Comparison analysis of efficiency between double-synchronous step-down-stress and step-up-stress accelerated life tests

Double-crossed-step-stress (DCSS) accelerated life test (ALT) method is widely used for estimating the lifetime of products with high reliability and long lifetime. In order to further reduce the test time and test cost, a double-synchronous-step-stress (DSSS) ALT method which combines a double-synchronous-step-down-stress (DSSDS) ALT method and a double-synchronous-step-up-stress (DSSUS) ALT method is proposed. The accelerated stresses decrease and increase in a synchronous way with one step in the DSSDS-ALT and DSSUS-ALT methods, respectively. Monte Carlo method is adopted to simulate the two methods, and the validity and efficiency of them are demonstrated by the simulation results. In addition, a comparison analysis of efficiency between DSSDS-ALT method and DSSUS-ALT method is carried out. The result shows that the DSSDS-ALT method compared with the DSSUS-ALT method can significantly improve the test efficiency under the same test condition.     

随机放电工况下锂离子电池容量预测方法

针对锂离子电池容量预测精度不高的问题,提出一种基于人群搜索优化的支持向量机(seeking optimization algorithm-support vector machine, SOA-SVM)的容量预测方法。通过分析锂离子电池随机放电过程,构建反映容量变化的随机放电容量均值和标准差两个指标,并以此作为预测容量的特征参数。采用主成分分析法分析特征参数之间的相关性,并提取主成分。基于部分测试电池第1主成分和容量数据,采用SOA对SVM超参数进行全局优化并训练模型。采用优化后的模型结合其余电池第1主成分数据预测锂离子电池容量。预测结果表明,本文中提出的锂离子电池容量预测方法具有较高的预测精度。