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On pre-emptive vehicle stability control
Vehicle System Dynamics ( IF 3.6 ) Pub Date : 2021-03-30 , DOI: 10.1080/00423114.2021.1895229
Alberto Parra 1, 2 , Davide Tavernini 3 , Patrick Gruber 3 , Aldo Sorniotti 3 , Asier Zubizarreta 2 , Joshué Pérez 1
Affiliation  

Future vehicle localisation technologies enable major enhancements of vehicle dynamics control. This study proposes a novel vehicle stability control paradigm, based on pre-emptive control that considers the curvature profile of the expected path ahead in the computation of the reference direct yaw moment and braking control action. The additional information allows pre-emptive trail braking control, which slows down the vehicle if the predicted speed profile based on the current torque demand is deemed incompatible with the reference trajectory ahead. Nonlinear model predictive control is used to implement the approach, in which also the steering angle and reference yaw rate provided to the internal model are varied along the prediction horizon, to account for the expected vehicle path. Two pre-emptive stability control configurations with different levels of complexity are proposed and compared with the passive vehicle, and two state-of-the-art nonlinear model predictive stability controllers, one with and one without non-pre-emptive trail braking control. The performance is assessed along obstacle avoidance tests, simulated with a high-fidelity model of an electric vehicle with in-wheel motors. Results show that the pre-emptive controllers achieve higher maximum entry speeds – up to ∼34% and ∼60% in high and low tyre-road friction conditions – than the formulations without preview.



中文翻译:

关于先发制人的车辆稳定性控制

未来的车辆本地化技术可以大大增强车辆动态控制。本研究提出了一种新的车辆稳定性控制范式,基于先发制人的控制,该控制在计算参考直接横摆力矩和制动控制动作时考虑了前方预期路径的曲率分布。附加信息允许先发制人的跟踪制动控制,如果基于当前扭矩需求的预测速度曲线被认为与前方的参考轨迹不兼容,这会使车辆减速。非线性模型预测控制用于实现该方法,其中提供给内部模型的转向角和参考偏航率沿预测范围变化,以考虑预期的车辆路径。提出了两种具有不同复杂程度的先发制人的稳定性控制配置,并与被动车辆进行了比较,以及两种最先进的非线性模型预测稳定性控制器,一种具有和一种不具有非先发制人的跟踪制动控制。性能通过避障测试进行评估,并使用带有轮毂电机的电动汽车的高保真模型进行模拟。结果表明,与没有预览的配方相比,先发制人的控制器实现了更高的最大进入速度——在高和低轮胎路面摩擦条件下高达 ∼34% 和 ∼60%。性能通过避障测试进行评估,并使用带有轮毂电机的电动汽车的高保真模型进行模拟。结果表明,与没有预览的配方相比,先发制人的控制器实现了更高的最大进入速度——在高和低轮胎路面摩擦条件下高达 ∼34% 和 ∼60%。性能通过避障测试进行评估,并使用带有轮毂电机的电动汽车的高保真模型进行模拟。结果表明,与没有预览的配方相比,先发制人的控制器实现了更高的最大进入速度——在高和低轮胎路面摩擦条件下高达 ∼34% 和 ∼60%。

更新日期:2021-03-30
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