Design of Intelligent Fault Diagnosis System for New Energy Vehicles Based on Deep Learning

The development of new energy vehicle industry puts forward new challenges to fault diagnosis technology. In this paper, an intelligent fault diagnosis system based on deep learning is designed to achieve intelligent diagnosis of key vehicle components through an improved residual neural network structure. The dual attention mechanism is innovatively proposed to enhance the feature extraction capability, and a complete fault diagnosis solution is constructed. The real vehicle test verification shows that the system has strong engineering application value and can provide effective technical support for the intelligent operation and maintenance of new energy vehicles.