@ARTICLE{Sun_Xiaoqiang_NFTSM_2021,
 author={Sun, Xiaoqiang and Wang, Yujun and Cai, Yingfeng and Wong, Pak Kin and Chen, Long},
 volume={69},
 number={3},
 journal={Bulletin of the Polish Academy of Sciences Technical Sciences},
 pages={e137065},
 howpublished={online},
 year={2021},
 abstract={To improve the curve driving stability and safety under critical maneuvers for four-wheel-independent drive autonomous electric vehicles, a three-stage direct yaw moment control (DYC) strategy design procedure is proposed in this work. The first stage conducts the modeling of the tire nonlinear mechanical properties, i.e. the coupling relationship between the tire longitudinal force and the tire lateral force, which is crucial for the DYC strategy design, in the STI (Systems Technologies Inc.) form based on experimental data. On this basis, a 7-DOF vehicle dynamics model is established and the direct yaw moment calculation problem of the four-wheel-independent drive autonomous electric vehicle is solved through the nonsingular fast terminal sliding mode (NFTSM) control method, thus the optimal direct yaw moment can be obtained. To achieve this direct yaw moment, an optimal allocation problem of the tire forces is further solved by using the trust-region interior-point method, which can effectively guarantee the solving efficiency of complex optimization problem like the tire driving and braking forces allocation of four wheels in this work. Finally, the effectiveness of the DYC strategy proposed for the autonomous electric vehicles is verified through the CarSim-Simulink co-simulation results.},
 type={Article},
 title={NFTSM control of direct yaw moment for autonomous electric vehicles with consideration of tire nonlinear mechanical properties},
 URL={http://www.czasopisma.pan.pl/Content/119664/PDF/16_01911_Bpast.No.69(3)_29.06.21_Druk.pdf},
 doi={10.24425/bpasts.2021.137065},
 keywords={autonomous electric vehicles, direct yaw moment control (DYC), tire nonlinear mechanical properties, nonsingular fast terminal sliding mode (NFTSM), trust-region interior-point method},
}