Switchable MPC-based multi-objective regenerative brake control via flow regulation for electric vehicles

Abstract

Recent investigations of the electric braking booster (E-Booster) focus on its potential to enhance brake energy regeneration. A vehicle’s hydraulic system is composed of the E-Booster and electric stability control to control the master cylinder and wheel cylinders. This paper aims to address the independent closed-loop control of the position and pressure as well as the maintenance of the pedal feel. To track both the reference signals related to piston displacement and the wheel cylinder pressure, an explicit model predictive control (MPC) is developed. First, the new flow model is introduced as the foundation for controller design and simulation. Next, in accordance with the operational conditions, the entire system is divided into three switchable subsystems. The three distributed MPCs are constructed based on the linearized subsystems, and a state machine is used to perform the state jump across the controllers. A linear piecewise affine control law can then be obtained by solving the quadratic program (QP) of explicit MPC. Afterwards, the non-linear extended Kalman filter including the recorded time-variant process noise is used to estimate all the state variables. The effectiveness of the explicit MPC is evidenced by the simulations compared with a single MPC in regenerative and dead-zone conditions. The proposed controller decreases the latency significantly by 85 milliseconds, which also helps to improve accuracy by 22.6%. Furthermore, the pedal feel remains consistent, even when factoring in the number of vibrations caused by the inherent hydraulic characteristic of pressure versus volume.

Hybrid Nonlinear Model Predictive Motion Control of a Heavy-duty Bionic Caterpillar-like Robot

“…3.1, the parameters Q 1 and Q 2 significantly influence the optimization outcome of Eq. (17). A high value for Q 1 or a low value for Q 2 can result in oscillations around the reference signal.…”

“…The simulation validated the efficacy of pressure control. There are also similar applications discussed in the references [16,17]. Reference [18] introduced an MPC-based controller to enhance the dynamic performance of an excavator boom, resulting in a substantial reduction in cost function and vibration.…”

Synchronization control of blanket remote maintenance robot based on MPC-CCC algorithm

“…Balint Varga et al proposed MPC in mid-sized heavy-duty vehicle manipulator systems with a hydraulic working arm and got smoother motions after the dual-trajectories optimization [12]. Qin Shi et al and Mingming Mei et al used MPC to get better performance in pressure-demand control of electro-hydraulic braking systems [13, 14]. Heybroek Kim et al proposed MPC in hydraulic multichamber actuator force control and got good force tracking performance [15].…”