Smart ECU: Scalable On-Vehicle Deployment of Drivetrain Fault Classification Systems for Commercial Electric Vehicles

Abstract

We present Smart ECU, the first on-vehicle drivetrain fault classification solution for motor-reducers on commercial electric vehicles (EVs), designed to be scalable in mass production. To develop and validate this system, we collect real-world vibration data from seven different EV models (e.g. Hyundai IONIQ 5, KIA EV6) and over 19 drivetrains under diverse driving conditions. This work addresses key challenges in deploying motor-reducer fault classification functionality onto an extremely resource-constrained ECU environment, facilitating on-vehicle deployment of PHM solutions on commercially manufactured EVs. Specifically, we tackle the following challenges: (1) real-vehicle data collection, (2) development under tight ECU resource constraints, (3) class imbalance between normal and fault conditions, and (4) scalability of the fault classification system across different EV models with limited fault data availability. We deploy and evaluate Smart ECU on both intra-car and inter-car scenarios, showing strong generalization performance in both setups. The proposed method enables rapid development of fault classification for new vehicle designs without requiring fault data from customer usage, significantly shortening the deployment timeline. Our solution addresses both technical and industrial challenges in deploying ECU-based smart diagnostics for commercial EVs, while also demonstrating broader applicability beyond drivetrain systems to other critical vehicle components. To the best of our knowledge, this is the first work to (1) collect real-world motor-reducer fault data, (2) implement a lightweight fault classification algorithm on ECUs, and (3) demonstrate its scalability across various EV types. © 2025 Copyright held by the owner/author(s).