Nonlinear Model Predictive Control for Integrated Energy-Efficient Torque-Vectoring and Anti-Roll Moment Distribution

Abstract

This study applies nonlinear model predictive control (NMPC) to the torque-vectoring and front-to-total anti-roll moment distribution control of a four-wheel-drive electric vehicle with in-wheel-motors, a brake-by-wire system, and active suspension actuators. The NMPC cost function formulation is based on energy efficiency criteria, and strives to minimize the power losses caused by the longitudinal and lateral tire slips, friction brakes, and electric powertrains, while enhancing the vehicle cornering response in steady-state and transient conditions. The controller is assessed through simulations using an experimentally validated high-fidelity vehicle model, along ramp steer and multiple step steer maneuvers, including and excluding the direct yaw moment and active anti-roll moment distribution actuations. The results show: i) the substantial enhancement of energy saving and vehicle stabilization performance brought by the integration of the active suspension contribution and torquevectoring; ii) the significance of the power loss terms of the NMPC formulation on the results; and iii) the effectiveness of the NMPC with respect to the benchmarking feedback and rule based controllers.

Robust super-twisting sliding mode controller for the lateral and longitudinal dynamics of rack steering vehicle

“…In terms of dynamics and control, the inertia cause by the friction force can be estimated and the longitudinal motion has potential to be controlled through direct actuation of the driving motors [6], [15]. At this point, the new challenge is opened in realizing mentioned proposal when the stiffness on tire motion frequently large in cornering motion.…”

“…Active steering system (ASS) or active front steering system (AFS) in [2], [3] is a popular rack steering vehicle (RSV) setup that is susceptible to inertial effects because to its non-skid arrangement. However, this vehicle is vulnerable to the collisions with the wall or off-road incidents, particularly on cornering tracks, as a consequence of overdriven [4]- [6]. The situation may become worse when this vehicle needs to pass through the uneven terrain and slippery terrain [7].…”

In-wheel motor control system used by four-wheel drive electric vehicle based on whale optimization algorithm-proportional–integral–derivative control

“…Nonlinear model predictive control was applied in the motor torque-vectoring and the control of front-to-total anti-roll moment distribution of fourwheel-drive EVs so that power loss was reduced and automotive steering response under stable and transient state were enhanced. 4 As the drive-wheel torque of the EV could be controlled, the four-wheel driving and braking torque were controlled through adjusting the output torque of the in-wheel motors. The pseudo inverse optimization algorithm was employed to optimize and distribute the driving torque of each wheel, so that transversal stability control of the EV could be realized.…”

“…Nonlinear model predictive control was applied in the motor torque-vectoring and the control of front-to-total anti-roll moment distribution of four-wheel-drive EVs so that power loss was reduced and automotive steering response under stable and transient state were enhanced. 4…”

A wheel slip ratio constraint control for ABS based on Tangent Type Barrier Lyapunov Function

“…Until now, constrained control algorithms have been investigated by some researchers. The existing constraint control methods mainly include: set invariance principle, 13,14 command governor, 15,16 reference governor, 17,18 extremum seeking control, 19 model predictive control, 20–23 etc. However, there are some limitations in these algorithms.…”