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Scientific Performance Testing
Power Models  :  Chung Method CdA Estimation
Ride Time (m:s)
Kilos (Rider + Bike)
Average Speed (KPH)
Temp (Deg C)
Highest Elev. (M)
Rel. Humidity (%)
Lowest Elev. (M)
Drivetrain Efficiency (%)
Endpoint elevation dif.
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Ever since bicycle-mounted power meters became popular there has been interest in using field test collected power and speed data to measure a riders aerodynamic drag. In principle this is an easy problem to solve : if you know the riders power, speed, and certain environmental variables you can use a physical model of required power to solve for the CdA parameter.
Unfortunately the test in its most basic form requires a flat, windless environment such as an indoor velodrome and these are thinly spread. What would be nicer is if the test could be conducted outdoors on terrain that isn’t necessarily flat, and in conditions that aren’t necessarily windless. This sounded like an impossibility until just such a test was developed and
by Robert Chung.
The test as implemented here can be conducted on any constant, uninterrupted circuit. It's recommended you use a true circuit, starting and finishing in exactly the same place because this minimises the risk of winds compromising the accuracy of the result and then the riders elevation change can be assumed equal to zero. What's the relevance of elevation change? - Well, this is the key to the method - if a riders speed, power and elevation change are known then a physical model of cycling power can be used to solve for that riders CdA. If you really dont want to use a circuit, can't, or finish the test with an incomplete number of circuits then this is OK too, as long as you can feed the model with the riders net elevation change in meters. This means the altitude of the finish point minus the altitude of the start point, with accuracy, in meters.
To use the simple model on this site you will need to collect speed and power data using a power meter and then extract a time series of this data from your ride file to create file in the form of the example set out
(column 1 is speed data, coulmn 2 is wattage). The file is then read and used to approximate the theoretical CdA of the rider during the ride in question.
Ride Data File
Data File. Create and select a text (.txt) or comma separated values (.csv) file having two comma separated columns of ride data in the same format as the example. A "txt" file can be created easily on most computers while the "Save As" menu in Excel is the easiest way to create a "csv" file from 2 simple columns of spreadsheet data.
Speed In. Select the unit of speed applicable to the recorded data (KPH or MPH).
Interval (Sec). Select the recording interval of your power data in seconds.
Rider + Bike Weight (Kilos). Input total weight in kilos (e.g. 80).
Pressure (Millibars). Input the ambient air pressure in Millibars (e.g. 1013). You can get this number from any good weather forecast.
Temprature (Deg C). Input a temperature in degrees Celcius (e.g. 20)
Relative Humidity (%). Input the ambient air humidity in percent (e.g. 20). Again you can get this number from a weather forecast.
CRR (Rolling Resistance). Select the coefficient of rolling resistance applicable to the course. Typical values are .004 (Asphalt) and .008 (Rough Tarmac).
Endpoint elevation dif. (non-circuits). Applicable only to tests not starting and finishing at the same point. Specify the Finish-Start elevation change in metres. Otherwise leave at 0.
Outputs – Sanity Checks
Before focussing on the CdA estimated by the model it is important to check that the ride data file fed into the model has been read in a way that makes sense. Based on the contents of the file and your parameter inputs each of the summary statistics in this section should make sense. If not, double check everything and try again.
Outputs - CdA
This is the metric of aerodynamic drag (
rag x frontal
rea) calculated in respect of the rider and bike combined. The figure is expressed in metres squared. Typical but not exceptional cycling values are in the range .25 to .40 and you should expect to see a valuewithin or close to this range, otherwise the validity of the test may be questionable. To see some typical CdA values have a look a the
Ride Elevation Profile
An important diagnostic of the validity of this test is whether a graph of the riders calculated changes in elevation matches with the real profile of the circuit or circuits used to conduct the field test. This data can be visualised here. Significant errors, undesirable interruptions such as traffic, or changeable wind effects should reveal themselves in this plot. If you're running the test on a non-circuit with elevation change then you should expect to see the climb or descent reflected in the graph.
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