Idle Speed Control plays a crucial role to reduce fuel
consumption that turns in both a direct economic benefit for
customers and CO\d reduction particularly important to tackle the
progressive global environmental warming. Typically, control
strategies available in the automotive literature solve the idle
speed control problem acting both on the throttle position and the
spark advance, while the Air-Fuel Ratio (AFR), that strongly
affects the indicated engine torque, is kept at the stoichiometric
value for the sake of emission reduction. Gasoline Direct Injection
(GDI) engines, working lean and equipped with proper mechanisms to
reduce NOx emissions, overcome this limitation allowing the AFR to
be used for the idle speed regulation.
In this paper, an effective model of the GDI engine dynamics is
derived, tuned and then used to synthesize a gain scheduling
control strategy which comprises a feedback action acting on the
throttle position, and a feedforward compensator which varies
dynamically the demand of the AFR control task. The former control
action is mainly exploited to accomplish smooth transitions from/to
idle speed regime, whereas the latter copes with torque
disturbances at idle speed mainly due to the intermittent use of
accessory loads. In so doing, a faster actuation path, provided
through the AFR control, is added to the air control path to
increase performance both in terms of disturbance rejection and
fuel economy. Comparison between performance provided by our
control approach and a classical LQ strategy, which controls both
the throttle angle and the spark advance when the AFR is kept at
the stoichiometric value, confirms the effectiveness of the
proposed control architecture with respect to different cost
indexes.
Model validation as well as the effectiveness of the control
design are carried out by means of ECU-1D Engine Co-Simulation
tools. The combination in a one integrated designing environment of
control systems and virtual engine, simulated through high
predictive commercial 1D-code, becomes a high predictive tool for
automotive control engineers and fast prototyping.