电动汽车动力电池组不确定性建模和状态多尺度估计方法研究

项目名称： 电动汽车动力电池组不确定性建模和状态多尺度估计方法研究

项目编号： No.51507012

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 电工技术

项目作者： 熊瑞

作者单位： 北京理工大学

项目金额： 21万元

中文摘要： 动力电池是电动汽车的技术瓶颈，其状态估计关乎能量管理、循环寿命、使用成本和安全，研究具有理论意义和应用价值。针对电动汽车锂离子动力电池成组状态估计的基础问题，研究：(1)建立动力电池单体n阶通用模型，采用信息熵理论研究模型复杂度、精度与实时性的权衡问题，建立基于数据-模型融合的参数和状态联合估计算法，探究系统时变特性、采样间隔、计算步长和参数变化路径等对状态估计的影响规律；(2)采用统计学理论揭示动力电池成组前后的不一致特性耦合机理，筛选单体样本表征总体水平，应用面向可靠性和实时性要求的不确定性优化方法，建立动力电池组预测模型；(3)研究动力电池组的强时变非线性非均一等复杂特性，揭示动力电池成组的电性能变化规律，提出动力电池组多维多尺度状态联合估计方法，实现动力电池组状态的高精度在线估计。研究成果将为电动汽车动力电池管理系统奠定新的理论基础，对提高动力电池组的能效具有重要的理论指导意义。

中文关键词： 电动汽车；锂离子动力电池；不确定性建模；多尺度；状态估计

英文摘要： Battery technology is the bottleneck with electric vehicles. It is important, both in theory and practical application, to do research on the state estimation, which is essential to optimizing energy management, extending the life cycle, reducing cost, and safeguarding the safe application of batteries in electric vehicles. This proposal focuses on the fundamental state estimation problem of lithium-ion battery packs used in electric vehicles. First, this proposal intends to build an n-order general battery model, and uses the information entropy theory to solve the balance calculation problem among model complexity, accuracy and real-time performance. To improve the state estimation accuracy of battery cell, a data and model fusion based joint estimation approach for battery parameter and state has been developed, and the influence factors from time-varying characteristics of battery system, sampling interval, calculation step and parameter degradation path have been investigated accordingly. Second, the proposal uses the statistical theory to analyze the coupling mechanism of the inconsistent characteristics for battery cells before and after their grouping, and the cell sample has been selected accordingly. Then, a real-time reliability battery prediction model has been built based on the uncertainty optimization method. Third, the trajectory of electricity performance for battery packs has been revealed through analyzing their strong time-varying, nonlinear and non-uniform complex characteristic. Then, to achieve accurate online state estimation of battery packs, the multi-dimensional multi-scale joint state estimation approach has been proposed. The research results of this project would provide new theoretical foundation for the battery management system of electric vehicles, and finally improve the energy efficiency of battery packs, both theoretically and meaningfully.

英文关键词： Electric vehicles;lithium-ion battery;uncertainty modeling;multi-scale;state estimation