【摘要】 为深入研究自动驾驶车辆的节能跟踪控制，并有效减小坡度对车辆燃油经济性和速度跟踪性能的不利影响，提出了一种新的自动驾驶车辆节能速度跟踪控制策略。该策略特别设计了适用于变速与匀速两种行驶状态下的模型预测控制（MPC）方法，同时建立了一个能够考虑坡度的车辆速度跟随模型。为了进一步提升控制精度，还引入了线性二次型调节器（LQR）作为辅助控制手段。此外，采用贝叶斯优化算法对MPC控制器的关键参数进行了精细调校。实验结果表明，通过在MATLAB/Simulink平台上的仿真测试，所提出的控制方案能耗降低9.1%，实现了预期的节能效果，同时车辆的速度最大跟踪误差减小59%，提高了车辆的速度跟踪性能，充分证明了其有效性和实用性。更多还原

【Abstract】 In order to further study the energy-saving tracking control of autonomous vehicles and effectively reduce the adverse effects of slope on vehicle fuel economy and speed tracking performance, an energy-saving speed tracking control strategy for autonomous vehicles was proposed. In this strategy, a model predictive control(MPC) method is specially designed for two driving states, and a vehicle speed following model that can consider the slope is established. In order to further improve the control accuracy, a linear quadratic regulator( LQR) is also introduced as an auxiliary control method. In addition, the Bayesian optimization algorithm was used to finely tune the key parameters of the MPC controller. The experimental results show that the energy consumption of the proposed control scheme is reduced by 9.1%through the simulation test on the MATLAB/Simulink platform, which realizes the expected energy-saving effect, and the maximum tracking error of the vehicle speed is reduced by 59%, which improves the speed tracking performance of the vehicle, which fully proves its effectiveness and practicability.更多还原