Applying data analytics and artificial intelligence techniques for optimal design and operation for electrification of the public bus transportation system
€202,250Total Project Costs
3 yrProject Duration
The implementation of a sustainable and efficient electric transportation network requires addressing multiple concerns such as: limited driving range and battery charging/discharging time. Nowadays, electric buses can travel up to 200km on a full charge and the charging time varies depending on the technology from a couple of minutes (with fast-charging stations rated at 450 kWh) to hours (with slow-charging stations rated at 30 kWh). In order to address these limitations, this research team plan to use multiple AI technologies to optimise critical components for the electrification of the public bus transportation system. In this context, they plan to design and implement new algorithms to optimise critical components for the electrification of the public bus transportation system. First, by applying Big Data to analyse the current operations of a selected set of routes. Second, by identifying suitable locations for slow and fast charging stations satisfying a pre-defined set of power and space capacity constraints. And finally, using optimisation technology (e.g., constraint programming, mixed integer linear programming, and metaheuristic search) to provide robust and stable schedules to charge the electric fleet without overloading the national grid and maximising the use of wind power.
Total Project Cost: €202,250
Funding Agency: SEAI
Year Funded: 2019
Lead Organisation: University College Cork (UCC)