基于道路工况分析的HEV控制策略优化方法
以某并联式混动公交车为研究对象,建立了四种典型工况模型,采用蚁群算法优化了最小等效燃油消耗控制策略中四种工况的充放电等效因子;分析了路面坡度与电池荷电状态（state of charge,SOC）目标值域调整之间的对应关系,设计了相应坡度自适应模块;提出了基于道路工况分析的混合动力汽车（hybrid electric vehicle,HEV）控制策略优化方法.典型工况下的仿真对比分析表明,该方法具有良好的工况适应能力,燃油经济性明显优于几类典型HEV控制策略....
Saved in:
| Published in | 东北大学学报(自然科学版) Vol. 38; no. 4; pp. 551 - 556 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
大连理工大学汽车工程学院,辽宁 大连,116024
2017
|
| Subjects | |
| Online Access | Get full text |
| ISSN | 1005-3026 |
| DOI | 10.3969/j.issn.1005-3026.2017.04.020 |
Cover
| Abstract | 以某并联式混动公交车为研究对象,建立了四种典型工况模型,采用蚁群算法优化了最小等效燃油消耗控制策略中四种工况的充放电等效因子;分析了路面坡度与电池荷电状态（state of charge,SOC）目标值域调整之间的对应关系,设计了相应坡度自适应模块;提出了基于道路工况分析的混合动力汽车（hybrid electric vehicle,HEV）控制策略优化方法.典型工况下的仿真对比分析表明,该方法具有良好的工况适应能力,燃油经济性明显优于几类典型HEV控制策略. |
|---|---|
| AbstractList | U469.72; 以某并联式混动公交车为研究对象,建立了四种典型工况模型,采用蚁群算法优化了最小等效燃油消耗控制策略中四种工况的充放电等效因子;分析了路面坡度与电池荷电状态(state of charge, SOC)目标值域调整之间的对应关系,设计了相应坡度自适应模块;提出了基于道路工况分析的混合动力汽车(hybrid electric vehicle, HEV)控制策略优化方法.典型工况下的仿真对比分析表明,该方法具有良好的工况适应能力,燃油经济性明显优于几类典型HEV控制策略. 以某并联式混动公交车为研究对象,建立了四种典型工况模型,采用蚁群算法优化了最小等效燃油消耗控制策略中四种工况的充放电等效因子;分析了路面坡度与电池荷电状态（state of charge,SOC）目标值域调整之间的对应关系,设计了相应坡度自适应模块;提出了基于道路工况分析的混合动力汽车（hybrid electric vehicle,HEV）控制策略优化方法.典型工况下的仿真对比分析表明,该方法具有良好的工况适应能力,燃油经济性明显优于几类典型HEV控制策略. |
| Abstract_FL | Taking a parallel hybrid bus as research object, four kinds of typical working condition models were established, and the ant colony optimization algorithm was used to optimize the charge and discharge equivalent factor for each working condition in minimal equivalent fuel consumption control strategy.The relation between road gradient and adjustment of battery SOC target range was analyzed, and the corresponding gradient adaptive module was designed.A control strategy optimization method was proposed based on driving cycle recognition for HEV.The results of simulation and comparison analysis under typical working conditions showed that the method has very well driving condition adaptability, and its fuel economy is significantly higher than that of other several typical HEV control strategies. |
| Author | 连静 范悟明 李琳辉 袁鲁山 |
| AuthorAffiliation | 大连理工大学汽车工程学院,辽宁大连116024 |
| AuthorAffiliation_xml | – name: 大连理工大学汽车工程学院,辽宁 大连,116024 |
| Author_FL | YUAN Lu-shan LI Lin-hui LIAN Jing FAN Wu-ming |
| Author_FL_xml | – sequence: 1 fullname: LIAN Jing – sequence: 2 fullname: FAN Wu-ming – sequence: 3 fullname: LI Lin-hui – sequence: 4 fullname: YUAN Lu-shan |
| Author_xml | – sequence: 1 fullname: 连静 范悟明 李琳辉 袁鲁山 |
| BookMark | eNo9j89LAkEcxedgkJn_RASddvvu_HSOIZaB0EW6yu7OjK3UWC6RHYMQDyJBKNGhTtIpOkRJ0p_jrvVftGF0erzHh_d4ayhn21YjtOmBSySX2y03imPregDMIYC5i8ETLlAXMORQ_j9fRcU4jgIAkFQwLPOIJ4-z-Wz4fXX7NX1JppOk95b0e-nDzeL-ulo5TIdPSf998TxejCbzz7tkME7HH-nraB2tGP841sU_LaD6bqVerjq1g7398k7NCZkEJ9TUMBMSakCBYoqWPII1Z0JSTrU0guvQZwYyF9KAKC1KFJcoYIUpEMFIAW0tay98a3zbbLTa5x2bDTZUoLrd4PcmZDxk5MaSDI_atnkWZexpJzrxO5cNLjwhCcm2fwD3bmgv |
| ClassificationCodes | U469.72 |
| ContentType | Journal Article |
| Copyright | Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
| Copyright_xml | – notice: Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
