ALBERT

Description: We present an adaptive-gain second order sliding mode (SOSM) control applied to a hybrid power system for electric vehicle applications. The main advantage of the adaptive SOSM is that it does not require the upper bound of the uncertainty. The proposed hybrid system consists of a polymer electrolyte membrane fuel cell (PEMFC) with a unidirectional DC/DC converter and a Li-ion battery stack with a bidirectional DC/DC converter, where the PEMFC is employed as the primary energy source and the battery is employed as the second energy source. One of the main limitations of the FC is its slow dynamics mainly due to the air-feed system and fuel-delivery system. Fuel starvation phenomenon will occur during fast load demand. Therefore, the second energy source is required to assist the main source to improve system perofrmance. The proposed energy management system contains two cascade control structures, which are used to regulate the fuel cell and battery currents to track the given reference currents and stabilize the DC bus voltage while satisfying the physical limitations. The proposed control strategy is evaluated for two real driving cycles, that is, Urban Dynamometer Driving Schedule (UDDS) and Highway Fuel Economy Driving Schedule (HWFET).

Description: Since the flow variations of Aksu River are strongly influenced by climate change and human activities which threat the local ecosystem and sustainable development, it is necessary to quantify the impact degree of the driving factors. Therefore, this study aims to quantify the impacts of climate change and human activities on the variability of runoff in the Aksu River Basin. The Mann-Kendall trend test and accumulative anomaly method were used to detect the break points of the flow difference value (FDV) between the upstream and downstream flume stations. The improved slope change ratio of cumulative quantity (SCRCQ) method and the Soil and Water Assessment Tool (SWAT) model were applied to decouple the contribution of each driving factor to the FDV variations. Furthermore, a Pearson Correlation Analysis was performed to show the relationships among the driving factors and the FDV. The time series prior to the year (1988) of break point was considered as the baseline period. Based on the annual precipitation and the potential evapotranspiration (PET), the relative impacts of precipitation, PET and human activities on FDV variations as determined by the SCRCQ method were 77.35%, −0.98% and 23.63%, respectively. In addition, the SWAT model indicated that climate factors and human activities were responsible for 92.28% and 7.72% of the variability, respectively. Thus, climate change and human activities showed a similar scale of impact on FDV changes.

Description: Three-port isolated (TPI) bidirectional DC/DC converters have three energy ports and offer advantages of large voltage gain, galvanic isolation ability and high power density. For this reason this kind of converters are suitable to connect different energy sources and loads in electric and hybrid vehicles. The purpose of this paper is to propose chaotic modulation and the related control scheme for TPI bidirectional DC/DC converters, in such a way that the switching harmonic peaks can be suppressed in spectrum and the conducted electromagnetic interference (EMI) is reduced. Two chaotic modulation strategies, namely the continuously chaotic modulation and the discretely chaotic modulation are presented. These two chaotic modulation strategies are applied for TPI bidirectional DC/DC converters with shifted-phase angle based control and phase-shifted PWM control. Both simulation and experiments are given to verify the validity of the proposed chaotic modulation-based control schemes.

Description: A field imaging spectrometer system (FISS; 380–870 nm and 344 bands) was designed for agriculture applications. In this study, FISS was used to gather spectral information from soybean leaves. The chlorophyll content was retrieved using a multiple linear regression (MLR), partial least squares (PLS) regression and support vector machine (SVM) regression. Our objective was to verify the performance of FISS in a quantitative spectral analysis through the estimation of chlorophyll content and to determine a proper quantitative spectral analysis method for processing FISS data. The results revealed that the derivative reflectance was a more sensitive indicator of chlorophyll content and could extract content information more efficiently than the spectral reflectance, which is more significant for FISS data compared to ASD (analytical spectral devices) data, reducing the corresponding RMSE (root mean squared error) by 3.3%–35.6%. Compared with the spectral features, the regression methods had smaller effects on the retrieval accuracy. A multivariate linear model could be the ideal model to retrieve chlorophyll information with a small number of significant wavelengths used. The smallest RMSE of the chlorophyll content retrieved using FISS data was 0.201 mg/g, a relative reduction of more than 30% compared with the RMSE based on a non-imaging ASD spectrometer, which represents a high estimation accuracy compared with the mean chlorophyll content of the sampled leaves (4.05 mg/g). Our study indicates that FISS could obtain both spectral and spatial detailed information of high quality. Its image-spectrum-in-one merit promotes the good performance of FISS in quantitative spectral analyses, and it can potentially be widely used in the agricultural sector.

Description: Continuous capacity increase of distributed grid-connected photovoltaic (PV) system produces more obvious disturbance on the grid. Monitoring network technology can provide protection for the safety and stability of power grid operation, but sensor nodes of the monitoring network will fall to failure due to environmental interference. According to the performance degradation problem caused by nodes failure in PV monitoring network, particle swarm optimization (PSO) of natural selection based on random weight is proposed in this paper to optimize monitoring performance. This method can restore the monitoring network by arousing redundant nodes. Simulation results show the effectiveness of the proposed algorithm.

Description: Small aperture microphone arrays provide many advantages for portable devices and hearing aid equipment. In this paper, a subspace based localization method is proposed for acoustic source using small aperture arrays. The effects of array aperture on localization are analyzed by using array response (array manifold). Besides array aperture, the frequency of acoustic source and the variance of signal power are simulated to demonstrate how to optimize localization performance, which is carried out by introducing frequency error with the proposed method. The proposed method for 5 mm array aperture is validated by simulations and experiments with MEMS microphone arrays. Different types of acoustic sources can be localized with the highest precision of 6 degrees even in the presence of wind noise and other noises. Furthermore, the proposed method reduces the computational complexity compared with other methods.

