【作者】 杨平；

【导师】 黄妙华；

【作者基本信息】 武汉理工大学 ， 车辆工程， 2015， 硕士

【摘要】 在当今世界面临着由传统汽车工业发展引发的能源短缺和环境污染的双重背景下,纯电动汽车以其独特的零排放、无污染、效能高等优点逐渐受到各国政府及车企的高度重视。在各式各样的纯电动汽车中,高速电动轮车因其四个轮子都采用线控技术的轮毂电机来驱动,底盘布置更加简化,逐渐成为纯电动汽车研究领域的热点。高速电动轮车的行驶必须依靠动力电池组提供能量,因此对动力电池组进行及时有效的在线监控与管理也成为当前电动汽车关键技术中研究的重点之一。本文以课题组研制的一款高速电动轮车对动力电池组的使用需求为背景,研究并开发出一款基于集中-分布式结构的锂电池管理系统,系统主要由一个主控单元模块和六个电池参数采集模块组成。在针对动力电池组的荷电状态(State Of Charge,SOC)估算方法的研究工作中,文章分析了影响SOC估算的相关因素和几种常见的SOC估算方法,采用了开路电压法与电流积分法相结合的估算方法,在开路电压法的计算公式中引入了电池剩余电量在静置状态下关于时间变量的加权运算,最终在静置和工作两种状态下分别估算出高速电动轮车动力电池组的SOC值。在软硬件设计过程中,基于本文设计的高速电动轮车BMS的总体结构方案和模块化设计的原则,将整个系统的硬件电路划分为主控单元电路、电池参数采集板电路、主从控制器SPI通信电路和整车电源转换电路四个部分,并在Altium Designer开发环境中依次完成了各部分的电路设计,在PCB板设计过程中引入了多种抗干扰处理措施,使系统的可靠性和稳定性得到增强。软件设计环节同样基于模块化及层次化的设计方法,依次对主控单元和电池参数采集板控制单元的主程序和子程序进行设计,对各个程序的实现过程进行了详细的介绍与分析,给出了各个主从控制单元的主程序及其子程序的软件流程图。最后,制作出了BMS的试验样机,完成了系统的软硬件调试,针对系统中的整车电源转换模块和LCD显示模块进行了实验验证,同时通过实车测试实验获得了大量实验数据。实验结果表明,系统针对各电池包温度的测量误差小于1℃,针对总电压的测量误差低于1V,针对干路电流的测量误差小于0.3A,SOC估算方法可行,估算结果有效。不仅为高速电动轮车动力电池组的能量管理提供了有效的解决方案,也为其它电池管理系统的开发提供了技术参考。更多还原

【Abstract】 Today, under the background of energy shortage and environmental pollution that caused by the development of traditional automobile industry, pure electric vehicles have received serious attention from lots of governments and automobile companies, for their unique advantages such as zero emissions, no pollution, high efficiency, etc. In different kinds of pure electric vehicles, the high-speed in-wheel motor driving electric vehicle is gradually becoming a research hotspot because its four wheels are driven by independent hub motors and use drive-by-wire technology. As a high-speed in-wheel motor driving electric vehicle’s working must rely on the power batteries to provide energy, so taking timely and effective online monitoring and management on the power batteries is also becoming a key technology of electric vehicles. With the usage requirements of high-speed in-wheel motor driving electric vehicle for power batteries, this paper develops a Li-ion Battery Management System(BMS) based on the centrally-distributed structure type. This BMS is mainly composed of a MCU module and six battery parameter acquisition modules.In the study of battery pack’s State Of Charge(SOC) estimation method, this paper analyzes related factors which influence the SOC estimation and several common SOC estimation methods, then uses an estimation method which combines the Open Circuit Voltage method and Ah Counting method. A time variable in the battery pack’s standing mode is introduced to make a weighted calculation in the Open Circuit Voltage method. The power battery pack’s SOC value is respectively worked out under the standing mode or working mode.In the hardware and software design process, this paper divides the whole system’s hardware circuit into four parts, namely the hardware circuits of MCU module, battery parameters acquisition boards, master-slave communication circuit for SPI communications and the vehicle’s power conversion circuit, based on the general structure of the car’s BMS and the modular and hierarchical design principles. All of the circuits’ schematics and PCB boards are finished in the Altium Designer. A variety of anti-jamming measures are used to improve the reliability and stability of the BMS. Software design is divided into two parts, namely the software design of MCU and the battery parameter acquisition control unit. Software flow chart is given for each program and the realization process is introduced or analyzed in detail. All of the BMS’s programs and subroutines are completed in the Keil uVision5.Finally, this thesis completes the BMS’s experimental prototype and the system’s hardware and software debugging. By carrying out two functional verification experiments, the vehicle’s power conversion circuit and the LCD module are validated. The final field testing is conducted to estimate the BMS’s acquisition error and the SOC feasibility. The results show that the BMS can work normally, and the measuring error for the temperature is less than 1℃, for the battery pack’s total voltage is less than 1 V, for the total current is less than 0.3 A. The SOC estimation result is feasible and effective. This paper not only gives a valid solution for power battery’s energy management of the high-speed in-wheel motor driving electric vehicle, but also provided a technical reference for the research of other BMS.更多还原