基于稳态卡尔曼滤波的车辆质量与道路坡度估计

Translated title of the contribution: Estimation of Vehicle Mass and Road Slope Based on Steady-state Kalman Filter
  • Shengqiang Hao
  • , Peipei Luo
  • , Junqiang Xi*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

25 Citations (Scopus)

Abstract

In view of that the automatic transmission control system of vehicle is difficult to measure the vehicle mass and road slope, the longitudinal kinematic and dynamic models of vehicle are built, based on which discrete Kalman filter is used to estimate vehicle mass and road slope. The co-simulation with Carsim and Maltab/Simulink and the real vehicle test with proper acceleration sensor and steady-state Kalman filter verify that using the method proposed to estimate vehicle mass and road slope has better real-time performance and accuracy than those obtained from inertial navigator.

Translated title of the contributionEstimation of Vehicle Mass and Road Slope Based on Steady-state Kalman Filter
Original languageChinese (Traditional)
Pages (from-to)1062-1067 and 1075
JournalQiche Gongcheng/Automotive Engineering
Volume40
Issue number9
DOIs
Publication statusPublished - 25 Sept 2018

Fingerprint

Dive into the research topics of 'Estimation of Vehicle Mass and Road Slope Based on Steady-state Kalman Filter'. Together they form a unique fingerprint.

Cite this