Method and system for monitoring hybrid energy storage state of battery based on big data processing

A method for monitoring hybrid energy storage state of battery based on big data processing, characterized in that a hybrid energy storage battery status monitoring system applied to big data processing, the method includes:

• Charging sample information collection step:
• Obtain the health state parameters of multiple hybrid energy storage batteries in different charging states at different times to form a charging information element matrix X1. The information elements of the row vector of the charging information element matrix X1 include:
• charging voltage Ui1, recharging current Ai1 Charging power Wi1 Charging temperature Ti1 Charging internal resistance Ri1, Expressed as xi1={Ui1, Ai1, Wi1, Ti1, Ri1)}, xil Represents health status data at different moments during charging;
• Discharge sample information collection step:
• Obtain the health state parameters of multiple hybrid energy storage batteries in the discharge state at different times to form a discharge information element matrix X2. The information elements of the row vector of the discharge information element matrix X2 include:
• discharge voltage Ui2. Discharge current Ai2 Discharge power Wi2 Discharge temperature Ti2 Discharge internal resistance Ri2, Expressed as xi2={Ui2, Ai2, Wi2, Ti2, Ri2}, xi2 Represents the health status data at different moments during discharge;
• Data sorting and fusion steps:
• Preprocess the health status data in the charging state and the health status data in the discharge state, including:
• S1. Select the status data in the corresponding proportion space according to the preset threshold ratio, and delete obviously unqualified data;
• S2. Complete the null value data through the average method;
• S3. Fusion of the charging sample data and discharge sample data at the corresponding time, expressed as
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• Get the health status matrix X at the corresponding moment;
• Estimation steps of hybrid energy storage battery SOH:
• input the data in the health state matrix X into the pre-trained health state model to predict the SOH of the hybrid energy storage battery;
• The steps to evaluate the health level of the hybrid energy storage battery:
• According to the SOH of the hybrid energy storage battery, search the corresponding health level from the preset database.