Matches in SemOpenAlex for { <https://semopenalex.org/work/W2047025295> ?p ?o ?g. }
Showing items 1 to 72 of
72
with 100 items per page.
- W2047025295 abstract "Increasing the degrees of freedom in the air path has become a popular way to reduce the fuel consumption and pollutant emissions of modern combustion engines. That is why technical definitions will usually contain components such as multi or single-stage turbocharger, throttle, exhaust gas recirculation loops, wastegate, variable valve timing or phasing, etc. One of the biggest challenges is to precisely quantify the gas flows through the engine. They include fresh and burnt gases, with trapping and scavenging phenomena. An accurate prediction of these values leads to an efficient control of the engine air fuel ratio and torque. Fuel consumption and pollutant emissions are then minimized. In this paper, we propose to use an artificial neural networkbased model as a prediction tool for the engine volumetric efficiency. Results are presented for a downsized turbocharged spark-ignited engine, equipped with inlet and outlet variable valve timing. The calibration process that is used in this study only requires steady-state operating points. The validation stage was conducted on both steady-state and vehicle transients. Model prediction is in very good agreement with experimental results while keeping a very low calibration effort and matching embedded computational requirements. The conclusion stresses that thanks to their generic structure, neural models offer an interesting potential for generalization to even more complex technical definitions." @default.
- W2047025295 created "2016-06-24" @default.
- W2047025295 creator A5024177322 @default.
- W2047025295 creator A5038162518 @default.
- W2047025295 creator A5063704368 @default.
- W2047025295 creator A5079259106 @default.
- W2047025295 date "2013-09-08" @default.
- W2047025295 modified "2023-10-16" @default.
- W2047025295 title "Neural Model for Real-Time Engine Volumetric Efficiency Estimation" @default.
- W2047025295 cites W1490318080 @default.
- W2047025295 cites W2019268734 @default.
- W2047025295 cites W2055555180 @default.
- W2047025295 cites W2066310692 @default.
- W2047025295 cites W2078733704 @default.
- W2047025295 cites W2090333804 @default.
- W2047025295 cites W2096873036 @default.
- W2047025295 cites W2099926886 @default.
- W2047025295 cites W2103063167 @default.
- W2047025295 cites W2103155040 @default.
- W2047025295 cites W2103496339 @default.
- W2047025295 cites W2114290010 @default.
- W2047025295 cites W2132062701 @default.
- W2047025295 cites W2143956139 @default.
- W2047025295 cites W2227672625 @default.
- W2047025295 cites W2279150123 @default.
- W2047025295 cites W2295867270 @default.
- W2047025295 cites W2315852074 @default.
- W2047025295 cites W3043808540 @default.
- W2047025295 doi "https://doi.org/10.4271/2013-24-0132" @default.
- W2047025295 hasPublicationYear "2013" @default.
- W2047025295 type Work @default.
- W2047025295 sameAs 2047025295 @default.
- W2047025295 citedByCount "8" @default.
- W2047025295 countsByYear W20470252952016 @default.
- W2047025295 countsByYear W20470252952017 @default.
- W2047025295 countsByYear W20470252952019 @default.
- W2047025295 countsByYear W20470252952021 @default.
- W2047025295 countsByYear W20470252952022 @default.
- W2047025295 crossrefType "proceedings-article" @default.
- W2047025295 hasAuthorship W2047025295A5024177322 @default.
- W2047025295 hasAuthorship W2047025295A5038162518 @default.
- W2047025295 hasAuthorship W2047025295A5063704368 @default.
- W2047025295 hasAuthorship W2047025295A5079259106 @default.
- W2047025295 hasConcept C127413603 @default.
- W2047025295 hasConcept C154945302 @default.
- W2047025295 hasConcept C201995342 @default.
- W2047025295 hasConcept C41008148 @default.
- W2047025295 hasConcept C96250715 @default.
- W2047025295 hasConceptScore W2047025295C127413603 @default.
- W2047025295 hasConceptScore W2047025295C154945302 @default.
- W2047025295 hasConceptScore W2047025295C201995342 @default.
- W2047025295 hasConceptScore W2047025295C41008148 @default.
- W2047025295 hasConceptScore W2047025295C96250715 @default.
- W2047025295 hasLocation W20470252951 @default.
- W2047025295 hasLocation W20470252952 @default.
- W2047025295 hasLocation W20470252953 @default.
- W2047025295 hasOpenAccess W2047025295 @default.
- W2047025295 hasPrimaryLocation W20470252951 @default.
- W2047025295 hasRelatedWork W1596801655 @default.
- W2047025295 hasRelatedWork W2130043461 @default.
- W2047025295 hasRelatedWork W2350741829 @default.
- W2047025295 hasRelatedWork W2358668433 @default.
- W2047025295 hasRelatedWork W2376932109 @default.
- W2047025295 hasRelatedWork W2382290278 @default.
- W2047025295 hasRelatedWork W2390279801 @default.
- W2047025295 hasRelatedWork W2748952813 @default.
- W2047025295 hasRelatedWork W2899084033 @default.
- W2047025295 hasRelatedWork W2530322880 @default.
- W2047025295 isParatext "false" @default.
- W2047025295 isRetracted "false" @default.
- W2047025295 magId "2047025295" @default.
- W2047025295 workType "article" @default.