Unmanned underwater vehicle semi-physical simulation and performance verification method and system
By constructing a dynamically adaptable unmanned underwater vehicle (UUV) simulation environment and gradient test conditions, combined with dynamic weight allocation and iterative optimization, the problem of the disconnect between the actual hardware and the virtual simulation model was solved, achieving comprehensive performance verification and accurate optimization suggestions, thus improving the efficiency of UUV performance verification.
Patent Information
- Application Number
- CN202610646140.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-05-12
- Publication Date
- 2026-07-24
AI Technical Summary
In existing hardware-in-the-loop simulation and performance verification of unmanned underwater vehicles, the physical hardware and the virtual simulation model are disconnected, making it impossible to achieve real-time parameter correction and dynamic adaptation of operating status. The deviation quantification results of data comparison and analysis do not match the actual working conditions, and cannot provide specific performance optimization suggestions. The verification process is broken and cannot support the performance improvement of the underwater vehicle.
By acquiring multi-source heterogeneous basic data, a dynamic adaptation environment for physical hardware and virtual simulation models is constructed, gradient test conditions are generated, and data deviation is quantitatively compared and analyzed using dynamic weight allocation and iterative optimization methods. Performance optimization suggestions are generated in combination with the design parameters of the submarine body, and iterative verification is carried out.
It achieves high consistency between the physical hardware and the virtual simulation model, fully covers the actual operating conditions of the submarine, accurately identifies performance shortcomings, provides targeted optimization suggestions, and improves the practical value and execution efficiency of the verification work.