Critical Aspects of Electric Motor Drive Controllers and Mitigation of Torque Ripple - Review

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 EVmotors, EV-motor drives powertrain mathematical modelling, and design procedure of EV-motors. The hardware results have also been compared with different control techniques for BLDC and SRM hub motors. Future direction towards the design of EV by 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.publishedVersio

Advances in Rotating Electric Machines

It is difficult to imagine a modern society without rotating electric machines. Their use has been increasing not only in the traditional fields of application but also in more contemporary fields, including renewable energy conversion systems, electric aircraft, aerospace, electric vehicles, unmanned propulsion systems, robotics, etc. This has contributed to advances in the materials, design methodologies, modeling tools, and manufacturing processes of current electric machines, which are characterized by high compactness, low weight, high power density, high torque density, and high reliability. On the other hand, the growing use of electric machines and drives in more critical applications has pushed forward the research in the area of condition monitoring and fault tolerance, leading to the development of more reliable diagnostic techniques and more fault-tolerant machines. This book presents and disseminates the most recent advances related to the theory, design, modeling, application, control, and condition monitoring of all types of rotating electric machines

Direct Torque Control for Silicon Carbide Motor Drives

Direct torque control (DTC) is an extensively used control method for motor drives due to its unique advantages, e.g., the fast dynamic response and the robustness against motor parameters variations, uncertainties, and external disturbances. Using higher switching frequency is generally required by DTC to reduce the torque ripples and decrease stator current total harmonic distortion (THD), which however can lower the drive efficiency. Through the use of the emerging silicon carbide (SiC) devices, which have lower switching losses compared to their silicon counterparts, it is feasible to achieve high efficiency and low torque ripple simultaneously for DTC drives. To overcome the above challenges, a SiC T-type neutral point clamped (NPC) inverter is studied in this work to significantly reduce the torque and flux ripples which also effectively reduce the stator current ripples, while retaining the fast-dynamic response as the conventional DTC. The unbalanced DC-link is an intrinsic issue of the T-type inverter, which may also lead to higher torque ripple. To address this issue, a novel DTC algorithm, which only utilizes the real voltage space vectors and the virtual space vectors (VSVs) that do not contribute to the neutral point current, is proposed to achieve inherent dc-link capacitor voltage balancing without using any DC-link voltage controls or additional DC-link capacitor voltages and/or neutral point current sensors. Both dynamic performance and efficiency are critical for the interior permanent-magnet (IPM) motor drives for transportation applications. It is critical to determine the optimal reference stator flux linkage to improve the efficiency further of DTC drives and maintain the stability of the drive system, which usually obtained by tuning offline and storing in a look-up table or calculated online using machine models and parameters. In this work, the relationship between the stator flux linkage and the magnitude of stator current is analyzed mathematically. Then, based on this relationship, a perturb and observe (P&O) method is proposed to determine the optimal flux for the motor which does not need any prior knowledge of the machine parameters and offline tuning. However, due to the fixed amplitude of the injected signal the P&O algorithm suffers from large oscillations at the steady state conditions. To mitigate the drawback of the P&O method, an adaptive high frequency signal injection based extremum seeking control (ESC) algorithm is proposed to determine the optimal reference flux in real-time, leading to a maximum torque per ampere (MTPA) like approach for DTC drives. The stability analysis and key parameters selection for the proposed ESC algorithm are studied. The proposed method can effectively reduce the motor copper loss and at the same time eliminate the time consuming offline tuning effort. Furthermore, since the ESC is a model-free approach, it is robust against motor parameters variations, which is desirable for IPM motors

A Low-Complexity Optimal Switching Time-Modulated Model-Predictive Control for PMSM With Three-Level NPC Converter

Conventional finite control set model-predictive control (FCS-MPC) presents a high computational burden, especially in three-level neutral-point-clamped (NPC) converters. This article proposes a low-complexity optimal switching time-modulated model-predictive control (OST-M2PC) method for a three-level NPC converter. In the proposed OST-M2PC method, the optimal switching time is calculated using a cost function. Compared with the conventional FCS-MPC, the proposed OST-M2PC method has a fixed switching frequency as well as better power quality. The proposed OST-M2PC can operate at a 20-kHz sampling frequency, reducing the computational burden of the processor. Simulation and experimental results validate the operation of the proposed method

Mathematical Approaches to Modeling, Optimally Designing, and Controlling Electric Machine

Optimal performance of the electric machine/drive system is mandatory to improve the energy consumption and reliability. To achieve this goal, mathematical models of the electric machine/drive system are necessary. Hence, this motivated the editors to instigate the Special Issue “Mathematical Approaches to Modeling, Optimally Designing, and Controlling Electric Machine”, aiming to collect novel publications that push the state-of-the art towards optimal performance for the electric machine/drive system. Seventeen papers have been published in this Special Issue. The published papers focus on several aspects of the electric machine/drive system with respect to the mathematical modelling. Novel optimization methods, control approaches, and comparative analysis for electric drive system based on various electric machines were discussed in the published papers

Advances in dual-three-phase permanent magnet synchronous machines and control techniques

