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Internal combustion spark ignition engine management systems regulate the fuel, spark, and idle air subsystems to achieve sufficient engine performance at acceptable fuel economy and tailpipe emission levels. Engine control units also monitor other engine processes, using a suite of sensors, and periodically check the system actuators' operation to satisfy legislated onboard diagnostics. The majority of production engines regulate the air-to-fuel ratio using a speed-density, or air-flow, control strategy. In this approach, the mass of air drawn into a given cylinder is calculated using the engine speed, manifold absolute pressure, and inlet air temperature. Based on the air mass, appropriate fuel amounts are injected to achieve stoichiometric operation. However, the wide range of operating conditions, inherent induction process nonlinearities, and gradual component degradations due to aging have prompted research into model-based algorithms. In this paper, a nonlinear model-based control strategy will be proposed for simultaneous air-to-fuel ratio control and speed tracking in hybrid electric vehicles. The motivation for engine speed management resides in the integrated control of the engine and a continuously variable transmission for increased efficiency. The proposed backstepping controller uses an observer to reduce the inputs to manifold air mass (e.g., manifold absolute pressure and inlet air temperature) and engine speed. The underlying engine model describes the air intake, fuel injection, and rotational dynamics. For comparison purposes, an existing multisurface sliding mode controller and an integrated speed-density air-to-fuel controller with attached engine speed regulation have been implemented. The performance of each controller is studied using an analytical engine model with representative numerical results presented and discussed to provide insight into the overall performances.