ALBERT

Beschreibung: The authors wish to make the following corrections to the published paper [1].[...]

Beschreibung: The battery internal temperature estimation is important for the thermal safety in applications, because the internal temperature is hard to measure directly. In this work, an online internal temperature estimation method based on a simplified thermal model using a Kalman filter is proposed. As an improvement, the influences of entropy change and overpotential on heat generation are analyzed quantitatively. The model parameters are identified through a current pulse test. The charge/discharge experiments under different current rates are carried out on the same battery to verify the estimation results. The internal and surface temperatures are measured with thermocouples for result validation and model construction. The accuracy of the estimated result is validated with a maximum estimation error of around 1 K.

Beschreibung: This study describes an online estimation of the model parameters and state of charge (SOC) of lithium iron phosphate batteries in electric vehicles. A widely used SOC estimator is based on the dynamic battery model with predeterminate parameters. However, model parameter variances that follow with their varied operation temperatures can result in errors in estimating battery SOC. To address this problem, a battery online parameter estimator is presented based on an equivalent circuit model using an adaptive joint extended Kalman filter algorithm. Simulations based on actual data are established to verify accuracy and stability in the regression of model parameters. Experiments are also performed to prove that the proposed estimator exhibits good reliability and adaptability under different loading profiles with various temperatures. In addition, open-circuit voltage (OCV) is used to estimate SOC in the proposed algorithm. However, the OCV based on the proposed online identification includes a part of concentration polarization and hysteresis, which is defined as parametric identification-based OCV (OCVPI). Considering the temperature factor, a novel OCV–SOC relationship map is established by using OCVPI under various temperatures. Finally, a validating experiment is conducted based on the consecutive loading profiles. Results indicate that our method is effective and adaptable when a battery operates at different ambient temperatures.

Beschreibung: This paper presents a mathematical model of hydro power units, especially the governor system model for different operating conditions, based on the basic version of the software TOPSYS. The mathematical model consists of eight turbine equations, one generator equation, and one governor equation, which are solved for ten unknown variables. The generator and governor equations, which are different under various operating conditions, are presented and discussed in detail. All the essential non-linear factors in the governor system (dead-zone, saturation, rate limiting, and backlash) are also considered. Case studies are conducted based on one Swedish hydro power plant (HPP) and three Chinese plants. The simulation and on-site measurements are compared for start-up, no-load operation, normal operation, and load rejection in different control modes (frequency, opening, and power feedback). The main error in each simulation is also discussed in detail. As a result, the model application is proved trustworthy for simulating different physical quantities of the unit (e.g., guide vane opening, active power, rotation speed, and pressures at volute and draft tube). The model has already been applied effectively in consultant analyses and scientific studies.

Beschreibung: As kerogen is the main organic component in shale, the adsorption capacity, diffusion and permeability of the gas in kerogen plays an important role in shale gas production. Based on the molecular model of type II kerogen, an organic nanoporous structure was established. The Grand Canonical Monte Carlo (GCMC) and Molecular Dynamics (MD) methods were used to study the adsorption and diffusion capacity of mixed gas systems with different mole ratios of CO2 and CH4 in the foregoing nanoporous structure, and gas adsorption, isosteric heats of adsorption and self-diffusion coefficient were obtained. The selective permeation of gas components in the organic pores was further studied. The results show that CO2 and CH4 present physical adsorption in the organic nanopores. The adsorption capacity of CO2 is larger than that of CH4 in organic pores, but the self-diffusion coefficient of CH4 in mixed gas is larger than that of CO2. Moreover, the self-diffusion coefficient in the horizontal direction is larger than that in the vertical direction. The mixed gas pressure and mole ratio have limited effects on the isosteric heat and the self-diffusion of CH4 and CO2 adsorption. Regarding the analysis of mixed gas selective permeation, it is concluded that the adsorption selectivity of CO2 is larger than that of CH4 in the organic nanopores. The larger the CO2/CH4 mole ratio, the greater the adsorption and permeation selectivity of mixed gas in shale. The permeation process is mainly controlled by adsorption rather than diffusion. These results are expected to reveal the adsorption and diffusion mechanism of gas in shale organics, which has a great significance for further research.

Beschreibung: This paper presents a novel grouping method for lithium iron phosphate batteries. In this method, a simplified electrochemical impedance spectroscopy (EIS) model is utilized to describe the battery characteristics. Dynamic stress test (DST) and fractional joint Kalman filter (FJKF) are used to extract battery model parameters. In order to realize equal-number grouping of batteries, a new modified K-means clustering algorithm is proposed. Two rules are designed to equalize the numbers of elements in each group and exchange samples among groups. In this paper, the principles of battery model selection, physical meaning and identification method of model parameters, data preprocessing and equal-number clustering method for battery grouping are comprehensively described. Additionally, experiments for battery grouping and method validation are designed. This method is meaningful to application involving the grouping of fresh batteries for electric vehicles (EVs) and screening of aged batteries for recycling.

Beschreibung: Energies, Vol. 11, Pages 665: A New Analytical Wake Model for Yawed Wind Turbines Energies doi: 10.3390/en11030665 Authors: Guo-Wei Qian Takeshi Ishihara A new analytical wake model for wind turbines, considering ambient turbulence intensity, thrust coefficient and yaw angle effects, is proposed from numerical and analytical studies. First, eight simulations by the Reynolds Stress Model are conducted for different thrust coefficients, yaw angles and ambient turbulence intensities. The wake deflection, mean velocity and turbulence intensity in the wakes are systematically investigated. A new wake deflection model is then proposed to analytically predict the wake center trajectory in the yawed condition. Finally, the effects of yaw angle are incorporated in the Gaussian-based wake model. The wake deflection, velocity deficit and added turbulence intensity in the wake predicted by the proposed model show good agreement with the numerical results. The model parameters are determined as the function of ambient turbulence intensity and thrust coefficient, which enables the model to have good applicability under various conditions.