Malcolm D. McCulloch

Analysis of the Yokeless And Segmented Armature Machine

This paper presents a new type of axial flux motor, the yokeless and segmented armature (YASA) topology. The YASA motor has no stator yoke, a high fill factor and short end windings which all increase torque density and efficiency of the machine. Thus, the topology is highly suited for high performance applications. The LIFEcar project is aimed at producing the worlds first hydrogen sports car, and the first YASA motors have been developed specifically for the vehicle. The stator segments have been made using powdered iron material which enables the machine to be run up to 300 Hz. The iron in the stator of the YASA motor is dramatically reduced when compared to other axial flux motors, typically by 50%, causing an overall increase in torque density of around 20%. A detailed Finite Element analysis (FEA) analysis of the YASA machine is presented and it is shown that the motor has a peak efficiency of over 95%.

Predicting the Temperature and Flow Distribution in a Direct Oil-Cooled Electrical Machine With Segmented Stator

This paper presents a computationally efficient thermo-fluid model to predict the temperature and flow distribution in an oil-cooled electrical machine with a segmented stator. The Yokeless and Segmented Armature axial flux machine was used as a case study in which a numerical model was set up and validated to within 6% of experimental results. The model was adapted to predict the temperature distribution of the segmented stator of a machine, identifying the hotspot temperatures and their location. Changes to the flow geometry on the stator temperature distribution were investigated. It was shown how by carefully controlling the flow distribution in the stator, the temperature distribution is improved and the hot spot temperature is reduced by 13 K. This benefits the machine by doubling the insulation lifetime or by increasing the current density by approximately 7%.

Sizing of Stand-Alone Solar PV and Storage System With Anaerobic Digestion Biogas Power Plants

This paper presents a deterministic approach for sizing a solar photovoltaic (PV) and energy storage system (ESS) with anaerobic digestion (AD) biogas power plant (BPP) to meet a proportional scaled-down demand of the national load in Kenya, Africa. The aim is to achieve a minimal levelized cost of energy (LCOE) for the system while minimizing the energy imbalance between generation and demand due to AD generator constraint and solar resource. This system also aims to maximize the sizing of PV as to follow the future trend of high penetration of PV. LCOE for the system and a levelized cost of delivery (LCOD) are calculated for the hybrid energy system with the presence of energy storage. Four years of solar data collected from Johannesburg, Africa, are used for system sizing purposes. An in-depth study of the optimization problem has been given and particle swarm optimization with the interior point method is chosen for solar panel sizing. The optimal sizing ratio for the generation sources AD and PV is 2.4:5. The results show that the hybrid system will be cost effective compared to the AD-only system when the discount rate drops below 8% with the current technology costs.

Comparative Experimental Investigation of Broken Bar Fault Detectability in Induction Motors

It has been shown in the past that the zero-sequence current spectrum can be reliably used to detect broken bar faults in induction motors. Previous work was carried out with extensive FEM analysis. Although it allows detailed study of spatial and time-dependent electromagnetic characteristics of induction motors, FEM is a heavily time-consuming tool and this limits full study. So, in this work, extensive experimental testing has been performed to validate the zero sequence current spectrum for detecting rotor asymmetries. Three identical induction motors have been used: one healthy, one with a broken rotor bar, and one with two broken rotor bars. The motors were tested under different voltage supply levels and with different mechanical loads. The zero-sequence current spectrum was calculated after measuring the three phase currents. It is for the first time experimentally shown that this approach offers greater diagnostic potential than traditional MCSA.

Dielectric Characteristics of Electric Vehicle Traction Motor Winding Insulation Under Thermal Aging

The electric motor is the heart of the electric vehicle. It is crucial that any occurring faults are detected promptly so that a catastrophic failure is avoided. At the same time, deep knowledge of the degradation mechanisms is required to allow maximum performance at minimum cost. This paper focuses on this balance. Statistical results from measurements of unaged and accelerated aged winding insulation samples provide information about the degradation processes, enabling steps toward a reliable prognosis model of the motors remaining life.

