基于故障树与数据流分析的新能源汽车高压配电故障诊断研究

Research on High Voltage Distribution Fault Diagnosis of New Energy Vehicles Based on Fault Tree and Data Flow Analysis

摘要: 新能源汽车作为我国战略性新兴产业发展迅速，但其高压配电系统的开发、调试与维护存在较高难度和危险性，故障诊断技术研究尤为关键。本文以某型号帝豪电动汽车为研究对象，通过文献调研与案例分析，系统剖析高压配电系统的结构组成与工作原理，梳理高压无法上电、高压互锁等典型故障类型及成因。采用数据流分析、故障树分析(FTA)等多维度诊断方法，结合优先级排查策略，构建涵盖高压互锁、动力系统、驱动电机系统的故障检修体系，并通过实际案例验证诊断策略的有效性。研究成果可降低电动汽车维护与研发成本，提升车辆动力性与安全性，为新能源汽车行业的安全发展提供技术支撑，为汽车企业创造经济效益。

Abstract: As a strategic emerging industry in China, new energy vehicles have achieved rapid development. Nevertheless, the development, commissioning, and maintenance of their high-voltage power distribution systems involve considerable complexity and potential risks, rendering research on fault diagnosis technology particularly critical. Taking a specific model of Emgrand electric vehicle as the research subject, this paper systematically analyzes the structural composition and operating principles of the high-voltage power distribution system through literature review and case studies, and summarizes typical fault types and their causes, such as high-voltage power-on failure and high-voltage interlock (HVIL) malfunctions. By adopting multi-dimensional diagnostic approaches, including data flow analysis and Fault Tree Analysis (FTA), combined with a priority-based troubleshooting strategy, a comprehensive fault maintenance system covering high-voltage interlock, power system, and drive motor system is constructed. The effectiveness of the proposed diagnostic strategy is validated through practical cases. The research findings can reduce the maintenance and R&D costs of electric vehicles, enhance their power performance and safety, provide technical support for the safe development of the new energy vehicle industry, and generate economic benefits for automotive enterprises.