城軌列車(chē)模型的關(guān)鍵參數(shù)擬合研究
發(fā)布時(shí)間：2018-10-13 08:24
【摘要】：近年來(lái),城市軌道交通領(lǐng)域的發(fā)展引領(lǐng)著城軌列車(chē)設(shè)計(jì)制造、信號(hào)設(shè)備研發(fā)生產(chǎn)等相關(guān)行業(yè)的飛速發(fā)展,越來(lái)越多的高校和研究機(jī)構(gòu)從事軌道交通領(lǐng)域的基礎(chǔ)研究和應(yīng)用研究。列車(chē)動(dòng)力學(xué)模型作為其研究的基礎(chǔ),對(duì)列車(chē)的運(yùn)行控制有著極大的影響。在對(duì)城軌列車(chē)節(jié)能優(yōu)化研究過(guò)程中,由于列車(chē)模型不夠精確,仿真環(huán)境下理論節(jié)能效果與現(xiàn)場(chǎng)實(shí)測(cè)節(jié)能效果有所差異。因此,準(zhǔn)確的列車(chē)模型對(duì)工程和理論研究具有深刻的意義。在總結(jié)了列車(chē)模型現(xiàn)有研究的基礎(chǔ)上,根據(jù)列車(chē)的運(yùn)行工況和數(shù)據(jù)特點(diǎn),本文建立了符合實(shí)際列車(chē)運(yùn)行情況的單質(zhì)點(diǎn)動(dòng)力學(xué)模型,將列車(chē)模型劃分為惰行階段模型、牽引階段模型和制動(dòng)階段模型。將牽引階段分為牽引建立和牽引切除階段,其中,牽引建立階段模型分為低速牽引建立階段模型和高速牽引建立階段模型。將列車(chē)模型劃分為若干個(gè)模型,能夠更準(zhǔn)確的表述實(shí)際列車(chē)運(yùn)行過(guò)程。針對(duì)參數(shù)擬合計(jì)算問(wèn)題,本文提出了果蠅優(yōu)化算法的一種改進(jìn)型算法CIP-FOA(Fruit Fly Optimization Algorithm with Changing Iteration and Population),該算法采用改變步長(zhǎng)半徑的方式,從迭代和種群兩個(gè)方面對(duì)步長(zhǎng)進(jìn)行改進(jìn)。通過(guò)與其他算法進(jìn)行了仿真對(duì)比分析,驗(yàn)證了 CIP-FOA在穩(wěn)定性、計(jì)算精度和計(jì)算效率等方面較其他算法有明顯優(yōu)勢(shì)。本文在分析處理的北京地鐵亦莊線的夜間測(cè)試數(shù)據(jù)的基礎(chǔ)上,應(yīng)用CIP-FOA對(duì)列車(chē)基本阻力參數(shù)、低速牽引建立階段、高速牽引建立階段、牽引切除階段共14個(gè)模型參數(shù)進(jìn)行擬合計(jì)算。本文在建立的城軌列車(chē)動(dòng)力學(xué)模型和提出的CIP-FOA的基礎(chǔ)上,開(kāi)發(fā)了"城軌列車(chē)動(dòng)力學(xué)模型仿真軟件",該軟件用于參數(shù)擬合計(jì)算和模型的仿真驗(yàn)證工作�；�"城軌列車(chē)動(dòng)力學(xué)模型仿真軟件",對(duì)不同控制策略的列車(chē)運(yùn)行數(shù)據(jù)進(jìn)行仿真計(jì)算,通過(guò)仿真結(jié)果的對(duì)比和分析,驗(yàn)證了本模型符合列車(chē)的實(shí)際運(yùn)行過(guò)程,良好的實(shí)驗(yàn)結(jié)果體現(xiàn)了本研究在工程規(guī)劃設(shè)計(jì)和列車(chē)動(dòng)力學(xué)模型性能預(yù)測(cè)方面的作用。
[Abstract]:In recent years, the development of urban rail transit has led the rapid development of urban rail train design and manufacture, signal equipment research and production and other related industries. More and more universities and research institutions are engaged in the basic research and application research in the field of rail transit. As the basis of the research, the train dynamics model has a great influence on the train operation control. In the course of energy saving optimization research of urban rail trains, due to the inaccuracy of train model, the effect of theoretical energy saving in simulation environment is different from that of field measurement. Therefore, the accurate train model has profound significance for engineering and theoretical research. On the basis of summarizing the existing research on the train model and according to the operating conditions and data characteristics of the train, this paper establishes a single mass point dynamic model which accords with the actual train operation, and divides the train model into the idling stage model. Traction stage model and braking stage model. The traction stage is divided into traction establishment and traction resection, in which the traction establishment stage model is divided into low speed traction establishment stage model and high speed traction establishment stage model. The train model can be divided into several models, which can more accurately describe the actual train operation process. To solve the problem of parameter fitting, this paper presents an improved algorithm, CIP-FOA (Fruit Fly Optimization Algorithm with Changing Iteration and Population), for the optimization algorithm of Drosophila melanogaster. The algorithm improves the step size in terms of iteration and population by changing the radius of step size. By comparing with other algorithms, it is proved that CIP-FOA has obvious advantages over other algorithms in terms of stability, accuracy and efficiency. On the basis of analyzing the night test data of Beijing Metro Yizhuang Line, this paper applies CIP-FOA to the basic resistance parameters of trains, the low speed traction establishment stage, the high speed traction establishment stage. A total of 14 model parameters were fitted and calculated in the traction resection stage. Based on the established dynamic