Evolving School Transport Electrification: Integrated Dynamic Route Optimization and Partial Charging for Mixed Fleets

TL;DR

This paper introduces a comprehensive optimization model for electric school bus routing and partial charging, demonstrating significant cost and distance reductions and supporting the transition to sustainable school transportation.

Contribution

It presents a novel integrated linearized MIP model for dynamic routing and partial charging of heterogeneous electric school bus fleets, considering practical constraints.

Findings

Up to 56.4% reduction in travel distance compared to current practices.

Heterogeneous fleets offer cost savings and efficiency improvements.

Partial charging and optimal riding time enhance route performance.

Abstract

School bus transportation, the largest fleet size for public transportation in the US, plays a significant role in sustainability through transport decarbonization. Thus, effective planning of electric school bus routes and recharge schedules is vital. This study proposes a novel approach that simultaneously addresses electric school bus dynamic routing and partial charge scheduling, considering practical scenarios such as varying student demands, bus capacities, maximum ride time, stop time window, and fleet mixes. The model incorporates constraints like bell time tolerance and battery capacity and charging infrastructure candidate location, making it robust for school bus electrification. A linearized Mixed Integer Programming (MIP) model for homogeneous and heterogeneous fleets with full and partial recharging strategies is formulated. The proposed objective function for nonlinear and linear models is executed and compared for computational effectiveness. The model is tested on various sizes of school networks using modified benchmark instances, and a real-world case study demonstrates the benefits of electrified school transportation. The results show that employing heterogeneous fleets can lead to cost savings, reduced routing distance, and travel time for both the tested networks and the case study. Sensitivity analyses highlight the trade-offs between battery size and total cost. Furthermore, the benefits of partial charging and optimum riding time for school bus routes are suggested. The proposed optimization approach can achieve significant reductions in travel distance, up to 56.4% compared to the current situation and fleet size, supporting the case for school transport electrification. Potential additional investment subsidies from federal and state governments are added benefits for accelerated school bus electrification.