An Energy Efficiency Optimization Strategy of Hybrid Electric Ship Based on Working Condition Prediction

Optimizing the operational performance of green ships can further improve energy saving and emission reduction effect ships, speed optimization is one more widely used effective measures. It a new challenge for shipping industry to achieve that simultaneously saves energy, reduces emissions meets transportation requirements, while considering changes in navigation environment. In this paper, hybrid electric ship efficiency strategy based on working condition prediction proposed solve problem at future moment, by making time series influencing factors, such as wind current speed. Further, basis establishing sailing model real-time operation index (EEOI) model, EEOI deviation are adopted comprehensive objective function establish dynamic efficiency, time-varying environmental factors. Then, fast Non-Dominated Sorting Genetic Algorithm II (NSGA-II) applied bi-objective obtain optimal engine real time. Finally, experimental studies show energy-saving emission-reduction under given limit requirements environment conditions, which provide theoretical support ships.