To ensure commercial vehicle stability during trajectory tracking, this paper proposes a comprehensive stability control system based on stability analysis that incorporates Active Front Steering (AFS), Direct Yaw Moment Control (DYC), and Active Suspension System (ASS). A stability region for lateral speed and yaw rate is created by quantitatively describing the evolution behavior of the vehicle model using the Lyapunov exponent theory. Considering vehicle rollover stability, the yaw rate is further constrained based on the Load Transfer Ratio (LTR). To track vehicle dynamics in unstable regions, an upper-level controller called Model Predictive Control (MPC) calculates additional front wheel steering angles, yaw moments, and roll moments. A lower-level allocation controller determines the actual actuator commands, such as front wheel steering angle, additional hub motor torque, and additional vertical force. This control architecture ensures that the vehicle maintains lateral, yaw, and rollover stability. The feasibility of this approach is supported through co-simulations using TruckSim and MATLAB-Simulink, which demonstrates its efficacy in maintaining vehicle stability across multiple dimensions.
XuHHuangG. Analysis of factors influencing the severity of heavy and medium truck traffic accidents. In: 2023 7th international conference on transportation information and safety (ICTIS), Xi’an, China, 4–6 August 2023, pp.1692–1698. New York: IEEE.
2.
YanMChenWWangJ, et al. Characteristics and causes of particularly major road traffic accidents involving commercial vehicles in China. Int J Environ Res Public Health2021; 18: 3878.
3.
Pourroostaei ArdakaniSCheshmehzangiA (ed.) Big data analytics and the future of smart transport and healthcare systems. In: Big data analytics for smart transport and healthcare systems. Singapore: Springer, 2023, pp. 175–184.
4.
SukumaranRGaurkarPVSubramanianSC.Integrated rollover prevention and antilock brake system for heavy commercial road vehicles. IEEE Access2023; 11: 124081–124097.
5.
NamK.Application of novel lateral tire force sensors to vehicle parameter estimation of electric vehicles. Sensors2015; 15: 28385–28401.
6.
WangHZhouJHuC, et al. Vehicle lateral stability control based on stability category recognition with improved brain emotional learning network. IEEE Trans Veh Technol2022; 71: 5930–5943.
7.
ZhuZTangXQinY, et al. A survey of lateral stability criterion and control application for autonomous vehicles. IEEE Trans Intell Transp Syst2023; 24: 10382–10399.
8.
XiongL.Stability criterion for the vehicle under critical driving situation. J Mech Eng2015; 51: 103.
9.
LiuWXiongLLengB, et al. Vehicle stability criterion research based on phase plane method. SAE technical paper 2017-01-1560, 2017.
10.
ZhangXWangPLinJ, et al. Real-time nonlinear predictive controller design for drive-by-wire vehicle lateral stability with dynamic boundary conditions. Fundam Res2021; 2: 131–143.
11.
ChoJHuhK.Active front steering for driver’s steering comfort and vehicle driving stability. Int J Automot Technol2019; 20: 589–596.
12.
LuYLingJWangF, et al. An active front steering system design considering the CAN network delay. IEEE Trans Transp Electrif2023; 9: 5244–5256.
13.
ParkJYNaSChaH, et al. Direct yaw moment control with 4WD torque-vectoring for vehicle handling stability and agility. Int J Automot Technol2022; 23: 555–565.
14.
ShiXWangHChenL, et al. Robust path tracking control of distributed driving six-wheel steering commercial vehicle based on coupled active disturbance rejection. IEEE Trans Veh Technol2023; 72(11): 13940–13952.
15.
LiQChenZSongH, et al. Model predictive control for speed-dependent active suspension system with road preview information. Sensors2024; 24: 2255.
16.
YuMEvangelouSADiniD.Advances in active suspension systems for road vehicles. Engineering2024; 33: 160–177.
17.
YuZFengYXiongL.Review on vehicle dynamics control of distributed drive electric vehicle. J Mech Eng2023; 49(8): 105–114.
18.
JinXYuZYinG, et al. Improving vehicle handling stability based on combined AFS and DYC system via robust Takagi-Sugeno fuzzy control. IEEE Trans Intell Transp Syst2028; 19: 2696–2707.
19.
WuJChengSLiuB, et al. A human-machine-cooperative-driving controller based on AFS and DYC for vehicle dynamic stability. Energies2017; 10: 1737.
20.
ZhaiLWangCHouY, et al. MPC-based integrated control of trajectory tracking and handling stability for intelligent driving vehicle driven by four hub motor. IEEE Trans Veh Technol2022; 71: 2668–2680.
21.
RajamaniRPiyabongkarnDN.New paradigms for the integration of yaw stability and rollover prevention functions in vehicle stability control. IEEE Trans Intell Transp Syst2013; 14: 249–261.
22.
HerHKohYJoaE, et al. An integrated control of differential braking, front/rear traction, and active roll moment for limit handling performance. IEEE Trans Veh Technol2016; 65: 4288–4300.
23.
LiLLuYWangR, et al. A three-dimensional dynamics control framework of vehicle lateral stability and rollover prevention via active braking with MPC. IEEE Trans Ind Electron2017; 64: 3389–3401.
24.
XuHZhaoYPiW, et al. Integrated control of active front wheel steering and active suspension based on differential flatness and nonlinear disturbance observer. IEEE Trans Veh Technol2022; 71: 4813–4824.
25.
ZhaoHChenWZhaoJ, et al. Modular integrated longitudinal, lateral, and vertical vehicle stability control for distributed electric vehicles. IEEE Trans Veh Technol2019; 68: 1327–1338.
26.
ShiXWangHChenL, et al. Hybrid trigger cooperative control of six-wheeled commercial vehicles with multiple sub-systems based on sub-regional linearization model. Simul Model Pract Theory2024; 135: 102973.
27.
SunYWangXWuQ, et al. Calculation of Lyapunov exponents using radial basis function networks for stability analysis of nonlinear control systems. In: Proceedings of the 2011 American control conference, San Francisco, CA, USA, 29 June–1 July 2011.
28.
RathJJDefoortMVeluvoluKC.Rollover index estimation in the presence of sensor faults, unknown inputs, and uncertainties. IEEE Trans Intell Transp Syst2016; 17: 2949–2959.
29.
LenzoBZanchettaMSorniottiA, et al. Yaw rate and sideslip angle control through single input single output direct yaw moment control. IEEE Trans Control Syst Technol2021; 29: 124–139.
30.
YuSShengEZhangY, et al. Efficient nonlinear model predictive control of automated vehicles. Mathematics2022; 10: 4163.
31.
SunCZhangXZhouQ, et al. A model predictive controller with switched tracking error for autonomous vehicle path tracking. IEEE Access2019; 7: 53103–53114.
32.
WuLLiuJVazquezS, et al. Sliding mode control in power converters and drives: a review. IEEE CAA J Autom Sin2022; 9: 392–406.
