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Advancements in Power Management Systems for Hybrid Electric Vessels
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Advancements in Power Management Systems for Hybrid Electric Vessels

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean Engineering".

Deadline for manuscript submissions: closed (15 December 2024) | Viewed by 12578

Special Issue Editors

Dr. Peilin Xie

E-Mail Website
Guest Editor
Department of Energy Technology, Aalborg University, 9200 Aalborg, Denmark
Interests: power management system; virtual synchronous generator; shipboard microgrids; distributed control
Dr. Sen Tan

E-Mail Website
Guest Editor
Energy Department, Aalborg University, 9220 Aalborg, Denmark
Interests: power management system; energy storage; security detection and cooperative control of microgrids; motor drive technologies
Special Issues, Collections and Topics in MDPI journals
Dr. Rosemary Norman

E-Mail Website
Guest Editor
School of Engineering, Newcastle University, Newcastle NE1 7RU, UK
Interests: hybrid-electric propulsion systems; fuel and emissions monitoring; marine renewable systems; tidal current turbines and associated electrical power converters; marine electrical systems; shore supplies; hybrid marine propulsion
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The maritime industry is currently undergoing a significant transformation, marked by the transition towards propulsion systems that are not only energy-efficient but also environmentally friendly. This shift is prominently reflected in the adoption of hybrid or all-electric propulsion systems, leveraging renewable energy sources (like photovoltaic and fuel cells) and evolving advanced electrical distribution topologies. As vessels embark on the journey towards all-electric propulsion, they encounter challenges associated with variable and fluctuating propulsion loads. In response to this, hybrid energy storage systems have emerged as effective solutions, particularly when integrating renewable sources. The integration of PV and fuel cells into these storage systems ensures that the vessels can adeptly handle high-frequency fluctuations, assist primary generators, and provide reliable energy backup across varying sea states and cruising conditions. This highlights the critical role of power management systems in optimizing the performance of these hybrid energy storage systems. Efficient power management is paramount in ensuring the reliability, sustainability, and overall effectiveness of hybrid or all-electric propulsion systems, especially as vessels navigate diverse operational conditions.

This Special Issue aims to present and share the most recent advancements in the theory, design, modeling, application, route planning, and energy optimization tailored specifically for hybrid electric maritime vessels.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Electrical propulsion and generation;
  • Energy storage systems;
  • Cold-ironing and shore power;
  • Green shipping;
  • Ship and system level models;
  • Fuel cells and integration;
  • Advanced modeling approaches;
  • Energy-efficient navigation;
  • Efficient navigation techniques;
  • Rule-based and optimization-based methods;
  • Real-time and offline power and energy management systems.

Dr. Peilin Xie
Dr. Sen Tan
Dr. Rosemary Norman
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Marine Science and Engineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • microgrid
  • maritime power systems
  • renewable energy
  • electrical propulsion system
  • fuel cells
  • power management system
  • energy management system
  • energy storage system

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Published Papers (11 papers)

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Editorial

Jump to: Research

4 pages, 147 KiB  
Editorial
Advancements in Power Management Systems for Hybrid Electric Vessels
by Sen Tan, Peilin Xie and Rose Norman
J. Mar. Sci. Eng. 2025, 13(4), 794; https://doi.org/10.3390/jmse13040794 - 16 Apr 2025
Viewed by 210
Abstract
With the growing urgency of climate change, environmental regulations governing the maritime industry have become increasingly stringent, imposing significant restrictions on ship emissions [...] Full article
(This article belongs to the Special Issue Advancements in Power Management Systems for Hybrid Electric Vessels)

