摘要
针对传统模糊控制中规则库制定单一、动力系统与控制策略参数协调性不高等问题,提出一种基于全局优化算法的增程式电动汽车模糊控制策略。根据增程器最优效率曲线,分析并提取动态规划算法在不同需求及动力部件状态下的多能源分配规则,并结合传统工程经验作为模糊控制规则库制定依据;以燃油经济性为优化目标,利用粒子群算法优化整车动力部件与隶属度参数,获取具有全局优化性的EREV能量分配。最后,在MATLAB/Simulink中建立整车模糊控制策略模型,嵌入到ADVISOR中仿真并进行硬件在环测试。结果表明:所提出的控制策略适用于多种工况,与原车功率跟随控制策略相比,能控制动力电池SOC在合理范围内,同时提高整车燃油经济性。
Aiming at the problems of single rule base formulation and low coordination between power system and control strategy parameters in traditional fuzzy control, a fuzzy control strategy of extended-range electric vehicle based on global optimization algorithm was proposed. According to the optimal efficiency curve of the extender, the multi-energy distribution rules of dynamic programming algorithm under different demands and power parts state were analyzed and extracted and combined with traditional engineering experience as the basis for the formulation of fuzzy control rule base. With fuel economy as the optimization goal, particle swarm optimization algorithm was used to optimize the vehicle power components and membership parameters to obtain globally optimized EREV energy distribution. Finally, the fuzzy control strategy model of the whole vehicle was established in MATLAB/Simulink and embedded in ADVISOR for simulation and hardware in the loop test. The results show that the proposed control strategy is suitable for a variety of operating conditions. Compared with the original vehicle power following control strategy, it can control the SOC of the power battery within a reasonable range and improve the fuel economy of the vehicle.
作者
牛礼民
张泉泉
朱奋田
宗发新
郑飞宇
NIU Limin;ZHANG Quanquan;ZHU Fentian;ZHONG Faxin;ZHENG Feiyu(School of Mechanical Engineering,Anhui University of Technology,Maanshan 243032,Anhui,China;Guzhen County Power Supply Company,Bengbu 233700,Anhui,China)
出处
《重庆交通大学学报（自然科学版）》
CAS
CSCD
北大核心
2022年第2期137-145,共9页
Journal of Chongqing Jiaotong University(Natural Science)
基金
安徽省高校重点实验室开放基金资助项目(XJSK202104)
浙江省激光加工机器人重点实验室/中国机械工业激光精细加工与检测技术重点实验室开放基金项目(lzsy-07)。
关键词
车辆工程
EREV
动态规划
粒子群算法
模糊控制策略
全局优化
vehicle engineering
EREV
dynamic programming
particle swarm algorithm
fuzzy control strategy
global optimization
