Currently, Lithium-ion batteries (LiB) are widely applied in energy storage devices in smart grids and electric vehicles. The state of charge (SOC) is an indication of the available battery capacity, and is one of the most important factors that should be monitored to optimize LiB’s performance and improve its lifetime. However, because the SOC relies on many nonlinear factors, it is difficult to estimate accurately. This paper presented the design of an effective SOC estimation method for a LiB pack Battery Management System (BMS) based on Kalman Filter (KF) and Artificial Neural Network (ANN). First, considering the configuration and specifications of the BMS and LiB pack, an ANN was constructed for the SOC estimation, and then the ANN was trained and tested using the Google TensorFlow open-source library. An SOC estimation model based on the extended KF (EKF) and a Thevenin battery model was developed. Then, we proposed a combined mode EKF-ANN that integrates the estimation of the EKF into the ANN. Both methods were evaluated through experiments conducted on a real LiB pack. As a result, the ANN and KF methods showed maximum errors of 2.6% and 2.8%, but the EKF-ANN method showed better performance with less than 1% error.

Recently, in order to overcome the difficulties of interrupting fault currents in multi-terminal direct current systems (MTDC), studies combining a saturated iron-core type superconducting current limiter (SFCL) and a direct current circuit breaker (DCCB) have been conducted. However, the effect of inductance change of the SI-SFCL on the interrupting time of the DCCB during fault has not been studied yet. In this paper, the interrupting time delay caused by the dynamic behavior of the inductance change during the fault current blocking process of the SI-SFCL combined with a DCCB was analyzed through experiments and a new fault detection method considering this phenomenon was proposed. After designing and manufacturing the laboratory-scale SI-SFCL and DCCB, a fault current interrupting test was performed and the inductance change pattern of the SI-SFCL was analyzed. Based on the analysis results, a new fault detection technique was proposed to alleviate the interruption time delay that occurs when applying the combined protection system to a MTDC, and its effectiveness was verified through a simulation. These results will be useful for planning protection coordination strategies when introducing a SI-SFCL in combination with a DCCB in actual MTDC systems.

A saturated iron-core superconducting fault current limiter (SI-SFCL) can significantly limit the magnitude of the fault current and reduce the stress on circuit breakers in direct current (DC) power systems. The SI-SFCL consists of three main parts: one magnetic iron-core, one normal conductive primary coil (CPC), and one superconducting secondary coil (SSC). This paper deals with the design options for the coil system of the SI-SFCL and confirms their operating characteristics through a physical experiment. The electromagnetic characteristics and operational features of the SI-SFCL was analyzed by a 3D finite element method simulation model. The design of the SSC was based on shape, wire types, required fault current limit and protection aspects. In the CPC, the bobbin was designed based on material selection, cost, structural design, and the effects of the SI-SFCL on the fault current limit. Based on these simulation results, a laboratory-scale SI-SFCL was developed, specifically fabricated to operate on a 500 V, 50 A direct current (DC) power system. In the experiment, the operating characteristics of each coil were analyzed, and the fault current limit of the SI-SFCL according to the operating currents of the SSC and bobbin design of the CPC were confirmed. Finally, the cost analysis of the SI-SFCL with the proposed design options of the coil system was implemented. The results obtained through this study can be effectively used to large-scale SI-SFCL development studies for high-voltage direct current (HVDC) power systems.