Comparisons of Energy Management Methods for a Parallel Plug-In Hybrid Electric Vehicle between the Convex Optimization and Dynamic Programming
This paper proposes a comparison study of energy management methods for a parallel plug-in hybrid electric vehicle (PHEV). Based on detailed analysis of the vehicle driveline, quadratic convex functions are presented to describe the nonlinear relationship between engine fuel-rate and battery chargin...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2018-01-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2076-3417/8/2/218 |
| _version_ | 1811278282861051904 |
|---|---|
| author | Renxin Xiao Baoshuai Liu Jiangwei Shen Ningyuan Guo Wensheng Yan Zheng Chen |
| author_facet | Renxin Xiao Baoshuai Liu Jiangwei Shen Ningyuan Guo Wensheng Yan Zheng Chen |
| author_sort | Renxin Xiao |
| collection | DOAJ |
| description | This paper proposes a comparison study of energy management methods for a parallel plug-in hybrid electric vehicle (PHEV). Based on detailed analysis of the vehicle driveline, quadratic convex functions are presented to describe the nonlinear relationship between engine fuel-rate and battery charging power at different vehicle speed and driveline power demand. The engine-on power threshold is estimated by the simulated annealing (SA) algorithm, and the battery power command is achieved by convex optimization with target of improving fuel economy, compared with the dynamic programming (DP) based method and the charging depleting–charging sustaining (CD/CS) method. In addition, the proposed control methods are discussed at different initial battery state of charge (SOC) values to extend the application. Simulation results validate that the proposed strategy based on convex optimization can save the fuel consumption and reduce the computation burden obviously. |
| first_indexed | 2024-04-13T00:33:03Z |
| format | Article |
| id | doaj.art-2923aaa16d0045aaab7d0475228a3d86 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-04-13T00:33:03Z |
| publishDate | 2018-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-2923aaa16d0045aaab7d0475228a3d862022-12-22T03:10:25ZengMDPI AGApplied Sciences2076-34172018-01-018221810.3390/app8020218app8020218Comparisons of Energy Management Methods for a Parallel Plug-In Hybrid Electric Vehicle between the Convex Optimization and Dynamic ProgrammingRenxin Xiao0Baoshuai Liu1Jiangwei Shen2Ningyuan Guo3Wensheng Yan4Zheng Chen5Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, ChinaFaculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, ChinaFaculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, ChinaFaculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, ChinaFaculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, ChinaFaculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, ChinaThis paper proposes a comparison study of energy management methods for a parallel plug-in hybrid electric vehicle (PHEV). Based on detailed analysis of the vehicle driveline, quadratic convex functions are presented to describe the nonlinear relationship between engine fuel-rate and battery charging power at different vehicle speed and driveline power demand. The engine-on power threshold is estimated by the simulated annealing (SA) algorithm, and the battery power command is achieved by convex optimization with target of improving fuel economy, compared with the dynamic programming (DP) based method and the charging depleting–charging sustaining (CD/CS) method. In addition, the proposed control methods are discussed at different initial battery state of charge (SOC) values to extend the application. Simulation results validate that the proposed strategy based on convex optimization can save the fuel consumption and reduce the computation burden obviously.http://www.mdpi.com/2076-3417/8/2/218battery powerconvex optimizationdynamic programmingengine-on powerplug-in hybrid electric vehiclesimulated annealing |
| spellingShingle | Renxin Xiao Baoshuai Liu Jiangwei Shen Ningyuan Guo Wensheng Yan Zheng Chen Comparisons of Energy Management Methods for a Parallel Plug-In Hybrid Electric Vehicle between the Convex Optimization and Dynamic Programming Applied Sciences battery power convex optimization dynamic programming engine-on power plug-in hybrid electric vehicle simulated annealing |
| title | Comparisons of Energy Management Methods for a Parallel Plug-In Hybrid Electric Vehicle between the Convex Optimization and Dynamic Programming |
| title_full | Comparisons of Energy Management Methods for a Parallel Plug-In Hybrid Electric Vehicle between the Convex Optimization and Dynamic Programming |
| title_fullStr | Comparisons of Energy Management Methods for a Parallel Plug-In Hybrid Electric Vehicle between the Convex Optimization and Dynamic Programming |
| title_full_unstemmed | Comparisons of Energy Management Methods for a Parallel Plug-In Hybrid Electric Vehicle between the Convex Optimization and Dynamic Programming |
| title_short | Comparisons of Energy Management Methods for a Parallel Plug-In Hybrid Electric Vehicle between the Convex Optimization and Dynamic Programming |
| title_sort | comparisons of energy management methods for a parallel plug in hybrid electric vehicle between the convex optimization and dynamic programming |
| topic | battery power convex optimization dynamic programming engine-on power plug-in hybrid electric vehicle simulated annealing |
| url | http://www.mdpi.com/2076-3417/8/2/218 |
| work_keys_str_mv | AT renxinxiao comparisonsofenergymanagementmethodsforaparallelpluginhybridelectricvehiclebetweentheconvexoptimizationanddynamicprogramming AT baoshuailiu comparisonsofenergymanagementmethodsforaparallelpluginhybridelectricvehiclebetweentheconvexoptimizationanddynamicprogramming AT jiangweishen comparisonsofenergymanagementmethodsforaparallelpluginhybridelectricvehiclebetweentheconvexoptimizationanddynamicprogramming AT ningyuanguo comparisonsofenergymanagementmethodsforaparallelpluginhybridelectricvehiclebetweentheconvexoptimizationanddynamicprogramming AT wenshengyan comparisonsofenergymanagementmethodsforaparallelpluginhybridelectricvehiclebetweentheconvexoptimizationanddynamicprogramming AT zhengchen comparisonsofenergymanagementmethodsforaparallelpluginhybridelectricvehiclebetweentheconvexoptimizationanddynamicprogramming |