data_analyze_platform/USER/SPF/01qixiang/09Behave/CBMSBatBehave.py

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

class BatBehave:
    def __init__(self,sn,celltype,df_bms):  #参数初始化

        self.sn=sn
        self.celltype=celltype
        self.param=BatParam.BatParam(celltype)
        self.df_bms=df_bms

        df_bms['时间戳']=pd.to_datetime(df_bms['时间戳'], format='%Y-%m-%d %H:%M:%S')
        
        self.packcrnt=df_bms['总电流[A]']*self.param.PackCrntDec
        self.bmstime= df_bms['时间戳']
        self.packsoc=df_bms['SOC[%]']

        self.cellvolt_name=['单体电压'+str(x) for x in range(1,self.param.CellVoltNums+1)]
        # othertemp=['其他温度'+str(x) for x in range(1,self.param.OtherTempNums+1)]
        self.celltemp_name=['单体温度'+str(x) for x in range(1,self.param.CellTempNums+1)]
        # self.celltemp_name=celltemp+othertemp

    
    def behave(self):
        if self.celltype<=50:
            df_res=self._bat_behave()
            return df_res    
        else:
            df_res=self._bat_behave()
            return df_res

    
    #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
    
    #筛选充电数据.......................................................................................................
    def _chrgdata(self):   
        self.ComeIn=[]
        self.ChgStart=[]
        self.ChgEnd=[]
        self.ComeOut=[]
        if len(self.df_bms)>10:
            state=0
            for i in range(3, len(self.bmstime) - 3):
                if state==0:
                    if abs(self.packcrnt[i])<=0.1:
                        self.ComeIn.append(i)
                        state=1
                elif state==1:
                    if self.packcrnt[i]<=-10 and self.packcrnt[i+1]<=-10:
                        self.ChgStart.append(i)
                        state=2
                    elif self.packcrnt[i]>1:
                        state=0
                        self.ComeIn.pop()
                    else:
                        pass
                elif state==2:
                    if self.packcrnt[i]>-0.1:
                        state=3
                        if (self.bmstime[i]-self.bmstime[self.ChgStart[-1]]).total_seconds()>300 and self.packsoc[i]-self.packsoc[self.ChgStart[-1]]>5:
                            self.ChgEnd.append(i)
                        else:
                            state=0
                            self.ComeIn.pop()
                            self.ChgStart.pop()
                    else:
                        pass
                else:
                    if self.packcrnt[i]>1:
                        state=0
                        self.ComeOut.append(i)
                    else:
                        pass
        else:
            pass

    #..........................................电池诊断功能..................................................................
    def _bat_behave(self):
        df_res=pd.DataFrame(columns=['sn','time_in', 'time_st', 'time_sp', 'time_out', 'soc_st', 'soc_sp'])
        self._chrgdata()
        if len(self.ComeOut)>0:
            for i in range(len(self.ChgEnd)):
                df_res.loc[i]=[self.sn, self.bmstime[self.ComeIn[i]], self.bmstime[self.ChgStart[i]], self.bmstime[self.ChgEnd[i]], self.bmstime[self.ComeOut[i]], self.packsoc[self.ChgStart[i]], self.packsoc[self.ChgEnd[i]]]
            return df_res
        else:
            return pd.DataFrame()