基于斯特林插值滤波器的锂离子电池荷电状态估计

发布时间：2018-03-26 19:13

本文选题：锂离子电池　切入点：电池特性　出处：《天津大学》2014年硕士论文

【摘要】：随着一次能源的逐渐枯竭、环境污染的日益加剧,锂离子电池作为新能源的一种,因其在多方面的优点,如环保、比能高等,在日常生活以及工业应用中使用广泛,电池的荷电状态(SOC)是电池管理系统功能实现的基础,因此准确的估计荷电状态对于电池的高效安全使用具有重要意义。本文探讨了磷酸铁锂电池的一些基本充放电特性、基于斯特林插值滤波器(DD1、DD2)的SOC估计,同时初步搭建了一个硬件系统用于算法的运行验证。电池的开路电压、容量和直流内阻等性能参数受电流、SOC等因子的影响很大。本文通过恒流脉冲放电实验,探讨了开路电压、直流内阻与SOC之间的关系;通过不同倍率下的恒流放电实验,研究了容量与电流之间的关系。为了克服扩展卡尔曼滤波(EKF)的各种应用缺陷,如需计算雅可比矩阵、要求非线性系统系统函数可微等,本文探讨了基于斯特林插值滤波算法的SOC估计,它采用差分式代替泰勒展开中的微分式,并且比泰勒展开更接近系统的非线性特性,并无需计算雅可比矩阵。最后在电池脉冲放电实验的基础上,应用DD2、DD1、EKF三种算法估计SOC,仿真结果表明斯特林插值滤波算法具有更高的估计精度。本文在最后一部分初步设计了一个硬件系统用于算法运行验证,整个硬件系统分为电池主控功能单元和测控功能单元。测控单元主要负责对电池的工作状态参数进行监控显示,并将状态信息上传至主控单元;主控单元通过采集到的状态信息用算法估计电池SOC,估计算法采用基于模块的方法编写。
[Abstract]:With the gradual depletion of primary energy and the worsening of environmental pollution, lithium ion batteries, as one of the new energy sources, are widely used in daily life and industrial applications because of their advantages in many aspects, such as environmental protection and higher specific energy. The state of charge (SOC) of the battery is the basis of the realization of the function of the battery management system, so it is important to estimate the state of charge accurately for the efficient and safe use of the battery. In this paper, some basic charge-discharge characteristics of the lithium iron phosphate battery are discussed. SOC estimation based on Stirling interpolation filter DD1 / DD2), and a hardware system is built to verify the algorithm. The performance parameters such as capacity and DC internal resistance are greatly affected by the current / SOC factors. In this paper, the relationship between open circuit voltage, DC internal resistance and SOC is discussed through constant current pulse discharge experiments, and the constant current discharge experiments at different rates are carried out. The relationship between capacity and current is studied. In order to overcome the disadvantages of extended Kalman filter (EKF), if Jacobian matrix is to be calculated, the system function of nonlinear system is required to be differentiable. In this paper, the SOC estimation based on Stirling interpolation filtering algorithm is discussed. The differential equation is used to replace the differential expression in Taylor expansion, and it is closer to the nonlinear characteristic of the system than Taylor expansion. There is no need to calculate Jacobian matrix. Finally, based on the experiment of battery pulse discharge, The simulation results show that the Stirling interpolation filtering algorithm has higher estimation accuracy. In the last part of this paper, a hardware system is preliminarily designed for the operation verification of the algorithm. The whole hardware system is divided into the battery main control function unit and the measurement and control function unit, which is mainly responsible for monitoring and displaying the working state parameters of the battery, and uploading the state information to the main control unit. The SOC of the battery is estimated by the state information collected by the main control unit, and the estimation algorithm is based on the modular method.
【学位授予单位】：天津大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM912

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