Research

Jump to: Editorial

22 pages, 8765 KiB  
Article
Nonlinear Model Predictive Control Energy Management Strategy for Hybrid Power Ships Based on Working Condition Identification
by Yucheng Yan, Zhichao Chen and Diju Gao
J. Mar. Sci. Eng. 2025, 13(2), 269; https://doi.org/10.3390/jmse13020269 - 31 Jan 2025
Cited by 1 | Viewed by 748
Abstract
Hybrid power technology for ships is an effective way to promote the green and low-carbon development of the maritime industry. The development of pattern recognition technology provides new research ideas for the rational allocation and utilization of energy in hybrid power ships. To [...] Read more.
Hybrid power technology for ships is an effective way to promote the green and low-carbon development of the maritime industry. The development of pattern recognition technology provides new research ideas for the rational allocation and utilization of energy in hybrid power ships. To reduce fuel consumption, a nonlinear model predictive control energy management strategy based on working condition identification is proposed for optimal energy management to solve the problem of real-time optimal adjustment of generators and batteries. The core of the strategy is to identify the ship’s working conditions and the nonlinear model predictive control algorithm. Firstly, to achieve the working condition identification task, a ship working condition dataset based on a hybrid supply power ship data is constructed. The labeled dataset is trained using deep learning techniques. Secondly, based on the identification results, a nonlinear model predictive control algorithm is designed to adjust the generator speed and the battery current to achieve energy optimization control under constraints. Finally, the effectiveness of the proposed strategy in optimizing energy control and reducing fuel consumption is verified through simulation. The proposed strategy can reduce the generator fuel consumption by 5.5% under no noise disturbance when compared with conventional predictive control. Under 10% noise disturbance, it is still able to reduce the fuel consumption by 2.6%. Full article
(This article belongs to the Special Issue Advancements in Power Management Systems for Hybrid Electric Vessels)
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21 pages, 3922 KiB  
Article
Prior Knowledge-Based Two-Layer Energy Management Strategy for Fuel Cell Ship Hybrid Power System
by Lin Liu, Xiangguo Yang, Xin Li, Xingwei Zhou, Yufan Wang, Telu Tang, Qijia Song and Yifan Liu
J. Mar. Sci. Eng. 2025, 13(1), 94; https://doi.org/10.3390/jmse13010094 - 7 Jan 2025
Viewed by 937
Abstract
Implementing energy management is crucial in the fuel cell and battery or supercapacitor hybrid energy systems of ships. Traditional real-time energy management strategies often struggle to adapt to complex operating conditions; to address this issue and mitigate fuel cell fluctuations during real-time operations [...] Read more.
Implementing energy management is crucial in the fuel cell and battery or supercapacitor hybrid energy systems of ships. Traditional real-time energy management strategies often struggle to adapt to complex operating conditions; to address this issue and mitigate fuel cell fluctuations during real-time operations while extending the lifespan of lithium-ion batteries, this paper proposes a two-layer energy management system (EMS) based on prior knowledge of ship operation. In the first layer of the EMS, which operates offline, dynamic programming (DP) and low-pass filtering (LPF) are used to allocate power optimally for different typical ship operating conditions. Distribution results are then used to train an SSA-BP neural network, creating an offline strategy library. In the second layer, operating in real-time, the current load power is input into a support vector machine (SVM) to classify the current operating condition. The corresponding strategy from the offline library is then selected and used to provide energy distribution recommendations based on the real-time load and the state of charge (SOC) of the lithium-ion batteries and supercapacitors. The proposed EMS was validated using different ship load cycles. The results demonstrate that, compared to second-order filtering-based real-time energy management strategies, the proposed method reduces fuel cell power fluctuations by 44% and decreases lithium-ion battery degradation by 28%. Furthermore, the simulation results closely align with the offline optimization results, indicating that the proposed strategy achieves near-optimal energy management in real-time ship operations with minimal computational overhead. Full article
(This article belongs to the Special Issue Advancements in Power Management Systems for Hybrid Electric Vessels)
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24 pages, 11745 KiB  
Article
Multi-Temporal Energy Management Strategy for Fuel Cell Ships Considering Power Source Lifespan Decay Synergy
by Xingwei Zhou, Xiangguo Yang, Mengni Zhou, Lin Liu, Song Niu, Chaobin Zhou and Yufan Wang
J. Mar. Sci. Eng. 2025, 13(1), 34; https://doi.org/10.3390/jmse13010034 - 29 Dec 2024
Cited by 1 | Viewed by 1052
Abstract
With increasingly stringent maritime environmental regulations, hybrid fuel cell ships have garnered significant attention due to their advantages in low emissions and high efficiency. However, challenges related to the coordinated control of multi-energy systems and fuel cell degradation remain significant barriers to their [...] Read more.
