TripEnergy is a model that turns incomplete information on a personal trip into an estimation of the trip’s energy requirements. It is designed to work with personal vehicle trips, producing energy estimates given travel survey information such trip distance and/or duration. The model is capable of estimating energy requirements for a large variety of internal combustion and battery electric vehicles, and can be extended to work for a wide variety of models including bus, heavy rail and ridesharing. 

Problem Addressed

As renewable energy becomes more integrated with the electric grid and electric vehicles become more common, there is great value for real-time information on current and future vehicular energy consumption for modeling purposes. Currently, trip energy consumption is estimated through complex, black-box simulations that are relatively slow to run and difficult to operate at scale for large datasets, especially in real time. Additionally, such simulation tools require high-resolution velocity vehicular histories that are often not available for the specific trips researchers would like to study. TripEnergy combines the analytic rigor of full simulation methods with ease of use and flexibility, and is particularly geared towards large-scale simulation of regional travel behavior and energy consumption. 


TripEnergy uses a demand model and a vehicle model to estimate personal vehicle energy consumption for trips recorded in a travel survey. The demand model inputs travel survey data and, for each survey trip, matches a large set of possible GPS velocity histories arising from similar trips. This set of GPS trips spans the range of driving conditions that could be associated with that trip through realistic use. 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 EPA reported test data and validated through vehicle simulation software, accounting for tractive energy consumption, conversion efficiency, and climate control auxiliary use.

Additionally, TripEnergy works to simulate travel behavior and energy consumption 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 the transportation network at any one time. Such simulations allow agents to make decisions based on the costs associated with this choice set. This functionality provides more options to the choice sets of simulated users, including more realistic options such as driving in a less aggressive, more fuel-efficient way, or purchasing a more fuel efficient vehicle. 


  • TripEnergy can provide real-time feedback to users regarding the energy impacts of their choices, without expensive direct modeling.
  • Realistic energy use component will allow for model functionality that minimizes energy use, rather than imperfect proxies such as total travel time or total vehicle miles traveled. 
  • Functionality can be expanded beyond vehicular energy consumption to monitor other sources of energy consumption in daily life, e.g. solar panels and other renewable energy sources.