Download Multidisciplinary Design Optimization Methods for Electrical by Gang Lei, Jianguo Zhu, Youguang Guo PDF

By Gang Lei, Jianguo Zhu, Youguang Guo

This e-book offers a number of computationally effective part- and system-level layout optimization equipment for complicated electric machines and force structures. Readers will observe novel layout optimization innovations built through the authors and different researchers within the final decade, together with application-oriented, multi-disciplinary, multi-objective, multi-level, deterministic, and strong layout optimization tools. A multi-disciplinary research contains a number of elements of fabrics, electromagnetics, thermotics, mechanics, strength electronics, utilized arithmetic, production expertise, and qc and administration. This ebook will gain either researchers and engineers within the box of motor and force layout and production, hence permitting the potent improvement of the top of the range construction of leading edge, high-performance force structures for tough purposes, similar to eco-friendly strength structures and electrical vehicles.

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Extra info for Multidisciplinary Design Optimization Methods for Electrical Machines and Drive Systems

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9 Prototype of a high speed claw pole motor B. High speed claw pole motor In our previous work, a high speed claw pole motor as shown in Fig. 9 with an SMC stator core was developed [3, 8, 9]. 4, and the structure (one pole pitch of one stack) is shown in Fig. 10. 11 illustrates the topology of one of the three stacks. The stator consists of the claw poles, the yoke, and the phase winding. The rotor is simply made of a ring PM magnetized in four poles and mounted on the rotor core. The three stator stacks are shifted for 120o (electrical) apart from each other.

IEEE Trans Evol Comput 6(2):182–197 27. Reyes-Sierra M, Coello CAC (2006) Multi-objective particle swarm optimizers: A survey of the state-of-the-art. Int J Comput Intell Res 2(3):287–308 28. Dias AHF, Vasconcelos JA (2002) Multiobjective genetic algorithms applied to solve optimization problems. IEEE Trans Magn 38(2):1133–1136 29. dos Santos Coelho L, Alotto P (2008) Multiobjective electromagnetic optimization based on a nondominated sorting genetic approach with a chaotic crossover operator. IEEE Trans Magn 44(6):1078–1081 30.

Generally, there are two kinds of analysis models for thermal analysis in electrical machines, namely the thermal network model and the FEM [14, 15, 20, 25]. The following sections will present examples for the two methods. 2 Thermal Network Model Two design examples will be illustrated to show the usage of thermal network model for the thermal analysis of PM-SMC motors. The first one is a TFM, and the second is a high speed claw pole motor. A. Transverse flux machine In this study, the temperature rise was calculated by using a hybrid thermal network model with distributed heat sources, as shown in Fig.

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