My interest is in long distance commuting (e.g. more than 50 km a day) and the relative efficiencies of different commute bike setups (e.g. drop bars vs flat bars, fenders vs no fenders, panniers vs backpack, etc).
As such, does anyone know if this type of information has been pulled together (e.g. magazine article, web page)? I am looking for hard hard numbers (e.g. wattage or relative difference in wattage) that document real world differences associated with how one sets up their commute bike.
Why I even care
Last year I had my commute bike stole. When I replaced it, I kept most of the build identical (e.g. drop bars, 2x racks, fenders, dynamo hub, disc brakes), except I also moved to an internal hub. When commuting distances, I notice this bike is slower. On the top end I think I lose anywhere from 5 - 10 km/hr. This bothered me so much I ended up building another commute bike, but went in the complete opposite direction (classic steel road, with low profile fenders and one low profile rack). This second bike is so much faster I typically use it on club rides and put the carbon crew to shame.
While there is no question the second bike is more efficient (32 vs 42 km/hr top flatland cruising speed), the builds are also night and day apart so I am racking my brain to point the finger at the main culprits behind this efficiency difference.
If this type of info isn't out there, I would like to run a series of experiments to understand the differences. I would have a designated time trial, record the power needed to cruise at a given set of speeds. I would then slowly strip the bikes down and repeat. The hope would be to determine the relative differences in efficiency different build decisions produce and by extension how much time difference there would be in a 50 km ride.
However before I start this, I would want to make sure this type of experiment hasn't been done before.
NOTE - There may be scepticism over how 'doable' this type of experiment is. If the type of information I am looking for doesn't already exist and there is sufficient interest, I am willing to draft up my planned methodology and post online for review (perhaps at a different and more appropriate venue). I do have expertise in both statistics and experimental design so I believe I would be up to the task.