A Scalable Modeling Approach for the Simulation and Design Optimization of Automotive Turbochargers
Engine downsizing and super/turbocharging is currently the most followed trend in order to reduce CO₂ emissions and increase the powertrain efficiency. A key challenge for achieving the desired fuel economy benefits lies in optimizing the design and control of the engine boosting system, which requi...
Gespeichert in:
| Veröffentlicht in: | SAE International journal of engines 2015-04, Vol.8 (4), p.1616-1628, Article 2015-01-1288 |
|---|---|
| Hauptverfasser: | , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 1628 |
|---|---|
| container_issue | 4 |
| container_start_page | 1616 |
| container_title | SAE International journal of engines |
| container_volume | 8 |
| creator | Canova, Marcello Naddeo, Massimo Liu, Yuxing Zhou, Junqiang Wang, Yue-Yun |
| description | Engine downsizing and super/turbocharging is currently the most followed trend in order to reduce CO₂ emissions and increase the powertrain efficiency. A key challenge for achieving the desired fuel economy benefits lies in optimizing the design and control of the engine boosting system, which requires the ability to rapidly sort different design options and technologies in simulation, evaluating their impact on engine performance and fuel consumption.
This paper presents a scalable modeling approach for the characterization of flow and efficiency maps for automotive turbochargers. Starting from the dimensional analysis theory for turbomachinery and a set of well-known control-oriented models for turbocharged engines simulation, a novel scalable model is proposed to predict the flow and efficiency maps of centrifugal compressors and radial inflow turbines as function of their key design parameters. The proposed approach is validated on a database of compressors and turbines for automotive boosting applications. Examples are given to illustrate how the characteristic curves can be scaled with key design parameters. |
| doi_str_mv | 10.4271/2015-01-1288 |
| format | Article |
| fullrecord | <record><control><sourceid>jstor_proqu</sourceid><recordid>TN_cdi_proquest_journals_2540550671</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><jstor_id>26278058</jstor_id><sourcerecordid>26278058</sourcerecordid><originalsourceid>FETCH-LOGICAL-c396t-41d4cf75b3c334dba10000f34e6278365521c2c25a7890941840f16e3d52a6053</originalsourceid><addsrcrecordid>eNpVkMtLxDAQxoMouD5uXoWAV6t5tz2W9Qkre9j1HNI03c3SNmuSCvrX21JZcS4zDD--me8D4AqjO0ZSfE8Q5gnCCSZZdgRmOGcioTljx4eZilNwFsIOIZEiimZAF3ClVaPKxsA3V5nGdhtY7PfeKb2FtfMwbg1c2bZvVLSug6qr4IMJdtPB5T7a1n5Pe1fDoo-uddF-Grjufen0VvmN8eECnNSqCebyt5-D96fH9fwlWSyfX-fFItE0FzFhuGK6TnlJNaWsKhVGQ9WUGUHSjArOCdZEE67SLEc5wxlDNRaGVpwogTg9BzeT7vD9R29ClDvX-244KQlniPPBNB6o24nS3oXgTS333rbKf0mM5BijHGOUCMsxxgFPJjwoI20XzSA4GlbNn_h__nridyE6f9AmowfEM_oDeyd8pQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2540550671</pqid></control><display><type>article</type><title>A Scalable Modeling Approach for the Simulation and Design Optimization of Automotive Turbochargers</title><source>Jstor Complete Legacy</source><creator>Canova, Marcello ; Naddeo, Massimo ; Liu, Yuxing ; Zhou, Junqiang ; Wang, Yue-Yun</creator><creatorcontrib>Canova, Marcello ; Naddeo, Massimo ; Liu, Yuxing ; Zhou, Junqiang ; Wang, Yue-Yun</creatorcontrib><description>Engine downsizing and super/turbocharging is currently the most followed trend in order to reduce CO₂ emissions and increase the powertrain efficiency. A key challenge for achieving the desired fuel economy benefits lies in optimizing the design and control of the engine boosting system, which requires the ability to rapidly sort different design options and technologies in simulation, evaluating their impact on engine performance and fuel consumption.
