A study on an independent steering &amp; driving control algorithm for 6WS/6WD vehicles

Choi, Joo-Young; Kim, Dong‐Hyung; Kim, Chang‐Jun; Kim, Young-Ryul; Kim, Sang-Ho; Han, Chang-Soo

doi:10.1109/iccas.2010.5670130

Cited by 1 publication

(2 citation statements)

References 5 publications

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“…Tran, T. H. [8] used the methodology of terramechanics to analyze tire-road contact characteristics for predicting the moving trace of a vehicle, but it was difficult for real-time computation. Kim [1,[9][10][11] developed an 18-DOF dynamic model based on a 6 × 6, armed suspension vehicle to study vehicle state estimation, driving torque distribution, slip rate control, and vehicle motion control. Caldwell [12] used a tire model considering coulomb friction for optimization and predicted the turning performance for a skid-steered wheeled vehicle.…”

Section: Modeling Skid-steered Wheeled Vehiclementioning

confidence: 99%

“…where F z f , F zm , F zr denote the vertical force on the front, middle, and rear axis, respectively; h denotes the height of mass center; ∆ zi denotes the suspension deformation on each axis; k si denotes the suspension stiffness, which would be divided out in the calculating procedure, and therefore the value would not influence the result. The tire vertical force on the longitudinal direction is as (11): Taking lateral acceleration into account:…”

Section: Tire Vertical Force Estimationmentioning

confidence: 99%

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Estimation of Skid-Steered Wheeled Vehicle States Using STUKF with Adaptive Noise Adjustment

et al. 2021

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Skid-steered wheeled vehicles are commonly adopted in outdoor environments with the benefits of mobility and flexible structure. However, different from Ackerman turning vehicles, skid-steered vehicles do not possess geometric constraint but only dynamic constraint when steered, which leads to motion control and state estimation problems for skid-steered vehicles. The controlling accuracy of a skid-steered vehicle depends largely on feedback state information from sensors and an observer. In this study, a 3-DOF dynamic model using a Brush nonlinear tire model is built, first, to model a 6 × 6 skid-steered wheeled vehicle in flat ground driving conditions. Then, an observer using the unscented Kalman filter with a strong tracking algorithm and adaptive noise matrix adjustment (AN-STUKF) is established to estimate vehicle motion states based on the 3-DOF dynamic model. Finally, the experiment is carried out in three different driving conditions to verify the accuracy and stability of the proposed method. The results show that the AN-STUKF method possesses better accuracy and tracking rate than the traditional UKF, and the phenomenon of ICRs shifting forward of the skid-steered wheeled vehicle is also verified.

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