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船用大型压气机质量流量分区域建模方法

沈浩生 张均东 杨柏丞 贾宝柱 甘辉兵

沈浩生, 张均东, 杨柏丞, 贾宝柱, 甘辉兵. 船用大型压气机质量流量分区域建模方法[J]. 交通运输工程学报, 2020, 20(6): 180-196. doi: 10.19818/j.cnki.1671-1637.2020.06.016
引用本文: 沈浩生, 张均东, 杨柏丞, 贾宝柱, 甘辉兵. 船用大型压气机质量流量分区域建模方法[J]. 交通运输工程学报, 2020, 20(6): 180-196. doi: 10.19818/j.cnki.1671-1637.2020.06.016
SHEN Hao-sheng, ZHANG Jun-dong, YANG Bo-cheng, JIA Bao-zhu, GAN Hui-bing. Zonal modeling method for mass flow of large-scale marine compressor[J]. Journal of Traffic and Transportation Engineering, 2020, 20(6): 180-196. doi: 10.19818/j.cnki.1671-1637.2020.06.016
Citation: SHEN Hao-sheng, ZHANG Jun-dong, YANG Bo-cheng, JIA Bao-zhu, GAN Hui-bing. Zonal modeling method for mass flow of large-scale marine compressor[J]. Journal of Traffic and Transportation Engineering, 2020, 20(6): 180-196. doi: 10.19818/j.cnki.1671-1637.2020.06.016

船用大型压气机质量流量分区域建模方法

doi: 10.19818/j.cnki.1671-1637.2020.06.016
基金项目: 

国家自然科学基金项目 52071090

国家自然科学基金项目 51479017

辽宁省自然科学基金项目 201602071

中央高校基本科研业务费专项资金项目 3132019315

详细信息
    作者简介:

    沈浩生(1989-), 男, 黑龙江海林人, 大连海事大学工学博士研究生, 从事轮机系统仿真研究

    张均东(1967-), 男, 浙江东阳人, 大连海事大学教授, 工学博士

  • 中图分类号: U664.121.1

Zonal modeling method for mass flow of large-scale marine compressor

Funds: 

National Natural Science Foundation of China 52071090

National Natural Science Foundation of China 51479017

Natural Science Foundation of Liaoning Province 201602071

Fundamental Research Funds for the Central Universities 3132019315

More Information
  • 摘要: 针对查表法外推能力不可靠以及采用单一曲线拟合法时在压气机不同工作区域的预测与外推精度不一致的问题, 提出了一种船用大型压气机质量流量分区域建模方法; 通过定义区域划分函数, 将压气机整个工作区域划分为设计工况区、低转速区、高转速区与低压比区, 通过对比与分析经典的和近年提出的压气机质量流量数学模型的预测和外推精度, 为每个区域选择精度最高的数学模型; 为防止在动态仿真过程中当压气机运行点由其他区进入低压比区时可能出现的不连续间断点, 应用一种曲线融合方法来保证等转速线的平滑过渡; 为验证所提出的建模方法的正确性与有效性, 将其应用于一台船用大型低速二冲程柴油机仿真模型中开展稳态与瞬态仿真试验。研究结果表明: 相比查表法, 提出的建模方法可有效提升主机仿真模型增压器转速的稳态预测精度, 平均绝对百分误差由3.54%下降至0.61%, 在改变主机转速与负载这2种瞬态工况下, 压气机的运行点可平稳、连续地由设计工况区过渡至非设计工况区; 提出的建模方法既能准确预测压气机设计工况区内的已有样本数据点, 又能合理、稳健地外推至非设计工况区, 既可直接应用于涡轮增压发动机的动态仿真研究中, 也可用于离线生成压气机在全工况范围内的性能图谱, 进而应用于商业发动机性能仿真软件中。

     

  • 图  1  压气机性能图谱

    Figure  1.  Compressor performance map

    图  2  压气机叶片进出口速度三角形

    Figure  2.  Velocity triangles at inlet and outlet of compressor impeller

    图  3  实际比焓变与质量流量线性拟合结果

    Figure  3.  Linear fitting results of actual specific enthalpy change and mass flow

