The classification between a sequence of highly variable combustion events that have an underlying deterministic pattern and a sequence of combustion events with similar level of variability but random characteristics is important for control of combustion phasing. In the case of high cyclic variation (CV) with underlying deterministic patterns, it is possible to apply closed-loop combustion control on a cyclic-basis with a fixed mean value, such as injection timing in homogeneous charge compression ignition (HCCI) or spark timing in spark ignition (SI) applications, to contract the CV. In the case of a random distribution, the high CV can be avoided by shifting operating conditions away from the unstable region via advancing or retarding the injection timing or the spark timing in the mean-sense. Therefore, the focus of this paper is on the various methods of computing CA50 for analyzing and classifying cycle-to-cycle variability. The assumptions made to establish fast and possibly online methods can alter the distribution of the calculated parameters from cycle-to-cycle, possibly leading to incorrect pattern interpretation and improper control action. Finally, we apply a statistical technique named “permutation entropy” for the first time on classifying combustion patterns in HCCI and SI engine for varying operating conditions. Then, the various fast methods for computing CA50 feed the two statistical methods, permutation and the Shannon entropy, and their differences and similarities are highlighted.
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November 2016
Research-Article
Fast Computation of Combustion Phasing and Its Influence on Classifying Random or Deterministic Patterns
Huan Lian,
Huan Lian
Department of Mechanical Engineering,
University of Michigan,
Ann Arbor, MI 48109
e-mail: hlian@umich.edu
University of Michigan,
Ann Arbor, MI 48109
e-mail: hlian@umich.edu
Search for other works by this author on:
Jason Martz,
Jason Martz
Department of Mechanical Engineering,
University of Michigan,
Ann Arbor, MI 48109
University of Michigan,
Ann Arbor, MI 48109
Search for other works by this author on:
Niket Prakash,
Niket Prakash
Department of Mechanical Engineering,
University of Michigan,
Ann Arbor, MI 48109
University of Michigan,
Ann Arbor, MI 48109
Search for other works by this author on:
Anna Stefanopoulou
Anna Stefanopoulou
Department of Mechanical Engineering,
University of Michigan,
Ann Arbor, MI 48109
University of Michigan,
Ann Arbor, MI 48109
Search for other works by this author on:
Huan Lian
Department of Mechanical Engineering,
University of Michigan,
Ann Arbor, MI 48109
e-mail: hlian@umich.edu
University of Michigan,
Ann Arbor, MI 48109
e-mail: hlian@umich.edu
Jason Martz
Department of Mechanical Engineering,
University of Michigan,
Ann Arbor, MI 48109
University of Michigan,
Ann Arbor, MI 48109
Niket Prakash
Department of Mechanical Engineering,
University of Michigan,
Ann Arbor, MI 48109
University of Michigan,
Ann Arbor, MI 48109
Anna Stefanopoulou
Department of Mechanical Engineering,
University of Michigan,
Ann Arbor, MI 48109
University of Michigan,
Ann Arbor, MI 48109
1Corresponding author.
Contributed by the IC Engine Division of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received January 4, 2016; final manuscript received April 8, 2016; published online May 17, 2016. Editor: David Wisler.
J. Eng. Gas Turbines Power. Nov 2016, 138(11): 112802 (8 pages)
Published Online: May 17, 2016
Article history
Received:
January 4, 2016
Revised:
April 8, 2016
Citation
Lian, H., Martz, J., Prakash, N., and Stefanopoulou, A. (May 17, 2016). "Fast Computation of Combustion Phasing and Its Influence on Classifying Random or Deterministic Patterns." ASME. J. Eng. Gas Turbines Power. November 2016; 138(11): 112802. https://doi.org/10.1115/1.4033469
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