模糊C均值BP神经网络算法及其应用

Application of BP neural network algorithm based on fuzzy C-means clustering

为了提高串联混合动力汽车(HEV)的燃油经济性,提出了一种新型能量管理算法。针对全局优化和瞬时优化算法的缺点,本文提出了基于模糊C均值的神经网络能量管理算法。首先利用猴群算法得到的全局最优规则作为待选样本,然后采用模糊C均值技术对这些样本分类,在每一类中训练神经网络。实验仿真表明,该算法可以获得全局最优解,获得了好的燃油经济性,具有较好的应用前景。

In order to improve fuel economy of series hybrid electric vehicle （HEV） , a new energy management （EM） algorithm was presented considering the shortcomings of global and instantaneous optimum methods. The improved monkey algorithm was used to get global EM rules. The training samples were classified by fuzzy C-means, and in each class were used for training neural networks. The EM strategy can simulate the global optimum rules, which ensures a good fuel economy of HEY. It has practicality value.