    图  4  A270-L59型船用大型压气机叶片直径估算结果

    Figure  4.  Estimation result of impeller diameter of A270-L59 large-scale marine compressor

    图  5  Leufvén-Llamas椭圆模型建模思想

    Figure  5.  Modeling idea of Leufvén-Llamas ellipse model

    图  6  各压气机质量流量模型在设计工况区内的预测结果(A270-L59)

    Figure  6.  Prediction results of various compressor mass flow models in design operating zone (A270-L59)

    图  7  各压气机质量流量模型在设计工况区内的预测结果(TCA88-25070)

    Figure  7.  Prediction results of various compressor mass flow models in design operating zone (TCA88-25070)

    图  8  阻塞压比和阻塞流量测量值与预测值(TCA88-25070)

    Figure  8.  Measured and predicted choking pressures and choking flows (TCA88-25070)

    图  9  各压气机质量流量模型的LS区外推结果(A270-L59)

    Figure  9.  Extrapolation results of LS zone with various compressor mass flow models (A270-L59)

    图  10  各压气机质量流量模型的LS区外推结果(TCA88-25070)

    Figure  10.  Extrapolation results of LS zone with various compressor mass flow models (TCA88-25070)

    图  11  各压气机质量流量模型的HS区外推结果(A270-L59)

    Figure  11.  Extrapolation results of HS zone with various compressor mass flow models (A270-L59)

    图  12  各压气机质量流量模型的HS区外推结果(TCA88-25070)

    Figure  12.  Extrapolation results of HS zone with various compressor mass flow models (TCA88-25070)

    图  13  区域划分方法

    Figure  13.  Zone division method

    图  14  喘振区与LPR区边界线上压比与质量流量测量与拟合结果

    Figure  14.  Measured and fitting results of pressure ratios and mass flows at border of surging and LPR zones

    图  15  LPR区融合函数

    Figure  15.  Blending function for LPR zone

    图  16  压气机工作特性曲线

    Figure  16.  Compressor operating characteristic curves

    图  17  压气机质量流量分区域建模方法预测与外推结果

    Figure  17.  Prediction and extrapolation results of zonal modeling method for mass flow of compressor

    图  18  主机转速改变时压气机的运行点轨迹

    Figure  18.  Trajectory of compressor operating points when main engine speed changes

    图  19  主机负载改变时压气机的运行点轨迹

    Figure  19.  Trajectory of compressor operating points when main engine loading changes

    表  1  两类压气机叶片直径估算方法的预测误差

    Table  1.   Prediction errors of two estimation methods for compressor impeller diameter

    型号 实际值/m 文献[19]中的方法 本文方法
    估计值/m 误差/% 估计值/m 误差/%
    TCA88-25070 0.893 0 0.836 2 -6.36 0.886 4 -0.74
    TCA55 0.500 0 0.468 2 -6.36 0.496 7 -0.66
    下载: 导出CSV

    表  2  A270-L59与TCA88-25070型船用大型压气机主要技术参数

    Table  2.   Main technical parameters of A270-L59 and TCA88-25070 large-scale marine compressors

    型号 A270-L59 TCA88-25070
    叶片直径/m 0.59 0.893
    最大流量/(m3·s-1) 23 60
    最大转速/(r·min-1) 16 800 11 763
    样本点数 289 54
    下载: 导出CSV

    表  3  各压气机质量流量模型在设计工况区内的预测精度(A270-L59)

    Table  3.   Prediction accuracies of various compressor mass flow models in design operating zone (A270-L59)

    模型名称 Rc2 E/% δ5%/% δ10%/%
    管聪模型 0.999 6 0.56 100.00 100.00
    Karlson-Ⅰ模型 0.998 9 1.00 98.96 99.65
    Karlson-Ⅱ模型 0.998 9 0.91 99.31 100.00
    Malkhede模型 0.990 5 3.20 82.00 97.92
    Kolmanovsky模型 0.989 0 3.39 82.00 92.73
    Müller-Ⅰ模型 0.986 4 2.13 89.27 98.96
    Müller-Ⅱ模型 0.971 4 3.52 77.51 95.85
    Leufvén-Llamas椭圆模型 0.913 3 6.81 77.85 84.78
    下载: 导出CSV

