Search Results (33)

This study presents a multi-objective predictive energy management system (EMS) for optimizing hybrid renewable energy systems (HRES) in autonomous marine vessels. The objective is to minimize fuel consumption and emissions while maximizing renewable energy usage and pure-electric sailing durations. The EMS combines nonlinear model predictive control (NMPC) with metaheuristic optimizers—Grey Wolf Optimization (GWO) and Genetic Algorithm (GA)—and is benchmarked against a conventional rule-based (RB) method. The HRES architecture comprises photovoltaic arrays, vertical-axis wind turbines (VAWTs), diesel engines, generators, and a battery storage system. A ship dynamics model was used to represent propulsion power under realistic sea conditions. Simulations were conducted using real-world operational and environmental datasets, with state prediction enhanced by an Extended Kalman Filter (EKF). Performance is evaluated using marine-relevant indicators—fuel consumption; emissions; battery state of charge (SOC); and emission cost—and validated using standard regression metrics. The NMPC-GWO algorithm consistently outperformed both NMPC-GA and RB approaches, achieving high prediction accuracy and greater energy efficiency. These results confirm the reliability and optimization capability of predictive EMS frameworks in reducing emissions and operational costs in autonomous maritime operations. Full article

Fast patrol boats account for a large number among the numerous vessels used in naval fleets. Owing to their operational characteristics, which involve relatively high speeds, they contribute to emissions significantly. This study presents an optimized design concept for a diesel–battery hybrid electric propulsion system integrated into the general ship design process for fast patrol boats. The optimization design uses mixed-integer linear programming to determine the most eco-friendly shares ratio of battery and diesel usage while satisfying high-endurance operational scenarios. A shares ratio of 1.259 tons of diesel to 2.88 tons of batteries was identified as the most eco-friendly configuration capable of meeting a 200-nautical-mile operational scenario at a maximum speed of 35 knots for the selected case study. A quantitative comparison through a global warming potential (GWP) analysis was conducted between conventional diesel propulsion systems and the designed diesel–battery hybrid electric propulsion system, using a life-cycle assessment (LCA) standardized under the ISO framework. The analysis confirmed that the optimized hybrid propulsion system can achieve a GWP reduction of approximately 7–9% compared with conventional propulsion systems. Few studies have applied LCA in this field, and the application of batteries as hybrid secondary energy sources is viable and sustainable for high-endurance scenarios. Full article

Owing to the global concern regarding fossil energy consumption and carbon emissions, the power supply for traditional diesel-driven ships is being replaced by low-carbon power sources, which include hydrogen energy generation and photovoltaic (PV) power generation. However, the uncertainty of shipboard PV power generation due to weather changes and ship motion variations has become an essential factor restricting the energy management of all-electric ships. In this paper, a deep reinforcement learning-based optimization algorithm is proposed for a green ship energy management system (EMS) coupled with hydrogen fuel cells (HFCs), lithium batteries, PV generation, an electric power propulsion system, and service loads. The focus of this study is reducing the total operation cost and improving energy efficiency by jointly optimizing power generation and voyage scheduling, considering shipboard PV uncertainty. To verify the effectiveness of the proposed method, real-world data for a hybrid hydrogen- and PV-driven ship are selected for conducting case studies under various sailing conditions. The numerical results demonstrate that, compared to those obtained with the Double DQN algorithm, the PPO algorithm, and the DDPG algorithm without considering the PV system, the proposed DDPG algorithm reduces the total economic cost by 1.36%, 0.96%, and 4.42%, while effectively allocating power between the hydrogen fuel cell and the lithium battery and considering the uncertainty of on-board PV generation. The proposed approach can reduce energy waste and enhance economic benefits, sustainability, and green energy utilization while satisfying the energy demand for all-electric ships. Full article

As advanced sensors and weapons require high power, naval vessels have increasingly adopted electric propulsion systems. This study aims to enhance the efficiency and operability of electric propulsion systems over traditional mechanical propulsion systems by analyzing the operational profiles of modern naval vessels. Consequently, a battery-integrated generator-based electric propulsion system was selected. Considering the purpose of the vessel, a specification selection procedure was developed, leading to the design of a hybrid electric propulsion system (comprising one battery and four generators). The power management control technique of the proposed propulsion system sets the operating modes (depending on the specific fuel oil consumption of the generators) to minimize fuel consumption based on the operating load. Additionally, load distribution control rules for the generators were designed to reduce energy consumption based on the load and battery state of charge. MATLAB/Simulink was used to evaluate the proposed system, with simulation results demonstrating that it maintained the same propulsion performance as existing systems while achieving a 12-ton (22%) reduction in fuel consumption. This improvement results in cost savings and reduced carbon dioxide emissions. These findings suggest that an efficient load-sharing controller can be implemented for various vessels equipped with electric propulsion systems, tailored to their operational profiles. Full article

