Optimal Fuel Consumption Modelling, Simulation, and Analysis for Hybrid Electric Vehicles
This paper reviews the latest studies of hybrid electric vehicles (HEVs) on modelling, controls, and energy management. HEV dynamics, formulas, calculations, and schemes of vehicle parts, such as battery, converter, electric motor, generator, and HEV Simulink models, are presented. Moreover, simulat...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-03-01
|
| Series: | Applied System Innovation |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2571-5577/5/2/36 |
| _version_ | 1797436941129482240 |
|---|---|
| author | Vu Trieu Minh Reza Moezzi Jindrich Cyrus Jaroslav Hlava |
| author_facet | Vu Trieu Minh Reza Moezzi Jindrich Cyrus Jaroslav Hlava |
| author_sort | Vu Trieu Minh |
| collection | DOAJ |
| description | This paper reviews the latest studies of hybrid electric vehicles (HEVs) on modelling, controls, and energy management. HEV dynamics, formulas, calculations, and schemes of vehicle parts, such as battery, converter, electric motor, generator, and HEV Simulink models, are presented. Moreover, simulations of the propulsion operation, regenerative braking system, and vehicle dynamics are conducted. A comprehensive HEV model is built that is simulated on different driving cycles of Federal Test Procedure 75 (FTP75), New York City Cycle (NYCC), Highway Fuel Economy Test (HWFET), and Extra Urban Driving Cycle (EUDC). Data achieved from these simulations were analysed and tested with several fuel regression models to determine the best fuel regression estimation for HEV fuel consumption on the basis of their weights and tire radiuses. The best fuel regression equation is obtained with a determination coefficient R-squared greater than 99%. Lastly, the optimal model and other HEVs models are simulated on different driving cycles to prove that the fuel consumption of our best-fit regression model is the best. |
| first_indexed | 2024-03-09T11:10:47Z |
| format | Article |
| id | doaj.art-3290e4b56bff46ef803cbedef456dbf1 |
| institution | Directory Open Access Journal |
| issn | 2571-5577 |
| language | English |
| last_indexed | 2024-03-09T11:10:47Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied System Innovation |
| spelling | doaj.art-3290e4b56bff46ef803cbedef456dbf12023-12-01T00:45:35ZengMDPI AGApplied System Innovation2571-55772022-03-01523610.3390/asi5020036Optimal Fuel Consumption Modelling, Simulation, and Analysis for Hybrid Electric VehiclesVu Trieu Minh0Reza Moezzi1Jindrich Cyrus2Jaroslav Hlava3Institute for Nanomaterials, Advanced Technologies and Innovation, Technical University of Liberec, 461 17 Liberec, Czech RepublicInstitute for Nanomaterials, Advanced Technologies and Innovation, Technical University of Liberec, 461 17 Liberec, Czech RepublicInstitute for Nanomaterials, Advanced Technologies and Innovation, Technical University of Liberec, 461 17 Liberec, Czech RepublicFaculty of Mechatronics, Informatics and Interdisciplinary Studies, Technical University of Liberec, 461 17 Liberec, Czech RepublicThis paper reviews the latest studies of hybrid electric vehicles (HEVs) on modelling, controls, and energy management. HEV dynamics, formulas, calculations, and schemes of vehicle parts, such as battery, converter, electric motor, generator, and HEV Simulink models, are presented. Moreover, simulations of the propulsion operation, regenerative braking system, and vehicle dynamics are conducted. A comprehensive HEV model is built that is simulated on different driving cycles of Federal Test Procedure 75 (FTP75), New York City Cycle (NYCC), Highway Fuel Economy Test (HWFET), and Extra Urban Driving Cycle (EUDC). Data achieved from these simulations were analysed and tested with several fuel regression models to determine the best fuel regression estimation for HEV fuel consumption on the basis of their weights and tire radiuses. The best fuel regression equation is obtained with a determination coefficient R-squared greater than 99%. Lastly, the optimal model and other HEVs models are simulated on different driving cycles to prove that the fuel consumption of our best-fit regression model is the best.https://www.mdpi.com/2571-5577/5/2/36HEV modellingvehicle dynamicsdriving cyclesfuel consumptionbest-fit curve |
| spellingShingle | Vu Trieu Minh Reza Moezzi Jindrich Cyrus Jaroslav Hlava Optimal Fuel Consumption Modelling, Simulation, and Analysis for Hybrid Electric Vehicles Applied System Innovation HEV modelling vehicle dynamics driving cycles fuel consumption best-fit curve |
| title | Optimal Fuel Consumption Modelling, Simulation, and Analysis for Hybrid Electric Vehicles |
| title_full | Optimal Fuel Consumption Modelling, Simulation, and Analysis for Hybrid Electric Vehicles |
| title_fullStr | Optimal Fuel Consumption Modelling, Simulation, and Analysis for Hybrid Electric Vehicles |
| title_full_unstemmed | Optimal Fuel Consumption Modelling, Simulation, and Analysis for Hybrid Electric Vehicles |
| title_short | Optimal Fuel Consumption Modelling, Simulation, and Analysis for Hybrid Electric Vehicles |
| title_sort | optimal fuel consumption modelling simulation and analysis for hybrid electric vehicles |
| topic | HEV modelling vehicle dynamics driving cycles fuel consumption best-fit curve |
| url | https://www.mdpi.com/2571-5577/5/2/36 |
| work_keys_str_mv | AT vutrieuminh optimalfuelconsumptionmodellingsimulationandanalysisforhybridelectricvehicles AT rezamoezzi optimalfuelconsumptionmodellingsimulationandanalysisforhybridelectricvehicles AT jindrichcyrus optimalfuelconsumptionmodellingsimulationandanalysisforhybridelectricvehicles AT jaroslavhlava optimalfuelconsumptionmodellingsimulationandanalysisforhybridelectricvehicles |