Full speed range position‑sensorless compound control scheme for PMSMs

Pu Liu,Di Liu,Yongpeng Shen,Ankang Liu,Xiaoliang Yang,Jun Zhao 전력전자학회 2022 JOURNAL OF POWER ELECTRONICS Vol.22 No.8

At low speeds, a high frequency signal injection method for the position-sensorless control of permanent magnet synchronous motors (PMSMs) produces additional power loss and position estimation delay. Meanwhile, at high speeds, the sliding mode observer (SMO) method has a chattering problem. With a focus on these problems, a full speed range position-sensorless compound control approach is proposed in this paper. First, the phase relationship between the different coordinate systems of the I/F control, and the mechanism of the chattering phenomenon of a sliding mode observer are analyzed. Then the full speed range position-sensorless control approach based on a combination of I/F control and an extended sliding mode observer is constructed. Through feeding back the estimated back electromotive force to the calculation of the stator current observer and using the rotated influence immune phase-locked loop, the innovative extended-SMO effectively improves the chattering phenomenon. Furthermore, the smooth transition between the two control schemes is achieved by a current slope decrement switching controller. Finally, the effectiveness of the proposed full speed range position-sensorless compound control approach for PMSMs is validated on a surface PMSM experimental bench.

Comparison of Target- and IgG-Enrichment Strategies to Measure Adalimumab Concentrations in Human Plasma Using an Immunocapture-Liquid Chromatography-High-Resolution Mass Spectrometry Platform

Ding Xiaoliang,Zhu Shengxiong,Liu Linsheng,Liu Xiaoxue,Zhu Kouzhu,Miao Liyan 대한진단검사의학회 2024 Annals of Laboratory Medicine Vol.44 No.5

Study on the mixing performance of mixing vane grids and mixing coefficient by CFD and subchannel analysis code in a 5×5 rod bundle

Han Bin,Zhu Xiaoliang,Yang Bao-Wen,Liu Aiguo,Xi Yanyan,Liu Lei,Liu Shenghui,Huang Junlin 한국원자력학회 2023 Nuclear Engineering and Technology Vol.55 No.10

Mixing Vane Grid (MVG) is one of the most important structures in fuel assembly due to its high performance in mixing the coolant and ultimately increasing Critical Heat Flux (CHF), which avoids the temperature rising suddenly of fuel rods. To evaluate the mixing performance of the MVG, a Total Diffusion Coefficient (TDC) mixing coefficient is defined in the subchannel analysis code. Conventionally, the TDC of the spacer grid is obtained from the combination of experiments and subchannel analysis. However, the processing of obtaining and determine a reasonable TDC is much challenging, it is affected by boundary conditions and MVG geometries. In is difficult to perform all the large and costing rod bundle tests. In this paper, the CFD method was applied in TDC analysis. A typical 5 5 MVG was simulated and validated to estimate the mixing performance of the MVG. The subchannel code was used to calculate the TDC. Firstly, the CFD method was validated from the aspect of pressure drop and lateral temperature distribution in the subchannels. Then the effect of boundary conditions including the inlet temperature, inlet velocities, heat flux ratio between hot and cold rods and the arrangement of hot and cold rods on MVG mixing and TDC were studied. The geometric effects on mixing are also carried out in this paper. The effect of vane pattern on mixing was investigated to determine which one is the best to represent the grid's mixing performance.

A Hybrid PWM Scheme for Stator Loss Reduction of Two Parallel Interleaved Inverter-Fed PMSM Drive with a Minimized Switching Loss

Liu Shengfu,Jin Xiaoliang,Shi Wen,Yang Huan,Zhao Rongxiang 대한전기학회 2022 Journal of Electrical Engineering & Technology Vol.17 No.1

The modulation’s eff ects on the stator losses have been explored by previous studies. It confi rms that the voltage vector error introduced by the PWM schemes dominants the PWM-related harmonic eddy-current loss and the PWM-related harmonic copper loss. However, the existing PWM schemes of two parallel inverter focus on the ZSCC peak reductions. They do not explore the reductions of the voltage vector error by the optimal vector sequences to suppress the stator loss. This paper aims to reduce the stator loss of the permanent magnet synchronous motor (PMSM) drive systems fed by the two parallel interleaved inverter with an optimal PWM scheme. First, this paper investigates the eff ects of the instantaneous voltage vector error, resulting from a PWM inverter, on the eddy-current loss and stator copper loss and reveals that a reduced voltage error reduces the eddy-current loss and stator copper loss. Then, this paper divides each 60° sector into six subsectors to minimize the voltage vector error, and with the proposed sector division, it further elects the optimal vector sequences for the subsectors, applying the minimum switching times per carrier period. Besides, the proposed optimal vector sequences are implemented through a simplifi ed carrier-based method. The presented analysis confi rms that the proposed PWM scheme can reduce the eddy-current loss, stator copper loss, and switching loss of the existing methods. Finally, the experimental results verify the theoretical analysis and optimal performance of the proposed modulation strategy.

