Estimation Method of State-of-Charge For Lithium-ion Battery Used in Hybrid Electric Vehicles Based on Variable Structure Extended Kalman Filter

Since the main power source of hybrid electric vehicle（HEV） is supplied by the power battery,the predicted performance of power battery,especially the state-of-charge（SOC） estimation has attracted great attention in the area of HEV.However,the value of SOC estimation could not be greatly precise so that the running performance of HEV is greatly affected.A variable structure extended kalman filter（VSEKF）-based estimation method,which could be used to analyze the SOC of lithium-ion battery in the fixed driving condition,is presented.First,the general lower-order battery equivalent circuit model（GLM）,which includes column accumulation model,open circuit voltage model and the SOC output model,is established,and the off-line and online model parameters are calculated with hybrid pulse power characteristics（HPPC） test data.Next,a VSEKF estimation method of SOC,which integrates the ampere-hour（Ah） integration method and the extended Kalman filter（EKF） method,is executed with different adaptive weighting coefficients,which are determined according to the different values of open-circuit voltage obtained in the corresponding charging or discharging processes.According to the experimental analysis,the faster convergence speed and more accurate simulating results could be obtained using the VSEKF method in the running performance of HEV.The error rate of SOC estimation with the VSEKF method is focused in the range of 5% to 10% comparing with the range of 20% to 30% using the EKF method and the Ah integration method.In Summary,the accuracy of the SOC estimation in the lithium-ion battery cell and the pack of lithium-ion battery system,which is obtained utilizing the VSEKF method has been significantly improved comparing with the Ah integration method and the EKF method.The VSEKF method utilizing in the SOC estimation in the lithium-ion pack of HEV can be widely used in practical driving conditions.

Nonparametric VSS-APA based on precise background noise power estimate

The adaptive algorithm used for echo cancellation(EC) system needs to provide 1) low misadjustment and 2) high convergence rate. The affine projection algorithm(APA) is a better alternative than normalized least mean square(NLMS) algorithm in EC applications where the input signal is highly correlated. Since the APA with a constant step-size has to make compromise between the performance criteria 1) and 2), a variable step-size APA(VSS-APA) provides a more reliable solution. A nonparametric VSS-APA(NPVSS-APA) is proposed by recovering the background noise within the error signal instead of cancelling the a posteriori errors. The most problematic term of its variable step-size formula is the value of background noise power(BNP). The power difference between the desired signal and output signal, which equals the power of error signal statistically, has been considered the BNP estimate in a rough manner. Considering that the error signal consists of background noise and misalignment noise, a precise BNP estimate is achieved by multiplying the rough estimate with a corrective factor. After the analysis on the power ratio of misalignment noise to background noise of APA, the corrective factor is formulated depending on the projection order and the latest value of variable step-size. The new algorithm which does not require any a priori knowledge of EC environment has the advantage of easier controllability in practical application. The simulation results in the EC context indicate the accuracy of the proposed BNP estimate and the more effective behavior of the proposed algorithm compared with other versions of APA class.

Adaptive Fuzzy Controller Using Nearest Neighborhood Clustering and Its Application

A novel control method for the nonlinear and complex plants with environmental uncertainties and variable parameters has been proposed by use of the nearest neighborhood clustering algorithm, the fuzzy control and the variable regressive estimation (VRE) technology. It overcomes the defects of the other adaptive methods such as the strong dependence to the system and the difficulty of the acquirement of the professional knowledge during the modifying period of the rules. The application of new algorithm to the electrical heating furnace with multiple zones demonstrates the advantages of the proposed method.

Institutional Distance and CrossNational Income Gaps

ihis paper examines the root causes of current cross-national institutional difference from the perspective of national hetereogeneity and provides detailed explanations on the justification and effectiveness of using cross-national genetic distance as the instrumental variable （IV） of institutional difference. We combined 10,585 samples by pairing 146 countries and regions, created a cross-national institutional distance variable composed of 14 indicators from the World Bank and the Heritage Foundation in three aspects including differences of political system, economic system and institutional implementation attributes, and conducted a cross-section IV estimation for the long-term effect of institutional differences on cross-national income gaps using data between 1996 and 2010. Empirical results indicate that institutional difference has a long-term significant positive effect on cross-national income gaps and such an effect has a tendency to increase during sample period. With factors like human capital, geographical factor, language and religion under control, we still arrived at similar conclusions. The empirical results are demonstrated to be robust using different genetic distance measurement indicators and estimation methods.

Innovation,financial permeation,and income inequality:From a dynamicperspective in China

Innovation is a driving force of wealth distribution.To explore its time-varying effect on income inequality,we propose a nonparametric model using the local linear dummy variable estimation(LLDVE)method.Based on province-level panel data from China spanning from 2006 to 2020,we find that innovation initially reduces income disparity until 2009,then exacerbates it from 2013 to 2016,and alleviates inequality again over 2018-2020.We further verify that financial permeation serves as a catalyst in the inequitable income distribution driven by innovation.However,this moderating effect reverses the relationship between green innovation and income inequality.This suggests that we should enhance the financial service towards all aspects of innovation beyond its support of green innovation.

Local Linear Estimation by TSLS with Variable Bandwidth for Semi-parametric Simultaneous Equation Models in Econometrics

Econometric simultaneous equation models play an important role in making economic policies, analyzing economic structure and economic forecasting. This paper presents local linear estimators by TSLS with variable bandwidth for every structural equation in semi-parametric simultaneous equation models in econometrics. The properties under large sample size were studied by using the asymptotic theory when all variables were random. The results show that the estimators of the parameters have consistency and asymptotic normality, and their convergence rates are equal to n^-1/2. And the estimator of the nonparametric function has the consistency and asymptotic normality in interior points and its rate of convergence is equal to the optimal convergence rate of the nonparametric function estimation.