An Optimal Energy‐Saving Coordination Control System for Sail‐Propeller of Wind‐Assisted Ships

ABSTRACT Wind‐assisted ship propulsion technology has been regarded as a promising sustainable development solution. Wind‐assisted ships generate navigation thrust by driving sails and propellers. This study proposes an optimal energy‐saving control system for coordinating sail thrust and propeller thrust, achieved by regulating sail azimuth and propeller speed. A coordination control algorithm based on the model predictive control‐adaptive Pontryagin minimum principle (MPC‐APMP) is proposed. This algorithm transforms the optimal control problem for enhancing sail and propeller energy efficiency into a rolling optimisation problem of MPC framework. Firstly, considering the system's delay relative to time‐varying environment and speed requirements, a wind direction/wind speed/ship speed prediction model based on a long short‐term memory neural network is designed. According to the sail aerodynamics and the propeller hydrodynamics, a dynamic model of sail‐propeller combined propulsion is established and used to evaluate potential wind energy and the overall thrust demand. The reference trajectory of battery power is determined using the established energy consumption model. Finally, the PMP algorithm is applied to derive the optimal control sequence. A co‐state variable adaptive law is designed to address model parameter uncertainties. The energy‐saving efficiency and stability of the proposed method are validated through simulations and a principle prototype.

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Publication Details

Journal
IET Intelligent Transport Systems
Published
2025-01-01
DOI
https://doi.org/10.1049/itr2.70090
Citations
1
Primary Topic
Maritime Transport Emissions and Efficiency
Type
article
Field-Weighted Citation Impact
0.80
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article

An Optimal Energy‐Saving Coordination Control System for Sail‐Propeller of Wind‐Assisted Ships

Jian Song, Sheng Liu, Yinchao Tan, Lanyong Zhang
1 citations
IET Intelligent Transport Systems
Maritime Transport Emissions and Efficiency
0.80
article

An Optimal Energy‐Saving Coordination Control System for Sail‐Propeller of Wind‐Assisted Ships

Jian Song, Sheng Liu, Yinchao Tan, Lanyong Zhang
article en
1 citations

Abstract

ABSTRACT Wind‐assisted ship propulsion technology has been regarded as a promising sustainable development solution. Wind‐assisted ships generate navigation thrust by driving sails and propellers. This study proposes an optimal energy‐saving control system for coordinating sail thrust and propeller thrust, achieved by regulating sail azimuth and propeller speed. A coordination control algorithm based on the model predictive control‐adaptive Pontryagin minimum principle (MPC‐APMP) is proposed. This algorithm transforms the optimal control problem for enhancing sail and propeller energy efficiency into a rolling optimisation problem of MPC framework. Firstly, considering the system's delay relative to time‐varying environment and speed requirements, a wind direction/wind speed/ship speed prediction model based on a long short‐term memory neural network is designed. According to the sail aerodynamics and the propeller hydrodynamics, a dynamic model of sail‐propeller combined propulsion is established and used to evaluate potential wind energy and the overall thrust demand. The reference trajectory of battery power is determined using the established energy consumption model. Finally, the PMP algorithm is applied to derive the optimal control sequence. A co‐state variable adaptive law is designed to address model parameter uncertainties. The energy‐saving efficiency and stability of the proposed method are validated through simulations and a principle prototype.

IET Intelligent Transport SystemsVol. 19(1)
Harbin Engineering University (CN), PLA Electronic Engineering Institute (CN), Weihai Chest Hospital (CN), Weihai Science and Technology Bureau (CN)
Openalex Percentile: Top 25%
Maritime Transport Emissions and Efficiency
0.80
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An Optimal Energy‐Saving Coordination Control System for Sail‐Propeller of Wind‐Assisted Ships — Jian Song, Sheng Liu, et al. · IET Intelligent Transport Systems (2025) | TGRS Research Map | TGRS