    表  4  各压气机质量流量模型在设计工况区内的预测精度(TCA88-25070)

    Table  4.   Prediction accuracies of various compressor mass flow models in design operating zone (TCA88-25070)

    模型名称 Rc2 E/% δ5%/% δ10%/%
    管聪模型 0.992 6 2.28 88.89 98.15
    Karlson-Ⅰ模型 0.987 0 2.96 85.19 96.30
    Karlson-Ⅱ模型 0.991 6 2.53 90.74 94.44
    Malkhede模型 0.970 3 5.39 66.67 90.74
    Kolmanovsky模型 0.961 8 6.76 57.41 75.93
    Müller-Ⅰ模型 0.972 2 4.37 66.67 90.74
    Müller-Ⅱ模型 0.945 6 6.28 51.85 83.33
    Leufvén-Llamas椭圆模型 0.919 1 7.61 64.81 70.37
    下载: 导出CSV

    表  5  不同转速下Leufvén-Llamas椭圆模型与Karlson-Ⅰ模型阻塞流量的预测精度

    Table  5.   Prediction accuracies of choking flows by Leufvén-Llamas ellipse model and Karlson-Ⅰ model at different rotational speeds

    模型名称 不同叶梢圆周速度下(m·s-1)的相对误差/%
    550 525 500 475 450 400 350 300 250
    Leufvén-Llamas椭圆模型 1.08 0.29 1.07 0.55 0.38 1.07 0.92 0.85 0.57
    Karlson-Ⅰ模型 0.53 1.66 1.64 1.90 2.00 0.31 1.88 3.04 1.30
    下载: 导出CSV

    表  6  各压气机质量流量模型的LS区外推精度(A270-L59)

    Table  6.   Extrapolation accuracies of LS zone with various compressor mass flow models (A270-L59)

    模型名称 管聪模型 Karlson-Ⅰ模型 Karlson-Ⅱ模型 Kolmanovsky模型
    E/% 2.53 5.53 2.97 16.34
    模型名称 Malkhede模型 Leufvén-Llamas椭圆模型 Müller-Ⅰ模型 Müller-Ⅱ模型
    E/% 12.49 38.53 1.60 3.07
    下载: 导出CSV

    表  7  各压气机质量流量模型的LS区外推精度(TCA88-25070)

    Table  7.   Extrapolation accuracies of LS zone with various compressor mass flow models (TCA88-25070)

    模型名称 管聪模型 Karlson-Ⅰ模型 Karlson-Ⅰ模型 Kolmanovsky模型
    E/% 5.45 14.06 16.08 44.41
    模型名称 Malkhede模型 Leufvén-Llamas椭圆模型 Müller-Ⅰ模型 Müller-Ⅱ模型
    E/% 13.77 23.36 3.51 8.90
    下载: 导出CSV

    表  8  各压气机质量流量模型的HS区外推精度(A270-L59)

    Table  8.   Extrapolation accuracies of HS zone with various compressor mass flow models (A270-L59)

    模型名称 管聪模型 Karlson-Ⅰ模型 Karlson-Ⅱ模型 Kolmanovsky模型
    E/% 28.73 2.57 1.01 7.68
    模型名称 Malkhede模型 Leufvén-Llamas椭圆模型 Müller-Ⅰ模型 Müller-Ⅱ模型
    E/% 4.73 32.47 5.76 6.94
    下载: 导出CSV

    表  9  各压气机质量流量模型的HS区外推精度(TCA88-25070)

    Table  9.   Extrapolation accuracies of HS zone with various compressor mass flow models (TCA88-25070)

    模型名称 管聪模型 Karlson-Ⅰ模型 Karlson-Ⅱ模型 Kolmanovsky模型
    E/% 17.58 4.97 2.28 7.85
    模型名称 Malkhede模型 Leufvén-Llamas椭圆模型 Müller-Ⅰ模型 Müller-Ⅱ模型
    E/% 5.58 40.43 5.16 8.47
    下载: 导出CSV

