Oxides based on vanadium redox couple, such as orthorhombic Li3VO4, has drawn great attentions due to its high theoretical capacity and moderate operating voltage. However, the rate property is largely hindered by the slow interfacial dynamics of Li3VO4. Here we synthesized the lotus stem-like Li3VO4 wrapped in N-doped carbon fibers (Li3VO4/C NF) stemmed from the chemical lithiation of V2O3/C NF. The knobbly Li3VO4 rooted in the interconnected carbon fibers provides abundant active sites and well-developed conductive networks. Thus, this anode delivers high specific capacity of 558.9 mAh g-1 at 0.2 A g-1 and excellent rate capacity of 419 mAh g-1 at 2 A g-1 sustaining 900 cycles with an average potential of 0.7 V vs. Li+/Li. Furthermore, the kinetic analysis reveals that the pseudocapacitance dominants the lithium storage process and the favorable interfacial ion and electronic transport is responsible for the enhanced rate performance. The full cell (Li3VO4/C NF||LiFePO4) also shows a competitive performance for commercialization. This work boosts the development of vanadium-based anode materials with desired electrochemical properties meeting devices requirements.
The consequent pole double stator hybrid excitation machines (CPDS-HEMs) with different stator topologies are investigated and compared to achieve the optimal topology, so as to flexibly adjust the airgap flux to further expand the speed. The consequent pole rotor with N-S-iron core-S-N sequence is adopted, in which the iron core replaces part of the permanent magnet (PM), so that the PM flux is in parallel with the excitation flux. The stator wound the AC field winding realizing brushless excitation can be placed in the rotor shaft side or inside stator to form different topologies. In addition, the interior permanent magnet synchronous machine (IPMSM) and consequent pole PMSM (CP-PMSM) are adopted for comparison, the electromagnetic characteristics, including magnetic field distribution, no-load back electromotive force (EMF), torque characteristics, flux regulation capability and efficiency are evaluated by finite element analysis (FEA), which shows that the CPDS-HEM with AC field winding placed in the rotor shaft side has advantages in improving the speed and torque. Finally, the prototype is manufactured to verify above analysis, which has good prospects in wide speed range driving applications.
Compared with the flux barriers synchronous reluctance motor (FB-SynRM), the non-flux barriers synchronous reluctance motor (NFB-SynRM) has the advantages of higher mechanical strength and smaller d-axis magnetic resistance which makes the parameters of NFB-SynRMs more linear compared with the FB-SynRMs. The rotor shape of the NFB-SynRMs is very critical for the motor performance. An improper rotor shape design may cause large torque ripple and decrease the motor torque density. To solve this problem, a convenient rotor shape design method of NFB-SynRMs is proposed and the rotor profile function is derived. The effectiveness of the proposed method is verified by electromagnetic finite element analysis.
Engine calibration poses a challenging multi-objective non-convex optimization problem due to its inherent complexity. In this study, we present a novel on-line engine calibration algorithm named Search Space Division-Momentum Gradient Descent (SSD-MGD), aimed at tackling this issue and reducing the calibration time. To commence, our investigation centers on a two-stroke kerosene engine, focusing on the calibration of spark timing and air-fuel ratio. We leverage experimental data to construct an engine response model utilizing support vector machines. This model serves as a virtual calibration test bench. The SSD-MGD methodology is then elaborated upon. It combines two key components: search space partitioning, which quickly identifies suitable initial points, and a momentum gradient descent algorithm, which solves for local optimal solutions from selected initial points. The two complement each other and we achieve a globally optimal solution. To evaluate the effectiveness of SSD-MGD, we performed a comparative analysis with traditional methods such as genetic algorithms in the context of virtual calibration tests. Our research results consistently show that SSD-MGD not only achieves the global optimal solution but also has significant efficiency.
Polluted flashover of insulators has always been a crucial hidden peril to the reliability of substation for supplying electricity. At present, the insulator of the substation is mainly cleaned manually in the case of power-cut, which greatly affects the reliability of power supply and operation safety. In this paper, an insulator dry-ice mechanical arm capable of electrified working is proposed. Under the regular operation of the power grid, the operator can remotely control the mechanical arm to clean the insulators of the substation with high-pressure gas mixed with dry-ice particles. This will not only ensure the regular operation of the power grid, but also greatly protects the safety of personnel. Considering the operation environment and high-voltage working conditions of the substation, the mechanism and control system of the dry-ice cleaning mechanical arm are designed, and the motion analysis, simulation, and strength analysis of the mechanical arm are carried out. Finally, the high-voltage-insulation test of the mechanical arm and the actual operation of the substation insulator cleaning working test are carried out, which proves that this mechanical arm can adapt to the operation environment of the substation, and the working is stable, safe, and reliable, which has an important application value to solve the problem in the cleaning of the substation insulator and other electrified equipment.
In order to achieve accurate rotor position estimation which is essential to sensorless drive of synchronous reluctance motors (SynRMs), this paper proposes a control strategy to eliminate the adverse effect of cross-saturation on rotor position extraction. Without encoder or finite element analysis which needs long-time calculation, the high-frequency (HF) rotating voltage injection method is adopted to identify the mutual inductances accounting for the estimation error. Meanwhile, a new error signal is derived to extract the rotor position angle, the influence of cross-saturation effect is avoided by the new method inherently. The effectiveness and feasibility of the proposed method is verified by simulation results.
Overall performance estimation of the inverter-fed induction machine by finite element analysis is a very time-consuming task, which is result of the long transient response time and various operating conditions of induction machines. To solve this problem, a method based on Multi-Layer Perceptron neural network is proposed. Firstly, minimum amount of operating conditions are calculated by finite element analysis to obtain the steady-state torque. Then the Multi-Layer Perceptron method is adopted to process the calculated result and build the prediction branching models classified by slip frequency. Finally, the prediction branching models are merged to construct the complete prediction model. It is tested that the steady-state torque obtained by this method has high accuracy. Compared the traditional method that requires sweeping all operating conditions, it has greatly reduced the time cost and operation cost of data acquisition.
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