摘要
在ADVISOR软件环境中建立燃料电池增程式电动汽车动力系统模型,利用该模型设计基于模糊控制理论的整车能量管理策略,并以车辆最大续驶里程为优化目标,利用遗传算法对模糊函数和模糊规则进行优化.对比发现优化后的模糊控制管理策略能改善燃料经济性,提高整车续驶里程.典型工况下不同能量管理策略的整车仿真结果显示,本文所制定的模糊控制能量管理策略优于常见的恒温器及功率跟随能量管理策略,适合用于增程式电动汽车.
The power train system model of a fuel cell extended - range electric vehicle ( E - REV) was modeled in the ADVISOR software environment, based on which a fuzzy control energy management strategy was designed. Taking the maximum driving range of the vehicle as the target, the parameters of fuzzy controller was optimized by genetic algorithm. After optimizing, the driving mileage and economic performance were improved greatly. The simulation results under typical driving conditions show that the designed fuzzy control energy man- agement strategy has a better fuel economic performance than those of common thermostat and power following energy management strategies and can be used in E -REVs.
出处
《佳木斯大学学报(自然科学版)》
CAS
2013年第2期174-178,共5页
Journal of Jiamusi University:Natural Science Edition
基金
国家"863"项目(2011AA11A265)
关键词
增程器
增程式电动车
模糊控制
遗传算法
优化
ADVIOSR
range extender
extended -range electric vehicle
fuzzy control
genetic algorithm
optimi- zation
advisor