Real-time global driving cycle construction and the application to economy driving pro system in plug-in hybrid electric vehicles
This paper proposes a global driving cycle construction method based on the real-time traffic information, which can realize online optimal energy management for plug-in hybrid electric vehicles (PHEVs). The construction method is mainly divided into three parts: the construction of velocity segment...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Hongwen, He [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2018transfer abstract |
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| Schlagwörter: |
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| Umfang: |
13 |
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| Übergeordnetes Werk: |
Enthalten in: Rheological analysis of itraconazole-polymer mixtures to determine optimal melt extrusion temperature for development of amorphous solid dispersion - Solanki, Nayan ELSEVIER, 2017, the international journal, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:152 ; year:2018 ; day:1 ; month:06 ; pages:95-107 ; extent:13 |
| Links: |
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| DOI / URN: |
10.1016/j.energy.2018.03.061 |
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ELV042964172 |
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| 245 | 1 | 0 | |a Real-time global driving cycle construction and the application to economy driving pro system in plug-in hybrid electric vehicles |
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| 520 | |a This paper proposes a global driving cycle construction method based on the real-time traffic information, which can realize online optimal energy management for plug-in hybrid electric vehicles (PHEVs). The construction method is mainly divided into three parts: the construction of velocity segments database; the construction of real-time traffic information tensor model database, and the construction of real-time global driving cycle. For the acquisition of the real-time traffic information, a two-step completion method is adopted to obtain the complete and accuracy traffic information; for the driving cycle construction, the velocity segment database, the road section velocity and the Markov transfer matrix with Monte Carlo are used to generate velocity segments which constitute the global driving cycle. With the updated real-time traffic information, the global driving cycle is reconstructed which further reflect the real-time road condition. The efficient dynamic programming (DP) algorithm is applied to realize online energy management in PHEVs. Its simulation shows that the fuel efficiency improves by at least 19.83% compared with charge depleting and charge sustain (CDCS) control strategy. Finally, the economy driving pro system (EDPS) is presented in this paper, and it contributes 5.79% fuel efficiency compared with non-EDPS. | ||
| 520 | |a This paper proposes a global driving cycle construction method based on the real-time traffic information, which can realize online optimal energy management for plug-in hybrid electric vehicles (PHEVs). The construction method is mainly divided into three parts: the construction of velocity segments database; the construction of real-time traffic information tensor model database, and the construction of real-time global driving cycle. For the acquisition of the real-time traffic information, a two-step completion method is adopted to obtain the complete and accuracy traffic information; for the driving cycle construction, the velocity segment database, the road section velocity and the Markov transfer matrix with Monte Carlo are used to generate velocity segments which constitute the global driving cycle. With the updated real-time traffic information, the global driving cycle is reconstructed which further reflect the real-time road condition. The efficient dynamic programming (DP) algorithm is applied to realize online energy management in PHEVs. Its simulation shows that the fuel efficiency improves by at least 19.83% compared with charge depleting and charge sustain (CDCS) control strategy. Finally, the economy driving pro system (EDPS) is presented in this paper, and it contributes 5.79% fuel efficiency compared with non-EDPS. | ||
| 650 | 7 | |a Tensor completion |2 Elsevier | |
| 650 | 7 | |a EDPS |2 Elsevier | |
| 650 | 7 | |a Global driving cycle |2 Elsevier | |
| 650 | 7 | |a Dynamic programming |2 Elsevier | |
| 650 | 7 | |a PHEV |2 Elsevier | |
| 650 | 7 | |a Traffic information |2 Elsevier | |
| 700 | 1 | |a Jinquan, Guo |4 oth | |
| 700 | 1 | |a Jiankun, Peng |4 oth | |
| 700 | 1 | |a Huachun, Tan |4 oth | |
| 700 | 1 | |a Chao, Sun |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier Science |a Solanki, Nayan ELSEVIER |t Rheological analysis of itraconazole-polymer mixtures to determine optimal melt extrusion temperature for development of amorphous solid dispersion |d 2017 |d the international journal |g Amsterdam [u.a.] |w (DE-627)ELV000529575 |