Developing an efficient power system is an important way for icebreakers to respond to high maneuverability and strong fluctuation loads under icebreaking conditions. The performance of power systems under short-period, regularly fluctuating load-sea conditions has been intensively studied. However, the performance of the power system in the face of a long-period, stochastic multi-frequency fluctuation icebreaking process has not been fully explored, especially the parameter uncertainty and battery cycle life. In this study, an integrated electric propulsion system with an optimal control strategy is suggested for improving the power system’s dynamic performance and battery cycle life. First, an energy flow model with a diesel–electric unit as the main body and coupled energy storage system/hybrid energy storage system has been constructed. A comparative analysis of rule-based and optimization-based energy management strategies has been performed, and an optimized strategy with dynamic programming as global regulation at the upper level and model predictive control at the lower level is suggested to integrate the slow and fast dynamic powers and achieve adaptability to strong fluctuation loads. In this control strategy, the uncertainties of energy storage system/hybrid energy storage system parameters have been introduced to eliminate their impact on the system performance. Then, the icebreaking process with multi-frequency fluctuation has been simulated, and the hybrid energy storage system with battery and supercapacitor is recommended to reach multi-objective with the lowest power fluctuation of diesel–electric unit, highest efficiency, and the minimum battery degradation. Finally, the fuel oil consumption and emissions of the hybrid energy storage system have been discussed, and the optimized strategy can save fuel oil by up to 5.33% and reduce the CO₂ emission by 22% during the icebreaking process, exhibiting great potential in the environmental friendliness and significant advantages in terms of low fuel oil consumption. Full article

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

Due to tightening regulations on exhaust emissions from ships, there is a growing need to develop electric or hybrid electric propulsion systems to replace conventional diesel-based ship power systems. The hybrid electric propulsion system is suitable for small and medium-sized vessels and its energy efficiency significantly depends on the arrangement of different power sources, power control strategies for energy sources, and energy storage system (ESS). Therefore, an analytical simulation to evaluate the energy efficiency of ships with their structure and control strategies is needed. In this study, a back–forward approach-based efficiency performance analysis model was developed using the Holtrop–Mennen resistance model to calculate ship resistance and power demand based on a given ship’s speed profiles. This model has the advantages of using easily obtainable ship speed profiles as the input and can be modularized for each power source and ESS, incorporating mechanical performance limitations, and allows for rapid analysis. The developed analytical model was applied to a hybrid electric propulsion system in a marine support vessel and its energy efficiency was evaluated by establishing rule-based power control strategies. As a result, the engine efficiency of the hybrid electric propulsion system increased from about 27% to 30% compared to the existing system, and the final effect of reducing fuel consumption by about 10% compared to the existing system was confirmed through the developed simulator. In the future, this analytical model could be utilized to derive the optimal layout of hybrid electric propulsion systems, and to formulate power control strategies. Full article

International trade is continuously rising, leading to an increase in the flow of goods passing through transportation hubs, including air and sea. In addition, the aging fleet of inland vessels necessitates renewal through the construction of new vessels, presenting opportunities for the adoption of modern transport technologies. Autonomous barges can transport bulk and containerized cargo between the central port of a specific region and smaller satellite ports, enabling the dispersal of goods over a wider area. Equipping autonomous barges with advanced sensors, such as LIDAR, computer vision systems that operate in visible light and thermal infrared, and incorporating advanced path finding and cooperation algorithms may enable them to operate autonomously, subject only to remote supervision. The purpose of this study is to explore the potential of autonomous electric propulsion barges in inland waterway transport. Given the increasing demand for efficient and sustainable transport solutions as a result of various new policies, which have set new ambitious goals in clean transportation, this study aims to develop a proposition of an electric propulsion hybrid drive inland waterway barge, and compare it to a conventional diesel-powered barge. The methodology involves the creation of a simulation model of an inland waterway class IV electric barge, equipped with advanced sensors and autonomous control systems. The barge’s navigation is managed through a multi-agent system, with evolutionary algorithms determining a safe passage route. This research also utilizes a proprietary networked ship traffic simulator, based on real inland vessel recorded routes, to conduct the autonomous navigation study. The energy consumption of the barge on a route resulting from the ship traffic simulation is then examined using the mathematical model using the OpenModelica package. As a result of the study, the proposed hybrid propulsion system achieved a 16% reduction in fuel consumption and CO₂ emissions, while cutting engine operation time by more than 71%. The findings could provide valuable insights into the feasibility and efficiency of autonomous electric propulsion barges, potentially helping future developments in inland waterway transport. Full article

