线系制动器摩擦制动力矩的建模与估计

C. M. Martinez, E. Velenis, D. Tavernini, Bo Gao, M. Wellers
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引用次数: 11

摘要

汽车工业的最新进展已将最新技术纳入汽车电气化,目的是减少燃料消耗,污染物排放,以及提高车辆性能和安全性。因此,电动汽车(EV)和混合动力汽车(HEV)已成为迫在眉睫的汽车未来,在车辆系统集成和控制方面提出了重要挑战。在这些车辆中,再生制动是目前能量回收的主要技术,提供了对制动扭矩的精确控制。然而,再生制动仍然需要传统摩擦制动的支持,主要是由于电池的限制。因此,两种制动策略的协调对于ABS和ESP等制动相关系统的安全驱动至关重要。不幸的是,由于系统输入不同,摩擦制动和再生制动之间的扭矩混合是一项复杂的任务;再生制动接收扭矩输入,而摩擦制动工作与压力输入。本文提出了摩擦制动转矩估计方法,以简化转矩混合,提高能量回收率和行驶安全性。制动扭矩的估算不仅考虑了卡钳处的压力,还考虑了制动盘温度和车轮转速对摩擦系数的影响。考虑到只有车轮速度传感器可用,无需在车辆平台上安装额外的传感器即可获得扭矩。使用扩展版的卡尔曼滤波器进行估计。所得结果令人满意,可以在安全的情况下提高命名系统的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modelling and estimation of friction brake torque for a brake by wire system
Recent advances in the automotive industry have incorporated the latest technology in vehicle electrification, with the aim to reduce fuel consumption, pollutants emissions, as well as enhance vehicle performance and safety. As a result, Electric Vehicles (EV) and Hybrid Electric Vehicles (HEV) have become the imminent automotive future, establishing important challenges in vehicle systems integration and control. In these vehicles, the regenerative braking is currently the major technique of energy recovery, providing accurate control on the brake torque applied. However regenerative brakes still need the support of conventional friction brakes, mainly due to the battery limitations. Consequently, the coordination of both braking strategies becomes critical for the safe actuation of braking related systems such as: ABS and ESP. Unfortunately, the torque blending between friction and regenerative brakes is a complicated task due to the different systems inputs; the regenerative brakes receive torque inputs, whilst the friction brakes work with pressure inputs. This paper proposes the friction brake torque estimation to simplify the torque blending, and improve the energy recovery and driving safety. The brake torque is estimated not only considering the pressure developed at the calipers, but also the brake disc temperature, and the wheel speed effect on the friction coefficient. The torque is obtained without installing additional sensors in the vehicle platform, considering that only wheel speed sensors are available. The estimation is performed using the extended version of the Kalman Filter. The results obtained are very satisfactory, and can improve the performance of the named systems in a safe way.
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