Daniel Auger is a senior lecturer at Cranfield University. He is an expert in control systems, vehicle electrification and autonomy. He leads major work streams on self-driving cars, and he has pioneered advanced battery management algorithms for lightweight lithium-sulfur batteries. He has also introduced new state-of-the-art MSc teaching in applied control engineering.
Control engineering is key to the successful deployment of many cutting-edge vehicle technologies. Even with a rigorous scientific understanding and excellent mathematical models, real-world systems can be unpredictable, since no model is a perfect match for its system ('model uncertainty') and all systems are affected by unknown external factors ('disturbance' and 'noise'). Sometimes the quantities of interest are unmeasurable, e.g. battery state-of-charge. All this can mean that it is difficult to make a system behave as intended, and this usually gets harder when moving away from the laboratory and into practical applications. Control engineers are experienced in managing problems like this and can often dramatically improve a system's behaviour. Sometimes, improvements come as increases in 'performance' measures such as energy efficiency, reliability and driveability. However, in many cases, a system will only work at all because of what control engineers do.
Daniel and his research team at Cranfield are experts in control, simulation, application and duty cycle modelling, hardware prototyping, mixed hardware/simulation test environments and state estimation. Typical applications include hybrid and electric vehicles, advanced battery management systems and autonomous road vehicles.
Daniel studied at Cambridge, receiving the MEng (Hons) and PhD degrees. He then worked in senior control engineering roles in BAE Systems and MathWorks Consulting Services. He joined Cranfield in 2013. He is a chartered engineer, an IET Fellow and an IEEE Senior Member.