KPI-related monitoring approach for powertrain system in hybrid electric vehicles

Abstract

This paper introduces a novel monitoring method related to key-performance-indicators (KPIs), specifically tailored for the hybrid electric vehicle (HEV) powertrain system. The proposed method establishes a new KPI that better reflects the performance of the HEV powertrain system. Through the application of partial least squares and contribution plot method, it excels in minimizing data scale and precisely monitoring HEV powertrain faults. Diverging from current methodologies, this method demands minimal prior knowledge and solely relies on previously observed HEV data. The simulation results demonstrate the method's capability to detect engine and motor overheating faults while accurately diagnosing their root causes. In summary, this innovative method marks a significant departure from existing approaches, providing a robust and powerful tool for state monitoring in the HEV powertrain system.