Search Results (69)

Electric mountain bikes (eMTBs) demand compact, high-torque motors capable of handling steep terrain and variable load conditions. Surface-mounted permanent magnet synchronous motors (SPMSMs) are widely used in this application due to their simple construction, ease of manufacturing, and cost-effectiveness. However, SPMSMs inherently lack reluctance torque, limiting their torque density and performance at high speeds. While interior PMSMs (IPMSMs) can overcome this limitation via reluctance torque, they require complex rotor machining and may compromise mechanical robustness. This paper proposes a surface-inset PMSM topology as a compromise between both approaches—introducing reluctance torque while maintaining a structurally simple rotor. The proposed motor features inset magnets shaped with a tapered outer profile, allowing them to remain flush with the rotor surface. This geometric configuration eliminates the need for a retaining sleeve during high-speed operation while also enabling saliency-based torque contribution. A baseline SPMSM design is first analyzed through finite element analysis (FEA) to establish reference performance. Comparative simulations show that the proposed design achieves a 20% increase in peak torque and a 33% reduction in current density. Experimental validation confirms these findings, with the fabricated prototype achieving a torque density of 30.1 kNm/m³. The results demonstrate that reluctance-assisted torque enhancement can be achieved without compromising mechanical simplicity or manufacturability. This study provides a practical pathway for improving motor performance in eMTB systems while retaining the production advantages of surface-mounted designs. The surface-inset approach offers a scalable and cost-effective solution that bridges the gap between conventional SPMSMs and more complex IPMSMs in high-demand e-mobility applications. Full article

The automotive industry is experiencing a period of transition from traditional internal combustion engine (ICE) vehicles to electric vehicles. Although electric machines have always been used in many applications, they are generally designed neglecting the sources of uncertainty, even such uncertainty can lead to significant deterioration of the motor performance. The aim of this paper is to compare the results obtained from the multi-objective optimization of an interior permanent magnet synchronous motor (IPMSM) using a robust approach versus a deterministic one. Unlike other studies in the literature, this research simultaneously considers different sources of uncertainty, such as geometric parameters, magnet properties, and operating temperature, to assess the variability of electric motor performance. Different designs of a 48 slot–8 pole motor are simulated with finite element analysis, then the outputs are used to train artificial neural networks that are employed to find the optimal design with different approaches. The method incorporates an innovative use of the neural network-based variance estimation (NNVE) technique to efficiently calculate the standard deviation of the objective functions. Finally, the results of the robust optimization are compared with those of the deterministic optimization. Due to the small margin of improvement in robustness, both methods lead to similar results. Full article

In this article, the linear non-equilibrium thermodynamic approach is used to mathematically describe the energy regularities of an interior permanent magnet synchronous motor (IPMSM), taking into account iron loss. The IPMSM is considered a linear power converter (PC) that is multiple-linearized at operating points with a given angular velocity and load torque. A universal description of such a PC by a system of dimensionless parameters and characteristics made it possible to analyze the perfection of energy conversion in the object. For IPMSM, taking into account iron loss, a mathematical model of the corresponding PC has been built, and an algorithm and research program have been developed, which is valid in a wide range of machine speed regulations. This allows you to choose the optimal points of PC operation according to the maximum efficiency criteria and obtain the efficiency maps for IPMSM in different speed regions. The results of the studies demonstrate the effectiveness of the proposed method for determining the references of the d and q components of the armature current for both the loss-minimization strategy at the constant torque range of motor speed and the flux-weakening strategy in the constant power range. Full article

This paper describes the detailed design procedure of electric machines using finite element analysis (FEA). The proposed method uses the available findings from the literature and FEA results for the design procedure. In addition to electromagnetic analysis, thermal analysis is executed to examine the capability of the designed machines for handling the load in terms of thermal limits. It allows for considering the normal and overload performance of the electric machines during design. The proposed design procedure is used for designing a 100 kW induction machine (IM) and interior permanent magnet synchronous machine (IPMSM) for a parallel hybrid electric vehicle (HEV). The differences between the performance parameters of the studied machines are discussed, and the advantages and disadvantages of each design are highlighted. The designed machines are compared with commercially available electrical machines in terms of performance and power density. The comparison demonstrates that the developed machines can offer comparable performance to other designs. Full article

Interior permanent magnet synchronous machines (IPMSMs) are widely used as traction motors in the electric drive-train because of their high torque-per-ampere characteristics and potential for wide field weakening operation to expand the constant power range. The paper aims to introduce the most important equations to calculate the operating trajectories of an IPMSM for optimal control. The main contribution is that the optimal operating trajectories are calculated by a feedforward, Newton–Raphson method-based searching algorithm that considers the iron loss resistance of IPMSMs. Steady-state calculations and dynamic simulation results prove the theoretical findings. Full article

