Recent research has focused on vanadium redox flow batteries (VRFBs) to address the short lifetimes and fire risks associated with lithium battery systems. While VRFBs offer advantages in safety, they suffer from low energy density and efficiency compared with lithium batteries. To improve VRFB performance, studies are exploring improvements in materials such as anodes, cathodes, and separators and optimizing operations by controlling electrolyte flow rates. However, the impact of current magnitude on VRFB efficiency has been less studied, with few analyses addressing both current and flow rate effects. This research proposes an experimental procedure to evaluate charge/discharge efficiency, energy efficiency, and system efficiency across varying current magnitudes and electrolyte flow rates, using a 40 W VRFB stack composed of four 10 W cells in series. In addition, we introduce a design method for an electrical equivalent circuit model that simulates the VRFB stack, reflecting experimental findings. The model’s accuracy was validated by comparing it with data from 11 full charge/full discharge cycle tests, which varied current and electrolyte amounts.

This paper presents robust input shaping commands with first-order actuators utilizing a classical robust input shaper for practical applications in input shaping technology. An ideal input shaping command can deviate due to actuator dynamics so that the modified command has a detrimental effect on the performance of oscillation reduction in feedforward control applications. A zero-vibration-derivative (ZVDF) shaper with first-order actuators is analytically proposed using a phasor–vector approach, an exponential function for the approximation of the dynamic response of first-order actuators and the usage of the ZVD shaper. In addition, an equivalent transformation is utilized based on the superposition principle for the convenient inclusion of first-order actuator dynamics and is applied to the individual segment input command. The residual deflection and robustness of the proposed robust input shaping commands are numerically evaluated and compared with those of a conventional ZVD shaper with respect to the parameter uncertainties of flexible systems and actuators. The robust input shaping commands that are possible with first-order actuators are experimentally validated, presenting a better robustness and residual deflection reduction performance than the classical ZVD shaper on a mini bridge crane.

Extensive research has been conducted on energy storage systems (ESSs) for efficient power use to mitigate the problems of environmental pollution and resource depletion. Various batteries such as lead-acid batteries, lithium batteries, and vanadium redox flow batteries (VRFBs), which have longer life spans and better fire safety, have been actively researched. However, VRFBs undergo capacity reduction due to electrolyte crossover. Additionally, research on the capacity and state of charge (SOC) estimation for efficient energy management, safety, and life span management of VRFBs has been performed; however, the results of short-term experimental conditions with little change in capacity are presented without considering the rebalancing process of the electrolyte. Therefore, herein we propose a method for estimating the capacity of a VRFB using the cumulative charge and electrolyte volume amount under long-term cycle conditions, including rebalancing. The main point of the estimation method is to design a capacity estimation equation in the form of a power function with the measured cumulative charge of the battery as a variable and to update the initial capacity value applied to the estimation equation with the amount of electrolyte measured at the time of rebalancing. Additionally, the performance verification results of the SOC estimation algorithm using the capacity estimation model were presented using the long-term charge/discharge cycle test data of a 10 W-class single cell.

A balancing circuit in a multi-series battery pack prevents a specific cell from being overcharged by reducing the voltage difference between the cells. Passive cell balancing is widely used for easy implementation and volume and size reduction. For optimal passive cell balancing, the charging/discharging current conditions and the state of charge (voltage condition) of the battery must be determined. In addition, the balancing algorithm must determine an allowable voltage deviation threshold between the cells connected in series to determine whether a specific cell performs a balancing operation. However, previous studies have not dealt with the design of balancing operating conditions in detail. In addition, the balancing time and efficiency improvement effect under specific conditions for arbitrary battery cells used in each previous study were mainly presented. Therefore, this study proposes a variable voltage deviation method in which the threshold for determining the voltage to be balanced is changed by reflecting the battery capacity, rated current specification, open-circuit voltage, and resistance of the balancing circuit. In addition, the voltage management performance and efficiency analysis results of the existing balancing algorithm and the proposed balancing method for the case where there is parameter deviation in the cells of the battery pack are also presented. The proposed method was verified through the simulation and experimental results of a reduced battery module in which three types of battery cells, INR 18650-30Q, INR 18650-29E, and INR 21700-50E, were arranged in 4-series.

