Integrated Optimization Of Electric Bus Scheduling And Maintenance

The electrification of urban buses has become a general trend.Due to the current battery capacity limitation and potential operation risks,electric buses need frequent charging to meet the driving range and frequent maintenance to ensure safety,which puts forward higher requirements for bus operation management.However,the existing research on electric bus scheduling does not take the vehicle maintenance into account,which is bound to push up the vehicle scale and increase the operation cost.In view of this,this paper considers the joint optimization of scheduling plan,maintenance plan and charging plan.The main innovative work of this paper is as follows:(1)On the basis of the scheduling plan,maintenance demands are further considered,a mixed integer programming model for the joint optimization of electric bus scheduling plan,charging plan and maintenance plan is constructed.The model aims to minimize the fleet size,electricity cost,vehicle load difference and maintenance cost.All kinds of constraints such as line operation,vehicle performance,charging and maintenance are considered comprehensively.(2)In view of the complexity of the problem,a three-stage hybrid algorithm is designed.In the first stage,the maintenance date of the vehicle in the future optimization cycle is quickly obtained by an exact algorithm.In the second stage,a simplified model of the original problem was obtained through model decomposition and reconstruction,and the daily scheduling plan and maintenance plan are obtained by exact algorithm.In the third stage,a heuristic algorithm is designed to adjust and optimize the results obtained in the second stage to ensure that the scheme meets the battery constraints and further improves the load balance of the buses.(3)Taking Beijing No.441 bus line as the case,the method is validated and analyzed.The comparative analysis results show that the joint optimization scheme can significantly reduce the fleet size and improve the balance of vehicle load;The solution quality of the proposed three-stage algorithm is better than genetic algorithm and tabu search algorithm.The sensitivity analysis results show that the change of the maintenance cycle has no obvious impact on the fleet size,while the temporary failure rate has a more significant impact on the fleet size.The research work of this paper can provide scientific theoretical guidance and decision-making method support for urban electric bus operation and management.It can also help urban bus operation enterprises improve management efficiency and save operating costs.