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GOALI: HCCI Engine Control and Optimization Using Extremum Seeking

GOALI: HCCI Engine Control and Optimization Using Extremum Seeking
GOALI:使用极值搜索进行 HCCI 发动机控制和优化
批准号:
0501403
负责人:
Miroslav Krstic
金额:
$0.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2005
资助国家:
美国
项目状态:
已结题
起止时间:
2005-05-15 至 2009-04-30

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中文摘要
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英文摘要
With ith increasing pressure to reduce emissions, the need for ne new lo low polluting engine technologyhas ne never er been greater greater. Consequently Consequently, the HCCI engine, with diesel lik like ef efficienc ficiency, yet lo low par par-iculate and NOx emissions, is a prime candidate. Ho However er, because HCCI en engines gines do not ha have adirect comb combustion ustion trigger trigger, controlling the start of comb combustion ustion is a complicated task. To help mak makethis technology a reality we ha have assembled a team with a background in HCCI engine fundamen- fundamentalstals (La Lawrence wrence Li Livermore ermore National Labs LLNL), state of the art automoti automotive control and enginemapping (F Ford), ord), and adv advanced anced nonlinear control methodologies (UCSD).We plan on addressing HCCI engine mapping issues, as well as engine control, which relieson engine maps. Mapping HCCI engines is a complicated and time consuming process due to theman many engine parameters which must be tuned. Extremum seeking (ES), which we plan to emplo employfor this problem, has been demonstrated at Ford ord Motor Compan Company to be an ef effecti fective tool to reducethe time to map spark ignition engines by a factor actor of three to fi five relati relative to traditional techniques,which can sa save months during the mapping process. The same benefits can be expected xpected with HCCIengines. We wil will impro improve upon Ford' ord's already successful algorithm and test this ne new method oncon conventional entional engines and an experimental xperimental HCCI engine.In addition to mapping and optimization, HCCI engines require feedback control during op- operationeration due to their sensiti sensitivity vity to temperature. We will construct nonlinear control algorithms tocontrol the comb combustion ustion process, building uilding upon our prior results on control of gas as turbine enginecomb combustors. ustors.Our algorithms will be applied to models of the HCCI engine with detailed chemical kineticsand on experimental xperimental engines at LLNL and Ford. ord. These will be helpful steps to bring the HCCIengine technology to a le level el in which we can benefit from its adv advantages antages over er con conventional entional internalcomb combustion ustion engines.Impact Statement. This research will help mak make HCCI engine technology a reality reality, which isimportant due to their promise of green operation and increasingly stringent emissions standards.Intellectual Merit. The program will mak make further adv advancements ancements to ES algorithms, especially inmulti multivariable, ariable, constrained, and fast ast on-line optimization. Such adv advances ances will ha have application toman many other technologies.
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Prescribed-Time Stabilization and Robust Safety
  • 批准号:
    2151525
  • 项目类别:
    Standard Grant
  • 资助金额:
    $37.5万
  • 财政年份:
    2022
  • 负责人:
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  • 依托单位:
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  • 批准号:
    2210315
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  • 资助金额:
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  • 财政年份:
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Smart and Connected Communities- Perspectives for Border Communities
  • 批准号:
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  • 项目类别:
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  • 资助金额:
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  • 财政年份:
    2018
  • 负责人:
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  • 依托单位:
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  • 批准号:
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  • 项目类别:
    Standard Grant
  • 资助金额:
    $17.95万
  • 财政年份:
    2018
  • 负责人:
    Miroslav Krstic
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国内基金
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  • 资助金额:
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  • 负责人:
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  • 批准号:
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  • 项目类别:
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  • 资助金额:
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  • 批准年份:
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