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Lithium-ion (Li-ion) batteries are an important component of energy storage systems used in various applications such as electric vehicles and portable electronics. There are many chemistries of Li-ion battery, but LFP, NMC, LMO, and NCA are four commonly used types. In order for the battery applications to operate safely and effectively, battery modeling is very important. The equivalent circuit model (ECM) is a battery model often used in the battery management system (BMS) to monitor and control Li-ion batteries. In this study, experiments were performed to investigate the performance of three different ECMs (1RC, 2RC, and 1RC with hysteresis) on four Li-ion battery chemistries (LFP, NMC, LMO, and NCA). The results indicated that all three models are usable for the four types of Li-ion chemistries, with low errors. It was also found that the ECMs tend to perform better in dynamic current profiles compared to non-dynamic ones. Overall, the best-performed model for LFP and NCA was the 1RC with hysteresis ECM, while the most suited model for NMC and LMO was the 1RC ECM. The results from this study showed that different ECMs would be suited for different Li-ion battery chemistries, which should be an important factor to be considered in real-world battery and BMS applications.

The ultrasonic frequency radial vibration of an elastic thin spherical shell composed of isotropic materials is studied, the frequency equation of its vibration is deduced, and the equivalent circuit is obtained. The finite element software COMSOL is used to verify the obtained analytical theory, and the calculated results are basically consistent with the theoretical calculated values. The relevant conclusions provide references for the application of spherical shell structure in related fields.

Circuit analysis of frequency selective surfaces is reviewed with the aim to underline range of validity of different models and their advantages in terms of simplicity and physical insight. The circuit approach is based on an equivalent representation of the FSSs with series or shunt connections of inductances and capacitances. Dense non-resonant periodic surfaces (i.e.: grid or patch arrays) can be analyzed analytically by computing the values of inductors or capacitors via the homogenization theory. As the lattice period increases with respect to the operating wavelength or the element shape becomes resonant, a fully analytical circuital approach fails, in particular, in the presence of thin substrates. However, simple circuit approaches can still be employed by deriving lumped parameters values via a quick pre-processing and then generalizing them. The results are accurate up to the resonant frequency region of the element. By including an additional lumped element it is possible, taking into account the effect of the first high order Floquet harmonic. The multi-mode formulation is also able to catch the highly nonlinear response of FSS screens in the grating lobe region provided that the current profile of the element does not change significantly.

The power system is experiencing a higher penetration of renewable energy generations (REGs). The short circuit ratio (SCR) and the grid impedance ratio (GIR) are two indices to quantify the system strength of the power system with REGs. In this paper, the critical short circuit ratio (CSCR) is defined as the corresponding SCR when the system voltage is in the critical stable state. Through static voltage stability analysis, the mathematical expression of the CSCR considering the impact of GIR is derived. The maximum value of CSCR is adopted as the critical value to distinguish the weak power system. Based on the static equivalent circuit analysis, it is proved that the CSCR is still effective to evaluate critical system strength considering the interactive impact among REGs. Finally, we find that the GIR can be neglected and the SCR can be used individually to evaluate the system strength when SCR>2 or GIR>5. The correctness and rationality of the CSCR and its critical value are validated on ADPSS.

With rapid transportation electrification worldwide, lithium-ion batteries have gained much attention for energy storage in electric vehicles (EVs). State of power (SOP) is one of the key states of lithium-ion batteries for EVs to optimise power flow, thereby requiring accurate online estimation. Equivalent circuit model (ECM)-based methods are considered as the mainstream technique for online SOP estimation. They primarily vary in their basic principle, technical contribution, and validation approach, which have not been systematically reviewed. This paper provides an overview of the improvements on ECM-based online SOP estimation methods in the past decade. Firstly, online SOP estimation methods are briefed, in terms of different operation modes, and their main pros and cons are also analysed accordingly. Secondly, technical contributions are reviewed from three aspects: battery modelling, online parameters identification, and SOP estimation. Thirdly, SOP testing methods are discussed, according to their accuracy and efficiency. Finally, the challenges and outlooks are presented to inspire researchers in this field for further developments in the future.

