摘要
锂离子电池与超级电容组合的混合储能系统(Hybrid energy storage system,HESS)通过超级电容补充输出峰值功率,有效解决了锂离子电池电动汽车在城市工况频繁启动和制动的大功率需求造成锂离子电池不可逆的容量衰减问题,但相比于单独使用动力电池,超级电容的加入增加了成本和重量并且降低了整个储能系统的输出效率。从能量分配策略和参数匹配两个方面论述了当前HESS的研究进展。目前能量分配策略的研究多采用燃油汽车的循环测试工况作为研究数据,依据在线运算能力及应用场景将能量分配策略分为离线控制和在线控制,前者依赖已知的能耗数据但能实现优化分配效果,而后者能实现在线实时分配但优化效果有限。参数匹配的研究由效率分析和策略匹配向基于能量分配策略的全局优化发展,以解决前两种方法未考虑HESS成本和重量的优化问题。最后,指出未来需要基于电动汽车的城市道路自然行驶数据,以优化整个动力电池组的寿命为目标,考虑驾驶员风格建立个性化的参数匹配全局优化模型,以降低其制造成本;并结合道路交通信息进行更准确的能耗预测,采用离线与在线控制相结合的智能化能量分配策略,以进一步提升能量分配效果。
The hybrid energy storage system(HESS)composed of lithium-ion battery and super capacitor supplements the output peak power through super capacitor,which effectively solves the problem of irreversible capacity attenuation of lithium-ion battery caused by the high power demand of frequent start and braking of lithium-ion battery electric vehicle under urban driving conditions.However,compared with the power battery alone,the addition of super capacitor increases the cost and weight and reduces the output efficiency of the whole energy storage system.The research progress of HESS is discussed from two aspects:energy allocation strategy and parameter matching.At present,the researches of energy allocation strategy mostly use the cycle test conditions of fuel-engined vehicles as the research data,and according to the online computing ability and application scenarios,the energy allocation strategies are divided into offline control and online control,the former relies on the known energy consumption data,but can achieve the optimal allocation effect,while the latter can achieve real-time energy allocation,but the optimization effect is limited.The researches of parameter matching have developed from efficiency analysis and strategy matching to global optimization based on energy allocation strategy to solve the optimization problem that the first two methods do not consider cost and weight of HESS.Finally,it is pointed out that in the future,it is necessary to establish a personalized parameter matching global optimization model based on the natural driving data of electric vehicles on urban roads,aiming at optimizing the service life of the whole power battery pack and considering the driver’s style,so as to reduce its manufacturing cost;and combined with road traffic information,more accurate energy consumption prediction would be carried out,and the intelligent energy distribution strategy combining off-line and on-line control is adopted to further improve the effect of energy allocation.
作者
胡林
田庆韬
黄晶
叶瑶
伍贤辉
HU Lin;TIAN Qingtao;HUANG Jing;YE Yao;WU Xianhui(School of Automotive and Mechanical Engineering,Changsha University of Science and Technology,Changsha 410114;Hunan Province Key Laboratory of Safety Design and Reliability Technology for Engineering Vehicle,Changsha University of Science and Technology,Changsha 410114;College of Mechanical and Vehicle Engineering,Hunan University,Changsha 410082;School of Traffic&Transportation Engineering,Central South University,Changsha 410083)
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2022年第16期224-237,共14页
Journal of Mechanical Engineering
基金
国家自然科学基金(52172399,51875049)
国家自然科学基金国际合作(52211530054)
湖南省重点研发计划(2020SK2099)
国家重点研发计划(2017YFE01184,2019YFE0108000)资助项目
关键词
电动汽车
混合储能系统
能量分配
参数匹配
electric vehicle
hybrid energy storage system
energy allocation
parameter matching
