TITLE:
Methodology for Precise Diagnostics of Intermittent Faults in Powertrain and Electronic Systems of Sports and Luxury Cars (Oscilloscope, Can/Lin, Thermal Imaging) with Plain Client Explanations
AUTHORS:
Hryhorii Popenko
KEYWORDS:
Intermittent Faults, CAN FD, LIN, Oscilloscope, Infrared Thermography, Powertrain, ECU, Diagnostics, Physical Layer, Plain Client Explanations
JOURNAL NAME:
Voice of the Publisher,
Vol.12 No.2,
April
29,
2026
ABSTRACT: Intermittent faults in powertrain and electronic subsystems continue to be a persistent source of cost, delay, and reputational risk in sports and luxury vehicles, where network density, feature content, and customer expectations are high. The article introduces a compact, field-ready methodology that combines physical-layer oscilloscope measurements, CAN/CAN-FD/LIN bus analytics, and infrared thermography to locate elusive faults more quickly and with fewer false negatives than traditional OBD-only diagnostics. A structured synthesis of empirical studies on intermittent short circuits, ground faults, connector degradation, and thermal anomalies supports the protocol and its chosen metrics. A small, pragmatic, quasi-experimental pilot is presented as a use case, where six units (four vehicles and two instrumented rigs with induced faults) are evaluated using both a control workflow and a triangulated workflow, with time-to-detect and detection rate as primary metrics. The article also features a clientfacing explainability module that transforms test findings into concise, plain-language reports. The synthesis shows that combining oscilloscope timing and amplitude checks (including CAN-FD loop delay and recessive bit width), framelevel error statistics and counters, and thermal imaging of connectors and power paths reduces “no fault found” outcomes and speeds up verification. In practice, this approach aligns with recent research on CAN physical layers, ECU ground-fault diagnostics, connector intermittency, and thermography-based condition monitoring across automotive components (Hancock, 2020; Schreiner, 2015; Du et al., 2023; Ahmad et al., 2014; Wang et al., 2024; Głowacz, 2023; Xu et al., 2024).