GOALI: HCCI Engine Control and Optimization Using Extremum Seeking

随着减排压力的加大，对新的低污染发动机技术的需求从未像现在这样强烈。因此，具有与柴油相似的效率、低比例和低NOx排放的均质压燃发动机是一种首选方案。然而，由于HCCI EN发动机没有直接的梳状燃烧使用触发器，控制梳状燃烧使用的启动是一项复杂的任务。为了帮助使这项技术成为现实，我们组建了一个团队，他们拥有HCCI发动机基础-基础(Lawrence Wrence Li Livermore National Labs LLNL)、最先进的汽车自动控制和引擎映射(F Ford，Order)和高级非线性控制方法(UCSD)的背景。我们计划解决HCCI发动机映射问题，以及依赖于发动机映射的发动机控制。映射均质压燃发动机是一个复杂而耗时的过程，因为有许多发动机参数需要调整。我们计划用来解决这个问题的极值搜索(ES)已经在福特汽车公司被证明是一种有效的工具，它可以减少绘制火花点火发动机的时间，比传统技术减少了三到五个因素，在绘制过程中可以节省几个月的时间。可以预期，在HCCI发动机上也会有同样的好处。我们将改进Ford‘Order已经成功的算法，并在传统的常规发动机和一台实验性的HCCI发动机上测试这一新方法。除了映射和优化之外，HCCI发动机由于对温度的敏感性，在操作过程中需要反馈控制。我们将构建非线性控制算法来控制梳子燃烧使用过程，建立在我们之前关于燃气作为涡轮发动机梳子燃烧室控制的结果的基础上。我们的算法将应用于具有详细化学动力学的HCCI发动机模型以及LLNL和福特的实验发动机。奥德。这些都将是将HCCI发动机技术提高到一个较低水平的有益步骤，使我们能够受益于其相对于传统内燃机的优势。这项研究将有助于使HCCI发动机技术成为现实，这一点非常重要，因为它们承诺的绿色运行和日益严格的排放标准。该程序将对ES算法作进一步的改进，特别是在多变量、变量、约束和快速在线优化方面。这样的进步将在许多其他技术中得到应用。

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.