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High fuel efficiency and low emission technologies, such as Direct Injection (DI) gasoline and diesel engines and hybrid powertrains, have been developed to resolve environmental and energy resource issues. The hybrid powertrain system has achieved superior power performance as well as higher system efficiency and is expected to be a core powertrain technology because it is compatible with various power sources including fuel cells. It becomes important to control complicated hybrid systems that consist of not only a powertrain but also vehicle systems such as regenerative braking. Model-based control and calibration enables both control strategy optimization and control system development efficiency improvement.

This paper considers an application of reference governor (RG) to automotive diesel aftertreatment temperature control. Recently, regulations on vehicle emissions have become more stringent, and engine hardware and software are expected to be more complicated. It is getting more difficult to guarantee constraints in control systems as well as good control performance. Among model-based control methods that can directly treat constraints, this paper focuses on the RG, which has recently attracted a lot of attention as one method of model prediction-based control. In the RG, references in tracking control are modified based on future prediction so that the predicted outputs in a closed-loop system satisfy the constraints. This paper proposes an online RG algorithm, taking account of the real-time implementation on engine embedded controllers.