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为降低外转子永磁同步电机(ERPMSM) 作为皮带输送机驱动电机时的永磁体成本并提高电机性能,提出基于响应面法(RSM)和改进多目标粒子群优化(IMOPSO)算法的优化设计方法。在建立电机基本结构的基础上,将永磁体尺寸、气隙长度、槽口宽度等作为优化参数,将永磁体成本、输出转矩、转矩脉动等作为优化目标。通过参数灵敏度分析筛选出显著参数,基于RSM结合有限元仿真建立样本空间,并拟合出优化目标和优化参数的函数关系,通过IMOPSO寻优。最后对比优化前后的方案结果,所提多目标优化算法准确可靠且具有更好的收敛性和多样性,能够在降低永磁体成本的同时优化电机的性能。 相似文献
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为降低具有高功率、高转矩密度等特点的电动汽车轮毂电机热源损耗,提出了基于博弈论的外转子式永磁同步轮毂电机的多目标优化设计方法。首先应用磁路法推导了电机各项损耗的解析表达式;其次以定子槽形的尺寸为设计变量,以定子铁耗、绕组铜耗、永磁体涡流损耗和电机效率为优化目标,建立电机优化设计数学模型;最后应用基于博弈论的多目标优化算法(Game Theory Optimization Algorithm,GTO),同时结合改进粒子群算法(Advanced Particle Swarm Optimization Algorithm,APSO)对电机定子槽型进行优化设计,并借助有限元仿真软件进行了辅助计算。研究结果表明:相较于原设计方案,优化后电机功率损耗减少32.6%,效率提高6.12%。 相似文献
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本文将瞬态热网络法应用到起重机用细长型外转子永磁电机的优化设计中,以电机效率和成本为优化目标,对一台37.0kW永磁电机进行优化设计。选择永磁体厚度、气隙长度g、电机铁心轴向长度、每槽导体数、导线线规、永磁体厚度六个参数为优化变量,同时约束其槽满率、定子齿部磁密、定子轭部磁密、最大温升、最大转矩在一定范围内。本文分析了细长型永磁电机结构参数对铜损耗和效率的影响,再利用粒子群优化算法对永磁电机进行优化设计。优化结果显示:电机效率提高1.1%,成本也略有下降。最后通过有限元仿真,验证了瞬态热网络法的可行性和准确性。 相似文献
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针对目前大功率高速永磁电机多采用的表贴式转子结构强度优化问题,以一台1.12 MW、18 000 r/min的表贴式高速永磁电机转子为优化对象,建立其结构参数化模型及应力场有限元仿真模型。将工况温度、护套厚度、永磁体厚度以及过盈量设置为优化参数,以永磁体和护套的法向及切向应力的最大值尽可能小为优化目标展开优化设计。对比分析两种技术路线:技术路线一采用进化算法(EA)调用有限元模型(FEM)进行优化设计;技术路线二对拉丁超立方法取得的样本空间进行拟合得到Kriging近似模型,基于近似模型结合EA算法进行优化设计。优化设计结果表明,技术路线一的优化结果更好;技术路线二更快速高效,大量样本点的集中分布情况可以反映优化参数与优化目标量间的关系。故实际工程优化问题应结合两种技术路线,初步寻优阶段采用技术路线二精确参数区间,进而采用技术路线一展开优化取得最优设计。 相似文献
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针对电机多参数多目标协同优化较为复杂的问题,提出了基于非支配排序遗传算法分层迭代优化的思想。首先,介绍定子分段混合励磁开关磁阻电机的设计流程和工作原理。其次,选择电机的待优化参数和优化目标,并引入Pearson相关系数分析电机参数与优化目标的相关性,根据相关性结果对待优化参数进行分层;建立各层优化参数与优化目标的非线性模型,将非线性目标模型引入多目标优化算法。最终,在Pareto前沿中选取最优个体,完成对电机结构参数和控制参数的分层迭代优化,确定电机的最优结构参数和控制参数,并通过有限元分析软件进行验证。相比较于初始模型,优化后电机的效率略有提高,平均转矩增加12.44%,转矩脉动减小64.96%。根据最优参数制造出实验样机,实验结果验证了优化设计的有效性和优越性。 相似文献
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双余度永磁同步电机有两个余度单元,具有容错率高、体积小、功率密度大等特点,在航空航天、国防、机器人等领域得到广泛应用。针对双余度电机的多目标优化设计问题,基于其典型工作模式,提出二次田口法迭代的多目标优化设计方法。首先,依据双余度度永磁同步电机的应用需求,确定优化目标参数;在初始设计参数基础上,筛选出对目标优化参数影响大的尺寸参数作为优化因子。其次,首次应用田口法筛选出双余度模式下的准最优参数;进而在单余度模式下再次应用田口法对准最优参数进行二次优化;综合两次优化结果确定最终优化参数。最后,通过有限元仿真分析对优化前后的目标参数变化进行验证分析,证明了所提出方法的有效性,也拓宽了对于该类电机的多目标优化设计思路。 相似文献
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为了拓展单边永磁盘式发电机的应用范围,对该类发电机进行优化设计。通过分析不同永磁体厚度、气隙、形状对发电机的影响,对比有无铁心单边结构发电机的性能,选择适合汽车工况的发电机为研究对象。通过响应曲面法,建立以永磁体厚度、形状为优化变量,电压波形畸变率、效率为优化目标的多目标优化方程。结果表明,不同永磁体厚度与形状对发电机性能具有重要影响,通过响应曲面优化后的单边永磁发电机效率提高了0.83%,THD降低了16.7%。因此,所提优化方法对单边盘式发电机永磁体结构的设计具有一定的指导意义。 相似文献
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This paper presents a method of multiobjective optimization design with anti‐demagnetization aiming at the problem of irreversible demagnetization in high‐density permanent magnet synchronous motors (PMSMs) due to temperature and external magnetic field, at the same time considering the volume of permanent magnets and cost, torque ripple, and core loss. In the first step, a two‐dimensional magnetic network model is used to rapidly assess the basic design parameters and its ability to avenge the anti‐demagnetization of the PMSM. In the second step, the finite element method (FEM) is used to design the key parts of motor, and regression models that solve the model of the multiobjective problem are built based on the simulation experiment data. On this basis, multiobjective optimization result using genetic algorithm is used that can achieve a fast and efficiently global optimal solution. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. 相似文献
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Bacterial Foraging Based Optimal Design of Transverse Flux Linear Motor for Thrust Force Improvement
