Map-based linear estimation of drive cycle for hybrid electric vehicles
Applications of hybrid electric vehicles (HEVs) and plug-in electric vehicles (PEVs) in modern power grids are increasing due to the growing concerns about environmental issues and unpredictable fuel prices. However, detailed information on drivers' behaviors which is required for vehicle contr...
| Main Authors: | , , , |
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| Format: | Conference Paper |
| Published: |
2015
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| Online Access: | http://hdl.handle.net/20.500.11937/49904 |
| _version_ | 1848758345943482368 |
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| author | Nejad, Arash Zargham Deilami, Sara Masoum, Mohammad Sherkat Haghdadi, N. |
| author_facet | Nejad, Arash Zargham Deilami, Sara Masoum, Mohammad Sherkat Haghdadi, N. |
| author_sort | Nejad, Arash Zargham |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Applications of hybrid electric vehicles (HEVs) and plug-in electric vehicles (PEVs) in modern power grids are increasing due to the growing concerns about environmental issues and unpredictable fuel prices. However, detailed information on drivers' behaviors which is required for vehicle control and management is not widely available. This paper presents a map-based linear estimation approach to estimate the drive cycles of hybrid electric vehicles (HEVs). It is shown that knowing geological data of the vehicle, a linear estimation of drive cycle is possible. Detailed simulations are presented to investigate the accuracy of the linear estimation compared with the real drive cycles. Simulation results are presented and analyzed for the linear estimations of two typical drive cycles including the highway fuel economy test (HWFET) cycle and the New York City cycle (NYCC). |
| first_indexed | 2025-11-14T09:42:31Z |
| format | Conference Paper |
| id | curtin-20.500.11937-49904 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:42:31Z |
| publishDate | 2015 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-499042017-09-13T15:37:42Z Map-based linear estimation of drive cycle for hybrid electric vehicles Nejad, Arash Zargham Deilami, Sara Masoum, Mohammad Sherkat Haghdadi, N. Applications of hybrid electric vehicles (HEVs) and plug-in electric vehicles (PEVs) in modern power grids are increasing due to the growing concerns about environmental issues and unpredictable fuel prices. However, detailed information on drivers' behaviors which is required for vehicle control and management is not widely available. This paper presents a map-based linear estimation approach to estimate the drive cycles of hybrid electric vehicles (HEVs). It is shown that knowing geological data of the vehicle, a linear estimation of drive cycle is possible. Detailed simulations are presented to investigate the accuracy of the linear estimation compared with the real drive cycles. Simulation results are presented and analyzed for the linear estimations of two typical drive cycles including the highway fuel economy test (HWFET) cycle and the New York City cycle (NYCC). 2015 Conference Paper http://hdl.handle.net/20.500.11937/49904 10.1109/AUPEC.2015.7324873 restricted |
| spellingShingle | Nejad, Arash Zargham Deilami, Sara Masoum, Mohammad Sherkat Haghdadi, N. Map-based linear estimation of drive cycle for hybrid electric vehicles |
| title | Map-based linear estimation of drive cycle for hybrid electric vehicles |
| title_full | Map-based linear estimation of drive cycle for hybrid electric vehicles |
| title_fullStr | Map-based linear estimation of drive cycle for hybrid electric vehicles |
| title_full_unstemmed | Map-based linear estimation of drive cycle for hybrid electric vehicles |
| title_short | Map-based linear estimation of drive cycle for hybrid electric vehicles |
| title_sort | map-based linear estimation of drive cycle for hybrid electric vehicles |
| url | http://hdl.handle.net/20.500.11937/49904 |