Brake failure and fault detection in heavy vehicles : trends, challenges, and research gap from a systematic literature review

Abstract

Brake failure in heavy vehicles, particularly trucks and buses, continues to be a major contributor to severe traffic accidents, especially on long downhill routes where braking systems are subjected to sustained thermal and mechanical loads. Although numerous approaches for brake fault detection and diagnosis have been proposed over the past decade, most studies remain confined to laboratory environments or simulation-based analyses and predominantly target passenger vehicles. This systematic literature review provides a critical examination of existing research on brake failure and fault detection, with a specific focus on heavy vehicle applications. A structured search of the Scopus database was conducted using the keywords (“brake failure” OR “brake fault”). AND vehicle*, covering publications from 2016 to 2025. Following the PRISMA framework, 32 relevant articles were selected from an initial set of 134 records. The selected studies were analyzed in terms of methodological approaches, key findings, reported limitations, and research contributions. The results reveal a notable increase in research activity since 2020, driven mainly by sensor-based techniques, physical modeling, and artificial intelligence–based methods. However, studies explicitly addressing heavy vehicles and validated under real-road operating conditions remain limited. This review synthesizes current research trends, clarifies unresolved gaps, and outlines future research directions, particularly in the areas of multi-sensor data integration, intelligent diagnostic algorithms, and Digital Twin–enabled predictive maintenance, to enhance brake failure detection and overall heavy vehicle safety.