Design And Implementation Of Vehicle Velocity Planning Subsystem Oriented To Fuel Consumption Optimization

In recent years,with the rising price of ship fuel,the proportion of fuel cost has increased year by year in the total cost of ship operation.The increased fuel cost has brought tremendous pressure to shipping companies.In addition,the International Marine Environment Protection Commission has put forward higher requirements for the energy-saving and environmental protection capability of ships.Therefore,it is of great significance for the development of shipping to control the fuel consumption and save the operation cost of ships.Previous studies have shown that ship speed is one of the main factors affecting fuel consumption.Reducing ship speed can greatly save fuel consumption.Therefore,that adjusting the speed of the ship in the course of navigation to save fuel consumption has become one of the hot research issues in the optimization of ship fuel consumption.The current speed planning seldom considers the influence of weather conditions on fuel consumption in different geographical locations and time between two ports,but carries out unified speed planning.Unified speed planning results in inaccurate results of speed planning and fuel consumption optimization,and can't save fuel most effectively.At the same time,the traditional genetic algorithm also has some shortcomings,such as dependence on the selection of initial population,easy convergence of population to chromosomes with higher fitness,and strong randomness of crossover operator search,which can't jump out of the interval restriction of paternal gene.Therefore,the weather conditions of each period are taken as the influencing factors of fuel consumption model,and the velocity-fuel consumption relationship model under each period of weather condition i s studied.Then the fuel consumption optimization problem of two port routes is transformed into the planning problem of time-interval speed.An adaptive genetic algorithm based on improved cross-selection operator is proposed to solve the speed regulation under multi-constraints.In order to solve the problem of low population richness in traditional genetic algorithm,evolutionary stabilization strategy is introduced into the selection operator to mutate a certain proportion of sub-optimal solutions.That operation has enhanced the diversity of genes while retaining the optimal solution,and ensuring the overall development of the whole population to evolve to the optimum.The method of recombination of crossover operators is improved to avoid the limitation of genes in a fixed interval.Solutions to the infeasible solutions generated by jumping out of gene intervals are proposed.These two improvements enable genetic algorithm to select crossover more reasonably,avoiding rapid convergence of chromosomes and trapping the algorithm into local optimum.The experimental results show that the improved genetic algorithm has stronger ability to optimize ship speed,and the planned sectional speed can effectively reduce the fuel consumption of ships.In addition,this paper develops a subsystem of ship speed planning oriented to fuel consumption optimization,based on the speed planning scheme based on fuel consumption optimization.The system is divided into data acquisition and pre-processing module,route management module,speed optimization module and other modules.Among them,the data acquisition and pre-processing module is responsible for real-time polling and acquisition of navigation weather prediction information,and preprocessing of navigation prediction information.Route management module can manage the routes.That module has realized the addition,deletion and modification of the basic information and other data of the routes.Speed optimization module realized speed planning based on minimum fuel consumption and visualized the display of optimization results.That the subsystem of ship speed planning developed in this paper can provide references for ship pilots to adjust real-time speed.