欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
在研究现有荷电状态（SOC）估算方法优缺点的基础上,采用了扩展卡尔曼滤波法（EKF）估算动力锂电池SOC.以卡尔曼滤波算法为基础,建立了基于戴维宁电池模型的状态空间表达式.根据估算误差分析及锂电池工作特性,对EKF中的卡尔曼滤波增益进行分类修正.设计了一套以DSP为主控制器的管理系统.仿真和实验表明,在模拟汽车工况条件下,改进EKF大大提高了估算精度,均衡方案可有效补偿电池组间不一致性.
英文摘要：
Based on the analysis of the relative merits of traditional state of charge （SOC） algorithm, the paper adoptes a extend Kalman fiher（EKF） algorithm for estimate SOC.The state-space representation of the battery model is established based on Thevenin battery model and Kalman filtering algorithm.According to the estimates and performance characteristics of batteries, a new improved-way by amending the Kalman filter gain is proposed.A power Li-ion battery management system with the DSP as the main controller is designed.The simulation and test results under the condition of simulated driving show that this new way really can increase the SOC accuracy, the equalization scheme can effectively compensate the performance inconsistency of battery pack.
同期刊论文项目
同项目期刊论文
Short-circuit Current Calculation Method for Partial Coupling Transmission Lines under Different Vol
期刊信息
位置：