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10.1016/j.energy.2018.03.061 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001024.pica (DE-627)ELV042964172 (ELSEVIER)S0360-5442(18)30469-9 DE-627 ger DE-627 rakwb eng 610 VZ 15,3 ssgn PHARM DE-84 fid 44.40 bkl Hongwen, He verfasserin aut Real-time global driving cycle construction and the application to economy driving pro system in plug-in hybrid electric vehicles 2018transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper proposes a global driving cycle construction method based on the real-time traffic information, which can realize online optimal energy management for plug-in hybrid electric vehicles (PHEVs). The construction method is mainly divided into three parts: the construction of velocity segments database; the construction of real-time traffic information tensor model database, and the construction of real-time global driving cycle. For the acquisition of the real-time traffic information, a two-step completion method is adopted to obtain the complete and accuracy traffic information; for the driving cycle construction, the velocity segment database, the road section velocity and the Markov transfer matrix with Monte Carlo are used to generate velocity segments which constitute the global driving cycle. With the updated real-time traffic information, the global driving cycle is reconstructed which further reflect the real-time road condition. The efficient dynamic programming (DP) algorithm is applied to realize online energy management in PHEVs. Its simulation shows that the fuel efficiency improves by at least 19.83% compared with charge depleting and charge sustain (CDCS) control strategy. Finally, the economy driving pro system (EDPS) is presented in this paper, and it contributes 5.79% fuel efficiency compared with non-EDPS. This paper proposes a global driving cycle construction method based on the real-time traffic information, which can realize online optimal energy management for plug-in hybrid electric vehicles (PHEVs). The construction method is mainly divided into three parts: the construction of velocity segments database; the construction of real-time traffic information tensor model database, and the construction of real-time global driving cycle. For the acquisition of the real-time traffic information, a two-step completion method is adopted to obtain the complete and accuracy traffic information; for the driving cycle construction, the velocity segment database, the road section velocity and the Markov transfer matrix with Monte Carlo are used to generate velocity segments which constitute the global driving cycle. With the updated real-time traffic information, the global driving cycle is reconstructed which further reflect the real-time road condition. The efficient dynamic programming (DP) algorithm is applied to realize online energy management in PHEVs. Its simulation shows that the fuel efficiency improves by at least 19.83% compared with charge depleting and charge sustain (CDCS) control strategy. Finally, the economy driving pro system (EDPS) is presented in this paper, and it contributes 5.79% fuel efficiency compared with non-EDPS. Tensor completion Elsevier EDPS Elsevier Global driving cycle Elsevier Dynamic programming Elsevier PHEV Elsevier Traffic information Elsevier Jinquan, Guo oth Jiankun, Peng oth Huachun, Tan oth Chao, Sun oth Enthalten in Elsevier Science Solanki, Nayan ELSEVIER Rheological analysis of itraconazole-polymer mixtures to determine optimal melt extrusion temperature for development of amorphous solid dispersion 2017 the international journal Amsterdam [u.a.] (DE-627)ELV000529575 volume:152 year:2018 day:1 month:06 pages:95-107 extent:13 https://doi.org/10.1016/j.energy.2018.03.061 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-PHARM SSG-OLC-PHA SSG-OPC-PHA 44.40 Pharmazie Pharmazeutika VZ AR 152 2018 1 0601 95-107 13 |
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10.1016/j.energy.2018.03.061 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001024.pica (DE-627)ELV042964172 (ELSEVIER)S0360-5442(18)30469-9 DE-627 ger DE-627 rakwb eng 610 VZ 15,3 ssgn PHARM DE-84 fid 44.40 bkl Hongwen, He verfasserin aut Real-time global driving cycle construction and the application to economy driving pro system in plug-in hybrid electric vehicles 2018transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper proposes a global driving cycle construction method based on the real-time traffic information, which can realize online optimal energy management for plug-in hybrid electric vehicles (PHEVs). The construction method is mainly divided into three parts: the construction of velocity segments database; the construction of real-time traffic information tensor model