文章基本信息

标题：Online optimisation of fuel consumption subject to NO x constraints
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作者：Miguel Ramos ; Chris Manzie ; Rohan Shekhar 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2017
卷号：50
期号：1
页码：8901-8906
DOI：10.1016/j.ifacol.2017.08.1288
语种：English
出版社：Elsevier
摘要：AbstractSeveral variations of extremum seeking algorithms have been successfully used to optimise the fuel consumption in automotive engines, albeit without explicit consideration of the emissions constraints that dictate whether the engine meets legislated standards. By treating the emissions constraints as requiring satisfactionon averageand assuming measurable tailpipe emissions, an augmented extremum seeking algorithm is proposed in this paper. The suggested approach utilises a constrained optimisation method developed for static plants that considers both the original cost function and a constraint function representing the satisfaction of the imposed average constraint. Existing theoretical results are modified to guarantee semi-global practical stability of the approach. The approach is then applied to a high fidelity engine and aftertreatment system simulation to find the optimal spark advance that minimises fuel consumption subject to an NOxconstraint, under the assumption that appropriate sensor feedback is available. The simulation results demonstrate the potential of the proposed approach, and suggest other existing extremum seeking schemes can be readily augmented with the ability to satisfy constraints in an averaged sense.