Parisa Akaber, a Knowledge Transfer Associate working on a joint project between Newcastle University and Siemens, has developed an artificial intelligence (AI) algorithm as a multi-stage optimisation solution for scheduling and load management of electric fleet charging. The solution enables the complex management of when and for how long vehicles, like buses and trucks, are recharged in large depots to take advantage of lowest cost to charge, matching charging levels of batteries to route requirements and ensure buses are ready to depart on time. Using the solution reduces the total E-fleet charging cost by up to 27% and a total reduction in maximum power peak of up to 50%, compared to unmanaged charging. The resulting savings for the e-depot operators are significant, pressure is taken off the grid at peak times and there is less unnecessary charging as EV batteries can be scheduled to charge only to a certain point based on estimated energy requirement for their next trip.
The project, to create a scheduling and power management platform for e-fleet charging, was the result of a Knowledge Transfer Partnership (KTP): a three-way collaboration between a business, one of the UK’s world- class knowledge bases, and a suitably qualified graduate, funded by a grant to the university from Innovate UK and delivered by KTN.
The KTP is designed to result in lasting and transformative performance enhancements for the business; enriched applications of knowledge and research for the university; and an employment opportunity in a highly fulfilling role for the graduate. Parisa Akaber applied for the post to fit with her PhD studies in Power Systems Engineering; she already has a BSc in Computer Engineering from Shiraz University in Iran and an MSc in Information Systems Engineering from Concordia University in Canada. Her appointment was to work, mentored by Siemens and Newcastle university, for two years embedded in the Siemens MindSphere Lab, already established on the Newcastle campus, linked to international Siemens teams working on overall product development and software implementation in Germany, India and Portugal. Parisa’s PhD studies in Power Systems Engineering and background in both Computer and Information Systems engineering, and her previous international industrial work experience with Hydro-Quebec and Thales Canada in the smart grid sector supported this focus area.
The AI solution that Parisa has developed through this KTP project is performing a multi-stage decision making process including a day-ahead scheduling of EV charging, E-vehicle route mapping and Ebus or Etruck parking allocation within the E-depot, based on available data such as E-vehicle timetables, battery data and depot grid connection capacity. This advance planning then responds to real-time practicalities such as vehicle delays, bad weather or traffic conditions, broken connectors, breakdowns or maintenance requirements which can alter the times and sequence of arrivals, battery state of charge on arrival and, potentially, routes a vehicle will serve. With the overriding requirement that vehicles must be ready to depart on time, the AI solution shifts power demand from time periods when electricity is expensive to times when it is cheap (load shifting); caps the maximum power used at any one time to avoid charging costs based on peak usage; and keeps charging for each EV to the minimum required to serve their assigned route, with a margin for safety.
Parisa, now a full-time member of the Siemens team, commented: “Working as a KTP associate on a cutting-edge project between a leading academic team at Newcastle University and a global technology company in the energy sector like Siemens was a fantastic opportunity for me to marry my academic knowledge and expertise with real-world industry experience. The ability to work with my university professors and the Siemens teams in tandem was hugely rewarding. It enabled a unique research and development process that helped to realise a solution which has the ability to transform the cost and operational profile of EV charging.”
Dr Tim Hughes, Global Product Lifecycle Manager at Siemens, said: “This KTP has been the best experience I have had of a collaboration programme with academia. This was a hugely positive experience for Siemens. Interfacing with the university in this way was very innovative and provided new perspectives on our product development.”
Dr Haris Patsios, Senior Lecturer in Power Systems at Newcastle University said: “This collaborative project was ranked as ‘Outstanding’ by Innovate UK and contributed to an industrial product having direct impact on energy efficiency and decarbonisation, which has a projected annual sales turnover of £4 Million in the next three years. There’s actually not much more to wish for.”
Professor Mike Capaldi, Dean of Innovation and Business, Newcastle University, added: “A core part of Newcastle University’s mission is to utilise our expertise in research to make a difference out there. This industrial collaborative research project has ticked all the boxes in that all parties are delighted with the outcome and Siemens now has a product on the market that will increase the efficiency of charging electric vehicles, taking us a step closer to achieving net zero carbon and reducing pollution in our cities.”
The AI solution is now a core part of the Siemens e-depot charging and power management platform sold globally as software-as-a-service (SaaS) alongside charging infrastructure. Electric buses are key to reducing air and noise pollution in cities, just having one e-Bus travelling approximately 200 km per day can save about 60 tons of CO2 per year compared to even the most modern diesel buses. For this reason, the electrification of local public transportation is often an essential aspect of climate measures in cities.
