Search Results (88)

This study presents an analytical methodology for evaluating the influence of hull design parameters on the controllability and manoeuvrability of ships equipped with integrated electric propulsion systems. Unlike traditional approaches that examine the hull and propulsion plant independently, the proposed method employs a generalized model of transient modes within the propulsion complex, enabling the coupled interaction among the hull, propulsion units, electric motors, and the electrical power system to be captured during manoeuvring. Active experimental design and regression modelling are applied to construct controllability diagrams, identify the most influential dimensionless parameters, and reduce computational effort. The methodology is used to assess the effect of hull elongation (0.08–0.16 L) with curvature variation limited to 6%. The results show that this degree of elongation has minimal impact on turning performance and course-keeping stability, confirming the feasibility of such design modifications. The proposed approach provides an effective tool for early-stage design and modernization of electric ships and supports decision-making in ship behaviour prediction and traffic management. Full article

This study presents an integrated techno-economic and environmental assessment of shaft generator (SG) integration in marine propulsion systems using alternative fuels. A comprehensive numerical model is developed to simulate the operation of a bulk carrier equipped with a low-speed two-stroke main engine, comparing conventional diesel generator (DG) configurations with SG-powered alternatives under varying ship speeds and auxiliary electrical loads. Three fuel types, heavy fuel oil (HFO), fatty acid methyl esters (FAMEs), and methanol–diesel dual fuel, are analyzed to evaluate fuel consumption, exhaust emissions, and economic feasibility. The results show that SG integration consistently reduces total fuel consumption by 0.1–0.5 t/day, depending on load and fuel type, yielding annual savings of up to 150 tonnes per vessel. Carbon dioxide (CO₂), Nitrogen oxide (NO_x), and sulphur oxide (SO_x) emissions decrease proportionally with increased SG load, with annual reductions exceeding 450 tonnes of CO₂ and up to 15 tonnes of NO_x for HFO systems. Methanol–diesel operation achieves the highest relative improvement, with up to 50% lower CO₂ and near-zero SO_x emissions, despite a moderate increase in total fuel mass due to methanol’s lower calorific value. Economically, SG utilization provides daily fuel cost savings ranging from $200 to $1050, depending on the fuel and load, leading to annual reductions of up to $320,000 for high-load operations. The investment analysis confirms the financial viability of SG installations, with net present values (NPVs) up to $1.4 million, internal rates of return (IRRs) exceeding 100%, and payback periods below one year at 600 kW load. The results highlight the dual benefit of SG technology, enhancing energy efficiency and supporting IMO decarbonization goals, particularly when coupled with low-carbon fuels such as methanol. The developed computational framework provides a practical decision-support tool for ship designers and operators to quantify SG performance, optimize energy management, and evaluate the long-term economic and environmental trade-offs of fuel transition pathways. Full article

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. Full article

In response to the urgent need for reducing greenhouse gas emissions, the Hybrid Contra Rotating Propeller (HCRP) system, which combines a main engine-driven propeller with an electrically driven Podded propeller, has become a promising propulsion system for CO₂ reduction. This paper presents a new power estimation method for ships with HCRP and outlines the required model test procedures. This study proposes a power estimation method tailored for ships equipped with HCRP and outlines towing tank test procedures required for validation. The method separately evaluates open water characteristics of each propeller and accounts for interactions between the propellers, pod, and hull. Sea trials on an actual vessel were conducted, including speed trials at constant rotational speed ratios and variation tests. These trials confirmed the method’s ability to predict propulsion performance across a wide range of ship speeds. The estimated error in total output from the main engine and generator was within 5% at low output and more accurate near the design speed for the tested case. Furthermore, the method accurately estimates the relationship between rotational speed ratio and power distribution between the main engine and generator for the pod motor, demonstrating its effectiveness for performance prediction and design optimization of HCRP-equipped vessels. Full article

In order to analyze and solve the problem of excessive commutation spark of DC motor in ship electric propulsion system, which leads to a decrease in output power and low torque, this paper first establishes a mathematical model of the ship DC motor, builds its simulation model based on the mathematical model, and conducts simulation verification. Secondly, the Cassie arc model is introduced to model the commutation spark, and the Cassie arc model is connected in series in the armature winding of the DC motor to achieve virtual injection of excessive spark fault of the DC motor. Finally, the Fourier transform and wavelet analysis are used to process the data of the armature winding current and excitation current of the DC motor. The simulation results show that when an arc fault occurs in the DC motor, the ripple coefficient of the armature current and excitation current will increase, and the high-frequency component will increase. DB8 is an adopted wavelet function that decomposes the armature current and excitation current six times, and calculates the energy changes before and after the fault of each decomposed signal layer. It is found that without considering the approximate components, the D4 layer wavelet energy of the armature current and excitation current has the largest proportion in the detail components. The D1, D2, and D3 layers’ wavelet decomposition signals of the armature current and excitation current have significant energy changes; that is, the energy increase in the middle and high frequency parts exceeds 20%, and the D3 layer wavelet decomposition signal has the largest energy change, exceeding 40%. This can be used as a fault characteristic quantity to determine whether the DC motor has a large spark fault. This study can provide reference and guidance for online detection technology of excessive sparks in ship DC motors. Full article

