【作者】 彭凯；

【导师】 李桂丹；

【作者基本信息】 天津大学 ， 电气工程， 2018， 硕士

【摘要】 随着全球能源日益枯竭、环境污染问题日益严重,电动汽车产业得到了迅速发展。锂离子电池作为一种高效清洁的绿色能源,逐渐成为电动汽车的主要动力来源,其性能是影响整车性能的关键因素。电池管理系统(BMS)对电动汽车充放电控制以及动力优化进行正确有效管理,确保锂离子电池工作在安全范围,为电动汽车的合理使用和维护提供重要依据,提高电动汽车的续航里程和使用寿命。电池管理系统的核心是对电池荷电状态(SOC)进行精确的估计,锂离子状态的精确估计能够避免电池的过充过放,延长电池的使用寿命。但SOC并不能直接通过测量得到,只能通过电池端电压、充放电电流等外部参数来估计,这些参数极易受到电池温度等工作状态影响,增加了SOC预测的难度。电池模型是描述电池外部电气特性和电池内部电化学反应的纽带,是进行SOC预测的前提,锂离子电池的使用环境和负载特性都极为复杂,具有高度的非线性。本文在研究各种电池模型的基础上,采用混合电化学模型进行建模,并通过遗忘因子最小二乘法对电池模型的参数进行辨识,实验结果验证电池模型具有较高的精度,能够较好反应电池的动态性能和静态特性。同时本文结合无迹卡尔曼滤波算法和粒子滤波算法的优势,提出一种新型的混合算法框架,并利用Matlab软件进行编程预测应用于磷酸铁锂电池的SOC预测。通过实验数据与扩展卡尔曼滤波算法、无迹卡尔曼滤波算法以及粒子滤波算法对比,验证了所提出的算法结构在预测精度、实时性以及鲁棒性等的优势。更多还原

【Abstract】 With the increasing global energy and environmental crisis,the electric vehicles have been widely developed.Lithium-ion battery,as a highly efficient clean green energy,has become the main power source of electric vehicles,and its performance is the key to the performance of the vehicle factor.The battery management system(BMS)manages the electric vehicle charging and discharging as well as the power optimization correctly and effectively.It can ensure that lithium ion batteries work in a safe range,which provides an important basis for the rational use and maintenance of electric vehicles,and improves the mileage and service life of electric vehicles.The core of the battery management system is to estimate the charge state of the battery(SOC)accurately,and the accurate estimation of the lithium ion state can avoid the overcharge and over discharge of the battery and prolong the service life of the battery.But the SOC cannot be directly measured,and it can only be estimated through the battery voltage,charge/discharge current and other external parameters.These parameters are easily influenced by the temperature of the battery and other working conditions,which increase the difficulty of forecasting SOC.The battery model is the link of the electrical characteristics of external and internal battery cell electrochemical reaction,and it is a prerequisite for the prediction of SOC.The parameter of Lithium-ion battery is effected by environment and load characteristics.The battery model is highly nonlinear.Based on the study of the various battery model,the hybrid electrochemical model is used in this paper.And forgetting factor least squares method is proposed for identifying the battery model’s parameters,the experimental results verify the battery model has high precision and good dynamic response to the battery and static characteristics.Based on UKF algorithm and PF algorithm,the paper proposes a new hybrid algorithm.The hybrid method is applied to estimate SOC of lithium-ion battery.By comparison with EKF,UKF and PF,the proposed algorithm has the superiority performance in accuracy,real-time and robustness advantages.更多还原