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为了在不牺牲油耗和行驶里程的条件下优化插电式混合动力汽车的能量分配过程,提升插电式混合动力汽车的节能潜力以及续航能力,提高插电式混合动力汽车能量管理策略的鲁棒性,以等效燃油消耗最小策略为基础,结合车辆对行驶路况变化的适应性研究,制定了相应的能量管理策略。以标准工况数据为基础开发车辆行驶路况识别器,在标准工况中选取相关的特征值参数,建立特征值参数矩阵。利用标准工况特征值参数矩阵训练BP神经网络识别器,使之能够完成对不同行驶路况的识别。将识别后的路况结果传递给以等效燃油消耗最小策略为基础的能量管理策略,针对不同的行驶路况给出能量流动的优化控制。研究结果表明:在完成对行驶路况的自适应识别之后,插电式混合动力汽车的发动机工作点更加集中在BSFC曲线附近,发动机工作在高效率区间的频率提升;使用自适应路况能量管理策略的插电式混合动力汽车,根据识别后的路况可灵活调整发动机和电池的能量输出,降低油耗并保护了电池的寿命。
In order to optimize the energy distribution process of plug-in hybrid vehicles without sacrificing fuel consumption and mileage and to improve the energy saving potential and endurance of plug-in hybrid vehicles, the robustness of energy management strategies for plug-in hybrid vehicles Based on the minimum equivalent fuel consumption strategy, the corresponding energy management strategy is formulated based on the adaptive study of the vehicle to the driving conditions. Based on the standard working condition data, a road traffic recognizer is developed to select the relevant eigenvalue parameters in the standard operating conditions and establish the eigenvalue parameter matrix. The BP neural network identifier is trained by using the standard working parameter eigenvalue parameter matrix to make it possible to recognize the different driving conditions. The identified road conditions are passed to the energy management strategy based on the minimum equivalent fuel consumption strategy, and the optimal control of energy flow is given for different driving conditions. The results show that after the adaptive identification of driving conditions is completed, the engine operating point of the plug-in hybrid vehicle is more concentrated near the BSFC curve and the frequency of the engine operating in the high-efficiency interval is increased. Using the adaptive traffic energy management strategy Plug-in hybrid vehicles, based on the identified traffic flexibility to adjust the engine and battery energy output, reduce fuel consumption and protect the battery life.