Kiwi-drive omni-wheeled go-kart, basic calculations

Hanna Lin and I are going to make kiwikart, a kiwi-drive go-kart. We are going to make two versions, a brushed motor 80-20 version and a brushless motor bamboo version.

Research so far:
Previous omni kart:

Previous bamboo go-kart:

Now for motor and gear ratio (sprocket) selections.

We chose 3x 6” wheels and 3x 4” wheels (for the cheaper brushed 80-20 version). We chose aluminum for the first one because it seemed more durable, and plastic for the latter because the Al version only holds 80lbs per wheel while the plastic version holds 120lbs per wheel. We picked kiwi drive instead of four-wheel drive because it’s much cheaper. (each brushless motor+wheel+controller assembly is upwards of 200 dollars). (plastic 4” dualie) (aluminum 4” dual omni wheel)

We also were trying to decide between a 3:1 and 4:1 ratio. Later we found out that for the 4” wheels at least we can’t get a 4:1 ratio because the sprocket is bigger than the wheels.

Max acceleration calculations:

[K_t = (K_v* frac{2 pi}{60})^{-1} [Nm/A]]
 where $K_t = 236 ; rpm/V$ from hobbyking motor specifications (
[K_t = (236* frac{2 pi}{60})^{-1} = 0.0405 ; Nm/A]
[tau_{max} = K_t I_{max}$ where $I_{max} = 50 ;A]
($I_max$ comes from the controller we selected,
Additionally, we know that

[tau_{max} = F*r = m*a*r] where $r$ is $radius$
[accel = frac{tau_{max}}{mr} = frac{2.03; Nm}{3 ; inches 200 ; lbs}]
where the radius of the wheel is 3” and the cart we estimate to be about 60 lbs with a rider weight of 140 lbs. Plugging into wolfram alpha or google we get
[ accel = frac{2.03}{0.076*90.7} = 0.29 m/sec/sec]

Finally, we account for the fact that, in a kiwi drive, while going forward we are only using 2 of 3 motors and the forward direction of motor force is only 70% ($sin 60 = sqrt{3}/2$). We also need to take the 4:1 or 3:1 gear ratio into account.

$accel = raw-accel * 2 * 0.7 * 4 = 1.6 ; m/sec/sec$ or about $1.6 / 9.8 = 0.16 ; g’s$ of acceleration. In other words, 3.67 mi/hr/sec or going from 0 to 60 mph in 16 seconds. Brisk but not award-winning, but should feel plenty fast on a low-to-the-ground go-kart.

Max speed calculations:
[Omega_{motor} = V_{sys} K_v [rpm]]
The motor can handle 37 volts so we picked 36 volts for the system voltage. As before, the $K_v$ is 236 rpm/V.
[Omega_{motor} = 36 * 236 = 8496 rpm = 141.6 ;rev/sec]
[v_{ground} = frac{141.6 rev}{sec}* frac{2 pi r}{rev} * frac {1}{K_{gear}} * 0.7 * 0.7]
where the 0.7 is for the forward efficiency again. We do another factor of 0.7 for cruising speed instead of no-load speed.
[v_{ground} = frac{141.6 rev}{sec}* frac{2 pi * 0.076}{rev} * frac {1}{4} * 0.49 = 17.5 ; mph]


That’s it so far. We’re using the same motors as chibikart, which are the lower $K_v$ in the SK3 50 mm class at 236 $K_v$. The wheels as mentioned before (100 dollars each for 6” wheels), #25 chain, and sprockets to be determined. We’re using kelly controllers KBS series that can handle 50 A 36V at $150 each. Whew. Okay, a lot more information to come, but a quick braindump for tonight.

research: best practices in online education [WIP]

1 to 2 hour lectures may be better for those driving to work

Yet as consummate professionals, all of you have conducted copious research, applying sound methods and appropriate metrics, which demonstrates the many positive academic benefits of high-quality technology-enhanced education for all learners. And your efforts have produced tremendous innovation in both technology development and the learning sciences.
The problem is that, for the most part, we are sharing that research with each other at conferences and in publications created specifically to advance the e-learning field. So without verifiable data to consider, our more traditional colleagues are still making instructional decisions based on personal experience or professional bias, political expediency, or just because everyone else is doing it.
To read! many links.

Firstly there is the issue of digital mimicry.  The Coursera platform, alongside rival Stanford start-up Udacity and the non-profit venture ‘edX’ from Harvard and MIT, currently hosts courses that are broadly conservative in terms of online educational practices.  All of these MOOC platforms appear to justify their status by promoting curricula that are equivalent to campus-based courses, with a strong focus on content delivery and an emphasis on the rigor and formality of their assessment methods.  However, some of the most interesting and innovative practices in online education have emerged by challenging these very ideas; loosening institutional control of learning outcomes and assessment criteria, shifting from a focus on content delivery to a foregrounding of process, community and learning networks, and working with more exploratory assessment methods – digital and multimodal assignments, peer assessment and group assignments, for example.


So we are keen to avoid both the over-celebratory fetishizing of the teacher associated with some MOOCs, and the tendency to see the technology as allowing us to write the teacher out of the equation altogether. We want to explore how a MOOC pedagogy might work with a construction of the teacher that has an immediacy that can succeed at scale.

The possibility of the ‘online version’ is overstated. The best online courses are born digital.

‘Best practice’ is a totalising term blind to context – there are many ways to get it right.