Component sizing of a series hybrid electric vehicle through artificial neural network. (15th February 2022)
- Record Type:
- Journal Article
- Title:
- Component sizing of a series hybrid electric vehicle through artificial neural network. (15th February 2022)
- Main Title:
- Component sizing of a series hybrid electric vehicle through artificial neural network
- Authors:
- Khamesipour, M.
Chitsaz, I.
Salehi, M.
Alizadenia, S. - Abstract:
- Highlights: The required battery size of a conventional series hybrid is less than 1.44 kWh. The required power of the electric motor is 80 kW for a conventional series hybrid. The effect of acceleration on the required power is not linear. A 20% increase in the road slope leads to a 59% increase in the steady power. Abstract: Series hybrid electric vehicles are the intermediate technology between gasoline-powered vehicles and full electric vehicles to suppress the emission and global warming issues. In the present study, the component sizing of a series hybrid electric vehicle including a high voltage battery, the combustion engine, and the electric motor is investigated employing experimental data and an artificial neural network. Despite previous studies, the experimental data is implemented to generate a robust artificial neural network model. About 3000 data series are implemented to train the artificial neural network. The results reveal that the 1.44 kWh for the high voltage battery is sufficient for all driving conditions. This battery size can overcome many challenges of this type of vehicle both in price and packaging. Three different working point of 6.7, 12.2 and 22 kW is proposed for a combustion engine in the best efficiency zone for urban, accelerating and highway driving conditions, respectively. The required power of the electric motor is 80 kW to support the drivability and vehicle acceleration in different conditions. This novel method can be extended toHighlights: The required battery size of a conventional series hybrid is less than 1.44 kWh. The required power of the electric motor is 80 kW for a conventional series hybrid. The effect of acceleration on the required power is not linear. A 20% increase in the road slope leads to a 59% increase in the steady power. Abstract: Series hybrid electric vehicles are the intermediate technology between gasoline-powered vehicles and full electric vehicles to suppress the emission and global warming issues. In the present study, the component sizing of a series hybrid electric vehicle including a high voltage battery, the combustion engine, and the electric motor is investigated employing experimental data and an artificial neural network. Despite previous studies, the experimental data is implemented to generate a robust artificial neural network model. About 3000 data series are implemented to train the artificial neural network. The results reveal that the 1.44 kWh for the high voltage battery is sufficient for all driving conditions. This battery size can overcome many challenges of this type of vehicle both in price and packaging. Three different working point of 6.7, 12.2 and 22 kW is proposed for a combustion engine in the best efficiency zone for urban, accelerating and highway driving conditions, respectively. The required power of the electric motor is 80 kW to support the drivability and vehicle acceleration in different conditions. This novel method can be extended to size the component of hybrid electric vehicles for different segments and driving conditions. … (more)
- Is Part Of:
- Energy conversion and management. Volume 254(2022)
- Journal:
- Energy conversion and management
- Issue:
- Volume 254(2022)
- Issue Display:
- Volume 254, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 254
- Issue:
- 2022
- Issue Sort Value:
- 2022-0254-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-02-15
- Subjects:
- Component sizing -- Series hybrid electric vehicle -- Artificial neural network -- Dynamic power -- Steady power -- High voltage battery
Direct energy conversion -- Periodicals
Energy storage -- Periodicals
Energy transfer -- Periodicals
Énergie -- Conversion directe -- Périodiques
Direct energy conversion
Periodicals
621.3105 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01968904 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.enconman.2022.115300 ↗
- Languages:
- English
- ISSNs:
- 0196-8904
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3747.547000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 20827.xml