摘要
以ISG柴油混合动力客车整车控制策略为基础,综合考虑客车燃油经济性和排放,提出一种基于模糊神经网络的能量分配策略,该策略根据模糊控制原理,结合人工神经网络自主学习功能,以电池SOC、整车需求转矩以及发动机转速为模糊输入来确定发动机和电机的最佳输出转矩分配,再以神经网络对控制的模糊规则进行记忆。仿真结果表明,该策略比普通逻辑控制更加有利于燃油经济性的提高,并在一定程度上改善了排放性能。
Based on vehicle control strategy for hybrid electric bus with diesel engine and ISG motor, a fuzzy neural network-based energy distribution strategy is put forward with considerations on both fuel consumption and emissions. The stategy combines the principle of fuzzy control with the self-learning function of artificial neural network to determine the optimal torque distribution between ISG and engine with fuzzy inputs of battery SOC, required torque and engine speed, and then using neural network to memorize the fuzzy control rules. Simulation results indicate that compared with ordinary logic control, this strategy is more conducive to better fuel economy and certain improvement in emissions performance.
出处
《汽车工程》
EI
CSCD
北大核心
2008年第2期121-125,共5页
Automotive Engineering