With increasingly stringent maritime environmental regulations, hybrid fuel cell ships have garnered significant attention due to their advantages in low emissions and high efficiency. However, challenges related to the coordinated control of multi-energy systems and fuel cell degradation remain significant barriers to their practical implementation. This paper proposes an innovative multi-timescale energy management strategy that focuses on optimizing the lifespan decay synergy of fuel cells and lithium batteries. The study designs an attention-based CNN-LSTM hybrid model for power prediction and constructs a two-stage optimization framework: The first stage employs Model Predictive Control (MPC) for long-term power planning to optimize equivalent hydrogen consumption, while the second stage focuses on real-time power allocation considering both power source degradation and system operational efficiency. The simulation results demonstrate that compared to single-layer MPC and the Equivalent Consumption Minimization Strategy (ECMS), the proposed method exhibits significant advantages in reducing single-voyage costs, minimizing differences in power source degradation rates, and alleviating power source stress. The overall performance of this strategy approaches the global optimal solution obtained through Dynamic Programming, comprehensively validating its superiority in simultaneously optimizing system economics and durability. Full article
(This article belongs to the Special Issue Advancements in Power Management Systems for Hybrid Electric Vessels)
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25 pages, 9193 KiB  
Article
Capacity Prognostics of Marine Lithium-Ion Batteries Based on ICPO-Bi-LSTM Under Dynamic Operating Conditions
by Qijia Song, Xiangguo Yang, Telu Tang, Yifan Liu, Yuelin Chen and Lin Liu
J. Mar. Sci. Eng. 2024, 12(12), 2355; https://doi.org/10.3390/jmse12122355 - 21 Dec 2024
Viewed by 709
Abstract
An accurate prognosis of the marine lithium-ion battery capacity is significant in guiding electric ships’ optimal operation and maintenance. Under real-world operating conditions, lithium-ion batteries are exposed to various external factors, making accurate capacity prognostication a complex challenge. The paper develops a marine [...] Read more.
An accurate prognosis of the marine lithium-ion battery capacity is significant in guiding electric ships’ optimal operation and maintenance. Under real-world operating conditions, lithium-ion batteries are exposed to various external factors, making accurate capacity prognostication a complex challenge. The paper develops a marine lithium-ion battery capacity prognostic method based on ICPO-Bi-LSTM under dynamic operating conditions to address this. First, the battery is simulated according to the actual operating conditions of an all-electric ferry, and in each charge/discharge cycle, the sum, mean, and standard deviation of each parameter (current, voltage, energy, and power) during battery charging, as well as the voltage difference before and after the simulated operating conditions, are calculated to extract a series of features that capture the complex nonlinear degradation tendency of the battery, and then a correlation analysis is performed on the extracted features to select the optimal feature set. Next, to address the challenge of determining the neural network’s hyperparameters, an improved crested porcupine optimization algorithm is proposed to identify the optimal hyperparameters for the model. Finally, to prevent the interference of test data during model training, which could lead to evaluation errors, the training dataset is used for parameter fitting, the validation dataset for hyperparameter adjustment, and the test dataset for the model performance evaluation. The experimental results demonstrate that the proposed method achieves high accuracy and robustness in capacity prognostics of lithium-ion batteries across various operating conditions and types. Full article
(This article belongs to the Special Issue Advancements in Power Management Systems for Hybrid Electric Vessels)
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21 pages, 5146 KiB  
Article
Early Fault Diagnosis and Prediction of Marine Large-Capacity Batteries Based on Real Data
by Yifan Liu, Huabiao Jin, Xiangguo Yang, Telu Tang, Qijia Song, Yuelin Chen, Lin Liu and Shoude Jiang
J. Mar. Sci. Eng. 2024, 12(12), 2253; https://doi.org/10.3390/jmse12122253 - 8 Dec 2024
Cited by 1 | Viewed by 1016
Abstract
The inconsistency of battery voltages in all-electric ships is a significant issue for electric vehicle battery systems, leading to numerous safety concerns during vessel operation. Therefore, timely fault diagnosis and accurate fault prediction are crucial for the safe operation of ships. This study [...] Read more.
The inconsistency of battery voltages in all-electric ships is a significant issue for electric vehicle battery systems, leading to numerous safety concerns during vessel operation. Therefore, timely fault diagnosis and accurate fault prediction are crucial for the safe operation of ships. This study examines the fault alarm system of marine battery management systems in conjunction with the unique operating conditions of ships, focusing on the system’s latency. To facilitate prompt fault detection, a fault diagnosis method based on the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm is proposed, utilizing the voltage data of battery clusters. Results indicate that the DBSCAN clustering algorithm demonstrates superior effectiveness and accuracy in identifying irregular battery clusters. Furthermore, the fault prediction method based on the iTransformer model is introduced to forecast variations in battery cluster voltages. Experimental findings suggest that this model can effectively predict consistency faults and over-/under-voltage conditions based on battery cluster voltage values and corresponding fault thresholds. Full article
