电动汽车用锂离子电池管理系统软件设计

发布时间：2018-05-28 04:13

本文选题：电动汽车 + 锂离子电池　；参考：《湖南大学》2014年硕士论文

【摘要】：汽车的发展，给人们的生活带来了各种便利，但同时也带来了各种问题。目前环境问题和能源问题对汽车工业的发展提出了新要求。新能源汽车以其各方面的优点备受关注，作为新能源汽车中的一个方向，电动汽车的研究取得了各方面的成绩。但仍有许多关键性共性技术问题亟待解决，电池管理系统就是其中之一。本文从电池管理系统软件设计的角度，构建了电池管理系统的软件大体框架，同时对电池SOC估算进行了相应研究。主要研究工作包括以下几个方面：（1）采用RC等效电路模型来模拟锂离子电池的电压特性，运用脉冲放电实验方法对本文研究电池进行充放电实验，对实验得到的数据进行多元线性回归分析，得到了本文研究锂离子电池RC等效电路模型的参数。考虑到电池管理系统中对于电池特性参数的计算要求，完成了本文电池管理系统中使用电池参数及数据格式的定义。（2）在电池管理系统的上位机软件设计中，采用了实时操作系统μC/OS II，完成了μC/OS II实时操作系统在上位机微控制器MC9S12XS256上的移植，并给出了移植代码。基于μC/OS II实时操作系统，对上位机所需完成的功能进行了任务划分，并分别设定了各个任务的优先级和调度周期。（3）定义了电池管理系统的功能需求，结构上将电池管理系统分为上位机和下位机，并分别给出了上位机和下位机的软件设计流程。其中，上位机软件基于μC/OS II操作系统进行设计，下位机软件基于下位机所需完成功能先后顺序进行设计，实现了上位机和下位机之间基于CAN总线的通信策略。并参照DeviceNet通信协议，完成了通信过程中单体电池电压、温度数据帧格式的系统定义。（4）采用模糊自适应卡尔曼滤波方法，改进自适应卡尔曼滤波方法采用指数加权方式修正噪声统计特性时容易由于突然扰动而导致发散的缺点，运用UDDS循环工况对滤波方法进行仿真对比，，结果表明本文使用的模糊自适应卡尔曼滤波法相比传统卡尔曼滤波法获得了较高的SOC估算精度。
[Abstract]:The development of automobile brings various conveniences to people's life, but it also brings various problems at the same time. At present, the environmental and energy problems have put forward new requirements to the development of the automobile industry. New energy vehicles are concerned with the advantages of all aspects. As a direction of new energy vehicles, the research of electric vehicles has made various aspects. But there are still many key common technical problems to be solved. The battery management system is one of them. From the point of view of the software design of the battery management system, this paper constructs the general framework of the software of the battery management system, and studies the SOC estimation of the battery. The main research work includes the following aspects:
(1) using the RC equivalent circuit model to simulate the voltage characteristics of the lithium ion battery, using the pulse discharge experiment method to study the battery charging and discharging experiments, the data obtained by the experiment are multivariate linear regression analysis, and the parameters of the study of the RC equivalent circuit model of the lithium ion battery are obtained. The requirement of battery characteristic parameters is calculated, and the definition of battery parameters and data format in battery management system is completed.
(2) in the design of the host computer software of the battery management system, the real-time operating system mu C/OS II is adopted, and the transplantation of the real-time operating system of the C/OS II on the PC micro controller MC9S12XS256 is completed, and the transplant code is given. Based on the real-time operating system of the C/OS II, the functions of the upper computer are divided and set up respectively. The priority of each task and the scheduling period are determined.
(3) the functional requirements of the battery management system are defined. The battery management system is divided into the upper computer and the lower computer, and the software design process of the upper computer and the lower computer is given. The upper computer software is designed based on the C/OS II operating system, and the lower computer software is designed in order to complete the function sequence based on the lower computer. The communication strategy based on the CAN bus between the host computer and the lower computer is realized, and the system definition of the single cell voltage and temperature data frame format in the communication process is completed with reference to the DeviceNet communication protocol.
(4) the fuzzy adaptive Calman filter method is used to improve the adaptive Calman filter method to modify the noise statistic characteristic by exponential weighting method, which is easily caused by sudden disturbance. The filter method is simulated and compared with the UDDS cycle condition. The result shows the fuzzy adaptive Calman filter method used in this paper. Compared with the traditional Calman filtering method, the SOC estimation accuracy is higher.
【学位授予单位】：湖南大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM912

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