Parameter identification of the Bouc-Wen model for the magnetorheological damper using fireworks algorithm

Xiaoliang Chen,Liyou Xu,Shuai Zhang,Sixia Zhao,Kui Liu 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.5

To solve the problems of low identification accuracy and complex identification methods in the Bouc-Wen model of the magnetorheological (MR) damper, a new parameter identification method using the fireworks algorithm (FWA) is proposed. According to the experimental results of the dynamic characteristics of the MR damper and the simulation data of the Bouc-Wen model, the FWA is used to identify the seven parameters of the Bouc-Wen model. On the basis of the relationship between the identification results and the command current, the current-controlled Bouc-Wen model (I-Bouc-Wen model) is constructed and compared with the experimental results under different sinusoidal excitation frequencies. Compared with the genetic algorithm (GA), differential evolution (DE) algorithm, and particle swarm optimization (PSO) algorithm, the FWA has the advantage of faster convergence, shorter calculation time, and higher stability in solving the parameter identification problem of the highly nonlinear hysteretic model. Under three harmonic excitations, the average calculation accuracies of the IBouc-Wen model reache 88.64 %, 90.45 %, and 81.28 %, respectively, and the dynamic characteristic curve of the model is in basic agreement with the experimental results. It can be used for the subsequent controller design and simulation research and lay a foundation for applying the parameterized model of the MR damper in vibration reduction control.

Pavement performance analysis of carbon nanotube/SBS composite modified asphalt

Liu Bo,Li Xiaoliang,Li Sheng 한국탄소학회 2024 Carbon Letters Vol.34 No.1

In order to prevent early distress in asphalt pavement and save on subsequent operational and maintenance costs, modifying asphalt is an effective approach. Styrene–butadiene–styrene (SBS) block copolymers, due to their excellent physicochemical properties, have become a mature and widely used asphalt modifier. Carbon nanotubes (CNTs) possess advantages such as a large specific surface area and high modulus, which, when incorporated into asphalt, can enhance its deformation resistance. To analyze the effect of incorporating CNTs on SBS-modified asphalt (SBS-A), this study analyzed the influence of different CNT concentrations on the high and low-temperature performance and aging properties of SBS-A through penetration, softening point, ductility, dynamic shear rheometry, and short-term aging tests. The optimal CNT concentration was determined to be 1.0%. Furthermore, the changes in the modified asphalt during the aging process were analyzed using infrared spectroscopy.

An Isotache Model for Frozen Soil Taking Account the Effect of Creep on Plastic Yield Pressure

Xiaoliang Yao,Jilin Qi,Xiangping Qiao,Mengxin Liu 대한토목학회 2018 KSCE JOURNAL OF CIVIL ENGINEERING Vol.22 No.2

Plastic yield pressure is a key factor influencing mechanical behavior of frozen soil. In this paper, an isotache model taking account the effect of creep on plastic yield pressure was modified to describe the mechanical behavior of frozen soil. A series K0 compression tests after different creep time and at different temperature were carried out on a fine grained soil obtained from Qinghai-Tibet plateau. Based on analysis of the tested results, it was proved that the strain development of the tested frozen soil obeys the postulation of parallel lines in isotache model. Meanwhile, the development of plastic yield pressure with creep strain is inversely related to temperature, which can be reasonably described by exponential function deduced from the isotache model. The sharp strain increase of frozen soil can be captured by the isotache model when the surcharge loading exceeds the plastic yield pressure. After modifying the isotache model as temperature dependent, mechanical behavior of frozen soil at different temperature can be described reasonably, and the development of plastic yield pressure with creep strain and temperature can be calculated conveniently.

