Research on Insulation Fault Early Warning and Active Service for New Energy Vehicles

AUTO ELECTRIC PARTS ›› 2026, Vol. 1 ›› Issue (3) : 17-19.

New Energy

Yu Tiantian

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Abstract

High-voltage system insulation faults represent a critical issue threatening the safety and user experience of new energy vehicles (NEVs). The traditional passive after-sales model struggles to address their suddenness and complexity, necessitating a transition towards a data-driven active service paradigm. This paper focuses on the high-value scenario of insulation fault early warning, systematically constructing an integrated after-sales big data platform encompassing data collection, real-time analysis, intelligent decision-making, and closed-loop management. The paper elaborates on the platform's layered architecture, including the data, computing, analytics, and application layers, and specifically investigates the development path of an early warning model that integrates deterministic rules with machine learning algorithms. By detailing the entire business closed-loop process from warning discovery and remote diagnosis to decision-making and push-notification, the study validates the platform's effectiveness and practical value in achieving early fault identification, precise intervention, and process optimization. It provides a key methodology and implementation case for automotive manufacturers building intelligent after-sales systems.

Key words

NEVs / big data platform / fault early warning / insulation fault / active service / predictive maintenance

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Yu Tiantian. Research on Insulation Fault Early Warning and Active Service for New Energy Vehicles[J]. AUTO ELECTRIC PARTS. 2026, 1(3): 17-19

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