Energy management strategy of hydrogen fuel cell hybrid power tractor based on wavelet stratified decoupling
XU Liyou1, XU Wenxiang1, LIU Mengnan1,2, ZHANG Shuai1
(1.College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang, Henan 471000, China; 2. State Key Laboratory of Power System of Tractor, Henan University of Science and Technology, Luoyang, Henan 471000, China)
Abstract:To solve the problems that single energy system could not give full play to its advantages and could not well satisfy the high density of random load spectrum during the operation of tractor,the composite energy system of electric tractor was designed based on parallel connection of hydrogen fuel cell, power battery and supercapacitor. The hierarchical decoupling control energy management strategy based on Haar wavelet and logical threshold rules was designed to realize the hierarchical decoupling of high frequency signal, sub-high frequency signal and steady state signal, and the power signal was distributed after decoupling. The simulation results show that compared with the power following control strategy and the fuzzy control strategy, the average efficiency of the hydrogen fuel cell based on the layered decoupling control strategy is respectively improved by 2.85% and 1.21%, and the vehicle equivalent hydrogen consumption is respectively reduced by 16.11% and 6.88% in the experimental cycle. The proposed control strategy can improve the vehicle economy on the promise of meeting the power demand of vehicle load, and the fuel cell can output power in efficient and stable working state.
YUKO U, JUN Y, KAZUNOBU S, et al. Study on the development of the electric tractor: specifications and traveling and tilling performance of a prototype tractor[J]. Engineering in Agriculture, Environment and Food, 2013,6(4):160-164.
[2]
LIU M, LI Y, XU L, et al. General modeling and energy management optimization for the fuel cell electric tractor with mechanical shunt type[J]. Computers and Electronics in Agriculture, 2023,213:1-14.
[3]
刘中峰.氢燃料电池拖拉机能量管理策略的研究[J].当代农机,2021(3):57-58.
LIU Z F. Research on energy management strategy of hydrogen fuel cell tractor[J]. Contemporary Farm Machinery, 2021(3):57-58.(in Chinese)
[4]
ZHANG C,LIU Z,ZHOU W,et al. Dynamic performance of a high-temperature PEM fuel cell:an experimental study[J]. Energy,2015,90:1-7.
WANG T, HE Y. Multi-objective energy management strategy of fuel cell vehicle based on nonlinear programming and XGBoost[J]. Journal of Jiangsu University(Natural Science Edition), 2023,44(2):142-150. (in Chinese)
WANG Q, LI D G,MIAO H C. Research on energy management strategy of fuel cell vehicle based on fuzzy logic control[J]. Automotive Engineering, 2019,41(12) :1347-1355.(in Chinese)
[7]
HE T,LU Z W,WANG X, et al. A length ratio based neural network energy management strategy for online control of plug-in hybrid electric city bus[J]. Applied Energy, 2016,177:71-80.
[8]
LI M, WANG L, WANG Y J, et al. Sizing optimization and energy management strategy for hybrid energy storage system using multi-objective optimization and random forests[J]. IEEE Transactions on Power Electronics, 2021,36(10):11421-11430.
[9]
LI S Q, HE H W, ZHAO P F. Energy management for hybrid energy storage system in electric vehicle: a cyber-physical system perspective[J]. Energy, 2021,230(4):1-10.
[10]
HAN Y, LI Q, WANG T H, et al. Multisource coordination energy management strategy based on SOC consensus for a PEMFC-battery-supercapacitor hybrid tramway[J]. IEEE Transactions on Vehicular Technology, 2018,67(1):296-305.
[11]
WU J D, HE H W, PENG J K, et al. Continuous reinforcement learning of energy management with deep Q network for a power split hybrid electric bus[J]. Applied Energy, 2018,222:799-811.
XU L Y, LIU E Z, LIU M N, et al. Energy management strategy of fuel cell and storage battery hybrid electric tractor[J]. Journal of Henan University of Science and Technology(Natural Science),2019,40(2):80-86.(in Chinese)
LIU M N, ZHOU Z L, XU L Y, et al. Electric tractor energy system and management strategy research based on load power spectral density[J]. Transactions of the Chinese Society for Agricultural Machinery,2018,49(2):358-366.(in Chinese)
[14]
SHIH-KUEN C, TSOMG-JUU L, JIANN-FUH C, et al. Novel high step-up DC/DC converter for fuel cell energy conversion system[J].IEEE Transactions on Industrial Electronics,2010,57(6):2007-2017.
[15]
HASELTALAB A, NEGENBORN R R. Model predictive maneuvering control and energy management for all-electric autonomous ships[J]. Applied Energy, 2019,251:1-27.
[16]
FALKOWSKI B J. Forward and inverse transformations between Haar wavelet and arithmetic functions[J]. Electronics Letters, 1998,34(11):1084-1085.
WANG Y C, CAI Z J, ZHANG Y L. Characteristic analysis of transformer winding amplitude frequency response curve based on Haar wavelet transform[J].Journal of Chinese Agricultural Mechanization,2014,35(1):103-106.(in Chinese)
LIU M N, XU L Y, ZHOU Z L, et al. Establishment of extended range electric tractor and its rotary cultivator′s simulative platforms[J]. Chinese Mechanical Engineering, 2016(3):413-419.(in Chinese)
XU L Y, ZHAO Y R, ZHAO X P, et al. Design and test of multifunctionai test system for electric tractor[J]. Transactions of the Chinese Society for Agricultural Machinery, 2020,51(1):355-363.(in Chinese)
LI Y Y, LIU M N, XU L Y, et al. Control strategy of series hybrid tractor based on nonlinear program genetic algorithm[J]. Journal of Jiangsu University(Natural Science Edition), 2023,44(2):166-172,185. (in Chinese)
[21]
XU W X, LIU M N, XU L Y. Simulation of multi-power composite electric tractor based on power fluctuation ratio[J]. Journal of Physics: Conference Series,DOI:10.1088/1742-6596/2125/1/012007.