Performance comparison of conventional synchronous reluctance machines and PM-assisted types with combined star-delta winding

This paper compares four prototype Synchronous Reluctance Motors (SynRMs) having an identical geometry of iron lamination stacks in the stator and rotor. Two different stator winding layouts are employed: a conventional three-phase star connection and a combined star-delta winding. In addition, two rotors are considered: a conventional rotor without magnets and a rotor with ferrite magnets. The performance of the four SynRMs is evaluated using a two-dimensional (2D) Finite Element Model (FEM). For the same copper volume and current, the combined star-delta-connected stator with Permanent Magnets (PMs) in the rotor corresponds to an approximately 22% increase in the output torque at rated current and speed compared to the conventional machine. This improvement is mainly thanks to adding ferrite PMs in the rotor as well as to the improved winding factor of the combined star-delta winding. The torque gain increases up to 150% for low current. Moreover, the rated efficiency is 93.60% compared to 92.10% for the conventional machine. On the other hand, the impact on the power factor and losses of SynRM when using the star-delta windings instead of the star windings is merely negligible. The theoretical results are experimentally validated using four identical prototype machines with identical lamination stacks but different rotors and winding layouts

Performance evaluation of synchronous reluctance motors with and without permanent magnets

Nowadays, a growing interest in the efficiency and the cost of electrical machines has been noticed. Therefore, Synchronous Reluctance Motors (SynRMs) have become more attractive, thanks to their higher efficiency and nevertheless acceptable cost compared to induction machines. The rotor design of SynRMs with or without permanent magnets (PMs) has a huge effect on the motor efficiency, torque density and power factor. This paper introduces an evaluation for the performance of SynRMs with and without PMs in terms of efficiency, torque and power factor maps. Three different rotor designs for the same machine have been compared. For one machine, the experimental measurements have been obtained and the validation of the simulation results have been confirme

Energy management control strategy for renewable energy system based on spotted hyena optimizer

Hydrocarbons, carbon monoxide and other pollutants from the transportation sector harm human health in many ways. Fuel cell (FC) has been evolving rapidly over the past two decades due to its efficient mechanism to transform the chemical energy in hydrogen-rich compounds into electrical energy. The main drawback of the standalone FC is its slow dynamic response and its inability to supply rapid variations in the load demand. Therefore, adding energy storage systems is necessary. However, to manage and distribute the power-sharing among the hybrid proton exchange membrane (PEM) fuel cell (FC), battery storage (BS), and supercapacitor (SC), an energy management strategy (EMS) is essential. In this research work, an optimal EMS based on a spotted hyena optimizer (SHO) for hybrid PEM fuel cell/BS/SC is proposed. The main goal of an EMS is to improve the performance of hybrid FC/BS/SC and to reduce the amount of hydrogen consumption. To prove the superiority of the SHO method, the obtained results are compared with the chimp optimizer (CO), the artificial ecosystem-based optimizer (AEO), the seagull optimization algorithm (SOA), the sooty tern optimization algorithm (STOA), and the coyote optimization algorithm (COA). Two main metrics are used as a benchmark for the comparison: the minimum consumed hydrogen and the efficiency of the system. The main findings confirm that the minimum amount of hydrogen consumption and maximum efficiency are achieved by the proposed SHO based EMS

Hybrid photovoltaic-thermoelectric generator powered synchronous reluctance motor for pumping applications

The interest in photovoltaic (PV) pumping systems has increased, particularly in rural areas where there is no grid supply available. However, both the performance and the cost of the whole system are still an obstacle for a wide spread of this technology. In this article, a hybrid photovoltaic (PV)-thermoelectric generator (TEG) is investigated for pumping applications. The electric drivetrain comprises a synchronous reluctance motor and an inverter. A control strategy for the drivetrain is employed to execute two main tasks: 1) driving the motor properly to achieve a maximum torque per Ampere condition and 2) maximizing the output power of the PV system at different weather conditions. This means that the conventional DC-DC converter is not used in the proposed system. Moreover, batteries, which are characterized by short life expectancy and high replacement cost, are also not used. It is found that the motor output power and the pump flow rate are increased by about 9.5% and 12% respectively when the hybrid PV-TEG array is used compared to only using PV array. Accordingly, the performance, cost and complexity of the system are improved. Measurements on an experimental laboratory setup are constructed to validate the theoretical results of this work

Transient analysis and stability limits for synchronous reluctance motors considering saturation effects

