Chris Whiteford is a man on a complex mission. He has just started to build an advanced aerodynamic sensing network that, coupled with data from computer models from CFD / wind tunnel and real world testing, will optimise aerofoil positioning on race cars for maximum efficiency, completely automatically.

The PhD project, which Whiteford is carrying out at Cranfield University, well-known as the UK’s number 1 centre of automotive and motorsport training and research, seeks to investigate exactly what drivers require from the aerofoils. For example, is it optimum downforce that is needed, or is straight-line speed the priority? And, when various manoeuvres are being undertaken, such as overtaking another vehicle or drafting, how is the ideal efficiency of the system affected?

Solution: CAN Datalogger

Kvaser’s Memorator CAN datalogger and interface is being used to build Whiteford’s sensing network, assisting in programming and the structuring of the system. All the systems are interconnected using CAN bus, with all of the sensors running on CAN bus extenders from Microchip. These include independent Pitot-Static sensors, which will provide a pressure comparison across the length of the vehicle, and front mounted sensors, which allow the system to analyse the airflow directly ahead of the car. Various hardware devices within the car, such as the car’s fuel / cooling management system, the power steering system and 4WD controller, will also contribute data.

Once assembled, the sensor system will be integrated into MATLAB and used to generate an aero model on the controlling PC. A combination of computational fluid dynamics / wind tunnel and real world testing will help generate a model of the aerodynamic behaviour of the car under varying conditions, which will then be used to program the car’s core CPU. The car’s aero system will then interact with the target model to determine the most efficient aerofoil position.

Explains Whiteford: “During testing, Memorator will be used to interface to the CAN bus and log the data offline, so it can be examined later. Having two distinct HS channels also allows me to use multiple CAN busses and log them simultaneously, meaning I can build two separate CAN networks to keep the timing essential transactions separate to the bulk data network.”

Notably, due to the complexity of the system and importance of the response times, the CAN data and error handling is extremely critical.

The end goal of this project is a system that runs almost entirely unaided and identifies requirements on the fly. We’ll provide an update when the project nears completion but for more information on the project or to help in any way, please contact Chris at [email protected]

Whiteford is in need of certain pieces of lab equipment and computing devices, so any sponsorship opportunities and/or loan of equipment is gratefully received.

Image courtesy of © Gunnar Assmy – Fotolia.com