Heuristic search towards the invention of an optimal-ignition internal combustion engine

Wuqiao Luo, Christoph Schoning, Lin Li, Yun Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

Abstract

Most internal combustion engines are built on compression or spark ignition, which is far from optimal and the problem of which is more than optimization. This paper first improves a genetic algorithm (GA) for such an application, aiming at the potential invention of a homogeneous charge microwave ignition (HCMI) engine. For an HCMI system, search for optimal emitters under the intrinsic constraints of resonant frequencies forms a coupled constraint optimization problem and poses an intractable challenge to the GA and virtual prototyping for the invention. A predefined GA (PGA) is then developed to handle appropriate frequency ranges for this problem so as to allow the parameters of the emitter, as well as its structure, to be optimized in an evolutionary process. The heuristic search is compared with the deterministic NM simplex and the nondeterministic conventional GA. Results show that while the NM and GA heuristics find an insufficient mode, the PGA often finds the global maximum, with a higher convergence rate and independent of the algorithm's initial settings. When the complexity of the problem increases with the number of variables, the PGA also delivers a robust performance while the NM and the GA yield divergent results. This application confirms the viability and power of evolutionary heuristics in inventing novel real-world solutions if properly adapted.

Original languageEnglish
Title of host publication2016 IEEE Congress on Evolutionary Computation, CEC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4634-4641
Number of pages8
DOIs
Publication statusPublished - 14 Nov 2016
Event2016 IEEE Congress on Evolutionary Computation, CEC 2016 - Vancouver, Canada
Duration: 24 Jul 201629 Jul 2016

Conference

Conference2016 IEEE Congress on Evolutionary Computation, CEC 2016
CountryCanada
CityVancouver
Period24/07/1629/07/16

Fingerprint

Internal Combustion Engine
Heuristic Search
Ignition
Patents and inventions
Internal combustion engines
Genetic algorithms
Genetic Algorithm
Microwave
Microwaves
Charge
Heuristics
Ignition systems
Virtual Prototyping
Robust Performance
Resonant Frequency
Electric sparks
Viability
Convergence Rate
Natural frequencies
Engine

Keywords

  • coupled constraint optimization
  • evolutionary algorithm
  • heuristic algorithm
  • homogeneous charge microwave ignition
  • internal combustion engine

Cite this

Luo, W., Schoning, C., Li, L., & Li, Y. (2016). Heuristic search towards the invention of an optimal-ignition internal combustion engine. In 2016 IEEE Congress on Evolutionary Computation, CEC 2016 (pp. 4634-4641). [7744381] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CEC.2016.7744381
Luo, Wuqiao ; Schoning, Christoph ; Li, Lin ; Li, Yun. / Heuristic search towards the invention of an optimal-ignition internal combustion engine. 2016 IEEE Congress on Evolutionary Computation, CEC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 4634-4641
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Luo, W, Schoning, C, Li, L & Li, Y 2016, Heuristic search towards the invention of an optimal-ignition internal combustion engine. in 2016 IEEE Congress on Evolutionary Computation, CEC 2016., 7744381, Institute of Electrical and Electronics Engineers Inc., pp. 4634-4641, 2016 IEEE Congress on Evolutionary Computation, CEC 2016, Vancouver, Canada, 24/07/16. https://doi.org/10.1109/CEC.2016.7744381

Heuristic search towards the invention of an optimal-ignition internal combustion engine. / Luo, Wuqiao; Schoning, Christoph; Li, Lin; Li, Yun.

2016 IEEE Congress on Evolutionary Computation, CEC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 4634-4641 7744381.

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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Luo W, Schoning C, Li L, Li Y. Heuristic search towards the invention of an optimal-ignition internal combustion engine. In 2016 IEEE Congress on Evolutionary Computation, CEC 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 4634-4641. 7744381 https://doi.org/10.1109/CEC.2016.7744381