Design optimization of modern machine drive systems for maximum fault tolerant and optimal operation

Modern electric machine drives, particularly three phase permanent magnet machine drive systems represent an indispensable part of high power density products. Such products include; hybrid electric vehicles, large propulsion systems, and automation products. Reliability and cost of these products are directly related to the reliability and cost of these systems. The compatibility of the electric machine and its drive system for optimal cost and operation has been a large challenge in industrial applications. The main objective of this dissertation is to find a design and control scheme for the best compromise between the reliability and optimality of the electric machine-drive system. The effort presented here is motivated by the need to find new techniques to connect the design and control of electric machines and drive systems. ^ A highly accurate and computationally efficient modeling process was developed to monitor the magnetic, thermal, and electrical aspects of the electric machine in its operational environments. The modeling process was also utilized in the design process in form finite element based optimization process. It was also used in hardware in the loop finite element based optimization process. The modeling process was later employed in the design of a very accurate and highly efficient physics-based customized observers that are required for the fault diagnosis as well the sensorless rotor position estimation. Two test setups with different ratings and topologies were numerically and experimentally tested to verify the effectiveness of the proposed techniques. ^ The modeling process was also employed in the real-time demagnetization control of the machine. Various real-time scenarios were successfully verified. It was shown that this process gives the potential to optimally redefine the assumptions in sizing the permanent magnets of the machine and DC bus voltage of the drive for the worst operating conditions. ^ The mathematical development and stability criteria of the physics-based modeling of the machine, design optimization, and the physics-based fault diagnosis and the physics-based sensorless technique are described in detail. ^ To investigate the performance of the developed design test-bed, software and hardware setups were constructed first. Several topologies of the permanent magnet machine were optimized inside the optimization test-bed. To investigate the performance of the developed sensorless control, a test-bed including a 0.25 (kW) surface mounted permanent magnet synchronous machine example was created. The verification of the proposed technique in a range from medium to very low speed, effectively show the intelligent design capability of the proposed system. Additionally, to investigate the performance of the developed fault diagnosis system, a test-bed including a 0.8 (kW) surface mounted permanent magnet synchronous machine example with trapezoidal back electromotive force was created. The results verify the use of the proposed technique under dynamic eccentricity, DC bus voltage variations, and harmonic loading condition make the system an ideal case for propulsion systems.^

Development of physics-based models and design optimization of power electronic conversion systems

The main objective for physics based modeling of the power converter components is to design the whole converter with respect to physical and operational constraints. Therefore, all the elements and components of the energy conversion system are modeled numerically and combined together to achieve the whole system behavioral model. Previously proposed high frequency (HF) models of power converters are based on circuit models that are only related to the parasitic inner parameters of the power devices and the connections between the components. This dissertation aims to obtain appropriate physics-based models for power conversion systems, which not only can represent the steady state behavior of the components, but also can predict their high frequency characteristics. The developed physics-based model would represent the physical device with a high level of accuracy in predicting its operating condition. The proposed physics-based model enables us to accurately develop components such as; effective EMI filters, switching algorithms and circuit topologies [7]. One of the applications of the developed modeling technique is design of new sets of topologies for high-frequency, high efficiency converters for variable speed drives. The main advantage of the modeling method, presented in this dissertation, is the practical design of an inverter for high power applications with the ability to overcome the blocking voltage limitations of available power semiconductor devices. Another advantage is selection of the best matching topology with inherent reduction of switching losses which can be utilized to improve the overall efficiency. The physics-based modeling approach, in this dissertation, makes it possible to design any power electronic conversion system to meet electromagnetic standards and design constraints. This includes physical characteristics such as; decreasing the size and weight of the package, optimized interactions with the neighboring components and higher power density. In addition, the electromagnetic behaviors and signatures can be evaluated including the study of conducted and radiated EMI interactions in addition to the design of attenuation measures and enclosures.

