Baik-Kee Song

Permanent magnet synchronous motors (PMSMs) are vital to electrified transportation due to their superior torque density, efficiency, and reliability. However, traditional workflows that rely on analytical models and finite element analysis (FEA) are highly computationally intensive, limiting their practicality for large-scale, multi-objective optimization. To address this challenge, we propose an AI driven ensemble metamodel for optimizing integrated electronic brake (IEB) motors. The framework combines Gradient Boosting Regressor (GBR), Gaussian Process Regressor (GPR), and Artificial Neural Networks (ANNs), leveraging the strengths of boosting for nonlinear regression, probabilistic modeling for uncertainty quantification, and hierarchical learning for capturing complex mappings. When embedded in the non-dominated sorting genetic algorithm III (NSGA-III), the ensemble enables simultaneous optimization of torque ripple, cogging torque, and total harmonic distortion (THD) of the back-electromotive force (back-EMF), while satisfying torque constraints. The methodology was validated on both extensive (1000-sample) and reduced (25–50 sample) datasets, confirming robust accuracy and efficiency even under data-scarce conditions. A prototype optimized motor demonstrated strong alignment between predicted and experimental performance trends.

A conventional dual-winding (DW) motor has two internal windings consisting of a master part and a slave part, each connected to a different electronic control unit (ECU) to realize a redundant system. However, existing DW motors have a problem related to heat generation in both the healthy mode and the faulty mode of the motor operation. In the healthy mode, unexpected overloads can cause both windings to burn out simultaneously due to equal heat distribution. If the current sensor fails to measure correctly, the motor may exceed the designed current density of 4.7 [Arms/mm²] under air-cooling conditions, further increasing burnout risk. External factors such as excessive load cycles or extreme heat conditions can further exacerbate this issue. In the faulty mode, the motor requires double the current to generate maximum torque, leading to rapid temperature increases and a high risk of overheating. To address these challenges, this paper proposes the design of a thermal fault-tolerant asymmetric dual-winding (ADW) motor, which improves heat management in both healthy and faulty modes for autonomous vehicles. A lumped-parameter thermal network (LPTN) with a piecewise stator-housing model (PSMs) was employed to evaluate the coil temperature during faulty operation. An optimal design approach, incorporating kriging modeling, Design of Experiments (DOE), and a genetic algorithm (GA), was also utilized. The results confirm that the proposed ADW motor design effectively reduces the risk of simultaneous burnout in the healthy mode and overheating in the faulty mode, offering a robust solution for autonomous vehicle applications.

Manufactures of automotive parts are struggling to secure redundancy in various ways. An alternative is to configure the system via a dual-winding motor and two electronic control units (ECUs). The dual-winding motor contains different winding arrangements according to poles/slots, and when only one of the two circuits is used owing to a failure, the electrical and mechanical characteristics differ depending on the winding arrangement. In this study, the electrical and mechanical characteristics were analyzed and compared according to the winding arrangement when the failure occurs. In particular, the winding arrangement of the motor is divided into line symmetry, point symmetry, and alternating symmetry. For each winding arrangement, the back-electromotive force, torque, and torque ripple were compared and analyzed through simulation and test. Also, vibration caused by electromagnetic force was analyzed. Here, to consider the tooth modulation effect, concentrated force was investigated and tangential force as well as radial force were considered. Additionally, the thermal characteristics were analyzed during fault operation using a lumped parameter thermal network with piecewise stator-housing modules. Lastly, the mechanical design characteristics of the motor hardware size that need to be changed according to the winding arrangement of the brake motor are explained. This study provides guidelines for the winding arrangement selection of a dual-winding motor with a similar magnetic field distribution suitable for the design purpose, by analyzing the electromechanical characteristics and size according to the winding arrangement during fault operation. The characteristics of other motor types or pole and slot number combinations can also be inferred from the results of this study, since the magnetic flux density distribution will be determined with line, point and alternating symmetry.

A system-level fault-tolerant design process of a dual-winding three-phase permanent magnet (PM) motor for overheat problem is introduced. Conventional dual-winding three-phase PM motors have been designed with a focus on the redundant system without considering the overheating. However, in the introduced design process, the overheating problem is considered of the motor that occurs in a faulty operation mode in an integrated electric brake (IEB) system. In the design process, the faulty operation mode is investigated in the system level. The design variables are selected as the main components of the IEB system such as the motor and pump piston. Then the selected design variables are optimized to operate without performance degradation even in the faulty operation mode. To analyze the coil temperature rise during the faulty operation mode of a dual winding motor by motor and pump piston size, a lumped-parameter thermal network with piecewise stator-housing modules (LPTN with PSMs) is utilized. In addition, to conduct the optimal design, latin hypercube sampling (LHS), kriging modeling, and a genetic algorithm (GA) are utilized. A prototype of the optimized model is manufactured and tested for verification of design results. It was confirmed that the dual-winding motor for autonomous vehicles, which is robust against overheating, even in faulty operation mode, is well designed.

