This study investigates the influence of the buried magnet arrangement on the efficiency and drivability performance provided by an on-board interior permanent magnet synchronous machine for a four-wheel-drive electric car with two single-speed on-board powertrains. The relevant motor characteristics, including flux-linkage, inductance, electromagnetic torque, iron loss, total loss, and efficiency, are analyzed for a set of six permanent magnet configurations suitable for the specific machine, which is controlled through maximum-torque-per-ampere and maximum-torque-per-voltage strategies. Moreover, the impact of each magnet arrangement is analyzed in connection with the energy consumption along four driving cycles, as well as the longitudinal acceleration and gradeability performance of the considered vehicle. The simulation results identify the most promising rotor solutions, and show that: (i) the appropriate selection of the rotor configuration is especially important for the driving cycles with substantial high-speed sections; (ii) the magnet arrangement has a major impact on the maximum motor torque below the base speed, and thus on the longitudinal acceleration and gradeability performance; and (iii) the configurations that excel in energy efficiency are among the worst in terms of drivability, and vice versa, i.e., at the vehicle level, the rotor arrangement selection is a trade-off between energy efficiency and longitudinal vehicle dynamics.
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.
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.
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.
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