Automotive combustion modelling and control

This thesis seeks to bring together advances in control theory, modelling and controller hardware and apply them to automotive powertrains. Automotive powertrain control is dominated by PID controllers, look-up tables and their derivatives. These controllers have been constantly refined over the last two decades and now perform acceptably well. However, they are now becoming excessively complicated and time consuming to calibrate. At the same time the industry faces ever increasing pressure to improve fuel consumption, reduce emissions and provide driver responsiveness. The challenge is to apply more sophisticated control approaches which address these issues and at the same time are intuitive and straightforward to tune for good performance by calibration engineers. This research is based on a combustion model which, whilst simplified, facilitates an accurate estimate of the harmful NO x and soot emissions. The combustion model combines a representation of the fuel spray and mixing with charge air to give a time varying distribution of in-cylinder air and fuel mixture which is used to calculate flame temperatures and the subsequent emissions. A combustion controller was developed, initially in simulation, using the combustion model to minimise emissions during transient manoeuvres. The control approach was implemented on an FPGA exploiting parallel computations that allow the algorithm to run in real-time. The FPGA was integrated into a test vehicle and tested over a number of standard test cycles demonstrating that the combustion controller can be used to reduce NO x emissions by over 10% during the US06 test cycle. A further use of the combustion model was in the optimisation of fuel injection parameters to minimise fuel consumption, whilst delivering the required torque and respecting constraints on cylinder pressure (to preserve engine integrity) and rate of increase in cylinder pressure (to reduce noise).