| DBID | 2RA 92L CQIGP ~WA 2B. 4A8 92I 93N PSX TCJ |
| DOI | 10.3969/j.issn.1005-3026.2017.04.020 |
| DatabaseName | 维普_期刊 中文科技期刊数据库-CALIS站点 维普中文期刊数据库 中文科技期刊数据库- 镜像站点 Wanfang Data Journals - Hong Kong WANFANG Data Centre Wanfang Data Journals 万方数据期刊 - 香港版 China Online Journals (COJ) China Online Journals (COJ) |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering |
| DocumentTitleAlternate | Control Strategy Optimization Method Based on Driving Cycle Recognition for HEV |
| DocumentTitle_FL | Control Strategy Optimization Method Based on Driving Cycle Recognition for HEV |
| EndPage | 556 |
| ExternalDocumentID | dbdxxb201704020 671793381 |
| GrantInformation_xml | – fundername: 国家自然科学基金资助项目; 中央高校基本科研业务费专项资金资助项目 funderid: (61473057); (DUT15LK13) |
| GroupedDBID | -03 2B. 2C. 2RA 5XA 5XD 92E 92I 92L ABDBF ACGFS ALMA_UNASSIGNED_HOLDINGS CCEZO CEKLB CQIGP CW9 EAD EAP EAS EOJEC ESX OBODZ TCJ TGP U1G U5M ~WA 4A8 93N ABJNI ACUHS PSX |
| ID | FETCH-LOGICAL-c590-ce4f5fc34f0d0d5d48132e6579464e9f76eca5f0464c4b3de78428402d2403753 |
| ISSN | 1005-3026 |
| IngestDate | Thu May 29 03:59:14 EDT 2025 Wed Feb 14 10:03:44 EST 2024 |
| IsPeerReviewed | false |
| IsScholarly | true |
| Issue | 4 |
| Keywords | control strategy ant colony optimization HEV(hybrid electric vehicle) 工况识别 SOC目标值域 混合动力汽车 driving cycle recognition 蚁群优化 控制策略 SOC target range |
| Language | Chinese |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c590-ce4f5fc34f0d0d5d48132e6579464e9f76eca5f0464c4b3de78428402d2403753 |
| Notes | 21-1344/T HEV（hybrid electric vehicle）; driving cycle recognition; ant colony optimization; SOC target range; control strategy Taking a parallel hybrid bus as research object,four kinds of typical working condition models were established,and the ant colony optimization algorithm was used to optimize the charge and discharge equivalent factor for each working condition in minimal equivalent fuel consumption control strategy.The relation between road gradient and adjustment of battery SOC target range was analyzed,and the corresponding gradient adaptive module was designed.A control strategy optimization method was proposed based on driving cycle recognition for HEV.The results of simulation and comparison analysis under typical working conditions showed that the method has very well driving condition adaptability,and its fuel economy is significantly higher than that of other several typical HEV control strategies. LIAN Jing,FAN Wu-ming,LI Lin- hui,YUAN Lu-shan（School of Automotive Engineering,Dalian University |
| PageCount | 6 |
| ParticipantIDs | wanfang_journals_dbdxxb201704020 chongqing_primary_671793381 |
| PublicationCentury | 2000 |
| PublicationDate | 2017 |
| PublicationDateYYYYMMDD | 2017-01-01 |
| PublicationDate_xml | – year: 2017 text: 2017 |
| PublicationDecade | 2010 |
| PublicationTitle | 东北大学学报(自然科学版) |
| PublicationTitleAlternate | Journal of Northeastern University（Natural Science） |
| PublicationTitle_FL | Journal of Northeastern University(Natural Science) |
| PublicationYear | 2017 |
| Publisher | 大连理工大学汽车工程学院,辽宁 大连,116024 |
