AI-controlled stations can charge electric cars at a personal price

However, the researchers point to the importance of taking ethical issues seriously, as there is a risk that the artificial intelligence exploits information from motorists.

Today's commercial charging infrastructure can be a jungle. The market is dynamic and complex, with various subscriptions and free competition between providers. At some fast-charging stations, congestion and long queues occur. In a new study, researchers at Chalmers create a mathematical model to investigate how fast charging stations controlled by artificial intelligence, AI, can help by offering electric car drivers personalised prices, which the drivers can choose to accept or refuse. The AI uses algorithms that adjust prices based on individual factors, such as battery level and the car's geographic location.

“The electric car drivers can choose to share information with the charging station providers and receive a personal price proposal from a smart charging station. In our study, we could show how rational and self-serving drivers react by only accepting offers that are beneficial to themselves. This leads to both price and waiting times being minimised,” says Balázs Kulcsár, Professor at the Department of Electrical Engineering at Chalmers.

In the study, the drivers always have the option to refuse the personal price and choose a conventional charging station with a fixed price instead. The personal prices received by the drivers can differ significantly from each other, but are almost always lower than the market prices. For the providers of charging stations, the iterative AI algorithm can find out which individual prices are accepted by the buyer, and under which conditions. However, during the course of the study, the researchers note that on some occasions the algorithm raises the price significantly when the electric car's batteries are almost completely empty, and the driver consequently has no choice but to accept the offer.

“Smart charging stations can solve complex pricing in a competitive market, but our study shows that they need to be developed and introduced with privacy protection for consumers, well in line with responsible-ethical AI paradigms,” says Kulcsár.

More about the study

The researchers create a mathematical model of the interaction between profit-maximising fast charging stations and electric car users. The ‘charging stations’ can offer public market prices or AI-driven profit-maximising personal prices, which the ‘electric car users’ can then accept or reject based on their own conditions and needs. In most cases, the results are promising, as the AI-generated prices are lower than the market prices.

The research is presented in the paper: ‘Personalised dynamic pricing policy for electric vehicles: Reinforcement learning approach’, published in the journal Transportation Research, Part C: Emerging Technologies.

The researchers involved in the study are Balázs Kulcsár, Sangjun Bae, and Sebastian Gros, active at Chalmers University of Technology, Sweden; Seyong Cyber University, China; and Norwegian University of Science and Technology.

The research is financed by the Swedish Electromobility Centre and partially by the EU project E-Laas.