This paper presents a scalable modeling approach for the characterization of flow and efficiency maps for automotive turbochargers. Starting from the dimensional analysis theory for turbomachinery and a set of well-known control-oriented models for turbocharged engines simulation, a novel scalable model is proposed to predict the flow and efficiency maps of centrifugal compressors and radial inflow turbines as function of their key design parameters. The proposed approach is validated on a database of compressors and turbines for automotive boosting applications. Examples are given to illustrate how the characteristic curves can be scaled with key design parameters.</description><identifier>ISSN: 1946-3936</identifier><identifier>ISSN: 1946-3944</identifier><identifier>EISSN: 1946-3944</identifier><identifier>DOI: 10.4271/2015-01-1288</identifier><language>eng</language><publisher>Warrendale: SAE International</publisher><subject>Air compressors ; Automotive engines ; Calibration ; Design optimization ; Downsizing ; Engines ; Flow velocity ; Fuel consumption ; Fuel economy ; Impellers ; Mach number ; Mathematical independent variables ; Modeling ; Parametric models ; Powertrain ; Superchargers ; Turbines</subject><ispartof>SAE International journal of engines, 2015-04, Vol.8 (4), p.1616-1628, Article 2015-01-1288</ispartof><rights>Copyright © 2015 SAE International</rights><rights>Copyright SAE International, a Pennsylvania Not-for Profit 2015</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c396t-41d4cf75b3c334dba10000f34e6278365521c2c25a7890941840f16e3d52a6053</citedby><cites>FETCH-LOGICAL-c396t-41d4cf75b3c334dba10000f34e6278365521c2c25a7890941840f16e3d52a6053</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/26278058$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/26278058$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,776,780,799,27901,27902,57992,58225</link.rule.ids></links><search><creatorcontrib>Canova, Marcello</creatorcontrib><creatorcontrib>Naddeo, Massimo</creatorcontrib><creatorcontrib>Liu, Yuxing</creatorcontrib><creatorcontrib>Zhou, Junqiang</creatorcontrib><creatorcontrib>Wang, Yue-Yun</creatorcontrib><title>A Scalable Modeling Approach for the Simulation and Design Optimization of Automotive Turbochargers</title><title>SAE International journal of engines</title><description>Engine downsizing and super/turbocharging is currently the most followed trend in order to reduce CO₂ emissions and increase the powertrain efficiency. A key challenge for achieving the desired fuel economy benefits lies in optimizing the design and control of the engine boosting system, which requires the ability to rapidly sort different design options and technologies in simulation, evaluating their impact on engine performance and fuel consumption.
This paper presents a scalable modeling approach for the characterization of flow and efficiency maps for automotive turbochargers. Starting from the dimensional analysis theory for turbomachinery and a set of well-known control-oriented models for turbocharged engines simulation, a novel scalable model is proposed to predict the flow and efficiency maps of centrifugal compressors and radial inflow turbines as function of their key design parameters. The proposed approach is validated on a database of compressors and turbines for automotive boosting applications. Examples are given to illustrate how the characteristic curves can be scaled with key design parameters.</description><subject>Air compressors</subject><subject>Automotive engines</subject><subject>Calibration</subject><subject>Design optimization</subject><subject>Downsizing</subject><subject>Engines</subject><subject>Flow velocity</subject><subject>Fuel consumption</subject><subject>Fuel economy</subject><subject>Impellers</subject><subject>Mach number</subject><subject>Mathematical independent variables</subject><subject>Modeling</subject><subject>Parametric models</subject><subject>Powertrain</subject><subject>Superchargers</subject><subject>Turbines</subject><issn>1946-3936</issn><issn>1946-3944</issn><issn>1946-3944</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNpVkMtLxDAQxoMouD5uXoWAV6t5tz2W9Qkre9j1HNI03c3SNmuSCvrX21JZcS4zDD--me8D4AqjO0ZSfE8Q5gnCCSZZdgRmOGcioTljx4eZilNwFsIOIZEiimZAF3ClVaPKxsA3V5nGdhtY7PfeKb2FtfMwbg1c2bZvVLSug6qr4IMJdtPB5T7a1n5Pe1fDoo-uddF-Grjufen0VvmN8eECnNSqCebyt5-D96fH9fwlWSyfX-fFItE0FzFhuGK6TnlJNaWsKhVGQ9WUGUHSjArOCdZEE67SLEc5wxlDNRaGVpwogTg9BzeT7vD9R29ClDvX-244KQlniPPBNB6o24nS3oXgTS333rbKf0mM5BijHGOUCMsxxgFPJjwoI20XzSA4GlbNn_h__nridyE6f9AmowfEM_oDeyd8pQ</recordid><startdate>20150414</startdate><enddate>20150414</enddate><creator>Canova, Marcello</creator><creator>Naddeo, Massimo</creator><creator>Liu, Yuxing</creator><creator>Zhou, Junqiang</creator><creator>Wang, Yue-Yun</creator><general>SAE