电动汽车动力电池管理系统设计与实现
哈尔滨工业大学工学硕士学位论文
Abstract
The battery management system is the key to the stable and reliable operation of electric vehicles. The BMS monitors and manages the battery voltage, temperature, state of charge, and vehicles/battery faults uniformly to complete the status display and alarm notification for users, which can effectively improve traffic safety and battery usage efficiency. For this reason, this paper studies the BMS embedded integrated machine and the host computer system.
Considering the amount of system computation and the difficulty of parameter identification methods, the first-order Thevenin model is adopted to be equivalent to the battery circuit. By experiment on the the hybrid pulse power for the battery, the parameters of the equivalent model and the hysteresis curve of the open circuit voltage are determined. The accuracy of the open circuit voltage curve is verified by the results of the discharge simulation model of the battery.
Taking the internal and external factors of the battery into account, the corresponding correction factor is introduced, combining with the open-circuit voltage method for determination of initial battery SOC, a modified ampere-hour integral method is designed to complete the SOC estimation. However, as the modified ampere-hour integration method is an open-loop method, where exists an irreparable initial error and cumulative error, Kalman filtering algorithm for SOC estimation is introduced. We establish the state space expression of the battery circuit based on the first-order Thevenin equivalent battery model, design the Kalman filter for SOC estimation, and guarantee the accuracy of the optimal value estimation by model simulation.
According to the functional requirements of the system, the MCU basic management circuit, bus communication circuit, and battery monitoring module of the integrated machine are designed. The functional testing of the model is completed, and the embedded system of the battery management integrated machine is built to provide a hardware platform for the algorithm and software.
We designed the embedded software based on the hardware platform of the integrated machine. The specific implementation process of the system and the battery/unit fault handling method is designed according to the corresponding execution actions of different working conditions of the system and state transition conditions. We introduce the BMS communication protocol, complete the graphic display and alarms of battery/machine status and fault information on the host computer monitoring software, and a unified monitoring and
哈尔滨工业大学工学硕士学位论文
management platform of the host computer. The system complete CAN bus communication through the USB-CAN, the integrated machine starts the embedded program to complete the battery monitoring and data upload,the host computer receives the data and displays it to accomplish the integration test of the overall system.
Keywords: BMS, SOC, Thevenin model, Kalman filter, fault treatment
哈尔滨工业大学工学硕士学位论文
目录
摘要................................................................................................................. I Abstract............................................................................................................. I I 第1章绪论 .. (1)
1.1 课题来源及研究的背景和意义 (1)
1.1.1 课题来源 (1)
1.1.2 课题研究背景和意义 (1)
1.2 国内外在该方向的研究现状及分析 (3)
1.2.1 国内研究现状 (3)
1.2.2 国外研究现状 (4)
1.2.3 国内外文献综述的简析 (4)
1.3 主要研究内容 (5)
1.3.1 SOC估计算法 (6)
1.3.2 一体机硬件设计 (7)
1.3.3 系统软件开发 (7)
1.4 论文具体结构 (7)
第2章BMS工作方式及电池参数化辨识 (9)
2.1 引言 (9)
2.2 BMS工作方式及电池原理介绍 (9)
2.2.1 BMS工作方式介绍 (9)
2.2.2 电池工作原理及选型 (11)
2.3 锂离子电池测试实验 (12)
2.4 电池模型及参数化辨识 (15)
2.4.1 电池电路模型概述 (15)
2.4.2 电池模型参数化辨识 (18)
2.4.3 OCV滞回特性测试 (20)
2.5 电池放电模型仿真 (24)
2.6 本章小结 (26)
第3章SOC算法设计及模型仿真 (27)
3.1 引言 (27)
3.2 SOC算法介绍 (27)
3.2.1 安时积分法 (27)
哈尔滨工业大学工学硕士学位论文
3.2.2 开路电压法 (27)
3.2.3 神经网络法 (28)
3.2.4 Kalman滤波法 (28)
3.3 修正安时积分法设计 (28)
3.3.1 充放电倍率修正 (29)
3.3.2 温度修正系数 (30)
3.3.3 电池老化及自放电修正 (30)
3.3.4 开路电压法修正 (31)
3.3.5 修正安时积分法仿真 (31)
3.4 Kalman滤波算法设计 (35)
3.4.1 Kalman滤波算法原理 (35)
3.4.2 Kalman滤波SOC估计 (37)
3.4.3 Kalman滤波模型仿真 (38)
3.5 SOC估计算法比较分析 (40)
3.6 本章小结 (42)
第4章硬件电路设计及测试 (43)
4.1 引言 (43)
4.2 硬件设计总体框架 (43)
4.3 MCU基本管理电路设计 (44)
4.3.1 MCU相关电路设计 (44)
4.3.2 电源自锁自断电路设计 (45)
4.3.3 外部EEPROM模块设计 (47)
4.3.4 DS1302时间管理模块设计 (48)
4.4 总线通信电路设计 (49)
4.4.1 RS232总线通信电路 (49)
4.4.2 RS485总线通信电路 (50)
4.4.3 CAN总线通信电路 (51)
4.5 电池监控模块设计 (52)
4.5.1 LTC6804相关电路设计 (52)
4.5.2 电池监控电路测试 (55)
4.6 电池管理一体机硬件平台 (58)
4.7 本章小结 (59)
第5章软件开发及系统联调 (60)
5.1 引言 (60)
哈尔滨工业大学工学硕士学位论文
5.2 嵌入式软件平台开发 (60)
5.2.1 嵌入式软件总体设计 (60)
5.2.2 软件系统状态转移 (61)
5.2.3 系统执行流程 (63)
5.2.4 系统故障处理设计 (66)
5.3 上位机监控平台开发 (69)
5.3.1 上位机监控软件设计 (69)
5.3.2 BMS通信协议介绍 (73)
5.3.3 上位机软件调试 (75)
5.4 上位机与嵌入式系统联调 (77)
5.5 本章小结 (79)
结论 (80)
参考文献 (81)
攻读硕士学位期间发表的学术论文 (84)
哈尔滨工业大学学位论文原创性声明及使用授权说明 (85)
致谢 (86)