基于数字孪生的智能网联汽车预测性维护技术研究

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中图分类号：U463.6 文献标识码：A 文章编号：1003-8639（2025）09-0028-03

Research onPredictiveMaintenanceTechnology for Intelligent Connected Vehicles Based onDigital Twins

HuWuchao，Gu Shuaijie （Ruzhou Polytechnic College，Ruzhou ， China）

【Abstract】To enhance the intellgence level and operational reliabilityof intelligent connected vehicle operation and maintenance，and to establish an eficient and precise predictive maintenance patern.By using he digital twin modeling method，a dynamic mapping model of keycomponents is built，and algorithms suchasparticle filteringand long short-term memory neural networks are combined to complete state recognition and life prediction. Taking the real vehicle platform as an example，multi-scenario verification is implemented to study the health assessment and maintenance response measures of key components during the degradation and evolution process. This technology features excellent fault early warning accuracy and robustnessin environmental tolerance，providing a feasible technical channel for intelligent operation and maintenance.

【Key words】intelligent connected vehicles;digital twin;predictive maintenance;LSTM

0 引言

随着智能网联汽车集成度与复杂性不断升高，其核心部件在运行时要面对更高的负载和环境产生的扰动。（剩余4052字）