ram_last3=self._ncm_intershort()
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- return df_res, df_ram_last, df_ram_last1,self.df_last2, df_ram_last3,self.df_lfp
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-
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- else:
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- df_res, df_ram_last, df_ram_last1, df_ram_last2, df_ram_last3, df_ram_lfp=self._lfp_intershort()
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- return df_res, df_ram_last, df_ram_last1, df_ram_last2, df_ram_last3, df_ram_lfp
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-
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-
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- #定义滑动滤波函数....................................................................................
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- def _np_move_avg(self,a, n, mode="same"):
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- return (np.convolve(a, np.ones((n,)) / n, mode=mode))
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-
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- #寻找当前行数据的最小温度值.............................................................................
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- def _celltemp_weight(self,num):
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- celltemp = list(self.df_bms.loc[num,self.celltemp_name])
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- celltemp=min(celltemp)
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- self.celltemp=celltemp
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- if self.celltype==99:
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- if celltemp>=25:
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- self.tempweight=1
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- self.StandardStandingTime=4800
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- elif celltemp>=15:
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- self.tempweight=0.6
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- self.StandardStandingTime=7200
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- elif celltemp>=5:
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- self.tempweight=0.
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- self.StandardStandingTime=10800
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- else:
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- self.tempweight=0.1
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- self.StandardStandingTime=10800
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- else:
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- if celltemp>=25:
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- self.tempweight=1
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- self.StandardStandingTime=4800
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- elif celltemp>=15:
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- self.tempweight=0.8
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- self.StandardStandingTime=7200
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- elif celltemp>=5:
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- self.tempweight=0.6
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- self.StandardStandingTime=7200
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- else:
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- self.tempweight=0.2
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- self.StandardStandingTime=10800
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-
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- #获取前半个小时每个电压的平均值........................................................................................
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- def _avgvolt_get(self,num):
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- time_now=self.df_bms.loc[num, 'time']
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- time_last=time_now-datetime.timedelta(seconds=1800)
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- df_volt=self.df_bms[(self.df_bms['time']>=time_last) & (self.df_bms['time']<=time_now)]
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- df_volt=df_volt[self.cellvolt_name]
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- cellvolt_std=df_volt.std(axis=0)
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- if len(df_volt)>2 and max(cellvolt_std)<1.5:
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- cellvolt_sum=df_volt.sum(0)-df_volt.max(0)-df_volt.min(0)
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- cellvolt_mean=cellvolt_sum/(len(df_volt)-2)
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- cellvolt=cellvolt_mean/1000
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- elif len(df_volt)==2:
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- # df_volt=pd.DataFrame(df_volt,dtype=np.float)
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- if max(abs(df_volt.iloc[1]-df_volt.iloc[0]))<3:
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- cellvolt=df_volt.mean(0)/1000
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- else:
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- cellvolt=pd.DataFrame()
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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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-
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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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- cellvolt = np.array(self.df_bms.loc[num,self.cellvolt_name])/1000
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- return cellvolt
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-
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- #获取当前行所有soc差...........................................................................................
