六自由度振动老化条件下锂离子电池的 衰退机理诊断与 SOH 预测
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TH707

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河北省自然科学基金创新群体项目(E2020202142)、河北省自然科学基金项目(E2020202221)资助


Diagnosis of degradation mechanism and SOH prediction of lithium-ion batteries under 6-DOF vibration and aging conditions
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    摘要:

    电动汽车锂离子电池会受振动与老化影响而加速衰减,为了诊断振动老化条件下的衰退机理,实现健康状态( SOH)预 测,采取如下措施:首先,分析电池受振动影响的衰减结果;其次,辨识衰退模式,利用容量增量-微分电压( IC-DV)曲线对衰退 模式进行量化,Z 组结果为:活性物质损失(36. 94% )、锂离子损失(35. 12% )、电导率损失(1. 9% );最后,将量化结果输入建立 的 GA-Elman 模型实现 SOH 预测,结果误差保持在 5% 以内,满足电池管理系统(BMS)预测的要求。 该研究为振动老化条件下 锂离子电池的衰退机理诊断与 SOH 预测提供了依据,有助于 BMS 制定相关策略延长电池使用寿命。

    Abstract:

    The lithium-ion battery in electric vehicle may decay quickly due to vibration and aging. One purpose of this research is to diagnose the degradation mechanism under such conditions. The other is to realize the state of health ( SOH) prediction. The specific methods are given as follows. First, the attenuation results of the battery affected by vibration are analyzed. Secondly, the degradation mode is identified. Then, the incremental capacity-differential voltage ( IC-DV) curve is used to quantify the degradation mode. The results of group Z are illustrated as follows. The loss of active material is 36. 94% , the loss of lithium ions is 35. 12% , and the conductivity loss is 1. 9% . Finally, the quantified results are taken as the input to formulate the GA-Elman model to realize SOH prediction. The errors are within 5% , which can meet the requirements of battery management system (BMS). This research provides a basis for the diagnosis and SOH prediction of lithium-ion batteries under vibration and aging conditions. It could help BMS formulate relevant strategies to extend battery life.

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李文华,邵方旭,暴二平,何明泽,王洋洋.六自由度振动老化条件下锂离子电池的 衰退机理诊断与 SOH 预测[J].仪器仪表学报,2021,(8):62-69

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  • 在线发布日期: 2023-06-28
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