Nonholonomically Constrained Dynamics and Optimization of Rolling Isolation Systems

Rolling Isolation Systems provide a simple and effective means for protecting components from horizontal floor vibrations. In these systems a platform rolls on four steel balls which, in turn, rest within shallow bowls. The trajectories of the balls is uniquely determined by the horizontal and rotational velocity components of the rolling platform, and thus provides nonholonomic constraints. In general, the bowls are not parabolic, so the potential energy function of this system is not quadratic. This thesis presents the application of Gauss's Principle of Least Constraint to the modeling of rolling isolation platforms. The equations of motion are described in terms of a redundant set of constrained coordinates. Coordinate accelerations are uniquely determined at any point in time via Gauss's Principle by solving a linearly constrained quadratic minimization. In the absence of any modeled damping, the equations of motion conserve energy. This mathematical model is then used to find the bowl profile that minimizes response acceleration subject to displacement constraint.

Energy efficiency optimization in hardware-constrained large-scale MIMO systems

Large-scale multiple-input multiple-output (MIMO) communication systems can bring substantial improvement in spectral efficiency and/or energy efficiency, due to the excessive degrees-of-freedom and huge array gain. However, large-scale MIMO is expected to deploy lower-cost radio frequency (RF) components, which are particularly prone to hardware impairments. Unfortunately, compensation schemes are not able to remove the impact of hardware impairments completely, such that a certain amount of residual impairments always exists. In this paper, we investigate the impact of residual transmit RF impairments (RTRI) on the spectral and energy efficiency of training-based point-to-point large-scale MIMO systems, and seek to determine the optimal training length and number of antennas which maximize the energy efficiency. We derive deterministic equivalents of the signal-to-noise-and-interference ratio (SINR) with zero-forcing (ZF) receivers, as well as the corresponding spectral and energy efficiency, which are shown to be accurate even for small number of antennas. Through an iterative sequential optimization, we find that the optimal training length of systems with RTRI can be smaller compared to ideal hardware systems in the moderate SNR regime, while larger in the high SNR regime. Moreover, it is observed that RTRI can significantly decrease the optimal number of transmit and receive antennas.

