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<p>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.</p>

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

  • 期刊论文

  • 发表日期：

    2025年5月10日

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  • Yunsai Chen,
  • Qiangguo Niu,
  • Zengkai Liu,
  • Boyuan Huang,
  • Tianyu Xie,
  • Liujun Zhong,
  • Danyang Wan,
  • Zheng Wang

摘要

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.