database, and the construction of real-time global driving cycle. For the acquisition of the real-time traffic information, a two-step completion method is adopted to obtain the complete and accuracy traffic information; for the driving cycle construction, the velocity segment database, the road section velocity and the Markov transfer matrix with Monte Carlo are used to generate velocity segments which constitute the global driving cycle. With the updated real-time traffic information, the global driving cycle is reconstructed which further reflect the real-time road condition. The efficient dynamic programming (DP) algorithm is applied to realize online energy management in PHEVs. Its simulation shows that the fuel efficiency improves by at least 19.83% compared with charge depleting and charge sustain (CDCS) control strategy. Finally, the economy driving pro system (EDPS) is presented in this paper, and it contributes 5.79% fuel efficiency compared with non-EDPS. This paper proposes a global driving cycle construction method based on the real-time traffic information, which can realize online optimal energy management for plug-in hybrid electric vehicles (PHEVs). The construction method is mainly divided into three parts: the construction of velocity segments database; the construction of real-time traffic information tensor model database, and the construction of real-time global driving cycle. For the acquisition of the real-time traffic information, a two-step completion method is adopted to obtain the complete and accuracy traffic information; for the driving cycle construction, the velocity segment database, the road section velocity and the Markov transfer matrix with Monte Carlo are used to generate velocity segments which constitute the global driving cycle. With the updated real-time traffic information, the global driving cycle is reconstructed which further reflect the real-time road condition. The efficient dynamic programming (DP) algorithm is applied to realize online energy management in PHEVs. Its simulation shows that the fuel efficiency improves by at least 19.83% compared with charge depleting and charge sustain (CDCS) control strategy. Finally, the economy driving pro system (EDPS) is presented in this paper, and it contributes 5.79% fuel efficiency compared with non-EDPS. Tensor completion Elsevier EDPS Elsevier Global driving cycle Elsevier Dynamic programming Elsevier PHEV Elsevier Traffic information Elsevier Jinquan, Guo oth Jiankun, Peng oth Huachun, Tan oth Chao, Sun oth Enthalten in Elsevier Science Solanki, Nayan ELSEVIER Rheological analysis of itraconazole-polymer mixtures to determine optimal melt extrusion temperature for development of amorphous solid dispersion 2017 the international journal Amsterdam [u.a.] (DE-627)ELV000529575 volume:152 year:2018 day:1 month:06 pages:95-107 extent:13 https://doi.org/10.1016/j.energy.2018.03.061 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-PHARM SSG-OLC-PHA SSG-OPC-PHA 44.40 Pharmazie Pharmazeutika VZ AR 152 2018 1 0601 95-107 13 |
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10.1016/j.energy.2018.03.061 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001024.pica (DE-627)ELV042964172 (ELSEVIER)S0360-5442(18)30469-9 DE-627 ger DE-627 rakwb eng 610 VZ 15,3 ssgn PHARM DE-84 fid 44.40 bkl Hongwen, He verfasserin aut Real-time global driving cycle construction and the application to economy driving pro system in plug-in hybrid electric vehicles 2018transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper proposes a global driving cycle construction method based on the real-time traffic information, which can realize online optimal energy management for plug-in hybrid electric vehicles (PHEVs). The construction method is mainly divided into three parts: the construction of velocity segments database; the construction of real-time traffic information tensor model database, and the construction of real-time global driving cycle. For the acquisition of the real-time traffic information, a two-step completion method is adopted to obtain the complete and accuracy traffic information; for the driving cycle construction, the velocity segment database, the road section velocity and the Markov transfer matrix with Monte Carlo are used to generate velocity segments which constitute the global driving cycle. With the updated real-time traffic information, the global driving cycle is reconstructed which further reflect the real-time road condition. The efficient dynamic programming (DP) algorithm is applied to realize online energy management in PHEVs. Its simulation shows that the fuel efficiency improves by at least 19.83% compared with charge depleting and charge sustain (CDCS) control strategy. Finally, the economy driving pro system (EDPS) is presented in this paper, and it contributes 5.79% fuel efficiency compared with non-EDPS. This paper