Research on the SOH Prediction Based on the Feature Points of Incremental Capacity Curve

The accurate prediction of the state of health (SOH) is an important basis for ensuring the normal operation of the lithium-ion battery (LIB). The accurate SOH can extend the life-span, ensure safety, and improve the performance of LIBs. The charging voltage curve and incremental capacity (IC) curve of the LIB in different SOH are obtained through experiments. The location parameters of each feature point on IC curve are closely related to battery aging, to characterize the SOH of the LIB with the location of feature points. To solve the difficulty in identifying feature points due to the oscillation in solving IC curves with a traditional numerical analytic method, the piecewise polynomial fitting method is adopted to smooth IC. To discuss the law between the location change of all feature points on the IC curve and the capacity attenuation, a capacity prediction regression model is established after the dimensionality reduction of the coordinate data of feature points on the IC curve with the principal component analysis method. The proposed method can rapidly estimate the online SOH of LIBs during the charging process of electric vehicles and the results show the maximum error is 0.63AH (3.15%).

Battery Capacity Estimation Based on Incremental Capacity Analysis Considering Charging Current Rate

Incremental capacity analysis (ICA) is widely used in the battery decay mechanism analysis since the features of battery incremental capacity (IC) curves are closely related to battery aging and maximum available capacity. However, the traditional ICA method to estimate battery capacity mainly focuses on a single charging condition, and the influence of charging current on IC curves is ignored. In this paper, an adaptive capacity estimation method based on ICA considering the charging current is established. First, the charging experiments using different charging current rates under different battery aging statuses are designed and conducted. Then, the relationship between battery maximum available capacity, IC curve features, and charging current is investigated. Furthermore, the fitting method and data-driven method considering charging current are proposed and compared. Finally, the capacity estimation results prove the accuracy and adaptability of the proposed method.

Definition of Socio-Economic Impacts of Large-Scale Development Projects within Urban Development

The article focuses on the socio-economic impacts of large-scale urban development projects in cities. Both in Czech cities and large cities around the world, there is increasing pressure on converting previously unused areas (“greenfields”) as well as the areas that no longer serve their original purpose and are inefficiently used (“brownfields”) to new use purposes. As a result, public administration representatives face a difficult decision on how to change the use of these areas to be consistent with the current zoning plan. The resulting decision has to be explained to the public in such a way that they feel they meet the public needs and interests. Decision-makers need valid and accurate inputs to make the right decisions. Therefore, it is necessary to clearly define and describe the procedure for assessing the benefits of these important revitalization or regeneration projects for various segments of the public. Only a small part of the urban development project impacts is of a purely financial character. Therefore, the evaluation process uses modelling of socio-economic impacts, which are evaluated financially, so that the decision-makers are able to compare the most valid impacts to the initial investment costs necessary for converting the territory into the area with new functional use. The research sample consists of important urban development projects in the largest cities in the Czech Republic. Most of these projects consist have a territorial study, which was established as the main source of relevant information for the analyses. The outputs of the research described in the article build on the previous research of the authors, where they defined 3 basic variables - Incremental capacity of jobs, Incremental capacity of the population and Incremental capacity of visitors as the carriers of following project socio-economic impacts on the territory. The research article presents a list of socio-economic impacts defined on the basis of incremental capacities.