The Influence of Winding Location in Flux-Switching Permanent-Magnet Machines

The main purpose of this paper is to investigate the influence of winding location on back electromotive force (EMF) and armature inductance in flux-switching permanent-magnet (FSPM) machines. To obtain an analytical solution, a double-stator-pitch model is built based on the equivalent magnetic circuit method. Then, the open-circuit characteristics in FSPM machines with different winding layouts are analyzed by both the analytical model and finite-element-analysis method. The analysis reveals that winding inductance is easier influenced by the winding location than the permanent-magnet flux linkage and corresponding back EMF. Finally, the analytical and finite-element predictions are verified by experimental results

An improved Kriging surrogate model method with high robustness for electrical machine optimization

This article presents a highly robust optimization method for electrical machines, taking the uncertain tolerances of machine manufacturing into account. Different from the traditional multi-objective optimization methods based on Kriging surrogate model, two genetic algorithm (GA) models with disparate sampling principles are used here to release heavy computational burden and to improve prediction accuracy. One is adding the final optimization result of GA as the samples into the initial surrogate model, while the other one is adding the samples from the optimization process for the initial surrogate model. A 12-slot 14-pole interior permanent magnet synchronous machine (IPMSM) is used for the case study, and two GA models are compared. Furthermore, the proposed robust optimization method is compared with a deterministic optimization method to demonstrate its superiority, and its effectiveness is verified by prototype tests.</p

An improved Kriging surrogate model method with high robustness for electrical machine optimization

This article presents a highly robust optimization method for electrical machines, taking the uncertain tolerances of machine manufacturing into account. Different from the traditional multi-objective optimization methods based on Kriging surrogate model, two genetic algorithm (GA) models with disparate sampling principles are used here to release heavy computational burden and to improve prediction accuracy. One is adding the final optimization result of GA as the samples into the initial surrogate model, while the other one is adding the samples from the optimization process for the initial surrogate model. A 12-slot 14-pole interior permanent magnet synchronous machine (IPMSM) is used for the case study, and two GA models are compared. Furthermore, the proposed robust optimization method is compared with a deterministic optimization method to demonstrate its superiority, and its effectiveness is verified by prototype tests.</p

Analytical Model of Modular Spoke-Type Permanent Magnet Machines for In-Wheel Traction Applications

This paper proposes an analytical model of modular spoke-type permanent magnet (MSTPM) machines based on air-gap field modulation (AFM) theory. Firstly, a fundamental AFM model of open-circuit MSTPM machines is introduced. The open-circuit air-gap field of MSTPM machines is determined by three fundamental elements including the primitive magnetizing magnetomotive force (MMF) produced by permanent magnet (PM), and two modulators which consist of stator and rotor permeance. The analytical MMF excited by PM (PM-MMF) can be calculated by using magnetic circuit method, while the stator and rotor permeance models are developed based on relative permeance (RP) method. Thereafter, a general model is proposed to calculate the open-circuit back electromotive force (EMF) of MSTPM machines. Further, the winding inductance model is established on the basis of equivalent magnetic circuit method and RP model. Finally, the machine performance is predicted by the analytical model, and verified by both finite element analysis (FEA) and experimental results

Predicting protective gene biomarker of acute coronary syndrome by the circRNA-associated competitive endogenous RNA regulatory network