    表  10  各稳态负荷条件下增压器转速预测结果对比

    Table  10.   Comparison of prediction results for turbocharger rotational speed at various steady loading conditions

    方法名称 不同稳态负荷(%)下的相对误差/% E/%
    15 25 50 75 80 100
    查表法[31] 13.250 -2.43 -0.98 -1.14 -2.08 -1.34 3.54
    分区域建模法 -0.043 -0.55 1.69 0.14 0.74 0.49 0.61
    下载: 导出CSV
  • [1] SONG Kang, UPADHYAY D, XIE Hui. A physics-based turbocharger model for automotive diesel engine control application[J]. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 2019, 233(7): 1667-1686. doi: 10.1177/0954407018770569
    [2] TABURRI M, CHIARA F, CANOVA M, et al. A model-based methodology to predict the compressor behavior for the simulation of turbocharged engines[J]. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 2012, 226(4): 560-574. doi: 10.1177/0954407011420790
    [3] 李先南, 黄立, 张文正, 等. 两级增压对船用柴油机性能影响的试验[J]. 内燃机学报, 2020, 38(2): 104-109. https://www.cnki.com.cn/Article/CJFDTOTAL-NRJX202002002.htm

    LI Xian-nan, HUANG Li, ZHANG Wen-zheng, et al. Experiment of the influence of two stage turbocharging on the performance of a marine diesel engine[J]. Transactions of CSICE, 2020, 38(2): 104-109. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-NRJX202002002.htm
    [4] LLAMAS X, ERIKSSON L. Parameterizing compact and extensible compressor models using orthogonal distance minimization[J]. Journal of Engineering for Gas Turbines and Power, 2016, 139(1): 012601.
    [5] 沈浩生, 张均东, 杨柏丞, 等. 一种考虑传热现象的船用压气机等熵效率分区域建模方法[J]. 船舶工程, 2020, 42(7): 76-87. https://www.cnki.com.cn/Article/CJFDTOTAL-CANB202007021.htm

    SHEN Hao-sheng, ZHANG Jun-dong, YANG Bai-cheng, et al. A zonal modeling approach of marine compressor isentropic efficiency with consideration of heat transfer phenomenon[J]. Ship Engineering, 2020, 42(7): 76-87. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-CANB202007021.htm
    [6] 涂环. 大型船舶柴油机推进系统建模及转速控制研究[D]. 武汉: 武汉理工大学, 2015.

    TU Huan. Investigation on the modelling and speed control of marine diesel engine propulsion system[D]. Wuhan: Wuhan University of Technology, 2015. (in Chinese).
    [7] MORAAL P, KOLMANOVSKY I. Turbocharger modeling for automotive control applications[J]. SAE Technical Papers, 1999, DOI: 10.4271/1999-01-0908.
    [8] GHOLAMREZAEI M, GHORBANIAN K. Compressor map generation using a feed-forward neural network and rig data[J]. Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, 2010, 224(1): 97-108. doi: 10.1243/09576509JPE792
    [9] 管聪. 大型船舶降速航行主机性能优化方法研究[D]. 武汉: 武汉理工大学, 2015.

