Design of Vehicle Running States-Fused Estimation Strategy Using Kalman Filters and Tire Force Compensation Method

Te Chen; Yingfeng Cai; Long Chen; Xing Xu; Haobin Jiang; Xiaoqiang Sun

doi:10.1109/access.2019.2925370

journal article Open Access Jan 01, 2019

Design of Vehicle Running States-Fused Estimation Strategy Using Kalman Filters and Tire Force Compensation Method

Te Chen

IEEE Access Vol. 7 pp. 87273-87287 · Institute of Electrical and Electronics Engineers (IEEE)

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Details

Published: Jan 01, 2019
Vol/Issue: 7
Pages: 87273-87287
License: View

Authors

Department of Genetics, Washington University, School of Medicine, St. Louis, MO 63110, USA

Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China; School of Mathematical and Computational Science, Sun Yat-Sen University, Guangzhou, 510000, China; School of Life Science, Sun Yat-Sen University, Guangzhou, 510275, China

Funding

National Natural Science Foundation of China Award: U1564201

Six Talent Peaks Project in Jiangsu Province Award: 2018-TD-GDZB-022

National Key Research and Development Program of China Award: 2017YFB0102603

Postgraduate Scientific Research Innovation Program of Jiangsu Province Award: SJKY19_2536

Cite This Article

Te Chen, Yingfeng Cai, Long Chen, et al. (2019). Design of Vehicle Running States-Fused Estimation Strategy Using Kalman Filters and Tire Force Compensation Method. IEEE Access, 7, 87273-87287. https://doi.org/10.1109/access.2019.2925370

Design of Vehicle Running States-Fused Estimation Strategy Using Kalman Filters and Tire Force Compensation Method

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