Search Results (137)

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

Since power demand varies due to uncertain environmental conditions, a deterministic power control strategy for hybrid electric propulsion ships contains a limitation in securing robust performance. To overcome this limitation, this study applies a stochastic power control strategy based on the augmented operational dataset. This study generated 150 datasets and derived the optimal control strategy set using a dynamic programming algorithm. By synthesizing a set of optimal control strategies, we divided them into a total of 10 bins according to the battery state of charge (SOC) and implemented a probabilistic map for the power distribution ratio according to the demanded power in each bin. Additionally, the memory and SOC correction factor were utilized to prevent frequent changes in power control and ensure that the SOC remains stable. This strategy resulted in a 3% improvement in efficiency compared to the deterministic method. In addition, it can be implemented in a real-time strategy utilizing stochastic maps. 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

Recently, as carbon emission regulations enforced by the International Maritime Organization (IMO) have become stricter and pressure from the World Trade Organization (WTO) to abolish tax-free fuel subsidies has increased, the demand for electric propulsion systems in the marine sector has grown. Most small domestic fishing vessels rely on tax-free fuel and have limited cruising ranges and constant-speed operation, which makes them well-suited for electric propulsion. This paper proposes replacing the internal combustion engine system of such vessels with an electric propulsion system. Based on real operating conditions, an Interior Permanent Magnet Synchronous Motor (IPMSM) was designed and optimized. The Savitsky method was used to calculate total resistance at a typical cruising speed, from which the required torque and output were determined. To reduce torque ripple, an asymmetric dummy slot structure was proposed, with two dummy slots of different widths and depths placed in each stator slot. These dimensions, along with the magnet angle, were set as optimization parameters, and a metamodel-based optimal design was carried out. As a result, while meeting the design constraints, torque ripple decreased by 2.91% and the total harmonic distortion (THD) of the back-EMF was lowered by 1.32%. 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

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

The conventional-speed Sliding Mode Controller (SMC) for ship PM propulsion motors, which employs exponential reaching laws and linear sliding surface functions, demonstrates susceptibility to oscillatory phenomena. To solve this problem, this paper proposes a saturation adaptive nonlinear integral sliding mode controller (SANI-SMC) which combines a nonlinear integral sliding surface function with an adaptive saturation gain reaching rate. The nonlinear integral sliding surface function improves the system responsiveness, and then enhances the stability and robustness of the system. The adaptive saturation gain reaching rate not only mitigates the chattering effect induced by the sign function in traditional exponential reaching rates, but also weakens the underlying oscillations. This approach effectively solves the overshoot problem inherent in traditional PI controllers, and has better anti-interference ability under sudden load variations. Finally, the proposed controller is experimentally verified based on an electric propulsion semi-physical experimental platform consisting of Rapid Control Prototyping (RCP), and compared with a Proportional–Integral (PI) controller and an SMC. Moreover, the integral absolute error (IAE), integral time-weighted absolute error (ITAE), and integral of the square value (ISV) metrics are calculated for the PI controller, SMC, and SANI-SMC based on experimental data collection. The results demonstrate that the SANI-SMC exhibits superior stability and robustness compared to both the PI controller and SMC. Full article

Electric propulsion ships have garnered significant attention for addressing the environmental impact associated with conventional shipping vessels. Their performance critically depends on the inverters that control propulsion motors. This study aims to enhance inverter control by addressing the limitations of conventional model predictive control (MPC), particularly its high current errors and total harmonic distortion (THD) owing to the limited switching frequency. Herein, a discontinuous MPC is proposed that is capable of reducing the switching losses by implementing discontinuous switching during high current periods. This approach employs zero-voltage vectors that are selected based on the polarity of the offset voltage to prevent unnecessary switching losses. Experimental results indicate that the proposed approach reduces the current error by up to 45%, THD by up to 30%, and switching losses by 15–25%. Therefore, this study demonstrates the potential of the proposed control strategy to improve the efficiency and reliability of electric propulsion systems, thereby contributing to the advancement of inverter control technology and development of eco-friendly shipping vessels. Full article