proposes a global driving cycle construction method based on the real-time traffic information, which can realize online optimal energy management for plug-in hybrid electric vehicles (PHEVs). The construction method is mainly divided into three parts: the construction of velocity segments database; the construction of real-time traffic information tensor model database, and the construction of real-time global driving cycle. For the acquisition of the real-time traffic information, a two-step completion method is adopted to obtain the complete and accuracy traffic information; for the driving cycle construction, the velocity segment database, the road section velocity and the Markov transfer matrix with Monte Carlo are used to generate velocity segments which constitute the global driving cycle. With the updated real-time traffic information, the global driving cycle is reconstructed which further reflect the real-time road condition. The efficient dynamic programming (DP) algorithm is applied to realize online energy management in PHEVs. Its simulation shows that the fuel efficiency improves by at least 19.83% compared with charge depleting and charge sustain (CDCS) control strategy. Finally, the economy driving pro system (EDPS) is presented in this paper, and it contributes 5.79% fuel efficiency compared with non-EDPS. Tensor completion Elsevier EDPS Elsevier Global driving cycle Elsevier Dynamic programming Elsevier PHEV Elsevier Traffic information Elsevier Jinquan, Guo oth Jiankun, Peng oth Huachun, Tan oth Chao, Sun oth Enthalten in Elsevier Science Solanki, Nayan ELSEVIER Rheological analysis of itraconazole-polymer mixtures to determine optimal melt extrusion temperature for development of amorphous solid dispersion 2017 the international journal Amsterdam [u.a.] (DE-627)ELV000529575 volume:152 year:2018 day:1 month:06 pages:95-107 extent:13 https://doi.org/10.1016/j.energy.2018.03.061 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-PHARM SSG-OLC-PHA SSG-OPC-PHA 44.40 Pharmazie Pharmazeutika VZ AR 152 2018 1 0601 95-107 13 |
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10.1016/j.energy.2018.03.061 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001024.pica (DE-627)ELV042964172 (ELSEVIER)S0360-5442(18)30469-9 DE-627 ger DE-627 rakwb eng 610 VZ 15,3 ssgn PHARM DE-84 fid 44.40 bkl Hongwen, He verfasserin aut Real-time global driving cycle construction and the application to economy driving pro system in plug-in hybrid electric vehicles 2018transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper proposes a global driving cycle construction method based on the real-time traffic information, which can realize online optimal energy management for plug-in hybrid electric vehicles (PHEVs). The construction method is mainly divided into three parts: the construction of velocity segments database; the construction of real-time traffic information tensor model database, and the construction of real-time global driving cycle. For the acquisition of the real-time traffic information, a two-step completion method is adopted to obtain the complete and accuracy traffic information; for the driving cycle construction, the velocity segment database, the road section velocity and the Markov transfer matrix with Monte Carlo are used to generate velocity segments which constitute the global driving cycle. With the updated real-time traffic information, the global driving cycle is reconstructed which further reflect the real-time road condition. The efficient dynamic programming (DP) algorithm is applied to realize online energy management in PHEVs. Its simulation shows that the fuel efficiency improves by at least 19.83% compared with charge depleting and charge sustain (CDCS) control strategy. Finally, the economy driving pro system (EDPS) is presented in this paper, and it contributes 5.79% fuel efficiency compared with non-EDPS. This paper proposes a global driving cycle construction method based on the real-time traffic information, which can realize online optimal energy management for plug-in hybrid electric vehicles (PHEVs). The construction method is mainly divided into three parts: the construction of velocity segments database; the construction of real-time traffic information tensor model database, and the construction of real-time global driving cycle. For the acquisition of the real-time traffic information, a two-step completion method is adopted to obtain the complete and accuracy traffic information; for the driving cycle construction, the velocity segment database, the road section velocity and the Markov transfer matrix with Monte Carlo are used to generate velocity segments which constitute the global driving cycle. With the updated real-time traffic information, the global driving cycle is reconstructed which further reflect the real-time road condition. The efficient dynamic programming (DP) algorithm