Advanced Techniques for Engine Optimization and Control

Exhibitor: Larry Weng

Supervisor: Zhao Dong

Research Group: Complex and Intelligent Systems

Industry Sector: Transport

With the increasing emphasis on improving emission control and fuel economy of the automotive engine and drive train, many automotive manufacturers are investigating more precise control of the internal combustion engine (ICE) in order to achieve the improvement requested. The proposed project will investigate methods of modelling, control and optimization of the internal combustion engine as a complex system in order to achieve robustness, reliability and efficiency of operation of the engine. This requires advanced optimization techniques, computer modelling and simulation techniques, mechanical analysis, and nonlinear control of dynamical systems. The outcome of this proposed project will help to improve the fuel economy and emission of conventional mass produced automobiles. Improved emission leads to reduction of green house gas impact on the world environment. As the government regulations on the emission become stricter, the automotive manufacturers are forced to develop vehicles with cleaner emission which requires more precise control. The project outcomes may also be used in motor sport to improve engine power. The project outcomes may also be useful for the development of a highly efficient power train for hybrid vehicles, which would also facilitate sustainable energy practice to reduce greenhouse effects.

The objective of this project is to investigate and develop a general framework for optimal engine controller design with control system components based on detailed modelling of the engine dynamics. The project will explore the state of art and advance the characteristic equations modelling an engine system including controllers, and investigate advanced control approaches and optimisation techniques in designing the engine system. The engine system is a complex, interactive, highly nonlinear and dynamical system. Design for such a system requires advanced control and optimisation techniques to meet the objectives that are ultimately targeted at achieving low greenhouse impact, high efficiency and reliability.