The pole phase modulation (PPM) technique is an effective method to extend speed range and torque capabilities for an integrated starter and hybrid electric vehicles applications. In this paper, the five pole-phase combination types of a multiphase induction motor (IM) with 36 stator slots and 36 stator conductors are presented and compared quantitatively by using the time-stepping finite element method (TS-FEM). The 36 stator conductors of the proposed multiphase IM are fed by a 36 leg inverter and the current phase angle and amplitude of each stator conductor can be controlled independently. This paper focuses on the winding connection, the PPM technique and the performance comparative analysis of each pole-phase combination types of the proposed multiphase IM. The flux distribution, air-gap flux density, output torque, core losses and efficiency of five pole-phase combination types have been investigated.
The recently proposed q-rung orthopair fuzzy set (q-ROFS) characterized by a membership degree and a non-membership degree is powerful tool for handling uncertainty and vagueness. This paper proposes the concept of q-rung orthopair linguistic set (q-ROLS) by combining the linguistic term sets with q-ROFSs. Thereafter, we investigate multi-attribute group decision making (MAGDM) with q-rung orthopair linguistic information. To aggregate q-rung orthopair linguistic numbers ( q-ROLNs), we extend the Heronian mean (HM) to q-ROLSs and propose a family of q-rung orthopair linguistic Heronian mean operators, such as the q-rung orthopair linguistic Heronian mean (q-ROLHM) operator, the q-rung orthopair linguistic weighted Heronian mean (q-ROLWHM) operator, the q-rung orthopair linguistic geometric Heronian mean (q-ROLGHM) operator and the q-rung orthopair linguistic weighted geometric Heronian mean (q-ROLWGHM) operator. Some desirable properties and special cases of the proposed operators are discussed. Further, we develop a novel approach to MAGDM within q-rung orthopair linguistic context based on the proposed operators. A numerical instance is provided to demonstrate the effectiveness and superiorities of the proposed method.
Electronic voltage transformers (EVT) and electronic current transformers (ECT) are important instruments in a digital substation. For simple, rapid and convenient development, the paper proposed an on-site calibration system for electronic instrument transformers based on LabVIEW. In the system, analog signal sampling precision and dynamic range are guaranteed by the Agilent 3458A digital multimeter, and data synchronization is also achieved based on a self-developed PCI synchronization card. To improve the measurement accuracy, an error correction algorithm based on the Hanning window interpolation FFT has good suppression of frequency fluctuation and inter-harmonics interference. The human-computer interface and analysis algorithm are designed based on LabVIEW, and the adaptive communication technology is designed based on IEC61850 9-1/2. The calibration system can take into account pairs of digital output and analog output of the electronic voltage/current transformer calibration. The results of system tests show that the calibration system can meet the requirements of 0.2 class calibration accuracy, and the actual type test and on-site calibration also show that the system is easy to operate with convenience and satisfactory stability.
This paper describes the design and test of a new high-current electronic current transformer based on a Rogowski coil. For better performances, electronic current transformers are used to replace conventional electro-magnetic inductive current transformers based on ferromagnetic cores and windings to measure high-current on the high voltage distribution grids. The design of a new high-current electronic current transformer is described in this paper. The principal schemes of the prototype and partial evaluation results are presented. Through relative tests it is known that the prototype has a wide dynamic range and frequency band, and it can allow high accuracy measurements.
This paper aims to propose a new multi-attribute decision making (MADM) method in complicated and fuzzy decision-making environment. To express both decision makers (DMs’) quantitative and qualitative evaluation information comprehensively and consider their high hesitancy in giving their assessment values in MADM process, we combine q-rung dual hesitant fuzzy sets (q-RDHFSs) with uncertain linguistic variables and develop a new tool, called the q-rung dual hesitant uncertain linguistic sets (q-RDHULSs). First, the definition, operations and comparison method of q-RDHULSs are proposed. Second, given the interrelationship among multiple q-rung dual hesitant uncertain linguistic variables (q-RDHULVs) we introduce some aggregation operators (AOs) to fuse q-rung dual hesitant uncertain linguistic (q-RDHUL) information based on the Muirhead mean, i.e. the q-RDHUL Muirhead mean operator, the q- RDHUL weighted Muirhead mean operator, the q-RDHUL dual Muirhead mean operator, and the q-RDHUL weighted dual Muirhead mean operator. To cope with MADM problems with q-RDHUL information, we propose a new method based on the proposed AOs. Afterwards, we apply the proposed method to an enterprise informatization level evaluation problem to verify its effectiveness. In addition, we also explain why our proposed method is more powerful and flexible than others.