Due to the intermittentness and variability of renewable energy sources(RES), flexible power generation is possible, and the importance of an integrated system capable of storing reserve power is increasing. In particular, the instability of the power system is intensifying due to the duck curve phenomenon (the net load between sunrise and sunset decreases rapidly and the demand for power increases for about 3 h after sunset). Therefore, this paper presents the ESS integrated gas turbine (EIGT) system, which is an integrated system of energy storage system (ESS) using micro gas turbine (MGT) and reused battery. This research contributes to verifying the utility of reused battery and compensating a duck curve through operation in a system that integrates an energy storage system using micro gas turbine and reused battery, which are small power sources that can be operated independently of the existing renewable energy. According to the result of this research, the state of health (SOH), state of charge (SOC), internal resistance, temperature, and heating rate of the reused battery were verified by supplying power, which is increased by about 66 % after sunset in a duck curve phenomenon. Accordingly, it may contribute to stabilizing the power system in the duck curve phenomenon.

Battery applications, such as electric vehicles, electric propulsion ships, and energy storage systems, are developing rapidly, and battery management issues are gaining attention. In this application field, a battery system with a high capacity and high power in which numerous battery cells are connected in series and parallel is used. Therefore, research on a battery management system (BMS) to which various algorithms are applied for efficient use and safe operation of batteries is being conducted. In general, maintenance/replacement of multi-series/multiple parallel battery systems is only possible when there is no load current, or the entire system is shut down. However, if the circulating current generated by the voltage difference between the newly added battery and the existing battery pack is less than the allowable current of the system, the new battery can be connected while the system is running, which is called hot swapping. The circulating current generated during the hot-swap operation is determined by the battery’s state of charge (SOC), the parallel configuration of the battery system, temperature, aging, operating point, and differences in the load current. Therefore, since there is a limit to formulating a circulating current that changes in size according to these various conditions, this paper presents a circulating current estimation method, using an artificial neural network (ANN). The ANN model for estimating the hot-swap circulating current is designed for a 1S4P lithium battery pack system, consisting of one series and four parallel cells. The circulating current of the ANN model proposed in this paper is experimentally verified to be able to estimate the actual value within a 6% error range.

The cathode active material, which is one of the four elements constituting a lithium-ion battery (LIB), determines the capacity and power of the battery, making it an important factor that determines the performance of the battery. In this study, NCM, LFP, and LMO, which are representative cathode active materials of LIBs based on electrochemistry, were applied to 18650 cylindrical battery cells. They were expanded to a battery pack model to be mounted on an electric vehicle (EV) to compare and analyze the battery performance according to the application of different cathode active materials. The battery modeling was based on a database provided by the Gamma Technologies LIB simulation, GT-AutoLion. To analyze the thermal stability according to the temperature and the capacity loss of the battery cell resulting from the different C-rate discharges for each positive electrode active material, an electrochemical-based 1D analysis was performed.