model of urban rail train and the proposed CIP-FOA, this paper develops a simulation software for the dynamic model of urban rail train, which is used for parameter fitting calculation and simulation verification of the model. Based on the simulation software of urban rail train dynamics model, the train operation data with different control strategies are simulated and calculated. Through the comparison and analysis of the simulation results, it is verified that the model accords with the actual running process of the train. Good experimental results show the function of this study in engineering planning and performance prediction of train dynamics model.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：U270.11;TP391.9
本文編號(hào)：2267933
[Abstract]:In recent years, the development of urban rail transit has led the rapid development of urban rail train design and manufacture, signal equipment research and production and other related industries. More and more universities and research institutions are engaged in the basic research and application research in the field of rail transit. As the basis of the research, the train dynamics model has a great influence on the train operation control. In the course of energy saving optimization research of urban rail trains, due to the inaccuracy of train model, the effect of theoretical energy saving in simulation environment is different from that of field measurement. Therefore, the accurate train model has profound significance for engineering and theoretical research. On the basis of summarizing the existing research on the train model and according to the operating conditions and data characteristics of the train, this paper establishes a single mass point dynamic model which accords with the actual train operation, and divides the train model into the idling stage model. Traction stage model and braking stage model. The traction stage is divided into traction establishment and traction resection, in which the traction establishment stage model is divided into low speed traction establishment stage model and high speed traction establishment stage model. The train model can be divided into several models, which can more accurately describe the actual train operation process. To solve the problem of parameter fitting, this paper presents an improved algorithm, CIP-FOA (Fruit Fly Optimization Algorithm with Changing Iteration and Population), for the optimization algorithm of Drosophila melanogaster. The algorithm improves the step size in terms of iteration and population by changing the radius of step size. By comparing with other algorithms, it is proved that CIP-FOA has obvious advantages over other algorithms in terms of stability, accuracy and efficiency. On the basis of analyzing the night test data of Beijing Metro Yizhuang Line, this paper applies CIP-FOA to the basic resistance parameters of trains, the low speed traction establishment stage, the high speed traction establishment stage. A total of 14 model parameters were fitted and calculated in the traction resection stage. Based on the established dynamic model of urban rail train and the proposed CIP-FOA, this paper develops a simulation software for the dynamic model of urban rail train, which is used for parameter fitting calculation and simulation verification of the model. Based on the simulation software of urban rail train dynamics model, the train operation data with different control strategies are simulated and calculated. Through the comparison and analysis of the simulation results, it is verified that the model accords with the actual running process of the train. Good experimental results show the function of this study in engineering planning and performance prediction of train dynamics model.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：U270.11;TP391.9
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，本文編號(hào)：2267933
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