The invention discloses a hybrid electric vehicle energy optimization control method and device, electronic equipment and a storage medium, and relates to the technical field related to vehicles. The method comprises the following steps: calculating a predicted vehicle speed and a predicted acceleration at each predicted moment after a current moment in a predicted time domain according to an actually measured vehicle speed and an actually measured acceleration, and calculating required power corresponding to the predicted vehicle speed according to the predicted vehicle speed and the predicted acceleration; the method comprises the following steps: selecting a battery charge state, a state in which required power is reinforcement learning and a motor torque and/or an engine torque which are corresponding to each prediction moment after the current moment in a prediction time domain as reinforcement learning actions, taking the minimum fuel consumption of the whole vehicle as an optimization target, and performing reinforcement learning to obtain a reinforcement learning result; obtaining an optimal torque distribution sequence corresponding to the minimum fuel consumption in the prediction time domain; and acting the first group of torques in the optimal torque distribution sequence on the vehicle. The requirement of a driver for the whole vehicle driving force can be met, and meanwhile the power source transmission power and the system energy efficiency can be optimized.

本发明公开一种混合动力车能量优化控制方法、装置、电子设备及存储介质，涉及车辆相关技术领域。方法包括：根据实测车速及实测加速度，计算预测时域内当前时刻之后每一预测时刻的预测车速和预测加速度，根据预测车速和预测加速度，计算预测车速对应的需求功率；选取预测时域内当前时刻之后每一预测时刻对应的电池荷电状态、需求功率为强化学习的状态，电动机转矩和/或发动机转矩为强化学习的动作，以整车燃油消耗量最小为优化目标，通过强化学习，获得预测时域内燃油消耗量最小所对应的最优转矩分配序列；将最优转矩分配序列中的第一组转矩作用到车辆上。本发明能满足驾驶员对整车驱动力的需求，同时又能优化动力源传递动力以及系统能量效率。