Comparative experimental investigation of broken bar fault detectability in induction motors

It has been shown in the past that the zero-sequence current spectrum can be reliably used to detect broken bar faults in induction motors. Previous work was carried out with extensive FEM analysis. Although it allows detailed study of spatial and time-dependent electromagnetic characteristics of induction motors, FEM is a heavily time-consuming tool and this limits full study. So, in this work, extensive experimental testing has been performed to validate the zero sequence current spectrum for detecting rotor asymmetries. Three identical induction motors have been used: one healthy, one with a broken rotor bar, and one with two broken rotor bars. The motors were tested under different voltage supply levels and with different mechanical loads. The zero-sequence current spectrum was calculated after measuring the three phase currents. It is for the first time experimentally shown that this approach offers greater diagnostic potential than traditional MCSA.

Meta-Analysis of Greenhouse Gas Emissions from Anaerobic Digestion Processes in Dairy Farms

This meta-analysis quantifies the changes in greenhouse gas (GHG) emissions from dairy farms, caused by anaerobically digesting (AD) cattle manure. As this is a novel quantifiable synthesis of the literature, a database of GHG emissions from dairy farms is created. Each case in the database consists of a baseline (reference with no AD system) and an AD scenario. To enable interstudy comparison, emissions are normalized by calculating relative changes (RCs). The distributions of RCs are reported by specific GHGs and operation units. Nonparametric tests are applied to the RCs in order to identify a statistical difference of AD with respect to baseline scenarios (Wilcoxon rank test), correlations (Spearman test), and best estimation for changes in emissions (Kernel density distribution estimator). From 749 studies identified, 30 papers yield 89 independent cases. The median reductions in emissions from the baseline scenarios, according to operation units, are -43.2% (n.s.) for storage, -6.3% for field application of slurries, -11.0% for offset of energy from fossil fuel, and +0.4% (n.s.) for offset of inorganic fertilizers. The leaks from digesters are found to significantly increase the emissions from baseline scenarios (median = +1.4%).

The Impact of Thermal Degradation on Properties of Electrical Machine Winding Insulation Material

Interturn stator short circuits can develop quickly leading to serious damage of an electric machine. However, degradation mechanisms of winding insulation material are not yet fully understood. Therefore, the main contribution of this paper is the analysis of the impact of thermal ageing on the electrical properties of the thin-film winding insulation. The insulation samples have been aged thermally at 200 °C-275 °C and for 100-1600 h. After ageing, impedance spectroscopy measurements were undertaken on the samples and equivalent-circuit model (ECM) parameters fitted for each measurement. This allows the impact of thermal ageing on ECM parameters to be analyzed, giving insight into the changes in the electrical properties of the insulation. Finally, high voltage was applied to the samples aiming to identify the breakdown-voltage (BV) characteristics of the insulation material.

Experiment, simulation and analysis of linear direct current motor for control

Rotating permanent-magnet motors are now in common use in industry. These machines have a good dynamic performance, especially used for position control. In this paper, the authors consider a new design of a linear direct current motor (LDM), which uses permanent magnets in the rotor. This paper seeks to confirm that this motor achieves similar performance characteristics compared to its rotating counterpart. Two different types of control methods are used to investigate the performance of the motor, namely constant damping force control and position and velocity feedback control. A comparison is made between a three phase version and a six phase version. The boundary element method (BEM) is used to develop and solve for the fields of the LDM. This information is used to model the LDM, which is then used to simulate the control performance of the motor. The simulation results are compared to measured results.

Optimal Design Method for Large-Scale YASA Machines

The objective of this paper is to develop an analytical optimal design tool to determine a megawatt-scale yokelss and segmented armature (YASA) machine design that fulfills the application requirements and constraints. This analytical tool considers both electromagnetic and structural designs. Different designs that provide similar performance will have emerged from this analytical process. A design reference map that graphically shows the relationships and tradeoffs between each objective function is introduced. A multicriteria optimization process is applied to determine a design optimum. In the optimization process, the design objectives considered in this study are to minimize the outer diameter, to minimize the structural mass of the machine, to minimize the copper and iron losses, and to minimize the active materials cost. Three variables considered in calculating the objective functions are the air-gap flux density, the ratio of outer-to-inner machine diameter, and the current loading. The optimization method uses a pseudoweight vector to provide the flexibility to prioritize one or more objective functions, dependant on the specific application requirements.