New energy automobile intelligent network connection remote diagnosis and fault early warning system

By building a personalized fault warning model and combining deep learning and intelligent networking technology, the false alarm and missed alarm problems of the new energy vehicle fault warning system have been solved, accurate remote diagnosis and warning have been achieved, and user experience and safety have been improved.

CN120628628AInactive Publication Date: 2025-09-12HUAIAN SENIOR VOCATIONAL & TECH SCHOOL
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Patent Information

Application Number
CN202510828795.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-06-20
Publication Date
2025-09-12
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

The existing new energy vehicle fault warning system does not fully consider personalized factors such as user driving habits, vehicle usage environment and historical fault records, resulting in frequent false alarms and missed alarms, affecting user experience and driving safety.

Method used

Establish a personalized early warning model based on user driving habits, vehicle usage environment and historical fault records. Through data collection, analysis and transmission, use intelligent network technology to achieve remote diagnosis, and use a deep learning framework to build a personalized fault early warning model.

Benefits of technology

It achieves the accuracy and timeliness of fault warning, avoids false alarms and missed alarms, ensures driving safety, improves user satisfaction and corporate competitiveness, and has good adaptability and scalability.

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Abstract

The invention discloses a new energy automobile intelligent network connection remote diagnosis and fault early warning system, and relates to the technical field of new energy automobiles, the system comprises a data acquisition module, a data transmission module, a data analysis and processing module, a personalized early warning model construction module and a fault diagnosis and early warning module; the data acquisition module is used for acquiring driving habit data, vehicle use environment data and historical fault record data of the new energy vehicle; according to the method, a personalized fault early warning model is established for each vehicle by collecting and analyzing multi-dimensional data such as user driving habits, vehicle use environments and historical fault records, accurate early warning of new energy vehicle faults is realized, and by collecting and analyzing the multi-dimensional data, the personalized difference of vehicle use is fully considered, so that the accuracy of new energy vehicle fault early warning is improved. Compared with a traditional general fault early warning system, the accuracy and timeliness of fault early warning are greatly improved, and the situations of false alarm and missing alarm are effectively avoided.
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