Optimization of wastepaper sludge ash (WSA) in robust cementitious systems

Abstract : Wastepaper sludge ash (WSA) is generated by a cogeneration station by burning wastepaper sludge. It mainly consists of amorphous aluminosilicate phase, anhydrite, gehlenite, calcite, lime, C2S, C3A, quartz, anorthite, traces of mayenite. Because of its free lime content (~10%), WSA suspension has a high pH (13). Previous researchers have found that the WSA composition has poor robustness and the variations lead to some unsoundness for Portland cement (PC) blended WSA concrete. This thesis focused on the use of WSA in different types of concrete mixes to avoid the deleterious effect of the expansion due to the WSA hydration. As a result, WSA were used in making alkali-activated materials (AAMs) as a precursor source and as a potential activator in consideration of its amorphous content and the high alkaline nature. Moreover, the autogenous shrinkage behavior of PC concrete at low w/b ratio was used in order to compensate the expansion effect due to WSA. The concrete properties as well as the volume change were investigated for the modified WSA blended concrete. The reaction mechanism and microstructure of newly formed binder were evaluated by X-ray diffraction (XRD), calorimetry, thermogravimetric analysis (TGA), scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX). When WSA was used as precursor, the results showed incompatible reaction between WSA and alkaline solution. The mixtures were not workable and provided very low compressive strength no matter what kinds of chemical activators were used. This was due to the metallic aluminum in WSA, which releases abundant hydrogen gas when WSA reacts with strong alkaline solution. Besides, the results of this thesis showed that WSA can activate the glassy phase contained in slag, glass powder (GP) and class F fly ash (FFA) with an optimum blended ratio of 50:50. The WSA/slag (mass ratio of 50:50) mortar (w/b of 0.47) attained 46 MPa at 28 days without heat curing assistance. A significant fast setting was noticed for the WSA-activated binder due to the C3A phase, free lime and metallic aluminum contained in the WSA. Adding 5% of gypsum can delay the fast setting, but this greatly increased the potential risk of intern sulfate attack. The XRD, TGA and calorimetry analyses demonstrated the formation of ettringite, C-S-H, portlandite, hydrogarnet and calcium carboaluminate in the hydrated binder. The mechanical performance of different binder was closely related to the microstructure of corresponding binder which was proved by the SEM observation. The hydrated WSA/slag and WSA/FFA binder formed a C-A-S-H type of gel with lower Ca/Si ratio (0.47~1.6). A hybrid gel (i.e. C-N-A-S-H) was observed for the WSA/GP binder with a very low Ca/Si ratio (0.26) and Na/Si ratio (0.03). The SEM/EDX analyses displayed the formation of expansive gel (ettringite and thaumasite) in the gypsum added WSA/slag concrete. The gradual emission of hydrogen gas due to the reaction of WSA with alkaline environment significantly increased the porosity and degraded the microstructure of hydrated matrix after the setting. In the last phase of this research WSA-PC blended binder was tailored to form a high autogenous shrinkage concrete in order to compensate the initial expansion. Different binders were proportioned with PC, WSA, silica fume or slag. The microstructure and mechanical properties of concrete can be improved by decreasing w/b ratios and by incorporating silica fume or slag. The 28-day compressive strength of WSA-blended concrete was above 22 MPa and reached 45 MPa when silica fume was added. The PC concrete incorporating silica fume or slag tended to develop higher autogenous shrinkage at low w/b ratios, and thus the ternary binder with the addition of WSA inhibited the long term shrinkage due to the initial expansion property to WSA. In the restrained shrinkage test, the concrete ring incorporating the ternary binder (PC/WSA/slag) revealed negligible potential to cracking up to 96 days as a result of the offset effect by WSA expansion. The WSA blended regular concrete could be produced for potential applications with reduced expansion, good mechanical property and lower permeability.

Multi-physics modelling for design optimization and manufacturing on high-performance parallel systems

Abstract not available

'The application of Bayesian Optimization and Classifier Systems in Nurse Scheduling'

Abstract. Two ideas taken from Bayesian optimization and classifier systems are presented for personnel scheduling based on choosing a suitable scheduling rule from a set for each person's assignment. Unlike our previous work of using genetic algorithms whose learning is implicit, the learning in both approaches is explicit, i.e. we are able to identify building blocks directly. To achieve this target, the Bayesian optimization algorithm builds a Bayesian network of the joint probability distribution of the rules used to construct solutions, while the adapted classifier system assigns each rule a strength value that is constantly updated according to its usefulness in the current situation. Computational results from 52 real data instances of nurse scheduling demonstrate the success of both approaches. It is also suggested that the learning mechanism in the proposed approaches might be suitable for other scheduling problems.

Optimization of aeroponic technology for future integration in quality potato seed production systems in tropical environments

Virus and soil borne pathogens negatively impact on the production of potatoes in tropical highland and sub-tropical environments, limiting supply of an increasingly popular and important vegetable in these regions. It is common for latent disease infected seed tubers or field grown cuttings to be used as potato planting material. We utilised an International Potato Centre technique, using aeroponic technology, to produce low cost mini-tubers in tropical areas. The system has been optimised for increased effectiveness in tropical areas. High numbers of seed tubers of cultivar Sebago (630) and Nicola per m2 (>900) were obtained in the first generation, and the system is capable of producing five crops of standard cultivars in every two years. Initial results indicate that quality seed could be produced by nurseries and farmers, therefore contributing to the minimisation of soil borne diseases in an integrated management plan. This technology reduces seed production costs, benefiting seed and potato growers. © ISHS.

