Brushless direct current (BLDC) motors are mostly preferred for dynamic applications such as automotive industries, pumping industries, and rolling industries. It is predicted that by 2030, BLDC motors will become mainstream of power transmission in industries replacing traditional induction motors. Though the BLDC motors are gaining interest in industrial and commercial applications, the future of BLDC motors faces indispensable concerns and open research challenges. Considering the case of reliability and durability, the BLDC motor fails to yield improved fault tolerance capability, reduced electromagnetic interference, reduced acoustic noise, reduced flux ripple, and reduced torque ripple. To address these issues, closed-loop vector control is a promising methodology for BLDC motors. In the literature survey of the past five years, limited surveys were conducted on BLDC motor controllers and designing. Moreover, vital problems such as comparison between existing vector control schemes, fault tolerance control improvement, reduction in electromagnetic interference in BLDC motor controller, and other issues are not addressed. This encourages the author in conducting this survey of addressing the critical challenges of BLDC motors. Furthermore, comprehensive study on various advanced controls of BLDC motors such as fault tolerance control, Electromagnetic interference reduction, field orientation control (FOC), direct torque control (DTC), current shaping, input voltage control, intelligent control, drive-inverter topology, and its principle of operation in reducing torque ripples are discussed in detail. This paper also discusses BLDC motor history, types of BLDC motor, BLDC motor structure, Mathematical modeling of BLDC and BLDC motor standards for various applications.

Electric vehicles (EVs) are playing a vital role in sustainable transportation. It is estimated that by 2030, Battery EVs will become mainstream for passenger car transportation. Even though EVs are gaining interest in sustainable transportation, the future of EV power transmission is facing vital concerns and open research challenges. Considering the case of torque ripple mitigation and improved reliability control techniques in motors, many motor drive control algorithms fail to provide efficient control. To efficiently address this issue, control techniques such as Field Orientation Control (FOC), Direct Torque Control (DTC), Model Predictive Control (MPC), Sliding Mode Control (SMC), and Intelligent Control (IC) techniques are used in the motor drive control algorithms. This literature survey exclusively compares the various advanced control techniques for conventionally used EV motors such as Permanent Magnet Synchronous Motor (PMSM), Brushless Direct Current Motor (BLDC), Switched Reluctance Motor (SRM), and Induction Motors (IM). Furthermore, this paper discusses the EV-motors history, types of EV-motors, EV-motor drives mathematical modelling, and design procedure of EV-motors. The hardware results have also been compared with different control techniques for BLDC hub and SRM. Future direction towards the design of EVs by a critical selection of motors and their control techniques to minimize the torque ripple and other research opportunities to enhance the performance of EVs are also presented.

Electric vehicles (EVs) are widespread, and their usage is increasing as a result of air pollution and rising fuel costs. EVs are quickly gaining popularity as a green means of transportation. By 2030, most cars will probably be battery-powered EVs. However, the development of EV power transmission is packed with important challenges and is an active topic of research. In EVs, the battery serves to store electrical energy. The DC-DC converter provides a direct current (DC) link between the battery and the inverter. A motor provides the transmission for the vehicle’s motion. Hence, this state-of-the-art provides exhaustive information about battery management systems (BMS), power electronics converters, and motors. Lithium-ion batteries are more efficient for EV applications, and boost converters and full bridge converters are commonly used in EVs. EVs use permanent magnet synchronous motors (PMSM) and induction motors (IM). The renewable energy-based charging station and the fast charging specifications are also clearly addressed for EV applications.

The low-cost silicon-made Switched Reluctance Motor (SRM) stands out as a prominent choice for traction motor applications due to its robust rotor structure, fault-tolerance characteristics, lack of permanent magnets, capable speed-torque characteristics, power, and torque density. However, the existing Direct Torque Control (DTC) approach 8 Voltage Vectors (VVs) gives high torque ripples due to the minimum selection of switching states and improper sector partition. On the other hand, the existing Model Predictive Direct Torque Control (MPDTC) model, which employs 8 VVs, suffers from high torque ripples due to the minimal switching state choice and improper sector partitioning. Therefore, this paper proposes an MPDTC utilization of active small and large VVs (i.e., 16 VVs) with a 16-sector partition scheme to effectively reduce torque ripple. The active VVs employed in the modified sector-based switching tables result in suppressing the torque ripples. The proposed strategy is validated and verified through MATLAB/Simulink, with detailed results that discuss the response of torque, flux, and speed in the SRM drive. The experimental results of the SRM drive operated under the MPDTC are presented to demonstrate the effective minimization of torque ripples compared to the existing DTC.

Power Factor Correction (PFC) is crucial for the efficient operation of Switched Reluctance Motor (SRM) converters, as it enhances energy utilization and minimizes system losses. Conventional PFC techniques often rely on passive components or simple active methods, which may not fully exploit the dynamic characteristics of SRM operation. Low power factors in SRM converters lead to increased reactive power consumption and potential grid disturbances, necessitating effective PFC strategies to optimize energy efficiency, enhance system performance, and ensure compliance with standards. Therefore, this paper proposes a buck-boost converter to efficiently regulate the DC voltage supplied to the load, enabling voltage levels higher or lower than the input voltage while improving PFC in SRM converters. The objective is to address current challenges and push the boundaries of efficiency and performance. The proposed control strategies leverage the unique characteristics of SRMs to achieve superior PFC performance by dynamically adjusting the converter’s operation in real time based on motor load conditions. This approach ensures optimal PFC across a wide range of operating conditions. The proposed model is developed and validated using MATLAB/Simulink. Simulation and experimental results assess the motor’s performance under both static and dynamic load conditions. Additionally, the effectiveness of the converter is evaluated by analyzing the total harmonic distortion of the input current.

The robust rotor structure and fault-tolerance characteristics of the Switched Reluctance Motors (SRMs) are the best choice for next-generation Electric Vehicle (EV) applications. This machine has few restraints like high torque and flux ripples. However, the existing Model Predictive Control (MPC) using multiple control objectives and maximum sectors in the switching table results in high torque ripples due to the improper sector partition, Voltage Vectors (VVs) and weight factor (K₁) selection. This paper proposes a Finite Set-Model Predictive Control (FS-MPC) for an analytical model of a non-linearity SRM machine to analyze the torque ripple performance. The proposed VVs are derived using sector partition based on the rotor position. The control is designed as a single cost function with the weighting factor contributing to smooth torque by selecting optimal control signals. Simulation studies and experiments with a four-phase 8/6 SRM drive verifies the enhanced FS-MPC for real-time implementation. The dynamic speed and ripple values of SRM Drives are measured using a mixed signal oscilloscope and the sensor probes. The laboratory outcomes calculate the analytical equations to validate the findings. The calculated value of torque ripple is 9 % through this FS-MPC. The study reveals that the proposed method is well suited for torque ripple reduction than flux ripples.