Herein, the voltage and current output characteristics of a laser photovoltaic (PV) module applied to a wireless power transmission system using a laser beam are analyzed. First, an experiment is conducted to obtain the characteristic data of the voltage and current based on the laser output power of the laser PV module, which generates the maximum power from the laser beam at a wavelength of 1080 nm; subsequently, the small-signal voltage and current characteristics of the laser PV module are analyzed. From the analysis results, it is confirmed that the laser PV module has a characteristic in which the maximum power generation point varies according to the power level of the laser beam. In addition, similar to the solar cell module, it is confirmed that the laser PV module has a current source and a voltage source region, and it shows a small signal resistance characteristic having a negative value as the operating point goes to the current source region. In addition, in this paper, by reflecting these electrical characteristics, a method for designing the controller of a power converter capable of charging a battery while generating maximum power from a PV module is proposed. Since the laser PV module corresponds to the input source of the boost converter used as the power conversion unit, the small-signal transfer function of the boost converter, including the PV module, is derived for the controller design. Therefore, by designing a controller that can stably control the voltage of the PV module in the current source, the maximum power point, and voltage source regions defined according to the output characteristics of the laser PV module, the maximum power is generated from the PV module. Herein, a systematic controller design method for a boost converter for laser wireless power transmission is presented, and the proposed method is validated based on the simulation and experimental results of a 25-W-class boost converter based on a microcontroller unit control.

This article newly suggests two-step Hamming neural network (HNN)-based pattern recognition which combines the discrete wavelet transform (DWT)-based multi-resolution analysis (MRA) for providing an innovative and unique cell distinction. In contrast to the conventional methods, there are some remarkable features. First, the discharging/charging current signals (DCCSs) for reflecting load conditions with various dissimilar scenarios are used as representative patterns in the first-step HNN. Specifically, the usage of decomposed low- or high-frequency components (A5/D5) by the DWT-based MRA enables added characteristic parameters for providing the closest matches. Second, according to state-of-charge (SOC) range, especially in high SOC ranges, the allowable maximum charging currents in constant current/voltage (CC/CV) schemes are adjusted for avoiding over-charging. Third, the second-step HNN finally completes the recognition after closely matching several representative discharging/charging voltage signals applying the selected DCCS in the first step. Finally, simultaneous internal parameter extraction in the equivalent electrical circuit model during the second-step HNN provides useful information for verification of this article. Then, unnecessary experimental procedure and the time required for getting parameters of an arbitrary lithium-ion cell are abbreviated or reduced.

Electric vehicles have been issued to achieve sustainable mobility. Main factors to sustainable electric vehicle (EV) are that lithium-ion battery (LIB) has to maintain lower cost, lighter weight, SOC (state of charge), thermal stability, and driving ranges. In this study, nickel-cobalt-manganese (NCM), lithium iron phosphate (LFP), and lithium manganese oxide (LMO), which are used as representative positive electrode materials, were applied to battery cells. Then, the battery characteristics at the system level, according to the application of different positive electrode materials, were compared and analyzed. To this end, each of the 18650 cylindrical battery cells was modeled by applying different positive electrode active materials. The battery modeling was based on a database provided by GT(Gamma Technologies)-AutoLion. To analyze the thermal stability and capacity loss according to the temperature of the battery cell by applying different C-rate discharge and temperature conditions for each positive electrode active material, an electrochemical-based zero-dimensional (0D) analysis was performed. A test was also performed to determine the model feasibility by using a MACCOR 4300 battery charger/discharger. Moreover, a lumped battery pack modeling was performed to extend the modeled battery cell to an EV battery pack. By combining the pack and one-dimensional (1D) EV models, various driving cycles were described to investigate the battery performance at the vehicle level. It was found that the 0D electrochemistry-coupled 1D vehicle model could well predict the feasible tendencies considering various positive electrode materials of the LIB battery cell.

Batteries used in electric vehicles and microgrid applications use battery modules connected in series to satisfy the voltage required for each system, and battery modules are connected in parallel to increase capacity. In this parallel connected system, in order to disconnect and reconnect a specific battery module or to reconnect a new battery module, the battery module to be newly connected should have a small state of charge (SOC) difference from the existing battery modules. In particular, when a new battery is to be connected under a load current, there is a problem that excessive inrush current may occur in a specific battery module due to the load current distributed to each module and the current due to the SOC difference. Therefore, in this paper, we propose a method of estimating the inrush current through an equivalent electrical modelling analysis for the case where a battery module is newly added in a system in which the battery modules are connected in parallel. In addition, the power management algorithm for the battery pack system with inrush current estimation is presented. The proposed method is validated through simulations and experiments of a battery pack system in which 10 battery modules of 710V and 120Ah are connected in parallel.

