Research On Airport Ground Operation Optimization For Fuel Consumption And Emission Reduction

The purpose of this paper is to control the time of the aircraft passing the airport node.Firstly,the calculation model of fuel consumption and emission based on taxiing action was proposed,This model can calculated the fuel consumption and emission during taxiing.The output shows that the aircraft consumes a large proportion of fuel consumption and emissions during waiting.Secondly,the problem of aircraft sequence was studied.The mathematical model was established by considering the constraints such as the landing interval.Reinforcement learning algorithm for dynamic sorting strategy solves the model.Comparison with the of FCFS strategy,the reinforcement learning algorithm combined with the dynamic ranking strategy are better than the FCFS strategy.Finally,based on the calculation model of fuel consumption and emission as the objective,considering the constraint of aircraft runway landing time and taxiing conflict constraint,the taxiing optimization model was established by the aircraft passing the node time as the decision variable.The genetic algorithm was used to solve this model,Compared with TAAM output data,the fuel consumption decreased by 31.59%,CO emissions decreased by 32.29%,HC emissions decreased by 37.74%,and NOX emissions decreased by 35.46%.SO2 emissions reduced by 21.15%,proved that the model-optimized results better than unoptimized results.