Hybrid Energy Storage to Control and Optimize Electric Propulsion Systems

Abstract

Today, ship development has concentrated on electrifying ships in commercial and military applications to improve efficiency, support highpower missile systems and reduce emissions. However, the electric propulsion of the shipboard system experiences torque fluctuation, thrust, and power due to the rotation of the propeller shaft and the motion of waves. In order to meet these challenges, a new solution is needed. This paper explores hybrid energy management systems using the battery and ultracapacitor to control and optimize the electric propulsion system. The battery type and ultracapacitor are ZEBRA and MAXWELL, respectively. The 3-, 4-and 5-blade propellers are considered to produce power and move rapidly. The loss factor has been reduced, and the sea states have been found through the Elephant Herding Optimization algorithm. The efficiency of the proposed system is greatly enhanced through torque, thrust and power. The model predictive controller control strategy is activated to reduce load torque and drive system Root Average Square (RMS) error. The implementations are conducted under the MATLAB platform. The values for torque, current, power, and error are measured and plotted. Finally, the performance of the proposed methodology is compared with other available algorithms such as BAT and Dragonfly (DF). The simulation results show that the results of the proposed method are superior to those of various techniques and algorithms such as BAT and Dragonfly.

Comparative Study of THD Characteristics in Different Cascaded H-Bridge Configurations for Multilevel Multicarrier Modulation

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Simulation-Based Evaluation of Sliding Mode Control with Washout Filter for Power Balancing in Battery Energy Storage Systems

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Integrating Quantitative and Qualitative Risk Assessment Models for Mega Infrastructure Ventures

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