Safety is critical issue for using lithium-ion battery. There are many causes and effects of faults in lithium-ion battery. Thermal runaway is the most hazardous safety problem. It leads to the dangerous result such as fire or explosion of the battery. If thermal runaway is occurred in application, its application like electrical vehicle or energy storage system would be a catastrophe. For preventing thermal runaway, diagnosis and prognosis of main causes are significant. One of the main causes of thermal runaway is internal short circuit. In this work, change of voltage and temperature from internal short circuit are analyzed. Usually, it is hard to detect internal short circuit in normal electrical equivalent circuit model (EECM). Thus, lots of papers apply a parallel resistor in EECM to catch internal short circuit. In this paper, this model is used to show effects from internal short circuit. Resistance of parallel resistor represents the probability of occurrence of internal short circuit. Current passing through the parallel resistor indicates the leakage current inside of the battery which is not detected. To verify the model in high energy lithium-ion battery, induced internal short circuit suggested in UL standard is conducted. And change of voltage, internal leakage current, parallel resistor’s value is analyzed.

The effect of hydrogen on catalytic soot oxidation was investigated to find new conditions for lowering the regeneration temperature in catalyzed diesel particulate filtration with hydrogen. Soot oxidation experiments using a flow reactor with a Pt/CeO2 catalyst were carried out to represent catalyzed diesel particulate filtration. Under conditions using more than 6% hydrogen with water, the soot oxidation by hydrogen.started at 155 degrees C for loose contact conditions and at 175 degrees C for tight contact conditions. The soot oxidation rate tended to increase with increasing concentrations of hydrogen and oxygen. In contrast, no difference was observed with various water concentrations. The HO2 generated during hydrogen oxidation oxidized soot at low temperature. The soot oxidation temperature of 155 degrees C was lower than the regeneration temperature in catalyzed diesel particulate filtration reported previously. (C) 2018 Energy Institute. Published by Elsevier Ltd. All rights reserved.

In this report, a method for estimating pulse power performance according to pulse duration is proposed. This approach can be used for power control logic in an environmentally friendly power generation system such as electric vehicles and an energy storage system (ESS). Although there have been studies on pulse power capability, we are unaware of any publications on the estimation of the magnitude of pulse power according to the power usage time, and the verification of the estimation result. Therefore, we propose a method to predict power performance according to the pulse duration of batteries and supercapacitors that are used in eco-friendly power generation systems. The proposed method is systematically presented using both a lithium-ion battery module with a nominal voltage of 44 V, 11 Ah, and a supercapacitor module with a maximum voltage of 36 V and a capacitance of 30 F.

The state of charge (SOC) estimation of battery pack influences the performance in electrical application. The Ah-counting method is used to estimate the SOC estimation the battery pack, but it has a disadvantage. If the initial value is uncertain, the estimation performance of the SOC is not guaranteed. Therefore, the electrical application has low performance because it cannot utilize a maximum capacity. This paper proposes the adaptive SOC estimator to improve the performance of the SOC estimation even though the initial value is incorrect. The performance of the proposed estimation method is verified by simulation and electrical characteristic experiments using Matlab/Simulink.

This research aims to evaluate Li-Ion cell failures under environmental (vibration and shock) and safety (over-discharge/-charge, and short) tests. For this objective, this research considered six Li-Ion different cells such as four NCA (Li[NiCoAl]O-2) cells for high-power and two NMC (Li[NiMnCo]O-2) cells for high-energy. After vibration and shock tests in X, Y, Z axis based on each procedure predetermined, discharge capacities and internal resistances are respectively compared before and after. It is also judged whether experimental NCA and NMC cells are suitable or not in space application under a predetermined condition of safety tests. Additional results of scanning electron microscope (SEM) and X-ray diffraction (XRD) are discussed.