自适应车辆队列中动力总成时间常数的正确在线估计
Correct Online Estimation of the Powertrain Time Constants in Adaptive Vehicular Platooning
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中文总结 AI 辅助
本研究提出一种自适应车辆队列方法，通过修改复合自适应控制框架，在无需持续激励的情况下正确估计动力总成时间常数，且具有无需测量加速度导数等优势，经CarSim实验验证其鲁棒性与实用性。
中文摘要 AI 辅助
在纵向队列中，关键的不确定性来源之一是车辆的动力总成时间常数。由于这类时间常数出现在队列动力学的输入矩阵中，采用要求持续激励的方法无法实现其正确估计，而采用要求输入矩阵已知的方法则不可能实现其正确估计。本研究提出一种新颖的自适应纵向队列方法，可实现动力总成时间常数的正确估计。为达成正确估计，对复合自适应控制框架及其稳定性分析进行了适当修改，以处理自适应律设计中的时间常数不确定性。所得队列协议保证估计的时间常数收敛到真实值，且无需持续激励：仅需加速度的导数在一段可能较短的瞬态过程中不为零，这是一种极为宽松的激励条件。与最先进的队列解决方案的对比显示，该方法具有无需测量加速度导数、无需收集过去数据等优势。基于CarSim的队列实验也验证了所提设计的鲁棒性和实用性。
英文摘要
In longitudinal platooning, some key sources of uncertainty are the powertrain time constants of the vehicles. Because such time constants appear in the input matrix of the platooning dynamics, their correct estimation is either impractical with methods requiring persistence of excitation, or impossible with methods requiring the input matrix to be known. This work proposes a novel adaptive longitudinal platooning method with correct estimation of the powertrain time constants. To achieve correct estimation, the composite adaptive control framework and its stability analysis are suitably modified to handle the time constant uncertainty in the design of the adaptive law. The result is a platooning protocol that guarantees convergence of the estimated time constants to their true values without the need for persistence of excitation: it is sufficient the derivative of the acceleration to be nonzero over a possibly short transient, an extremely relaxed excitation condition. Comparisons with state-of-the-art platooning solutions reveal advantages such as no required measurements of acceleration derivative nor collection of past data. The robustness and practicality of the proposed design is also verified with CarSim-based platooning experiments.
