EV–EV ENERGY TRADING RESEARCH

Two journeys. One coordinated energy trade.

An optimization framework for recommending charging pads, matching EVs, and defining trading regions.

01 / THE JOURNEY BEGINS

Two journeys. One opportunity to trade.

The white consumer EV needs energy. The blue provider EV has surplus to offer. Follow both journeys as they approach a shared wireless charging pad.

C1 needs 12 kWh · P1 offers up to 18 kWh

01 / 06

Journey

SHARED JOURNEYSimulated traffic

C1 originC1 destinationP1 originP1 destinationC1 D1Need 12 kWhP1 D1Offer surplus

Green · Free flowVehicles move freely.

Yellow · Slow trafficVehicles move in a slower line.

Red · Stopped queueVehicles wait without moving.

The queues on the vertical road are slowing to a stop; they turn red when stopped.

C1 · Consumer18 / 60 kWh

Slow traffic ahead3 vehicles ahead · still moving

Decision 1 · Set the energy need

Where can I obtain 12 kWh?

C1 has 18 kWh in a 60 kWh battery and requests a 12 kWh trade.

P1 · Provider45 / 60 kWh

Slow traffic ahead3 vehicles ahead · still moving

Decision 1 · Set the energy need

Can I offer surplus energy?

P1 has 45 kWh in a 60 kWh battery and offers up to 18 kWh.

00:0000:48

Both EVs keep their own origin and destination as surrounding traffic moves and queues. The next stages identify a suitable meeting pad and trading partner.

DECISION CONTEXT01Both origins and destinations identified02Consumer and provider travel together in view03Energy demand and available surplus considered

Simulated video using generated imagery. Journeys, conditions, ranks, matches, and regions illustrate the research; they are not recorded traffic or live model outputs. Use the linked applications to run the models.

Live research applicationsExplore the coordination pipelineRecommendation → matching → spatial scoping

001 / connected decisionsFrom discovery to coordinated trading

4,551electric vehicles

192wireless charging points

>17Msource journeys

3connected decisions