Abstract-This paper studies a dual-level response surface methodology (DRSM) coupled with Booth's algorithm using a simulated annealing (BA-SA) method as a multiobjective technique for parametric modeling and machine design optimization for the first time. The aim of the research is for power maximization and cost of manufacture minimization resulting in a highly optimized wind generator to improve small power generation performance. The DRSM is employed to determine the best set of design parameters for power maximization in a surface-mounted permanent magnet synchronous generator with an exterior-rotor topology. Additionally, the BA-SA method is investigated to minimize material cost while keeping the volume constant. DRSM by different design functions including mixed resolution robust design, full factorial design, central composite design, and box-behnken design are applied to optimize the power performance resulting in very small errors. An analysis of the variance via multilevel RSM plots is used to check the adequacy of fit in the design region and determines the parameter settings to manufacture a high-quality wind generator. The analytical and numerical calculations have been experimentally verified and have successfully validated the theoretical and multiobjective optimization design methods presented.Index Terms-Dual response surface methodology, Booth's algorithm, synchronous machine, finite element analysis, multiobjective optimization.
This paper utilizes a Pareto-based, three-dimensional (3-D) analysis to identify complete and partial shading of photovoltaic (PV) systems for an complicated urban environment, where unusual shape of PV and installation topology is studied. The Pareto optimization attempts to minimize losses in a certain area with an improved output energy and without compromising the overall efficiency of the system of which, the nominal operating cell temperature (NOCT) for a glass/glass-module is considered as a significant parameter. The system is referenced to the environment based on IEC61215 via a closed-circuit and resistive load to ensure the module operates at the maximum power point. A Maximum Power Point Tracking (MPPT) controller is enhanced with an advanced perturb and observe (P&O) algorithm to maintain the PV operating point at its maximum output under various working conditions. The most cost-effective design of the PV module is achieved via optimizing installation parameters such as tilt angle, pitch, and shading to improve the energy yield. The parameter settings and suitability of the design are also determined based on the reduced amount of CO2 emissions. An experimental investigation has been carried out to verify the 3-D shading analysis and NOCT technique for both open-circuit and grid-connected PV modules.
Abstract--This paper presents a robust sizing design optimisation of a permanent magnet synchronous generator (PMSG) using three-dimensional finite element analysis (3D FEA). In order to build an optimal parametric model structure, the efficiency of the PMSG is taken as the objective function, and a dual-level response surface methodology (D-RSM) with a window-zoom-in approach for a variable speed range analysis as a robust optimisation technique is employed to find out the optimal design variables of the objective function. The D-RSM using mixed-resolution central composite design (MR-CCD), full factorial design (FFD), central composite design (CCD), and box-behnken design (BBD) is applied to optimise the geometry with very small error. Analysis of variance (ANOVA) and multi-level RSM plots in order to check the adequacy of fit. However, the MR-CCD exceed the range of the boundary in the design region. Hence, a modified MR-CCD has improved the efficiency and proposed the parameter settings to manufacture the wind generator with high-class quality. The validation of the analytical and numerical fashions is successfully achieved through rigorous FEA, and the experimental verifications are perfectly marked the theoretical and significance optimisation design.
This research presents a rotor shape multi-levelobjective optimization designed to reduce the mechanical stress distribution in the rotor core of a double-stator permanent magnet synchronous motor. The second objective is weight minimization performed via a response surface methodology (RSM) with a uniform precision central composite design (UP-CCD) function. The optimal operation point, with a substantial population size, is reached using a Monte Carlo algorithm on the fitted model. The goodness-of-fit for the model is evaluated based on the modified Akaike information criterion (AICc) and the Bayesian information criterion (BIC) with a linear regression approach. To achieve these goals, a multi-level design procedure is proposed for the first time in machine design engineering. All the electromagnetic forces of the machine such as normal, tangential, and centrifugal forces are calculated using 3-D transient finite element analysis (FEA). The outcome of the proposed rotor core optimization shows that the finalized shape of the studied core has significantly smaller weight and mechanical stress, while the electromagnetic performance of the machine has remained consistent with a pre-optimized machine.