Multi-phase brushless DC motors (BLDCMs) have broad prospects in the power propulsion systems of electric vehicles, submarines, electric ships, etc., due to their advantages of high efficiency and high power density. In the above application scenarios, accurately obtaining the rotor position information is crucial for ensuring the efficient and stable operation of multi-phase BLDCMs. Therefore, by analyzing the fault conditions of position sensors in this paper, a fault diagnosis method for position sensors in multi-phase brushless DC motor drive systems based on position signals and fault current characteristics is proposed, with the aim of improving the reliability of the system. This method utilizes the Hall state value determined by the Hall position signal and the current characteristics under the fault state to achieve rapid fault diagnosis and precise positioning of the position sensor. Its advantage lies in the fact that it does not require additional hardware support or complex calculations, and can efficiently identify the fault conditions of position sensors. To verify the effectiveness of the proposed method, this paper conducts experiments based on a nine-phase brushless DC motor equipped with nine Hall position sensors. The results of steady-state and dynamic experiments show that this method can achieve rapid fault diagnosis and location. Full article

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

The implementation of hybrid propulsion systems in vessels has gained prominence due to their significant advantages in energy efficiency and their reduction in harmful emissions, particularly during low engine load operations. This study evaluates hybrid propulsion system applications in two different tugboats, focusing on fuel consumption and engine load across eight distinct operational scenarios, including Istanbul Strait crossings and towing and pushing manoeuvres. The scenarios incorporate asynchronous electric motors with varying power ratings, lead-acid and lithium iron phosphate batteries with distinct storage capacities, and photovoltaic panels of different sizes. The highest fuel savings of 72.4% were recorded in the second scenario, which involved only towing and pushing operations using lithium iron phosphate batteries. In contrast, the lowest fuel savings of 5.2% were observed in the sixth scenario, focused on a strait crossing operation employing lead-acid batteries. Although integrating larger-scale batteries into hybrid propulsion systems is vital for extended ship operations, their adoption is often limited by space and weight constraints, particularly on tugboats. Nevertheless, ongoing advancements in hybrid system technologies are expected to enable the integration of larger, more efficient systems, thereby enhancing fuel-saving potential. Full article

This paper presents a robust optimization-based approach for voyage and power generation scheduling to enhance the economic efficiency and reliability of electric propulsion ships powered by polymer electrolyte membrane fuel cells (PEMFCs) and battery energy storage systems (BESSs). The scheduling method is formulated considering generation cost curves of PEMFCs with mixed-integer linear programming (MILP) and is extended to a robust optimization framework that accounts for marine environmental uncertainties. The robust optimization approach, implemented via the column-and-constraint generation (C&CG) method, ensures stable operation under various uncertainty scenarios, such as wave speed and direction influenced by wind and tidal currents. To validate the proposed method, a simulation was conducted under realistic operational conditions, followed by a case study comparing the MILP and robust optimization approaches in terms of economic efficiency and reliability. Additionally, the optimization model incorporated degradation costs associated with PEMFCs and BESSs to account for long-term operational efficiency. The case study assessed the performance of both methods under load variation scenarios across different marine environmental uncertainties. Full article

Regarding the high susceptibility problem of the Permanent Magnet Synchronous Motor (PMSM) to various uncertain factors, including load variations, parameter perturbations, and external interferences in the ship’s electric propulsion system, this paper presents a non-singular fast terminal composite sliding mode control (NFTCSMC) strategy based on the improved exponential reaching law. This strategy integrates the system’s state variables and the power function of the sliding mode surface into the traditional exponential reaching law, not only enhancing the sliding mode reaching rate but also effectively mitigating system chattering. Additionally, a sliding mode disturbance observer is developed to compensate for both internal and external disturbances in real time, further enhancing the system’s robustness. Finally, the proposed control strategy is experimentally validated using the rapid control prototyping (RCP) technology applied on a semi-physical experimental platform for ship electric propulsion. Experimental results indicate that, compared to traditional proportional–integral (PI), sliding mode control (SMC), and fast terminal sliding mode control (FTSMC) strategies, the NFTCSMC strategy enhances the propulsion and anti-interference capabilities of the propulsion motor, thereby improving the dynamic performance of the ship’s electric propulsion system. Full article

