大型营运客车运行安全性能监测方法研究

发布时间：2018-02-24 16:28

本文关键词： 大型营运客车制动系统转向系统行驶系统安全性能监测　出处：《北京理工大学》2015年博士论文　论文类型：学位论文

【摘要】：遏制营运车辆导致的群死群伤事故一直是我国道路交通安全管理的重点工作。营运车辆本身因素是造成道路交通事故的主要原因之一。在车辆运行过程中，其技术性能变差、关键零部件损坏失灵会造成事故的意外发生。本论文以造成群死群伤交通事故比重较大的大型营运客车为研究对象，研究提出制动系统与转向系统安全性能以及行驶系统疲劳可靠性监测方法，研究成果的应用对于遏制群死群伤事故的发生具有重要意义。具体研究内容和结论如下：（1）构建了大型营运客车运行安全性能监测方案与实车试验平台。结合目前营运客车安全性能监测存在的关键问题，通过分析大型客车气压制动系统、液压助力转向系统工作过程以及行驶系统疲劳可靠性的主要影响因素，研究提出了制动系统与转向系统运行安全性能以及行驶系统疲劳可靠性监测方案。按照监测方案，确定了需要采集的信号和需要加装的传感器，搭建了基于VBOX的制动系统、转向系统安全性能监测试验平台（简称VBOX试验平台）和基于eDAQ的行驶系统疲劳可靠性监测试验平台（简称eDAQ试验平台）。VBOX试验平台和eDAQ试验平台能够实现监测方案所需信号的同步采集、实时监测与数据处理，能够满足本论文研究工作的需要。（2）建立了大型客车整车动力学仿真模型，并进行了实车试验验证。参照福田某大型客车，利用Trucksim动力学仿真软件，建立了大型客车动力学仿真模型；进行了稳态转向实车试验与仿真试验，对比分析了车辆侧向加速度、侧倾角、横摆角速度等参数的稳态值，各项参数最大相对误差在10%以内，验证了所建车辆动力学仿真模型的有效性。（3）提出了典型制动工况下的制动系统状态监测方法。基于平稳制动、下坡恒速制动和直线紧急制动典型工况对客车制动系统进行综合监测。对平稳制动时的制动器制动力矩估计、下坡恒速制动时的制动效能监测以及直线紧急制动时充分发出的平均制动减速度(MFDD)估算进行了理论分析。在理论分析的基础上，利用VBOX试验平台进行了平稳制动实车试验，回归建立了制动踏板力、制动踏板位移与制动器制动力矩的关系模型。进行了直线紧急制动实车试验、平稳制动和下坡恒速制动仿真实验与故障模拟试验，验证了理论分析的正确性。（4）提出了基于卡尔曼滤波残差移动平均值的转向系统状态监测方法。建立了三自由度大型客车模型，构建了卡尔曼滤波状态估计器；卡尔曼滤波状态估计器以转向盘转角和车速为输入信号，以侧向加速度为测量信号，实现车辆横摆角速度的实时估计；将横摆角速度估计值与测量值对比产生残差，计算残差移动平均值；分析转向系统性能良好时残差的移动平均值，设定故障判定阈值，超出阈值判定系统出现故障。进行稳态转向实车试验和故障模拟试验验证了该方法的有效性。（5）提出了考虑车辆行驶速度分布的行驶系统疲劳可靠性监测方法。基于名义损伤疲劳寿命预测理论和Miner线性累积损伤法则，，主要分析了车辆行驶速度对疲劳寿命的影响，提出了不同速度段的当量系数，建立了行驶系统疲劳可靠性监测模型。利用eDAQ试验平台采集了大型客车轴头载荷数据，计算了不同速度段的当量系数。根据设计目标可靠性、车辆行驶速度分布以及当量系数实现了四条不同运营线路车辆行驶系统剩余疲劳寿命的预测，验证了监测模型的有效性。
[Abstract]:Qunsiqunshang accident caused containment operation of vehicles has been the focus of China's road traffic safety management. The operation of the vehicle itself factors is one of the main reasons causing traffic accidents. In the running process of the vehicle, its technical performance becomes poor, the key parts of damage failure can cause accidents accidents. In this paper, the proportion of traffic accidents Qunsiqunshang the large passenger vehicles as the research object, the research put forward the braking system and steering system and driving safety monitoring system of fatigue reliability method, the research results are important to curb the Qunsiqunshang accident. The specific research contents and conclusions are as follows:
(1) the construction of large passenger operation operation safety monitoring scheme and real vehicle test platform. Combined with the key problem in the operation of passenger safety monitoring exists, through the analysis of large passenger car air braking system, hydraulic steering system working process and main factors affecting the fatigue reliability of driving system, research and put forward the braking system and steering safety the performance of system operation and reliability monitoring scheme of system fatigue. According to the monitoring plan, identified the need for signal acquisition and sensor installation, build a braking system based on VBOX, steering test platform monitoring system safety performance (VBOX test platform) and driving system fatigue reliability monitoring test platform based on eDAQ (eDAQ test platform).VBOX test platform and eDAQ test platform can achieve synchronous acquisition monitoring scheme of the desired signal, real-time monitoring And data processing can meet the needs of the research work in this paper.
(2) a large passenger vehicle dynamics simulation model, and the real vehicle test. According to a large car Futian, using the dynamic simulation software Trucksim established a large passenger dynamics simulation model; the test and Simulation of vehicle test comparison and analysis of the vehicle steady steering, lateral acceleration, roll angle, yaw steady angular velocity values of the parameters, the parameters of the maximum relative error is less than 10%, to verify the effectiveness of the vehicle dynamics simulation model.
(3) the braking system state monitoring method of typical braking conditions. Based on the stationary brake, constant speed brake and emergency brake line typical conditions of comprehensive monitoring of bus braking system downhill. Estimation of brake torque smooth braking, the average braking constant speed braking braking performance monitoring and emergency brake line fully developed deceleration (MFDD) estimation is analyzed. On the basis of theoretical analysis, the smooth braking vehicle test using the VBOX test platform, regression to establish a brake pedal force, brake pedal displacement and the relation model of brake torque. The linear emergency braking vehicle test, braking and downhill constant speed test and braking fault simulation test, verify the correctness of the theoretical analysis.
(4) proposed steering condition monitoring method system of Calman filter residual moving average value. Based on the three degree of freedom was established a large bus model, constructed the Calman filter state estimator; Calman filter state estimator with steering wheel angle and vehicle speed as the input signal to the lateral acceleration measurement signal, the real-time estimation of vehicle yaw rate the yaw rate estimation; the value of residual contrast produced and measured values, computing the residual moving average; analysis of the steering system has good performance when the residual moving average, setting threshold exceeds a threshold value to determine fault, system failure. The steady state to verify the effectiveness of the method of real vehicle test and fault simulation test of steering.
(5) considering the vehicle driving fatigue reliability monitoring system. The method of velocity distribution of nominal damage fatigue life prediction theory and Miner linear cumulative damage rule based on the influence of vehicle speed on fatigue life, the equivalent coefficient of different speeds, established the traveling system fatigue reliability monitoring model using eDAQ. The test platform for collecting large bus axle load data, equivalent coefficient of different speeds were calculated. According to the design goals of reliability prediction, the vehicle speed distribution and equivalent coefficient to achieve four different operation line vehicle residual fatigue life of the system, to verify the effectiveness of the monitoring model.

【学位授予单位】：北京理工大学
【学位级别】：博士
【学位授予年份】：2015
【分类号】：U492.8

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