电动汽车动力电池状态估计方法与均衡控制技术研究

项目名称： 电动汽车动力电池状态估计方法与均衡控制技术研究

项目编号： No.61273097

项目类型： 面上项目

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： 崔纳新

作者单位： 山东大学

项目金额： 82万元

中文摘要： 动力电池作为电动汽车的核心，是制约其规模发展的瓶颈。动力电池高效管理、优化控制和寿命延长对于电动汽车的使用成本、节能和安全性至关重要，也是电动汽车普及的先决条件之一。电池是一类复杂的非线性、多变量耦合、参数时变系统，其成组使用存在的性能衰减、一致性、安全性等问题日益凸显并亟待解决。本课题拟首先研究动力电池非线性动态建模，并基于自校正融合Kalman滤波理论研究慢时变模型参数的实时辨识；然后结合非线性鲁棒最优估计和主元分析法研究电池SOC、SOH等状态估计及剩余寿命RUL预测问题；引入博弈论思想研究电池均衡控制策略，并设计模块化可扩展均衡电路拓扑；最后搭建电池管理系统试验平台验证新模型新理论方法的有效性。本课题属于控制理论、电气工程、电化学等多学科交叉的前沿，不仅对发展我国电动汽车技术推进其产业化具有重要意义，而且对于相关学科的理论研究和应用有显著的促进作用。

中文关键词： 动力电池；电池模型；状态估计；主动均衡；

英文摘要： Power battery is the core component of the electric vehicles (EVs) and the key factor which restricts the development of EVs. Its efficiency management, optimal control and life extended are very crucial for EVs' cost, safety and energy conservation, and also one of the important conditions for the popularization of EVs. The battery is a system with complex nonlinear, multivariable and time-varying parameters. The performance decay, consistency and security have become increasingly significant due to the battery modular used in energy storage system and urgently need to be solved. Firstly nonlinear dynamic battery model will be proposed, and the model parameters will be identified online based on self-tuning fusion Kalman filter theory. Then combined with the nonlinear robust optimal estimation theory, compression perception and principal component analysis method are used to investigate the SOC, SOH, and other state estimation and the accurate prediction of RUL. The method of game theory is applied to solve the battery equalization problem and extended modulization circuit will be designed. At last a battery management system test platform will be built to verify the validities of the new models and the new methods. This project involves the interdisciplinary frontiers of control theory, electrical engineerin

英文关键词： Power Battery；Battery Model；State Estimation；Active Equilization；