轮式装载机典型作业工况构建与分析

doi:10.6040/j.issn.1672-3961.0.2015.095

摘要/Abstract

摘要： 为了获取更准确的循环作业参数,模拟循环燃油消耗量,提出了基于运动学片段和作业特点的轮式装载机典型作业工况构建方法。定义转速扭矩面积等13个特征参数表征循环作业过程参数变化,并采用主成分分析法和模糊C均值聚类法将运动学片段聚为5类,选取每类中欧式距离最小的片段组合构成典型作业工况。结果表明:试验工况和典型工况的加速度、速度等行驶特征参数区间分布相似;基于典型工况的循环仿真油耗为0.176 L,误差为4.7%,在工程误差允许的范围内。该方法可以有效地实现轮式装载机试验数据的处理、分析以及典型作业工况的构建,对于研究装载机循环作业经济性具有一定的指导作用。

关键词: 装载机, 特征值, 主成分分析, 聚类分析, 典型作业工况

Abstract: In order to obtain more precise operating parameters of typical working cycle and simulate the fuel consumption, a constructing method of typical working cycle for wheel loader was proposed based on kinetic sequences and operating characteristics. Thirteen characteristic parameters, including speed-torque area etc., were defined to evaluate the variation of operating parameters during working process. Meanwhile, the kinetic sequences were classified into five clusters by the adoption of the Principal Component Analysis and fuzzy C-means algorithm. Afterwards, the sequences with minimum Euclidean distance in each cluster were selected to constitute the typical working cycle. The results showed that parameters of the test condition and the typical working cycle, such as acceleration and speed, had the similar distribution; fuel consumption based on the typical working cycle simulation was 0.176 L with an error of 4.7%, which was within the scope of the engineering allowable error. The proposed method could be effectively employed to process and analyze the test data of wheel loader and construct the typical working cycle, which was also greatly helpful to further study the fuel economy of loader working cycle.

Key words: loader, eigenvalue, principal component analysis, cluster analysis, typical working cycle

中图分类号:

TK427

马相明,孙霞,张强. 轮式装载机典型作业工况构建与分析[J]. 山东大学学报 (工学版), 2015, 45(5): 82-87.

MA Xiangming, SUN Xia, ZHANG Qiang. Construction and analysis on typical working cycle of wheel loader[J]. Journal of Shandong University(Engineering Science), 2015, 45(5): 82-87.

参考文献

[1] ANDRE M, HICKMAN J A, HASSEL D, et al. Driving cycles for emission measurements under european conditions[C] //SAE 1995 International Congress & Exposition. Detroit, USA:SAE, 950926.
[2] 石琴, 仇多洋, 周洁瑜. 基于组合聚类法的行驶工况构建与精度分析[J]. 汽车工程, 2012, 34(2):164-169. SHI Qin, QIU Duoyang, ZHOU Jieyu. Driving cycle construction and accuracy analysis based on combined clustering technique[J]. Automotive Engineering, 2012, 34(2):164-169.
[3] 姜平,石琴, 陈无畏. 基于马尔科夫的城市道路行驶工况构建方法[J]. 农业机械学报, 2009, 40(11):26-30. JIANG Ping, SHI Qin, CHEN Wuwei. Driving cycle construction methodology of city road based on markov process[J]. Transactions of the Chinese Society for Agricultural Machinery, 2009, 40(11):26-30.
[4] 石琴, 郑与波, 姜平. 基于运动学片段的城市道路行驶工况的研究[J]. 汽车工程, 2011, 33(3):256-261. SHI Qin, ZHENG Yubo, JIANG Ping. A research on driving cycle of city roads based on microtrips[J]. Automotive Engineering, 2011, 33(3):256-261.
[5] 王楠楠. 城市道路行驶工况构建及油耗研究[D]. 合肥:合肥工业大学, 2012. WANG Nannan. Construction of the urban road driving cycle and research of the fuel consumption[D]. Hefei:Hefei University of Technology, 2012.
[6] EISINGER D S, NIEMEIER D A, STOECHENIUS T, et al. Collecting driving data to support mobile source emissions estimation[J]. Journal of Transportation Engineering, 2006, 132(11):845-854.
[7] LIN J, NIEMEIER D A. Estimating regional air quality vehicle emission inventories:constructing robust driving cycles[J]. Transportation Science, 2003, 37(3):330-346.
[8] 常绿, 王国强, 张英爽. 基于ADVISOR软件的液力变矩器仿真模块的开发[J]. 系统仿真学报, 2006, 18(12):3396-3398. CHANG Lyu, WANG Guoqiang, ZHANG Yingshuang. Development of simulation module for performance of torque-converter based on advisor software[J]. Journal of System Simulation, 2006, 18(12):3396-3398.
[9] 常绿, 王国强, 李春然, 等. 装载机性能仿真模块开发[J]. 农业机械学报, 2007, 38(1):195-197. CHANG Lü, WANG Guoqiang, LI Chunran, et al. Development of loader performance simulation module[J]. Transactions of the Chinese Society for Agricultural Machinery, 2007, 38(1):195-197.
[10] MARKUS S, OLIVER K, JUERGEN W. Green wheel loader-operating strategy of an energy efficient hybrid drive train[C] //SAE 2014 Commercial Vehicle Engineering Congress. Detroit, USA:SAE, 2014-01-2400.
[11] KWANG S O, SEUNGJAE Y, HAKGU K, et al. Development of wheel loader dynamic simulation model[C] //SAE 2013 World Congress & Exhibition. Detroit, USA:SAE, 2013-01-1194.
[12] 杨瑜, 陈波宁, 高波. 基于行程分析法的行驶工况的构建研究[J]. 现代车用动力, 2013, 150(2):24-27. YANG Yu, CHEN Boning, GAO Bo. Research of driving cycle data construction based on travelling analysis method[J]. Modern Vehicle Power, 2013, 150(2):24-27.
[13] 张英爽. 装载机传动系载荷谱的测取与应用研究[D]. 长春:吉林大学, 2014. ZHANG Yingshuang. Research on the load spectra acquisition and application of loader powertrain[D]. Changchun:Jilin University, 2014.
[14] 徐礼超, 葛如海, 常绿. 典型工况下装载机液压系统载荷时间历程的制取方法[J]. 农业工程学报, 2012, 28(6):57-62. XU Lichao, GE Ruhai, CHANG Lyu. Acquisition method of load time course of loader hydraulic system under typical operating conditions[J]. Transactions of the Chinese Society of Agricultural Engineering, 2012, 28(6):57-62.
[15] 常绿, 徐礼超, 刘永臣. 工程车辆载荷谱试验方法及应用[M].江苏:中国矿业大学出版社, 2011:50-55.
[16] 张英爽, 王国强, 王继新, 等. 工程车辆传动系载荷谱编制方法[J]. 农业工程学报, 2011, 27(4):179-183. ZHANG Yingshuang, WANG Guoqiang, WANG Jixin, et al. Compilation method of power train load spectrum of engineering vehicle[J]. Transactions of the CSAE, 2011, 27(4):179-183.
[17] 王国军, 蒋美华, 王俊. 载荷谱信号奇异值剔除与降噪处理[J]. 仪器仪表学报, 2009, 30(S1):310-313. WANG Guojun, JIANG Meihua, WANG Jun. Remove spike and noise in the load spectrum method[J]. Chinese Journal of Scientific Instrument, 2009, 30(S1):310-313.
[18] 王继新, 季景方, 张英爽, 等. 基于小波分形理论的工程车辆时域载荷信号降噪方法[J]. 吉林大学学报:工学版, 2011, 41(S2):221-225. WANG Jixin, JI Jingfang, ZHANG Yingshuang. Denoising method of time domain load signals of engineering vehicles based on wavelet and fractal theory[J]. Journal of Jilin University:Engineering and Technology Edition, 2011, 41(S2):221-225.
[19] WANG J X, TANG X B. Wavelet denoise method applied in load spectrum analysis of engineering vehicles[J]. Advanced Materials Research, 2010, 108:1320-1325.
[20] 李健成. 矿山装载机设计[M]. 北京:机械工业出版社, 1985:50-62.
[21] 孙强. 应用于压缩式环卫车的单轴并联式混合动力总成匹配技术研究[D]. 济南:山东大学, 2014. SUN Qiang. Investigation on single-axle parallel hybrid powertrain matching technique used in compression sanitation trucks[D]. Jinan:Shandong University, 2014.

