Design of an SI Engine Cold Start Controller based on Dynamic Coupling Analysis

In this paper, the dynamic couplings among different inputs and outputs of a highly nonlinear spark ignition (SI) engine control problem during the cold start phase are evaluated by using relative gain array (RGA) technique. First, based on the experimental data, a multi-input multi-output model is developed to represent the engine dynamics. Second, the coupling among different inputs and outputs of the model is evaluated by using RGA technique in both open-loop and closed-loop structures. The results show that although there is an internal coupling within the engine dynamics in the open-loop framework, the closed-loop engine controller can be designed using a decentralized structure without significantly affecting the system performance. In the next step, based on a nonlinear physics-based model of the engine, a set of single-input single-output (SISO) adaptive second order discrete sliding mode controllers (DSMC) are designed to drive the states of the engine model to their pre-defined desired trajectories and minimize the tailpipe HC emission, under modelling and implementation (data sampling and quantization) uncertainties. The real-time test results on an actual engine control unit (ECU) show that the proposed SISO adaptive second order DSMC provides accurate and fast tracking performance for the highly nonlinear and internally coupled engine dynamics, and can meet the HC emission limit by controlling the engine-out emissions and exhaust catalytic converter efficiency.