The paper aims to investigate the holistic environmental benefits of using a battery system on a roll on/roll off (ro-ro) passenger ship which was originally fitted with a diesel engine engaged in Korean coastal service. The process of this research has multiple layers. First, the operating profiles of the case ship were collected, such as speed, output, operation time and the configuration of the diesel propulsion system. Second, the full battery propulsion system, in place of the diesel system, was modelled and simulated on a power simulation software (PSIM) platform to verify the adequacy of the proposed battery propulsion system. Then, the life cycle assessment method was applied to comprehensively compare the environmental footprint of the diesel-mechanical and fully battery-powered vessels. A focus was placed on the life cycle of the energy sources consumed by the case ship in consideration of the South Korea’s current energy importation and production status. Three life cycle stages were considered in the analysis: ‘production’, ‘transport’ and ‘use’. With the aid of Sphera GaBi Software Version 2019 and its extensive data library, the environmental impacts at the energy production and transport stages were evaluated, while the same impacts at the use stage were determined based on actual laboratory measurements. The environmental performance of the two scenarios in four impact categories was discussed: global warming potential (GWP), acidification potential (AP), eutrophication potential (EP) and photochemical ozone creation potential (POCP). Results of the comparative analysis are presented based on estimates of the overall reduction in the environmental impact potential, thereby demonstrating the overall benefits of using a battery driven propulsion, with a decrease of the GWP by 35.7%, the AP by 77.6%, the EP by 87.8% and the POCP by 77.2%. A series of sensitivity analyses, however, has delivered the important message that the integration of batteries with marine transportation means may not always be the best solution. The types of energy sources used for electricity generation will be a key factor in determining whether the battery technology can ultimately contribute to cleaner shipping or not. By casting doubts on the benefits of battery propulsion, this paper is believed to offer a meaningful insight into developing a proper road map for electrifying ship propulsion toward zero emission of shipping.

Decarbonization is an ongoing issue in the shipping industry, and electric propulsion systems are being proposed as alternative solutions to satisfy this requirement. To answer the fundamental questions of “Are electric propulsion systems the green solution?” and “Can DC distribution systems contribute to the decarbonization in shipping?”, this paper analyzed DC distribution system electrical characteristics, economic feasibility, and environmental evaluation for a full-scale AC-DC hybrid distribution electric propulsion system facility. By applying the actual ship’s operating profile as inputs, a DC distribution system with an active front end rectifier and a variable speed generator engine was proven to guarantee the same electric stability as the conventional AC distribution system. The life cycle assessment results achieved economic and life cycle environmental benefits of about 10% (8.9% for Case 1 and 12.4% for Case 2). These research findings offer meaningful insights into the DC distribution system to minimize fuel consumption and emissions toward cleaner shipping.

This paper introduces an optimal energy control method whose rule-based control employs the equivalent consumption minimization strategy as the design standard to support a neural network technique. Using the proposed control method, the output command values for each power source based on the load of the ship and the state of charge of the battery satisfy the target of energy optimization. Based on the rules, the load of the ship and the state of charge of the battery were the input in the neural network, and the outputs of two generators were recorded as the output values of the neural network. To optimize the weights of the neural network and reduce the error between the predicted values and results, the Bayesian regularization method was employed, and a single hidden layer with 20 nodes, 2 input layers, and 2 output layers were considered. For the hidden layer, the tansigmoid function was applied, and for the activation functions of the output layers, linear functions were adopted considering the correlation between the input and output data used for training the neural network. The propulsion motor was fitted with a speed controller to ensure a stable speed, and a torque load was applied on the propulsion motor. To verify the accuracy of the neural network learning, a generator–battery hybrid system simulation was conducted using MATLAB Simulink, and the neural network learned values were compared with the generator output command values obtained based on the load of the ship and the battery state of charge. Additionally, it was confirmed that the generator command values were consistent with the neural network learned values, and the stability of the system was maintained by controlling the speed, voltage, and current control of the propulsion motor under various loads of the ship and different battery charge statuses.

In Korea, fishing boats account for 65,452 out of 71,174 coastal ships, and aging ships are a leading cause of environmental problems and economic loss. To solve this problem, the government has enacted a policy to promote the development and distribution of environmental vessels. Electric propulsion systems and hybrid systems are suggested as alternatives. However, to study whether this hybrid system is environmentally friendly, a system for measuring the performance of conventional diesel-powered ships was developed and measured. A case study applying the battery hybrid system was analyzed through a Matlab/Simulink simulation, and the effect of reducing the carbon dioxide emissions by 7.6% was verified. In addition, comparing with a case where the load-sharing optimal control was introduced, we proved that the carbon dioxide reduction with the controller was 10.7%. By applying the results of this study to various countries with different fuel production processes through the LCA technique, it was confirmed that the battery hybrid system is eco-friendly from the energy production stage, rather than unconditionally, according to the national power production method. Additional research is needed to reflect the aging trend of the entire fleet and to create a detailed category classification through future research.

Global interest in environmentally friendly ships has surged as a result of greenhouse gas reduction policies and the demand for carbon neutrality. Despite growing demand for electric propulsion systems, there is a lack of research and development on crucial components. Efficiency and stability are primarily influenced by the performance of inverters, which are essential for driving propulsion motors. Existing inverter control techniques can be of two types: continuous-PWM (pulse width modulation) methods for harmonic performance enhancement and discontinuous-PWM methods for efficiency improvement by reducing losses. However, there are limitations in that each PWM method exhibits substantial variations in inverter performance based on its operating conditions. To address these challenges, this study proposes the hybrid pulse-width-modulation (HPWM) method for optimal inverter operation. By analyzing the inverter’s operating conditions, the proposed HPWM method adopts various pulse-width-modulation (PWM) strategies based on a modulation index to achieve harmonic improvement and loss reduction. Our focus is on comparing and analyzing diverse PWM techniques under varying modulation indices and frequency conditions to attain the optimal operating conditions. Experimental validation of the proposed method was conducted using a 2.2 kW dynamometer. In comparison with existing PWM methods, the proposed method demonstrated superior performance.

Regulations on emissions from ships are being strengthened, and emission reduction systems and alternative technologies are being developed. In addition, the amount of emissions is closely related to the performance of the propulsion systems of the ship; however, performance measurement systems have mainly been developed for large commercial ships. For small and medium-sized ships, although the output of the propulsion system is rather low, the number of vessels sailing in the coast is very high. Therefore, a performance-monitoring system is required for small and medium-sized ships. However, for small and medium-sized ships, there are no suitable performance and emissions calculation systems. Conventional performance-measuring and analysis systems for large ships have difficulties in terms of their cost and installation when applied to small and medium-sized ships. In this study, a new system was developed that is able to calculate the speed, power, fuel consumption, carbon dioxide emission assumptions, and efficiency of a ship by receiving simple key data such as GPS, fuel flow, and rpm data rather than checking the ship’s condition using massive forms of data. The system transmits data to the shore’s remote-monitoring center in real-time through a communication network. Using these data, it is possible to estimate a ship’s aging factor, engine performance, amount of exhaust gas, etc., and the accumulated data of all coastal ships in a country can be used as basic data for governments to use to support eco-friendly ship policies.