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基于燃料电池的复合电源式装载机分层控制

张志文 杜文杰 梁君飞 张艳岗 武雅文

张志文, 杜文杰, 梁君飞, 等 . 基于燃料电池的复合电源式装载机分层控制[J]. 北京航空航天大学学报, 2022, 48(11): 2165-2176. doi: 10.13700/j.bh.1001-5965.2021.0099
引用本文: 张志文, 杜文杰, 梁君飞, 等 . 基于燃料电池的复合电源式装载机分层控制[J]. 北京航空航天大学学报, 2022, 48(11): 2165-2176. doi: 10.13700/j.bh.1001-5965.2021.0099
ZHANG Zhiwen, DU Wenjie, LIANG Junfei, et al. Layered control of hybrid power loader based on fuel cell[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(11): 2165-2176. doi: 10.13700/j.bh.1001-5965.2021.0099(in Chinese)
Citation: ZHANG Zhiwen, DU Wenjie, LIANG Junfei, et al. Layered control of hybrid power loader based on fuel cell[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(11): 2165-2176. doi: 10.13700/j.bh.1001-5965.2021.0099(in Chinese)

基于燃料电池的复合电源式装载机分层控制

doi: 10.13700/j.bh.1001-5965.2021.0099
基金项目: 

国家自然科学基金 51605447

山西省基础研究计划 201901D211208

山西省高等学校科技创新项目 2019L0605

详细信息
    通讯作者:

    张志文, E-mail: zhzhw666@nuc.edu.cn

  • 中图分类号: U469.72+2

Layered control of hybrid power loader based on fuel cell

Funds: 

National Natural Science Foundation of China 51605447

Applied Basic Research Programs of Shanxi 201901D211208

Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi 2019L0605

More Information
  • 摘要:

    装载机能耗高、排放差, 研究装载机新能源技术具有重要意义。结合装载机工况特性提出了燃料电池与超级电容联合驱动的电源系统, 围绕复杂工况下燃料电池和超级电容系统动态模型的实时工况数据进行自适应能量管理策略研究。设计了复合电源拓扑结构与动力传动方案, 建立装载机复杂工况下系统多状态模型, 基于Haar小波理论对整车系统进行功率分流, 提出模糊逻辑能量管理策略动态平衡需求功率中的低频分量, 采用粒子群算法对控制系统进行优化。仿真结果显示:载荷功率经过最优阈值3层Haar小波处理后, 功率变化大幅度减缓, 有效提升燃料电池系统的寿命;模糊逻辑控制器输出的燃料电池功率曲线变化光滑, 超级电容SOC值处于设定区域内, 提高复合电源系统的综合效率;经过粒子群算法优化控制器后, 燃料电池输出平均功率同比下降约5%, 超级电容SOC值在约0.6达到动态平衡状态, 改善了装载机的动态响应和稳定性。

     

