Overview of Sensitivity Analysis Methods Capabilities for Traction AC Machines in Electrified Vehicles

© 2021 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.A robust design in electrified powertrains substantially helps to enhance the vehicle's overall efficiency. Robustness analyses come with complexity and computational costs at the vehicle level. The use of sensitivity analysis (SA) methods in the design phase has gained popularity in recent years to improve the performance of road vehicles while optimizing the resources, reducing the costs, and shortening the development time. Designers have started to utilize the SA methods to explore: i) how the component and vehicle level design options affect the main outputs i.e. energy efficiency and energy consumption; ii) observing sub-dependent parameters, which might be influenced by the variation of the targeted controllable (i.e. magnet thickness) and uncontrollable (i.e. magnet temperature) variables, in nonlinear dynamic systems; and iii) evaluating the interactions, of both dependent, and sub-dependent controllable/uncontrollable variables, under transient conditions. Hence the aim of this study is to succinctly review recent utilization of SA methods in the design of AC electric machines (EM)s used in vehicle powertrains, to evaluate and discuss the findings presented in recent research papers while summarizing the current state of knowledge. By systematically reviewing the literature on applied SAs in electrified powertrains, we offer a bibliometric analysis of the trends of application-oriented SA studies in the last and next decades. Finally, a numerical-based case study on a third-generation TOYOTA Prius EM will be given, to verify the SA-related findings of this article, alongside future works recommendations.Peer reviewe

Modelling and Control of Switched Reluctance Machines

Today, switched reluctance machines (SRMs) play an increasingly important role in various sectors due to advantages such as robustness, simplicity of construction, low cost, insensitivity to high temperatures, and high fault tolerance. They are frequently used in fields such as aeronautics, electric and hybrid vehicles, and wind power generation. This book is a comprehensive resource on the design, modeling, and control of SRMs with methods that demonstrate their good performance as motors and generators

Modelling and Control of Switched Reluctance Machines

Today, switched reluctance machines (SRMs) play an increasingly important role in various sectors due to advantages such as robustness, simplicity of construction, low cost, insensitivity to high temperatures, and high fault tolerance. They are frequently used in fields such as aeronautics, electric and hybrid vehicles, and wind power generation. This book is a comprehensive resource on the design, modeling, and control of SRMs with methods that demonstrate their good performance as motors and generators

Core loss estimation under sinusoidal and non-sinusoidal flux density waveforms overview and challenges

Nowadays, electrical machines design and control developments are much attached to simulation models. Accurate loss estimation methods are fundamental for improving efficiency, but also to achieve the desired operation conditions [1].N/

Position estimation and performance prediction for permanent-magnet motor drives

PhD ThesisThis thesis presents a theoretical and experimental development of a novel position estimator, a simulation model, and an analytical solution for brushless PM motor drive. The operation of the drive, the position estimation model of the test motor, development of hardware, and basic operation of inverter are discussed. Starting with the well-known continuous-time model of brushless PM motor, a sampled-data model is developed that is suitable for th6, application of real-time position estimator. An analytical methodo f calculating the steady-stateb ehaviouro f the brushlessP M motor for 1200in verter operation is presentedT. he analysisa ssumesth at the machinea ir gap is free of saliency effects, and has sinusoidal back EMF. The analytical solution is derived for 60" electrical of the whole period. By experimental results, it is shown that the method of analysis is adequate to predict Ihe motor's performance for typical operating points including phase advance and phase delay operation. C) I A computer simulation model for prediction of the performance of brushless PM moto rs is presented. The model is formulated entirely in the natural abc frame of reference, which allows direct comparison of the simulation and corresponding experimental results. The equations and diagrams are put into a convenient form for the simulation and future developments and library modules. The simulation model and corresponding experimental data of the brushless PM motor drive is given. The thesis describes a modem solution to real-time rotor position estimation, which has been subject to intense research activity for the last 15 years. The implemented new algorithm for shaft position sensorless operation of PM motors is based on the flux linkage and line current estimation. The position estimation algorithm has also been verified by both off-line and on-line experiments (accomplished by a DSP, TMS320C30), and a wide range of steady-statea nd transient results have been 0gi0v en including starting from rest. The position estimation method effectively moves the position measurement point in the drive from the mechanical side to the motor's terminals. As well as eliminating the mechanical shaft position sensor, the investigated method can be used for high performance torque control of brushless PM motors. The thesis demonstrates that, in contrast to many other "sensorless" schemes, the new position estimation method is able to work effectively over the full operating range of the drive, and is applicable to a wide range of motor/converter types. Since the hardware is straightforward, only the new position estimation algorithm differentiates a system. Therefore, if a DSP control system is already implemented in the drive, the position estimator can be implemented at low cost.Istanbul Technical University and Higher Education Counci

