Artificial neural network-based highest surface temperature prediction method of secondary battery

The present invention relates to a secondary battery of the highest surface temperature prediction algorithm based on artificial neural networks, battery thermal management system belongs to the technical field. The secondary battery in high and low temperature test chamber, connected to the charge and discharge test machine; charging the battery is discharged; monitoring changes in the maximum temperature of the battery surface during the charging process; an input by setting Back-Propagation neural network model, output, number of neurons, layers, transfer function and training algorithm to either build the model; model training data for the prediction model can be applied; the maximum surface temperature of the battery charging process at ambient temperature by other models to predict. Model of the invention to apply it is simple, easy to control parameters, useful results; the maximum surface temperature of the battery at different ambient temperatures to predict, safe and effective to provide a guarantee for the working cell and a battery thermal management system.