With ith increasing pressure to reduce emissions, the need for ne new lo low polluting engine technology has 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 a direct comb combustion ustion trigger trigger, controlling the start of comb combustion ustion is a complicated task. To help mak make this technology a reality we ha have assembled a team with a background in HCCI engine fundamen- fundamentals tals (La Lawrence wrence Li Livermore ermore National Labs LLNL), state of the art automoti automotive control and engine mapping (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 relies on engine maps. Mapping HCCI engines is a complicated and time consuming process due to the man many engine parameters which must be tuned. Extremum seeking (ES), which we plan to emplo employ for this problem, has been demonstrated at Ford ord Motor Compan Company to be an ef effecti fective tool to reduce the 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 HCCI engines. We wil will impro improve upon Ford' ord's already successful algorithm and test this ne new method on con conventional entional engines and an experimental xperimental HCCI engine. In addition to mapping and optimization, HCCI engines require feedback control during op- operation eration due to their sensiti sensitivity vity to temperature. We will construct nonlinear control algorithms to control the comb combustion ustion process, building uilding upon our prior results on control of gas as turbine engine comb combustors. ustors. Our algorithms will be applied to models of the HCCI engine with detailed chemical kinetics and on experimental xperimental engines at LLNL and Ford. ord. These will be helpful steps to bring the HCCI engine technology to a le level el in which we can benefit from its adv advantages antages over er con conventional entional internal comb combustion ustion engines. Impact Statement. This research will help mak make HCCI engine technology a reality reality, which is important 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 in multi multivariable, ariable, constrained, and fast ast on-line optimization. Such adv advances ances will ha have application to man many other technologies.

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University of California San Diego
La Jolla
United States
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