摘要
针对插电式混合动力电动汽车(PHEV)动力系统结构复杂、建立精确的数学模型非常困难的特点和模糊控制器设计主要依靠专家经验、主观性较大的缺点,提出一种基于粒子群优化的模糊能量管理策略,保持按专家知识设计的模糊规则不变,采用粒子群优化算法优化模糊控制器隶属度函数参数。利用Matlab/simulink建立该策略模型,并将该模型嵌入到Advisor软件中进行仿真和对比分析,结果表明,采用基于粒子群优化的模糊能量管理策略与采用未优化的模糊能量管理策略相比,能够更有效地降低燃油消耗,减少尾气排放。
Because of complex system configuration, it is difficult to find precise mathematics model of PHEV drivetrain. The fuzzy controller design depends mainly on expert＇s experience and has much subjectivity. A fuzzy energy management strategy （EMS） based on particle swarm optimization （PSO） is presented. In this EMS, the fuzzy rules obtained from expert knowledge are unaltered and the PSO is used to optimize the parameters of membership functions of the fuzzy controller. The provided EMS model is built by Matlab/simulink and embedded in the Advisor software for simulation and comparative analysis. The result shows that, compared with the conventional fuzzy EMS, the fuzzy EMS based on PSO can more effectively reduce oil consumption and reduce tail gas emission.
出处
《系统仿真学报》
CAS
CSCD
北大核心
2018年第1期242-248,共7页
Journal of System Simulation
基金
国家自然科学基金(51405367)
关键词
插电式混合动力电动汽车
能量管理策略
粒子群优化
模糊控制
plug-in hybrid electric vehicle
energy management strategy
particle swarm optimization
fuzzy control
