Autonomous drift controller for distributed drive electric vehicle with input coupling and uncertain disturbance

Hou, Xiaohui; Zhang, Junzhi; Ji, Yuan; Liu, Weilong; He, Chengkun

doi:10.1016/j.isatra.2021.03.009

Cited by 22 publications

(3 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With respect to (w.r.t.) autonomous drifting implementations not based on MPC, reference [23] uses a high-level fuzzyintegral sliding mode controller, and a low-level constrained optimization for control allocation (CA). In [24] and [25], desirable lateral error and sideslip angle are imposed, resulting in reference course and yaw rates.…”

Section: State-of-the-artmentioning

confidence: 99%

Enhanced Active Safety Through Integrated Autonomous Drifting and Direct Yaw Moment Control via Nonlinear Model Predictive Control

Stano,

Tavernini,

Montanaro

et al. 2024

IEEE Trans. Intell. Veh.

View full text Add to dashboard Cite

The introduction of active safety systems and advanced driver assistance systems has enhanced the control authority over the vehicle dynamics through specialized actuators, enabling, for instance, independent wheel torque control. During emergency situations, these systems step in to aid the driver by limiting vehicle response to a stable and controllable range of low longitudinal tire slips and slip angles. This approach makes vehicle behavior predictable and manageable for the average human driver; however, it is conservative in case of driving automation. In fact, past research has shown that exceeding the operational boundaries of conventional active safety systems enables trajectories that are otherwise unattainable. This paper presents a nonlinear model predictive controller (NMPC) for path tracking (PT), which integrates steering, front-to-total longitudinal tire force distribution, and direct yaw moment actuation, and can operate beyond the limit of handling, e.g., to induce drift, if this is beneficial to PT. Simulation results of emergency conditions in an intersection scenario highlight that the proposed solution provides significant safety improvements, when compared to the concurrent operation of PT algorithms and the current generation of vehicle stability controllers.

show abstract

Section: State-of-the-artmentioning

confidence: 99%

Enhanced Active Safety Through Integrated Autonomous Drifting and Direct Yaw Moment Control via Nonlinear Model Predictive Control

Stano,

Tavernini,

Montanaro

et al. 2024

IEEE Trans. Intell. Veh.

View full text Add to dashboard Cite

show abstract

“…In this section, the parameters of the virtual reference are optimized, and a simulation is conducted to verify the control performance of the designed VRFF on the vehicle simulation software, IPG CarMaker. IPG CarMaker has been widely used for validation on vehicle stability and active/semi-active suspension control over the last decade [52][53][54][55]. Through the simulation, the objective functions for the virtual reference are compared to one another.…”

Section: Simulationmentioning

confidence: 99%

Design of Virtual Reference Feedforward Controller for an Active Suspension System

et al. 2022

View full text Add to dashboard Cite

“…Since the four-wheel motors are mounted on each of the four wheels, this facilitates independent decoupling control of each wheel’s torque [ 2 ]. 4MIDEV is a typical overdrive system [ 3 , 4 ] with more actuators than control system degrees of freedom [ 5 , 6 , 7 ]. Under steering conditions, different control distribution methods yield different torque distribution results when four-wheel torque multi-objective optimization is performed to improve the stability and economy of 4WIDEV [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

Coordinated Optimal Control of AFS and DYC for Four-Wheel Independent Drive Electric Vehicles Based on MAS Model

Zhang

Wang

et al. 2023

Sensors

View full text Add to dashboard Cite

The problem that it is difficult to balance vehicle stability and economy at the same time under the starting steering condition of a four-wheel independent drive electric vehicle (4WIDEV) is addressed. In this paper, we propose a coordinated optimal control method of AFS and DYC for a four-wheel independent drive electric vehicle based on the MAS model. Firstly, the angular velocity of the transverse pendulum at the center of mass and the lateral deflection angle of the center of mass are decoupled by vector transformation, and the two-degree-of-freedom eight-input model of the vehicle is transformed into four two-degree-of-freedom two-input models, and the reduced-dimensional system is regarded as four agents. Based on the hardware connection structure and communication topology of the four-wheel independent drive electric vehicle, the reduced-dimensional model of 4WIDEV AFS and DYC coordinated optimal control is established based on graph theory. Secondly, the deviation of the vehicle transverse swing angular velocity and mass lateral deflection angle from their ideal values is oriented by combining sliding mode variable structure control (SMC) with distributed model predictive control (DMPC). A discrete dynamic sliding mode surface function is proposed for the ith agent to improve the robustness of the system in response to parameter variations and disturbances. Considering the stability and economy of the ith agent, an active front wheel steering and drive torque optimization control method based on SMC and DMPC is proposed for engineering applications. Finally, a hardware-in-the-loop (HIL) test bench is built for experimental verification, and the results show that the steering angle is in the range of 0–5°, and the proposed method effectively weighs the system dynamic performance, computational efficiency, and the economy of the whole vehicle. Compared with the conventional centralized control method, the torque-solving speed is improved by 32.33 times, and the electrical consumption of the wheel motor is reduced by 16.6%.

show abstract

Autonomous drift controller for distributed drive electric vehicle with input coupling and uncertain disturbance

Cited by 22 publications

References 24 publications

Enhanced Active Safety Through Integrated Autonomous Drifting and Direct Yaw Moment Control via Nonlinear Model Predictive Control

Enhanced Active Safety Through Integrated Autonomous Drifting and Direct Yaw Moment Control via Nonlinear Model Predictive Control

Design of Virtual Reference Feedforward Controller for an Active Suspension System

Coordinated Optimal Control of AFS and DYC for Four-Wheel Independent Drive Electric Vehicles Based on MAS Model

Contact Info

Product

Resources

About