Analysis of coupling between two sub-machines in co-axis dual-mechanical-port flux-switching PM machine for fuel-based extended range electric vehicles

The permanent magnet (PM) field coupling between inner and outer machines of co-axis dual-mechanical-port flux-switching PM (CADMP-FSPM) machines is investigated. Firstly, the relationships between the inner and outer stator teeth are analytically evaluated, with three key stator teeth types defined, i.e. series, parallel, and independent teeth. Secondly, the negative effects of PM field coupling, including high even-order electromotive force (EMF) harmonics, three-phase EMFs asymmetry and DC bias component in flux-linkages, are investigated and verified by two CADMP-FSPM machines, namely, 5/6–12/22, and 5/6–18/42 structures. It is found that for avoiding the negative effects of PM field coupling, all inner and outer stator teeth types should be the same, thus, a 10/12–12/22 structure CADMP-FSPM machine is introduced for analysis. Thirdly, the performance of the 10/12–12/22, 5/6–12/22, and 5/6–18/42 structures, featured by PM field distributions, d-axis flux-linkage ripples, cogging torques, electromagnetic torques, losses and efficiencies, are comparatively analysed by finite element (FE) analysis. The results indicate that the 10/12–12/22 structure exhibits the lowest PM field coupling level and the best performance. Moreover, the 10/12–12/22 structure can avoid all the negative effects of PM field couplings. A prototyped 10/12–12/22 CADMP-FSPM machine is built and tested to verify the FE predicted results.</p

Resilience assessment for power systems under sequential attacks using double DQN with improved prioritized experience replay

The information and communication technology enhances the performance and efficiency of cyber-physical power systems (CPPSs). However, it makes the topology of CPPSs more exposed to malicious cyber attacks in the meantime. This article proposes a double deep-Q-network (DDQN)-based resilience assessment method for power systems under sequential attacks. The DDQN agent is devoted to identifying the least sequential attacks to the ultimate collapse of the power system under different operating conditions. A cascading failure simulator considering the characteristics of generators is developed to avoid a relatively optimistic assessment result. In addition, a novel resilience index is proposed to reflect the capability of the power system to deliver power under sequential attacks. Then, an improved prioritized experience replay technique is developed to accelerate the convergence rate of the training process for DDQN agent. Simulation results on the IEEE 39-bus, 118-bus, and 300-bus power systems demonstrate the effectiveness of the proposed DDQN-based resilience assessment method

Analysis and optimization of key dimensions of co-axial dual-mechanical-port flux-switching permanent magnet machines for fuel-based extended range electric vehicles

In this paper, key dimensions of a co-axial dual-mechanical-port flux-switching permanent magnet (CADMP-FSPM) machine for fuel-based extended range electric vehicles (ER-EVs), including split ratio, stator/rotor pole arcs, rotor yoke thickness, etc., are analyzed and optimized. Firstly, the topologies and operation principles of an exampled 3-phase CADMP-FSPM are introduced briefly, in which an inner-rotor FSPM machine with 12-stator-slots/10-rotor-poles for high-speed generation and an outer-rotor FSPM machine with 12-stator-slots/22-rotor-poles for low-speed motoring are assembled co-axially. Then, the relationship between the key dimensions and electromagnetic performance, particularly for electromagnetic torque (power), of the CADMP-FSPM machine is studied by 2D-finite element analysis (FEA). Further, the reasonable matches of split ratio, rotor/stator pole arcs and rotor yoke are determined and the original CADMP-FSPM machine is optimized correspondingly. Finally, the static characteristics, including no-load PM flux-linkage, electro-motive-force (EMF), winding inductances, cogging torques and electromagnetic torques, of the original and optimized machines are compared by 2D-FEA. The results verify that the optimized CADMP-FSPM machine can exhibit improved torque characteristics than the original one, i.e., the torque ripples of the inner and outer machines can be reduced by 22.7% and 4.7%, respectively, and the average torque of the inner and outer machines can be increased by 0.43Nm and 2Nm, respectively

Identification of hepatocellular carcinoma-related subtypes and development of a prognostic model: a study based on ferritinophagy-related genes

Abstract Background Hepatocellular carcinoma still has a high incidence and mortality rate worldwide, and further research is needed to investigate its occurrence and development mechanisms in depth in order to identify new therapeutic targets. Ferritinophagy is a type of autophagy and a key factor in ferroptosis that could influence tumor onset and progression. Although, the potential role of ferritinophagy-related genes (FRGs) in liver hepatocellular carcinoma (LIHC) is unknown. Methods Single-cell RNA sequencing (scRNA-seq) data of LIHC were obtained from the Gene Expression Omnibus (GEO) dataset. In addition, transcriptome and clinical follow-up outcome data of individuals with LIHC were extracted from the The Cancer Genome Atlas (TCGA) dataset. FRGs were collected through the GeneCards database. Differential cell subpopulations were distinguished, and differentially expressed FRGs (DEFRGs) were obtained. Differential expression of FRGs and prognosis were observed according to the TCGA database. An FRG-related risk model was constructed to predict patient prognosis by absolute shrinkage and selection operator (LASSO) and COX regression analyses, and its prognosis predictive power was validated. Ultimately, the association between risk score and tumor microenvironment (TME), immune cell infiltration, immune checkpoints, drug sensitivity, and tumor mutation burden (TMB) was analyzed. We also used quantitative reverse transcription polymerase chain reaction (qRT-PCR) to validate the expression of key genes in normal liver cells and liver cancer cells. Results We ultimately identified 8 cell types, and 7 differentially expressed FRGs genes (ZFP36, NCOA4, FTH1, FTL, TNF, PCBP1, CYB561A3) were found among immune cells, and we found that Monocytes and Macrophages were closely related to FRGs genes. Subsequently, COX regression analysis showed that patients with high expression of FTH1, FTL, and PCBP1 had significantly worse prognosis than those with low expression, and our survival prediction model, constructed based on age, stage, and risk score, showed better prognostic prediction ability. Our risk model based on 3 FRGs genes ultimately revealed significant differences between high-risk and low-risk groups in terms of immune infiltration and immune checkpoint correlation, drug sensitivity, and somatic mutation risk. Finally, we validated the key prognostic genes FTH1, FTL, using qRT-PCR, and found that the expression of FTH1 and FTL was significantly higher in various liver cancer cells than in normal liver cells. At the same time, immunohistochemistry showed that the expression of FTH1, FTL in tumor tissues was significantly higher than that in para-tumor tissues. Conclusion This study identifies a considerable impact of FRGs on immunity and prognosis in individuals with LIHC. The collective findings of this research provide new ideas for personalized treatment of LIHC and a more targeted therapy approach for individuals with LIHC to improve their prognosis