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Due to its accuracy, simplicity, and other advantages, the Kalman filter method is one of the common algorithms to estimate the state-of-charge (SOC) of batteries. However, this method still has its shortcomings. The Kalman filter method is an algorithm designed for linear systems and requires precise mathematical models. Lithium-ion batteries are not linear systems, so the establishment of the battery equivalent circuit model (ECM) is necessary for SOC estimation. In this paper, an adaptive Kalman filter method and the battery Thevenin equivalent circuit are combined to estimate the SOC of an electric vehicle power battery dynamically. Firstly, the equivalent circuit model is studied, and the battery model suitable for SOC estimation is established. Then, the parameters of the corresponding battery charge and the discharge experimental detection model are designed. Finally, the adaptive Kalman filter method is applied to the model in the unknown interference noise environment and is also adopted to estimate the SOC of the battery online. The simulation results show that the proposed method can correct the SOC estimation error caused by the model error in real time. The estimation accuracy of the proposed method is higher than that of the Kalman filter method. The adaptive Kalman filter method also has a correction effect on the initial value error, which is suitable for online SOC estimation of power batteries. The experiment under the BBDST (Beijing Bus Dynamic Stress Test) working condition fully proves that the proposed SOC estimation algorithm can hold the satisfactory accuracy even in complex situations. [ABSTRACT FROM AUTHOR]

Abstract: Co3O4/graphene nanosheet (GNS) composites were synthesized via the in situ growth of mesoporous Co3O4 nanoparticles on graphene. The as-prepared Co3O4/GNS composites exhibited superior Li-ion battery performance and showed a large reversible capacity, excellent cycling, and good rate capability when used as an anode material in lithium ion batteries (LIBs). The uniform coating of Co3O4 around the graphene surface ensured tight electrical contact, resulting in a material with higher specific capacity and enhanced cycling performance compared with pure Co3O4 electrodes. The composites delivered a reversible capacity of 900mAhg−1 at a discharge current density of 100mAg−1 with good cycling ability. Moreover, the composites showed exceptional high-current charge–discharge performance, achieving 650mAhg−1 at a current density of 1000mAg−1. [Copyright &y& Elsevier]

In response to an increasing demand for understanding electrochemical processes on the nanometer scale, it now becomes possible to monitor electron transfer reactions at the single-nanoparticle level, namely particle collision electrochemistry. This technique has great potential in the development of research tools towards single-particle electrocatalysis and selective and multiplexed particle sizing. However, one existing problem that may discourage these applications is the relatively weak colloidal stability of nanoparticles in an electrolytic solution. Here we report on a facile but efficient way to achieve a good stability of gold nanoparticles in an acidic media so that ‘zero-aggregation’ collisions can be achieved at a carbon ultramicroelectrode. This allows us to obtain anodic dissolution currents from individual nanoparticles in a ‘one particle at a time’ manner, based on which accurate particle sizing with a resolution of 1–2 nm can be achieved. Our work strongly suggests that to maintain a well dispersed nanoparticle solution during a particle impact electrochemical experiment is critically important for accurate particle sizing, as well as other applications that require information to be extracted from individual nanoparticles (not their aggregates). [ABSTRACT FROM AUTHOR]