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中国物理学会期刊

基于改进LSP2D的锂离子电池电化学模型降阶重构方法

Reduced order reconstruction method of lithium ion battery electrochemical model based on improved LSP2D

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  • 电化学建模对于锂离子动力电池的运行状态估计、全生命周期故障诊断、多工况安全管控等具有重要意义,但早期提出的伪二维电化学模型由于参数繁多且辨识困难等问题,很难真正应用于工程实践。针对目前基于固液相扩散过程近似重构的LSP2D模型难以满足高倍率工况的难题,通过在液相浓度变化过程近似中引入液相扩散表征项,提出一种基于改进LSP2D的锂离子电池电化学模型降阶重构方法。算例仿真结果表明改进LSP2D模型在各倍率下的预测精度均优于传统LSP2D模型。对于液相锂离子浓度而言,1C-7C放电倍率下改进LSP2D模型较传统LSP2D模型的预测精度均提升86.96%以上;对于端电压而言,放电倍率为1C-3C时,改进LSP2D模型较传统LSP2D模型的预测精度均提升97.12%以上;放电倍率为4C-7C时,改进LSP2D模型较传统LSP2D模型的预测精度均提升29.56%以上。文中所提方法可以为锂离子电池电化学模型高精度降阶重构提供新的思路,对于提高锂离子动力电池电化学模型的工程实用性具有一定意义。

    Electrochemical modeling is of great significance for estimating the operational state, performing full-life-cycle fault diagnosis, and enabling multi-condition safety management of lithium-ion power batteries. However, early proposed pseudo-two-dimensional electrochemical models are difficult to apply in engineering practice due to issues such as numerous parameters and challenging identification. To address the problem that current LSP2D models based on approximate reconstruction of solid–liquid phase diffusion processes struggle to meet high-rate conditions, this paper proposes a reduced-order reconstruction method for lithium-ion battery electrochemical models based on an improved LSP2D model. By refining the third-order parabolic approximation of the liquid-phase lithium-ion concentration and innovatively introducing a liquid-phase diffusion characterization term during the approximation process, the method achieves accurate characterization of the lithium-ion diffusion process dominated by concentration gradients under high-rate conditions. Simulation results show that while computational efficiency remains comparable, the improved LSP2D model outperforms the traditional LSP2D model in prediction accuracy across various rates. For liquid-phase lithium-ion concentration, the prediction accuracy of the improved LSP2D model is increased by over 86.96% compared to the traditional model at discharge rates of 1C–7C. For terminal voltage, the improvement exceeds 97.12% at 1C–3C discharge rates, and remains above 29.56% at 4C–7C discharge rates. Furthermore, the theoretical reasons for the significantly lower accuracy improvement at 4C–7C compared to 1C–3C are discussed, providing direction for subsequent research on reduced-order reconstruction of electrochemical models under high-rate conditions. The proposed method offers a new approach for high-accuracy reduced-order reconstruction of lithium-ion battery electrochemical models and contributes to enhancing the engineering practicality of electrochemical models for lithium-ion power batteries.

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