Vehicle independent road resistance estimation

Road resistance is commonly divided into a few different components such as rolling resistance, wind resistance and resistance from road gradient (hills). The total sum of road resistance is the force that must be delivered by the powertrain to the wheels of the vehicle in order to maintain speed. The different components of the road resistance have been studied in a number of different projects and a lot is well known. However, in most studies the model parameters used are often dependent on both the vehicle, the road and the surroundings. Some exceptions exist though, especially when it comes to the rolling resistance. The idea with this project is to find models for each of the different components of the road resistance where the input parameters used are either purely vehicle dependent or purely dependent on the road and the surrounding conditions and to develop a method to estimate the data of the surrounding conditions from a large population of vehicles (big data). The advantages with this approach is that data from any vehicle can be used to improve the estimation and that all vehicles can benefit from the estimated data. In the long run, this can lead to a system that dynamically calculates the surrounding parameters of the road resistances and that adapts rapidly to changing conditions such as wind and wet road surface.

The project is expected to:

  • Point out a number of vehicle independent road resistance coefficients
  • Point out a number of road resistance independent vehicle parameters
  • Develop an estimation method from measurements from a large population of vehicles
  • Develop a method for approximating the energy consumption of a road segment from the road resistance coefficients and the vehicle parameters

The result is expected to be useful for:

  1. Improved range estimation of battery electric vehicles
  2. Improved vehicle energy management
  3. Energy efficient and economical route planning.