Failure Modes and Reliability Analysis of Autonomous Underwater Vehicles–A Review

Abstract

Autonomous Underwater Vehicles (AUVs) are pivotal for deep-sea exploration and resource exploitation, yet their reliability in extreme underwater environments remains a critical barrier to widespread deployment. Through systematic analysis of 150 peer-reviewed studies employing mixed-methods research, this review yields three principal advancements to the reliability analysis of AUVs. First, based on the hierarchical functional division of AUVs into six subsystems (propulsion system, navigation system, communication system, power system, environmental detection system, and emergency system), this study systematically identifies the primary failure modes and potential failure causes of each subsystem, providing theoretical support for fault diagnosis and reliability optimization. Subsequently, a comprehensive review of AUV reliability analysis methods is conducted from three perspectives: analytical methods, simulated methods, and surrogate model methods. The applicability and limitations of each method are critically analyzed to offer insights into their suitability for engineering applications. Finally, the study highlights key challenges and research hotpots in AUV reliability analysis, including reliability analysis under limited data, AI-driven reliability analysis, and human reliability analysis. Furthermore, the potential of multi-sensor data fusion, edge computing, and advanced materials in enhancing AUV environmental adaptability and reliability is explored.

Keywords

Autonomous underwater vehicles / Reliability analysis / Failure modes classification / Human reliability analysis / AI-based reliability analysis / Literature review

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