The invention provides an electric vehicle longitudinal control method based on deep reinforcement learning and sliding mode control, and aims to solve the problem that the vehicle following speed and the vehicle distance are not accurately controlled during longitudinal driving of an automatic driving vehicle. Firstly, a relation model of the distance, the speed and the acceleration between a controlled vehicle and a front vehicle is established; then, longitudinal control is conducted through a sliding-mode control algorithm in combination with a vehicle longitudinal dynamics model, and sliding-mode control gain is introduced to improve the anti-interference capacity of the system. Secondly, a depth deterministic strategy algorithm DDPG method is used to carry out adaptive setting on sliding mode control gain, and an expected acceleration is output to a lower layer controller. And finally, designing a switching control strategy of an accelerator and a brake based on the inverse longitudinal dynamics model to realize stable switching of vehicle driving and braking and complete vehicle longitudinal control. Deep reinforcement learning and sliding mode control are fused into longitudinal control of the electric vehicle, the control precision is high, the adaptability is high, and safe and efficient driving of the vehicle is guaranteed.
本发明提出一种基于深度强化学习与滑模控制的电动汽车纵向控制方法,旨在解决自动驾驶汽车纵向行驶存在跟车速度以及车间距控制不精的问题。首先,建立受控车辆与前车之间的距离、速度和加速度的关系模型;然后,结合车辆纵向动力学模型,采用滑模控制算法进行纵向控制,引入滑模控制增益以提高系统抗干扰能力。其次,利用深度确定性策略算法DDPG方法对滑模控制增益进行自适应整定,并输出期望加速度至下层控制器。最后,基于逆纵向动力学模型设计油门和刹车的切换控制策略,以实现车辆驱动和制动的平稳切换,完成车辆纵向控制。本发明将深度强化学习与滑模控制融合至电动汽车纵向控制中,控制精度高、适应性强,保证车辆实现安全高效行驶。
Electric vehicle longitudinal control method based on deep reinforcement learning and sliding mode control
一种基于深度强化学习与滑模控制的电动汽车纵向控制方法
2025-05-27
Patent
Electronic Resource
Chinese
IPC: | B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion |
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