Ehsan Sobhani - MSc Computer Science Thesis Defense - July 23, 2024

Ehsan Sobhani will have his Computer Science MSc defense on Tuesday, July 23 at 10 a.m. on Zoom. The presentation will take place over zoom. Please email Brenda at grad.compsci@lakeheadu.ca for the link.

With the growing focus on sustainable transportation, Battery Electric Buses (BEBs) have emerged as a viable solution. BEBs have received significant recognition as an environmentally conscious and sustainable means of transportation. Designing an effective strategy, which encompasses placing charging sites and implementing proper charging mechanisms, is crucial to ensuring the efficient and consistent charging of BEBs in an electrified public transit system.This research endeavours to tackle the challenge of efficient charging strategies including placement of charging stations, cost of running electric buses, and adhering to the bus timetable. To this end, this thesis outlines a four-step approach for transit system planners to attain optimal solutions, including worst-case energy consumption calculation, off-service charging site placement, off-service (overnight) charging mechanisms, on-route charging planning, determining the required number of BEBs, and their integration into a fully electric transit system. Four novel methods are designed for planning: the Constrained Greedy Clustering (CGC) algorithm, the Priority Charging Mechanism (PCM), the Constraint Affinity Clustering Algorithm (CACA), and timetable tuning. A case study based on the real-world Thunder Bay, ON transit system is discussed to validate the proposed methodologies and assess their effectiveness in improving the BEB fleet’s overall performance. The research results demonstrate significant improvements in operational efficiency, cost reduction, and environmental sustainability by implementing the proposed charging infrastructure optimization strategies.

Everyone is welcome