Hany M. Hasanien 《电力部件与系统》2015,43(1):95-104
Abstract—This article presents a novel optimal design for a permanent magnet excitation transverse flux linear motor with an inner mover using bacterial foraging optimization. The target is maximizing the motor thrust force, which is the most important quantity in linear electric drives. The stator pole length, air-gap length, winding window width, and stator pole width define the search space for the optimization problem. The response surface methodology is used to build the mathematical model of the motor thrust force in terms of the design variables. It can create an objective function easily, and great computational time is saved. Finite-element computations are used for numerical experiments on the geometrical design variables to determine the coefficients of a second-order analytical model for the response surface methodology. The bacterial foraging optimization technique is used as a searching tool under the constraints of design variables for design optimization of the transverse flux linear motor to improve the motor thrust force. The effectiveness of the proposed bacterial foraging optimization model is then compared with that of both genetic algorithm and particle swarm optimization models. With this proposed bacterial foraging optimization technique, the thrust force of the initially designed transverse flux linear motor can be increased. 相似文献
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用于电动汽车的永磁同步电机不仅需要考虑额定工况的性能,还需要考虑整个路谱下的综合效率。基于此,介绍了一种基于新标欧洲循环测试(NEDC)路谱的非对称V型内嵌式永磁同步电机优化设计方法。将上述非对称电机中永磁体上下两部分的几何参数分别作为独立参数进行参数化建模,然后以NEDC效率和转矩成本比为优化目标,采用遗传算法分别对对称和非对称V型永磁同步电机进行多目标优化。最后,选取帕累托前沿上的最佳设计点进行电磁性能仿真比较。仿真结果表明,与对称结构相比,非对称转子结构由于磁场偏移效应而表现出更强的转矩性能。因此,非对称V型永磁同步电机具有更加优异的电磁性能和更低的制造成本,在电动汽车领域具有广阔的应用前景。 相似文献
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基于粒子群算法的直线振动发电机优化设计 总被引:3,自引:0,他引:3
设计了一种新型圆筒式永磁直线振动发电机,电机中永磁体放置在绕组外侧,内部通过放置铁心来增大感应电动势的幅值。其结构简单,尺寸多变,可将原来损失的小幅振动能量转化为电能,为小型设备提供低压直流。通过二维有限元对其非线性无边界轴对称磁场进行了系统的分析,得到一系列电机感应电动势与电机尺寸间的变化规律,并以有限元分析结果为基础,结合粒子群优化算法,归纳出通用的优化设计准则和公式。优化结果表明,为了得到更高的材料利用率,应取较大的永磁体外径,且样机实验和有限元分析结果吻合良好。 相似文献
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Yoshihiro Hosokawa So Noguchi Hideo Yamashita Shigeya Tanimoto 《Electrical Engineering in Japan》2002,138(3):72-79
In optimal design of a permanent magnet (PM) motor, many design variables are required to consider some device properties. These variables are, for example, the shape of core and magnet, the tooth length, the number of turns, and the winding radius. Moreover, many restrictions must be considered in practical PM motor design. These restrictions are, for example, the slot space factor and the cogging torque. However, the optimization problem, which has many design variables by the finite element method (FEM), has not been reported. In this paper, the efficiency of PM motor under the considerations given above is optimized by using FEM and optimization algorithm. In this problem, an objective function has many local minima and it is difficult to calculate its gradient. For these reasons, the genetic algorithm (GA) and simulated annealing method (SA), which are stochastic methods, are used for optimization method, because of the possibility of global range search and because gradient calculation is not required. Adding to both optimization methods, in this paper, SA combined with GA is used for one of the optimization methods. It is found that the solutions optimized by these methods are reasonable from an engineering point of view. © 2001 Scripta Technica, Electr Eng Jpn, 138(3): 72–79, 2002 相似文献