动力锂电池的建模、状态估计及管理策略研究

发布时间：2018-04-07 16:33

本文选题：动力锂电池　切入点：电池建模　出处：《中国科学技术大学》2017年博士论文

【摘要】：环境污染和能源危机是世界各国面对的两大难题,电动汽车作为一种零排放的交通工具是解决环境与能源问题的一个优选方案。针对动力电池系统当前国内外的研究热点,本文依托复杂系统的建模与分析手段以及现代滤波技术,开展动力锂电池的建模、状态估计和管理策略的研究,目的是建立一套涵盖动力系统建模、估计与控制的理论与方法体系,为储能系统的精细化、安全化、高效化管理提供借鉴。本论文的主要工作如下:(1)精确的电池模型有助于电池的行为描述与分析,也是电池状态估计的基础和前提。锂电池本身是一个复杂的电化学系统,具有很强的非线性和时变性,同时电池的参数易受外界环境等因素的影响,增加了电池在随机环境下建模的难度。基于对电池内部机理和外部行为的分析,本文提出了一种基于数据驱动的电池建模与参数辨识方法。(2)提出了基于多模型切换策略的电池荷电状态估计方法,通过引入改进解释结构模型,实现了四种典型电化学模型的切换,通过实验对算法的精度和实时性进行了验证;分析了温度对库伦效率的影响,建立了电池的容量保持率模型,提出了一种基于容量保持率模型的荷电状态估计方法,在实验验证中分析了漂移电流对估计精度的影响;针对传统卡尔曼滤波器方法在解决非线性、非高斯系统的状态变量估计问题时容易出现发散的问题,提出一种基于贝叶斯估计理论的电池荷电和能量状态估计方法,并通过动态工况下的实验对该方法的精度和鲁棒性进行了验证。(3)研究了电池被动均衡和主动均衡的电路拓扑和均衡控制策略,针对被动均衡的不足,提出了一种基于双向DC/DC的主动均衡电路。基于对电池模型和电池状态估计方法的研究,提出了基于荷电状态的电池主动均衡控制策略,通过实验对比了不同均衡策略的性能。(4)将锂电池的建模与状态估计方法拓展到锂电池/超级电容混合储能系统的建模与状态估计中。创造性地提出了基于双滤波器的参数与状态联合估计器,采用扩展卡尔曼滤波器和无迹卡尔曼滤波器分别对锂电池和超级电容的模型参数以及荷电状态进行更新和估计。为了降低模型参数的收敛时间,在参数更新阶段采用递推最小二乘法寻找模型参数的初始最优值。通过比较锂电池和超级电容在动态放电工况下状态估计的精度,对本文提出的估计策略进行了验证。(5)将电池的建模、状态估计、均衡管理等技术集成到电池管理系统的应用中,可以提高电池管理系统的精细化、智能化管理程度,延长电池的使用寿命。通过分析管理系统积累的电池数据,可以进一步优化电池的建模、状态估计和管理策略。本文介绍了电池管理系统的软硬件架构,并对电动汽车电池管理系统进行了案例分析。
[Abstract]:Energy crisis and environmental pollution are two major problems facing the world, the electric car as a kind of zero emission vehicles is a preferred solution to solve the problems of environment and energy. According to the research hotspot of power battery system based on complex system modeling and analysis methods and modern technology to carry out filtering, modeling power lithium battery research, state estimation and management strategy, the purpose is to establish a set covering power system modeling, estimation and control theory and method system for fine, storage system security, provide reference for efficient management. The main work of this paper are as follows: (1) the behavior description and analysis of the battery the precise model is helpful for the battery, the battery is the basis and premise of state estimation. Lithium battery itself is a complex electrochemical system, with strong nonlinearity and degeneration, and battery The parameters are easily affected by external factors such as the increase of battery in the random environment modeling difficulty. Analysis of battery internal and external mechanism based on behavior, this paper presents a data driven cell modeling and parameter identification method based on (2) method is proposed to estimate the state of charge of multimode type switching strategy based on the battery, through the introduction of improved interpretative structural model, realizes the switching of the four typical electrochemical model, through the precision of the algorithm and the real-time experiment was verified; analyzes the influence of temperature on the efficiency of Kulun, established the capacity retention ratio of the battery model, proposed a capacity retention rate of charged state estimation model based on the method in experiment analysis of drift current impact on the estimation accuracy; the traditional Calman filter method in solving the nonlinear state variable estimation problem of non Gauss system To avoid the divergence problem, proposed a Bayesian estimation method to estimate the theory of battery charge and energy status based on dynamic conditions and through experiments on the methods of precision and robustness are verified. (3) studied the circuit topology and control strategy of battery equalization equalization and passive active equalization, according to under equilibrium, this paper presents an active two-way balanced circuit based on DC/DC. Study on the estimation methods of the battery and battery status based on the model, the proposed active balancing control strategy based on state of charge of the battery, through the experiment on the performance of different ratio equilibrium strategy. (4) the modeling and state estimation of lithium battery the method is extended to modeling and state of lithium battery / super capacitor hybrid energy storage system estimation. Creatively put forward the combined parameter and state estimator based on double filter, using extended Calman filter For Calman and the unscented filter respectively for lithium battery and super capacitor model parameters and state of charge of updating and estimation. In order to reduce the convergence time of the model parameters, the parameter updating stage using recursive least squares method to find the optimal initial values of model parameters. By comparing the lithium battery and super capacitor discharge conditions in dynamic state the precision of estimation of estimation strategy proposed in this paper is verified. (5) the battery modeling, state estimation, equalization management technology is integrated into the application of battery management system, can improve the precision of battery management system, intelligent management, prolonging the service life of the battery. The battery through data analysis and management the system of accumulation, can further optimize the battery modeling, state estimation and management strategies. This paper introduces the hardware and software architecture of the battery management system of electric vehicle battery. A case analysis of the management system is carried out.

【学位授予单位】：中国科学技术大学
【学位级别】：博士
【学位授予年份】：2017
【分类号】：TM912

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