Novel enhancement of energy distribution for marine hybrid propulsion systems by an advanced variable weight decision model predictive control. (1st July 2023)

• Record Type: Journal Article
• Authors: Sun, Xiaojun; Yao, Chong; Song, Enzhe; Liu, Zhijiang; Ke, Yun; Ding, Shunliang
• Is Part Of: Energy. Volume 274(2023)
• Publication Date: 2023-07-01
• Subjects: Variable weights -- Hybrid power -- Energy management -- Energy distribution -- Weight-tuning; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2023.127269
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Marine hybrid technology is attracting increasing research interest thanks to its power versatility and potential economic advantages. However, its overall quality performance is determined by the energy management strategy. This research deals with a variable weighted decision model predictive control (VWDMPC) for marine hybrid energy management, where the main task is to dynamically weight-tuning and optimally allocate energy to obtain the optimal trade-off in terms of fuel consumption, power performance, and energy allocation. For the sake of enhancing the real-time and adaptability of VWDMPC, we utilize the KKT condition to compress the optimal energy management problem and the weight tuning process in one, which cleverly simplifies the optimization process. Performance experiments are performed on a test bench and a real-time hardware execution platform. Different weighting decision comparison scenarios were designed to evaluate the power performance improvement and equivalent fuel consumption of the proposed VWDMPC and give the best proportional weights (0.33, 0.27, 0.2, 0.2) that take both aspects into account. Moreover, this paper also provides validation and feedback based on the evaluation results, which show that the optimal combination of weights that take into account economy and dynamics ranges from (0.3, 0.3, 0.2, 0.2)-(0.33, 0.27, 0.2, 0.2) based on the radar plot drawn from the performance index parameters. Highlights: A model predictive control with real-time tuned weights is proposed. The KKT condition is cleverly used to integrate weight tuning. The effectiveness of VWDMPC-based is verified using CompackRIO.