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Model-based multiobjective evolutionary algorithm optimization for HCCI engines
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Ma, He, Xu, Hongming, Wang, Jihong, Schnier, Thorsten, Neaves, Ben, Tan, Cheng and Wang, Zhi (2014) Model-based multiobjective evolutionary algorithm optimization for HCCI engines. IEEE Transactions on Vehicular Technology, 64 (9). pp. 4326-4331. doi:10.1109/TVT.2014.2362954 ISSN 0018-9545.
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WRAP_1071244-es-200516-model-based_intelligence_multi-objective_globally_optimization_for_hcci_engines_0212.pdf - Accepted Version - Requires a PDF viewer. Download (2559Kb) | Preview |
Official URL: http://dx.doi.org/10.1109/TVT.2014.2362954
Abstract
Modern engines feature a considerable number of adjustable control parameters. With this increasing number of degrees of freedom (DoFs) for engines and the consequent considerable calibration effort required to optimize engine performance, traditional manual engine calibration or optimization methods are reaching their limits. An automated and efficient engine optimization approach is desired. In this paper, interdisciplinary research on a multiobjective evolutionary algorithm (MOEA)-based global optimization approach is developed for a homogeneous charge compression ignition (HCCI) engine. The performance of the HCCI engine optimizer is demonstrated by the cosimulation between an HCCI engine Simulink model and a Strength Pareto Evolutionary Algorithm 2 (SPEA2)-based multiobjective optimizer Java code. The HCCI engine model is developed by Simulink and validated with different engine speeds (1500-2250 r/min) and indicated mean effective pressures (IMEPs) (3-4.5 bar). The model can simulate the HCCI engine's indicated specific fuel consumption (ISFC) and indicated specific hydrocarbon (ISHC) emissions with good accuracy. The introduced MOEA optimization is an approach to efficiently optimize the engine ISFC and ISHC simultaneously by adjusting the settings of the engine's actuators automatically through the SPEA2. In this paper, the settings of the HCCI engine's actuators are intake valve opening (IVO) timing, exhaust valve closing (EVC) timing, and relative air-to-fuel ratio $lambda$. The cosimulation study and experimental validation results show that the MOEA engine optimizer can find the optimal HCCI engine actuators' settings with satisfactory accuracy and a much lower time consumption than usual.
Item Type: | Journal Article | ||||
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Subjects: | T Technology > TL Motor vehicles. Aeronautics. Astronautics | ||||
Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||
Library of Congress Subject Headings (LCSH): | Automobiles -- Motors -- Cylinders, Automobiles -- Fuel consumption, Automobiles -- Motors -- Exhaust gas, Algorithms | ||||
Journal or Publication Title: | IEEE Transactions on Vehicular Technology | ||||
Publisher: | IEEE | ||||
ISSN: | 0018-9545 | ||||
Official Date: | 31 October 2014 | ||||
Dates: |
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Volume: | 64 | ||||
Number: | 9 | ||||
Page Range: | pp. 4326-4331 | ||||
DOI: | 10.1109/TVT.2014.2362954 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access | ||||
Date of first compliant deposit: | 20 May 2016 | ||||
Date of first compliant Open Access: | 20 May 2016 | ||||
Funder: | Engineering and Physical Sciences Research Council (EPSRC), Jaguar Cars Ltd, Shell Global Solutions (UK) | ||||
Grant number: | EP/J00930X/1 EP/J01043X/1 (EPSRC) |
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