A Hybrid System Approach to Energy Optimization in Gas–Electric Hybrid Powertrains

Xiaojun Sun (), Benrong Zhang, Jiangning Zhu () and Chong Yao
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Xiaojun Sun: School of Automobile and Traffic Engineering, Liaoning University of Technology, Jinzhou 121000, China
Benrong Zhang: School of Automobile and Traffic Engineering, Liaoning University of Technology, Jinzhou 121000, China
Jiangning Zhu: Department of Mathematics and Computer Science, Chaoyang Normal University, Chaoyang 122000, China
Chong Yao: Yantai Research Institute, Harbin Engineering University, Harbin 150001, China

Sustainability, 2025, vol. 17, issue 18, 1-27

Abstract: Amid growing global concerns over environmental sustainability, the shipping industry is under increasing pressure to implement innovative power systems that minimize ecological impact. A promising approach is the marine gas–electric hybrid system, which combines conventional marine propulsion with electric power to offer a cleaner energy solution. Characterized by the integration of continuous and discrete variables, these systems reflect the hybrid nature of gas–electric propulsion. Despite their potential, research on marine hybridization remains limited. To address this gap, a hybrid system model has been developed to optimize energy allocation while accurately capturing the hybrid characteristics of gas–electric systems in ships. Additionally, an energy distribution strategy based on predictive control has been proposed to validate the model’s practical applicability. A weighted evaluation method was employed on a marine gas–electric hybrid test platform to verify the performance of both the model and the control strategy. Results show that different weighting configurations lead to varying torque distribution patterns, confirming the effectiveness of the hybrid system model. Moreover, tuning the weighting parameters within the energy allocation strategy yields diverse control behaviors, further demonstrating the system’s viability for marine applications.

Keywords: gas–electric hybrid propulsion; hybrid system modeling; energy management; model predictive control (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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