Modeling, Identification, and Validation of a Vector Propelled Amphibious Vehicle

High-fidelity models play an essential role in advancing the structural optimization and motion simulation of amphibious vehicles. However, the complexity of hydrodynamics poses significant challenges in dynamic modeling, parameter identification, and experimental validation. To address these challenges, this research derives a six-degree-of-freedom dynamic model for a vector propelled amphibious vehicle based on maneuvering theory, including a dedicated propulsion system dynamic model. Given the system identification challenges posed by the highly coupled multi-parameter dynamics, a systematic experimental framework is devised, featuring decoupled measurements of the propulsion and maneuvering dynamics. A staged parameter identification methodology integrating the genetic algorithm and the least squares method is proposed. The methodology initially identifies a subset of parameters through decoupled reduced-order models, and subsequently performs a systematic identification of the remaining parameters based on the complete coupled model. For model validation, a simulation platform based on numerical integration methods is developed, with real-time visualization implemented in Unreal Engine 4 (UE4). Field tests and hardware-in-the-loop (HIL) validation demonstrate that the established model with identified parameters can accurately capture the motion characteristics of the amphibious vehicle.