AEM AQ1 – Using Data to Develop a Car

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Data trace for turn 8

 

Here we have the data trace for turn 8. Turn 8 and 9 are very high speed corners and are well suited for a car like ours that has high horsepower and a lot of grip. One thing Mark is particularly interested in this area is finding places where he can carry more speed. Within the last two years, the car has gained a lot of horsepower and grip. This means that previous habits that Mark developed for this track are no longer applicable with the new setup.  Looking at the green circled area of the boost trace we see that Mark gets on throttle 63 meters earlier on the main lap than he does in the secondary lap. Looking at the purple circled region of the GPS speed trace, we see that by doing so, Mark is able to maintain more speed throughout turn 8 on the main lap than he did on the secondary lap. The blue circled region in the boost trace represents an area where Mark thinks there can be a lot of improvement. In this region we can see that Mark feathers the throttle a bit here, a habit he was used to doing when the car had less grip. Now, however, Mark feels that he can actually go near to fully flat out on throttle in this region, based on the new tires and aero setup that the car runs. This region represents an area where a lot of time is still left on the table. Looking at the speed split report, we see that Mark has an average speed of 5mph faster and a time of .3 seconds quicker during his main lap than on his secondary lap.

 

Data trace through turn 9 and into the main straight.

 

The image above shows the data trace through turn 9 and onto the main straight. When looking at this trace, Mark was interested to know how much time it takes to return to full boost after closing the throttle, as seen in the green circled areas on the boost trace. Looking at the time traces for these events we found that it takes about a full second to go from vacuum to full boost. Thus, this is one thing that Mark has to keep in mind when he is shifting: is it worth to add a 1 second power delay by shifting or can he just stay at redline for a longer period of time? 

For the driver, data is invaluable as a coaching device. Data can be used to show areas on the track where time can be made up, bad habits that need correcting, or used to investigate subtle things like power delay as a result of shifting. The other beauty behind data logging is that a lot can be learned from a few logged channels. Consider that the above analysis was based off 4 logged channels, of which only 2 sensors were not included with the stock AQ1 data logger. The other beauty with this logger is that more sensors can be added in the future for more in depth data analysis. In the future we plan to expand our “driver aid” sensors to include: steering angle, brake pressure, and clutch sensor to further help Mark find more speed.

 

Using Data from the tuner’s perspective:

Paul Leung of Yimisport is the mastermind behind much of the vehicle fabrication and powertrain tuning of the Jager Racing STI. I sat down with him recently to talk about how he uses data to tune and improve our car.

Currently we use the AQ1 to monitor the performance of our heat exchangers, turbo, and engine oil pressure. In the future we plan to expand the AQ1 to read all our engine parameters, but for now we stick to these few things.

When looking at the data for Paul is interested in these things:

  • Do the heat exchanger temperature readings follow expected trends throughout the run?
  • How does the engine oil pressure change during and after high lateral acceleration?
  • Do we run the risk of boiling coolant or engine oil?
  • How well is wastegate performing at high boost? Do we have any issues here?
  • Do we have adequately sized heat exchangers? Is their placement optimal?

 

Global temperature changes throughout run session.

 

Global oil pressure changes throughout run.

 

The two images above show the oil pressure and temperature traces throughout an entire run session at Big Willow in August. The overall view of the data for the entire session shows a few interesting things. We can see that the fluid temperatures all follow the expected trend: as time increases, temperatures get higher. What is interesting here, however is that the fluid temperatures have not hit their steady state values as they keep increasing throughout the run. This is an interesting by product of the short nature of time attack sessions, and the large heat exchangers and ducting on the car. Considering this data trace was taken during a hot August day, and the car was not “up to temp” by the end of the run suggests that we could probably get away with smaller heat exchangers and ducting. Naturally this is a unique feature of the low number of laps we run in time attack, had this been an endurance racer our outlook would be much different!

 

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