Design of Outrunner Eectric Machines for Green Energy Applications

Interests in using rare-earth free motors such as switched reluctance motors (SRMs) for electric and hybrid electric vehicles (EV/HEVs) continue to gain popularity, owing to their low cost and robustness. Optimal design of an SRM, to meet specific characteristics for an application, should involve simultaneous optimization of the motor geometry and control in order to achieve the highest performance with the lowest cost. This dissertation firstly presents a constrained multi-objective optimization framework for design and control of a SRM based on a non-dominated sorting genetic algorithm II (NSGA-II). The proposed methodology optimizes SRM operation for high volume traction applications by considering multiple criteria including efficiency, average torque, and torque ripple. Several constraints are defined by the application considered, such as the motor stack length, minimum desired efficiency, etc. The outcome of this optimization includes an optimal geometry, outlining variables such as air gap length, rotor inner diameter, stator pole arc angle, etc as well as optimal turn-on and turn-off firing angles. Then the machine is manufactured according to the obtained optimal specifications. Finite element analysis (FEA) and experimental results are provided to validate the theoretical findings. A solution for exploring optimal firing angles of nonlinear current-controlled SRMs is proposed in order to minimize the torque ripple. Motor torque ripple for a certain electrical load requirement is minimized using a surrogate-based optimization of firing angles by adjusting the motor geometry, reference current, rotor speed and dc bus voltage. Surrogate-based optimization is facilitated via Neural Networks (NN) which are regression tools capable of learning complex multi-variate functions. Flux and torque of the nonlinear SRM is learned as a function of input parameters, and consequently the computation time of design, which is crucial in any micro controller unit, is expedited by replacing the look-up tables of flux and torque with the surrogate NN model. This dissertation then proposes a framework for the design and analysis of a coreless permanent magnet (PM) machine for a 100 kWh shaft-less high strength steel flywheel energy storage system (SHFES). The PM motor/generator is designed to meet the required specs in terms of torque-speed and power-speed characteristics given by the application. The design challenges of a motor/generator for this architecture include: the poor flux paths due to a large scale solid carbon steel rotor and zero-thermal convection of the airgap due to operation of the machine in vacuum. Magnetic flux in this architecture tends to be 3-D rather than constrained due to lack of core in the stator. In order to tackle these challenges, several other parameters such as a proper number of magnets and slots combination, number of turns in each coil, magnets with high saturated flux density and magnets size are carefully considered in the proposed design framework. Magnetic levitation allows the use of a coreless stator that is placed on a supporting structure. The proposed PM motor/generator comprehensive geometry, electromagnetic and mechanical dimensioning are followed by detailed 3-D FEA. The torque, power, and speed determined by the FEA electromagnetic analysis are met by the application design requirements and constraints for both the charging and discharging modes of operation. Finally, the motor/generator static thermal analysis is discussed in order to validate the proposed cooling system functionality

Nonlinear H-infinity control for switched reluctance machines

AbstractThe article proposes a nonlinear H-infinity control method for switched reluctance machines. The dynamic model of the switched reluctance machine undergoes approximate linearization round local operating points which are redefined at each iteration of the control algorithm. These temporary equilibria consist of the last value of the reluctance machine's state vector and of the last value of the control signal that was exerted on it. For the approximate linearization of the reluctance machine's dynamics, Taylor series expansion is performed through the computation of the associated Jacobian matrices. The modelling errors are compensated by the robustness of the control algorithm. Next, for the linearized equivalent model of the reluctance machine an H-infinity feedback controller is designed. This requires the solution of an algebraic Riccati equation at each time-step of the control method. It is shown that the control scheme achieves H-infinity tracking performance, which implies maximum robustness to modelling errors and external perturbations. The stability of the control loop is proven through Lyapunov analysis

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