高效电池均衡策略研究

发布时间：2018-08-20 10:09

【摘要】：随着现代经济的高速发展,人类对石油天然气等化石能源依赖程度越来越高,随之带来的环境问题和能源可持续性等问题越来越突出。近年来,动力电池在电动汽车、移动通信设备和空间电源等领域应用广泛,锂离子电池因其高容量和循环充电无记忆性等优点被广泛应用于动力系统中。锂离子电池单体电压低,为满足动力系统高电压、大电流的需求通常将若干锂离子电池单体串联使用,随着电池组循环使用,电池不一致性逐渐加大,使得电池过冲过放频繁给电池造成不可修复损伤,严重时可能引起电池爆炸,稳定高效的电池均衡系统是解决这一问题的唯一途径。本文的主要目的是针对电池组的不一致性建立一套稳定高效的均衡系统方案。本文采用仿真与实验相结合的方式来进行理论分析与功能验证,首先对电池组不一致性产生的原因和影响进行分析,然后对体现电池不一致性的均衡元素分别进行验证分析,得出最为合适的均衡检测变量,为均衡系统的建立提供依据。本文提出的均衡系统主要分为监控模块、主控模块、算法控制模块和均衡电路四大模块,监控模块采用市场应用成熟的AD7820A芯片解决方案,可以提供电池单体电压、电流和温度的精确采集,以MSP430微控制器作为主控系统协调各模块的运行。针对目前相关研究人员提出繁多的均衡电路方案进行比较分析,选取并优化了Cük电路作为高效均衡电路,此Cük变形电路拥有双向充放电、在整个周期内可持续均衡等优点,是高效的均衡电路拓扑结构。本文高效策略的研究还在于电池均衡的智能化,分析了模糊控制理论在电池均衡中应用的优缺点,将自适应神经网络与模糊算法很好结合的ANFIS系统引入到电池均衡系统中。ANFIS系统的模糊化可避免复杂电池模型的建立有效利用认为经验,同时随电池使用中状态的变化来自适应调整控制系统,使均衡系统有高效的均衡输出。本文以FPGA为硬件载体实现ANFIS系统,得到一套完整高效的均衡系统。此系统经仿真分析与实验验证,系统高效稳定,易于模块化实现,对于大容量动力电池组的高效均衡提供了有效的解决方案。
[Abstract]:With the rapid development of modern economy, people rely more and more on fossil energy such as petroleum and natural gas, and the environmental problems and energy sustainability become more and more prominent. In recent years, power battery has been widely used in electric vehicles, mobile communication equipment and space power supply, and lithium ion battery has been widely used in power system because of its high capacity and memoryless rechargeability. In order to meet the demand of high voltage in power system, a number of lithium ion battery units are usually used in series to meet the high voltage of lithium ion battery. With the battery recycling, the cell inconsistency increases gradually. The battery overshoot and overdischarge frequently cause irreparable damage to the battery, which may cause battery explosion when serious. A stable and efficient battery equalization system is the only way to solve this problem. The main purpose of this paper is to establish a stable and efficient equalization system for battery pack inconsistency. In this paper, theoretical analysis and functional verification are carried out by combining simulation and experiment. Firstly, the causes and effects of battery pack inconsistency are analyzed, and then the equilibrium elements which reflect the battery inconsistency are verified and analyzed respectively. The most suitable equilibrium detection variable is obtained, which provides the basis for the establishment of the equalization system. The proposed equalization system is divided into four modules: monitoring module, main control module, algorithm control module and equalization circuit. The monitoring module adopts the mature solution of AD7820A chip, which can provide battery cell voltage. The accurate collection of current and temperature, the MSP430 microcontroller as the main control system to coordinate the operation of each module. According to the comparison and analysis of various equalization circuit schemes put forward by relevant researchers at present, C 眉 k circuit is selected and optimized as an efficient equalization circuit. This C 眉 k deformed circuit has the advantages of bidirectional charging and discharging, sustainable equalization throughout the whole cycle, etc. It is an efficient topology of equalization circuit. The research of high efficiency strategy in this paper also lies in the intelligence of battery equalization. The advantages and disadvantages of fuzzy control theory applied in battery equalization are analyzed. Introducing the adaptive neural network and fuzzy algorithm into the fuzzy system of the battery equalization system can avoid the effective use of the complex battery model. At the same time, it adaptively adjusts the control system with the change of the state of the battery in use, so that the equalization system has an efficient equalization output. In this paper, FPGA is used as the hardware carrier to realize the ANFIS system, and a complete and efficient equalization system is obtained. Simulation analysis and experimental verification show that the system is efficient and stable and easy to be realized by modularization, which provides an effective solution for the efficient equalization of large capacity power batteries.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM912

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