New design of switched reluctance motor using finite element analysis for hybrid electric vehicle applications

Switched reluctance motors (SRMs) have been gaining increasing popularity and emerging as an attractive alternative to traditional electrical motors in hybrid vehicle applications due to their simple structure, ruggedness, ability of fault-tolerance, extremely high-speed operation, high power density, and low manufacturing cost. However, large torque ripple and acoustic noise are well-known as their major disadvantages. This thesis presents a novel five-phase 15/12 SRM which features higher power density, very low level of vibration with flexibility in controlling the torque ripple profile. This design is classified as an axial field SRM, hence it needs 3-dimensional finite-element analysis model. Nonetheless, an alternative 2-dimensional model is developed and simulated using FEA software (MagNet) in order to analyze the proposed model. The findings from the simulation is scrutinized and analyzed to realize various design features along with performance of the model. The finding in reference to the proposed axial field model is then compared with existing radial field models to validate its performance improvement. The manufacturing issues were addressed to prove its feasibility and cost effectiveness in conjunction with its assembly competences. Taking all the aspects into account superiority of new model\u27s efficiency is comprehended to justify its application in HEV application

SRM drives for electric traction

"GAECE" -- PortadaDescripció del recurs: 11 maig 2020GAECE (Grup d’accionaments elèctrics amb commutació electrònica). The group of electronically commutated electrical drives is a research team of Universitat Politècnica de Catalunya (UPC BARCELONATECH), which conducts investigation in four areas: electrical drives, power electronics, mechanics and energy and sustainability. Regarding electrical drives, research focuses on the development of new reluctance, permanent magnet and hybrid electrical drives. The main goal of those electrical drives is the integration of the power converter/controller and the mechanical transmission, being specially intended for the traction of light electric vehicles. That research is carried out by using the analysis of finite elements, taking into account eco-design criteria, considering new materials and new control strategies.First editio

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

Outer Rotor SRM Design for Electric Vehicle without Reducer via Speed-Up Evolutionary Algorithm

Reducers utilized in automotive industry provide motor to run in most effective region and transmission output torque to increase. However, they cause mass and cost to increase and also efficiency to decrease due to mechanical losses. The aim of this study is to design a direct drive motor (outer rotor switched reluctance motor (OR-SRM)) without reducer resulting in enhanced efficiency for electric vehicle (EV). To estimate dimension and electrical parameters of OR-SRM, mathematical equations are originally derived from its geometry. Considering the constraints of package size and outer diameter, all the dimension parameters of the motor are optimized via multi-objective genetic algorithm (MOGA) to get the desired efficiency and torque. In order to validate the results in the proposed approach, OR-SRM is modeled by Maxwell 3D using optimized dimension parameters. In-wheel OR-SRM with 18/12 poles (30 kW) is manufactured to employ it in an EV. Theoretical results are compared to experimental results. It can be concluded that the results are satisfactory

Design of Outrunner Electric 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

Design of Outrunner Electric 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

Flux switching machine design for high-speed geared drives

Electrical machines capable of high-speed operation are key technology used in many modern applications, such as gas turbine electrical systems, high-speed fly-wheels, turbochargers, and computer numerical control (CNC) machines. The use of geared high-speed machines to replace low-speed high torque drives has not been adequately researched to-date. The rationale of this thesis is to investigate a candidate high speed machine, namely flux switching machines to be used together with new types of core material with mechanical gearing to deliver high-torque and low speeds. Modern developments in advanced material technology have produced new magnetic materials capable of dealing with high resulting in very low losses in high speed machines. However, such metals typically have low mechanical strength, and they are found to be brittle. In order to manufacture electromechanical device with such new materials, it has to be reinforced with a mechanically strong structure. The use of multiple types of magnetic materials referred as a MMLC has been proposed in this thesis for high-speed machine design. In this research, a generic method using magnetic equivalent circuit to model flux switching machines (FSMs) is investigated. Moreover modeling, based on machine dimensions for multiphase FSMs having any pole and slot number has been introduced. The air-gap permeance modeling to simplify the magnetic circuit calculation of FSMs was also investigated in this thesis. It is shown that the permeability of magnetic material can be adjusted with the use of MMLC material. Using this feature, the FSM mathematical model is used to show the impact on electromagnetic performance using MMLCs and is shown to be beneficial. In order the evaluate the weight benefits of using geared high speed FSMs, the planetary gear systems are studies and their design constraints have been identified. An abstract form of weight estimation for given torque and speed requirements has been developed and validated using commercially available planetary gear specifications. FSMs together with gear boxes have been considered and it is shown that significant weight savings can be achieved at higher diameter and at high speeds

Two-axis torque control of BLDC motors for electric vehicle applications.