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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(self.param.CellVoltNums): #获取每个电芯电压对应的SOC值
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- cellvolt=cellvolt_list[j]
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- ocv_soc=np.interp(cellvolt,self.param.LookTab_OCV,self.param.LookTab_SOC)
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- if j+1 in dict_baltime.keys():
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- ocv_soc=ocv_soc+dict_baltime[j+1]*self.param.BalCurrent/(capacity*3600) #补偿均衡电流
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- else:
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- pass
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- cellsoc.append(ocv_soc)
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-
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- if self.celltype==1 or self.celltype==2:
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- consum_num=7
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- cellsoc1=cellsoc[:self.param.CellVoltNums-consum_num] #切片，将bms耗电的电芯和非耗电的电芯分离开
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- cellsocmean1=(sum(cellsoc1)-max(cellsoc1)-min(cellsoc1))/(len(cellsoc1)-2)
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- cellsoc2=cellsoc[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(cellsoc)): #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(cellsoc[j]-cellsocmean1)
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- else:
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- celldeltsoc.append(cellsoc[j]-cellsocmean2)
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- return np.array(celldeltsoc), np.array(cellsoc)
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-
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- elif self.celltype==99:
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- consum_num=10
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- cellsoc1=cellsoc[:self.param.CellVoltNums-consum_num] #切片，将bms耗电的电芯和非耗电的电芯分离开
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- cellsocmean1=(sum(cellsoc1)-max(cellsoc1)-min(cellsoc1))/(len(cellsoc1)-2)
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- cellsoc2=cellsoc[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(cellsoc)): #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(cellsoc[j]-cellsocmean1)
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- else:
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- celldeltsoc.append(cellsoc[j]-cellsocmean2)
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- return np.array(celldeltsoc), np.array(cellsoc)
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-
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- else:
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- cellsocmean=(sum(cellsoc)-max(cellsoc)-min(cellsoc))/(len(cellsoc)-2)
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- for j in range(len(cellsoc)): #计算每个电芯的soc差
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- celldeltsoc.append(cellsoc[j]-cellsocmean)
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- return np.array(celldeltsoc), np.array(cellsoc)
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-
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- #获取所有电芯的As差
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- def _cellDeltAs_get(self,chrg_st,chrg_end,dict_baltime):
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- cellAs=[]
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- celldeltAs=[]
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- 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
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- if j in dict_baltime.keys(): #补偿均衡电流
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- As=-self.param.BalCurrent*dict_baltime[j]
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- else:
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- As=0
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- As_tatol=0
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- symbol=0
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- for m in range(chrg_st+1,chrg_end):
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- As=As-self.packcrnt[m]*(self.bmstime[m]-self.bmstime[m-1]).total_seconds()
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- if symbol<5:
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- if self.df_bms.loc[m,'单体电压'+str(j)]/1000>self.param.PeakCellVolt[symbol]:
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- As_tatol=As_tatol+As
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- symbol=symbol+1
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- else:
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- continue
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- else:
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- cellAs.append(As_tatol/5)
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- break
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-
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- if self.celltype==99:
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- consum_num=10
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- cellAs1=cellAs[:self.param.CellVoltNums-consum_num] #切片，将bms耗电的电芯和非耗电的电芯分离开
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- cellAsmean1=(sum(cellAs1)-max(cellAs1)-min(cellAs1))/(len(cellAs1)-2)
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- cellAs2=cellAs[self.param.CellVoltNums-consum_num:]
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- cellAsmean2=(sum(cellAs2)-max(cellAs2)-min(cellAs2))/(len(cellAs2)-2)
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-
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- for j in range(len(cellAs)): #计算每个电芯的soc差
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- if j<self.param.CellVoltNums-consum_num:
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- celldeltAs.append(cellAs[j]-cellAsmean1)
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- else:
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- celldeltAs.append(cellAs[j]-cellAsmean2)
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- else:
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- cellAsmean=(sum(cellAs)-max(cellAs)-min(cellAs))/(len(cellAs)-2)
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- for j in range(len(cellAs)): #计算每个电芯的soc差
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- celldeltAs.append(cellAs[j]-cellAsmean)
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-
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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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-
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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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- dict_baltime={}
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- dict_baltime1={}
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- for key in dict_bal:
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- count=1
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- x=eval(key)
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- while x>0:
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- if x & 1==1: #判断最后一位是否为1
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- if count in dict_baltime.keys():
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- dict_baltime[count] = dict_baltime[count] + dict_bal[key]
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- else:
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- dict_baltime[count] = dict_bal[key]
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- else:
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- pass
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- count += 1
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- x >>= 1 #右移一位
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-
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- dict_baltime=dict(sorted(dict_baltime.items(),key=lambda dict_baltime:dict_baltime[0]))
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- for key in dict_baltime: #解析均衡的电芯编号
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- if self.celltype==1: #科易6040
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- if key<14:
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- dict_baltime1[key]=dict_baltime[key]
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- elif key<18:
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- dict_baltime1[key-1]=dict_baltime[key]
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- else:
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- dict_baltime1[key-3]=dict_baltime[key]
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- elif self.celltype==1: #科易4840
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- if key<4:
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- dict_baltime1[key-1]=dict_baltime[key]
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- elif key<8:
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- dict_baltime1[key-1]=dict_baltime[key]
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- elif key<14:
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- 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,'SOH[%]'])
|
|
|
- capacity=self.param.Capacity*batsoh/100
|
|
|
- else:
|
|
|
- batsoh=self.df_soh.loc[len(self.df_soh)-1,'soh']
|
|
|
- capacity=self.param.Capacity*batsoh/100
|
|
|
-
|
|
|
- #参数初始化
|
|
|
- if 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,'SOH[%]'])
|
|
|
- capacity=self.param.Capacity*batsoh/100
|
|
|
- else:
|
|
|
- batsoh=self.df_soh.loc[len(self.df_soh)-1,'soh']
|
|
|
- capacity=self.param.Capacity*batsoh/100
|
|
|
- #参数初始化
|
|
|
- if 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 and abs(self.packcrnt[i+1]) < 0.1:
|
|
|
- delttime=(self.bmstime[i]-self.bmstime[i-1]).total_seconds()
|
|
|
- standingtime=standingtime+delttime
|
|
|
- standingtime1=standingtime1+delttime
|
|
|
- self._celltemp_weight(i)
|
|
|
-
|
|
|
- #长时间静置法计算内短路-开始.....................................................................................................................................