A Hybrid Electric Ship (HES) is investigated in this work to improve its dynamic response to sudden power demand changes. The HES system is based on a Variable-Speed Diesel Generator (VSDG) used for long-term energy supply, with Two Energy Storage Systems (TESSs) using Batteries and supercapacitors for transient power supply. The TESS mitigates the power demand fluctuations and reduces its impact on VSDG, which is linked to a DC-bus through a controlled rectifier. Batteries and Supercapacitors (SCs) are connected in a DC-bus using the bidirectional DC/DC converters to manage the transient and fluctuating components. Two thrusters (one in the front and the second in the back of the Ship) are considered for the propulsion system. The HES power demand includes the requirement of the thrusters and embedded power consumers (elevator, package lifting, air conditioning, onboard electronics devices, etc.). The highlight of this paper is based on the HES fast response improvement in sudden power demand situations via TESS-based batteries and supercapacitors. The other highlight concerns the SCs’ electrothermal modeling using an extension of the SCs’ current ripples’ frequency range (0 to 1 kHz), considering parameter evolution according to using the temperature and current waveform. This energy management-based dynamic power component separation method is tested via simulations using a variable operating temperature scenario. Full article

Increasingly, the melting of Arctic ice due to global warming has provided opportunities for commercial shipping between Asia and Europe. Given the vulnerability of the Arctic environment, especially due to emissions of short-lived pollutants from shipping activities, a more effective propulsion system with a comprehensive control strategy is required to reduce fuel consumption, thus potentially mitigating the impacts of shipping activities on the northern sea route (NSR). In this paper, a shipboard DC hybrid system powered by a combination of diesel generator sets and batteries is proposed and analysed in terms of its application on a ship in the NSR. The specific fuel consumption and various losses in the power sources were analysed to develop an efficiency-optimisation control strategy for the proposed DC hybrid power system. To evaluate the performance of the hybrid power system with the proposed optimisation control strategy, lab-scale experiments have been conducted in the Shanghai Marine Diesel Engine Research Institute to compare the proposed system with a conventional hybrid system. The experimental results indicate that the proposed DC hybrid power plant with the energy optimisation control contributes a 5.35% fuel saving compared with the DC fixed-speed diesel electric configuration during a scaled-down NSR scenario. Full article

Hybrid electric propulsion, using batteries for energy storage, is making significant inroads into railway transportation because of its potential for notable fuel savings and the related reductions in greenhouse gases emissions of hybrid railway traction over non-electrified railway lines. Due to the inherent complexity of hybridized powertrains, combining different power conversions and energy storage capabilities, the corresponding operation of their energy management needs to be precisely optimized in order to achieve the minimum possible fuel consumption. Having this in mind, this paper proposes a real-time energy management control strategy for a diesel–electric hybrid locomotive based on the optimization results obtained by means of a dynamic programming optimization algorithm aimed at fuel consumption minimization while honoring the battery state-of-charge constraints and powertrain physical constraints. The final optimization result, expressed in terms of the optimal battery state-of-charge reference (target), is used as an additional input into the state-of-charge controller within the real-time energy management system. The subsequent simulation analysis shows clear fuel economy improvement with 22.9% of fuel savings obtained for the locomotive featuring a hybrid powertrain equipped with batteries over the conventional one. Full article