(This article belongs to the Special Issue Advancements in Power Management Systems for Hybrid Electric Vessels)
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17 pages, 4177 KiB  
Article
Advanced Energy Management System for Generator–Battery Hybrid Power System in Ships: A Novel Approach with Optimal Control Algorithms
by Eunbae Choi and Heemoon Kim
J. Mar. Sci. Eng. 2024, 12(10), 1755; https://doi.org/10.3390/jmse12101755 - 4 Oct 2024
Cited by 4 | Viewed by 1866
Abstract
Advancements in the reduction of carbon dioxide emissions from ships are driving the development of more efficient onboard power systems. The proposed non-equivalent parallel running operation system is explored in this study, which improves the efficiency of the main power generation source compared [...] Read more.
Advancements in the reduction of carbon dioxide emissions from ships are driving the development of more efficient onboard power systems. The proposed non-equivalent parallel running operation system is explored in this study, which improves the efficiency of the main power generation source compared with traditional equal load-sharing methods used in power management systems. However, the asymmetric method reduces the efficiency of the auxiliary power sources. To address this issue, we propose a control method that integrates a battery system with an efficiency-based algorithm to optimize the overall system performance. The proposed approach involves establishing operation command values based on the characteristics of the power generation source and adjusting these commands according to the battery’s state of charge (SOC). MATLAB/Simulink simulations confirmed the effectiveness of this method across various operating modes and revealed no operational issues. When applied to a ship’s operating profile over 222 h, the method reduced fuel consumption by approximately 2.98 tons (5.57%) compared with conventional systems. Over 38 annual voyages, this reduction equates to savings of 115.96 tons of fuel or approximately 96.47 million Korean won. This study demonstrates that integrating an optimal efficiency algorithm into the energy management system significantly enhances both the propulsion and overall energy efficiency of ships. Full article
(This article belongs to the Special Issue Advancements in Power Management Systems for Hybrid Electric Vessels)
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25 pages, 8710 KiB  
Article
Enhancing Efficiency in Hybrid Marine Vessels through a Multi-Layer Optimization Energy Management System
by Hoai Vu Anh Truong, Tri Cuong Do and Tri Dung Dang
J. Mar. Sci. Eng. 2024, 12(8), 1295; https://doi.org/10.3390/jmse12081295 - 31 Jul 2024
Cited by 3 | Viewed by 1070
Abstract
Configuring green power transmissions for heavy-industry marines is treated as a crucial request in an era of global energy and pollution crises. Following up on this hotspot trend, this paper examines the effectiveness of a modified optimization-based energy management strategy (OpEMS) for a [...] Read more.
Configuring green power transmissions for heavy-industry marines is treated as a crucial request in an era of global energy and pollution crises. Following up on this hotspot trend, this paper examines the effectiveness of a modified optimization-based energy management strategy (OpEMS) for a dual proton exchange membrane fuel cells (dPEMFCs)-battery-ultra-capacitors (UCs)-driven hybrid electric vessels (HEVs). At first, the summed power of the dual PEMFCs is defined by using the equivalent consumption minimum strategy (ECMS). Accordingly, a map search engine (MSE) is proposed to appropriately split power for each FC stack and maximize its total efficiency. The remaining power is then distributed to each battery and UC using an adaptive co-state, timely determined based on the state of charge (SOC) of each device. Due to the strict constraint of the energy storage devices’ (ESDs) SOC, one fine-corrected layer is suggested to enhance the SOC regulations. With the comparative simulations with a specific rule-based EMS and other approaches for splitting power to each PEMFC unit, the effectiveness of the proposed topology is eventually verified with the highest efficiency, approximately about 0.505, and well-regulated ESDs’ SOCs are obtained. Full article
(This article belongs to the Special Issue Advancements in Power Management Systems for Hybrid Electric Vessels)
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15 pages, 6094 KiB  
Article
Current Harmonic Suppression in Maritime Vessel Rudder PMSM Drive System Based on Composite Fractional-Order PID Repetitive Controller
by Tianqing Yuan, Tianli Wang, Jingwen Fan and Jing Bai
J. Mar. Sci. Eng. 2024, 12(7), 1108; https://doi.org/10.3390/jmse12071108 - 30 Jun 2024
Viewed by 1080
Abstract
To address the control performance and harmonic suppression issues in maritime vessel rudder permanent magnet servo systems, a fractional-order PID controller was introduced into the existing improved repetitive control strategy. We used the Oustaloup approximation algorithm and particle swarm optimization for tuning the [...] Read more.
