Extended Kalman Filter to Estimate NO, NO2, Hydrocarbon and Temperatures in a DOC during Active Regeneration and Under Steady State Conditions

2015 ◽  
Author(s):  
Harsha Shankar Surenahalli ◽  
Gordon Parker ◽  
John H. Johnson
Keyword(s):  
Kalman Filter ◽  
Steady State ◽  
Extended Kalman Filter ◽  
Active Regeneration

Identification of Pacejka’s Coefficients Through Full Vehicle Experimental Tests

2007 ◽  
Author(s):  
Federico Cheli ◽  
Francesco Braghin ◽  
Ferruccio Resta ◽  
Edoardo Sabbioni
Keyword(s):  
Experimental Data ◽  
Kalman Filter ◽  
Steady State ◽  
Extended Kalman Filter ◽  
Experimental Tests ◽  
Constrained Minimization ◽  
Identification Procedure ◽  
Tyre Model ◽  
Full Vehicle ◽  
Minimization Approach

A methodology aimed at identifying the MF-Tyre model coefficients for the steady-state pure cornering condition is presented in this paper. Only the measurements carried out on board vehicle during standard handling manoeuvres (step-steer) are considered by the identification procedure. The proposed methodology is made of three subsequent steps. During the first phase the axles cornering forces are identified through an extended Kalman filter. Then the vertical loads and the slip angles at each tire are estimated. The results of these two steps are passed as an input to the last phase, during which through a constrained minimization approach, the MF coefficients are identified. The identification procedure has been applied to the experimental data collected on an instrumented sport car.

scholarly journals Performance evaluation of GPS / BDS combined single-point positioning based on RTKLIB

2020 ◽  
Vol 165 ◽  
pp. 03009
Author(s):  
Li Yan-yi ◽  
Huang Jin ◽  
Tang Ming-xiu
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Single Point ◽  
Least Square Method ◽  
Least Square ◽  
Filter Method ◽  
Single System ◽  
Positioning Error ◽  
Dual Mode ◽  
Kalman Filter Method

In order to evaluate the performance of GPS / BDS, RTKLIB, an open-source software of GNSS, is used in this paper. In this paper, the least square method, the weighted least square method and the extended Kalman filter method are respectively applied to BDS / GPS single system for data solution. Then, the BDS system and GPS system are used for fusion positioning and the positioning results of the two systems are compared with that of the single system. Through the comparison of experiments, on the premise of using the extended Kalman filter method for positioning, when the GPS signal is not good, BDS data is introduced for dual-mode positioning, the positioning error in e direction is reduced by 36.97%, the positioning error in U direction is reduced by 22.95%, and the spatial positioning error is reduced by 16.01%, which further reflects the advantages of dual-mode positioning in improving a system robustness and reducing the error.

Sign in / Sign up

Export Citation Format

Share Document