An autonomous emergency braking strategy based on non‐linear model predictive deceleration control

Abstract

Surrogate safety measures (SSM) are used to assess the risk for autonomous emergency braking system (AEBS). Developing appropriate SSM and accurately executing the braking request are the key issues. Time‐to‐collision (TTC) is a typical time‐based SSM with limitations. By analyzing the braking process, this paper proposes a new SSM based on deceleration rate to avoid collision (DRAC). As the brake actuator, vehicle electronic stability control (ESC) system has many problems, such as large overshoot and pressure fluctuation. Considering the model of hydraulic control unit (HCU) and vehicle, a deceleration controller based on non‐linear model predictive control (NMPC) is proposed. Based on this, a layered AEBS architecture is proposed. The upper‐layer AEBS controller calculates the expected deceleration based on modified DRAC (MDRAC), and transmits it to the lower‐layer NMPC deceleration controller. Finally, the simulation and experimental tests are carried out. The results show that the system has a fast and stable response. In addition, the performance of the proposed AEBS strategy is tested according to the Euro‐NCAP test protocol. Comparing the results with the TTC method, the proposed method can improve the stability of the distance margin by more than 0.55 m, which ensures the safety and improves the stability of the vehicle.

Energy‐efficiency optimization and control for electric vehicle platooning with regenerating braking

“…The results in [22, 23] study the suitable and energy‐efficient controller design methods, respectively. Further, the results in [24] proposed An autonomous emergency braking strategy for elective vehicles. It is worth noting that there are lots of existing research results for single‐vehicle energy management; however, few of the studies focus on energy‐saving for the entire vehicle platooning, especially the EV platooning with regenerating braking.…”