Winning Data: Taking data-driven driving decisions with IOT

July 17, 2017, 6:21 p.m.

Project Blyth, part of the Greenpower Education Trust initiative, sees young people building and racing their own electric cars. Since all the cars have the same power source, the difference between winning and losing is dependent on making improvements to the car’s design and driving style.

But how do you know if a change will make the car perform better or worse?

photo taken from the front of an electric race car before the start of the race as teacher carries out final checks with students, driver sitting and ready in car

As part of Connected Hull, we worked with Francis Askew Primary School to investigate collecting data on the forces that were exerted on a car as it raced.

They mounted a 3-axis accelerometer on their race car and used it to measure acceleration. The data was collected with a Raspberry Pi with a LoRaWAN interface, which enabled it to transmit the data, and a sensor board. It was powered by a USB battery pack.

Man holding raspberry pi with sensor hat and aerial to connect to the things network

The graph below shows the magnitude of acceleration and hence the forces acting on the car.

From this we were able to see some oscillations present, and at which points acceleration dropped. Analysing the results the team concluded that, in theory, the car was capable of reaching a higher top speed and reaching that speed faster.

graph showing acceleration data from a car built by 9-11 year olds for Project Blyth

It’s important to remember that these projects are about learning experiences for everyone; unfortunately the sensor was able to move so we couldn’t break down the data to determine the cause of the oscillating forces on race day. However, the collaboration demonstrated the potential of improving race performance as a result of collecting data to inform decision making.

connected hull team member sharing data to teacher on laptop screen

How does the the team intend to secure pole position in future years? They already have plans and ideas about using data and sensors as part of their future builds.

Hear some of their insights on the podcast below:

Images and podcast by Jerome Whittingham


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