Multiphase electrical machines are advantageous for many industrial applications that require a high power rating, smooth torque, power/torque sharing capability, and fault-tolerant capability, compared with conventional single three-phase electrical machines. Consequently, a significant number of studies of multiphase machines has been published in recent years. This paper presents an overview of the recent advances in multiphase permanent magnet synchronous machines (PMSMs) and drive control techniques, with a focus on dual-three-phase PMSMs. It includes an extensive overview of the machine topologies, as well as their modelling methods, pulse-width-modulation techniques, field-oriented control, direct torque control, model predictive control, sensorless control, and fault-tolerant control, together with the newest control strategies for suppressing current harmonics and torque ripples, as well as carrier phase shift techniques, all with worked examples

Repetitive predictive control and its application to PMSMs

Repetitive Control is a learning control algorithm used to solve the problems of tracking the references and/or rejecting the disturbances that have repetitive nature. One of the challenging problems in repetitive control is to maintain the performance of the controller when the manipulated and/or state variables are hitting the constraints. Meanwhile, it is well known that Model Predictive Control (MPC) has its reputation in dealing with the constrained control problem through the use of optimization algorithms. This thesis incorporates the concept of repetitive control into the design of an MPC controller, resulting a new controller termed Repetitive-Predictive Control (RPC), so that the benefits of both controllers are combined, such as repetitiveness, constraints and multi-variable control. The design of the RPC controller is achieved by incorporating the dominant frequency components identified by the frequency decomposition of the reference signal into the receding horizon control of MPC. To further investigate the strength and weakness of the RPC, the design, tuning and performance of the RPC controller is thoroughly explored by its application to the control of Permanent Magnet Synchronous Motors (PMSMs) that have been broadly adopted for industrial control application due to their low volume and high efficiency. The decision to use PMSMs as the application of RPC is reflected by the increasing trend to apply the Repetitive Control (RC) and Model Predictive Controller (MPC) for the electric drives in recent years. The design of RPC for the position, speed and current regulation of a PMSM has been investigated under two different schemes based on the Field Oriented Control (FOC). The first scheme employs the cascade structure with constrained MPC and RPC replacing the PI controllers for the inner-loop current control and outer-loop speed/position control, respectively. The second scheme is to combine both speed and current controllers into one single multi-variable model predictive controller with operating constraints imposed. The experimental comparisons of the two control schemes with cascade PI controllers demonstrate the superior performance of cascade RPC/MPC in terms of the ability of constrained control, disturbance rejection and position tracking. All results in the thesis have been validated by an experimental test-bed with an industrial-sized PMSM

Design and Control of Electrical Motor Drives

Dear Colleagues, I am very happy to have this Special Issue of the journal Energies on the topic of Design and Control of Electrical Motor Drives published. Electrical motor drives are widely used in the industry, automation, transportation, and home appliances. Indeed, rolling mills, machine tools, high-speed trains, subway systems, elevators, electric vehicles, air conditioners, all depend on electrical motor drives.However, the production of effective and practical motors and drives requires flexibility in the regulation of current, torque, flux, acceleration, position, and speed. Without proper modeling, drive, and control, these motor drive systems cannot function effectively.To address these issues, we need to focus on the design, modeling, drive, and control of different types of motors, such as induction motors, permanent magnet synchronous motors, brushless DC motors, DC motors, synchronous reluctance motors, switched reluctance motors, flux-switching motors, linear motors, and step motors.Therefore, relevant research topics in this field of study include modeling electrical motor drives, both in transient and in steady-state, and designing control methods based on novel control strategies (e.g., PI controllers, fuzzy logic controllers, neural network controllers, predictive controllers, adaptive controllers, nonlinear controllers, etc.), with particular attention to transient responses, load disturbances, fault tolerance, and multi-motor drive techniques. This Special Issue include original contributions regarding recent developments and ideas in motor design, motor drive, and motor control. The topics include motor design, field-oriented control, torque control, reliability improvement, advanced controllers for motor drive systems, DSP-based sensorless motor drive systems, high-performance motor drive systems, high-efficiency motor drive systems, and practical applications of motor drive systems. I want to sincerely thank authors, reviewers, and staff members for their time and efforts. Prof. Dr. Tian-Hua Liu Guest Edito

Control techniques of switched reluctance motors in electric vehicle applications: A review on torque ripple reduction strategies

As electric vehicles (EVs) continue to acquire prominence in the transportation industry, improving the outcomes and efficiency of their propulsion systems is becoming increasingly critical. Switched Reluctance Motors (SRMs) have become a compelling option for EV applications due to their simplicity, magnet-free design, robustness, and cost-effectiveness, making them an attractive choice for the growing EV market. Despite all these features and compared to other electrical machines, SRMs suffer from some restrictions, such as torque ripple and audible noise generation, stemming from their markedly nonlinear characteristics, which affect their productivity and efficiency. Therefore, to address these problems, especially the torque ripple, it is crucial and challenging to enhance the performance of the SRM drive system. This paper proposed a comprehensive review of torque ripple minimization strategies of SRMs in EV applications. It covered a detailed overview and categorized and compared many strategies, including two general categories of torque ripple mitigation encompassing optimization design topologies and control strategy developments. Then, focused on control strategy improvements and divided them into torque and current control strategies, including the sub-sections. In addition, the research also provided an overview of SRM fundamental operations, converter topologies, and excitation angle approaches. Last, a comparison between each method in torque control and current control strategies was listed, including the adopted method, features, and drawbacks