Autonomous emergency braking (AEB) is one of the safety technologies of the integrated electronic brake (IEB) system and is critical to avoiding or mitigating vehicular collisions. In addition, a motor is a significant component of the IEB system for its actuation, and it greatly affects this system’s performance under AEB. Notably, the determination of the IEB system’s motor parameters without considering its performance under AEB will not satisfy its requirements, especially due to this system’s hydraulic and electric complexity. In addition, the IEB system motor’s dynamic characteristics have a significant impact on the AEB performance. They are also closely related to this motor’s parameters, such as flux-linkage, inductance, and resistance. Therefore, this research performs the IEB system’s motor parametric design corresponding to this system’s necessary performance under AEB, using a coupled simulation model composed of this system’s motor and hydraulic subsystems. First, the IEB system’s motor and hydraulic subsystems are modeled in MATLAB/Simulink and AMESim, respectively, and the coupled simulation of these subsystems is performed in Simulink using their models. Second, the respective ranges of the IEB system’s motor parameters corresponding to this system’s necessary performance under AEB are determined from the above-mentioned coupled simulation, and their corresponding motor is designed using a finite element analysis in ANSYS Maxwell. Third, the IEB system’s fabricated, parametric-designed motor is tested for standalone performance. Finally, the IEB system incorporated with the said parametric-designed motor is experimentally verified of its performance under AEB. Meanwhile, the respective simulated and experimental performances of the IEB system under AEB and its parametric-designed motor agree well. This agreement indicates that the IEB system’s motor parametric design presented in this research, based on this system’s coupled simulation model and finite element analysis on this model, is valid.

This article introduces the single winding type selection process for a dual winding (DW) three-phase motor. Unlike the conventional DW three-phase motor design, the proposed single winding type selection process simultaneously considers the mechanical length determined by the single winding type and the motor overheating problem caused by faulty operation for each single winding type. The proposed single winding type selection process consists of four steps. First, all single-winding combinations, the point symmetry dual winding (PSDW), line symmetry dual winding (LSDW), and cross symmetry dual winding (CSDW) for DW three-phase motor are investigated. Second, according to the selected single winding types, the busbar height (BH) required for dual division is designed and compared. Third, the stack length (SL) of motor in the PSDW, the LSDW, and the CSDW obtained through overheat compensation design to avoid the overheating problem in the faulty mode are investigated and compared. In the overheat compensation design, the thermal map utilizing measurement data from the previously developed motor for an integrated electric brake (IEB) system, a radial basis function, an overheat compensation coefficient, and the IEB brake load condition are utilized. Finally, the single winding type of DW three-phase motor is selected as the CSDW by comparing the total motor size. As a result of the DW three-phase motor design, the proposed CSDW can reduce the motor size by 12.0% and 4.2%, respectively, compared with the PSDW and LSDW.

With the increased interest in intelligent transportation, the need for fault-tolerant systems has also increased. In this paper, we propose a piecewise stator-housing module (PSM) and construct a lumped-parameter thermal network (LPTN) that can be used in a fault-tolerant system based on the PSM. The proposed LPTN model considers not only radial and axial heat transfer but also tangential heat transfer; therefore, even if only one of the two circuits is running on a fault-tolerant motor (dual winding motor), the coil temperature can be estimated. To verify the proposed model, three winding-type motors are tested with varying current values during normal and fault operations, and the test and analysis results are in good agreement. Additionally, the usefulness of the proposed model is demonstrated by comparing the temperatures of both the conventional and proposed LPTNs in the event of a brake system fault during braking operation in a virtual traffic jam simulation. This simulation demonstrates that temperature estimation of the motor is important for motor design because the brake operation time is dependent on the motor temperature. Furthermore, the system performance or size can be determined by accurately predicting the temperature, even in the event of a fault in the brake system, where the fault-tolerant motor is used, thus keeping the driver safe. The proposed LPTN can be used in brake systems and in other systems that utilize fault-tolerant dual winding motors.

The performance of motors can vary considerably, depending not only on the design but also the manufacturing process. In particular, for motors used in systems wherein vibration and noise are important, the characteristics of the motors change according to the manufacturing method; hence, it is essential to study the effect of the manufacturing process on the characteristics of motors. In this study, motors with a connected core and segmented core are compared and analyzed; particularly, the motors are intended for use in a brake system. The general strengths and weaknesses of each core type are determined, and the electrical and mechanical properties of the motors are analyzed through finite element analysis (FEA). The motors are applied to an integrated brake system that does not employ a vacuum booster, and motors with each type of core are fabricated and tested to verify their characteristics. Finally, the analysis results obtained using FEA and the test results are compared and analyzed to evaluate the validity of this study.