Short battery ranges are perceived as a major weakness of electric cars. However, this is closely related to a driver’s behaviour. An example: A driver takes her children to school and drives to work, then to the supermarket and finally to the dry cleaner’s. She will likely follow a specific routine, fully charging the car battery beforehand and fast-charging on the way home – both of which is reduces the car’s battery lifespan. Therefore, as part of the project, the researchers are working on the ‘Advanced Driver Assistance System’ (ADAS), an intelligent satellite navigation (satnav) system that will:
- suggest battery-friendly charging times and places: for example at the petrol station next to the dry cleaner’s, when the battery would actually require recharging.
- include real-time information from the power grid. The system will calculate a route that maximises renewable energy use.
- use local power grid data and the weather forecast to prevent strong voltage fluctuations in the grid: If one million electric cars will be on German roads by 2020, as has been envisaged, this could lead to a situation where too many cars are being charged at the same time, potentially causing the power network to become unstable or even to break down completely.
All these factors – the capacity of the electricity grid, the quality of electricity consumed and optimal charging times – are bundled by the Passau team of researchers and sent to the intelligent satnav system. The team will develop learning algorithms able to make decisions and to adapt them according to changing information. For instance, the satnav could prompt the driver to consider weather data on her route: If the sun is shining whilst the driver is at the supermarket, it would be expedient to recharge the car battery sooner than originally planned, thereby significantly increasing the proportion of solar power used in the recharging process, thus making it more environmentally friendly.
Team from Passau examines network integration
‘Our team is focusing on four dimensions of optimisation: First, we want to develop technical solutions that are more battery-friendly. Second, charging processes need to become more network-friendly, protecting the grid stability from the possible effects of increasing e-mobility. One major weakness of e-mobility until now has been a lack of integration of renewable energy sources; we want to offer solutions and control methods for the use of renewable energies. Lastly, we consider drivers’ interests by looking for suitable incentives’, Professor Hermann de Meer explained the remit of the sub-project in Passau.
Deggendorf investigates battery-saving charging processes
The Deggendorf research time are working on battery-friendly charging processes as well as processes optimising battery aging. ‘When considering the driver of a vehicle, their driving behaviour and needs, we can reduce the charging stress of a battery’, Professor Andreas Berl, leader of the Electrific project at the Institute, said. Professor Berl and his team can build on the expertise gained through the E-WALD project. The driver assistance system InCarApp, developed by the institute and installed in the vehicles of fleet operator E-WALD GmbH, collects the necessary data for analysis. Pilot tests will take place in three European regions – the Bavarian Forest, Šumava in the Czech Republic and Barcelona, Spain. Psychological and financial incentive structures are being developed by experts from the fields of psychology and information systems, including discounts or bonuses offered at charging stations.
Eleven European partners are involved in Electrific:
- GFI ADELIOR (Belgium), co-ordinating unit
- University of Mannheim
- Deggendorf Institute of Technology
- E-WALD GmbH
- University of Passau
- FREEMIND CONSULTING (Belgium)
- Czech Technical University in Prague (Czech Republic)
- Has-to-be GmbH (Austria)
- Expertise Ladeinfrastruktur Backend
- Agencia de Ecología Urbana de Barcelona Consorcio (Spain)
- Bayernwerk AG (energy provider/co-operating partner E-WALD GmbH)
- E-Šumava (Czech Republic)
This project is funded by the European Union’s Horizon 2020 Framework Programme for Research and Innovation, Grant Agreement No. 713864.