Description: Energies, Vol. 10, Pages 1297: Interconnecting Microgrids via the Energy Router with Smart Energy Management Energies doi: 10.3390/en10091297 Authors: Yingshu Liu Yue Fang Jun Li A novel and flexible interconnecting framework for microgrids and corresponding energy management strategies are presented, in response to the situation of increasing renewable-energy penetration and the need to alleviate dependency on energy storage equipment. The key idea is to establish complementary energy exchange between adjacent microgrids through a multiport electrical energy router, according to the consideration that adjacent microgrids may differ substantially in terms of their patterns of energy production and consumption, which can be utilized to compensate for each other’s instant energy deficit. Based on multiport bidirectional voltage source converters (VSCs) and a shared direct current (DC) power line, the energy router serves as an energy hub, and enables flexible energy flow among the adjacent microgrids and the main grid. The analytical model is established for the whole system, including the energy router, the interconnected microgrids and the main grid. Various operational modes of the interconnected microgrids, facilitated by the energy router, are analyzed, and the corresponding control strategies are developed. Simulations are carried out on the Matlab/Simulink platform, and the results have demonstrated the validity and reliability of the idea for microgrid interconnection as well as the corresponding control strategies for flexible energy flow.

Description: Sensors, Vol. 17, Pages 1700: High-Temporal-Resolution High-Spatial-Resolution Spaceborne SAR Based on Continuously Varying PRF Sensors doi: 10.3390/s17081700 Authors: Zhirong Men Pengbo Wang Chunsheng Li Jie Chen Wei Liu Yue Fang Synthetic Aperture Radar (SAR) is a well-established and powerful imaging technique for acquiring high-spatial-resolution images of the Earth’s surface. With the development of beam steering techniques, sliding spotlight and staring spotlight modes have been employed to support high-spatial-resolution applications. In addition to this strengthened high-spatial-resolution and wide-swath capability, high-temporal-resolution (short repeat-observation interval) represents a key capability for numerous applications. However, conventional SAR systems are limited in that the same patch can only be illuminated for several seconds within a single pass. This paper considers a novel high-squint-angle system intended to acquire high-spatial-resolution spaceborne SAR images with repeat-observation intervals varying from tens of seconds to several minutes within a single pass. However, an exponentially increased range cell migration would arise and lead to a conflict between the receive window and ‘blind ranges’. An efficient data acquisition technique for high-temporal-resolution, high-spatial-resolution and high-squint-angle spaceborne SAR, in which the pulse repetition frequency (PRF) is continuously varied according to the changing slant range, is presented in this paper. This technique allows echo data to remain in the receive window instead of conflicting with the transmitted pulse or nadir echo. Considering the precision of hardware, a compromise and practical strategy is also proposed. Furthermore, a detailed performance analysis of range ambiguities is provided with respect to parameters of TerraSAR-X. For strong point-like targets, the range ambiguity of this technique would be better than that of uniform PRF technique. For this innovative technique, a resampling strategy and modified imaging algorithm have been developed to handle the non-uniformly sampled echo data. Simulations are performed to validate the efficiency of the proposed technique and the associated imaging algorithm.

Description: Energies, Vol. 10, Pages 1169: Parametric Design of an Ultrahigh-Head Pump-Turbine Runner Based on Multiobjective Optimization Energies doi: 10.3390/en10081169 Authors: Linhai Liu Baoshan Zhu Li Bai Xiaobing Liu Yue Zhao Pumped hydro energy storage (PHES) is currently the only proven large-scale energy storage technology. Frequent changes between pump and turbine operations pose significant challenges in the design of a pump-turbine runner with high efficiency and stability, especially for ultrahigh-head reversible pump-turbine runners. In the present paper, a multiobjective optimization design system is used to develop an ultrahigh-head runner with good overall performance. An optimum configuration was selected from the optimization results. The effects of key design parameters—namely blade loading and blade lean—were then investigated in order to determine their effects on runner efficiency and cavitation characteristics. The paper highlights the guidelines for application of inverse design method to high-head reversible pump-turbine runners. Middle-loaded blade loading distribution on the hub, back-loaded distribution on the shroud, and large positive blade lean angle on the high pressure side are good for the improvement of runner power performance. The cavitation characteristic is mainly influenced by the blade loading distribution near the low pressure side, and large blade lean angles have a negative impact on runner cavitation characteristics.

Description: Sensors, Vol. 18, Pages 2587: Infrared Image Super Resolution by Combining Compressive Sensing and Deep Learning Sensors doi: 10.3390/s18082587 Authors: Xudong Zhang Chunlai Li Qingpeng Meng Shijie Liu Yue Zhang Jianyu Wang Super resolution methods alleviate the high cost and high difficulty in applying high resolution infrared image sensors. In this paper we present a novel single image super resolution method for infrared images by combining compressive sensing theory and deep learning. Low resolution images can be regarded as the compressed sampling results of the high resolution ones in compressive sensing. With sparsity in this theory, higher resolution images can be reconstructed. However, because of diverse level of sparsity for different images, the output contains noise and loss of high frequency information. Deep convolutional neural network provides a solution to relieve the noise and supplement some missing high frequency information. By concatenating two methods, we manage to produce better results in super resolution tasks for infrared images than SRCNN and ScSR. PSNR and SSIM values are used to quantify the performance. Applying our method to open datasets and actual infrared imaging experiments, we also find better visual results are preserved.