This paper presents an innovative design for an interior permanent magnet synchronous motor (IPMSM), targeting enhanced performance for electric vehicle (EV) applications. The proposed motor features a double V-shaped rotor structure with irregular ferrite magnets embedded in the slots between the permanent magnets. This design significantly enhances torque performance. Furthermore, a machine learning-based surrogate model is developed by integrating fine and coarse mesh data. Optimized using the Non-dominated Sorting Genetic Algorithm II (NSGA-II), this surrogate model effectively reduces computational time compared to traditional finite element analysis (FEA). Full article

The use of interior permanent-magnet synchronous machines (IPMSMs) is prevalent in automotive and vehicle traction applications due to their high efficiency over a wide speed range. Given the high-power-density requirements of automotive IPMSMs, it is imperative to consider the effect of nonlinearities, such as saturation and cross-coupling, on the motor model. The aforementioned nonlinearities render conventional linear motor models incapable of accurately describing the operating characteristics of the IPMSM, including the maximum torque per ampere (MTPA) trajectory, the flux-weakening (FW) trajectory, and the maximum torque per volt (MTPV) trajectory. With respect to the linear motor model, the nonlinear flux-linkage model is gradually receiving attention from researchers. This modeling method represents the nonlinear behavior of the motor through the direct establishment of a bidirectional mapping relationship between flux-linkage and current. It is capable of naturally incorporating the effects of magnetic saturation and cross-coupling factors. However, the analysis of the current trajectory optimal criteria based on this model has not yet been reported. In this paper, the optimal criteria for the MTPA and MTPV current trajectories are analyzed based on the nonlinear flux-linkage model of IPMSMs. Firstly, the nonlinear flux-linkage model of the tested IPMSM is established by the experimental calibration method. The mathematical analytical expressions of the MTPA and MTPV optimal criteria are then analyzed by constructing and solving optimal problems with different objectives. Finally, the current command table applicable to actual motor control is constructed by calculating the current command for different operating conditions according to the optimal criteria proposed in this paper. The validity and feasibility of the optimal criteria proposed in this paper are verified through experimental tests on different operating conditions. Full article

Interior permanent magnet synchronous machines (IPMSMs) driven with a square-wave control (i.e., six-step, block, or 120° control), known commonly as brushless direct current (BLDC) drives, are used widely due to their high power density and control simplicity. The advance firing (AF) angle is employed to achieve improved operation characteristics of the drive. The AF angle is, in general, applied to compensate for the commutation effects. In the case of an IPMSM, the AF angle can also be adjusted to exploit reluctance torque. In this paper, a detailed study was performed to understand its effect on the drive’s performance in regard to reluctance torque. Furthermore, a multi-objective optimization of the machine’s cross-section using neural network models was conducted to enhance performance at a constant AF angle. The reference and improved machine designs were evaluated in a system-level simulation, where the impact was considered of the commutation of currents. A significant improvement in the machine performance was achieved after optimizing the geometry and implementing a fixed AF angle of 10°. Full article

In this paper, the enhanced nonlinear magnetic model of the low voltage interior permanent magnet synchronous machine (IPMSM) is developed using the frozen permeability (FP) technique in finite element analysis (FEA) FEMM 4.2 software. The magnetic model is derived by obtaining flux saturation maps for a wide range of dq stator currents. Furthermore, the FEA FP technique accounts for the corresponding offset in the flux maps due to the excitation of the permanent magnets, and well as for fitting the coefficients for the curve-fitting procedure. In order to demonstrate the usefulness of the proposed magnetic model, a nonlinear control strategy based on the maximum torque per ampere (MTPA) optimal algorithm for IPMSM is employed. The magnetic model and the MTPA control strategy are validated through a variety of computer simulations based on FEMM 4.2 and MATLAB R2023a software, as well as on a real IPMSM electric vehicle (EV) traction drive experimental setup. Full article

Post-assembly magnetization can significantly simplify the manufacturing of the rotor of permanent magnet (PM) electrical machines. The optimization of the post-assembly magnetizing device using finite element analysis (FEA) is time-consuming; therefore, a globally optimal solution aiming at achieving an adequate magnetizing level and minimal energy consumption is difficult to achieve. In this paper, a field–circuit coupling analysis (FCCA) model is proposed to optimize the auxiliary stator-type magnetizing device for interior permanent magnet synchronous machines (IPMSMs). A reasonable simplification of the highly saturated magnetic circuit is made based on FEA results so that the magnetic equivalent circuit (MEC) model can be established. On the other hand, the eddy currents in the PMs are equivalent to an eddy current short-circuit; thus, by converting the field calculation into a circuit calculation, the time cost can be reduced significantly, which greatly improves the speed of multi-objective optimization of the magnetizing device with multiple degrees of freedom. A V-type IPMSM is taken as a study case, and its post-assembly magnetizing device is optimized with the proposed method. FEA and experimental results show that the PMs are fully magnetized, while the required energy consumption is greatly reduced when compared with an existing magnetizing device. Full article

