Discover the SciOpen Platform and Achieve Your Research Goals with Ease.
Search articles, authors, keywords, DOl and etc.
This paper uses the minimization and weighted sum of battery capacity loss and energy consumption under driving cycles as objective functions to improve the economy of Electric Vehicles (EVs) with an hybrid energy storage system composed of power batteries and ultracapacitors. Furthermore, Dynamic Programming (DP) is employed to determine the objective function values under different weight coefficients, the comprehensive cost consisting of battery aging and power consumption costs, and the relationship between the hybrid power distribution. We also evaluate the real-time fuzzy Energy Management Strategy (EMS), fuzzy control strategies, and a strategy based on DP using the World Light vehicle Test Procedure (WLTP) driving cycle and a synthesis driving cycle derived from New European Driving Cycle (NEDC), WLTP, and Urban Dynamometer Driving Schedule (UDDS) as examples. Then, the proposed strategy is compared with the fuzzy control strategy and the strategy based on DP. Compared with fuzzy energy management strategy (namely FZY-EMS), the proposed EMS reduces the battery capacity loss and system energy consumption. The results demonstrate the effectiveness of the proposed EMS in improving EV economy.
B. Zhao, Q. Song, and W. Liu, Power characterization of isolated bidirectional dual-active-bridge DC-DC converter with dual-phase-shift control, IEEE Trans. Power Electron, vol. 27, no. 9, pp. 4172–4176, 2012.
C. X. Song, F. Zhou, and F. Xiao, Energy management optimization of Hybrid Energy Storage System (HESS) based on dynamic programming, (in Chinese), J. Jilin Univ. (Eng. Technol. Ed.), vol. 47, no. 1, pp. 8–14, 2017.
D. Z. Yao, C. J. Xie, T. Zeng, and L. Huang, Multi-Fuzzy control based energy management strategy of battery/super-capacitor hybrid energy system of electric vehicles, (in Chinese), Automot. Eng., vol. 41, no. 6, pp. 615–624&640, 2019.
D. Xu, H. Zhou, B. Wang, B. G. Cao, and J. L. Wang, A simplified cascading hybrid power and its control scheme for electric vehicles, (in Chinese), Automot. Eng., vol. 39, no. 12, pp. 1368–1374, 2017.
Y. T. Luo, X. T. Liu, W. Q. Liu, and X. S. Ruan, Design of hybrid power system for prolonging lifespan of lithium-ion battery applied to electric vehicles, (in Chinese), J. South China Univ. Technol. (Nat. Sci. Ed.), vol. 44, no. 3, pp. 51–59, 2016.
M. Ding, G. D. Lin, Z. N. Chen, Y. Q. Luo, and B. Zhao, A control strategy for hybrid energy storage systems, (in Chinese), Proc. CSEE, vol. 32, no. 7, pp. 1–6, 2012.
J. J. Hu, Y. Zheng, Z. H. Hu, and J. Xiao, Parameter matching and control strategies of hybrid energy storage system for pure electric vehicle, (in Chinese), China J. Highway Transp., vol. 31, no. 3, pp. 142–150, 2018.
J. Li, Y. Z. Zhu, L. Ji, and Y. J. Xu, Optimization of fuzzy control strategy for hybrid electric vehicle, (in Chinese), Automot. Eng., vol. 38, no. 1, pp. 10–14&21, 2016.
Y. Li, X. Lu, and N. C. Kar, Rule-based control strategy with novel parameters optimization using NSGA-II for power-split PHEV operation cost minimization, IEEE Trans. Veh. Technol., vol. 63, no. 7, pp. 3051–3061, 2014.
Y. H. Cheng and C. M. Lai, Control strategy optimization for parallel hybrid electric vehicles using a memetic algorithm, Energies, vol. 10, no. 3, p. 305, 2017.