Diesel-electric hybrid propulsion system (HPS) is widely applied for shunting locomotive due to the characteristics of flexible configuration, economic and environmental protection in the world. Energy management strategy (EMS) is an important design factor of HPS that can optimize the energy distribution of each power sources, improve system efficiency, and reduce fuel consumption. In this paper, the model of HPS for shunting locomotive and system operating profile are firstly carried out. Then the EMS consist of the conventional rule-based (RB) strategy rule, and a fuzzy neural network base on dynamic programming (FNN-DP) strategy are studied. Finally, the simulations were carried out with these EMSs in the system model at full operating conditions to derive the fuel consumption. The conclusion is that the theoretical optimal solution of DP provides reference and guidance for the fuzzy neural network strategy to improve the rules, and the fuel consumption of the FNN-DP strategy is 10.2% lower than the conventional RB strategy. Full article

Nowadays, mobility represents a key sector to achieve the goal of carbon neutrality. Indeed, the development of hybrid powertrains is contributing to a reduction in the environmental impact of vehicles. One of the most promising energy-saving solutions is regenerative braking, which enables deceleration while recovering energy, otherwise wasted. Even though much scientific community effort has been addressed to the optimization of this technology in the automotive field, the increase of energy storage systems efficiencies enables the overcoming of the constraints related to the reuse of electric energy in railway vehicles. This solution could be extremely useful for those railway vehicles which operate on non-electrified lines, where traction is usually provided by diesel engines. For this reason, the present work focuses on how regenerative braking technology could be exploited in diesel-powered rail applications. In further detail, a diagnostic train working on real railway lines has been considered as a case study. Given the real duty-cycle of the vehicle, a simulation model has been developed with the aim of evaluating the amount of energy recovered during braking phases and, consequently, the fuel saving and the avoided CO₂ emissions. As a result, the analysis shows an improved energy efficiency of propulsion system. Compared with a pure diesel operation, it leads to fuel savings of 20%, a reduction of CO₂ emissions of 22.3 kg with 23.25 kWh stored in the battery at the end of the route. Full article

Advances in power and propulsion and energy management improvements can significantly contribute to reducing emissions. The International Maritime Organization (IMO) Marpol regulations impose increasingly stringent restrictions on ship’s emission. According to the measured data of the target ship in typical working profiles, the power fluctuation, fuel consumption and emission data are analyzed, and the result represented that there are serious fuel consumption and pollution problems in the diesel engine power system. Based on the ship-engine propeller matching design theory, the ship-engine propeller model was built, and the new propulsion system power of the target ship was obtained by simulation. From the perspectives of power, economy and green, the performance and emission indexes of diesel engine and LNG engine are compared and analyzed, and the fuel cost advantage, green advantage and power performance disadvantage of LNG engine compared with diesel engine are determined. By comparing the topological structures of different hybrid propulsion forms, the new propulsion form of the ship is improved to be the gas-electric hybrid propulsion system based on the ESS (Energy Storage System), and the selection of the supercapacitors and lithium batteries is compared. Based on the low-pass filter strategy, the power distribution of the ultracapacitor and lithium battery is distributed. In order to determine the optimal ESS configuration, a capacity configuration model with investment cost, fuel cost and energy storage life as objective functions was established. NGSA-II algorithm was used to calculate the model and scheme selection was completed based on the scheme decision model. In this case, the optimal scheme significantly reduces pollutant emissions, it also reduces daily fuel costs by 38% and the result shows that we can complete the cost recovery in 1.28 years. Full article

The increasing environmental concerns due to emissions from the shipping industry have accelerated the interest in developing sustainable energy sources and alternatives to traditional hydrocarbon fuel sources to reduce carbon emissions. Predominantly, a hybrid power system is used via a combination of alternative energy sources with hydrocarbon fuel due to the relatively small energy efficiency of the former as compared to the latter. For such a hybrid system to operate efficiently, the power management on the multiple power sources has to be optimised and the power requirements for different vessel types with varying loading operation profiles have to be understood. This can be achieved by using energy management systems (EMS) or power management systems (PMS) and control methods for hybrid marine power systems. This review paper focuses on the different EMSs and control strategies adopted to optimise power management as well as reduce fuel consumption and thus the carbon emission for hybrid vessel systems. This paper first presents the different commonly used hybrid propulsion systems, i.e., diesel–mechanical, diesel–electric, fully electric and other hybrid systems. Then, a comprehensive review of the different EMSs and control method strategies is carried out, followed by a comparison of the alternative energy sources to diesel power. Finally, the gaps, challenges and future works for hybrid systems are discussed. Full article