This paper investigates the influence of the magnetic saturation on the performance of Synchronous Reluctance Motors (SynRMs) at transient operating conditions. In addition, the stability limits for the SynRM are studied with a more accurate method. The saturation, cross-saturation and position effects on both direct (d) and quadrature (q) axis flux linkages are considered. A Finite Element Method (FEM) is used to obtain an accurate representation for the dq-axis flux linkages relations. In order to reduce the calculation time of the finite element analysis, a look-up table (LUT) for the dq-axis flux linkages is generated based on the FEM to be used for simulating the SynRM characteristics. It is found that the magnetic saturation in the adopted motor results in an enlarged region of stable operation of the SynRM. The torque increases by about 200 % compared with the unsaturated case, which proves that it makes no sense to model this type of motor without saturation. The results show the importance of including the saturation factors on the performance of the SynRM and its stability limits. Hence, the magnetic saturation effect will not only affect the stability of the motor but also on the whole drive system

Solar array fed synchronous reluctance motor driven water pump : an improved performance under partial shading conditions

An improved performance of a photovoltaic (PV) pumping system employing a synchronous reluctance motor (SynRM) under partial shading conditions is proposed. The system does not include the dc-dc converter that is predominantly being utilized for maximizing the output power of the PV array. In addition, storage batteries are also not contained. A conventional inverter connected directly to the PV array is used to drive the SynRM. Further, a control strategy is proposed to drive the inverter so that the maximum output power of the PV array is achieved while the SynRM is working at the maximum torque per Ampere condition. Consequently, this results in an improved system efficiency and cost. Moreover, two maximum power point tracking (MPPT) techniques are compared under uniform and partial shadow irradiation conditions. The first MPPT algorithm is based on the conventional perturbation and observation (P&O) method and the second one uses a differential evolution (DE) optimization technique. It is found that the DE optimization method leads to a higher PV output power than using the P&O method under the partial shadow condition. Hence, the pump flow rate is much higher. However, under a uniform irradiation level, the PV system provides the available maximum power using both MPPT techniques. The experimental measurements are obtained to validate the theoretical work

Finite element based overall optimization of switched reluctance motor using multi-objective genetic algorithm (NSGA-II)

The design of switched reluctance motor (SRM) is considered a complex problem to be solved using conventional design techniques. This is due to the large number of design parameters that should be considered during the design process. Therefore, optimization techniques are necessary to obtain an optimal design of SRM. This paper presents an optimal design methodology for SRM using the non-dominated sorting genetic algorithm (NSGA-II) optimization technique. Several dimensions of SRM are considered in the proposed design procedure including stator diameter, bore diameter, axial length, pole arcs and pole lengths, back iron length, shaft diameter as well as the air gap length. The multi-objective design scheme includes three objective functions to be achieved, that is, maximum average torque, maximum efficiency and minimum iron weight of the machine. Meanwhile, finite element analysis (FEA) is used during the optimization process to calculate the values of the objective functions. In this paper, two designs for SRMs with 8/6 and 6/4 configurations are presented. Simulation results show that the obtained SRM design parameters allow better average torque and efficiency with lower iron weight. Eventually, the integration of NSGA-II and FEA provides an effective approach to obtain the optimal design of SRM

Multi-objective optimization of switched reluctance machine design using Jaya algorithm (MO-Jaya)

The switched reluctance machine (SRM) design is different from the design of most of other machines. SRM has many design parameters that have non-linear relationships with the performance indices (i.e., average torque, efficiency, and so forth). Hence, it is difficult to design SRM using straight forward equations with iterative methods, which is common for other machines. Optimization techniques are used to overcome this challenge by searching for the best variables values within the search area. In this paper, the optimization of SRM design is achieved using multi-objective Jaya algorithm (MO-Jaya). In the Jaya algorithm, solutions are moved closer to the best solution and away from the worst solution. Hence, a good intensification of the search process is achieved. Moreover, the randomly changed parameters achieve good search diversity. In this paper, it is suggested to also randomly change best and worst solutions. Hence, better diversity is achieved, as indicated from results. The optimization with the MO-Jaya algorithm was made for 8/6 and 6/4 SRM. Objectives used are the average torque, efficiency, and iron weight. The results of MO-Jaya are compared with the results of the non-dominated sorting genetic algorithm (NSGA-II) for the same conditions and constraints. The optimization program is made in Lua programming language and executed by FEMM4.2 software. The results show the success of the approach to achieve better objective values, a broad search, and to introduce a variety of optimal solutions