This paper introduces a parameter-estimation-based sensorless adaptive direct voltage maximum torque per ampere (MTPA) control strategy for interior permanent magnet synchronous machines (IPMSMs). In direct voltage control, the motor’s electrical parameters, speed, and rotor position are of great significance. Thus, any mismatch in these parameters or failure to acquire accurate speed or position information leads to a significant deviation in the MTPA trajectory, causing high current consumption and hence affecting the performance of the entire control system. In view of this problem, a fuzzy logic control-based cascaded model reference adaptive system (FLC-MRAS) is introduced to mitigate the effect of parameter variation on the tracking of the MTPA trajectory and to provide precise information about the rotor speed and position. The cascaded scheme consists of two parallel FLC-MRAS for speed and multiparameter estimation. The first MRAS is utilized to estimate motor speed and rotor position to achieve robust sensorless control. However, the speed estimator is highly dependent on time-varying motor parameters. Therefore, the second MRAS is designed to identify the quadratic inductance and permanent magnet flux and continuously update both the speed estimator and control scheme with the identified values to ensure accurate speed estimation and real-time MTPA trajectory tracking. Unlike conventional MRAS, which uses linear proportional-integral controllers (PI-MRAS), an FLC is adopted to replace the PI controllers, ensuring high estimation accuracy and enhancing the robustness of the control system against sudden changes in working conditions. The effectiveness of the proposed scheme is evaluated under different speed and torque conditions. Furthermore, a comparison against the conventional PI-MRAS is extensively investigated to highlight the superiority of the proposed scheme. The evaluation results and our quantitative assessment show the ability of the designed strategy to achieve high estimation accuracy, less oscillation, and a faster convergence rate under different working conditions. The quantitative assessment reveals that the FLC-MRAS can improve the estimation accuracy of speed, permanent magnet flux, and quadratic inductance by 19%, 55.8% and 44.55%, respectively. Full article

At present, the majority of electric machine design software employs its own unique machine data structure. However, when users need to transfer their designs between software, they are often faced with significant obstacles or cannot obtain a parametric model suitable for optimization. In order to solve this issue, a universal parametric modeling framework is proposed for electric machine design. The geometric structure is strictly constrained to ensure that the model will not interfere with each part because of the randomness of input parameters. A data structure consisting of points, lines, and surfaces is constructed, and a conversion interface for parametric modeling with different software is established. Consequently, this universal framework can automatically generate parametric models appropriate for different finite element analysis (FEA) software according to the input parameters. The framework is especially convenient for users who need to design or optimize an electric machine, particularly when FEA software is required for verification. Numerical verification is performed using different software based on interior permanent magnet (IPM) synchronous machines to demonstrate the effectiveness of the framework. Full article

Electrical machines generate unwanted flux and current harmonics. Harmonics can be suppressed using various methods. In this paper, the harmonics are significantly reduced using Iterative Learning Control (ILC) and Neural Networks (NNs). The ILC can compensate for the harmonics well for operation at constant speed and current reference values. The NNs are trained with the data from the ILC and help to suppress the harmonics well even in transient operation. The simulation model is based on flux and torque maps, depending on $dq$-currents and the electrical angle. The maps are generated from FEM simulation of an interior permanent magnet synchronous machine (IPM) and are published with the paper. They are intended to serve other researchers for direct comparison with their own methods. Simulation results in this paper verify that by using ILC and NNs together, current harmonics in transient operation can be eliminated better than without NNs. Full article

At present, the induction motor (IM), synchronous reluctance motor (SynRM), ferrite-assisted synchronous reluctance motor (ferrite-assisted SynRM) and interior permanent magnet motor (IPM) are research hotspots, but comprehensive comparative research on the four motors is still rare. This paper mainly compares the four motors from the aspects of electromagnetic performance, material cost and temperature distribution. Firstly, the volume of the four motors is ensured to be the same. The influence of the rotor design parameters of the SynRM, ferrite-assisted SynRM and IPM on the electromagnetic properties of the machine is analyzed. Secondly, based on the effects of each parameter, the overall design parameters of the four motors are determined. The electromagnetic performance, material cost and temperature of the four motors are compared and discussed. Finally, the comparison results are summarized, and the advantages of the four motors are analyzed. In different applications, the electromagnetic performance, heat dissipation and cost requirements of the four motors are different. Therefore, this paper makes a comprehensive comparison of the four motors to provide a reference for the selection of motors for different applications. Full article

This paper introduces a state-of-the-art inverter–machine codesign methodology for achieving an energy-efficient electric drive system. The methodology is applied in an optimal design case study with the context of the latest trend in the 800 V system. To reduce the voltage rating, a three-level active neutral point clamped topology is utilized in the inverter design, incorporating silicon carbide technology for high-speed operation. This combination allows for efficient power conversion with reduced losses. In the machine design, the increased number of poles that can be achieved in the design phase, along with the utilization of high-speed switching frequencies, enables the development of more efficient machines. Based on the design of the experiment method, by optimizing the parameters of both the inverter and machine simultaneously, using a cosimulation model, the 7.7% of total energy loss during drive cycle operation can be improved. Full article