Electric and hybrid marine vessels are marking a new phase of eco-friendly maritime transport, combining electricity and traditional propulsion to boost efficiency and reduce emissions. The industry’s advancements in charging infrastructure and strict regulations help these vessels lead the way toward a sustainable and economically viable future in shipping. In this review, electric and hybrid marine vessels are discussed, including past applications and trend demonstrations. This paper systematically analyzes maritime vessels’ energy management and battery systems, highlighting advances in lithium-based and alternative battery technologies. Additionally, the review examines the impact of these technologies on sustainability and operational efficiency in the maritime industry. This paper contributes to the field by presenting a holistic view of the challenges and solutions associated with the electrification of maritime vessels, aiming to inform future developments and policymaking in this dynamic sector. Unlike many existing reviews that focus exclusively on battery chemistries or energy management algorithms, this manuscript integrates multiple aspects of maritime electrification—including propulsion types, charging infrastructure, grid systems (MVDC), EMS, BMS, and AI applications—into one cohesive systems-level review. This cross-sectional integration is particularly rare in the literature and enhances the practical value of the review for designers, policymakers, and shipbuilders. Full article

In the context of the new energy hybrid ship propulsion system (NE-HSPS), the parameters of the rotor speed, torque, and current of the permanent magnet synchronous motor (PMSM) are susceptible to environmental variations and unmodeled disturbances. Conventional nonlinear controllers (e.g., backstepping, PI, and sliding mode) encounter challenges related to response speed, interference immunity, and vibration jitter. These challenges stem from the inherent uncertainties in perturbations and the limitations of the traditional nonlinear controllers. In this paper, a novel Adaptive Finite-Time Command-Filtered Backstepping Controller (AFTCFBC) is proposed, featuring a faster response time and the elimination of overshoot. The proposed controller is a significant advancement in the field, addressing the computational complexity of backstepping control and reducing the maximum steady-state error of the control output. The novel controller incorporates a Nonlinear Finite-Time Command Filter (NFTCF) adapted to the variation in motor speed. Secondly, a novel Nonlinear Sliding Mode Observer (NSMO) is proposed based on the designed nonlinear sliding mode gain function (φ(S_w)) to estimate the load disturbance of the electric propulsion system. The Uncertainty Parameter-Adaptive law (UPAL) is designed based on Lyapunov theory to improve the robust performance of the system. The construction of a simulation model of a hybrid ship PMSM under four distinct working conditions, including constant speed and constant torque, the lifting and lowering of speed, loading and unloading, and white noise interference, is presented. The results of this study demonstrate a significant reduction in speed-tracking overshoot to zero, a substantial decrease in integral squared error by 90.15%, and a notable improvement in response time by 18.6%. 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

The transition to environmentally sustainable maritime operations has gained urgency with the International Maritime Organization’s (IMO) 2023 GHG reduction strategy, aiming for net-zero emissions by 2050. While alternative fuels like LNG and methanol serve as transitional solutions, lithium-ion battery energy storage systems (ESSs) offer a viable low-emission alternative. However, safety concerns such as thermal runaway, overcharging, and internal faults pose significant risks to marine battery systems. This study presents an AI-based fault prediction algorithm to enhance the safety and reliability of lithium-ion battery systems used in electric propulsion ships. The research employs a Long Short-Term Memory (LSTM)-based predictive model, integrating electrochemical impedance spectroscopy (EIS) data and voltage deviation analyses to identify failure patterns. Bayesian optimization is applied to fine-tune hyperparameters, ensuring high predictive accuracy. Additionally, a recursive multi-step prediction model is developed to anticipate long-term battery performance trends. The proposed algorithm effectively detects voltage deviations and pre-emptively predicts battery failures, mitigating fire hazards and ensuring operational stability. The findings support the development of safer and more reliable energy storage solutions, contributing to the broader adoption of electric propulsion in maritime applications. 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