M. Sc. Eng. University of KwaZulu-Natal, Durban 2014.This thesis begins with a literature review focusing on electric vehicle (EV) applications. Systems used for steering, braking and energy storage are investigated, with specific concentration on torque control in various DC and AC motors commonly used in EVs. A final solution for a low range personal transportation EV in the form of a wheelchair is proposed. The theme for this thesis is motion control, focusing on a two axis (or two wheel drive) brushless DC hub motor (BLDCHM) EV, with torque and direction control tracking a user reference. The operation principle for a BLDCHM is documented and the dynamic and electrical equations derived. Simulation results for motor response under different load and speed conditions are compared to practical measurements. Current and torque control loops are designed, implemented and tuned on a single-axis test-bed with an induction motor (IM) load coupled via a torque transducer. A Texas Instrument DSP development kit is used for the control algorithm bench testing. The final control algorithm is then duplicated and expanded in simulation to form a dynamic two axis system for an electric wheelchair. It incorporates both motor drive and regenerative capabilities. After demonstrating two axis controls for BLDCHMs, a control algorithm is designed simulated and compared to traditional systems. The final solution focuses specifically on an intuitive response to the driver input whilst maintaining direction tracking, even when there is a difference in smoothness of the individual terrains traversed by the left and right wheels. In addition the motor drives are equipped with controllers that ensure regenerative braking in order to recover as much energy as possible when the wheelchair is commanded to decelerate

Optimal Design of Modular High Performance Brushless Wound Rotor Synchronous Machine for embedded systems

This thesis is dedicated to the design and the optimization of modular brushless wound rotor synchronous machine for embedded systems. This machine is constructed based on POKIPOKITM structure with integrated drive electronics. Finite element analysis based optimization becomes more popular in the field of electrical machine design because analytical equations are not easily formalized for the machines which have complicate structures. Using electromagnetic analysis to comparatively study different modular brushless wound rotor synchronous machines and therefore, to select the structure which offers the best fault tolerant capability and the highest output performances. Firstly, the fundamental winding factor calculated by using the method based on voltage phasors is considered as a significant criterion in order to select the numbers of phases, stator slots and poles. After that, 2D finite element numerical simulations are carried out for a set of 15 machines to analyze their performances. The simulation results are then compared to find an appropriate machine according to torque density, torque ripple and machine efficiency. The 7phase/7-slot/6-pole machine is chosen and compared with a reference design surfacemounted permanent magnet synchronous machine in order to evaluate the interesting performance features of the wound rotor synchronous machine. In the second design stage, this machine is optimized by using derivative-free optimization. The objective is to minimize external volume under electromagnetic, thermal and mechanical constraints. Given that an accurate finite element analysis for machine performance takes a long time. Moreover, considering that the average torque can be obtained by simulating the model with only four rotor positions instead of one electric period, optimization strategy is proposed to reduce computational time and therefore, obtain a fast convergence ability by defining relaxed problems which enable minimizing the external volume of the machine under only several constraints such as average torque, torque ripple and copper losses. By testing relaxed problems, two different optimization methods (NOMAD and fmincon) are compared in order to select an appropriate method for our optimization problem. Using NOMAD method based on Mesh Adaptive Direct Search, we achieve optimal results which satisfy all of the constraints proposed. In the third design stage, all constraints are validated by 3D electromagnetic and thermal simulations using finite element and computational fluid dynamics methods. The 3D results show that the average torque obtained is lower than the desired value. By increasing the length of the machine, a new corrected machine is thus obtained. It can be observed that the iron losses obtained in 3D are higher than that in 2D due to the leakage flux in the end-winding. Then, the machine temperature is analyzed by using ANSYS Fluent. Note that the surface temperature is higher than that calculated in the optimization and the coil temperature is 8.48°C higher than the desired value (105°C). However, some dissipation by the shaft and the bearings of the machine are expected to reduce the machine temperature. Finally, a machine prototype is built and some experimental tests are carried out. The results show that the electromotive force has a similar waveform compared to 3D prediction and the difference of the measured and predicted maximum static torques is small

Sliding Mode Control

The main objective of this monograph is to present a broad range of well worked out, recent application studies as well as theoretical contributions in the field of sliding mode control system analysis and design. The contributions presented here include new theoretical developments as well as successful applications of variable structure controllers primarily in the field of power electronics, electric drives and motion steering systems. They enrich the current state of the art, and motivate and encourage new ideas and solutions in the sliding mode control area