Dynamic Surrogate Trip-Level Energy Model for Electric Bus Transit System Optimization
Document Type
Journal Article
Publication Date
2023
Subject Area
mode - bus, place - north america, place - urban, technology - alternative fuels, technology - emissions, planning - methods, infrastructure - vehicle, infrastructure - maintainance
Keywords
battery-electric buses (BEBs), BEB infrastructure, charging schedules
Abstract
The introduction of electric mobility solutions mitigates transportion-related greenhouse gas emissions. Transit buses are considered a promising candidate for electrification. This study contributes to the growing literature on battery-electric buses (BEBs) and aims to quantify the optimal allocation of BEB infrastructure and charging schedules. A generic model for the charging capacity and scheduling of the BEB network is developed. The proposed model proposes an algorithm for the calculation of trip-level BEB energy consumption based on a surrogate model-based space mapping algorithm. Instead of using vehicle simulators or constant values for the energy consumption rate for each trip, the input space mapping has been applied to a simple coarse model to build an accurate surrogate model. The proposed algorithm is tested on the bus transit network in Belleville City in Canada considering BEBs using both Flash and Opportunity charging. The results show the efficiency of the proposed model and highlight the impact on the optimization results of calculating the trip-level energy consumption compared with the traditional methods.
Rights
Permission to publish the abstract has been given by SAGE, copyright remains with them.
Recommended Citation
Foda, A., Mohamed, M., & Bakr, M. (2023). Dynamic Surrogate Trip-Level Energy Model for Electric Bus Transit System Optimization. Transportation Research Record, 2677(1), 513-528.
