Nonlinear design optimization of electric machines by using parametric Fourier coefficients of air gap flux density
Nonlinear design optimization of electric machines by using parametric Fourier coefficients of air gap flux density
复制标题
使用气隙磁通密度的参数傅立叶系数优化电机的非线性设计
DOI:
10.1109/aim.2016.7576841
复制
发表时间:
2016
期刊:
影响因子:
--
通讯作者:
R. Kasper
中科院分区:
文献类型:
--
作者:
N. Borchardt;R. Kasper
Weight and efficiency are conflicting top requirements for all kind of mobile applications of electrical machines. Utilizing the design freedom of a novel machine design, based on a slotless air gap winding while providing high torque and efficient cooling, this paper presents a design optimization approach that allows for precise and fast design of that type of machine. Design speed is achieved by building a simplified parametric model of the electrical machine that combines very well with a nonlinear optimization formulation of the design problem, where machine mass and losses are balanced out to find a Pareto optimal design set. Additional design requirements are treated via constraints. The parametric machine model was built upon a numerical finite elements method analysis of magnetic flux density in the air gap with ANSYS Maxwell, which is used to formulate parametric Fourier series based models of flux acting on a phase, flux acting on a six-step commutated winding and effective flux useful to define machine torque constant. Except the numerical optimization procedure, all model and design equations can be formulated analytically exploiting Maple's symbolic computation features, thus simplifying analysis and speeding up design. Finally, an optimal motor design study for a 15-inch rim wheel-hub drive is presented. The range of a tradeoff between demands for weight and efficiency while delivering the required torque at nominal speed is shown.