Tire Force Control Research Articles

Integrated optimization control strategy for vehicle longitudinal and lateral assisted driving

In order to coordinate the control objectives of the longitudinal and lateral auxiliary driving system of the vehicle and the vehicle dynamics control requirements, this paper takes the four-wheel independent drive electric vehicle as the control object, and combines deep learning and model predictive control to establish the vehicle generalized control force prediction-dynamic optimization distribution control strategy. The upper-level algorithm calculates the generalized control force that meets the vehicle control requirements according to the reference objectives of the longitudinal and lateral auxiliary driving strategies; the middle-level module includes the vehicle expected generalized force neural network prediction model and the active set numerical solution algorithm; the lower level calculates the tire slip rate and sideslip angle according to the expected tire force, realizes the tire force control requirements by controlling the motor torque and the braking system, and adjusts the vehicle movement direction through the steering system. This paper uses simulation tests and hardware-in-the-loop tests to verify the algorithm. The results show that the established algorithm can simultaneously meet the longitudinal and lateral control requirements of the vehicle, with a lateral path following error of 0.0117 m and a vehicle speed error of 0.59 km/h.

NMPC-based controller for vehicle longitudinal and lateral stability enhancement under extreme driving conditions

This paper proposes a real-time NMPC-based controller for four-wheel independent motor-drive electric vehicles to improve vehicle longitudinal and lateral stability under extreme driving conditions. First, considering the interactive and highly coupled longitudinal–lateral vehicle dynamics, a combined-slip tire model is applied to develop the stability controller on low friction coefficient surfaces. Second, the wheel slip ratios and slip angles are selected as the virtual control inputs of the NMPC controller to concurrently achieve three main control objectives: Slip control, lateral stability control, and handling performance improvement. Simultaneously, multiple safety constraints are contained. Then, based on the dynamic relationships between the longitudinal tire force and virtual control inputs, the wheel slip ratios and slip angles obtained from the NMPC controller are converted into additional torques acting directly on each wheel. Finally, the control performance is investigated by co-simulation with MATLAB/Simulink and CarSim, and a hardware-in-the-loop simulation system. The effect of uncertainties on control performance is also verified. The results show that the proposed controller can rapidly solve the optimization problem, and vehicle overall stability are efficiently enhanced under extreme conditions. The robustness of the controller is proved with uncertainties on the road adhesion coefficient and vehicle mass.

Tire Force Control and Tire Workload Maximization Method for Independent-four-wheel-drive Electric Vehicle

Tire Force Control and Tire Workload Maximization Method for Independent-four-wheel-drive Electric Vehicle

Optimal Tire Force Control & amp; Allocation for Longitudinal and Yaw Moment Control of HEV with eAWD Capabilities

Optimal Tire Force Control & amp; Allocation for Longitudinal and Yaw Moment Control of HEV with eAWD Capabilities

Tire Force Control Strategy for Semi Active Magnetorheological Damper Suspension System Using Quarter Heavy Vehicle Model

This paper proposed semi active controller scheme for magnetorheological (MR) damper of a heavy vehicle suspension known as Tire Force Control (TFC). A reported algorithm in the literature to reduce tire force is Groundhook (GRD). Thus, the objective of this paper is to investigate the effectiveness of the proposed TFC algorithm compared to GRD. These algorithms are applied to a quarter heavy vehicle models, where the objective of the proposed controller is to reduce unsprung force (tire force). The simulation model was developed and simulated using MATLAB Simulink software. The use of semi active MR damper using TFC is analytically studied. Ride test was conducted at three different speeds and three bump heights, and the simulation results of TFC and GRD are compared and analysed. The results showed that the proposed controller is able to reduced tire force significantly compared to GRD control strategy.

Robust Wheel Torque Control for Traction/Braking Force Tracking Under Combined Longitudinal and Lateral Motion

Slip-ratio-based methods are commonly used to control the wheel torque such that the wheel dynamics is stabilized and the desired traction/braking force is attained; however, slip-ratio-based controllers are incompetent for precise longitudinal tire force tracking due to nonparametric tire model uncertainties. Force tracking performance further deteriorates whenever the tire is under combined longitudinal and lateral motion. In this paper, we propose an observer-based tire force control scheme that guarantees to achieve the desired longitudinal tire force accurately and robustly with respect to tire model uncertainties, changes in road conditions, and simultaneous lateral motion. Convergence of the force estimation and tracking errors is rigorously proved by the Lyapunov method. Then, simulations are conducted to verify the robust and accurate performance in longitudinal tire force estimation and tracking under a series of severe driving conditions.

Advanced Motion Control of Electric Vehicles Based on Robust Lateral Tire Force Control via Active Front Steering

This paper presents a new motion control method based on robust lateral tire force control (LTFC) to improve vehicle stability or maneuverability. During cornering, vehicle motion is totally governed by lateral forces acting on tires. Thus, the real-time information on tire forces provides advantages in vehicle motion control. Since the lateral tire force measurements are available by using multisensing hub (MSHub) units which were invented by NSK Ltd., the direct LTFC is realizable via active front steering. In control design, a robust control method, e.g., two degree-of-freedom control (2-DOF) with a disturbance observer, is used for improving the reference tracking performance. Moreover, the stability of the proposed control system is discussed by using small gain theorem. The proposed motion controller is implemented on an experimental in-wheel-motor-driven electric vehicle and its performance and effectiveness are verified by field tests. Finally, practical applications of lateral tire force sensors to vehicle motion control systems are discussed.

Dynamic Tire Force Control by Semiactive Suspensions

This paper presents a semiactive suspension control algorithm to reduce dynamic tire forces and it includes the development and application of observers for bilinear systems with unknown disturbances. The peak dynamic tire forces, which are greatly in excess of static tire forces, are highly dependent on the dynamic characteristics of vehicle suspensions. One way to reduce dynamic tire forces is to use advanced suspension systems such as semiactive suspensions. Semiactive control laws to reduce dynamic tire forces are investigated and a bilinear observer structure for bilinear systems with unknown disturbances is formulated such that the estimation error is independent of the unknown external disturbances and the error dynamics are stable for bounded inputs. The motivation for the development of a disturbance decoupled bilinear observer comes from the state estimation problem in semiactive suspensions. An experimental study on the performance of a semiactive suspension to reduce the dynamic tire forces is made via a laboratory vehicle test rig. The semiactive suspension has been implemented by using a modulable damper, accelerometers and a personal computer. Experimental studies show that the performance of the semiactive suspension is close to that of the best passive suspension for all frequency ranges in the sense of minimizing the dynamic tire forces and that the dynamic tire force can be replaced by the estimated one. The dynamic tire forces for both passive and semiactive control test cases are compared to show the potential of a semiactive suspension to reduce the dynamic tire forces.