Field Oriented Sliding Mode Control of Surface-Mounted Permanent Magnet AC Motors: Theory and Applications to Electrified Vehicles

Permanent magnet ac motors have been extensively utilized for adjustable-speed traction motor drives, due to their inherent advantages including higher power density, superior efficiency and reliability, more precise and rapid torque control, larger power factor, longer bearing, and insulation life-time. Without any proportional-and-integral (PI) controllers, this paper introduces novel first- and higher-order field-oriented sliding mode control schemes. Compared with the traditional PI-based vector control techniques, it is shown that the proposed field oriented sliding mode control methods improve the dynamic torque and speed response, and enhance the robustness to parameter variations, modeling uncertainties, and external load perturbations. While both first- and higher-order controllers display excellent performance, computer simulations show that the higher-order field-oriented sliding mode scheme offers better performance by reducing the chattering phenomenon, which is presented in the first-order scheme. The higher-order field-oriented sliding mode controller, based on the hierarchical use of supertwisting algorithm, is then implemented with a Texas Instruments TMS320F28335 DSP hardware platform to prototype the surface-mounted permanent magnet ac motor drive. Last, computer simulation studies demonstrate that the proposed field-oriented sliding mode control approach is able to effectively meet the speed and torque requirements of a heavy-duty electrified vehicle during the EPA urban driving schedule

Automated Design Optimization of Synchronous Machines: Development and Application of a Generic Fitness Evaluation Framework

A rotating synchronous electric machine design can be described to its entirety by a combination of 17 to 24 discrete and continuous parameters pertaining the geometry, material selection, and electrical loading. Determining the performance attributes of a design often involves numerical solutions to thermal and magnetic equations. Stochastic optimization methods have proven effective for solving specific design problems in literature. A major challenge to design automation, however, is whether the design tool is versatile enough to solve design problems with different types of objectives and requirements. This work proposes a black-box approach in an attempt to encompass a wide variety of synchronous machine design problems. This approach attempts to enlist all possible attributes of interest (AoIs) to the end-user so that the design optimization problem can be framed by combination of such attributes only. The number of ways the end-user can input requirements is now defined and limited. Design problems are classified based on which of the AoI’s are constraints, objectives or design parameters. It is observed that regardless of the optimization problem definition, the evaluation of any design is based on a common set of physical and analytical models and empirical data. Problem definitions are derived based on black-box approach and efficient fitness evaluation algorithms are tailored to meet requirements of each problem definition. The proposed framework is implemented in Matlab/C++ environment encompassing different aspects of motor design. The framework is employed for designing synchronous machines for three applications where designs based on conventional motor construction did not meet all design requirements. The first design problem is to develop a novel bar-conductor tooth-wound stator technology for 1.2 kW in-wheel direct drive motor for an electric/hybrid-electric two wheeler (including practical implementation). The second design problem deals with a novel outer-rotor buried ferrite magnet geometry for a 1.2 kW in-wheel geared motor drive used in an electric/hybrid-electric two wheeler (including practical implementation). The third application involves design of an ultra-cost-effective and ultra-light-weight 1 kW aluminum conductor motor. Thus, the efficacy of automated design is demonstrated by harnessing the framework and algorithms for exploring new technologies applicable for three distinct design problems originated from practical applications

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

Predictive Stator Flux and Load Angle Control of Synchronous Reluctance Motor Drives Operating in a Wide Speed Range

This paper presents a new simplified finitecontrol- set model predictive control strategy for synchronous reluctance motors operating in the entire speed range. It is a predictive control scheme that regulates the stator flux and the load angle of the synchronous reluctance motor, incorporating the ability to operate the drive in the field-weakening region and respecting the motor voltage and current limits as well as the load angle limitation needed to operate this type of motor in the maximum torque per voltage region. The proposed control strategy possesses some attractive features, such as no need for controller calibration, no weighting factors in the cost function, good robustness against parameter mismatch, and smaller computational cost compared to more traditional finite-control-set model predictive control algorithms. Simulation and experimental results obtained using a high-efficiency synchronous reluctance motor demonstrate the effectiveness of the proposed control scheme.info:eu-repo/semantics/publishedVersio

Analysis of Implementation Methodologies of Deadbeat Direct-Torque and Flux Control (DB-DTFC) for IPMSMs in Stationary and Rotatory Reference Frames

Deadbeat-control is a well-established control technique that uses the inverse machine model to determine the voltage commands required to achieve the desired torque and flux commands. Its classic implementation requires solving a quadratic equation with an extensive number of terms. Moreover, it can be only solved in the dq-reference frame. In this paper, two novel implementations are presented. The first methodology, in the dq-reference frame, reduces the algorithm's complexity and computation time. Moreover, it is immune to estimation errors of the permanent magnet flux. A second methodology based on the flux vector orientation is also presented. As opposed to the classic implementation, the proposed method does not require solving a quadratic equation; this reduces its complexity and computation time. Furthermore, the proposed methodology can be solved both in the dq and aß frames since it relies only on the stator flux's magnitude and angle. Up to date and to the best of the author's knowledge, DB-DTFC in the stationary frame has not been presented before for salient machines. DB-DTFC in the stationary frame reduces the reliance on the position observer and facilitates the implementation of overmodulation techniques and six-step operation. The proposed methodology can operate in the MTPF line without any adjustments and it shows an adequate dynamic performance. Simulation and experimental results validate the methodologies. Caveats regarding their implementation are also discussed

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

Rapid optimization of interior permanent magnet (IPM) machines using the response surface method and dimensionless parameters

The primary objective for this work is to create a method to rapidly optimize interior permanent magnet (IPM) machines. For this research, a method was created called dimensionless optimization (DO). Eight dimensionless parameters determine nineteen dimensions of the machine based on design rules, stresses in the rotor and back EMF. Given a maximum torque specification and a local design space, a hypercube design of 64 machines is created using an 8 factor I-optimal design. Analysis is performed using a commercial program which incorporates electromagnetic FEA, and provides the current and phase angle requirements, and efficiency of the machines at the defined test points. Response surfaces are created for efficiency and current at each test point. The method determines the variance of the response surfaces, the optimum predicted design in the local design space, and the location of design spaces which may yield better designs. The method was validated by comparing 20 kW and 50 kW machines designed by an electric machines manufacturer, to machines designed using dimensionless optimization. The efficiencies of both machines were improved using dimensionless optimization

Coupled Electromagnetic and Thermal Analysis and Design Optimization of Synchronous Electric Machines

A new technique for coupling the electromagnetic, thermal, and air-flow analysis is proposed for electronically controlled synchronous machines. A computationally efficient finite element analysis (CE-FEA) technique is employed for the electromagnetic field analysis. An equivalent circuit network is used for thermal and air-flow analysis. An iterative algorithm, which exploits the fact that the type of machines studied have very low rotor losses and also a relatively reduced dependency of core losses with temperature and load, has been developed. The overall computational time is significantly reduced in comparison with the conventional coupling method, such that the new technique is highly suitable for large scale optimization studies. An automated design optimization method based on differential evolution algorithms has also been developed and implemented on a multi-core computer system. Example case studies are provided for permanent magnet and for synchronous reluctance machines. Computational and experimental results from prototype motors are included