Novel design of charging infrastructure for electrified bus transit network systems

Developed countries globally are designing and implementing strategies to reduce long term greenhouse gas emissions and increase resilience to climate change, with electric vehicle (EV) adoption as a priority. In developing countries, the electrification of public transport and fleet vehicles will likely progress ahead of privately owned ones as these can be more readily regulated to encourage adoption. However, it is likely that a mixture of public and private charging infrastructure would be deployed but that 'hub-based solutions supported by renewable energy mini-grids present an attractive option. This work develops a mathematical modelling toolkit to model the BRT system electrification modelling. The mathematical model that manages the routing of BEBs is extended to a longitudinal dynamic model that describes transit buses' energy consumption rate. To support this, a mathematical optimisation process for determining the critical design variables of allocation of the conductive and inductive chargers is also presented. The proposed mathematical analysis is based on designing and modelling multi-terminal (hub) charging infrastructure to cater to the bus transit network system's charging demand. This novel charging optimisation tool is developed to demonstrate how multiple charging strategies can be employed for a fleet of BEBs to study essential factors of the transit system: such as the trade-offs between alternative charger designs, charger locations, battery sizes, and cost. In this scenario, a series of contextualised simulation studies have been undertaken that focus primarily on the current situation in Lagos, Nigeria. The simulation results for the average power consumption of BEBs show that traffic conditions and route congestion increase the BEB energy consumption. Also, the BEB charging study shows that this proposed transit charging strategy saves costs and could be a key for energy management for the BEB transit network. Furthermore, this work estimates the possible GHG emission saving figure based on the case study.Developed countries globally are designing and implementing strategies to reduce long term greenhouse gas emissions and increase resilience to climate change, with electric vehicle (EV) adoption as a priority. In developing countries, the electrification of public transport and fleet vehicles will likely progress ahead of privately owned ones as these can be more readily regulated to encourage adoption. However, it is likely that a mixture of public and private charging infrastructure would be deployed but that 'hub-based solutions supported by renewable energy mini-grids present an attractive option. This work develops a mathematical modelling toolkit to model the BRT system electrification modelling. The mathematical model that manages the routing of BEBs is extended to a longitudinal dynamic model that describes transit buses' energy consumption rate. To support this, a mathematical optimisation process for determining the critical design variables of allocation of the conductive and inductive chargers is also presented. The proposed mathematical analysis is based on designing and modelling multi-terminal (hub) charging infrastructure to cater to the bus transit network system's charging demand. This novel charging optimisation tool is developed to demonstrate how multiple charging strategies can be employed for a fleet of BEBs to study essential factors of the transit system: such as the trade-offs between alternative charger designs, charger locations, battery sizes, and cost. In this scenario, a series of contextualised simulation studies have been undertaken that focus primarily on the current situation in Lagos, Nigeria. The simulation results for the average power consumption of BEBs show that traffic conditions and route congestion increase the BEB energy consumption. Also, the BEB charging study shows that this proposed transit charging strategy saves costs and could be a key for energy management for the BEB transit network. Furthermore, this work estimates the possible GHG emission saving figure based on the case study