Research On The Operation And Scheduling Problem Of Urban Electric Bus

In recent years,in order to cope with climate change and mobile source pollution,alleviate the energy pressure,and promote the concept of green and low-carbon development,the Chinese government has issued a series of policies to support the development of electric vehicle industry.Since the urban public transit undertakes the daily travel of most urban residents,it has obvious publicity and demonstration effect on the promotion of electric vehicles.Therefore,in recent years,urban public transit has become a key area for the country to implement the development policy of electric vehicles.In the bus fleet of many cities,the number of electric buses is increasing year by year.However,due to the limited driving range and charging technology of electric buses,which do not match the existing operation and scheduling management system,many problems and difficulties have arisen in the practical operation,thus reducing the efficiency of public transit companies operation and vehicle scheduling.In addition,the time for the large-scale operation of electric bus is relatively short,and the corresponding operation and scheduling methods need to be further investigated.Therefore,based on the practical operation characteristics of urban public transit,this study conducts research on the operation and scheduling problems of urban electric bus with the goal of improving the operational efficiency of electric bus fleet,improving the service quality of urban public transit,and reducing operating costs.The main research contents of this study are as follows:First of all,from the perspective of public transit companies in the planning stage of electric bus routes,considering the needs and characteristics of the practical operation of urban public transit,this study conducts research on the scheduling problem of electric buses considering multiple vehicle types and nonlinear charging functions with flexible recharging policy.To avoid the problems that may be caused by directly introducing the nonlinear charging function into the mathematical model,such as the difficulty of solving the model,or the inability to verify the accuracy of the solution results,a piecewise linear function method is proposed to model the vehicle’s nonlinear charging process.A mixed integer programming mathematical model for this problem is established based on the connected network theory,and a case study is carried out for four bus lines in Nanjing.The results show the differences in bus purchase cost and deadhead mileages between different bus purchase strategies and different recharging strategies,and verify the validity of the linear approximate charging function.Specifically,the results show that if the linear approximate charging function is directly used to arrange the bus schedule,it will lead to a deviation between the estimated recharging energy and the actual recharging energy of the bus,which may cause serious operational problems such as bus breakdown.Secondly,to meet the needs of the development and reform of Chinese urban public transit in the operation and schedule mode,this study carried out a research on the regional scheduling strategy suitable for Chinese urban public transit.Considering the advantages of regional scheduling strategy and the operability of bus scheduling management,this study proposes two limited regional scheduling strategies,the partial mixed-route strategy and the strategy of limiting the number of route changes of single bus.The two strategies are based on the number of routes that can be crossed by buses and the number of times that buses can cross routes to reasonably control the extent of regional scheduling.Through the analysis and definition of the bus scheduling problem under the two scheduling strategies,mixed integer programming model for the electric bus scheduling problem under these two strategies are established.This problem takes into account complex factors such as multiple depots and multiple vehicle types,and can be proved as an NP-hard problem.In order to solve this problem efficiently,an adaptive largescale neighborhood search algorithm is designed,and the effectiveness and accuracy of the algorithm are verified by random instances.The results of case studies and sensitivity analyses using real-world bus routes data show that both strategies can reduce the total cost of the bus fleet.It also enables public transit companies to comprehensively determine the most reasonable strategy based on their own equipment and management conditions.Then,considering that urban bus routes are affected by complex road environment and other factors,the time and electricity consumption of trips will fluctuate within a certain range,which may affect on the punctuality and cost-effectiveness of bus services.In this study,the static robust scheduling problem of urban electric bus is studied.A scenario-based optimization method is used to establish a static robust scheduling model for electric buses considering multiscenarios.In order to ensure the accuracy of the multi-scenario model,this study obtained several typical bus operation scenarios through cluster analysis method based on the historical operation data of bus routes.In addition,in order to verify the effectiveness of the multiscenario model,a traditional static robust bus scheduling model is also given based on the traditional bus scheduling model.The results of the case study show that the multi-scenario model can better improve the robustness of the resulting bus schedule compared to the traditional model.However,the results of the multi-scenario model are significantly affected by the number of scenarios,and the optimal number of scenarios needs to be determined according to the practical situation.The research results also show that it is better to select the maximum electricity consumption rate based on the historical electricity consumption data of the trip when the transit company formulates the bus purchase plan and schedule.In this way,a more robust plan can be obtained with negligible cost increase.Finally,in order to improve the dynamic control ability of public transit companies in practical operation,this study further studies the dynamic robust scheduling method of electric bus based on the multi-scenario static robust scheduling method.The dynamic robust scheduling method divides the whole day’s operation time of the bus route into several time periods,so that transit companies can predict the subsequent travel time and electricity consumption according to the real-time information.According to the predicted results,the transit company can dynamically adjust the subsequent bus schedule and recharging plan.The mathematical model of the dynamic robust bus scheduling problem of electric bus is established,and case studies are conducted.The research results show that the dynamic robust scheduling method can effectively reduce the delay time and operation cost.Even in the case of large fluctuations in travel time and electricity consumption,the dynamic method can still ensure the stability and punctuality of bus services as much as possible.The research data of this study come from real urban bus route operation data and real urban electric bus electricity consumption data.The research results obtained based on this can provide references and suggestions for public transit companies to scientifically plan and make decisions on electric bus routes,and have important practical significance for improving the service level and reliability of urban electric bus routes.