An improved adaptive unscented Kalman filter for estimating the states of in‐wheel‐motored electric vehicle

DOI10.1002/acs.3059zbMath1451.93388OpenAlexW2981580324WikidataQ127024125 ScholiaQ127024125MaRDI QIDQ5128853

X. Han, Fei Lei, Caixia Huang, Zhi Yong Zhang

Publication date: 26 October 2020

Published in: International Journal of Adaptive Control and Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/acs.3059

zbMATH Keywords

state estimationadaptive adjustmentunscented Kalman filterelectric vehiclein-wheeled motored

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Application models in control theory (93C95) Adaptive control/observation systems (93C40) Estimation and detection in stochastic control theory (93E10)

Cites Work

• Robust \(H_\infty\) dynamic output-feedback control for four-wheel independently actuated electric ground vehicles through integrated AFS/DYC
• Estimation of lateral tire-road forces and sideslip angle for electric vehicles using interacting multiple model filter approach
• Windowing and random weighting-based adaptive unscented Kalman filter
• Design and implementation of an adaptive Kalman filtering for the launcher of multiple launch rocket system
• A novel variable-length sliding window blockwise least-squares algorithm for on-line estimation of time-varying parameters
• Mobile vehicle navigation in unknown environments: a multiple hypothesis approach

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