Increasing the number of pole-pairs leds to a lower electromagnetic yoke, and therefore lower vibration and magnetic noise occur. In this research, the influence of different numbers of pole-pairs on the vibro-acoustic design aspects of the machine is studied for the first time using a multi-slice subdomain method (MS-SDM) while considering the natural frequencies under a variable speed analysis. This study aims to determine the optimal number of pole-pairs for a lowspeed, high-torque permanent magnetic synchronous generator (PMSG) with double-layer, fractional-slot, nonoverlapping, concentrated windings (FSCW) for wind turbine applications. First, all possible slots per pole per phase combinations which offer the use of double-layer FSCW are studied through a magnetomotive force (MMF) harmonic analysis. Second, the MS-SDM of the PMSG is studied to examine the vibro-acoustic performance under a variable speed analysis. Finally, all affected major parameters are compared in order to find the optimal pole number of the PMSG. To verify the MS-SDM-based results, both 3-D finite element analysis and experimental investigations are employed.
A robust design in electrified powertrains substantially helps to enhance the vehicle's overall efficiency. Robustness analyses come with complexity and computational costs at the vehicle level. The use of sensitivity analysis (SA) methods in the design phase has gained popularity in recent years to improve the performance of road vehicles while optimizing the resources, reducing the costs, and shortening the development time. Designers have started to utilize the SA methods to explore: i) how the component and vehicle level design options affect the main outputs i.e. energy efficiency and energy consumption; ii) observing sub-dependent parameters, which might be influenced by the variation of the targeted controllable (i.e. magnet thickness) and uncontrollable (i.e. magnet temperature) variables, in nonlinear dynamic systems; and iii) evaluating the interactions, of both dependent, and sub-dependent controllable/uncontrollable variables, under transient conditions. Hence the aim of this study is to succinctly review recent utilization of SA methods in the design of AC electric machines (EM)s used in vehicle powertrains, to evaluate and discuss the findings presented in recent research papers while summarizing the current state of knowledge. By systematically reviewing the literature on applied SAs in electrified powertrains, we offer a bibliometric analysis of the trends of application-oriented SA studies in the last and next decades. Finally, a numericalbased case study on a third-generation TOYOTA Prius EM will be given, to verify the SA-related findings of this paper, alongside future works recommendations.INDEX TERMS Automotive engineering, AC machines, electric vehicles, robustness, sensitivity analysis, permanent magnet machines, time series analysis, statistics.
The increase of electric vehicles (EVs), environmental concerns, energy preservation, battery selection, and characteristics have demonstrated the headway of EV development. It is known that the battery units require special considerations because of their nature of temperature sensitivity, aging effects, degradation, cost, and sustainability. Hence, EV advancement is currently concerned where batteries are the energy accumulating infers for EVs. This paper discusses recent trends and developments in battery deployment for EVs. Systematic reviews on explicit energy, state-of-charge, thermal efficiency, energy productivity, life cycle, battery size, market revenue, security, and commerciality are provided. The review includes battery-based energy storage advances and their development, characterizations, qualities of power transformation, and evaluation measures with advantages and burdens for EV applications. This study offers a guide for better battery selection based on exceptional performance proposed for traction applications (e.g., BEVs and HEVs), considering EV’s advancement subjected to sustainability issues, such as resource depletion and the release in the environment of ozone and carbon-damaging substances. This study also provides a case study on an aging assessment for the different types of batteries investigated. The case study targeted lithium-ion battery cells and how aging analysis can be influenced by factors such as ambient temperature, cell temperature, and charging and discharging currents. These parameters showed considerable impacts on life cycle numbers, as a capacity fading of 18.42%, between 25–65 °C was observed. Finally, future trends and demand of the lithium-ion batteries market could increase by 11% and 65%, between 2020–2025, for light-duty and heavy-duty EVs.
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