This paper presents a state-of-the-art review of axial-flux permanent-magnet (AFPM) machines in the aspects of construction, features, electromagnetic and thermal modeling, simulation, analysis, design, materials, and manufacturing. Some key references on the above-mentioned aspects pertaining to the machine are discussed briefly. Particular emphasis is given on the design and performance analysis of AFPM machines. A comparison among different permanent magnet machines is also provided. Thus, this paper makes a bridge between the currently used permanent magnet machines in industry and the recent developments of AFPM machines.

This paper determines the optimal capacity of solar photovoltaic (PV) and battery energy storage (BES) for grid-connected households to minimize the net present cost of electricity. Real-time rule-based home energy management systems using actual annual data of solar insolation, ambient temperature, household electricity consumption and electricity rates are used in the optimization process. The above technique is applied to two system configurations — household with a solar PV, and household with a solar PV and a BES. The uncertainty analysis is implemented using 10 years real data to confirm the optimal results. An accurate cash flow analysis is also presented to illustrate the customer payment in each year during the project lifetime. Sensitivity analysis are conducted by varying the cost and capacity of system components, grid constraint, average daily electricity demand, and retail price of electricity. A typical grid-connected household in South Australia is considered as the case study. A practical guideline is presented for the residential consumers in South Australia to select the optimal PV/BES based on their daily average electricity demand and the available rooftop space for PV installation. Finally, the proposed optimization method is applied to households of other Australian States and a comparison of results is presented.

This paper presents an axial-flux permanent magnet motor optimized by the genetic algorithm (GA)-based sizing equation and the finite-element analysis (FEA). The designed slotted TORUS motor produces sinusoidal back-EMF waveform, maximum power density, and reduced cogging torque. The GA obtained the dimensions of motors with different numbers of slots and the highest possible power density. Electromagnetic field analysis of the candidate motors obtained from GA with various dimensions is subjected through FEA to obtain the motors' characteristics. Based on the GA and FEA results, a candidate motor design is introduced and subjected to FEA for reoptimization and finalization of the motor design. Techniques like modifying winding configuration and permanent magnet skewing are investigated to attain the most sinusoidal back-EMF waveform and reduced cogging torque. FEA and GA simulation results are compared and agreed well to the flux density in various areas of the designed motor at no-load condition. The final designed motor (1 kW, 50 Hz, four poles) is fabricated and tested. Experimental results agree with those of the simulation, both satisfying the desired technical specifications.

Integration of renewable and energy storage components in standalone/grid‐connected energy systems, which results in hybrid energy systems, is increasing nowadays. Optimisation of hybrid energy systems is an essential matter for economic, clean, convenient and reliable energy supply. Since the optimal design should satisfy multiple objectives, application of multi‐objective optimisation is preferred rather than a single‐objective solution. By multi‐objective optimisation, a trade‐off among different objectives can be obtained. This study presents a timely survey on the state‐of‐the‐art in multi‐objective optimal design of hybrid standalone/grid‐connected energy systems. The existing literature is categorised by various indices: (i) standalone or grid‐connected mode; (ii) number and type of objective functions; (iii) completely renewable‐based or diesel‐renewable‐based hybrid systems; and (iv) multi‐energy systems. The applied objective functions, design constraints and decision variables in the optimisation of hybrid energy systems are addressed. It is found that the recent objective functions like customer satisfaction and grid‐dependency need further investigation in the multi‐objective design procedure.

This paper investigates the calculation, modelling and interpretation of efficiency maps for electrical machines. The efficiency maps are calculated using a finite-element based mapping of losses, torque and flux-linkage as a function of the d- and q-axis currents and speed. For modelling efficiency maps, it is shown that a number of key loss types can be described in the form T ^m ω ⁿ . The effect of each of these losses on the shape of the efficiency map is then explored. It is found that practical efficiency maps can be approximated using a series of such terms which leads to a better understanding of the losses in the machine. The above results are validated using the loss and efficiency maps of three example machines.