摘要
根据锂离子超级电容的储能机理和性能特点建立了等效电路模型,在此基础上提出了一种结合强跟踪滤波法和安时积分的荷电状态(SOC)估算方法。强跟踪滤波法在卡尔曼滤波法的基础上引入渐消因子以改善算法的鲁棒性,将强跟踪滤波法与电流积分法通过一个加权因子结合起来,提高了SOC估算的准确性。按照锂离子超级电容在混合动力车应用中的典型工况对模型和SOC算法进行了实验验证,实验和仿真结果表明该模型能够较好地模拟锂离子超级电容的动态特性,所提算法具有较高的精度。
A equivalent circuit model of the lithium-ion ultracapacitor was proposed based on the energy storage mechanism and charge discharge characteristics. A combined algorithm for SOC estimation of the ultracapacitor was proposed based on the model. The algorithm was obtained by combining the strong tracking filter method and the Amper-Hour integral method using a weighting factor. The strong tracking filter method was used to improve the robustness of the algorithm and the accuracy of SOC estimation was improved by the weighting factor. The model and the SOC estimation algorithm were evaluated under a specific current profile which simulating the typical working condition of the lithium-ion ultracapacitor on HEVs. The comparison between the simulation result and the test data shows that the proposed model depicts the electrical behavior of the ultracapacitor very well, and the proposed SOC estimation algorithm has high accuracy.
出处
《电源技术》
CAS
CSCD
北大核心
2015年第3期515-517,共3页
Chinese Journal of Power Sources
基金
国家"863"项目(2011AA11A207)
关键词
锂离子超级电容
模型
荷电状态
强跟踪滤波
加权因子
lithium-ion ultracapacitor
model
state of charge
strong tracking filter
weighting factor
