The invention relates to a hybrid electric vehicle energy management method based on reinforcement learning. The method comprises the following steps: obtaining energy management strategies of a hybrid electric vehicle under different cycle conditions based on a Q-learning algorithm in reinforcement learning; writing the energy management strategy into a microcontroller; determining a current cycle working condition, acquiring current driving parameters and transmitting the current driving parameters to the microcontroller by the data acquisition system, acquiring a control action by the microcontroller based on an energy management strategy under the current cycle working condition, and transmitting the control action to the vehicle control unit; and adjusting the power system by the vehicle control unit according to the control action. Compared with the prior art, the energy management strategies of the hybrid electric vehicle under different cycle working conditions are obtained based on reinforcement learning and written into the microcontroller of the hybrid electric vehicle, the optimal control action under the current state can be quickly found only by looking up the table when the vehicle runs, the speed is high, And the sampling frequency of state monitoring of the hybrid electric vehicle at present or even in the future can be met.
本发明涉及一种基于强化学习的混合动力汽车能量管理方法,包括以下步骤:基于强化学习中的Q‑学习算法得到混合动力汽车在不同循环工况下的能量管理策略;将能量管理策略写入微型控制器;确定当前循环工况,数据采集系统获取当前驾驶参数并传输至微型控制器,微型控制器基于当前循环工况下的能量管理策略得到控制动作,并将控制动作传输至整车控制器;整车控制器根据控制动作调整动力系统。与现有技术相比,本发明基于强化学习得到混合动力汽车在不同循环工况下的能量管理策略并写入混合动力汽车的微型控制器,在汽车行驶时只需查表就可以快速找到当前状态下的最优控制动作,速度快,能够满足目前甚至未来的混合动力汽车状态监测的采样频率。
Hybrid electric vehicle energy management method based on reinforcement learning
一种基于强化学习的混合动力汽车能量管理方法
2021-01-29
Patent
Elektronische Ressource
Chinesisch
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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