Genetic algorithm based design optimisation for permanent magnet synchronous motors

This research work presents a new and efficient design methodology for the specification, development and manufacture of permanent magnet synchronous motors (PMSMs). In this paper a genetic algorithm based design optimisation technique for PMSMs is presented in which the multicriteria considered in the optimisation are the electromagnetic performance, the thermal performance and the material cost. Models have been developed for each criterion in order to calculate the objective vector. A software tool called PMSM Analyser was developed to assist the motor design methodology. The optimisation algorithms and the electromagnetic, thermal and cost models were integrated and interfaced using this software. The programme is demonstrated for the design of a 12 slot 10 pole PMSM. The design parameter vector contains stator bore diameter, stator tooth thickness and stator back iron thickness. For the base design the outer diameter of the stator is 180mm and the stack length of the motor is 90mm. The base design refers to the design before optimisation and the optimal design refers to the design with optimised dimensions. The optimisation programme predicts significant improvements over the baseline design and experimental results are presented which indicate good agreement with the predictions of the programme. The new approach has been used successfully in the development and design of a PMSM with a stall torque of 125Nm, rated torque of 75Nm at 1500r/min and output power of 12kW. The strengths of the design methodology are summarised with the genetic algorithm optimisation, innovative multi-objective handling and design models for the various disciplines of PMSM development

High Efficiency and High Speed PM Motors for the More Electric Aircraft

More electric aircraft has been a subject of increasing discussions and research for more than ten years now, both in Europe and in North America. These efforts follow the growing realisation of the benefits that are likely to emerge from the future growth of the more electric aircraft technology. This is evident from the sizes and numbers of research and development programmes currently undertaken on the subject by both aerospace industry and academic institutions. High speed permanent magnet motors, excited by rare-earth magnetic materials, are used extensively in majority of these research programmes. The applications, on more electric aircrafts, often demand motor drives that have very high reliability, energy efficiency and high power density. On of the factors that require significant design consideration is the effect of high speed on the operational performance of the motor. High rotational speed impacts heavily on the rotational losses whilst the high peripheral speed influences the mechanical construction of the rotor. Iron and windage losses can become dominating factors in determining the overall rating and efficiency of the motor. The other important consideration relate to the ability of the motor to generate high torque at low speed, a feature that is very essential in actuation drive systems on the aircraft

Developing lean six sigma framework for use in small and medium enterprises

Previous researches in manufacturing operations concluded that the best opportunities for improvement are achieved when the manufacturing system is designed from the top down and from customer to the supplier. The most effective manufacturing system designs is the one that consider the whole product value stream rather than just shop-floor activities. Although the lean deployment is a critical success factor, yet there is no holistic or a step by step approach to the deployment process. The lack of a framework that provides a systematic practical approach to lean implementation is increasingly becoming an issue for manufacturing organisations and professionals. This paper presents an attempt to develop a framework that can be used to develop a lean manufacturing system in small and medium enterprises (SME). The framework is based on lean six sigma principles of efficiency, speed, reduced waste and high quality

Improved cogging calculation methods for surface mounted permanent magnet synchronous motors

As part of the design process of surface mounted permanent magnet synchronous motors (PMSM), a combination of analytical calculation and finite element analysis (FEA) is proposed for the cogging torque calculation. The analytical methods are recommended for the initial design iterations in view of their high computational speed. In general, however, finite element analysis is more accurate and is therefore recommended for the final design iterations. In order to obtain continuity when switching from analytical calculations to FEA, two modifications are made to the equations upon which the analytical methods are based in order to improve accuracy. This is demonstrated by comparing the results from the unmodified and modified analytical method with those using the finite element method through their application using the nominal parameters of a Control Techniques Dynamics CTD 142UMC300 motor. Air-gap flux density calculations are compared as well as cogging torque calculations

Modelling Mobile Agent Mobility in Virtual Learning Environment (VLE) using Fitness function

This paper reports on a study conducted to ascertain the requirement for developing Virtual Learning Environments (VLEs) and how these needs are met using fitness function for modelling the solution to meet the requirements and demands of such as system. The systems used for this study was University of East London blackboard Learning System called UEL Plus. We realized that UEL Plus has multiple features to support teaching and learning. UEL Plus provides an improved communication, access to resources and advanced assessment capabilities. Our study focused fundamentally on the UEL Plus which part of VLE. The rest of the paper is organized as follows: Section 2 will describe end user categories and section 3 will highlight the mobile agents as a solution. Section 4 will introduce mobile agent fitness function and Section 5 will discusses the mobility in VLE in section 6 draws conclusion

