Battery health prediction method and system based on cloud edge collaboration

• Main Authors: SUN ZHENDONG, WANG JIAN, CHEN RUIYANG, KHOR, SWEE LOONG, GUI WANGSHENG
• Format: Patent
• Language: Chinese; English
• Published: 22.09.2023
• Subjects: CALCULATING; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; ELECTRIC DIGITAL DATA PROCESSING; MEASURING; MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR; TESTING

The invention discloses a battery health prediction method and system based on cloud edge collaboration. The method comprises the following steps: acquiring and storing battery operation data and health state calibration data uploaded by an edge end in real time; preprocessing the battery operation data to obtain first type health feature data; and inputting the first type of health feature data and the battery charging and discharging equivalent cycle number into the trained battery health prediction cloud model to obtain a first prediction value of battery health corresponding to the current moment. Through simultaneous deployment of the battery health prediction cloud model and the local health prediction correction model, on one hand, the data processing efficiency is improved by applying the bidirectional GRU recurrent neural network to the health prediction task of the battery, and on the other hand, the computing processing amount and the storage occupation amount of the side end are reduced by collabo