X. S. Hu, N. Murgovski, L. M. Johannesson, and B. Egardt, Comparison of three electrochemical energy buffers applied to a hybrid bus powertrain with simultaneous optimal sizing and energy management, IEEE Trans. Intell. Transport. Syst., vol. 15, no. 3, pp. 1193–1205, 2014.
F. Zhou, C. X. Song, T. W. Liang, and F. Xiao, Parameter matching of on-board hybrid energy storage system using NSGA-II algorithm, (in Chinese), J. Jilin Univ. (Eng. Technol. Ed.), vol. 47, no. 5, pp. 1336–1343, 2017.
Z. Song, H. Hofmann, J. Li, X. Han, X. Zhang, and M. Ouyang, A comparison study of different semi-active hybrid energy storage system topologies for electric vehicles, J. Power Sources, vol. 274, pp. 400–411, 2015.
Z. Chen, R. Xiong, and J. Cao, Particle swarm optimization-based optimal power management of plug-in hybrid electric vehicles considering uncertain driving conditions, Energy, vol. 96, pp. 197–208, 2016.
S. B. Xie, K. K. Zhang, Q. K. Zhang, and H. R. Luo, Study on energy management strategy for parallel plug-in hybrid electric vehicles considering battery electric-thermal-depth-of-discharge, (in Chinese), Automot. Eng., vol. 43, no. 6, pp. 791–798&832, 2021.
P. Zhang, F. Yan, and C. Du, A comprehensive analysis of energy management strategies for hybrid electric vehicles based on bibliometrics, Renew. Sust. Energ. Rev., vol. 48, pp. 88–104, 2015.
L. Zhang, X. Hu, Z. Wang, F. Sun, J. Deng, and D. G. Dorrell, Multiobjective optimal sizing of hybrid energy storage system for electric vehicles, IEEE Trans. Veh. Technol., vol. 67, no. 2, pp. 1027–1035, 2018.
X. Wu, X. Yan, Y. Wang, B. X. Huang, and Z. C. Liu, Study on DC resistance characteristics of ternary lithium batteries, (in Chinese), Chin. J. Power Sources, vol. 43, no. 4, pp. 568–570&684, 2019.
L. Zhang, X. Hu, Z. Wang, J. Ruan, C. Ma, Z. Song, D. G. Dorrell, and M. G. Pecht, Hybrid electrochemical energy storage systems: An overview for smart grid and electrified vehicle applications, Renew. Sust. Energ. Rev., vol. 139, p. 110581, 2021.
Q. Wang, Z. Wang, L. Zhang, P. Liu, and L. Zhou, A battery capacity estimation framework combining hybrid deep neural network and regional capacity calculation based on real-world operating data, IEEE Trans. Ind. Electron., vol. 70, no. 8, pp. 8499–8508, 2023.
D. T. Qin, Z. Y. Peng, Y. G. Liu, Z. H. Duan, and Y. Yang, Dynamic energy management strategy of HEV based on driving pattern recognition, (in Chinese), China Mechan. Eng., no. 11, pp. 1550–1555, 2014.
M. Sharafi, and T. Y. El Mekkawy, Multi-objective optimal design of hybrid renewable energy systems using PSO-simulation based approach, Renew. Energ., vol. 68, pp. 67–79, 2014.
L. H. Xi, X. Zhang, C. Geng, and Q. C. Xue, Energy management strategy optimization of extended-range electric vehicle based on dynamic programming, (in Chinese), J. Traffic Transp. Eng., vol. 18, no. 3, pp. 148–156, 2018.
S. B. Xie, T. Liu, H. L. Li, and Z. K. Xin, A study on predictive energy management strategy for a plug-in hybrid electric bus based on Markov Chain, (in Chinese), Automot. Eng., vol. 40, no. 8, pp. 871–877&911, 2018.
436
Views
59
Downloads
5
Crossref
3
Web of Science
5
Scopus
0
CSCD
Altmetrics
The articles published in this open access journal are distributed under the terms of theCreative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).