Challenges in the onboard oil condition monitoring

Engine oil is an essential component in modern engines and must fulfil a broad range of duties. The engine oil condition is closely related to the engine performance and to the engine reliability. Different effects during the engine operation cause the formation of contaminants reaching into the oil and degrading the oil condition. Monitoring the oil condition with an onboard sensor could provide information about the current oil status. The available sensor data and their correlation to oil contamination effects is further illustrated and examined. The major challenge to derive a reliable oil condition statement from these data is also discussed in this paper

Vektorski upravljani elektromotorni pogoni s reluktantnim sinkronim motorima uz definiranu dinamiku zatvorenog kruga brzine vrtnje

A new speed control system for electric drives employing reluctance synchronous motors is presented. Design control system combines two control methods. Conventional vector control method is here completed with forced dynamics closed-loop control. Since the closed-loop system response is a first order lag whose pole location can be chosen by the user, the drive may be included as an actuator in a larger scale control scheme to which linear control system design methods can be applied. To improve robustness of the design control structure, the outer control loop based on model reference adaptive control is added. Simulation results presented show good correspondence with theoretical predictions and MRAC outer control loop improves overall drive performances.Prikazana je nova koncepcija sustava upravljanja brzinom vrtnje elektromotornog pogona s reluktantnim sinkronim motorima, temeljena na dvijema metodama upravljanja. Konvencionalna vektorska metoda nadograđena je elementom sustava koji predstavlja dinamiku zatvorenog kruga po brzini vrtnje. Budući da je dinamika zatvorenog sustava prikazana proporcionalnim članom prvog reda, čiji pol odabire korisnik, predložena koncepcija može biti šire primjenjiva. Da bi se poboljšala robusnost sustava, dodana je vanjska petlja upravljanja zasnovana na adaptivnom upravljanju s referentnim modelom. Simulacijski rezultati prikazani u radu potvrđuju valjanost predložene koncepcije

Active Learning to Overcome Sample Selection Bias: Application to Photometric Variable Star Classification

Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because a) standard assumptions for machine-learned model selection procedures break down and b) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting (IW), co-training (CT), and active learning (AL). We argue that AL---where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up---is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and OGLE, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply active learning to classify variable stars in the ASAS survey, finding dramatic improvement in our agreement with the ACVS catalog, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.Comment: 43 pages, 11 figures, submitted to Ap

Precise Dynamical Masses and Orbital Fits for β Pic b and β Pic c

We present a comprehensive orbital analysis to the exoplanets $\beta$ Pictoris b and c that resolves previously reported tensions between the dynamical and evolutionary mass constraints on $\beta$ Pic b. We use the MCMC orbit code orvara to fit fifteen years of radial velocities and relative astrometry (including recent GRAVITY measurements), absolute astrometry from Hipparcos and Gaia, and a single relative radial velocity measurement between $\beta$ Pic A and b. We measure model-independent masses of $9.3^{+2.6}_{-2.5}\, M_{\rm Jup}$ for $\beta$ Pic b and $8.3\pm 1.0\,M_{\rm Jup}$ for $\beta$ Pic c. These masses are robust to modest changes to the input data selection. We find a well-constrained eccentricity of $0.119 \pm 0.008$ for $\beta$ Pic b, and an eccentricity of $0.21^{+0.16}_{-0.09}$ for $\beta$ Pic c, with the two orbital planes aligned to within $\sim$0.5$^\circ$. Both planets' masses are within $\sim$1$\sigma$ of the predictions of hot-start evolutionary models and exclude cold starts. We validate our approach on $N$-body synthetic data integrated using REBOUND. We show that orvara can account for three-body effects in the $\beta$ Pic system down to a level $\sim$5 times smaller than the GRAVITY uncertainties. Systematics in the masses and orbital parameters from orvara's approximate treatment of multiplanet orbits are a factor of $\sim$5 smaller than the uncertainties we derive here. Future GRAVITY observations will improve the constraints on $\beta$ Pic c's mass and (especially) eccentricity, but improved constraints on the mass of $\beta$ Pic b will likely require years of additional RV monitoring and improved precision from future Gaia data releases.Comment: Published in AJ. 16 pages, 10 figures. Fix to mismatch of columns in predicted position

Circumstellar discs: What will be next?

This prospective chapter gives our view on the evolution of the study of circumstellar discs within the next 20 years from both observational and theoretical sides. We first present the expected improvements in our knowledge of protoplanetary discs as for their masses, sizes, chemistry, the presence of planets as well as the evolutionary processes shaping these discs. We then explore the older debris disc stage and explain what will be learnt concerning their birth, the intrinsic links between these discs and planets, the hot dust and the gas detected around main sequence stars as well as discs around white dwarfs.Comment: invited review; comments welcome (32 pages