Battery anti-aging control for a plug-in hybrid electric vehicle with a hierarchical optimization energy management strategy
Battery anti-aging control for a plug-in hybrid electric vehicle with a hierarchical optimization energy management strategy
复制标题
具有分层优化能量管理策略的插电式混合动力汽车电池抗老化控制
DOI：
10.1016/j.jclepro.2019.117841
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发表时间：
2019
影响因子：
11.1
通讯作者：
Yang Qingqing
中科院分区：
文献类型：
--
作者：
Bai Yunfei;He Hongwen;Li Jianwei;Li Shuangqi;Wang Ya xiong;Yang Qingqing
针对插电式混合动力汽车的电池老化问题，提出了一种分级优化的能量管理策略。在第一级中，提出了一种变阈值动态规划算法，用于在储能系统和发动机之间分配功率。通过添加超级电容器组成混合储能系统，并采用自适应低通滤波算法，将能量分配到电池和超级电容器之间。为了控制超级电容器和电池在容量范围内工作，设计了一个功率限制管理模块，用于在发动机、超级电容器和电池之间重新分配功率。自适应低通滤波算法和功率限制管理模块构成了第二级的自适应功率分配方法。在此基础上，本文采用雨流计数算法计算电池老化成本。利用雨流计数算法对电池性能进行了分析，结果表明，与全局动态规划算法相比，自适应功率分配方法可使电池寿命提高约54.9%。综合考虑超级电容器的初始成本、电池老化成本、油耗、电耗和报废电池的管理成本，与全局动态规划算法相比，车辆的寿命周期经济性提高了12.4%。
This paper proposes a hierarchical optimization energy management strategy to suppress the battery aging in plug-in hybrid electric vehicles. In the first-level, a variable-threshold dynamic programming algorithm to distribute the power between the energy storage system and the engine is proposed. By adding supercapacitor to form the hybrid energy storage system, and using adaptive low-pass filtering algorithm, the power between the battery and the supercapacitor is distributed. To control the supercapacitor and battery to work within the capacity range, a power limits management module for redistributing the power between the engine, the supercapacitor and the battery is considered. The adaptive low-pass filtering algorithm and power limits management module constitute adaptive power allocation method in the second-level. After that, the rain-flow counting algorithm is applied in this paper to calculate battery aging cost. By using the rain-flow counting algorithm, the battery performances are analyzed, and the results show that the adaptive power allocation method can improve the battery service life by about 54.9% compared with the global dynamic programming algorithm. Considering the initial cost of the supercapacitor, the costs of battery aging, fuel consumption, electricity consumption, and management cost of retired batteries, compared with the global dynamic programming algorithm, the life cycle economy of the vehicle is improved by 12.4% under the proposed method.