Total engine optimization and control for SI engines using linear parameter-varying models

Abstract

The role that supervisory control or upper-level multi-objective optimization can play in total engine control is considered. This involved the control of an SI engine for a combination of air-fuel ratio, torque, fuel consumption and residual gas fraction. The upper level optimization algorithm, based on Model Predictive Control principles, makes use of a ‘reference model.’ This is constructed as a closed-loop interconnection of the engine model and the lower-level classical torque/air charge and lambda controller. This model is derived in a linear parameter varying form, which facilitates the application of the predictive control law. The main contribution is the proposed hierarchical control structure, which has been assessed in simulation and on a test track, and provides a useful separation in tasks and functionality. The solution is also compared briefly with MPC at both upper and lower levels, using different sample rates.