'The application of Bayesian Optimization and Classifier Systems in Nurse Scheduling'

Abstract. Two ideas taken from Bayesian optimization and classifier systems are presented for personnel scheduling based on choosing a suitable scheduling rule from a set for each person's assignment. Unlike our previous work of using genetic algorithms whose learning is implicit, the learning in both approaches is explicit, i.e. we are able to identify building blocks directly. To achieve this target, the Bayesian optimization algorithm builds a Bayesian network of the joint probability distribution of the rules used to construct solutions, while the adapted classifier system assigns each rule a strength value that is constantly updated according to its usefulness in the current situation. Computational results from 52 real data instances of nurse scheduling demonstrate the success of both approaches. It is also suggested that the learning mechanism in the proposed approaches might be suitable for other scheduling problems.

Design Optimization of Modern Machine-drive Systems for Maximum Fault Tolerant and Optimal Operation

Modern electric machine drives, particularly three phase permanent magnet machine drive systems represent an indispensable part of high power density products. Such products include; hybrid electric vehicles, large propulsion systems, and automation products. Reliability and cost of these products are directly related to the reliability and cost of these systems. The compatibility of the electric machine and its drive system for optimal cost and operation has been a large challenge in industrial applications. The main objective of this dissertation is to find a design and control scheme for the best compromise between the reliability and optimality of the electric machine-drive system. The effort presented here is motivated by the need to find new techniques to connect the design and control of electric machines and drive systems. A highly accurate and computationally efficient modeling process was developed to monitor the magnetic, thermal, and electrical aspects of the electric machine in its operational environments. The modeling process was also utilized in the design process in form finite element based optimization process. It was also used in hardware in the loop finite element based optimization process. The modeling process was later employed in the design of a very accurate and highly efficient physics-based customized observers that are required for the fault diagnosis as well the sensorless rotor position estimation. Two test setups with different ratings and topologies were numerically and experimentally tested to verify the effectiveness of the proposed techniques. The modeling process was also employed in the real-time demagnetization control of the machine. Various real-time scenarios were successfully verified. It was shown that this process gives the potential to optimally redefine the assumptions in sizing the permanent magnets of the machine and DC bus voltage of the drive for the worst operating conditions. The mathematical development and stability criteria of the physics-based modeling of the machine, design optimization, and the physics-based fault diagnosis and the physics-based sensorless technique are described in detail. To investigate the performance of the developed design test-bed, software and hardware setups were constructed first. Several topologies of the permanent magnet machine were optimized inside the optimization test-bed. To investigate the performance of the developed sensorless control, a test-bed including a 0.25 (kW) surface mounted permanent magnet synchronous machine example was created. The verification of the proposed technique in a range from medium to very low speed, effectively show the intelligent design capability of the proposed system. Additionally, to investigate the performance of the developed fault diagnosis system, a test-bed including a 0.8 (kW) surface mounted permanent magnet synchronous machine example with trapezoidal back electromotive force was created. The results verify the use of the proposed technique under dynamic eccentricity, DC bus voltage variations, and harmonic loading condition make the system an ideal case for propulsion systems.

Development of Physics-based Models and Design Optimization of Power Electronic Conversion Systems

The main objective for physics based modeling of the power converter components is to design the whole converter with respect to physical and operational constraints. Therefore, all the elements and components of the energy conversion system are modeled numerically and combined together to achieve the whole system behavioral model. Previously proposed high frequency (HF) models of power converters are based on circuit models that are only related to the parasitic inner parameters of the power devices and the connections between the components. This dissertation aims to obtain appropriate physics-based models for power conversion systems, which not only can represent the steady state behavior of the components, but also can predict their high frequency characteristics. The developed physics-based model would represent the physical device with a high level of accuracy in predicting its operating condition. The proposed physics-based model enables us to accurately develop components such as; effective EMI filters, switching algorithms and circuit topologies [7]. One of the applications of the developed modeling technique is design of new sets of topologies for high-frequency, high efficiency converters for variable speed drives. The main advantage of the modeling method, presented in this dissertation, is the practical design of an inverter for high power applications with the ability to overcome the blocking voltage limitations of available power semiconductor devices. Another advantage is selection of the best matching topology with inherent reduction of switching losses which can be utilized to improve the overall efficiency. The physics-based modeling approach, in this dissertation, makes it possible to design any power electronic conversion system to meet electromagnetic standards and design constraints. This includes physical characteristics such as; decreasing the size and weight of the package, optimized interactions with the neighboring components and higher power density. In addition, the electromagnetic behaviors and signatures can be evaluated including the study of conducted and radiated EMI interactions in addition to the design of attenuation measures and enclosures.

