改进的Unscented卡尔曼滤波与电池组SOC快速精确估计

项目名称： 改进的Unscented卡尔曼滤波与电池组SOC快速精确估计

项目编号： No.60871088

项目类型： 面上项目

立项/批准年度： 2009

项目学科： 武器工业

项目作者： 高明煜

作者单位： 杭州电子科技大学

项目金额： 32万元

中文摘要： 本项目主要研究 UKF 的改进方法，使其能够适用于非线性非高斯系统，并将改进的UKF 算法用于电池组SOC 精确估计。同传统的模糊算法、神经元算法用于电池组SOC 估计相比，UKF 具有数据计算量少，预测精度高等优点。本项目的创新点在于：1、对UKF 算法进行改进，使其能够适用于非线性非高斯系统，同时对提高UKF 算法运行速度的优化方法也做了相应研究，使得UKF 算法的实时性与稳定性进一步提高；2、在已有的基于Kalman 滤波和扩展Kalman 滤波进行电池SOC 估计的基础上，提出将改进的Unscented Kalman Filter(UKF)应用于电池组SOC 的估计，在提高SOC 估计精度的同时，避免了扩展Kalman 滤波中繁琐的求导过程，进一步提高了算法运行的实时性。通过本项目的研究，进一步从理论上设计了合理的电池组SOC 估算模型，改进了电池可测参数的测量方法，为我国开发自主知识产权的电动汽车相关技术提供了相关研究基础。

中文关键词： UKF；电池组；SOC；精确估计

英文摘要： The project concentrates on the research on how to improve the Unscented Kalman Filter (UKF) so that it can be utilized to non-linear non-gaussian systems, and the aim is to accurately estimate of the Sate of Charge (SOC) of a battery group. Compared to the traditional methods such as the fuzzy algorithm based method, neuro based method, etc., the UKF has higher accuracy with less computation. The innovation points of this projects are: 1. Make improvements to the UKF so that it can be utilized to the nonlinear non-gaussian systems. Meanwhile, techniques of speed optimization of the UKF will also be concerned so as to improve its stability and make it run at realtime. 2. Different with the traditional techniques such as Kalman Filter based methods and Extended Kalman Filter(EKF) based methods to estimate the SOC of a battery, we use the improved UKF for the estimation of the SOC of a batter group. For UKF need not compute the differentiation of the system function and the state function, it is faster and more accurate than EKF. Through this project, we design a reasonable model for the estimation of the SOC of a battery group to improve the measure methods of the measurable parameters of the battery, and make great progress in the related research field.The research results are fundamental to the related electric vehicle technologies and several copyrights are obtained.

英文关键词： Unscented Kalman Filter; battery group; State of Charge; accurate estimation