In this study, we present a novel dual-polarized patch antenna that exhibits high isolation and two in-band transmission zeros (TZs). The design consists of a suspended metal patch, two feeding probes connected to an internal neutralization line (I-NL), and a T-shaped decoupling network (T-DN). The I-NL is responsible for generating the first TZ, and its decoupling principles are explained through an equivalent circuit model. Rigorous design formulas are also derived to aid in the construction of the feeding structure. The T-DN realizes the second TZ, resulting in further improvement of the decoupling bandwidth. Simulation and experimental results show that the proposed antenna has a wide operating bandwidth (2.5–2.7 GHz), high port isolation (>30 dB), and excellent efficiency (>85%).

Equivalent circuit model has been proposed to describe the solar cell characteristics and commonly used is single diode model. Sundry methods are currently utilized to determine the values of voltage, current, and power of a photovoltaic cell. A new method is suggested to numerically find these values using the popular methods, Newton Raphson method (NRM); Aitken’s extrapolation algorithm (AEM) and Three-step method (TSM) at various values of a load resistance R. Equation based on equivalent circuit of a solar cell so all determinations is imlemented in a Matlab in ambient temperature. The obtained results of this new method are given and contrasted with NRM.

In the present work, improvement of Newton’s method with high order convergence has been suggested. This improvement is based on Two-Point Bracketing method. The proposed method Inverse Quadratic Interpolation method requires two steps per iteration. By means of the numerical equation of the one diode model of PV equivalent circuit, included five values of R from 1 to 5 ohms (load resistance of the circuit). The results obtained explain that the new suggested technique is easy to use, more accurate and efficient than other numerical methods are presented here.

High-energy-density lithium batteries play a crucial role in the lightweight design of stratospheric airship systems. This paper conducts an in-depth experimental study of the equivalent circuit model of soft-pack batteries, with a focus on how parameter identification methods affect model accuracy. To this end, first-order RC, second-order RC, and third-order RC equivalent circuit models were constructed, and model parameters under different temperature and current conditions were obtained through constant-current intermittent discharge experiments. During the parameter identification process, special consideration was given to the impact of sampling time on voltage measurements and the interdependent constraints among models. Additionally, the effects of current, temperature, and SOC (state of charge) variations on ohmic resistance and polarization resistance–capacitor parameters were analyzed. The experimental results show that the root mean square error (RMSE) of battery terminal voltage calculated using parameter identification methods that account for these factors is significantly lower than when these factors are not considered. By comparing the voltage calculation accuracy and operational efficiency of the three models, the second-order RC model was determined to be the preferred choice due to its simple structure, high computational efficiency, and superior accuracy.

This paper presents three equivalent thermal circuit models with multiple input parameters, namely, the state of health (SOH), state of charge (SOC), current and temperature. Typical physiochemical models include parameters such as porosity and tortuosity, which are not easily experimentally available; this model allows for model parameters such as the internal impedance to be easily estimated using more practical inputs. The paper models the internal impedance resistance of a LiFePO4 battery at five different ambient temperatures (5, 15, 25, 35, 45 °C), at three different discharge rates (1C, 2C, 3C) and at three different SOHs (90%, 83%, 65%). The internal impedance surface fit experimental measurements with a Pearson coefficient of 0.945. Three thermal models were then created that implemented the internal resistance model. The first two thermal models were 0D models that did not include the influence of the thermal conductivity of the battery. The first model assumed simple heating through internal resistance and convection energy loss, while the second also included the Bernardi Reversible heat term. The final third model was a 2D model that included all previous heat source terms as well as tab heating. The 2D model was solved using a simple Euler method and finite center difference. The R2 values for the 0D thermal models were 0.9964 and 0.9962 for the simple internal resistance and reversible heating models, respectively. The R2 value for the 2D thermal model was 0.996.