Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Disruptive innovations in electrical machine design optimization are observed in this paper, motivated by emerging trends. Improvements in mathematics and computer science enable more detailed optimization scenarios that cover evermore aspects of physics. In the past, electrical machine design was equivalent to investigating the electromagnetic performance. Nowadays, thermal, rotor dynamics, power electronics, and control aspects are included. The material and engineering science have introduced new dimensions on the optimization process and impact of manufacturing, and unavoidable tolerances should be considered. Consequently, multifaceted scenarios are analyzed and improvements in numerous fields take effect. This paper is a reference for both academics and practicing engineers regarding recent developments and future trends. It comprises the definition of optimization scenarios regarding geometry specification and goal setting. Moreover, a materials-based perspective and techniques for solving optimization problems are included. Finally, a collection of examples from the literature is presented and two particular scenarios are illustrated in detail.

Modern Electrical Machine Design Optimization: Techniques, Trends, and Best Practices

A permanent-magnet (PM)-assisted synchronous reluctance (PMASR) machine exhibits both high efficiency and high flux-weakening (FW) range. However, the best performance is achieved after a machine design optimization. In industry applications, the design of PMASR machines requires to satisfy an increasing number of limitations. The key points are lamination geometry, material property, and control strategy. This paper analyzes the influence of PM volume (flux level) on the motor performance, although lamination geometry and stack length are kept fixed. Thus, the PM volume inset in the rotor is optimized. The considered PMASR motor is designed for a very high FW speed range. The study is based on a finite-element (FE) analysis. The accuracy of the FE simulations is verified comparing their results with measurements on a prototype. The FE model is then used to study the different cases.

Permanent-Magnet Optimization in Permanent-Magnet-Assisted Synchronous Reluctance Motor for a Wide Constant-Power Speed Range

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Integration Of Alternative Sources Of Energy

Computationally efficient finite-element analysis (FEA) (CE-FEA) fully exploits the symmetries of electric and magnetic circuits of sine-wave current-regulated synchronous machines and yields substantial savings of computational efforts. Motor performance is evaluated through Fourier analysis and a minimum number of magnetostatic solutions. The major steady-state performance indices (average torque, ripple and cogging torque, back-electromotive-force waveforms, and core losses) are satisfactorily estimated as compared with the results of detailed time-stepping (transient) FEA. In this paper, the CE-FEA method is presented and applied to a parametric design study for an interior-permanent-magnet machine. Significant reduction of simulation times is achieved (approximately two orders of magnitude), permitting a comprehensive search of large design spaces for optimization purposes. In this case study, the influence of three design variables, namely, stator tooth width, pole arc, and slot opening, on three performance indices, namely, average torque, efficiency, and full-load torque ripple, is examined, and design trends are derived. One hundred candidate designs are simulated in less than 20 minutes on a state-of-the-art workstation.

Modeling and Parametric Design of Permanent-Magnet AC Machines Using Computationally Efficient Finite-Element Analysis

Synchronous machines that are optimally designed using finite-element (FE) software, and control of such machines using powerful digital signal processors (DSPs), are commonplace today. With field-orientated control, the maximum-torque-per-ampere control strategy for unsaturated voltage conditions (below the base speed) is well known; the field-weakening strategy, however, could be rather complicated. In this paper, a straightforward torque control strategy for the entire speed range is proposed and demonstrated. Practical implementation of the method is very simple since the calculations are done offline in an automated process and are therefore removed from the load of the DSP. The process relies on machine-specific data from FE analysis and therefore includes nonlinear effects such as saturation and cross coupling. Simulation and practical results for a permanent-magnet and a reluctance synchronous machine show that the torque is controlled effectively in the entire speed range using this generic method.

Optimal Torque Control of Synchronous Machines Based on Finite-Element Analysis

Short-term solar power forecasting: Investigating the ability of deep learning models to capture low-level utility-scale Photovoltaic system behaviour

In this paper, the performances of electric vehicle (EV) in-wheel (hub) nonoverlap-winding permanent-magnet motors with different stator and rotor topologies are compared. The calculation of the frequency losses in the design optimization of the hub motors is specifically considered. Also, the effect of the slot and pole number choice that determines the winding factor of the machine is investigated. It is shown that the torque-per-copper-loss performance of the machine cannot be judged solely on the winding factor of the machine. Wide open stator slot machines with rectangular preformed coils and, hence, low manufacturing costs are found to perform better than expected. The design detail and test results of a prototype 10-kW water-cooled EV hub drive are presented. The test results confirm the finite-element-calculated results, specifically in the high-speed region of the drive where the rotor topology affects the constant power speed range.

Radial-Flux Permanent-Magnet Hub Drives: A Comparison Based on Stator and Rotor Topologies

This paper addresses the impact of high penetration of renewable energy sources (RES), in particular wind and solar power generation on the western transmission network of the South African (Eskom) power system. The study focuses on the power system’s stability, specifically the frequency dynamics. With a decline in power system inertia, inertial response emulated by inverter based RES, is considered as a means to restore the system’s inertia. Virtual inertia is seen as a valuable ”resource”, but comes at the cost of active power generation. In addition virtual inertia also provides an additional degree of control, which must be used in an optimal manner to provide maximum system stability at a reasonable cost to power generation. This paper utilizes an optimal virtual inertia placement and allocation method, for the western transmission network considering a trip of the Koeberg nuclear power plant in the Western Cape province. Simulation test results show that the virtual inertia and optimal allocation improves the system stability significantly. This in return gives additional incentive for RES integration.

Optimising Power System Frequency Stability Using Virtual Inertia from Inverter-based Renewable Energy Generation.

Minibus taxi public transport is a seemingly chaotic phenomenon in the developing cities of the Global South with unique mobility and operational characteristics. Eventually this wide-spread fleet of minibus taxis will have to transition to electric vehicles. This paper examines the impact of this inevitable evolution on a city-wide scale in Kampala, Uganda. We present a generic simulation environment to assess the grid impact and charging opportunities, given the unique paratransit mobility patterns. We used floating car data to assess the energy requirements of electric minibus taxis, which will have a knock-on effect on the region’s already fragile electrical grid. We used spatio-temporal and solar photovoltaic analyses to assess the informal and formal stops that would be needed for the taxis to recharge from solar PV in the region’s abundant sunshine. The results showed that the median energy demand across all simulated days of the fleet of taxis was 220 kWh /d. This ranged to a maximum of 491 kWh /d, with a median charging potential (stationary time) across taxis of 8 h /d to 12 h /d. The median potential for charging from solar PV ranged from 0.24 kWh/m2 to 0.52 kWh/m2 per day, across the taxis. Our simulator and results will allow traffic planners and grid operators to assess and plan for looming electric vehicle roll-outs to the most-used mode of transport in Africa. 

https://engrxiv.org/preprint/download/1855/3773

A.J. Rix

Papers

Optimal Torque Control of Synchronous Machines Based on Finite-Element Analysis

Short-term solar power forecasting: Investigating the ability of deep learning models to capture low-level utility-scale Photovoltaic system behaviour

Radial-Flux Permanent-Magnet Hub Drives: A Comparison Based on Stator and Rotor Topologies

Optimising Power System Frequency Stability Using Virtual Inertia from Inverter-based Renewable Energy Generation.

Walking on sunshine: Pairing electric vehicles with solar energy for sustainable informal public transport in Uganda