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Cascaded Dual Extended Kalman Filter for Combined Vehicle State Estimation and Parameter Identification
Technical Paper
2013-01-0691
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
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.
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Citation
Rezaeian, A., Zarringhalam, R., Fallah, S., Melek, W. et al., "Cascaded Dual Extended Kalman Filter for Combined Vehicle State Estimation and Parameter Identification," SAE Technical Paper 2013-01-0691, 2013, https://doi.org/10.4271/2013-01-0691.Also In
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