Cascaded Dual Extended Kalman Filter for Combined Vehicle State Estimation and Parameter Identification Univ. of Waterloo

Format:

Conference/Event

Author/Creator:

Rezaeian, Rezaeian, author.

Contributor:

Chen, Shih-Ken

Fallah, Saber

Khajepour, Amir

Litkouhi, Baktiarr

Melek, William

Zarringhalam, Reza

Conference Name:

SAE 2013 World Congress & Exhibition (2013-04-16 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2013

Summary:

This paper proposes a model-based "Cascaded Dual Extended Kalman Filter" (CDEKF) for combined vehicle state estimation, namely, tire vertical forces and parameter identification. A sensitivity analysis is first carried out to recognize the vehicle inertial parameters that have significant effects on tire normal forces. Next, the combined estimation process is separated in two components. The first component is designed to identify the vehicle mass and estimate the longitudinal forces while the second component identifies the location of center of gravity and estimates the tire normal forces. A Dual extended Kalman filter is designed for each component for combined state estimation and parameter identification. Simulation results verify that the proposed method can precisely estimate the tire normal forces and accurately identify the inertial parameters

Notes:

Vendor supplied data

Publisher Number:

2013-01-0691

Access Restriction:

Restricted for use by site license