Research on Energy Management Strategy of Hydrogen-electric Hybrid Tug Based on PMP Algorithm

Luxi Liu; Zhe Li; Zhirong Li

doi:10.62177/jaet.v3i5.993

Authors

Luxi Liu Qingdao Jari Industrial Control Technology Co., Ltd.
Zhe Li Qingdao Jari Industrial Control Technology Co., Ltd.
Zhirong Li Qingdao Jari Industrial Control Technology Co., Ltd.

DOI:

https://doi.org/10.62177/jaet.v3i5.993

Keywords:

Hybrid Tug, Operating Condition Recognition, Energy Management Strategy

Abstract

This study addresses energy management challenges in hydrogen-electric hybrid tugs by proposing an energy allocation strategy based on operating condition recognition and optimization algorithms. Standard operating conditions were classified through cluster analysis, a hybrid system performance model was established, and the Pontryagin Minimum Principle (PMP) algorithm was employed to achieve optimal power distribution between hydrogen fuel cells and lithium batteries. Simulation experiments demonstrated that the proposed energy management strategy prevented the fuel cell from operating under high-power heavy-load conditions, with only brief periods of low-power idle operation. This effectively reduced the operational strain on the fuel cell, thereby enhancing its long-term durability. Experimental results indicate that this method significantly improves energy utilization efficiency, reduces energy consumption, and extends equipment service life, providing technical support for the efficient operation of hydrogen-electric hybrid tugs.

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References

Shen, J., Li, F., Li, M., et al. (2021). Prediction of PM10 concentration in port clusters considering regional spatiotemporal correlation characteristics. Journal of Transport Science and Engineering. Advance online publication. https://doi.org/10.16544/j.cnki.cn43-1494/u.20250811001

Liu, M., Luo, C., & Zhang, J. (2018). Research on safety limiting factors of tugboat fleet through restricted straight sections. Journal of Safety and Environment, 18(2), 566–570. https://doi.org/10.13637/j.issn.1009-6094.2018.02.99

Deng, Q., & Lei, B. (2020). New developments in tugboat power systems. Marine Electric & Electronic Engineering, 40(5), 18–20.

Liu, X. (2024). Current status and development trends of new energy tugs. China Ports, (11), 48–50.

Liu, J., Sun, Y., Wang, K., et al. (2025). A review of energy management research for fuel cell hybrid electric vehicles. Mechanical Engineer, (12), 92–96.

Song, L., & Liu, W. (2025). Application status and development trend of new energy ships. Marine Equipment/Materials & Marketing, 33(11), 52–55.

Li, Z., Zhao, X., Zhu, H., & Chen, J. (2023). Engine-propeller matching design for multi-mode hybrid harbor tugs. Ship Engineering, 45(S1), 301–304.

Zhang, Y., Chen, L., & Zhu, J. (2018). A review of hybrid ship power plants and energy management. Ship Science and Technology, 40(5), 1–7.

Gao, D., Shen, A., Chu, J., et al. (2015). Energy management and control strategies for hybrid ships. Journal of Shanghai Maritime University, 36(1), 70–74.

Lan, X., Shen, A., Gao, D., et al. (2016). Optimal control of energy management systems for hybrid ships. Chinese Journal of Power Sources, 40(9), 1859–1862.

Li, L., Tao, F., & Fu, Z. (2025). Research on condition-adaptive energy management strategy for PHEV. Computer Simulation, 42(2), 147–154.

Guo, X., Yuan, Y., & Tong, L. (2024). Energy management strategy for diesel-electric hybrid ships based on Pontryagin’s minimum principle. Journal of Harbin Engineering University, 45(11), 2176–2184.

Xu, S., & Wu, Z. (2014). Research on global optimal energy management strategy for HEV based on PMP. China Mechanical Engineering, 25(1), 138–141.

Li, P., Zhang, J., Zhang, C., et al. (2025). Research on low altitude multi UAV path planning method based on improved A * algorithm. Journal of Transport Science and Engineering, 41(4), 61–68. https://doi.org/10.16544/j.cnki.cn43-1494/u.20205529002

Zhang, D., Zhong, X., Wang, X., et al. (2024). Analysis of the development status and trends of intelligent connected transportation technology based on WOS. Journal of Transport Science and Engineering, 40(3), 144–152. https://doi.org/10.16544/j.cnki.cn43-1494/u.20230607204061987

Liu, C., Zhang, J., Fan, X., et al. (2024). Dual induction logging inversion method based on quadratic programming. Journal of Henan Polytechnic University(Natural Science), 43(6), 49–56. https://doi.org/10.16186/j.cnki.1673-9787.2023070034

Liu, Y. (2025). Research on energy management strategy for fuel cell hybrid heavy-duty truck based on statistical characteristics of working condition parameters [Doctoral dissertation]. Chongqing University of Technology.

Hou, S. (2024). Research on energy management strategy for new energy vehicle hybrid power system [Doctoral dissertation]. Jilin University.