International</general><general>SAE International, a Pennsylvania Not-for Profit</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20150414</creationdate><title>A Scalable Modeling Approach for the Simulation and Design Optimization of Automotive Turbochargers</title><author>Canova, Marcello ; Naddeo, Massimo ; Liu, Yuxing ; Zhou, Junqiang ; Wang, Yue-Yun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c396t-41d4cf75b3c334dba10000f34e6278365521c2c25a7890941840f16e3d52a6053</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Air compressors</topic><topic>Automotive engines</topic><topic>Calibration</topic><topic>Design optimization</topic><topic>Downsizing</topic><topic>Engines</topic><topic>Flow velocity</topic><topic>Fuel consumption</topic><topic>Fuel economy</topic><topic>Impellers</topic><topic>Mach number</topic><topic>Mathematical independent variables</topic><topic>Modeling</topic><topic>Parametric models</topic><topic>Powertrain</topic><topic>Superchargers</topic><topic>Turbines</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Canova, Marcello</creatorcontrib><creatorcontrib>Naddeo, Massimo</creatorcontrib><creatorcontrib>Liu, Yuxing</creatorcontrib><creatorcontrib>Zhou, Junqiang</creatorcontrib><creatorcontrib>Wang, Yue-Yun</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>Technology Collection (ProQuest)</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><jtitle>SAE International journal of engines</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Canova, Marcello</au><au>Naddeo, Massimo</au><au>Liu, Yuxing</au><au>Zhou, Junqiang</au><au>Wang, Yue-Yun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Scalable Modeling Approach for the Simulation and Design Optimization of Automotive Turbochargers</atitle><jtitle>SAE International journal of engines</jtitle><date>2015-04-14</date><risdate>2015</risdate><volume>8</volume><issue>4</issue><spage>1616</spage><epage>1628</epage><pages>1616-1628</pages><artnum>2015-01-1288</artnum><issn>1946-3936</issn><issn>1946-3944</issn><eissn>1946-3944</eissn><abstract>Engine downsizing and super/turbocharging is currently the most followed trend in order to reduce CO₂ emissions and increase the powertrain efficiency. A key challenge for achieving the desired fuel economy benefits lies in optimizing the design and control of the engine boosting system, which requires the ability to rapidly sort different design options and technologies in simulation, evaluating their impact on engine performance and fuel consumption.
This paper presents a scalable modeling approach for the characterization of flow and efficiency maps for automotive turbochargers. Starting from the dimensional analysis theory for turbomachinery and a set of well-known control-oriented models for turbocharged engines simulation, a novel scalable model is proposed to predict the flow and efficiency maps of centrifugal compressors and radial inflow turbines as function of their key design parameters. The proposed approach is validated on a database of compressors and turbines for automotive boosting applications. Examples are given to illustrate how the characteristic curves can be scaled with key design parameters.</abstract><cop>Warrendale</cop><pub>SAE International</pub><doi>10.4271/2015-01-1288</doi><tpages>13</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1946-3936 |
| ispartof | SAE International journal of engines, 2015-04, Vol.8 (4), p.1616-1628, Article 2015-01-1288 |
| issn | 1946-3936 1946-3944 1946-3944 |
| language | eng |
| recordid | cdi_proquest_journals_2540550671 |
| source | Jstor Complete Legacy |
| subjects | Air compressors Automotive engines Calibration Design optimization Downsizing Engines Flow velocity Fuel consumption Fuel economy Impellers Mach number Mathematical independent variables Modeling Parametric models Powertrain Superchargers Turbines |
| title | A Scalable Modeling Approach for the Simulation and Design Optimization of Automotive Turbochargers |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-06T11%3A53%3A46IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-jstor_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20Scalable%20Modeling%20Approach%20for%20the%20Simulation%20and%20Design%20Optimization%20of%20Automotive%20Turbochargers&rft.jtitle=SAE%20International%20journal%20of%20engines&rft.au=Canova,%20Marcello&rft.date=2015-04-14&rft.volume=8&rft.issue=4&rft.spage=1616&rft.epage=1628&rft.pages=1616-1628&rft.artnum=2015-01-1288&rft.issn=1946-3936&rft.eissn=1946-3944&rft_id=info:doi/10.4271/2015-01-1288&rft_dat=%3Cjstor_proqu%3E26278058%3C/jstor_proqu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2540550671&rft_id=info:pmid/&rft_jstor_id=26278058&rfr_iscdi=true |