The electrification of ships and the use of electric propulsion systems are projects which have attracted increased research and industrial interest in recent years. Efforts are particularly focused on reducing pollutants for better environmental conditions and increasing efficiency. The main source of propulsion for such a ship’s shafts is related to the operation of electrical machines. In this case, several advantages are offered, related to both reduced fuel consumption and system functionality. Nowadays, two types of electric motors are used in propulsion applications: traditional induction motors (IMs) and permanent magnet synchronous motors (PMSMs). The evolution of magnetic materials and increased interest in high efficiency and power density have established PMSMs as the dominant technology in various industrial and maritime applications. This paper presents a comprehensive comparative analysis of PMSMs and both Squirrel-Cage and Wound-Rotor IMs for ship propulsion applications, focusing on design optimization. The study shows that PMSMs can be up to 3.11% more efficient than IMs. Additionally, the paper discusses critical operational and economic aspects of adopting PMSMs in large-scale ship propulsion systems, such as various load conditions, torque ripple, thermal behavior, material constraints, control complexity, and lifetime costs, contributing to decision making in the marine industry. Full article

Motor vehicles in transport, as one of the important sectors of the economy, emit a significant amount of carbon dioxide and other products in the form of exhaust gases, which are harmful to human health. The emission of exhaust gases from motor vehicles is limited by appropriate regulations in accordance with environmental goals, such as the Paris Climate Agreement. Reduced emissions and fuel (energy) consumption is mainly achieved by applying modern technologies for the production of internal combustion engines; transitioning to cleaner fuels, such as renewable natural gas or biomethane; and using alternative propulsion systems. Biomethane stored in a liquid state in on-board reservoirs has advantages in truck transport, ships, and air traffic. The reason for this is due to the higher concentration of energy per unit volume of the reservoirs and the lower storage pressure and thus higher safety compared to the high-pressure storage option (compressed biomethane). The presented research is related to a proposition regarding the design of drive systems of city buses using biomethane as fuel in cases when fuel is stored on-board the vehicle as gas in a compressed aggregate state. In this study, the results of a calculation method regarding the roof-supporting structure of an experimental bus with gas reservoirs under higher pressure are discussed as well. This study also presents the possibility of reducing harmful emissions if biomethane is used instead of conventional fuels as a transitional solution to electric-powered vehicles. For the sake of comparison, it is suggested that the engaged energy and the amount of produced carbon dioxide emissions within the drive systems of different fuels are calculated according to the recommendations of the standard EN16258:2012. 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

The increasing emphasis on environmental sustainability and stricter gas emissions regulations has made the optimization of fuel and emissions a crucial factor for marine propulsion systems. This paper investigates the potential to improve fuel efficiency and reduce emissions of LNG ship propulsion systems by using different load sharing strategies in Dual-Fuel Diesel-Electric (DFDE) propulsion systems. Using data collected from on-board cyclic measurements and an optimization model, the effects of different load sharing strategies for various types of fuel, such as HFO, MDO, and LNG, under different engine load conditions were investigated. The results of these strategies are compared with those of on-board power management systems (PMS), which evenly allocate power among the engines, irrespective of fuel usage and emission levels. The results show that load adjustments according to the optimization model can considerably increase fuel economy and contribute to the reduction of CO₂ and NO_x compared to standard practice at the equal load in different ship operating modes. Our approach introduces an innovative optimization concept that has been proven to improve fuel efficiency and reduce emissions beyond standard practices. This paper demonstrates the robustness of the model in balancing environmental and operational objectives and presents an effective approach for more sustainable and efficient ship operations. The results are in line with global sustainability efforts and provide valuable insights for future innovations in energy optimization and ship emission control. Full article

The continuously intensified pursuit to reduce emissions related to human activity and the increased competition in maritime sector calls for sustainable and well-planned solutions to conform with environmental constraints and maximize profit, respectively. In a sector that is very critical for human activities, such as the maritime industry, it is essential to be able to reduce ship emissions without increasing the overall cost of operations and the time to transfer the cargo. All these parameters make ship routing and ship emission reduction very crucial. This work examines the effective routing of large ships with an integrated full-electric propulsion system and the optimal power generation scheduling of their generators to attain the minimum possible operational cost. To achieve this, the problem was formulated, modeled and solved in two stages, namely, ship routing and power generation scheduling, respectively. The first stage was solved using the Particle Swarm Optimization (PSO) method and the second one with a conventional optimization algorithm based on the steepest decent concept. The proposed ship routing method is based on the sea resistance concept and the minimization of total ship propulsion energy. The obtained results show that the optimal path is a combination of the minimum distance path and the minimum resistance path. Ship sustainability is reinforced with the reduction in ship operation cost and ship emissions. Ship emission reduction is achieved in the second optimization stage using a suitable emission index that complies with IMO regulations. Full article