【摘要】 在Newman模型以及单粒子模型(SPM)的基础上,提出基于Legendre正交多项式的电池模型降阶算法;同时,将固液相物理量的分布纳入模型算法,在提高运算速度的情况下,保证运算精度。以磷酸铁锂(Li Fe PO4)正极锂离子电池为例,对导出的降阶模型进行仿真验证。与全阶模型相比,该模型所计算的电池状态量误差均能保持在2%下。更多还原

【Abstract】 A model order reduction algorithm based on the classical Newman model and the single particle model(SPM) using Legendre orthogonal polynomials method was proposed in which the distribution of physical variables in both liquid and solid phase was included,while the calculation speed was improved,a relatively high calculation precision was guaranteed.As an example,a lithium-iron-phosphate Li-ion battery was simulated in order to validate the proposed model.In comparison with full-order model,the proposed model was proven to indicate an error smaller than 2% of estimated battery states.更多还原