Energy management of a parallel hybrid electric vehicle based on Lyapunov algorithm
Aiming at the time-consuming problem of basic dynamic programming (DP) algorithm and the fact that adaptive energy control management strategy (A-ECMS) cannot provide the optimal fuel consumption, this paper proposes highly integrated model of the vehicle coupling with a detailed engine model which...
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| Published in | eTransportation (Amsterdam) Vol. 13; p. 100184 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
01.08.2022
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| Subjects | |
| Online Access | Get full text |
| ISSN | 2590-1168 2590-1168 |
| DOI | 10.1016/j.etran.2022.100184 |
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| Abstract | Aiming at the time-consuming problem of basic dynamic programming (DP) algorithm and the fact that adaptive energy control management strategy (A-ECMS) cannot provide the optimal fuel consumption, this paper proposes highly integrated model of the vehicle coupling with a detailed engine model which is validated by the NEDC tested value. Then, an online energy management algorithm is proposed based on Lyapunov optimization analysis considering the system stability. The results show that (1) the cumulative fuel consumption obtained from the integrated model is 832.01g while the tested fuel consumption is 845.82g. The relative error between the simulated and tested fuel consumption is 1.63%. On this basis, the integrated model can be considered to predict the fuel economy of the vehicle with extraordinarily high accuracy. (2) Comparing the Lyapunov algorithm with DP and A-ECMS algorithms on a series parallel hybrid electric vehicle, the average fuel consumption of the proposed online energy management algorithm based on Lyapunov optimization is reduced by 13% compared with A-ECMS algorithm, which lays the foundation for the development of a unified algorithm platform.
•An integrated model of the vehicle coupling with a detailed engine model is built.•Energy management of a PHEV based on Lyapunov algorithm is presented.•Fuel consumption of A-ECMS algorithm based on Lyapunov optimization is reduced by 13%. |
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| AbstractList | Aiming at the time-consuming problem of basic dynamic programming (DP) algorithm and the fact that adaptive energy control management strategy (A-ECMS) cannot provide the optimal fuel consumption, this paper proposes highly integrated model of the vehicle coupling with a detailed engine model which is validated by the NEDC tested value. Then, an online energy management algorithm is proposed based on Lyapunov optimization analysis considering the system stability. The results show that (1) the cumulative fuel consumption obtained from the integrated model is 832.01g while the tested fuel consumption is 845.82g. The relative error between the simulated and tested fuel consumption is 1.63%. On this basis, the integrated model can be considered to predict the fuel economy of the vehicle with extraordinarily high accuracy. (2) Comparing the Lyapunov algorithm with DP and A-ECMS algorithms on a series parallel hybrid electric vehicle, the average fuel consumption of the proposed online energy management algorithm based on Lyapunov optimization is reduced by 13% compared with A-ECMS algorithm, which lays the foundation for the development of a unified algorithm platform.
•An integrated model of the vehicle coupling with a detailed engine model is built.•Energy management of a PHEV based on Lyapunov algorithm is presented.•Fuel consumption of A-ECMS algorithm based on Lyapunov optimization is reduced by 13%. |
| ArticleNumber | 100184 |
| Author | Ouyang, Minggao Deng, Xintao Ma, Jugang Yang, Fuyuan Liu, Biao Li, Yangyang |
| Author_xml | – sequence: 1 givenname: Yangyang surname: Li fullname: Li, Yangyang email: lyy025930@163.com – sequence: 2 givenname: Xintao surname: Deng fullname: Deng, Xintao – sequence: 3 givenname: Biao surname: Liu fullname: Liu, Biao – sequence: 4 givenname: Jugang surname: Ma fullname: Ma, Jugang – sequence: 5 givenname: Fuyuan surname: Yang fullname: Yang, Fuyuan email: fyyang@mail.tsinghua.edu.cn – sequence: 6 givenname: Minggao surname: Ouyang fullname: Ouyang, Minggao email: ouymg@tsinghua.edu.cn |
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| CitedBy_id | crossref_primary_10_1016_j_energy_2022_125262 crossref_primary_10_1016_j_fuel_2022_126493 crossref_primary_10_1016_j_ijthermalsci_2023_108804 crossref_primary_10_1016_j_energy_2024_130659 crossref_primary_10_1016_j_seta_2023_103379 crossref_primary_10_3390_su15097539 crossref_primary_10_1109_TVT_2023_3336937 crossref_primary_10_1016_j_etran_2024_100332 crossref_primary_10_18186_thermal_1370731 crossref_primary_10_1016_j_iot_2024_101085 crossref_primary_10_1016_j_cej_2022_138327 crossref_primary_10_1016_j_etran_2023_100269 crossref_primary_10_1177_09544070231199282 |
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