data_analyze_platform/USER/SPF/01qixiang/04BatSoc/main.py

#coding=utf-8
import sys
import datetime
import pandas as pd
from LIB.BACKEND import DBManager, Log
from sqlalchemy import create_engine
import time, datetime
from apscheduler.schedulers.blocking import BlockingScheduler
from LIB.MIDDLE.CellStateEstimation.Common.V1_0_1 import DBDownload
from LIB.MIDDLE.CellStateEstimation.Common.V1_0_1 import log

#...................................SOC计算函数......................................................................................................................
def soc_cal():
    import CBMSBatSoc
    global SNnums
    global df_ram

    start=time.time()
    end_time=datetime.datetime.now()-datetime.timedelta(seconds=10)
    start_time=end_time-datetime.timedelta(seconds=70)
    start_time=start_time.strftime('%Y-%m-%d %H:%M:%S')
    end_time=end_time.strftime('%Y-%m-%d %H:%M:%S')

    for sn in SNnums:
        if 'PK500' in sn:
            celltype=1 #6040三元电芯
        elif 'PK502' in sn:
            celltype=2 #4840三元电芯
        elif 'K504B' in sn:
            celltype=99    #60ah林磷酸铁锂电芯
        elif 'MGMLXN750' in sn:
            celltype=3 #力信50ah三元电芯
        elif 'MGMCLN750' or 'UD' in sn: 
            celltype=4 #CATL 50ah三元电芯
        else:
            print('SN：{}，未找到对应电池类型！！！'.format(sn))
            continue
            # sys.exit()
        
        # sn='PK504B10100003033'
        # celltype=2
        # start_time='2021-05-02 09:12:26'
        # end_time='2021-06-03 19:12:26'
        # # df_bms= pd.read_csv(r'D:\Platform\platform_python\data_analyze_platform\USER\spf\01qixiang\98Download\\'+'BMS_'+sn+'.csv',encoding='GB18030')

        #读取原始数据库数据........................................................................................................................................................
        dbManager = DBManager.DBManager()
        df_data = dbManager.get_data(sn=sn, start_time=start_time, end_time=end_time, data_groups=['bms'])
        df_bms = df_data['bms']
        # df_bms.to_csv(r'D:\Platform\platform_python\data_analyze_platform\USER\spf\01qixiang\99Result\\''BMS_'+sn+'.csv',encoding='GB18030')

        #读取结果数据库数据........................................................................................................................................................
        host='rm-bp10j10qy42bzy0q77o.mysql.rds.aliyuncs.com'
        port=3306
        db='qx_cas'
        user='qx_read'
        password='Qx@123456'
        mode=1
        tablename='cellstateestimation_soh'
        DBRead=DBDownload.DBDownload(host, port, db, user, password, mode)
        with DBRead as DBRead:
            df_soh=DBRead.getdata(param='time_st,sn,soh', tablename=tablename, sn=sn, timename='time_sp', st=start_time, sp=end_time)
        
        if celltype==99:
            tablename='cellstateestimation_uniform_socvoltdiff'
            with DBRead as DBRead:
                df_socdiff=DBRead.getdata(param='time,sn,cellsoc_diff', tablename=tablename, sn=sn, timename='time', st=start_time, sp=end_time)
        else:
            df_socdiff=pd.DataFrame()

        # print(df_bms)
        # print(df_soh)
        
        #socram存储...............................................................................................................................................................
        if not df_bms.empty:
            df_ram_sn=df_ram[df_ram['sn']==sn]

            if df_ram_sn.empty:
                with open(r'D:\Platform\platform_python\data_analyze_platform\USER\spf\01qixiang\04BatSoc\\'+'soc_'+str(sn)+'.txt','a') as file:
                    file.write(str(tuple(df_ram_sn.columns))+'\n')
            
            BatSoc=CBMSBatSoc.BatSoc(sn,celltype,df_bms,df_soh,df_ram_sn,df_socdiff)
            df_res, df_ram_sn=BatSoc.batsoc()
            if not df_ram_sn.empty:
                sn_index=df_ram.loc[df_ram['sn']==sn].index
                df_ram=df_ram.drop(index=sn_index)
                df_ram=df_ram.append(df_ram_sn)
                df_ram.reset_index(inplace=True,drop=True)     #重置索引
            
            # print(df_res)
            # print(df_ram)

            if not df_ram_sn.empty:
                with open(r'D:\Platform\platform_python\data_analyze_platform\USER\spf\01qixiang\04BatSoc\\'+'soc_'+str(sn)+'.txt','a') as file:
                    file.write(str(tuple(df_ram_sn.iloc[-1]))+'\n')
                    
        
        end=time.time()
        print(end-start)
        
#...............................................主函数.......................................................................................................................
if __name__ == "__main__":

    excelpath=r'D:\Platform\platform_python\data_analyze_platform\USER\spf\01qixiang\sn-20210903.xlsx'
    SNdata_6060 = pd.read_excel(excelpath, sheet_name='科易6060')
    SNdata_6040 = pd.read_excel(excelpath, sheet_name='科易6040')
    SNdata_4840 = pd.read_excel(excelpath, sheet_name='科易4840')
    SNdata_L7255 = pd.read_excel(excelpath, sheet_name='格林美-力信7255')
    SNdata_C7255 = pd.read_excel(excelpath, sheet_name='格林美-CATL7255')
    SNdata_U7255 = pd.read_excel(excelpath, sheet_name='优旦7255')
    SNnums_6060=SNdata_6060['SN号'].tolist()
    SNnums_6040=SNdata_6040['SN号'].tolist()
    SNnums_4840=SNdata_4840['SN号'].tolist()
    SNnums_L7255=SNdata_L7255['SN号'].tolist()
    SNnums_C7255=SNdata_C7255['SN号'].tolist()
    SNnums_U7255=SNdata_U7255['SN号'].tolist()
    SNnums= SNnums_6060 + SNnums_L7255 + SNnums_C7255 + SNnums_6040 + SNnums_4840 + SNnums_U7255
    SNnums=['UD02030118B4C0046','MGMCLN750N215I005','PK504B10100004327','PK504B10100003032','PK504B00100004172','PK504B10100003033','PK50001A100000222']
    #

    #log信息配置
    mylog=log.Mylog('log_soc.txt','error')
    mylog.logcfg()

    #参数初始化.........................................................................................................................................................................
    column_name=['time', 'sn', 'bms_soc', 'soc','cellsocmin','cellsocmax','standingtime','rampackcrnt','ramcellvoltmin','ramcellvoltmax','kocellvoltmin','kocellvoltmax','ocvweight','as_accum','socstep']
    df_ram=pd.DataFrame(columns=column_name)

    scheduler = BlockingScheduler()
    scheduler.add_job(soc_cal, 'interval', seconds=60, id='soc_job')
    
    try:
        
        scheduler.start()

    except Exception as e:
        scheduler.shutdown()
        print(repr(e))
        mylog.logopt(e)