Power allocation strategy for fuel cell distributed drive electric tractor based on adaptive multi-resolution analysis theory

被引:5
作者
Li, Xian-zhe [1 ,2 ]
Zhang, Ming-zhu [1 ]
Yan, Xiang-hai [1 ,2 ,4 ]
Liu, Meng-nan [2 ,3 ]
Xu, Li-you [1 ,2 ,5 ]
机构
[1] Henan Univ Sci & Technol, Coll Vehicle & Traff Engn, Luoyang 471003, Peoples R China
[2] State Key Lab Intelligent Agr Power Equipment, 39 Xiyuan Rd, Luoyang 471039, Peoples R China
[3] YTO Grp Corp R&D Ctr, Luoyang 471039, Peoples R China
[4] Henan Univ Sci & Technol, Adv Mfg Mech Equipment Henan Prov Collaborat Innov, Luoyang 471003, Peoples R China
[5] Henan Univ Sci & Technol, 48 Xiyuan Rd, Luoyang 471003, Peoples R China
基金
国家重点研发计划;
关键词
Fuel cell; Tractor; Distributed drive system; Power allocation; Adaptive multi-resolution analysis; Experimentation; ENERGY MANAGEMENT STRATEGY;
D O I
10.1016/j.energy.2023.129350
中图分类号
O414.1 [热力学];
学科分类号
摘要
Fuel cell distributed drive electric tractor (FCDET) provided a novel pathway for the development of green agricultural machinery technology. However, FCDET faced problems such as low traction efficiency, short endurance, and high hydrogen consumption. Relevant studies have shown that reasonable and effective power allocation strategy can improve the efficiency and reduce the energy consumption of fuel cell systems. In this paper, a drive power allocation strategy based on adaptive multi-resolution analysis theory (AMRA) was proposed. The strategy could realize effective decoupling between various energy sources, reduce the problems of frequent start-stop and large power fluctuation for fuel cells. We started with an equivalent circuit model of the fuel cell system, a total efficiency solution model, an energy dissipation model, and a drive motor response model. The first-time reconstruction strategy was based on Tunable Q-factor Wavelet Transform (TQWT) to obtain a subsequence that responds to the oscillatory characteristics of the power signal. The second-time reconstruction strategy took the low-frequency subsequence through Variational Mode Decomposition (VMD) into a number of discrete sub-signals with special sparse properties. Meanwhile, the Sparrow Search Algorithm (SSA) was used to obtain the optimal combined values of the modal decomposition layers and the quadratic penalty factor in the VMD on real time. Finally, the second-time decomposed subsequences and sub-signals were reconstructed according to the frequency characteristics, and the reconstructed power signals were redistributed among the individual energy sources. In order to validate the proposed power allocation strategy, we used the ET504-H prototype as a research object. The power information of plowing and transportation operating con-ditions was collected in Mengjin test base of China YTO Group. The MATLAB/Simulink-PXI joint simulation platform was set up and the driving motor bench test was carried out in the New Energy Key Laboratory of Henan Province. The results show that the AMRA-based FCDET drive power allocation strategy can effectively improve the energy utilization of the fuel cell system and the economy of the whole tractor operating unit. Compared to the power-following strategy under plowing and transportation conditions, the average efficiency of the fuel cell system was improved by 8.3 % and 3.3 %, the equivalent hydrogen consumption was reduced by 35.6 % and 43.89 %, respectively. The average efficiency of the drive motor was improved by 2.06 % and 2.08 %, the total energy consumption was reduced by 3.73 % and 2.6 %, respectively. This study can provide a theoretical foundation and a novel technical approach for the development of FCDET control system.
引用
收藏
页数:24
相关论文
共 40 条
  • [1] The effects of driving patterns and PEM fuel cell degradation on the lifecycle assessment of hydrogen fuel cell vehicles
    Ahmadi, Pouria
    Torabi, Seyed Hosein
    Afsaneh, Hadi
    Sadegheih, Yousef
    Ganjehsarabi, Hadi
    Ashjaee, Mehdi
    [J]. INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2020, 45 (05) : 3595 - 3608
  • [2] Improving fuel economy and performance of a fuel-cell hybrid electric vehicle (fuel-cell, battery, and ultra-capacitor) using optimized energy management strategy
    Ahmadi, Saman
    Bathaee, S. M. T.
    Hosseinpour, Amir H.
    [J]. ENERGY CONVERSION AND MANAGEMENT, 2018, 160 : 74 - 84
  • [3] Prospects and impediments for hydrogen and fuel cell vehicles in the transport sector
    Ajanovic, A.
    Haas, R.
    [J]. INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2021, 46 (16) : 10049 - 10058
  • [4] Ajmani P., 2023, Advances in Environmental Engineering and Green Technologies, P124
  • [5] An overview: Current progress on hydrogen fuel cell vehicles
    Aminudin, M. A.
    Kamarudin, S. K.
    Lim, B. H.
    Majilan, E. H.
    Masdar, M. S.
    Shaari, N.
    [J]. INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2023, 48 (11) : 4371 - 4388
  • [6] Traction Performance Evaluation of the Electric All-Wheel-Drive Tractor
    Baek, Seung-Yun
    Baek, Seung-Min
    Jeon, Hyeon-Ho
    Kim, Wan-Soo
    Kim, Yeon-Soo
    Sim, Tae-Yong
    Choi, Kyu-Hong
    Hong, Soon-Jung
    Kim, Hyunggun
    Kim, Yong-Joo
    [J]. SENSORS, 2022, 22 (03)
  • [7] Basma H, 2022, Fuel cell electric tractor-trailers: technology overview and fuel economy
  • [8] Basma H, 2021, Battery electric tractor-trailers in the European Union: a vehicle technology analysis
  • [9] Improving the Fuel Economy and Battery Lifespan in Fuel Cell/Renewable Hybrid Power Systems Using the Power-Following Control of the Fueling Regulators
    Bizon, Nicu
    Oproescu, Mihai
    Thounthong, Phatiphat
    Varlam, Mihai
    Carcadea, Elena
    Culcer, Mihai
    Iliescu, Mariana
    Raboaca, Maria Simona
    Sorlei, Ioan Sorin
    [J]. APPLIED SCIENCES-BASEL, 2020, 10 (22): : 1 - 23
  • [10] A spatially adaptive multi-resolution generative algorithm: Application to simulating flood wave propagation
    Carreau, Julie
    Naveau, Philippe
    [J]. WEATHER AND CLIMATE EXTREMES, 2023, 41