Something a bit different for fun... (credit to Prof. Robert Chung for this concept).
Here's a plot I created from OBD data captured on my short drive from home this morning to a local town:
It's a calculated estimate of the elevation profile of the drive using the relevant equations of motion using the power, speed and distance data the OBD CarScanner app supplies.
First of all it's wrong. The calculated elevation changes are way over exaggerated.
I'm yet to sort through the reasons. The raw data format from the CarScanner app doesn't help and I'm assuming my initial attempt to massage the data into a useable format likely resulted in virtual elevation calculation errors, but really it's just an example of a visual diagnostic tool.
Essentially the principle is balance sheet accounting for energy.
For each time interval, given the speed data you can estimate how much power would be required for each of:
i. the change in kinetic energy from the start to the end of the interval,
ii. overcoming air resistance,
iii. overcoming rolling resistance, and
iv. drivetrain losses.
You add those up and the difference from actual recorded power is then assigned to changes in elevation (gravitational potential energy).
You enter in some starting guesstimates for the coefficients of aerodynamic drag and rolling resistance and then adjust those until they match the actual elevation profile.
It's easiest if you do a loop circuit a few times, then the "virtual elevation" should return to the same level at the same point in the loop on each lap. If they don't then you adjust the CdA and Crr estimated values until they do.
In the above I used the following inputs / assumptions:
Drivetrain Efficiency: 85%
Air density: 1.205 kg.m⁻³
Mass: 1,770 kg
Crr: 0.017
CdA: 0.80 m²
I'll try to find a suitable loop and also see what I can do to correct my data massaging of the carScanner OBD data, and then report back.
It can be a nifty way to estimate the aerodynamics of the car.