is applied to realize online energy management in PHEVs. Its simulation shows that the fuel efficiency improves by at least 19.83% compared with charge depleting and charge sustain (CDCS) control strategy. Finally, the economy driving pro system (EDPS) is presented in this paper, and it contributes 5.79% fuel efficiency compared with non-EDPS. Tensor completion Elsevier EDPS Elsevier Global driving cycle Elsevier Dynamic programming Elsevier PHEV Elsevier Traffic information Elsevier Jinquan, Guo oth Jiankun, Peng oth Huachun, Tan oth Chao, Sun oth Enthalten in Elsevier Science Solanki, Nayan ELSEVIER Rheological analysis of itraconazole-polymer mixtures to determine optimal melt extrusion temperature for development of amorphous solid dispersion 2017 the international journal Amsterdam [u.a.] (DE-627)ELV000529575 volume:152 year:2018 day:1 month:06 pages:95-107 extent:13 https://doi.org/10.1016/j.energy.2018.03.061 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-PHARM SSG-OLC-PHA SSG-OPC-PHA 44.40 Pharmazie Pharmazeutika VZ AR 152 2018 1 0601 95-107 13 |
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10.1016/j.energy.2018.03.061 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001024.pica (DE-627)ELV042964172 (ELSEVIER)S0360-5442(18)30469-9 DE-627 ger DE-627 rakwb eng 610 VZ 15,3 ssgn PHARM DE-84 fid 44.40 bkl Hongwen, He verfasserin aut Real-time global driving cycle construction and the application to economy driving pro system in plug-in hybrid electric vehicles 2018transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper proposes a global driving cycle construction method based on the real-time traffic information, which can realize online optimal energy management for plug-in hybrid electric vehicles (PHEVs). The construction method is mainly divided into three parts: the construction of velocity segments database; the construction of real-time traffic information tensor model database, and the construction of real-time global driving cycle. For the acquisition of the real-time traffic information, a two-step completion method is adopted to obtain the complete and accuracy traffic information; for the driving cycle construction, the velocity segment database, the road section velocity and the Markov transfer matrix with Monte Carlo are used to generate velocity segments which constitute the global driving cycle. With the updated real-time traffic information, the global driving cycle is reconstructed which further reflect the real-time road condition. The efficient dynamic programming (DP) algorithm is applied to realize online energy management in PHEVs. Its simulation shows that the fuel efficiency improves by at least 19.83% compared with charge depleting and charge sustain (CDCS) control strategy. Finally, the economy driving pro system (EDPS) is presented in this paper, and it contributes 5.79% fuel efficiency compared with non-EDPS. This paper proposes a global driving cycle construction method based on the real-time traffic information, which can realize online optimal energy management for plug-in hybrid electric vehicles (PHEVs). The construction method is mainly divided into three parts: the construction of velocity segments database; the construction of real-time traffic information tensor model database, and the construction of real-time global driving cycle. For the acquisition of the real-time traffic information, a two-step completion method is adopted to obtain the complete and accuracy traffic information; for the driving cycle construction, the velocity segment database, the road section velocity and the Markov transfer matrix with Monte Carlo are used to generate velocity segments which constitute the global driving cycle. With the updated real-time traffic information, the global driving cycle is reconstructed which further reflect the real-time road condition. The efficient dynamic programming (DP) algorithm is applied to realize online energy management in PHEVs. Its simulation shows that the fuel efficiency improves by at least 19.83% compared with charge depleting and charge sustain (CDCS) control strategy. Finally, the economy driving pro system (EDPS) is presented in this paper, and it contributes 5.79% fuel efficiency compared with non-EDPS. Tensor completion Elsevier EDPS Elsevier Global driving cycle Elsevier Dynamic programming Elsevier PHEV Elsevier Traffic information Elsevier Jinquan, Guo oth Jiankun, Peng oth Huachun, Tan oth Chao, Sun oth Enthalten in Elsevier Science Solanki, Nayan ELSEVIER Rheological analysis of itraconazole-polymer mixtures to determine optimal melt extrusion temperature for development of amorphous solid dispersion 2017 the international journal Amsterdam [u.a.] (DE-627)ELV000529575 volume:152 year:2018 day:1 month:06 pages:95-107 extent:13 https://doi.org/10.1016/j.energy.2018.03.061 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-PHARM SSG-OLC-PHA SSG-OPC-PHA 44.40 Pharmazie Pharmazeutika VZ AR 152 2018 1 0601 95-107 13 |
