TripEnergy uses a demand model and vehicle model to estimate personal vehicle energy consumption for which only limited information is available. The demand model takes limited-resolution input information on a trip's characteristics and matches it with a large set of possible high-resolution velocity histories arising from similar trips. This set of trips spans the range of driving conditions that could be associated with that trip through realistic use. If ambient temperature is not supplied as an input, the demand model also produces a set of possible ambient temperatures for that trip based on the location, time of day, and day of the year on which the trip was taken. This set of velocity histories and temperatures is fed into the vehicle model which converts them into a distribution of possible energy requirements of that trip. The vehicle model is extensively calibrated based on test data and validated through vehicle simulation software, accounting for tractive energy consumption, conversion efficiency, and climate control auxiliary use.
Additionally, TripEnergy has been integrated with a regional transport network simulation, allowing for travel behavior and energy consumption to be modeled on a large scale. These simulation methods evaluate a large number of possible choices for each of the hundreds of thousands of separate agents active on a transportation network at any one time. Such simulations allow agents to make decisions based on the costs associated with this choice set. The ability to estimate energy consumption in real time allows the simulation to provide more options to the choice sets of simulated users, including more realistic options such as driving in a less aggressive, more fuel-efficient way, choosing routes based on minimizing fuel costs, or purchasing a more fuel efficient vehicle.