电动汽车动力电池SOC与开路端电压的非光滑迟滞特性建模及SOC估算研究

项目名称： 电动汽车动力电池SOC与开路端电压的非光滑迟滞特性建模及SOC估算研究

项目编号： No.61263013

项目类型： 地区科学基金项目

立项/批准年度： 2013

项目学科： 自动化技术、计算机技术

项目作者： 党选举

作者单位： 桂林电子科技大学

项目金额： 44万元

中文摘要： 动力电池高效、安全运行是新能源汽车关键技术之一。动力电池处在随机动态充、放电交替运行状态下过度充电和深度放电，可能导致动力电池不可逆的损坏，并涉及到安全问题。其电荷状态（SOC）是动力电池组动态充放电过程高效、安全管理中关键的状态参数之一。 针对汽车动力电池电化学反应的复杂性和多次充放的漂移问题，从SOC与开路端电压(OCV)所表现出的复杂迟滞特性及稳定的重复一致性角度，以分层建模的方法，解决其漂移问题，实现SOC估计。重点研究：1）基于能够描述机理特性的电池等效电路模型结构，构建一个全新的神经网络OCV预估模型,实现模型的参数与状态同时辨识，基于模型状态实现OCV快速在线估算，可避免因得到OCV需长时间等待问题；2）建立SOC与OCV混合迟滞模型，精细化描述动力电池的非光滑复杂迟滞非线性特性，实现对迟滞非线性的补偿。SOC在线准确估算,将为动力电池智能优化管理提供关键理论和技术支撑。

中文关键词： SOC( State of Charge )；双神经网络电池模型；OCV-SOC关系；扩展卡尔曼滤波；ARMAX模型

英文摘要： The high efficient and safe operation for the electric vehicle power battery is one of the key technologies to the development of new energy vehicle. The battery being over-charged and over-discharged will result in the permanent damage and un-safety including the combustion and blast. Therefore, the battery state of charge (SOC) is one vital state parameter for the high efficient and safe management system of battery under the condition of the dynamic charging and discharging. The drift problem of the frequent charging and discharging and the complexity of the electrochemical reaction for the battery are considered. Basis on the hysteresis behavior relationship between the SOC and the open-circuit voltage (OCV) for the battery and the consistency under the condition of the dynamic charging and discharging,the SOC estimation is realized by the hierarchical modeling，and the drift problem is solved. The main the research includes two respects: 1) the equivalent circuit model based a new neural networks estimation model for the OCV is conducted, in which the parameter and state (SOC) variable in the model are identified at the same time so that the long waiting time for battery to reach a steady state for obtaining for the OCV can be avoided and 2) The hybrid hysteresis model, which is used to describe the characte

英文关键词： SOC ( State of Charge )；Dual neural network battery model；OCV-SOC relationship；Extend Kalman Filter；ARMAX model