To address the control performance and harmonic suppression issues in maritime vessel rudder permanent magnet servo systems, a fractional-order PID controller was introduced into the existing improved repetitive control strategy. We used the Oustaloup approximation algorithm and particle swarm optimization for tuning the fractional-order PID controller. The optimized parameters substantially improved the control performance. By integrating the fractional-order PID controller with the improved repetitive controller, a composite fractional-order PID repetitive control strategy was formed. Finally, MATLAB/Simulink simulations were conducted to compare and verify the disturbance rejection and harmonic suppression capabilities of the improved control strategy. The results demonstrate its superior control performance, thereby increasing the practicality of the control system in dealing with various situations. Full article
(This article belongs to the Special Issue Advancements in Power Management Systems for Hybrid Electric Vessels)
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17 pages, 5207 KiB  
Article
Parameter Identification of Maritime Vessel Rudder PMSM Based on Extended Kalman Particle Filter Algorithm
by Tianqing Yuan, Tianli Wang, Jing Bai and Jingwen Fan
J. Mar. Sci. Eng. 2024, 12(7), 1095; https://doi.org/10.3390/jmse12071095 - 28 Jun 2024
Cited by 3 | Viewed by 1014
Abstract
To address the issue of system parameter variations during the operation of a maritime light vessel rudder permanent magnet synchronous motor (PMSM), an extended Kalman particle filter (EKPF) algorithm that combines a particle filter (PF) with an extended Kalman filter (EKF) is proposed [...] Read more.
To address the issue of system parameter variations during the operation of a maritime light vessel rudder permanent magnet synchronous motor (PMSM), an extended Kalman particle filter (EKPF) algorithm that combines a particle filter (PF) with an extended Kalman filter (EKF) is proposed in this paper. This approach enables the online identification of motor resistance and inductance. For highly nonlinear problems that are challenging for traditional methods such as Kalman filtering, this algorithm is typically a statistical and effective estimation method that usually yields good results. Firstly, a standard linear discrete parameter identification model is established for a PMSM. Secondly, the PF algorithm based on Bayesian state estimation as a foundation for subsequent research is derived. Thirdly, the advantages and limitations of the PF algorithm are analyzed, addressing issues such as sample degeneracy, by integrating it with the Kalman filtering algorithm. Specifically, the EKPF algorithm for online parameter identification is employed. Finally, the identification model within MATLAB/Simulink is constructed and the simulation studies are executed to ascertain the viability of our suggested algorithm. The outcomes from these simulations indicate that the proposed EKPF algorithm identifies resistance and inductance values both swiftly and precisely, markedly boosting the robustness and enhancing the control efficacy of the PMSM. Full article
(This article belongs to the Special Issue Advancements in Power Management Systems for Hybrid Electric Vessels)
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23 pages, 7417 KiB  
Article
A Study on Fishing Vessel Energy System Optimization Using Bond Graphs
by Sang-Won Moon, Won-Sun Ruy and Kwang-Phil Park
J. Mar. Sci. Eng. 2024, 12(6), 903; https://doi.org/10.3390/jmse12060903 - 28 May 2024
Cited by 1 | Viewed by 1768
Abstract
Recently, environmental regulations have been strengthened due to climate change. This change comes in a way that limits emissions from ships in the shipbuilding industry. According to these changes, the trend of ship construction is changing installing pollutant emission reduction facilities such as [...] Read more.
Recently, environmental regulations have been strengthened due to climate change. This change comes in a way that limits emissions from ships in the shipbuilding industry. According to these changes, the trend of ship construction is changing installing pollutant emission reduction facilities such as scrubbers or applying alternative fuels such as low sulfur oil and LNG to satisfy rule requirements. However, these changes are focused on large ships. Small ships are limited in size. So, it is hard to install large facilities such as scrubbers and LNG propulsion systems, such as fishing boats that require operating space. In addition, in order to apply the pure electric propulsion method, there is a risk of marine distress during battery discharge. Therefore, the application of the electric–diesel hybrid propulsion method for small ships is being studied as a compromised solution. Since hybrid propulsion uses various energy sources, a method that can estimate effective efficiency is required for efficient operation. Therefore, in this study, a Bond graph is used to model the various energy sources of hybrid propulsion ships in an integrated manner. Furthermore, based on energy system modeling using the Bond graph, the study aims to propose a method for finding the optimal operational scenarios and reduction ratios for the entire voyage, considering the navigation feature of each different maritime region. In particular, the reduction gear is an important component at the junction of the power transmission of the hybrid propulsion ship. It is expected to be useful in the initial design stage as it can change the efficient operation performance with minimum design change. Full article
(This article belongs to the Special Issue Advancements in Power Management Systems for Hybrid Electric Vessels)
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