首页> 外文会议>IEEE International Conference on Power Electronics and Drive Systems >Identification scheme of maximum traction force using recursive least square for traction control in electric locomotives
【24h】

Identification scheme of maximum traction force using recursive least square for traction control in electric locomotives

机译:基于递推最小二乘的电力机车牵引力控制最大牵引力识别方案

获取原文

摘要

The railway traction system that incorporates a slip controller provides a significant improvement in the adhesion between rail and train which can lead to increase in the traction force and wheel slip controllability. Due to the change of rail track and running speed, both slip and operating traction force keep changing. Therefore, there is a requirement of reliable identification of wheel-rail contact force properties and adhesion level for acceleration or braking controls to adapt to different track conditions. Since wheel slip controller shows many applications in the aspect of safety relevant features, such as slip control, emergency brake assistance, locomotive operation, etc. the proper estimation of traction force and the detection of maximum traction force between rail and wheels are very important factors in the railway industry. Furthermore, an advanced scheme with traction drive control is required to achieve the maximum adhesion level for a railway vehicle. This paper proposes a new identification technique scheme which is designed to regulate the torque reference according to the maximum traction force. The proposed scheme is built with Recursive Least Square (RLS) scheme to identify the peak slip level at maximum traction force with the searching technique based on the traction force estimated by a Kalman Filter. Furthermore, this scheme is also used to operate the traction system within the identified maximum traction force region. Simulation model validates that the proposed controller with identification scheme can control the train or locomotive to obtain its maximum adhesion force.
机译:结合了滑移控制器的铁路牵引系统显着改善了铁路与火车之间的附着力,这可能导致牵引力和车轮滑移可控制性的提高。由于铁轨和运行速度的变化,滑移力和操作牵引力都不断变化。因此,需要可靠地识别轮轨接触力特性和附着力水平,以用于加速或制动控制以适应不同的履带条件。由于车轮滑移控制器在安全相关功能方面具有许多应用,例如滑移控制,紧急制动辅助,机车运行等,因此正确估算牵引力以及检测铁轨与车轮之间的最大牵引力是非常重要的因素在铁路行业。此外,需要具有牵引驱动控制的先进方案来实现铁路车辆的最大附着力水平。本文提出了一种新的识别技术方案,该方案旨在根据最大牵引力来调节转矩参考值。所提出的方案是采用递归最小二乘(RLS)方案构建的,以基于卡尔曼滤波器估计的牵引力的搜索技术来识别最大牵引力下的峰值滑移水平。此外,该方案还用于在所识别的最大牵引力区域内操作牵引系统。仿真模型验证了所提出的带有识别方案的控制器可以控制火车或机车获得最大的附着力。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号