关键词: 电动公交, 车辆调度, 遗传算法, 电池退化, 混合电池配置

Abstract:

To address the challenges such as accelerated battery lifespan degradation and significant fluctuations in driving range caused by extreme temperature variations in cold-region electric buses, this study proposes an integrated scheduling strategy based on “battery-vehicle matching”. This strategy involves equipping buses with batteries of different capacities according to seasonal temperatures and route load demands, enabling public transport operators to formulate more efficient operational plans. In terms of modeling, a mixed-integer programming model is established with the objective of minimizing operator cost. The model comprehensively calculates vehicle battery procurement expenses, daily maintenance costs, and charging expenses that consider time-of-use electricity pricing and demand charges. It quantifies both cyclic and calendar degradation of batteries and integrates them into a comprehensive battery lifespan degradation function incorporated into the overall cost calculation. For algorithm design, a hybrid genetic algorithm ( HGA ) incorporating a post-processing refinement strategy is developed to efficiently solve this NP-hard model. A case study based on actual bus routes in Harbin demonstrates that the optimized strategy reduces the annualized total cost by 17.8%, decreases the required fleet size by 16.4%, and lowers maintenance costs by 16.8%. It is obvious that the dual battery configuration reduces the annualized degradation cost of battery ownership cost by 39.7 %, effectively extending the actual service life of battery assets. Sensitivity analysis shows that appropriately relaxing the state-of-charge (SOC) upper limit during moderate-temperature seasons (e.g., spring and autumn) can reduce cycling frequency, thereby better mitigating battery aging. Finally, the applicability of the model to larger-scale scenarios is discussed. This study provides a theoretical model and optimization tool for the sustainable operation of electric buses in cold regions, and plays an important role in formulating seasonal operation strategies for operators.

Key words: electric bus, vehicle scheduling, genetic algorithm, battery degradation, hybrid battery configuration