Citation
Selina Pan, Andreas Hansen, Kyle Edelberg, Karl Hedrick. "Enhancing Model-Based Control for Automotive Cold Start Emissions". Talk or presentation, 13, February, 2014; Poster presented at the 2014 BEARS conference.

Abstract
The increasing complexity of modern automotive powertrain systems is creating challenges in the control design and implementation process. This work presents two model-based approaches to overcome these challenges, the goal being more sophisticated control designs that yield reduced development effort: (1) The Verification & Validation (V&V) protocol is employed such that the early design phase mitigates potential issues to save time and cost before the hardware implementation phase. Given a set of control targets, a series of control strategies for uncertainty mitigation have been developed to track ideal desired engine states recommended by Toyota Motor Corporation. These control strategies employ sliding mode control, discrete control, error incorporation, and adaptive control. (2) The high-level modeling (HLM) tool was developed by Toyota to facilitate a mechatronic design, where controller and engine are developed simultaneously. This methodology focuses on framing the model in terms of the laws of conservation, and therefore emphasizes physical relations over empirical ones in order to reduce dependency on test data. Using the HLM approach a cold-start model is derived and model simplification techniques are utilized to obtain a model description that is suitable for symbolic derivation of control laws. For evaluating our research paths experimental testing on a Toyota 2AZ-FE test engine during cold start is performed.

Electronic downloads

• CHESSOverview_BEARS2014_PosterPanHansenEdelbergHedrick.pdf · application/pdf · 753 kbytes

• HTML

  Selina Pan, Andreas Hansen, Kyle Edelberg, Karl Hedrick.
  <a
  href="http://chess.eecs.berkeley.edu/pubs/1057.html"
  ><i>Enhancing Model-Based Control for Automotive
  Cold Start Emissions</i></a>, Talk or
  presentation,  13, February, 2014; Poster presented at the
  2014 BEARS conference.

• Plain text

  Selina Pan, Andreas Hansen, Kyle Edelberg, Karl Hedrick.
  "Enhancing Model-Based Control for Automotive Cold
  Start Emissions". Talk or presentation,  13, February,
  2014; Poster presented at the 2014 BEARS conference.

• BibTeX

  @presentation{PanHansenEdelbergHedrick14_EnhancingModelBasedControlForAutomotiveColdStartEmissions,
      author = {Selina Pan and Andreas Hansen and Kyle Edelberg
                and Karl Hedrick},
      title = {Enhancing Model-Based Control for Automotive Cold
                Start Emissions},
      day = {13},
      month = {February},
      year = {2014},
      note = {Poster presented at the 2014 BEARS conference.},
      abstract = {The increasing complexity of modern automotive
                powertrain systems is creating challenges in the
                control design and implementation process. This
                work presents two model-based approaches to
                overcome these challenges, the goal being more
                sophisticated control designs that yield reduced
                development effort: (1) The Verification \&
                Validation (V\&V) protocol is employed such that
                the early design phase mitigates potential issues
                to save time and cost before the hardware
                implementation phase. Given a set of control
                targets, a series of control strategies for
                uncertainty mitigation have been developed to
                track ideal desired engine states recommended by
                Toyota Motor Corporation. These control strategies
                employ sliding mode control, discrete control,
                error incorporation, and adaptive control. (2) The
                high-level modeling (HLM) tool was developed by
                Toyota to facilitate a mechatronic design, where
                controller and engine are developed
                simultaneously. This methodology focuses on
                framing the model in terms of the laws of
                conservation, and therefore emphasizes physical
                relations over empirical ones in order to reduce
                dependency on test data. Using the HLM approach a
                cold-start model is derived and model
                simplification techniques are utilized to obtain a
                model description that is suitable for symbolic
                derivation of control laws. For evaluating our
                research paths experimental testing on a Toyota
                2AZ-FE test engine during cold start is performed.},
      URL = {http://chess.eecs.berkeley.edu/pubs/1057.html}
  }
  

Posted by Christopher Brooks on 20 Feb 2014.
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