Method for design and customization of a multiphase electric motor

Patent metadata

Field	Value
Publication number	US-10185802-B2
Application number	US-201514825834-A
Country	US
Kind code	B2
Filing date	Aug 13, 2015
Priority date	Aug 13, 2014
Publication date	Jan 22, 2019
Grant date	Jan 22, 2019

Abstract

A method for designing and customizing a multiphase motor provides reduced modeling and customization time by utilizing a lumped parameter model (LPM) of the multiphase motor. In addition, during the design process, environmental factors, monitoring results of multiphase motors used in the field, market requirements, and the particular application for which the multiphase motor is to be used are all taken into account by the design method. Thus, by considering such factors together with the LPM of the multiphase motor allows the method of the present invention to optimize the overall design of the multiphase motor so that is achieves high reliability, high efficiency, and low cost.

First claim

What is claimed is:

1. A method for designing and customizing a multiphase electric motor comprising the steps of:
selecting a candidate electric motor design;
determining whether said candidate electric motor design meets one or more predetermined physical constraints;
calculating operating performance parameters using a lumped parameter model (LPM) of said candidate electric motor design if said one or more predetermined physical constraints are met at said determining step;
determining whether said performance parameters of said candidate electric motor design meet or exceed one or more predetermined operating performance values;
customizing said candidate electric motor design based on an objective function of said candidate electric motor design if said one or more operating performance values are met or exceeded at aid second determining step, such that said objection function comprises:

(

k
1

×
Machine
⁢

⁢

loss
2

+

k
2

×
Machine
⁢

⁢

cost
2

+

k
3

×
Torque
⁢

⁢

ripple
2

)

,

wherein k 1 , k 2 , and k 3 are weighting coefficients;
analyzing a plurality of predetermined number of electric motor models to determine acceptable electric motor designs to generate machine performance characteristics; and
generating the electric motor design based on the machine performance characteristics and the predetermined number of electric motor models that meet predetermined motor characteristics.

2. The method of claim 1 , wherein if said one or more predetermined physical constraints are not met at said first determining step, said selecting step is performed, whereby said candidate electric motor design is updated.

3. The method of claim 1 , wherein if said one or more predetermined operating performance values are not met or exceed at said second determining step, said selecting step is performed, whereby said candidate electric motor design is updated.

4. The method of claim 1 , further comprising:
calculating the numerical value of k1, k2, and k3 based on one or more of monitoring results of a physical electric motor, environmental factors, market requirements, or application requirements.

5. The method of claim 1 , wherein said operating performance parameters include a plurality of an air gap flux, a permanent magnet flux, an estimated saturation flux, an air gap reluctance, a flux barrier, a magnetic potential with respect to a q-axis, a magnetic potential with respect to a d-axis, a stator core reluctance, and a rotor core reluctance.

6. The method of claim 1 , wherein said lumped parameter model is a magnetic equivalent circuit model.

7. The method of claim 1 , wherein said stored candidate electric motor design is used in one or more subsequent iterations of said selecting step.

8. The method of claim 1 , wherein said objective function is a penalty function.

Assignees

• Choi Seungdeog
• Bonthu Sai Sudheer Reddy
• Univ Akron

Inventors

• Choi Seungdeog
• Bonthu Sai Sudheer Reddy

Classifications

• G06F2111/06

  Multi-objective optimisation, e.g. Pareto optimisation using simulated annealing [SA], ant colony algorithms or genetic algorithms [GA] · CPC title

• G06F30/20

  Design optimisation, verification or simulation (optimisation, verification or simulation of circuit designs G06F30/30) · CPC title

• G06F30/17 Primary

  Mechanical parametric or variational design · CPC title

• Y02T10/82

  Elements for improving aerodynamics · CPC title

• G06F17/5086 Primary

  Physics · mapped topic