Article: Dynamic modelling and state estimation of hub motor-driven amphibious vehicles for water-to-land transition Journal: International Journal of Vehicle Systems Modelling and Testing (IJVSMT) 2026 Vol.20 No.3 pp.323 - 350 Abstract: This study investigates the modelling and state estimation of a hub-motor-driven amphibious vehicle under water-to-land transition conditions. The focus is on modelling during land-to-water transitions and the design of an effective estimation framework. Accurate estimation must consider complex coupled effects such as buoyancy, fluid resistance, low-adhesion surfaces, and dynamic slopes. To address this, a fading memory unscented Kalman filter (FM-UKF) is proposed, integrating wheel speed and acceleration for vehicle velocity estimation. A longitudinal slope estimation method is also developed by fusing acceleration sensor data with a forgetting factor recursive least squares (FF-RLS) algorithm. A multibody dynamics model is established, enabling real-time estimation of longitudinal speed, terrain slope, and adhesion coefficient through the proposed fusion framework. Simulation results demonstrate the method's effectiveness under transition conditions. Additionally, a real-vehicle experiment on a multi-gradient ramp confirms the accuracy and practicality of the proposed approach in real amphibious driving scenarios. Inderscience Publishers - linking academia, business and industry through research

Title: Dynamic modelling and state estimation of hub motor-driven amphibious vehicles for water-to-land transition

Authors: Bin Huang; Wenbin Yu; Lianbing Suo; Zineng Yuan

Addresses: Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan, 430070, China ' Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan, 430070, China ' Dongfeng Off-road Vehicle Co. Ltd., Wuhan, 430070, China ' Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan, 430070, China

Abstract: This study investigates the modelling and state estimation of a hub-motor-driven amphibious vehicle under water-to-land transition conditions. The focus is on modelling during land-to-water transitions and the design of an effective estimation framework. Accurate estimation must consider complex coupled effects such as buoyancy, fluid resistance, low-adhesion surfaces, and dynamic slopes. To address this, a fading memory unscented Kalman filter (FM-UKF) is proposed, integrating wheel speed and acceleration for vehicle velocity estimation. A longitudinal slope estimation method is also developed by fusing acceleration sensor data with a forgetting factor recursive least squares (FF-RLS) algorithm. A multibody dynamics model is established, enabling real-time estimation of longitudinal speed, terrain slope, and adhesion coefficient through the proposed fusion framework. Simulation results demonstrate the method's effectiveness under transition conditions. Additionally, a real-vehicle experiment on a multi-gradient ramp confirms the accuracy and practicality of the proposed approach in real amphibious driving scenarios.

Keywords: amphibious vehicle; state estimation; water-to-land composite conditions; multibody dynamics model.

DOI: 10.1504/IJVSMT.2026.155794

International Journal of Vehicle Systems Modelling and Testing, 2026 Vol.20 No.3, pp.323 - 350

Received: 26 Mar 2025
Accepted: 11 Jun 2025
Published online: 14 Aug 2026 *

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Title: Dynamic modelling and state estimation of hub motor-driven amphibious vehicles for water-to-land transition

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