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In this paper, the dynamic couplings among different inputs and outputs of ahighly nonlinear spark ignition (SI) engine control problem during the coldstart phase are evaluated by using relative gain array (RGA) technique. First,based on the experimental data, a multi-input multi-output model is developedto represent the engine dynamics. Second, the coupling among different inputsand outputs of the model is evaluated by using RGA technique in both open-loopand closed-loop structures. The results show that although there is an internalcoupling within the engine dynamics in the open-loop framework, the closed-loopengine controller can be designed using a decentralized structure withoutsignificantly affecting the system performance. In the next step, based on anonlinear physics-based model of the engine, a set of single-inputsingle-output (SISO) adaptive second order discrete sliding mode controllers(DSMC) are designed to drive the states of the engine model to theirpre-defined desired trajectories and minimize the tailpipe HC emission, undermodelling and implementation (data sampling and quantization) uncertainties.The real-time test results on an actual engine control unit (ECU) show that theproposed SISO adaptive second order DSMC provides accurate and fast trackingperformance for the highly nonlinear and internally coupled engine dynamics,and can meet the HC emission limit by controlling the engine-out emissions andexhaust catalytic converter efficiency.

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