Research On Energy-saving Path Planning Algorithm For Pure Electric Special Vehicle

Sanitation vehicles are mainly specialized vehicles that complete cleaning,liquor,and garbage transfer functions in urban areas.Pure electric sanitation vehicles can achieve zero emissions and no pollution,and are of great significance to energy conservation,emission reduction and environmental protection.Reasonable planning of routes during the operation of pure electric vehicles can effectively improve energy efficiency and reduce transportation costs.However,due to the characteristics of electric vehicles due to their own battery capacity constraints and many factors that consume electricity during transportation,the path planning model of traditional fuel vehicles is not suitable for electric vehicles.Aiming at the path planning of pure electric sanitation vehicles,this article considers speed,slope and vehicle load to establish a power consumption model.Based on the power consumption model,a path planning model for pure electric vehicles is constructed,and hybrid genetic algorithms and traditional methods are used.The genetic algorithm solves the model separately,and compares and analyzes the results.The main research work of the thesis is as follows:Constructed a path planning model for pure electric special vehicles based on energy consumption: constructed a power consumption model of pure electric special vehicles with respect to factors such as slope,speed and load;built a path planning model for pure electric special vehicles based on the power consumption model,set The constraint conditions such as node,time,power and load are established,and the objective function is established to minimize the total cost of the vehicle,the total mileage cost and the time penalty cost.Designed an energy-saving path planning algorithm for pure electric special vehicles considering energy consumption: Determine the basic elements of genetic algorithm,including offspring,population,encoding and decoding,and genetic operations(selection,cross-mutation),etc.;combined with simulated annealing algorithm,designed a hybrid process Genetic algorithm,including encoding and decoding,genetic operation,fitness function;finally introduced the basic process of hybrid genetic algorithm operation.Carried out the application analysis of the energy-saving path planning algorithm for the pure electric special vehicle: According to the relevant data of a pure electric special vehicle,the actual driving data was analyzed and investigated to determine the common driving speed;the slope constraint and the time window constraint were carried out Solving calculation: The hybrid genetic algorithm is used to solve the path planning model of the pure electric special vehicle,and compared with the solution result of the traditional genetic algorithm,the optimization effect is summarized and analyzed.The main research results of this paper are as follows:(1)After the slope constraint is added to the power consumption model,and compared with the solution result without slope constraint,the total mileage of the vehicle is reduced by 6.15%,the total power consumption is reduced by 3.03%,and the total time cost is reduced by 6.18%.The total cost has been reduced by 1.02%;(2)After adding the time window constraint to the path planning model,and comparing with the solution result without time window constraint,the total mileage of vehicle distribution is reduced by 0.36%,the total time cost is reduced by 0.37%,and the total power consumption is reduced The total cost was reduced by 4.32%,and the total cost was reduced by 1.08%.(3)Comparing the optimal solution of the hybrid genetic algorithm and the original algorithm,when the hybrid genetic algorithm is used to solve the problem,the total mileage of the vehicle is reduced by 0.95%,the total power consumption is reduced by 5.84%,and the total time cost is reduced The total cost is reduced by 0.96%,and the total cost is reduced by 1.48%,so the hybrid genetic algorithm has better solution results.