Reduction of hydrocarbon emissions during the engine cold start process is a major design and control goal in the automotive industry in recent years, with considerable impact on not only the vehicle's fuel economy, but the environment as well. The key to producing the most emission efficient powertrain system is the ability to drive the engine variables to operate under certain behavioral parameters, that is, to drive the engine states to follow ideal desired trajectories. Therefore, the control target of driving down tracking error to produce ideal engine behavior is an important consideration in the control design process. Due to the highly nonlinear and transient nature of the engine cold start process, the choice was made in this work to employ a scalar sliding control technique. Additionally, in order to mitigate possible model uncertainty in real time, an adaptation update algorithm was incorporated. The combined algorithm was implemented on an engine test cell and experimentally validated. The work was inspired by the Verification & Validation procedure used in standard industry practice to reduce errors and uncertainties early on in the control design phase so as to produce desired engine behavior as soon as possible.
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