Abstract
Estimation of vehicle state (e.g., vehicle velocity and sideslip angle) and road friction coefficient is essential for electric vehicle stability control. This article proposes a novel real-time model-based vehicle estimator, which can be used for estimation of vehicle state and road friction coefficient for the distributed driven electric vehicle. The estimator is realized using the extended Kalman filter (EKF) and the recursive least squares (RLS) technique. The proposed estimation algorithm is evaluated through simulation and experimental test. Results to data indicate that the proposed approach is effective and it has the ability to provide with reliable information for vehicle active safety control.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
