摘 要
随着智能网联汽车技术的快速发展，车辆远程故障诊断与维护服务成为提升车辆安全性和可靠性的重要手段。本文针对智能网联汽车远程故障诊断与维护服务展开研究，旨在构建高效、准确且实时性强的故障诊断与维护服务体系。基于车联网平台，融合大数据分析、机器学习算法及边缘计算技术，提出一种多源异构数据驱动的故障诊断模型，该模型能够对车辆运行状态进行实时监测并精准定位故障源。通过实车测试验证了所提方法的有效性，在故障识别率和诊断速度方面较传统方法有显著提升。研究结果表明，利用智能网联技术可实现对车辆故障的早期预警和快速响应，有效降低维修成本并提高用户体验。此外，本研究还设计了一套完整的远程维护服务流程，为车主提供个性化、智能化的售后服务支持，进一步推动了智能网联汽车产业的发展。创新点在于将多种先进技术有机结合起来，解决了复杂工况下故障诊断难题，并首次提出了适用于智能网联汽车的远程维护服务框架，为后续研究奠定了理论基础和技术支撑。
关键词：智能网联汽车；远程故障诊断；多源异构数据；机器学习；边缘计算
Abstract
With the rapid development of intelligent connected vehicle (ICV) technology, remote fault diagnosis and maintenance services have become crucial for enhancing vehicle safety and reliability. This study focuses on developing an efficient, accurate, and real-time fault diagnosis and maintenance service system for ICVs. By leveraging a vehicular network platform, this research integrates big data analytics, machine learning algorithms, and edge computing technologies to propose a multi-source heterogeneous data-driven fault diagnosis model. The proposed model enables real-time monitoring of vehicle operation status and precise identification of fault sources. Experimental validation through in-vehicle testing demonstrates the effectiveness of the proposed method, showing significant improvements in fault recognition rates and diagnostic speed compared to traditional methods. The results indicate that utilizing ICV technology can achieve early warning and rapid response to vehicle faults, effectively reducing maintenance costs and improving user experience. Additionally, this study designs a comprehensive remote maintenance service process, providing personalized and intelligent after-sales support for vehicle owners, thereby further promoting the development of the ICV industry. The innovation lies in organically combining multiple advanced technologies to address complex fault diagnosis challenges under various operating conditions and proposing a novel remote maintenance service fr amework specifically designed for ICVs, laying a theoretical foundation and technical support for future research.
Keywords: Intelligent Connected Vehicle；Remote Fault Diagnosis；Multi-source Heterogeneous Data；Machine Learning；Edge Computing
目 录
摘 要 I
Abstract II
引言 1
一、智能网联汽车远程诊断技术基础 1
（一）远程故障诊断系统架构 1
（二）关键通信技术分析 1
（三）数据采集与预处理方法 2
二、故障诊断算法与模型研究 2
（一）常见故障模式识别 2
（二）机器学习算法应用 3
（三）实时诊断模型构建 3
三、维护服务系统设计与实现 4
（一）远程维护服务平台架构 4
（二）用户交互界面设计 4
（三）维护任务调度优化 5
四、安全性与可靠性保障 5
（一）数据传输安全保障 5
（二）系统容错机制研究 6
（三）可靠性评估指标体系 6
结 论 7
致 谢 8
参考文献 9