| Publisher_xml | – name: 大连理工大学汽车工程学院,辽宁 大连,116024 |
| SSID | ssib000947529 ssib051368049 ssib023167010 ssj0040330 ssib002039846 ssib004675270 ssib006703041 ssib002263414 ssib008679651 ssib001128993 |
| Score | 2.1292558 |
| Snippet | 以某并联式混动公交车为研究对象,建立了四种典型工况模型,采用蚁群算法优化了最小等效燃油消耗控制策略中四种工况的充放电等效因子;分析了路面坡度与电池荷电状态（state... U469.72; 以某并联式混动公交车为研究对象,建立了四种典型工况模型,采用蚁群算法优化了最小等效燃油消耗控制策略中四种工况的充放电等效因子;分析了路面坡度与电池荷电状... |
| SourceID | wanfang chongqing |
| SourceType | Aggregation Database Publisher |
| StartPage | 551 |
| SubjectTerms | SOC目标值域 工况识别 控制策略 混合动力汽车 蚁群优化 |
| Title | 基于道路工况分析的HEV控制策略优化方法 |
| URI | http://lib.cqvip.com/qk/90188A/201704/671793381.html https://d.wanfangdata.com.cn/periodical/dbdxxb201704020 |
| Volume | 38 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVEBS databaseName: EBSCOhost Academic Search Ultimate issn: 1005-3026 databaseCode: ABDBF dateStart: 20150901 customDbUrl: https://search.ebscohost.com/login.aspx?authtype=ip,shib&custid=s3936755&profile=ehost&defaultdb=asn isFulltext: true dateEnd: 99991231 titleUrlDefault: https://search.ebscohost.com/direct.asp?db=asn omitProxy: true ssIdentifier: ssj0040330 providerName: EBSCOhost |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3NaxQxFA-lBdGD-Im1Kj00pzJ1ZvIxyXFmd5ZF0NMqvS07H2lP26otlN4EKT1IEaRFPOipeBIPosXin9Pd1b_Bi-9lZrc5lKLCEt5mkvde3ptJfskkbwhZyAzAiLA0ntE97vFeUHoq8yPPcMNybYI8y3G94-Ej2X7MHyyL5amp386upc2NbCnfPvNcyf94FfLAr3hK9h88O2EKGUCDfyEFD0P6Vz6mqaC6RZOYphxTldJUAzakmtFU0SSicQvLICGQUJImFaGQTiXVKdU-TSOqoTpvp08wE_jEUV0skXg1blJtCS0sKxDXoFrZMg17SWKaaCQSRqtPWo5Rry2vqG6My1vmMa-lAPNYOgQoEFspLSslxrYo0CFGBRQfqwTKBE4tuARtn-zMtQZoYfvAJBrU14uWT4MqZkWEaDpUGzLTRUs1rQUjtEhSWTAFprZeHKJdgVVSEWDUAH7uokl1OrTu4TH0KvOrY_rjIYAp51bnTn8u6mi4Zf1PnjXqMC21HXVQwNJEAO4bjGwc3dA_HW0neyBlhH0jw7ABMyEuJk2TmThpJi0H_fJIOOgVoDHMjh105TOt3OhwoQRM4h47hupOdyyxd3fQr421ePpSOMSgCP4pGhQBk8q-hK2ADfcZq4J71A28QBbq1t8_r-0YtWR1rb_yFLCYPRrXN73-ioPiOlfI5Xr6NR9Xz9JVMrW9eo1ccoJyXidy8OH45Hjv14s3P48-D44OBztfB7s7w_evR-9ewvMx3Ps42P02-nQw2j88-fF28OpgePB9-GX_Bum00k6j7dVfF_FyoX0vL7kRJmfc-IVfiIKrgIWlFPjBBV5qE8ky7wmDb_5znrGijBTM1LkfFhjBEib5N8l0f61f3iLzTGbMBAHnptfjBZcYmUFIxoK8MFkYFrNkbmKA7noVRKY7cf8sma9N0q27lufdIiu2tjK0oY_rO7fPZTBHLmLJal3wDpneeLZZ3gWkvJHdq--oPyliiqo |
| linkProvider | EBSCOhost |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=%E5%9F%BA%E4%BA%8E%E9%81%93%E8%B7%AF%E5%B7%A5%E5%86%B5%E5%88%86%E6%9E%90%E7%9A%84HEV%E6%8E%A7%E5%88%B6%E7%AD%96%E7%95%A5%E4%BC%98%E5%8C%96%E6%96%B9%E6%B3%95&rft.jtitle=%E4%B8%9C%E5%8C%97%E5%A4%A7%E5%AD%A6%E5%AD%A6%E6%8A%A5%EF%BC%9A%E8%87%AA%E7%84%B6%E7%A7%91%E5%AD%A6%E7%89%88&rft.au=%E8%BF%9E%E9%9D%99+%E8%8C%83%E6%82%9F%E6%98%8E+%E6%9D%8E%E7%90%B3%E8%BE%89+%E8%A2%81%E9%B2%81%E5%B1%B1&rft.date=2017&rft.issn=1005-3026&rft.volume=38&rft.issue=4&rft.spage=551&rft.epage=556&rft_id=info:doi/10.3969%2Fj.issn.1005-3026.2017.04.020&rft.externalDocID=671793381 |
| thumbnail_s | http://utb.summon.serialssolutions.com/2.0.0/image/custom?url=http%3A%2F%2Fimage.cqvip.com%2Fvip1000%2Fqk%2F90188A%2F90188A.jpg http://utb.summon.serialssolutions.com/2.0.0/image/custom?url=http%3A%2F%2Fwww.wanfangdata.com.cn%2Fimages%2FPeriodicalImages%2Fdbdxxb%2Fdbdxxb.jpg |