一种基于简化电化学模型的锂电池互联状态观测器

An interconnected state observer for lithium-ion battery based on reduced electrochemical model

锂电池正、负极固相浓度分布以及荷电状态的精确估计对于开发锂电池工作状态的实时监控算法,进而构建高效、可靠的锂电池管理系统具有重要意义.本文基于多孔电极理论和浓度理论,提出基于扩展单粒子模型的锂电池关键内部参数识别的优化模型和方法;在该电化学模型简化的基础上,提出一种基于H_∞鲁棒控制理论框架的锂电池新型双向互联观测器,可同时实现对锂电池正、负电极浓度及荷电状态的估计,并通过对比分析不同工况下的仿真结果和实验数据,对所提出的互联观测器性能进行了系统验证.结果表明:所设计的互联观测器能够准确预测锂电池的输出电压和荷电状态,有效提高了锂电池系统模型的动态性能和鲁棒稳定性,为锂电池管理系统的开发奠定了理论基础.

The accurate estimation of the solid concentration distribution in anode and cathode, and state-of-charge（SOC）for a Li-ion battery cell is significantly important for developing the real-time monitoring algorithm of the Li-ion cell＇s working operation, and further establishing an efficient and reliable advanced battery management system（BMS）. Firstly,according to the porous electrode theory and concentration theory, in this article we present a systematic optimized model and a method of identifying the key internal state parameters based on a Li-ion cell＇s enhanced single-particlemodel（ESPM）, in which, an appropriate parameter vector is identified in the typical hybrid-pulse-power-characterization（HPPC） operation scenario by using the parameter sensitivity analysis method, and then this parameter optimization problem is evaluated by genetic algorithm. It is verified that the maximum relative errors of the cell＇s output voltage for ESPM are 1.92%, 3.18% and 2.86% under HPPC, 1 C-discharge and urban dynamometer driving schedule（UDDS）current profiles, respectively. Secondly, by introducing some assumptions and reduction techniques, the battery ESPM is further reduced and then a novel interconnected state observer is proposed through the combination of the reduced ESPM and H∞robust control theory framework, which can realize the concurrent estimation of solid concentration and SOC in anode and cathode. Finally, the comparative validation and analysis study are conducted by using the experimental data acquired in HPPC and UDDS condition to demonstrate the effectiveness and feasibility of the proposed interconnected observer. The results show that the maximum relative errors of output voltage for the ESPM, the single-electrode concentration observer（Obsv-1） and the proposed interconnected observer（Obsv-2） of Li-ion cell are 2.0%, 3.8% and2.6%, respectively, under HPPC operation at 23？C; under the same input current profile and operating condition, the maximum relative errors of SOC estimation are 2.4%, 4.7% and 3.4%, respectively. Moreover, the maximum relative errors of cell＇s output voltage for ESPM, Obsv-1 and Obsv-2 model are 1.9%, 3.2% and 2.1%, respectively, and the maximum relative errors of SOC estimation values for these three mathematical models are 2.1%, 4.4% and 3.2%,respectively. It is concluded that the proposed robust observer for a Li-ion cell can accurately predict the output voltage and SOC, and can also improve the dynamic performance and robust stability of Li-ion cell, which provides a solid theoretical foundation for developing the BMS.