The present paper details a performance analysis made through model-based simulation of a dual stage multi-level control algorithm applied to heavy duty vehicles that accounts for traffic information. Such work exploits a control algorithm at different level of traffic congestion. In the two stages control, the first level entails a supervisory optimizer, which evaluates the optimal speed and gear shifting profile according to road and vehicle information to minimize fuel consumption; the second level is an actuator control that computes the powertrain signals to be applied to the engine actuators to comply with the indications given by the supervisory control. The advancement brought by the present work resides in the introduction of speed constraints related to different traffic levels: i) free flow, ii) free flow/conditioned, iii) conditioned and iv) congested. To each state, a maximum limiting speed is associated and several scenarios are investigated in simulated environment. All the results are compared to a conventional Cruise Controller to assess the achievements in terms of fuel consumption reduction, assessing that the proposed control strategy ensures an average reduction of about 3.5% over all the investigated conditions.
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