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Enthalten in Rheological analysis of itraconazole-polymer mixtures to determine optimal melt extrusion temperature for development of amorphous solid dispersion Amsterdam [u.a.] volume:152 year:2018 day:1 month:06 pages:95-107 extent:13 |
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real-time global driving cycle construction and the application to economy driving pro system in plug-in hybrid electric vehicles |
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Real-time global driving cycle construction and the application to economy driving pro system in plug-in hybrid electric vehicles |
| abstract |
This paper proposes a global driving cycle construction method based on the real-time traffic information, which can realize online optimal energy management for plug-in hybrid electric vehicles (PHEVs). The construction method is mainly divided into three parts: the construction of velocity segments database; the construction of real-time traffic information tensor model database, and the construction of real-time global driving cycle. For the acquisition of the real-time traffic information, a two-step completion method is adopted to obtain the complete and accuracy traffic information; for the driving cycle construction, the velocity segment database, the road section velocity and the Markov transfer matrix with Monte Carlo are used to generate velocity segments which constitute the global driving cycle. With the updated real-time traffic information, the global driving cycle is reconstructed which further reflect the real-time road condition. The efficient dynamic programming (DP) algorithm is applied to realize online energy management in PHEVs. Its simulation shows that the fuel efficiency improves by at least 19.83% compared with charge depleting and charge sustain (CDCS) control strategy. Finally, the economy driving pro system (EDPS) is presented in this paper, and it contributes 5.79% fuel efficiency compared with non-EDPS. |
| abstractGer |
This paper proposes a global driving cycle construction method based on the real-time traffic information, which can realize online optimal energy management for plug-in hybrid electric vehicles (PHEVs). The construction method is mainly divided into three parts: the construction of velocity segments database; the construction of real-time traffic information tensor model database, and the construction of real-time global driving cycle. For the acquisition of the real-time traffic information, a two-step completion method is adopted to obtain the complete and accuracy traffic information; for the driving cycle construction, the velocity segment database, the road section velocity and the Markov transfer matrix with Monte Carlo are used to generate velocity segments which constitute the global driving cycle. With the updated real-time traffic information, the global driving cycle is reconstructed which further reflect the real-time road condition. The efficient dynamic programming (DP) algorithm is applied to realize online energy management in PHEVs. Its simulation shows that the fuel efficiency improves by at least 19.83% compared with charge depleting and charge sustain (CDCS) control strategy. Finally, the economy driving pro system (EDPS) is presented in this paper, and it contributes 5.79% fuel efficiency compared with non-EDPS. |
| abstract_unstemmed |
This paper proposes a global driving cycle construction method based on the real-time traffic information, which can realize online optimal energy management for plug-in hybrid electric vehicles (PHEVs). The construction method is mainly divided into three parts: the construction of velocity segments database; the construction of real-time traffic information tensor model database, and the construction of real-time global driving cycle. For the acquisition of the real-time traffic information, a two-step completion method is adopted to obtain the complete and accuracy traffic information; for the driving cycle construction, the velocity segment database, the road section velocity and the Markov transfer matrix with Monte Carlo are used to generate velocity segments which constitute the global driving cycle. With the updated real-time traffic information, the global driving cycle is reconstructed which further reflect the real-time road condition. The efficient dynamic programming (DP) algorithm is applied to realize online energy management in PHEVs. Its simulation shows that the fuel efficiency improves by at least 19.83% compared with charge depleting and charge sustain (CDCS) control strategy. Finally, the economy driving pro system (EDPS) is presented in this paper, and it contributes 5.79% fuel efficiency compared with non-EDPS. |
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