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Citation:
　Yunsai Chen,Qiangguo Niu,Zengkai Liu,et al.Failure Modes and Reliability Analysis of Autonomous Underwater Vehicles–A Review[J].Journal of Marine Science and Application,2025,(5):900-924.[doi:10.1007/s11804-025-00627-2]
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Failure Modes and Reliability Analysis of Autonomous Underwater Vehicles–A Review

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Title:
Failure Modes and Reliability Analysis of Autonomous Underwater Vehicles–A Review
Author(s):
Yunsai Chen1; 2;  Qiangguo Niu1; 2;  Zengkai Liu1; 2;  Boyuan Huang1; 2;  Tianyu Xie1; 2;  Liujun Zhong1; 2;  Danyang Wan1; 2;  Zheng Wang1; 2
Affilations:
Author(s):
Yunsai Chen1; 2;  Qiangguo Niu1; 2;  Zengkai Liu1; 2;  Boyuan Huang1; 2;  Tianyu Xie1; 2;  Liujun Zhong1; 2;  Danyang Wan1; 2;  Zheng Wang1; 2
1. College of Shipbuilding, Harbin Engineering University, Harbin 150001, China;
2. Qingdao Innovation and Development Base, Harbin Engineering University, Qingdao 266000, China
Keywords:
Autonomous underwater vehicles|Reliability analysis|Failure modes classification|Human reliability analysis|AI-based reliability analysis|Literature review
分类号:
-
DOI:
10.1007/s11804-025-00627-2
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.

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Memo

Memo:
Received date:2024-3-4;Accepted date:2025-3-17。<br>Foundation item:The National Key R & D Program Projects (Grant No. 2022YFC2803601), the Natural Science Foundation of Shandong Province (Grant No. ZR2021YQ29), the Natural Science Foundation of Heilongjiang Province (Grant No. YQ2024E036), and the Taishan Scholars Project (Grant No. tsqn202312317).<br>Corresponding author:Zengkai Liu,E-mail:liuzengk@hrbeu.edu.cn
Last Update: 2025-10-24