电动汽车用锂电池高效运行管理技术研究

发布时间：2019-02-28 07:25

【摘要】：环境污染和能源危机,使人类迫切需要找一种新能源汽车来替代传统机动车。电动汽车在电池能量转换和尾气排放等方面具有很大优势,电动汽车成为人们替代传统机动车首选,而锂电池管理制约了电动汽车普及和推广。本文对锂离子电池种类进行分析比较,最终选择磷酸铁锂电池作为电动汽车用锂电池管理研究对象。本文首先介绍了国内外电动汽车产业发展现状和电动汽车在推广普及中遇到一些难题,锂电池管理技术是电动汽车发展遇到最为突出的难点,随后对锂电池管理技术难点进行分析研究。锂电池剩余电量(SOC)估算精度和锂电池组单体电池之间不一致性是锂电池管理难点。通过对磷酸铁锂电池进行大量充放电试验,得到电池关键性能基本特性参数,其中基本特性参数包括充放电特性、倍率特性、温度特性以及静置特性。本文在对电动汽车用锂电池高效运行管理进行设计研究,提出了基于扩展卡尔曼滤波算法(EKF)复合算法的SOC估算和基于GS7708芯片主动均衡控制策略,是本文重点研究部分。在电动汽车使用过程中,锂电池组没有得到有效管理,不能实时估算锂电池工作状态,降低锂电池整体性能,导致汽车续驶里程短以及使用成本激增。本文结合安时计量法、开路电压法以及扩展卡尔曼滤波算法,提出了基于EKF复合算法的SOC估算,并对复合算法建立Thevenin电池模型,采用了MATLAB仿真验证了基于EKF复合算法精度及可行性。另外针对单体锂电池在循环工作一段时间后,存在不一致性,容易导致锂电池过充过放,提出了基于GS7708芯片电感主动均衡控制策略以及全局最优化算法,设计了相关主动均衡控制电路。此外还对磷酸铁锂电池电池组进行了主动均衡实验,比较均衡前后电压变化,验证本文主动均衡策略的可行性。通过提高了SOC估算准确性以及减少锂电池主动均衡时间,实现了对锂电池有效管理。在硬件上,设计了基于STM32F103VBT6芯片的电动汽车用锂电池组整体硬件电路,主要包括CPU最小系统、电源模块、EEPROM、RS485通信接口电路、人机界面以及锂电池组充放电电压电流信号采样,并采用专门电池监控芯片AD7280A进行信号数据采样。软件设计上对STM32的Keil uVision4开发环境及功能作了简要概述,在硬件电路基础上,完成锂电池充放电管理系统的软件程序设计,并设计了相应的程序和电路流程图。最后,对本文进行了一些总结和展望。
[Abstract]:Because of environmental pollution and energy crisis, it is urgent to find a new energy vehicle to replace the traditional motor vehicle. Electric vehicles have great advantages in battery energy conversion and exhaust emissions. Electric vehicles have become the first choice to replace traditional vehicles, while lithium battery management has restricted the popularization and promotion of electric vehicles. In this paper, the types of lithium-ion batteries are analyzed and compared. Finally, the lithium-iron phosphate battery is selected as the research object of the management of lithium-ion batteries for electric vehicles. This paper first introduces the development of electric vehicle industry at home and abroad and some difficult problems encountered in the promotion and popularization of electric vehicle. Lithium battery management technology is the most prominent difficulty in the development of electric vehicle. Then the technical difficulties of lithium battery management are analyzed and studied. The precision of (SOC) estimation and the inconsistency between lithium battery and lithium battery are difficult to manage lithium battery. The basic performance parameters of lithium ferric phosphate battery were obtained by a large number of charge-discharge tests, including charge-discharge characteristics, rate-doubling characteristics, temperature characteristics and static characteristics. In this paper, the efficient operation management of lithium battery for electric vehicle is designed and studied, and the SOC estimation based on extended Kalman filter algorithm (EKF) compound algorithm and the active equalization control strategy based on GS7708 chip are put forward, which is the focus of this paper. In the process of using electric vehicle, lithium battery pack is not managed effectively, can not estimate the working state of lithium battery in real time, reduces the overall performance of lithium battery, and results in the short driving mileage and the rapid increase in using cost. In this paper, combined with amperometric method, open circuit voltage method and extended Kalman filter (EKF) algorithm, the SOC estimation based on EKF composite algorithm is proposed, and the Thevenin battery model is established for the composite algorithm. The accuracy and feasibility of the composite algorithm based on EKF are verified by MATLAB simulation. In addition, aiming at the inconsistency of lithium battery after a period of cycle operation, which can easily lead to overcharging and discharge of lithium battery, the active equalization control strategy and global optimization algorithm based on GS7708 chip inductor are proposed. An active equalization control circuit is designed. In addition, the active equalization experiment of lithium iron phosphate battery pack is carried out to compare the voltage change before and after the equalization, and verify the feasibility of the active equalization strategy in this paper. By improving the accuracy of SOC estimation and reducing the active equalization time of lithium batteries, the effective management of lithium batteries is realized. In hardware, the whole hardware circuit of lithium-ion battery pack for electric vehicle based on STM32F103VBT6 chip is designed, which mainly includes CPU minimum system, power module, EEPROM,RS485 communication interface circuit, man-machine interface, charge-discharge voltage and current signal sampling of lithium battery pack. The special battery monitor chip AD7280A is used to sample the signal data. In the software design, the development environment and function of Keil uVision4 of STM32 are briefly summarized. On the basis of hardware circuit, the software program design of charge and discharge management system for lithium battery is completed, and the corresponding program and circuit flow chart are designed. Finally, this paper makes some summary and prospect.
【学位授予单位】：安徽理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM912

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