  • 图 1  复合电源装载机动力传动方案

    Figure 1.  Power transmission scheme of hybrid power loader

    图 2  燃料电池极化曲线

    Figure 2.  Polarization curves of fuel cell

    图 3  燃料电池模型结构

    Figure 3.  Structure of fuel cell model

    图 4  超级电容等效电路模型

    Figure 4.  Equivalent circuit model of super capacitor

    图 5  超级电容模型结构

    Figure 5.  Structure of super capacitor model

    图 6  kW电动机模型结构65 kW/125

    Figure 6.  Structure of 65 kW/125 kW motor model

    图 7  装载机工作示意图

    Figure 7.  Working diagram of loader

    图 8  整车控制系统结构框图

    Figure 8.  Structure block diagram of vehicle control system

    图 9  Haar小波信号处理

    Figure 9.  Haar wavelet signal processing

    图 10  复合电源系统模糊逻辑控制结构

    Figure 10.  Fuzzy logic control structure of composite power supply system

    图 11  模糊逻辑控制器

    Figure 11.  Fuzzy logic controller

    图 12  Pdem、SOC、PFC对应的调节规则

    Figure 12.  Regulation rules of Pdem, SOC and PFC

    图 13  三层Haar小波处理载荷谱曲线

    Figure 13.  Three-layer wavelet processing of load spectrum curves

    图 14  动力系统负载功率曲线

    Figure 14.  Load power curves of power system

    图 15  液压系统负载功率曲线

    Figure 15.  Load power curves of hydraulic system

    图 16  复合电源系统仿真模型

    Figure 16.  Simulation model of composite power supply system

    图 17  超级电容SOC变化曲线

    Figure 17.  SOC curves of super capacitor

    图 18  燃料电池输出功率曲线

    Figure 18.  Output power curves of fuel cell

    图 19  PSO算法优化流程

    Figure 19.  Flow chart of particle swarm optimization algorithm

    图 20  优化前后的模糊逻辑规则观察器(部分)

    Figure 20.  Rule observer before and after fuzzy logic controller optimization (part)

    图 21  优化后燃料电池输出功率变化曲线

    Figure 21.  Output power curves of optimized fuel cell

    图 22  优化后超级电容输出功率变化曲线

    Figure 22.  Output power curves of optimized super capacitor

    图 23  优化后超级电容SOC变化曲线

    Figure 23.  SOC curves of optimized supercapacitor

  • [1] LI T Y, HUANG L T, LIU H Y. Energy management and economic analysis for a fuel cell supercapacitor excavator[J]. Energy, 2019, 172: 840-851. doi: 10.1016/j.energy.2019.02.016
    [2] DE MIRANDA P E V, CARREIRA E S, ICARDI U A, et al. Brazilian hybrid electric-hydrogen fuel cell bus improved on-board energy management system[J]. International Journal of Hydrogen Energy, 2017, 42(19): 13949-13959. doi: 10.1016/j.ijhydene.2016.12.155
    [3] ZHANG X, MI C, 等. 车辆能量管理: 建模、控制与优化[M]. 张希, 米春亭, 译. 北京: 机械工业出版社, 2013.

    ZHANG X, MI C, et al. Vehicle energy management: Modeling, control and optimization[M]. ZHANG X, MI C T, translated. Beijing: China Machine Press, 2013(in Chinese).
    [4] LI T Y, LIU H Y, WANG H, et al. Hierarchical predictive control-based economic energy management for fuel cell hybrid construction vehicles[J]. Energy, 2020, 198: 117327. doi: 10.1016/j.energy.2020.117327
    [5] MUNOZ P M, CORREA G, GAUDIANO M E, et al. Energy management control design for fuel cell hybrid electric vehicles using neural networks[J]. International Journal of Hydrogen Energy, 2017, 42(48): 28932-28944. doi: 10.1016/j.ijhydene.2017.09.169
    [6] SNOUSSI J, BEN ELGHALI S, BENBOUZID M, et al. Auto-adaptive filtering-based energy management strategy for fuel cell hybrid electric vehicles[J]. Energies, 2018, 11(8): 1-20.
    [7] IBRAHIM M, JEMEI S, WIMMER G, et al. Non cinear autoregressive neural network in an energy management strategy for battery lultra-capacitor hybrid electrical vehicles[J]. Electric Power Systems Research, 2016, 136: 262-269. doi: 10.1016/j.epsr.2016.03.005
    [8] ZHANG R D, TAO J L, ZHOU H Y. Fuzzy optimal energy management for fuel cell and super capacitor systems using neural network based driving pattern recognition[J]. IEEE Transactions on Fuzzy Systems, 2019, 27(1): 45-57. doi: 10.1109/TFUZZ.2018.2856086
    [9] HE D, SHI Y, SONG X. Weight-free multi-objective predictive cruise control of autonomous vehicles in integrated perturbation analysis and sequential quadratic programming optimization framework[J]. Dynamic System Measurement Control, 141, 9: 91015.
    [10] 杜文杰. 基于燃料电池复合双电源装载机系统功率控制研究[D]. 太原: 中北大学, 2020.

