Embedded AI-Enabled Fault Detection System for Electric Vehicle Powertrains

作者：T. Adegbite, Shady S. Refaat, Mostafa Farrag, Amira Mohammed · 发表于：2025 IEEE 4th Industrial Electronics Society Annual On-Line Conference (ONCON) · 年份：2025 · DOI：10.1109/oncon68412.2025.11384182 · 被引用次数：1

The increasing adoption of electric vehicles (EVs) has heightened the demand for advanced safety and reliability solutions. This paper presents a Field Programmable Gate Array (FPGA)-based fault detection and diagnosis (FDD) framework tailored for EV powertrains. The proposed system leverages the FPGA's high-speed parallel processing, low latency, reconfigurability, and real-time capabilities to efficiently analyze large volumes of sensor data. To enhance adaptability under evolving fault conditions, an artificial intelligence (AI) model based on machine learning techniques is integrated on the FPGA, enabling accurate fault prediction and classification. The obtained simulation outcomes verify that the FPGA-based fault detection and diagnosis framework achieves 98.9% accuracy, exhibits faster response characteristics, and offers scalable implementation potential, thus enhancing both the safety and operational reliability of electric vehicles.