Blackburn_Tech_Trainers_web.pdf

Blackburn Trainers White Paper

Abstract

In March 2009, engineers Michael McColligan and Niko Henderson authored a

comprehensive study analyzing the factors that contribute to bicycle trainer perfor-

mance. heir work efectively debunks a number of longstanding myths and pro-

poses some new ideas for trainer performance metrics.

his abstract presents some of their most important indings in a less technical for-

mat for the cycling professional and enthusias t.

Introduction

Given the competitive nature of the bicycle trainer market—not to mention of

cyclists themselves—it’s no wonder there would be a complex and oten self-con-

tradictory body of information in the ield about which trainers perform better

than others.

From a pure engineering viewpoint, it’s a complex and sophisticated topic in-

volving some highly technical elements like the luid mechanics

of shear stress, magnetic eddy currents and Lenz’s Law, vacuum

cavitation, impellor design, and optimized lywheel mass. But

from the cyclist’s viewpoint—in terms of what you get out of the

trainer once you climb on and start riding—everything boils

down to a handful of critical elements that directly impact the

trainer experience.

One of the problems facing cyclists is that the market is full of

competing claims and counterclaims about what trainers are sup-

posed to do, how they’re supposed to do it, and what they end up

doing in the real world.

We applied standard engineering analyses and practices to the

prevailing wisdom about trainer performance and arrived at some

startling conclusions. (Speciic protocols, math, and data analyses

are all in the White Paper, but here’s the in-the-saddle reality.)

Part One: Three Prevailing Myths About Trainer

Performance

M y th #1: Trainers can—and ought to—“realistically” simulate the resistance forces in-

volved in riding a bicycle.

Trainer manufacturer presentations generally start by showing you a power curve of how

much wattage it takes to ride a bike at increasing speed. he curve itself looks like this:

hen the resistance curve for the trainer is shown to closely match the idealized power curve.

his proposition sounds pretty good until you take a look at the premise their reasoning is

based on.

Re alit y: he whole idea of a “realistic” resistance curve isn’t very realistic.

Diferences in rider/bike weight and the normal range of rider frontal area alone (.4-.7m 2 ) cre-

ate huge diferences in real-world resistance 1 which trainers have no means of correcting for.

Factor in other uncompen-

sated elements such as hills,

crosswinds, and cornering,

and it’s clear that no existing

trainer technology allows for

this kind of variance.

In terms of aerodynamics

alone, the smallest-normal

frontal area rider (lat course,

no wind), is going to take

196 watts to maintain a

speed of 11 m/s (slightly less

than 40kph/25mph) But the

largest-normal rider the same

speed will require 318 watts of

output, a 62% net diference.

Figure 1. An idealized power curve (from the rider’s point of view) or resistance curve

(from the trainer’s).

Of course, trainer manufac-

turers (including us) try to

hit a value somewhere in the

middle of that range. hat’s

only reasonable. And some

1 All speed/power calculations are done using Tom Compton’s excellent Forces On Rider calculator (http://www.analyticcycling.com/ForcesPow-

er_Page.html). his method was selected because of its analytical rigor, the general acceptance of its methodology among competing trainer

brands, and because riders can easily access it and plug their own variables in. For a good discussion of the mechanics of bicycle speed/power

dynamics, see http://en.wikipedia.org/wiki/Bicycle_performance, which in turn, is based largely on S.S. Wilson’s groundbreaking Bicycle

Technology,( Scientiic American , March 1973) and, the venerable Bicycling Science (hird Edition ed.), 2004. he MIT Press. p. 126. ISBN 0-262-

73154-1.) by David Gordon Wilson & Jim Papadopoulos.

succeed better than others.

But the point is, as a cyclist,

there’s only one curve that

matters. Yours . And unless

you happen to have exactly

the combination of inputs 2 as

your trainer’s resistance curve

(pretty unlikely), your trainer

will not simulate your on-bike

reality .

Figure 2. Power/resistance curves for two riders with typical frontal areas. As you can

see, not just the wattage, but the shape of the curve itself is markedly diferent.

So at best, a trainer can have

a resistance curve that is

the same general shape as a

typical rider’s power curve

under typical conditions.

And it turns out that even

that’s not particularly useful,

given the way cyclists actually

use trainers.

M y th #2: Some trainer

brands are more “realistic”

than others .

his is a variation on the “accurate” resistance curve myth. A number of trainer brands gener-

ate graphs that attempt to prove this.

Re alit y: It’s a lot more complicated than some manufacturers would have you believe. And

the likelihood of any trainer coming within 100 watts of your entire personal power curve is

efectively zero.

When we actually put trainers from leading brands into the test lab 3 , some interesting things

come to light.

Manufacturer

Magnetic Resistance

Fluid Resistance

Elite

Crono

Primo

Kurt-Kinetic

(none)

Road Machine

Minora

Mag 850

VFS-G

Tacx

Satori

Cycle Force Flow

CycleOps

Magneto, Magneto 2006

Jet Fluid Pro

Blackburn

Tech Mag 6

Tech Fluid

2 he Forces on Rider model recognizes ten elements: Efective Frontal Area, Drag, Air Density, Rider/Bike Weight, Rolling Resistance, Slope, Speed,

Pedal Cadence, Crank Length, and Efective Pedaling Range.

3 Test igures and protocols are reviewed in detail in the white paper.

First let’s look at test results

from the magnetic-resistance

trainers on their lowest and

highest settings, in Figure 3

on to your let.

And the luid-resistance 4

units (Fig. 4, following page),

which have a single setting:

As you can see, the magnet-

ic-resistance trainer curves

are generally more “linear”

than the luid resistance

units. However the test data

reveals some important ad-

ditional conclusions:

• All trainers tested gener-

ally fall within the broad

overall range of predicted

“real world” results.

Figure 3. Magnetic-resistance trainers on their lowest and highest settings, respectively.

• None of the trainers tested

reliably models any “real

world” curve . More to the

point, a more expensive

trainer does not deliver a

‘realistic’ feel.

• While diferent trainers and

resistance technologies get

closer to an idealized curve

at diferent points in their

power/resistance band, no

trainer tested consistently

came within 100W of a

theoretical-average power

curve , let alone the speciic

one for any individual rider

or course.

So where does this leave the

larger question of trainer

performance? it turns out the answer has more to do with how cyclists use trainers than with

the trainers themselves. In other words, it’s all about the rider. More about that in a minute.

M y th #3: Fluid resistance trainers provide a more “realistic” and “accurate” road feel

overall.

4 Note: because it uses centripetal magnets in an attempt to simulate a luid-resistance unit’s resistance curve, the CyclOps Magento is tested with

both groups.

Plik z chomika:

Inne pliki z tego folderu:

Inne foldery tego chomika: