Driving Cycle Synthesis, Aiming for Realness, by Extending Real-World Driving Databases
In order to transform conventional buses into electric ones, exact knowledge of the energy consumption of the vehicles is essential. Furthermore, for a proper design of the transition and to avoid inefficiencies and excessive costs, this information must be adjusted to real operating scenarios. Howe...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9775695/ |
| _version_ | 1817986718508253184 |
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| author | Roman Michael Sennefelder Petr Micek Ruben Martin-Clemente Jesus Carrion Risquez Ramon Carvajal Jesus Antonio Carrillo-Castrillo |
| author_facet | Roman Michael Sennefelder Petr Micek Ruben Martin-Clemente Jesus Carrion Risquez Ramon Carvajal Jesus Antonio Carrillo-Castrillo |
| author_sort | Roman Michael Sennefelder |
| collection | DOAJ |
| description | In order to transform conventional buses into electric ones, exact knowledge of the energy consumption of the vehicles is essential. Furthermore, for a proper design of the transition and to avoid inefficiencies and excessive costs, this information must be adjusted to real operating scenarios. However, a recurring problem in this context is the lack of data to address all these issues. Previous studies have focused on the use of standard driving cycles or on the synthesis of cycles from a single route. This paper presents a methodology for extending real-world driving databases to perform massive simulations, thereby narrowing the confidence interval of estimates. As a case study, the method was applied to a municipal bus operator’s database in a project to assess the feasibility of retrofitting a diesel to an electric bus. The proposed framework is useful for generating a valid database for research on energy consumption distribution and powertrain optimization, as well as to support public transport bus operators and manufacturers. |
| first_indexed | 2024-04-14T00:12:58Z |
| format | Article |
| id | doaj.art-1981202f48ea4f388a7fa1a60acb95ba |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-14T00:12:58Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-1981202f48ea4f388a7fa1a60acb95ba2022-12-22T02:23:14ZengIEEEIEEE Access2169-35362022-01-0110541235413510.1109/ACCESS.2022.31754929775695Driving Cycle Synthesis, Aiming for Realness, by Extending Real-World Driving DatabasesRoman Michael Sennefelder0https://orcid.org/0000-0002-1911-3959Petr Micek1Ruben Martin-Clemente2https://orcid.org/0000-0002-5905-7189Jesus Carrion Risquez3https://orcid.org/0000-0003-2525-0826Ramon Carvajal4https://orcid.org/0000-0003-3891-8987Jesus Antonio Carrillo-Castrillo5EVO Engineering GmbH, Munich, GermanyÙvolution Synergétique, Edelstauden, AustriaSignal Processing and Communications Department, University of Seville, Seville, SpainElectronics Engineering Department, University of Seville, Seville, SpainElectronics Engineering Department, University of Seville, Seville, SpainElectronics Engineering Department, University of Seville, Seville, SpainIn order to transform conventional buses into electric ones, exact knowledge of the energy consumption of the vehicles is essential. Furthermore, for a proper design of the transition and to avoid inefficiencies and excessive costs, this information must be adjusted to real operating scenarios. However, a recurring problem in this context is the lack of data to address all these issues. Previous studies have focused on the use of standard driving cycles or on the synthesis of cycles from a single route. This paper presents a methodology for extending real-world driving databases to perform massive simulations, thereby narrowing the confidence interval of estimates. As a case study, the method was applied to a municipal bus operator’s database in a project to assess the feasibility of retrofitting a diesel to an electric bus. The proposed framework is useful for generating a valid database for research on energy consumption distribution and powertrain optimization, as well as to support public transport bus operators and manufacturers.https://ieeexplore.ieee.org/document/9775695/Battery electric busenergy demanddatabase extensiondriving cyclespeed profile characterization |
| spellingShingle | Roman Michael Sennefelder Petr Micek Ruben Martin-Clemente Jesus Carrion Risquez Ramon Carvajal Jesus Antonio Carrillo-Castrillo Driving Cycle Synthesis, Aiming for Realness, by Extending Real-World Driving Databases IEEE Access Battery electric bus energy demand database extension driving cycle speed profile characterization |
| title | Driving Cycle Synthesis, Aiming for Realness, by Extending Real-World Driving Databases |
| title_full | Driving Cycle Synthesis, Aiming for Realness, by Extending Real-World Driving Databases |
| title_fullStr | Driving Cycle Synthesis, Aiming for Realness, by Extending Real-World Driving Databases |
| title_full_unstemmed | Driving Cycle Synthesis, Aiming for Realness, by Extending Real-World Driving Databases |
| title_short | Driving Cycle Synthesis, Aiming for Realness, by Extending Real-World Driving Databases |
| title_sort | driving cycle synthesis aiming for realness by extending real world driving databases |
| topic | Battery electric bus energy demand database extension driving cycle speed profile characterization |
| url | https://ieeexplore.ieee.org/document/9775695/ |
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