Four-wheel independent brake control to limit tire slip under unknown road conditions

Abstract This paper presents a four-wheel independent brake control method for vehicle stability under various road conditions without any tire–road friction information. For safety reasons, it is important to guarantee vehicle stability under unknown road conditions. The proposed algorithm is based on analysis of vehicle dynamic behavior on a tire slip force plane, and consists of three parts, Lateral stability decision, Desired motion governor, and Brake allocation. Lateral stability decision identifies whether vehicle is stable or unstable based on ‘Peak slip line’. The desired motion governor determines both target yaw moment and deceleration to stabilize the vehicle. The brake allocation decides brake inputs of four wheels to achieve desired motions. The proposed algorithm has been evaluated via both computer simulations and vehicle tests. The performance evaluation has been conducted on dry asphalt and wet pebble road using E-segment car. It has been shown via both computer simulations and vehicle tests that the proposed algorithm can successfully maintain the vehicle stability under various road conditions. The performance of the proposed algorithm has been compared to previously developed reference yaw rate and side slip angle tracking algorithm at simulation level and built-in Electronic Stability Control(ESC) logic in the vehicle tests. It has been also shown that the proposed control law provides improved performance compared to others.

[1]  Kirstin L. R. Talvala,et al.  Pushing the limits: From lanekeeping to autonomous racing , 2011, Annu. Rev. Control..

[2]  Masayoshi Tomizuka,et al.  A novel integrated chassis controller for full drive-by-wire vehicles , 2015 .

[3]  Chen Lv,et al.  Cooperative control of regenerative braking and hydraulic braking of an electrified passenger car , 2012 .

[4]  J. Christian Gerdes,et al.  Low friction emulation of lateral vehicle dynamics using four-wheel steer-by-wire , 2014, 2014 American Control Conference.

[5]  Daniel E. Koditschek,et al.  The controllability of planar bilinear systems , 1985, IEEE Transactions on Automatic Control.

[6]  Francesco Borrelli,et al.  Predictive Control of Autonomous Ground Vehicles With Obstacle Avoidance on Slippery Roads , 2010 .

[7]  Katsuhiko Ogata,et al.  Modern Control Engineering , 1970 .

[8]  Hui Zhang,et al.  Robust gain-scheduling energy-to-peak control of vehicle lateral dynamics stabilisation , 2014 .

[9]  Bernhard Schick,et al.  Simulation methods supporting homologation of Electronic Stability Control in vehicle variants , 2017 .

[10]  Seibum Choi,et al.  Vehicle Velocity Observer Design Using 6-D IMU and Multiple-Observer Approach , 2012, IEEE Transactions on Intelligent Transportation Systems.

[11]  Hans B. Pacejka,et al.  Tire and Vehicle Dynamics , 1982 .

[12]  Lars Nielsen,et al.  An Investigation of Optimal Vehicle Maneuvers for Different Road Conditions , 2013 .

[13]  Chen Lv,et al.  Mechanism analysis and evaluation methodology of regenerative braking contribution to energy efficiency improvement of electrified vehicles , 2015 .

[14]  Konghui Guo,et al.  A novel direct yaw moment controller for in-wheel motor electric vehicles , 2013 .

[15]  Eunhyek Joa,et al.  A tyre slip-based integrated chassis control of front/rear traction distribution and four-wheel independent brake from moderate driving to limit handling , 2018 .

[16]  Karl Hedrick,et al.  Estimation of the Maximum Tire-Road Friction Coefficient , 2003 .