The invention relates to a hybrid electric vehicle queue energy-saving driving hierarchical control method based on deep reinforcement learning, and belongs to the technical field of new energy automobiles, and the method comprises the following steps: S1, constructing a vehicle queue motion model according to a vehicle longitudinal dynamics model, and constructing vehicle queue motion constraint conditions; s2, acquiring operation data of the vehicle by using a V2V communication technology; s3, constructing an upper-layer cooperative adaptive cruise control model based on a double-delay depth deterministic strategy gradient algorithm, and providing vehicle speed data for a lower-layer energy management model; s4, constructing a lower layer energy management model based on the deep Q network and considering cabin temperature control; and S5, training the lower-layer energy management model. According to the invention, the safety and the energy-saving property of the vehicle queue of the hybrid electric vehicle can be effectively improved, and meanwhile, the thermal comfort of a cabin is improved.
本发明涉及一种基于深度强化学习的混合动力汽车队列节能驾驶分层控制方法,属于新能源汽车技术领域,包括以下步骤:S1:根据车辆纵向动力学模型构建车辆队列运动模型,并构建车辆队列运动约束条件;S2:利用V2V通信技术获取车辆的运行数据;S3:构建基于双延迟深度确定性策略梯度算法的上层协同自适应巡航控制模型,为下层能量管理模型提供车速数据;S4:构建基于深度Q网络的考虑座舱温控的下层能量管理模型;S5:训练所述下层能量管理模型。本发明能够有效地提升混合动力汽车车辆队列的安全性和节能性,同时提高了座舱热舒适性。
Hybrid electric vehicle queue energy-saving driving hierarchical control method based on deep reinforcement learning
基于深度强化学习的混合动力汽车队列节能驾驶分层控制方法
25.04.2025
Patent
Elektronische Ressource
Chinesisch
IPC: | G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G05B Steuer- oder Regelsysteme allgemein , CONTROL OR REGULATING SYSTEMS IN GENERAL / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS |
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