Energy Consumption Analysis And Optimization Of The Deep-Sea Self-Sustaining Intelligent Buoy

The deep-sea self-sustaining intelligent buoy(DSIB)is an ocean observation device used for detecting the profile parameters from sea level to 4000 m sea area.After deployment,the DSIB will work in the sea for more than 2 years until the power supply is exhausted.Due to the high cost of buoy recovery and the inconvenience of replacing the battery,how to reduce the energy consumption of the buoy operation process to a greater extent has become an urgent problem to be solved.In order to reduce the energy consumption of the DSIB and improve the running time of it,the low energy consumption design of the DSIB is studied as follows:Firstly,the profile motion process and energy consumption source of the DSIB are analyzed,and the energy consumption of the DSIB's cross-section movement process is divided into static energy consumption and dynamic energy consumption,then the static energy consumption is optimized by improved component selection and improved hardware operating modes.The total energy consumption(including dynamic energy consumption and static energy consumption)of a single cross-section motion process is reduced from 1997.5k J to 80.7k J,and the energy consumption ratio in the hovering stage is reduced from 85.85% to 20.94%.Secondly,focusing on the optimization of dynamic energy consumption in the floating stage,the dynamic model of the DSIB's floating process is established,and the energy consumption model is established by combining the dynamic model of the DSIB.At the same time,a stage variable oil draining control mode is proposed.Aiming at the optimization of the energy consumption model of the DSIB's floating process,a single-objective optimization model and a multi-objective optimization model are established respectively.For the single-objective optimization model,the total energy consumption of the DSIB's floating process is set to the optimization objective,and the optimization objectives of the multi-objective optimization model are the dynamic energy consumption and the floating time of the floating motion process.Finally,the non-dominated sorting genetic algorithm-II(NSGA-?)is used to optimize the single-objective energy optimization model and the multi-objective energy optimization model of the DSIB.The results show that the stage variable oil draining control mode can be used as the DSIB's floating control strategy to optimize the floating dynamic energy consumption.The NSGA-? algorithm has good timeliness and accuracy for single-objective optimization of the DSIB.On the basis of considering the increase of static energy consumption,the parameters such as the stage oil quantity and the floating speed judgment threshold obtained by the NSGA-? algorithm can reduce the dynamic energy consumption in the DSIB's floating process by more than 28%.