基于模糊神经网络的智能能量管理策略研究——以混合动力电动汽车模型为例

A strategic study of the fuzzy neural network in intelligent energy management ——A case study of the hybrid electric vehicles

针对当前在标准行驶工况下开发的混合动力电动汽车优化控制策略不能根据变化的行驶工况动态调整控制策略的问题,提出一种基于模糊神经网络的混合动力电动汽车动态能量管理策略:先利用模糊神经网络进行工况识别,然后根据识别的工况类型动态调整自身控制参数.仿真实验显示,该策略可以有效提高混合动力汽车的燃油消耗,并降低污染物的排放量.

Under normal circumstances, hybrid electric vehicles fail to coordinate via automatic controlling optimization units. Therefore, this study concerns the use of the fuzzy neural network in intelligent energy management. Namely, identification is completed with the fuzzy neural network, and auto control parameters are adjusted. Simulation experiments show that this can effectively improve the efficiency of fuel consumption, and reduce the discharge of pollutants.