    DU W J. Research on power control of fuel cell compound dual energy source system[D]. Taiyuan: North University of China, 2020(in Chinese).
    [11] 吕沁阳, 滕腾, 张宝迪, 等. 增程式燃料电池车经济性与耐久性优化控制策略[J]. 哈尔滨工业大学学报, 2021, 53(7): 126-133. https://www.cnki.com.cn/Article/CJFDTOTAL-HEBX202107015.htm

    LV Q Y, TENG T, ZHANG B D, et al. Optimal control strategy for economy and durability of extended range fuel cell vehicle[J]. Journal of Harbin Institute of Technology, 2021, 53(7): 126-133(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-HEBX202107015.htm
    [12] 胡尊严. 车用燃料电池系统耐久性建模与状态估计研究[D]. 北京: 清华大学, 2019: 3-7.

    HU Z Y. Durability modeling and state estimation for vehicular fuel cell system[D]. Beijing: Tsinghua University, 2019: 3-7(in Chinese).
    [13] SULAIMAN N, HANNAN M A, MOHAMED A, et al. Optimization of energy management system for fuel-cell hybrid electric vehicles: Issues and recommendations[J]. Applied Energy, 2018, 228: 2061-2079. doi: 10.1016/j.apenergy.2018.07.087
    [14] 崔宁, 秦四成, 赵丁选. 液压挖掘机并联混合节能动力系统多目标优化控制策略[J]. 西安交通大学学报, 2016, 50(6): 116-121. https://www.cnki.com.cn/Article/CJFDTOTAL-XAJT201606018.htm

    CUI N, QIN S C, ZHAO D X. A multi object optimal control strategy for a parallel hybrid power system in hydraulic excavators[J]. Journal of Xi'an Jiaotong University, 2016, 50(6): 116-121(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-XAJT201606018.htm
    [15] SONG K, DING Y H, HU X, et al. Degradation adaptive energy management strategy using fuel cell state-of-health for fuel economy improvement of hybrid electric vehicle[J]. Applied Energy, 2021, 285: 1-12.
    [16] LI T Y, LIU H Y, WANG H, et al. Multiobjective optimal predictive energy management for fuel cell/battery hybrid construction vehicles[J]. IEEE Access, 2020, 8: 25927-25937. doi: 10.1109/ACCESS.2020.2969494
    [17] FAISAL M, HANNAN M A, KER P J, et al. Particle swarm optimised fuzzy controller for charging-discharging and scheduling of battery energy storage system in MG applications[J]. Energy Reports, 2020, 6: 215-228.
    [18] AFZAL A, RAMIS M K. Multi-objective optimization of thermal performance in battery system using genetic and particle swarm algorithm combined with fuzzy logics[J]. Journal of Energy Storage, 2020, 32: 101815.
    [19] LI J, ZHOU Q, WILLIAMS H, et al. Back-to-back competitive learning mechanism for fuzzy logic based supervisory control system of hybrid electric vehicles[J]. IEEE Transactions on Industrial Electronics, 2020, 67(10): 8900-8909.
    [20] 吕柏权, 张静静, 李占培, 等. 基于变换函数与填充函数的模糊粒子群优化算法[J]. 自动化学报, 2018, 44(1): 74-86. https://www.cnki.com.cn/Article/CJFDTOTAL-MOTO201801007.htm

    LV B Q, ZHANG J J, LI Z P, et al. Fuzzy partical swarm optimization based on filled function and transformation function[J]. Acta Automatica Sinica, 2018, 44(1): 74-86(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-MOTO201801007.htm
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出版历程
  • 收稿日期:  2021-03-02
  • 录用日期:  2021-08-23
  • 网络出版日期:  2021-09-28
  • 整期出版日期:  2022-11-20

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