### Car Car = Fuelish Hyperbolae

Thursday, October 4th, 2007My blogoverse buddy (B_{v}B^{TM}) Jonathan asked me to contribute to CoM-18, which he is hosting and I am happy to do so. But first a belatedÂ shoutout to my B_{v}B, and best reviewer,Â Dave Marain, who interviewsÂ Professor Lynn Steen,Â a principal architect of the original NCTM Standards andÂ a highly respected voice in reform mathematics.

Don’t expect any research topics here. This is about solving a practical problem in automotive gas economy which involves a pricing anomoly, aÂ Greek mathmatician who may have tutored Alexander the Great,Â and an 18th century Scottish math professor who *almost* loses his job by taking an unauthorized 2-year sabbatical to tour the Continent.Â Can you imagine *not* losing yourÂ job today?

So what is the problem?Â I have 2 cars, an older model which uses regular gas, and a slightly newer model which only uses the more expensive high-test gas, but also gets more miles per gallon (mpg). The question is which isÂ more economical toÂ drive? The pricing anomaly I have observed is that no matter the price per gallon (ppg)Â of gasoline, and the price has fluctuated up and down quite a bit, the difference inÂ price between regular and high-test is almost always a constant, viz., 25 cents.Â So which carÂ is more economical to drive actually depends on the price of gasoline! Observe.

The price per mile, ppmÂ = price per gallon / miles per gallon.Â The percent difference in ppm between regular and high-test,

%diff= (ppm/_{regular}ppm) – 1 = (_{high-test}p/m) – 1,where

p=ppg/_{regular}ppgand_{high-test}

m=mpg/_{regular}mpg._{high-test}

If we take

d=ppg–_{high-test}ppg= $0.25 and_{regular}

m= 25 / 27 and

thenÂ plot **ppg _{high-test }**against

**%diff**we get:

So if the price of high-test is below about $3.35 the gas guzzler is more economical fuel-wise, and versa vice. But what is thisÂ curve?Â A cubic polynomial trend line fits it almost perfectly. So is it a polynomial?Â Zooming out gives usÂ a clue.

It is a rectangular hyperbola (first studied by Menaechmus, a student of Plato,Â about 350 BC)Â flipped on the X axis and asymptotic to X = 0 and Y = 0.08 = (1 / **m**) -1. You can easily see this by rewriting the equation for **%diff** as

%diff=A/ppg+_{high-test}Bwhere

A= -d/mand

B= (1 /m) – 1

So this leaves the question of why a cubic polynomial fits the data so well.Â And here is where our Scottish math professor, Colin MacLaurin, comes in.Â In 1742 heÂ wrote *A Treatise on Fluxions* (pdf), the first systematic applicationÂ of Newton’s calculus, in which he shows, among other trigonometric marvels, how the equation for a hyperbola could be closely approximated by truncating an infinite polynomial series.