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Fuel Economy Assessment of MPC-ACC on Powertrain Testbed

  • Stefano Favelli,
  • Luis M. Castellanos Molina,
  • Alessandro Mancarella,
  • Omar Marello,
  • Eugenio Tramacere,
  • Raffaele Manca,
  • Mario Silvagni,
  • Andrea Tonoli,
  • Nicola Amati

摘要

The development and testing of Advanced Driver Assistance Systems (ADAS) is one of the most active fields in the automotive industry towards Automated Driving (AD). This work presents the deployment and testing of an Adaptive Cruise Control (ACC) based on Model Predictive Control (MPC). The goal is to design and validate through the experimental campaign a computationally efficient longitudinal dynamics controller and assess its fuel economy potential. The development of the control structure as well as the definition of the testing method for energy efficiency assessment are central aspects of this work. The performance of the approach is tested on a light-duty commercial vehicle on a state-of-the-art 4-axis powertrain testbed. The findings demonstrate that the speed profile can be optimized to achieve a fuel reduction of up to \(13\%\) while maintaining mission timing and comfort.