混合动力汽车能量管理策略研究
Research on Energy Management Strategy of Hybrid Electric Vehicle
李东兵 1王妮 2马涛涛3
作者信息
- 1. 长春汽车工业高等专科学校,吉林 长春 130013
- 2. 吉林大学,吉林 长春 130012
- 3. 长春一汽股份有限公司,吉林 长春 130011
- 折叠
摘要
针对混合动力汽车能源管理策略中能量分布不合理的现象,同时降低混合动力汽车的能耗和电池寿命衰减率,在动力系统结构的基础上,提出了一种将RBF神经网络和动态规划方法相结合用于混合动力汽车的能量管理策略.RBF神经网络用于在预测时域中预测车速,获得预测时域中的车辆需求扭矩,动态规划方法用于优化求解预测时域,实现合理分配发动机和电机扭矩.通过仿真与传统能源管理策略进行比较,验证了该方法的优越性和准确性.实验结果表明,与传统策略相比,提出的能源管理策略可以显著提高燃油经济性,降低能耗15.47%,具有实际应用潜力.
Abstract
Aiming at the phenomenon of unreasonable energy distribution in the energy management strategy of hybrid electric vehi-cles,while reducing the energy consumption and battery life decay rate of hybrid electric vehicles,based on the power system struc-ture,a method of RBFneural network and dynamic programming is proposed.Incorporate energy management strategies for hybrid vehicles.RBFneural network used in the prediction time domain predicted speed,in the time domain of the prediction vehicle demand torque,dynamic programming optimizes the predicted time domain and provides a rational distribution of engine and motor torque.The comparison between simulation and traditional energy management strategy verifies the superiority and accuracy of this method.The experimental results show that compared with the traditional strategy,the proposed energy management strategy can significant-ly improve fuel economy and reduce energy consumption by15.47%,which has practical application potential.
关键词
混合动力/电动汽车/RBF神经网络/动态规划方法/能量管理策略Key words
Hybrid/Electric Vehicle/RBF Neural Network/Dynamic Programming Method/Energy Management Strategy引用本文复制引用
基金项目
吉林省职业技术教育学会科学研究课题(20JL0801263)
出版年
2024
NETL
NSTL
万方数据