Real-time train acceleration estimation method based on least-square piecewise linear fitting

ZHU Baolin; CHEN Mingyang; LIU Yexuan; JIANG Fan; LI Tiebing; ZHOU Wenwei

doi:10.13890/j.issn.1000-128X.2022.01.004

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Real-time train acceleration estimation method based on least-square piecewise linear fitting

Intelligent Technology Column | 更新时间：2024-08-02

- Real-time train acceleration estimation method based on least-square piecewise linear fitting
- Electric drive for locomotives Issue 1, Pages: 20-24(2022)
- 作者机构：
  
  1.株洲中车时代电气股份有限公司技术中心，湖南株洲　412001
  2.伦敦大学学院，英国;伦敦　WC1T6BT
- 作者简介：
- 基金信息：
- DOI：10.13890/j.issn.1000-128X.2022.01.004
  CLC： U268.4
- Published：10 January 2022，
  
  Received：16 January 2020，
  
  Revised：20 November 2021，
- 稿件说明：
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ZHU Baolin, CHEN Mingyang, LIU Yexuan, et al. Real-time train acceleration estimation method based on least-square piecewise linear fitting. [J]. Electric drive for locomotives (1):20-24(2022)
DOI：

ZHU Baolin, CHEN Mingyang, LIU Yexuan, et al. Real-time train acceleration estimation method based on least-square piecewise linear fitting. [J]. Electric drive for locomotives (1):20-24(2022) DOI： 10.13890/j.issn.1000-128X.2022.01.004.

摘要

在列车自动驾驶控车过程中，加速度是一个重要的反馈量和控制量，它能够反应列车的运动状态和平稳性，在重载列车平稳操纵控制中尤为重要。文章提出一种准确、快速、计算量小的加速度在线估计算法，该方法适合计算能力有限的嵌入式平台，能够有效应用于实际工程项目。该算法首先使用中值平均滤波算法处理速度传感器采集的数据；然后采用改进型最小二乘分段拟合算法，进行加速度估计。相比于加速度定义法直接求取加速度，加速度在线估计算法的精度高，更逼近列车真实加速度。神朔智能驾驶项目实际数据验证表明，该方法能准确、快速地在自动驾驶车载嵌入式平台中计算加速度。

Abstract

The acceleration is an important feedback and control factor in the process of automatic train driving and controlling

which can reflect the movement state and stability of the train. It is especially important in the stationary control of the heavy-haul train. In this paper

an accurate

fast and much less computations acceleration observation algorithm was proposed

which was suitable for embedded platform with limited computing power and could be applied to practical engineering projects effectively. Firstly

the median average filter algorithm was used to process the data collected by the speed sensor

and then the improved least square piecewise fitting algorithm was used to estimate the acceleration. Compared with the direct calculation of acceleration by definition

the on-line acceleration estimation algorithm has high accuracy and is closer to the real acceleration of the train. The actual data verification of Shenshuo intelligent driving project shows that this method can accurately and quickly calculate the acceleration in the automatic driving vehicle embedded platform.

关键词

自动驾驶重载列车最小二乘法分段拟合加速度

Keywords

automatic train drivingheavy haul trainleast square methodpiece-wise fittingacceleration

references

何玉庆, 韩建达. 一种新的角加速度估计方法及其应用[J]. 控制理论与应用, 2007, 24(1): 6-12.

HE Yuqing, HAN Jianda. A new angular acceleration estimation method and its application in acceleration feedback control[J]. Control Theory & Applications, 2007, 24(1): 6-12.

李殿起, 薛定宇, 崔建国, 等. 一种新型的速度和加速度估计器[J]. 系统仿真学报, 2008, 20(15): 4132-4135.

LI Dianqi, XUE Dingyu, CUI Jianguo, et al. Novel velocity and acceleration estimator[J]. Journal of System Simulation, 2008, 20(15): 4132-4135.

ZHU W H, LAMARCHE T. Velocity estimation by using position and acceleration sensors[J]. IEEE Transactions on Industrial Electronics, 2007, 54(5): 2706-2715.

SHAO Y M, SU D Z, AL-HABAIBEHC A, et al. A new fault diagnosis algorithm for helical gears rotating at low speed using an optical encoder[J]. Measurement, 2016, 93: 449-459.

RIJNEN M, SACCON A, NIJMEIJER H. Motion signals with velocity jumps: velocity estimation employing only quantized position data[J]. IEEE Robotics and Automation Letters, 2018, 3(3): 1498-1505.

FALCÃO CARNEIRO J, GOMES DE ALMEIDA F. On the influence of velocity and acceleration estimators on a servopneumatic system behaviour[J]. IEEE Access, 2016, 4: 6541-6553.

RODRIGUEZ-MALDONADO J. Estimation of angular velocity and acceleration with Kalman filter, based on position measurement only[J]. Measurement, 2019, 145: 130-136.

张永涛, 贾延明. 最小二乘法中代数多项式曲线拟合的分析及实现[J]. 计算机与数字工程, 2017, 45(4): 637-639.

ZHANG Yongtao, JIA Yanming. Analysis and program implementation of least squares polynomial curve fitting[J]. Computer and Digital Engineering, 2017, 45(4): 637-639.

刘霞, 王运锋. 基于最小二乘法的自动分段多项式曲线拟合方法研究[J]. 科学技术与工程, 2014, 14(3): 55-58.

LIU Xia, WANG Yunfeng. Research of automatically piecewise polynomial curve-fitting method based on least-square principle[J]. Science Technology and Engineering, 2014, 14(3): 55-58.

高盼, 郭广礼. 基于最小二乘法道路平面曲线拟合[J]. 测绘信息与工程, 2011, 36(2): 19-21.

GAO Pan, GUO Guangli. Fitting highway planar curve based on least squares method[J]. Journal of Geomatics, 2011, 36(2): 19-21.

薛丽红. 基于最小二乘法的分段直线拟合算法[J]. 贵阳学院学报(自然科学版), 2015, 10(4): 9-10.

XUE Lihong. Piecewise linear fitting algorithm based on least square method[J]. Journal of Guiyang College(Natural Sciences), 2015, 10(4): 9-10.

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