相关文章 15

[1]	肖卓宇,何锫,余波,黎妍,胡振涛. 基于FCA与CBR的设计模式检测[J]. 山东大学学报(工学版), 2016, 46(2): 22-28.
[2]	李发权, 杨立才, 颜红博. 基于PCA-SVM多生理信息融合的情绪识别方法[J]. 山东大学学报(工学版), 2014, 44(6): 70-76.
[3]	郑从奇1,许彦刚2,赵胜3,郭晓娜1,官庆朔1,任春凤1,魏泽彪1. 水库移民生产生活水平可变模糊评价方法与应用[J]. 山东大学学报(工学版), 2013, 43(3): 75-81.
[4]	王琳1,刘保东2 *. 随机可变模糊识别模型在清洁生产评价中的应用[J]. 山东大学学报(工学版), 2013, 43(1): 54-62.
[5]	刘海青,杨立才*,吴磊,孔璐璐. 基于Fuzzy-PCA的城市区域交通拥挤评价方法[J]. 山东大学学报(工学版), 2012, 42(6): 56-62.
[6]	翟俊海1,翟梦尧1,张素芳2,王熙照1. 基于小波子空间集成的人脸识别[J]. 山东大学学报(工学版), 2012, 42(2): 1-6.
[7]	颜子夜,陆耀,李建武,马跃. 一种基于核主成分分析的图像超分辨率算法[J]. 山东大学学报(工学版), 2011, 41(4): 101-105.
[8]	董凤娟,邹华彬*,陆玮洁,杜爱琴. 双指标等级序列模式识别法分析十全大补丸氯仿提取物红外指纹图谱[J]. 山东大学学报(工学版), 2010, 40(6): 113-119.
[9]	吴东洋,业宁. 基于BIRCH的木材缺陷识别[J]. 山东大学学报(工学版), 2010, 40(5): 137-140.
[10]	王好芳吴美陈文艳. 模糊聚类分析在区域水资源承载能力评价中的应用[J]. 山东大学学报(工学版), 2009, 39(3): 139-143.
[11]	许文杰,曹升乐 . 水质综合评价的模糊可变模型及其应用[J]. 山东大学学报(工学版), 2008, 38(3): 40-45 .
[12]	刘新国,栾世宝 . 一类周期辛矩阵对特征值问题的向后误差分析[J]. 山东大学学报(工学版), 2007, 37(1): 94-98 .
[13]	叶华,刘玉田,牛新生 . 基于Prony和稀疏特征值算法的区间低频振荡分析[J]. 山东大学学报(工学版), 2006, 36(5): 30-34 .
[14]	王耘,穆勇,刘庆红 . 基于灰关联分析的模糊聚类最优划分判定模型[J]. 山东大学学报(工学版), 2006, 36(2): 86-89 .
[15]	王耘,穆勇,刘庆红 . 基于灰关联分析的模糊聚类最优划分判定模型[J]. 山东大学学报(工学版), 2006, 36(2): 86-89 .

多维度评价

Viewed

Full text

Abstract

Cited

Shared

Discussed