    GUAN Cong. Investigation on the performance optimisation method for large containership propulsion engine at slow steaming conditions[D]. Wuhan: Wuhan University of Technology, 2015. (in Chinese).
    [10] JENSEN J P, KRISTENSEN A F, SORENSON S C, et al. Mean value modeling of a small turbocharged diesel engine[J]. SAE Technical Papers, 1991, DOI: 10.4271/910070.
    [11] ERIKSSON L. Modeling and control of turbocharged SI and DI engines[J]. Oil and Gas Science and Technology, 2007, 62(4): 523-538. doi: 10.2516/ogst:2007042
    [12] DOWELL P G, AKEHURST S. Advanced mapping techniques for radial compressor for use in real-time engine models[J]. SAE Technical Papers, 2010, DOI: 10.4271/2010-01-1227.
    [13] HADEF J E, COLIN G, CHAMAILLARD Y, et al. Physical-based algorithms for interpolation and extrapolation of turbocharger data maps[J]. SAE International Journal of Engines, 2012, 5(2): 363-378. doi: 10.4271/2012-01-0434
    [14] MARTIN G, TALON V. Implementing turbomachinery physics into data map-based turbocharger models[J]. SAE International Journal of Engines, 2009, 2(1): 211-229. doi: 10.4271/2009-01-0310
    [15] MALKHEDE D N, SETH B, DHARIWAL H C. Mean value model and control of a marine turbocharged diesel engine[J]. SAE Technical Papers, 2005, DOI: 10.4271/2005-01-3889.
    [16] KARLSON A T. On modeling of a ship propulsion system for control purposes[D]. Trondheim: Norwegian University of Science and Technology, 2012.
    [17] DINESCU D C, TAZEROUT M. Mean value modeling of a variable nozzle turbocharger (VNT)[J]. UPB Scientific Bulletin, Series D: Mechanical Engineering, 2010, 72(1): 109-116.
    [18] ZENG Tao, UPADHYAY D, ZHU Guo-ming. A reduced complexity model for the compressor power of an automotive turbocharger[J]. Journal of Dynamic Systems, Measurement and Control, 2018, 140(6): 061018. doi: 10.1115/1.4039285
    [19] ERIKSSON L, NEZHADALI V, ANDERSSON C. Compressor flow extrapolation and library design for the modelica vehicle propulsion library-vehprolib[J]. SAE Technical Papers, 2016, DOI: 10.4271/2016-01-1037.
    [20] MÜLLER M, HENDRICKS E, SORENSON S C. Mean value modeling of turbocharged spark ignition engines[J]. SAE Technical Papers, 1998, DOI: 10.4271/980784.
    [21] LEUFVÉN O, ERIKSSON L. A surge and choke capable compressor flow model-validation and extrapolation capability[J]. Control Engineering Practice, 2013, 21(12): 1871-1883. doi: 10.1016/j.conengprac.2013.07.005
    [22] LEUFVÉN O, ERIKSSON L. Measurement, analysis and modeling of centrifugal compressor flow for low pressure ratios[J]. International Journal of Engine Research, 2014, 17(2): 153-168.
    [23] LLAMAS X, ERIKSSON L. Control-oriented compressor model with adiabatic efficiency extrapolation[J]. SAE International Journal of Engines, 2017, 10(4): 1903-1916. doi: 10.4271/2017-01-1032
    [24] ORIKISZ M, STAWARS S. Modeling of turbine engine axial-flow compressor and turbine characteristics[J]. Journal of Propulsion and Power, 2000, 16(2): 336-339. doi: 10.2514/2.5574
    [25] ANDERSSON P. Air charge estimation in turbocharged spark ignition engines[D]. Linköping: Linköping University, 2005.
    [26] BITEUS J. Mean value engine model of a heavy duty diesel engine[D]. Linköping: Linköping University, 2004.
    [27] GUZZELLA L, AMSTUTZ A. Control of diesel engines[J]. IEEE Control Systems Magazine, 1998, 18(5): 53-71. doi: 10.1109/37.722253
    [28] SIEROS G, STAMATIS A, MATHIOUDAKIS K. Jet engine component maps for performance modeling and diagnosis[J]. Journal of Propulsion and Power, 1997, 13(5): 665-674. doi: 10.2514/2.5218
    [29] FANG Xian-de, CHEN Wei-wei, ZHOU Zhan-ru, et al. Empirical models for efficiency and mass flow rate of centrifugal compressors[J]. International Journal of Refrigeration, 2014, 41: 190-199. doi: 10.1016/j.ijrefrig.2014.03.005
    [30] YANG Bei, FANG Xian-de, ZHANG Li-sheng, et al. Applicability of empirical models of isentropic efficiency and mass flow rate of dynamic compressors to jet engines[J]. Progress in Aerospace Sciences, 2019, 106: 32-42. doi: 10.1016/j.paerosci.2019.01.007
    [31] TANG Yuan-yuan, ZHANG Jun-dong, GAN Hui-bing, et al. Development of a real-time two-stroke marine diesel engine model with in-cylinder pressure prediction capability[J]. Applied Energy, 2017, 197: 55-70.
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  • 收稿日期:  2020-06-01
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