Thermal-Aware Functional Safety Analysis of Automotive LED Drivers: FMEDA for Junction Temperature-Induced Failures

Thermal overstress is the primary accelerator of random hardware failures in Automotive Head Lamp LED drivers; yet, most Failure Modes, Effects, and Diagnostic Analyses (FMEDAs) still rely on room-temperature handbook data. This systematic review analysed 62 studies (2020–2025) to develop a thermal-aware FMEDA framework for automotive LED drivers. Out of 320 screened publications, 12 were included in the final analysis, covering buck, SEPIC, and matrix topologies. SaberRD simulations demonstrate >30 % variation in FIT rate under ±30 °C/s cycling in 100 W matrix headlamps, while diagnostic coverage (DC) erodes by up to 16 percentage points above 140 °C. This paper proposes a thermal-aware FMEDA framework that decomposes λ by failure mechanism, models DC as a function of temperature, and recalibrates β via spatial thermal-coupling analysis. The synthesis shows that bond-wire fatigue, capacitor electrolyte evaporation, and gate-oxide breakdown accelerate super-linearly above 140 °C. Co-simulation workflows that couple circuit, thermal, and reliability models can inject temperature-segmented λ and DC into FMEDA spreadsheets, satisfying ISO 26262 Clause 10. However, open datasets linking measured temperature profiles to safety metrics are scarce, and common-cause β factors are often assigned heuristically. The review proposes a thermal-aware FMEDA framework that decomposes failure rates by mechanism, expresses DC as a function of temperature, and recalibrates β via spatial thermal-coupling analysis. These findings guide design engineers toward sensor-integrated drivers, mission-profile-specific derating, and material upgrades, and urge regulators to mandate temperature-segmented reliability reporting. By bridging physics-of-failure evidence with functional-safety engineering, the study advances credible ASIL qualification for next-generation, high-power automotive LED lighting systems.