基于电化学老化衰退模型的锂离子动力电池外特性

当前锂离子动力电池电化学模型存在模型复杂、建模难度大、计算效率低、老化评估效果差的问题,本文提出一种考虑电池衰退老化的机理模型(ADME).本文首先通过有限差分法对伪二维(P2D)电化学模型进行离散降阶处理,得到简化伪二维(SP2D)模型.在SP2D模型的基础上,基于阴阳两极发生的副反应导致的衰退老化现象,提出一种考虑电池衰退老化的机理模型.其次,使用多变量偏差补偿最小二乘法实现模型参数辨识.最后通过动力电池衰退老化性能循环实验,对比分析了恒流、脉冲工况下SP2D模型和ADME模型的终端电压输出.结果表明:ADME模型较为简单、计算效率和估算精度高,可以有效评估电池容量老化衰退,得到理想的锂离子动力电池外特性曲线.     

Synthesis of yolk-shell Bi2O3@TiO2 submicrospheres with enhanced potassium storage

Science China Chemistry - Due to their enormous potential for large-scale energy storage, rechargeable potassium-ion batteries have been widely researched and developed. However, the drastic volume...     

Enhanced thermoelectric performance of PEDOT:PSS films via ionic liquid post-treatment

Thermoelectric(TE)energy harvesting can effectively convert waste heat into electricity,which is a crucial technology to solve energy concerns.As a promising candidate for energy conversion,poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate)(PEDOT:PSS)has gained significant attention owing to its easy doping,high transparency,and solution processability.However,the TE performance of PEDOT:PSS still needs to be further enhanced.Herein,different approaches have been applied for tuning the TE properties:(i)direct dipping PEDOT:PSS thin films in ionic liquid;(ii)post-treatment of the films with concentrated sulfuric acid(H₂SO₄),and then dipping in ionic liquid.Besides,the same bis(trifluoromethanesulfonyl)amide(TFSI)anion and different cation salts,including 1-ethyl-3-methylimidazolium(EMIM+)and lithium(Li+),are selected to study the influence of varying cation types on the TE properties of PEDOT:PSS.The Seebeck coefficient and electrical conductivity of the PEDOT:PSS film treated with H2SO4EMIM:TFSI increase simultaneously,and the resulting maximum power factor is 46.7μW·m^-1·K^-2,which may be attributed to the ionic liquid facilitating the rearrangement of the molecular chain of PEDOT.The work provides a reference for the development of organic films with high TE properties.     

Output feedback regulation of large-scale feedforward systems with discrete and distributed delays

Nonlinear Dynamics - This paper proposes an output feedback control strategy to achieve the global regulation of a class of large-scale feedforward nonlinear systems with discrete and distributed...     

On the balanced domination of graphs

Czechoslovak Mathematical Journal - Let G = (VG,EG) be a graph and let NG[υ] denote the closed neighbourhood of a vertex υ in G. A function f: VG ? {?1,0,1} is said to be a...     

Experimental and Numerical Simulation Research on Boundary Layer Transition Front over a Swept Wing at M = 6

Fluid Dynamics - To predict the boundary layer transition on swept wings, experimental and numerical researches were conducted to obtained the accurate boundary layer transition front and to...     

Power spectral density analysis for nonlinear systems based on Volterra series

Applied Mathematics and Mechanics - A consequence of nonlinearities is a multi-harmonic response via a mono-harmonic excitation. A similar phenomenon also exists in random vibration. The power...     

Differential Entropy of Induced Random State Ensemble

International Journal of Theoretical Physics - In this paper, we will consider the exact calculation of differential entropy of induced random state ensemble by partial tracing a subsystem over...     

A Neural Network-Based Policy Iteration Algorithm with Global $$H^2$$ -Superlinear Convergence for Stochastic Games on Domains

In this work, we propose a class of numerical schemes for solving semilinear Hamilton–Jacobi–Bellman–Isaacs (HJBI) boundary value problems which arise naturally from exit time problems of diffusion processes with controlled drift. We exploit policy iteration to reduce the semilinear problem into a sequence of linear Dirichlet problems, which are subsequently approximated by a multilayer feedforward neural network ansatz. We establish that the numerical solutions converge globally in the \(H^2\)-norm and further demonstrate that this convergence is superlinear, by interpreting the algorithm as an inexact Newton iteration for the HJBI equation. Moreover, we construct the optimal feedback controls from the numerical value functions and deduce convergence. The numerical schemes and convergence results are then extended to oblique derivative boundary conditions. Numerical experiments on the stochastic Zermelo navigation problem are presented to illustrate the theoretical results and to demonstrate the effectiveness of the method.