锂离子电池健康评估研究进展

锂离子电池以其优越的性能成为电动汽车的主流动力源。然而，与其他化学电源一样，锂离子电池在使用过程中会逐渐暴露出倍率、能量和功率性能衰退的问题。围绕电池老化机理和状态估计方法进行系统地综述。此外，还总结了未来锂离子电池应用方面的挑战和前景，以期为电池管理系统的开发和设计提供一些启发。     

基于数据-模型驱动的锂离子电池健康状态估计

本文以容量和能量为电池健康表征参数进行电池健康状态(State of health, SOH)评估方法研究。首先分别采用两种方法进行健康状态估计：一种是直接输入原始电池容量、能量序列,利用灰色预测算法(Metabolic grey algorithm, MGA)对电池容量和能量进行预测;另一种是先输入原始模型参数,利用灰色预测算法对简化电化学-老化模型(Simplifiedelectrochemical model, SEM)参数进行预测,将预测后的参数值代入到模型当中,拟合电池端电压曲线,再通过积分法获取电池的容量和能量。针对两种健康表征参数衰退速度、估计精度等问题,提出基于数据-模型混合驱动的锂离子电池健康状态的综合评估方法,实现电池健康状态的准确估计。     

Research on Fossil Fuel Related Carbon Emissions Reduction Scheme Effects

There is a worldwide consensus that excessive anthropogenic carbon dioxide emissions will lead to global warming and other environmental problems. Supports from regulations and policies have gradually implemented in this area. As one of the most discussed policies, the carbon emissions trading schemes(CETS) has an advantage in its price-oriented and cost-saving characteristics. In this paper, we analyze and assess the CETS effect from static and dynamic perspectives by applying provincial panel data covering a period ranging from 2004 to 2017. The CETS policy has a significant constraining effect on both carbon emissions and primary energy consumption. Compared to the other two uncertainties, namely the energy price uncertainty and the technology uncertainty, the carbon permit price uncertainty has a relatively smooth impact on the economy, which is being pursued consistently by the policymakers.