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Closed-loop controller for post-impact vehicle dynamics using individual wheel braking and front axle steering

机译:使用单独的车轮制动和前轴转向功能的碰撞后车辆动力学的闭环控制器

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摘要

This paper presents a vehicle path controller for reducing the maximum lateral deviation (Ymax) after an initial impact in a traffic accident. In previous research, a Quasi-Linear Optimal Controller (QLOC) was proposed and applied to a simple vehicle model with individually controlled brake actuators. QLOC uses non-linear optimal control theory to provide a semiexplicit approximation for optimal post-impact path control, and in principle can be applied to an arbitrary number of actuators. The current work extends and further validates the control method by analysing the effects of adding an active front axle steering actuator at different post-impact kinematics, as well as increasing the fidelity of the vehicle model in the closed-loop controlled system. The controller performance is compared with the results from open-loop numerical optimisation which uses the same vehicle model. The inherent robustness properties of the QLOC algorithm are demonstrated by its direct application to an independent high-fidelity multi-body vehicle model. Towards real-time implementation, the algorithm is further simplified so that the computational efficiency is enhanced, whereas the performance is shown not to be degraded.
机译:本文提出了一种车辆路径控制器,用于减少交通事故中的初始冲击后的最大横向偏差(Ymax)。在先前的研究中,提出了一种拟线性最优控制器(QLOC),并将其应用于具有独立控制的制动执行器的简单车辆模型。 QLOC使用非线性最优控制理论来提供最佳冲击后路径控制的半显式逼近,并且原则上可以应用于任意数量的执行器。当前的工作扩展并通过分析在不同的碰撞后运动学上增加主动前轴转向执行器的效果,以及在闭环控制系统中提高车辆模型的逼真度来进一步验证控制方法。将控制器性能与使用相同车辆模型的开环数值优化结果进行比较。通过将QLOC算法直接应用于独立的高保真多体车辆模型,证明了QLOC算法固有的鲁棒性。在实时实现方面,该算法得到了进一步简化,从而提高了计算效率,而性能却没有下降。

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