Background: The mortality and disability rates of acute coronary syndrome (ACS) are quite high. Circular RNA (circRNA) is a competitive endogenous RNA (ceRNA) that plays an important role in the pathophysiology of ACS. Our goal is to screen circRNA-associated ceRNA networks for biomarker genes that are conducive to the diagnosis or exclusion of ACS, and better understand the pathology of the disease through the analysis of immune cells. Materials and methods: RNA expression profiles for circRNAs (GSE197137), miRNAs (GSE31568), and mRNAs (GSE95368) were obtained from the GEO database, and differentially expressed RNAs (DEcircRNAs, DEmiRNAs, and DEmRNAs) were identified. The circRNA-miRNA and miRNA-mRNA regulatory links were retrieved from the CircInteractome database and TargetScan databases, respectively. As a final step, a regulatory network has been designed for ceRNA. On the basis of the ceRNA network, hub mRNAs were verified by quantitative RT-PCR. Hub genes were validated using a third independent mRNA database GSE60993, and ROC curves were used to evaluate their diagnostic values. The correlation between hub genes and immune cells associated with ACS was then analyzed using single sample gene set enrichment analysis (ssGSEA). Results: A total of 17 DEcircRNAs, 229 DEmiRNAs, and 27 DEmRNAs were found, as well as 52 circRNA-miRNA pairings and 10 miRNA-mRNA pairings predicted. The ceRNA regulatory network (circRNA-miRNA-mRNA) was constructed, which included 2 circRNA (hsa_circ_0082319 and hsa_circ_0005654), 4 miRNA (hsa-miR-583, hsa-miR-661, hsa-miR-671-5p, hsa-miR-578), and 5 mRNA (XPNPEP1, UCHL1, DBNL, GPC6, and RAD51). The qRT-PCR analysis result showed that the XPNPEP1, UCHL1, GPC6 and RAD51 genes had a significantly decreased expression in ACS patients. Based on ROC curve analysis, we found that XPNPEP1 has important significance in preventing ACS occurrence and excluding ACS diagnosis. ACS immune infiltration analysis revealed significant correlations between the other 3 hub genes (UCHL1, GPC6, RAD51) and the immune cells (Eosinophils, T folliculars, Type 2 T helper cells, and Imumature dendritic cells). Conclusion: Our study constructed a circRNA-related ceRNA network in ACS. The XPNPEP1 gene could be a protective gene biomarker for ACS. The UCHL1, GPC6 and RAD51 genes were significantly correlated with immune cells in ACS

Thermal Model Approach to the YASA Machine for In-Wheel Traction Applications

The axial-flux permanent magnet (AFPM) machines with yokeless and segmented armature (YASA) topology are suitable for in-wheel traction systems due to the high power density and efficiency. To guarantee the reliable operation of the YASA machines, an accurate thermal analysis should be undertaken in detail during the electrical machine design phase. The technical contribution of this paper is to establish a detailed thermal analysis model of the YASA machine by the lumped parameter thermal network (LPTN) method. Compared with the computational fluid dynamics (CFD) method and the finite element (FE) method, the LPTN method can obtain an accurate temperature distribution with low time consumption. Firstly, the LPTN model of each component of the YASA machine is constructed with technical details. Secondly, the losses of the YASA machine are obtained by the electromagnetic FE analysis. Then, the temperature distribution of the machine can be calculated by the LPTN model and loss information. Finally, a prototype of the YASA machine is manufactured and its temperature distribution under different operating conditions is tested by TT-K-30 thermocouple temperature sensors. The experimental data matches the LPTN results well

Thermal Model Approach to Multisector Three-Phase Electrical Machines

© 1982-2012 IEEE. Multisector machines reveal a high fault-tolerant capability, since failure events can be isolated by de-energizing the faulty sector, while the healthy ones contribute in delivering the required power. This article is focused on the thermal analysis of multisector three-phase machines in healthy and faulty operations. First, a 3-D lumped parameter thermal network (LPTN) of a single sector is developed and finetuned against experimental data, through a genetic algorithm for identifying the uncertain parameters. According to the operating conditions, the varying housing surface temperature affects the heat exchanged to the ambient. Hence, an analytical formula is proposed to adjust the natural convection coefficient value depending on the operating condition. Then, the 3-D LPTN, modeling the whole machine, is built aiming at investigating the thermal behavior during faulty conditions. Finally, the complete 3-D LPTN is employed for predicting the machine thermal performance under several faulty conditions. Furthermore, the current overload experienced by the healthy sector (in order to keep the same torque level as during the pre-fault operation) is determined, in accordance with the magnet wire thermal class. The effectiveness of the 3-D LPTN in predicting the temperature is experimentally demonstrated

