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Model Predictive Powertrain Control: An Application to Idle Speed Regulation

  • Stefano Di Cairano
  • Diana Yanakiev
  • Alberto Bemporad
  • Ilya Kolmanovsky
  • Davor Hrovat
Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 402)

Abstract

Model Predictive Control (MPC) can enable powertrain systems to satisfy more stringent vehicle requirements. To illustrate this, we consider an application of MPC to idle speed regulation in spark ignition engines. Improved idle speed regulation can translate into improved fuel economy, while improper control can lead to engine stalls. From a control point of view, idle speed regulation is challenging, since the plant is subject to time delay and constraints. In this chapter, we first obtain a control-oriented model where ancillary states are added to account for delay and performance specifications. Then the MPC optimization problem is defined. The MPC feedback law is synthesized as a piecewise affine function, suitable for implementation in automotive microcontrollers. The obtained design has been extensively tested in a vehicle under different operating conditions. Finally, we show how competing requirements can be met by a switched MPC controller.

Keywords

Engine Speed Model Predictive Control Disturbance Rejection Idle Speed Model Predictive Controller 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer London 2010

Authors and Affiliations

  • Stefano Di Cairano
    • 1
  • Diana Yanakiev
    • 1
  • Alberto Bemporad
    • 2
  • Ilya Kolmanovsky
    • 1
  • Davor Hrovat
    • 1
  1. 1.Powertrain Control R&A, Ford Motor CompanyDearborn
  2. 2.Dipartimento di Ingegneria dell’InformazioneUniversità di SienaItaly

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