Neodymium-boron (NdFeB) permanent magnets (PMs) have been widely studied in the past years since they became the material of choice in permanent magnet synchronous machines (PMSMs). Although NdFeB PMs have a better energy density than other types of magnets and are cost-effective, their magnetization is very sensitive to the PMSM operating conditions, in particular temperature, where the irreversible demagnetization degree increases over time. Therefore, it is important to characterize and diagnose demagnetization at an early stage. In this context, this paper proposes a two-step analysis study dealing with both uniform and partial demagnetization. A 2D finite element method-based (FEM) approach is used for demagnetization characterization, and then a PMSM motor current signature analysis (MCSA) approach, based on fast Fourier transform (FFT), is considered where fault cases harmonics are considered as faults indices to detect demagnetization. In some situations, the proposed two-step approach achieved results that clearly allow distinguishing and characterizing demagnetization. Indeed, a local demagnetization introduces specific sub-harmonics while a uniform demagnetization leads to the current amplitude increase for a given torque.

In recent years, the investment in the wind energy sector has increased in the context of producing green electricity and saving the environment. The installation of small wind turbines (SWTs) represents an actual strategy for meeting energy needs for off-grid systems and certain specialized applications. SWTs are more expensive per kilowatt installed as compared to large-scale wind turbines. Therefore, the main objective of this study is to produce an economical technology for the wind power market offering low-cost SWTs. The idea consists of considering a simple structure of the wind turbine using direct-drive permanent magnet synchronous generator (DDPMSG). DDPMSGs are the most useful machines in the wind energy field thanks to several advantages, such as elimination of noise and maintenance cost due to suppression of the gearbox and absence of the rotor circuit excitation barriers by the presence of the permanent magnets (PMs). Their major downside is the high cost of active materials, especially the PMs. Thus, the improvement of the generator design is treated as being the main component of the considered chain to assure active materials’ mass and cost reduction. The methodology studied aims to explain the approach of the design integrated by optimization of the considered system. It is based on the elaboration of analytical models to find a feasible structure for the system, taking into account the multi-disciplinary analysis. The relevance of these models is validated by the finite element method using 2D MATLAB-FEMM simulation. The models are integrated to elaborate the optimization problem based on a genetic algorithm to improve the cost of the proposed generator by minimizing the mass of its active constructive materials. As an outcome, an optimal solution is offered for the wind generators market, providing a 16% cost reduction.

The efficiency of an `IM' drive depends on the accuracy of the given parameters values, and the swiftness with which they are submitted to the `IM' drive. In this paper a two dimensional Finite Element Method `FEM' is performed to identify stator inductance, rotor time constant and magnetic dispersion coefficient. Calculations, using `FEM' analysis, for magnetic field density and magnetic flux are carried, by simulation using `FEMM' software, to identify the `IM' parameters. Study results, for different magnetising currents and rotor speeds, reflect the variation of the `IM' parameters and thus the `IM' behaviour. The obtained results are verified and compared to those obtained by practical tests.

In this paper, an optimal design approach for a permanent magnet synchronous machine (PMSM), as an electric vehicle (EV) traction machine is proposed in such a way that a high power density machine can be achieved. A surface mounted PMSM is selected for its high efficiency and torque density. The machine parameters and the design constraints are established based on the EV characteristics. Guided by the analytical results of the design approach, a finite element study is performed on the machine to verify the relevance of the proposed approach. Then, a new optimization method, combining particle swarm optimization (PSO) and chaos theory, is applied for the machine design parameters in order to maximize the power density. This algorithm, referred to as CPSO, utilizes the chaos system properties such as its sensitivity to the initial conditions and its dynamical behaviour to enhance the global search capabilities of the PSO algorithm. The simulation results show the effectiveness of this algorithm compared to other meta-heuristic algorithms in increasing the machine power density. Furthermore, it is found that the optimized PMSM offers a 41.60% improvement in power while respecting the EV characteristics.

This paper presents analysis, design, and optimization of a high-power permanent-magnet synchronous generator (PMSG). This generator is introduced in a large-scale wind turbine which can be used in a big wind farm. This generator is used in gearless configuration. The work focuses on the geometric sizing and the finite element analysis (FEA) of the PMSG. FEA is a good choice for analyzing problems over complicated domains. The flux, the electromotive force, the cogging torque, and the torque are calculated using analytical equations. Then, these parameters are obtained using finite element method (FEM) in the software FEMM and the compared with analytical results in order to validate our study. The second part presents the formulation of the optimization problem, including the optimization space, constraints, and objectives. The genetic algorithm (GA) is adopted in this design optimization in order to minimize the generator cost.

In this paper, a simple method battery charge controller has been designed to protect the battery from over-charging and deep discharges. The control of the process is entrusted to Arduino Uno board, that must be able to find out the battery state and determine when the charge process must be finished. The state of the battery is perfectly controlled all the time. The use of an Arduino Uno based on microcontroller has been considered in order to allow a good flexibility, to simplify the hardware required (only a few external components are used), and to provide an intelligent tool to undertake, through the programmed algorithm. A buck DCDC Converter has been used to step down voltage from the panel photovoltaic to charge voltage of the battery. This paper presents a comparison between the simulation and practical realization results of the device. A good agreement is obtained.