|
|
|
- if firsttime==1:
|
|
|
- if standingtime>self.StandardStandingTime: #静置时间满足要求
|
|
|
- standingtime=0
|
|
|
- cellvolt_now=self._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 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:
|
|
|
- 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=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:
|
|
|
- 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_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 12<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
|
|
|
-
|
|
|
- #获取充电数据——开始..............................................................................................................
|
|
|
- try:
|
|
|
- balstat=int(self.df_bms.loc[i,'单体均衡状态']) #统计均衡状态
|
|
|
- if balstat>0.5:
|
|
|
- bal_step=(self.bmstime[i+1]-self.bmstime[i]).total_seconds() #均衡步长
|
|
|
- bal_step=int(bal_step)
|
|
|
- if str(balstat) in dict_bal2.keys():
|
|
|
- dict_bal2[str(balstat)]=dict_bal2[str(balstat)]+bal_step
|
|
|
- else:
|
|
|
- dict_bal2[str(balstat)]=bal_step
|
|
|
- else:
|
|
|
- pass
|
|
|
- except:
|
|
|
- dict_bal2={}
|
|
|
-
|
|
|
- #判断充电状态
|
|
|
- if self.packcrnt[i]<=-1 and self.packcrnt[i+1]<=-1 and self.packcrnt[i-1]<=-1:
|
|
|
- if charging==0:
|
|
|
- if self.bms_soc[i]<41:
|
|
|
- cellvolt_now=self._cellvolt_get(i)
|
|
|
- if min(cellvolt_now)<self.param.CellFullChrgVolt-0.15:
|
|
|
- charging=1
|
|
|
- chrg_start=i
|
|
|
- else:
|
|
|
- pass
|
|
|
- else:
|
|
|
- pass
|
|
|
-
|
|
|
- else: #充电中
|
|
|
- cellvolt_now=self._cellvolt_get(i)
|
|
|
- if (self.bmstime[i+1]-self.bmstime[i]).total_seconds()>180 or (self.packcrnt[i]>self.param.Capacity/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
|
|
|
- charging=0
|
|
|
- continue
|
|
|
- elif min(cellvolt_now)>self.param.CellFullChrgVolt-0.13: #电压>满充电压-0.13V，即3.37V
|
|
|
- self._celltemp_weight(i)
|
|
|
- if i-chrg_start>10 and self.celltemp>20:
|
|
|
- chrg_end=i+1
|
|
|
- charging=0
|
|
|
-
|
|
|
- #计算漏电流值...................................................................
|
|
|
- if firsttime2==1:
|
|
|
- firsttime2=0
|
|
|
- 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 min(cellvolt_now)>self.param.CellFullChrgVolt-0.1: #电压>满充电压
|
|
|
- # self._celltemp_weight(i)
|
|
|
- # if i-chrg_start>10 and self.celltemp>10:
|
|
|
- # chrg_end=i+1
|
|
|
- # charging=0
|
|
|
-
|
|
|
- # #计算漏电流值...................................................................
|
|
|
- # if firsttime2==1:
|
|
|
- # dict_baltime={}
|
|
|
- # 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_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
|
|
|
- # 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
|
|
|
- else:
|
|
|
- pass
|
|
|
- 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
|