Retinoic acid modulation guides human-induced pluripotent stem cell differentiation towards left or right ventricle-like cardiomyocytes

Background: Cardiomyocytes (CMs) derived from human induced pluripotent stem cells (hiPSCs) by traditional methods are a mix of atrial and ventricular CMs and many other non-cardiomyocyte cells. Retinoic acid (RA) plays an important role in regulation of the spatiotemporal development of the embryonic heart. Methods: CMs were derived from hiPSC (hi-PCS-CM) using different concentrations of RA (Control without RA, LRA with 0.05μM and HRA with 0.1 μM) between day 3-6 of the differentiation process. Engineered heart tissues (EHTs) were generated by assembling hiPSC-CM at high cell density in a low collagen hydrogel. Results: In the HRA group, hiPSC-CMs exhibited highest expression of contractile proteins MYH6, MYH7 and cTnT. The expression of TBX5, NKX2.5 and CORIN, which are marker genes for left ventricular CMs, was also the highest in the HRA group. In terms of EHT, the HRA group displayed the highest contraction force, the lowest beating frequency, and the highest sensitivity to hypoxia and isoprenaline, which means it was functionally more similar to the left ventricle. RNAsequencing revealed that the heightened contractility of EHT within the HRA group can be attributed to the promotion of augmented extracellular matrix strength by RA. Conclusion: By interfering with the differentiation process of hiPSC with a specific concentration of RA at a specific time, we were able to successfully induce CMs and EHTs with a phenotype similar to that of the left ventricle or right ventricle.</p

Comparative study on two modular spoke-type PM machines for in-wheel traction applications

This paper focuses on the comparative analysis of modular spoke-type permanent magnet machines with two magnetization modes, which are referred to as M-I and M-II types. The analytical models of the proposed machines are built based on the simple magneto-motive-force-permeance method. With the help of finite element analysis and the analytical models, magnetic fields in machines with different magnetization modes are compared. Then, taking as a base an existing commercial in-wheel machine used in an electric motorcycle, two proposed machines with different magnetization modes are designed as in-wheel traction machines and compared with respect to electromagnetic torque, flux-weakening performance, over-load capability, etc. The machines are prototyped and experimentally tested to verify the prediction that the M-II machines exhibit a higher torque output while the M-I machines have a wider speed range

Running Performance of Soccer Players During Matches in the 2018 FIFA World Cup: Differences Among Confederations

With the purpose of quantifying the differences in the running performance of soccer players during matches from different continental confederations, data of 1508 match observations generated from 559 players in 59 matches at the 2018 FIFA World Cup held in Russia were analyzed. Generalized mixed linear modeling was carried out to estimate the effect of confederations on each of the selected thirteen match running performance related variables (total distance covered, top speed achieved, number of sprints, distance covered and time spent in walking, jogging, low-speed running, moderate-speed running, and high-speed running), controlling the effects of match result, competition phase, and team and opponent strength. Results showed that the differences in the match running performance of UEFA and CONMEBOL players were trivial (ES between 0.04 and 0.14); players from AFC, CAF, and CONCACAF covered less total distance (ES between 0.26 and 0.54), spent less playing time, and covered less distance in jogging and low-speed running (ES between 0.20 and 0.53), whereas they spent more time walking (ES between 0.27 and 0.41) as compared with players from UEFA and CONMEBOL; top speed achieved, number of sprints made, and time spent and distance covered in the moderate- and high-speed running intensity zones by players from all confederations were similar (ES between 0.01 and 0.15), with an exception that high-speed-running distance covered by CONCACAF players was less than that by CAF players (2.0 ± 1.5 m/min vs. 2.3 ± 1.7 m/min, ES = 0.23, ±90% CL: ±0.21)