Race Velocity model
The Race Velocity Model was made from the ground up by Team Ladata for Turku AMK's eRallyCross project. The model uses MATLAB and Simulink and works using the process below.
take gps data of any route
Simulate any desired route by importing GPS data into the model. This can be done using free route tracking software such as Garmin or Strava to export the route in GPX format.
Once the *.GPX is imported, the model runs it through a series of projection transformations. This changes the polar latitude and longitude data into cartesian xyz data. This makes calculations significantly less complex and allows the tool to remain understandable from a high level.
Consider Vehicle Characteristics
Next, the model accounts for vehicle parameters, such as motor performance, vehicle drag, and braking force. This is combined with the processed GPS data to create a realistic estimate of the vehicle velocity around the track.
First, acceleration and braking curves are generated for the vehicle over a range of slopes. These are generated by processing the user’s data through fundamental equations for air resistance and vehicle drag. These curves are then combined with the maximum stay on track velocity (from the GPS data) to produce a realistic velocity estimation of the vehicle.
Feed Results into external models
Finally, the estimated velocity data has the potential to be fed into various subsystem models, such as a battery model, to analyse each component’s performance during the race.
For example, the velocity estimation can be fed into the custom battery heat model to produce initial estimates of battery heat production. This can then be used to design a cooling system capable of withstanding the vehicle operating loads. The velocity estimation could also be converted into a battery power demand to feed into a researched model, such as the Equivalent Circuit battery model. This would allow more complex battery behaviour to be accounted for.