Use of deep learning in nano image processing through the CNN model

Xing, Lumin,Liu, Wenjian,Liu, Xiaoliang,Li, Xin,Wang, Han Techno-Press 2022 Advances in nano research Vol.12 No.2

Deep learning is another field of artificial intelligence (AI) utilized for computer aided diagnosis (CAD) and image processing in scientific research. Considering numerous mechanical repetitive tasks, reading image slices need time and improper with geographical limits, so the counting of image information is hard due to its strong subjectivity that raise the error ratio in misdiagnosis. Regarding the highest mortality rate of Lung cancer, there is a need for biopsy for determining its class for additional treatment. Deep learning has recently given strong tools in diagnose of lung cancer and making therapeutic regimen. However, identifying the pathological lung cancer's class by CT images in beginning phase because of the absence of powerful AI models and public training data set is difficult. Convolutional Neural Network (CNN) was proposed with its essential function in recognizing the pathological CT images. 472 patients subjected to staging FDG-PET/CT were selected in 2 months prior to surgery or biopsy. CNN was developed and showed the accuracy of 87%, 69%, and 69% in training, validation, and test sets, respectively, for T1-T2 and T3-T4 lung cancer classification. Subsequently, CNN (or deep learning) could improve the CT images' data set, indicating that the application of classifiers is adequate to accomplish better exactness in distinguishing pathological CT images that performs better than few deep learning models, such as ResNet-34, Alex Net, and Dense Net with or without Soft max weights.

Effects of ball milling on structural changes and hydrolysis of lignocellulosic biomass in liquid hot-water compressed carbon dioxide

Houfang Lu,Xiaoliang Yuan,Shijie Liu,Guangrong Feng,Yingying Liu,Yongdan Li,Bin Liang 한국화학공학회 2016 Korean Journal of Chemical Engineering Vol.33 No.7

Mechanical activation is an effective method for destroying the crystalline structure. Biomass, especially its hemicellulose, can be degraded in the green solvent of liquid hot-water compressed carbon dioxide. To improve the degradation of crystalline cellulose in liquid hot-water compressed carbon dioxide, pretreatment of camphorwood sawdust by mechanical activation with a stirring ball mill was studied. Ball milling parameters and their effects on structure were determined by SEM, XRD and FT-IR. The influence of milling parameters on cellulose conversion can be ranked as follows: ball milling speed>activation time>the mass ratio of ball to biomass. The optimum milling condition was obtained at ball milling speed of 450 rpm and mass ratio of 30 : 1 of ball to biomass for 2 h. In this condition, cellulose crystallinity of sawdust decreased from 60.93% to 21.40%. The cellulose conversion was 37.8%, which was nearly four times of raw material (10.2%). The glucose yield in the hydrolysate was 1.49 g·L−1, which was nearly three times of that of raw material. It showed mechanical activation can destroy the crystalline structure of cellulose to promote degradation and the damage of lignocellulosic internal structure caused by ball milling is irreversible.

MiR-200c-3p inhibits LPS-induced M1 polarization of BV2 cells by targeting RIP2

Zhao Lei,Liu Xiaosong,Yang Jiankai,Wang Xiaoliang,Liu Xiaomeng,Wu Jianliang,Li Chen,Xu Donggang,Hu Yuhua 한국유전학회 2022 Genes & Genomics Vol.44 No.4

Background: Microglia are important immune cells, which can be induced by lipopolysaccharide (LPS) into M1 phenotype that express pro-inflammatory cytokines. Some studies have shown that microRNAs play critical roles in microglial activation. Objective: This study was designed to investigate the role of miR-200c-3p in regulating inflammatory responses of LPS-treated BV2 cells. Methods: The expression of miR-200c-3p in BV2 cells was detected by real-time PCR. Receptor-interacting protein 2 (RIP2) was predicted as a target gene of miR-200c-3p. Their relationship was verified by dual-luciferase reporter assay. The function of miR-200c-3p and RIP2 in microglial polarization and NF-κB signaling was further evaluated. Results: LPS treatment reduced miR-200c-3p expression in a dose-dependent and time-dependent manner in BV2 cells. LPS treatment increased the expression of M1 phenotype markers inducible nitric oxide synthase (iNOS) and major histocompatibility complex class (MHC)-II, promoted the release of pro-inflammatory cytokines interleukin (IL)-1β, IL-6 and tumor necrosis factor (TNF)-α, and enhanced the nuclear translocation and phosphorylation of nuclear factor-kappaB (NF-κB) p65. Reversely, miR-200c-3p mimics down-regulated the levels of these inflammatory factors. Furthermore, RIP2 was identified to be a direct target of miR-200c-3p. RIP2 knockdown had a similar effect to miR-200c-3p mimics. Overexpression of RIP2 eliminated the inhibitory effect of miR-200c-3p on LPS-induced M1 polarization and NF-κB activation in BV2 cells. Conclusions: MiR-200c-3p mimics suppressed LPS-induced microglial M1 polarization and NF-κB activation by targeting RIP2. MiR-200c-3p/RIP2 might be a potential therapeutic target for the treatment of neuroinflammation-associated diseases.