Model And Simulation Of Multi-objective Dispatching For Unmanned Electric Trucks Of New Energy In Open-pit Mine

With the continuous expansion of the mine scale,the queuing phenomenon of mining vehicles caused by the traditional dispatching and management mode is becoming seriously.Meanwhile,the heavy use of mine vehicles also produces huge carbon emissions,which leads to a series of environmental pollution problems.In this background,to vigorously promote the construction of low-carbon green mines,the electric unmanned trucks of new energy are widely applied in the production of open-pit mines.However,due to the limited capacity of their batteries,reasonable charging scheduling is required for trucks in the process of mine transportation to ensure smooth and efficient production.Therefore,to improve the truck transportation efficiency and maximize the mining benefit,a multi-objective scheduling optimization model for openpit mine of new energy pure electric unmanned truck based on charging demand was constructed,and the efficient solution of the algorithm was studied for the truck scheduling model.The main contents of the research are as follows:(1)Firstly,the domestic and foreign-related researches were summarized from the aspects of the construction of vehicle scheduling model and design of solution method,and the necessity of new energy pure electric unmanned truck of building a multiobjective scheduling model was discussed.Secondly,centering on the scheduling demand of mine vehicles,the new energy of electric driverless truck and the traditional vehicle scheduling mode were compared and analyzed,which laid a theoretical foundation for the establishment of subsequent scheduling model.Meanwhile,the basic concept of multi-objective optimization is summarized,which provides the method support for settling the multi-objective vehicle scheduling model.(2)Starting from the needs of mine production and vehicle charging,the vehicle battery,shovel production capacity,ore grade,and vehicle loading capacity,and other constraints are considered.A transportation cost and overall truck waiting time for the multi-objective scheduling model of the target was built,which to meet the business enterprise of new energy pure electric open-pit mine no one truck scheduling requirements and development needs.The use of the vehicle can effectively reduce the carbon emission and energy consumption in the transportation while increasing the utilization rate of the vehicle.(3)Aiming at the obvious disadvantages of the classic multi-objective genetic algorithm NSGA-II in solving the vehicle scheduling,such as the loss of population diversity due to fast search,A hybrid genetic immune algorithm suitable for the multiobjective scheduling model in this paper is designed.It is based on the NSGA-II and combined with the mechanism of preserving population diversity of the immune algorithm.Finally,the performance of the algorithm is tested through an example simulation,and the experiment shows that the design of the algorithm in this paper can improve the quality of the obtained scheme significantly.(4)Taking an unmanned intelligent mining area of an open-pit mine in Henan Province as the background,combined with the actual demand of the mine truck dispatching,the multi-objective dispatching model and algorithm constructed were simulated and applied.Through the simulation results,it is found that the model and algorithm can provide a set of economical and feasible vehicle scheduling schemes and charging arrangements for mine transportation while considering the charging demand and production requirements.It improves the utilization rate of equipment and increases the ore transport volume by 12.44%,and reduces the energy consumption in the dispatching process.It can meet the current application demand of new energy pure electric trucks in an open-pit mine and then promote the sustainable development of the mine.