Development, Evaluation and Optimization of Fabrication Processes for Daylight Guiding Systems Based on Micromirror Arrays

In this work, fabrication processes for daylight guiding systems based on micromirror arrays are developed, evaluated and optimized.Two different approaches are used: At first, nanoimprint lithography is used to fabricate large area micromirrors by means of Substrate Conformal Imprint Lithography (SCIL).Secondly,a new lithography technique is developed using a novel bi-layered photomask to fabricate large area micromirror arrays. The experimental results showing a reproducible stable process, high yield, and is consuming less material, time, cost and effort.

Bidding and Optimization Strategies for Wind-PV Systems in Electricity Markets

The variability in non-dispatchable power generation raises important challenges to the integration of renewable energy sources into the electricity power grid. This paper provides the coordinated trading of wind and photovoltaic energy to mitigate risks due to the wind and solar power variability, electricity prices, and financial penalties arising out the generation shortfall and surplus. The problem of wind-photovoltaic coordinated trading is formulated as a linear programming problem. The goal is to obtain the optimal bidding strategy that maximizes the total profit. The wind-photovoltaic coordinated operation is modeled and compared with the uncoordinated operation. A comparison of the models and relevant conclusions are drawn from an illustrative case study of the Iberian day-ahead electricity market.

Bidding and Optimization Strategies for Wind-PV Systems in Electricity Markets Assisted by CPS

The variability in non-dispatchable power generation raises important challenges to the integration of renewable energy sources into the electricity power grid. This paper provides the coordinated trading of wind and photovoltaic energy assisted by a cyber-physical system for supporting management decisions to mitigate risks due to the wind and solar power variability, electricity prices, and financial penalties arising out the generation shortfall and surplus. The problem of wind-photovoltaic coordinated trading is formulated as a stochastic linear programming problem. The goal is to obtain the optimal bidding strategy that maximizes the total profit. The wind-photovoltaic coordinated operation is modelled and compared with the uncoordinated operation. A comparison of the models and relevant conclusions are drawn from an illustrative case study of the Iberian day-ahead electricity market.

Optimization and development of low environmental impact propulsion systems

The aim of the Ph.D. research project was to explore Dual Fuel combustion and hybridization. Natural gas-diesel Dual Fuel combustion was experimentally investigated on a 4-Stroke, 2.8 L, turbocharged, light-duty Diesel engine, considering four operating points in the range between low to medium-high loads at 3000 rpm. Then, a numerical analysis was carried out using a customized version of the KIVA-3V code, in order to optimize the diesel injection strategy of the highest investigated load. A second KIVA-3V model was used to analyse the interchangeability between natural gas and biogas on an intermediate operating point. Since natural gas-diesel Dual Fuel combustion suffers from poor combustion efficiency at low loads, the effects of hydrogen enriched natural gas on Dual Fuel combustion were investigated using a validated Ansys Forte model, followed by an optimization of the diesel injection strategy and a sensitivity analysis to the swirl ratio, on the lowest investigated load. Since one of the main issues of Low Temperature Combustion engines is the low power density, 2-Stroke engines, thanks to the double frequency compared to 4-Stroke engines, may be more suitable to operate in Dual Fuel mode. Therefore, the application of gasoline-diesel Dual Fuel combustion to a modern 2-Stroke Diesel engine was analysed, starting from the investigation of gasoline injection and mixture formation. As far as hybridization is concerned, a MATLAB-Simulink model was built to compare a conventional (combustion) and a parallel-hybrid powertrain applied to a Formula SAE race car.