[python] Re: A Bicycle Can Be Self-Stable Without Gyroscopic or Caster Effects
- From: Rodger Evans <sunnycanuck@xxxxxxxxx>
- To: "python@xxxxxxxxxxxxx" <python@xxxxxxxxxxxxx>
- Date: Mon, 18 Apr 2011 10:02:30 -0700
Hi all
I haven't checked the programs but many times a problem with many degrees of
freedom have been well explored with genetic algorithms.
Cheers
Rodger
Sent from Rowlf
On Apr 17, 2011, at 11:04, Vi Vuong <vi_vuong@xxxxxxxxx> wrote:
> Hi Ray,
>
> Thanks for sharing the program. Is there a way to automatically grind
> through the 18 parameter space, and save the output? I think we need to find
> stable speed between 4-8mph to run along with the experimental bike. The
> console output
> velo A B C D E #6 #7
> m/k 10**8 10**9 10**9 10**9 10**10 10**20 10**26
> suggests that when colunm #6 and #7 both go positive then we have stability,
> and can be used to search the parameter space.
>
> Vi
>
> From: RayS <rays@xxxxxxxxxxxxx>
> To: python@xxxxxxxxxxxxx
> Sent: Sun, April 17, 2011 8:01:36 AM
> Subject: [python] Re: A Bicycle Can Be Self-Stable Without Gyroscopic or
> Caster Effects
>
> Interesting thread - the self-stability program I wrote
> http://rjs.org/Python/FrameGeometry.zip
> shows the effect the researchers wrote of pretty clearly. It does also have
> input for rim/tire mass (mouse over the boxes for explanation).
> If a python's:
> - front mass is at least 45cm in front of the pivot line
> - rear mass is <24cm to rear axle
> - trail <11cm
> -wheel mass is low
> it is nearly neutral.
> All these things have been covered on the list one way or another, except
> wheel mass.
> Panniers off the back, shifting weight backward, reduces self-centering force
> on the pivot.
> Weight in the very front can increase some desired flop, but is a sensitive
> factor and makes slow riding more tiresome.
> Trail should generally be minimized.
> Importantly, the dynamics are very sensitive to wheel mass; heavy wheels,
> especially the front, eliminate any chance of stability! If you think about
> it, gyroscopic effect prevents the front wheel from responding to lean, which
> is what gives bikes stability; it actually turns the forks the opposite way
> when leaned.
>
> Remember all this has to do with self-stability, and not necessarily how a
> python "feels" to ride using leg steer. Note that in the attached I set the
> pivot torsional K to -7; a small opposite force like your hips make when
> riding the python which counters the self-center effect. It then has a wide
> range of stable speed. The further mass is from the rear axle the more -K is
> required, and the lower it is the less stable.
>
> It would also be interesting to let the code grind through all reasonable
> combinations of the 18 variables used and see where the islands of stability
> are.
>
> Ray
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