Affiliation:
1. State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle College of Mechanical and Vehicle Engineering Hunan University Changsha 410082 China
2. Wuxi Intelligent Control Research Institute of Hunan University Wuxi 214115 China
3. State Key Laboratory of Exploitation and Utilization of Deep‐Sea Mineral Resources Changsha Research Institute of Mining and Metallurgy Co., Ltd. Changsha 410012 China
Abstract
AbstractThe aim of this paper is to propose a novel method for identifying the hydrodynamic parameters of a deep‐sea mining vehicle during deployment and retrieval. The proposed approach combines numerical simulation with a nonlinear filter. Initially, a dedicated hydrodynamic model for the deployment and retrieval of the mining vehicle is constructed. The identification process commences with simulations based on computational fluid dynamics (CFD). This approach utilizes CFD to simulate the motion of the deep‐sea mining vehicle during deployment and retrieval, employing an implicit solution approach to analyze its motion in Heave and Yaw degrees of freedom under periodic external forces. Consequently, this provides hydrodynamic performance data. Subsequently, the unscented Kalman filter (UKF) estimator is applied to optimally solve an augmented matrix that incorporates both motion data and hydrodynamic parameters, yielding numerical values for the hydrodynamic parameters. Simulation results demonstrate that, in comparison to motion performance obtained by the CFD method, the hydrodynamic model derived from UKF enables an effective prediction of the motion of the deep‐sea mining vehicle, with prediction errors consistently below 6%.