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Development of Intelligent Energy Management in a Hybrid Charging Station for Commercial Electric Vehicles


   Centre for Doctoral Training in Advanced Automotive Propulsion Systems (AAPS)

   Applications accepted all year round  Competition Funded PhD Project (UK Students Only)

About the Project

Electrification for commercial vehicle (CEV) fleets shows an opportunity to cut emissions, reduce fuel costs, and improve operational metrics. However, infrastructure limitations often inhibit the ability to charge a considerable number of CEVs, particularly all fleets in one designated area.

The use of renewable energy resources such as solar photovoltaic (PV) is a promising energy cost-saving selection for large-scale (commercial) charging stations like depots for commercial electric vehicles (CEVs) to deliver goods and services around the country. However, the intermittency of power output renders it challenging to realise reliable and economical operations. This project proposes a multi-stage hierarchical operation energy management technique of CEVs for depots with a hybrid power generation facility such as on-site PV-grid-tied. In the predictive mode like a day-ahead stage, considering real road networks and battery swapping mode; a coordinated scheduling model of delivery service and charging and discharging for CEVs will be developed to minimise the overall energy and logistics delivery costs considering the predicted PV power generation. Additionally, an optimal solution approach based on digital systems, optimisation, and integration tools like the natural aggregation algorithm can be developed for the software. In the actual operation stage, a model predictive control (MPC)-based rolling horizon operation scenario will be provided to improve CEVs’ charging and discharging decisions with the realisation of real-time PV power output, aiming to minimise the deviation in the actual and day-ahead scheduled interactive power between the depot and the main grid. The project’s main outcome will be a cost-effective software which monitors in real-time and manages the power generation/delivery and charging solutions for CEVs.

In summary, the project’s main tasks are:

  1. Developing a hybrid PV-grid-tied microgrid for CEV depots.
  2. Equipping the microgrid with prediction algorithms to forecast the PV power generations during the day.
  3. Developing an energy management unit to improve the power supply/demand daily.
  4. Real-time monitoring of CEVs for daily routes and corresponding charging plans of each CEV.
  5. Offering cost-effective software oversees the power network as-a-whole from supply to demand (each CEV) for power reliability and availability assessments.
  6. A techno-economic analysis will be carried out to study and better understand the economical benefits for the UK CEVs using the proposed technology. 

Funding Notes

AAPS CDT studentships are available on a competition basis for UK students for up to 4 years. Funding will cover UK tuition fees as well as providing maintenance at the UKRI doctoral stipend rate (£17,668 per annum for 2022/23 rate) and a training support fee of £1,000 per annum.

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