Jin Hwan Lee

In the conventional power trunk locking system for vehicles, the mechanical latch is used. However, because the mechanical latch is exposed on the trunk exterior, it is vulnerable to damage during use. Therefore, this article proposes a novel power trunk locking system using electromagnetic force to remove protrusion of conventional trunk locking system. The proposed system consists of contact plate, magnetic module, gear train, and cinching motor. The electromagnetic force from the permanent magnet in the magnetic module is applied to the contact plate attached to the trunk, thereby maintaining the holding force. In this article, firstly, the principle of a proposed magnetic trunk locking system is introduced. Subsequently, the performance of the prototype magnetic module is analyzed using three-dimensional finite element analysis, and further verified by experimental tests. Furthermore, a magnetic equivalent circuit model is developed to derive a design strategy for weight reduction. Finally, design variables for weight reduction of the magnetic module are selected, and weight reduction design is carried out using machine learning based meta model.

This article proposes a hybrid approach that combines magneto-quasi-static finite element analysis (MQS-FEA) with analytical formulas to efficiently estimate ac copper losses in an electric vehicle propulsion motor with hairpin windings. The method accurately accounts for both skin and proximity effect losses, while substantially reducing computation time. Skin effect losses caused by both the sinusoidal current and pulse width modulation (PWM) harmonics are calculated using a reactance-limited loss equation, which effectively captures current redistribution and accelerates loss evaluation. For proximity effect losses, MQS-FEA is first used to compute the slot leakage flux and PM fields under sinusoidal excitation. The frozen permeability method is then applied to estimate PWM-induced slot leakage flux. To improve the accuracy of proximity loss estimation, a probabilistic approach is employed. The representative external fields are defined by selecting harmonic components based on kernel density estimation of the continuous probability density function of element-wise flux densities. The resulting eddy current losses are evaluated using the reactance-limited formulation, incorporating PWM-induced fields. Compared with using only transient FEA, it also facilitated rapid efficiency map construction. Finally, experimental validation using a 150 kW target motor confirmed the accuracy of the proposed method.

The interior permanent magnet synchronous motor (IPMSM), widely used in electric vehicles, shows performance variations with temperature, which can impact control accuracy and driving range. Therefore, this article derives the rotor shape of IPMSM to reduce performance deviation under temperature variation. First, the overall operating characteristics of IPMSM in response to temperature variation, such as constant torque curve and maximum torque per ampere trajectories, are analyzed. Second, the effects of temperature on efficiency of IPMSM are investigated. As a result, for reducing rated torque and efficiency deviation caused by temperature changes, the proportion of reluctance torque needs to be increased. Furthermore, the improvement design considering temperature variation are conducted using machine learning based meta models and multi-objective optimization algorithm. Finally, to validate the theoretical analysis and numerical simulations, a prototype is fabricated and tested.

This study investigates the interrelationship between shaft voltage (SV) and AC copper loss (ACCL) based on design variables that influence both characteristics. In previous works, issues with SV and ACCL have been reported in electric vehicle propulsion motors operating at high speeds. While methods to individually reduce these characteristics are well established, the correlation between them with respect to design variables has not yet been explored. To analyze this correlation, an analysis of the equations related to parasitic capacitances and ACCL is conducted to identify the key design variables affecting both SV and ACCL. These variables include the distance between the winding and the rotor, slot opening width, and winding width. Based on these design variables, a correlation analysis is conducted to confirm how these characteristics change simultaneously, and the results are verified through finite element analysis. Finally, an optimization process is implemented to minimize SV and ACCL while achieving the target average torque. The results are validated experimentally.

This study proposes a novel wedge-less stator (WLS) geometry to reduce the winding-to-rotor capacitance C_wr for mitigating shaft voltage in electric vehicle propulsion motors, with consideration for manufacturability. The WLS geometry features a unique structure termed a winding holder, positioned beneath the winding, which not only blocks the electric field between the winding and rotor but also secures the winding without the wedge. Initially, the working principle of the proposed geometry is investigated in terms of electric fields. Subsequently, a comparative study of a wedged stator model (WSM) and the WLS model (WLSM), including a base model, is conducted to evaluate the C_wr mitigation effect according to the stator geometry. Finally, the WSM and WLSM are optimized to enhance torque and electrostatic performances. Lastly, prototypes of optimized models are fabricated and tested to validate the improved performance and manufacturability of the proposed concept.

This paper proposes the optimization algorithm, an adjusted evolution strategy (AES) and verifies performance of the AES applying the optimal design of the outer-rotor surface mounted permanent magnet synchronous motor (SPMSM) for unmanned aerial vehicle. The proposed algorithm improved disadvantage of the conventional evolution strategy, which requires long computation time when solving the optimization problem, utilizing an exponential function of the annealing factor. In addition, the AES further enhances the convergence characteristic by combining with the compass segment method which is deterministic algorithm. This paper shows that the superiority of AES over NGA and ES in three test functions, with 30% to 70% reduction in the number of function calls, and an improvement of 5%p to 30%p in the convergence accuracy. Finally, the AES is applied to the optimization design of the outer-rotor SPMSM, and this paper derived the optimal model of the SPMSM to increase average torque and reduce torque ripple that causes vibration in unmanned aerial vehicle. As a result, proposed algorithm successfully derived the optimal model and verified the robustness. Therefore, the results of this study are expected to be widely applied to the multimodal optimization problem of various electrical machines utilizing FEM.