pyleecan.Classes.LossModelJoule module

Method code available at https://github.com/Eomys/pyleecan/tree/master/pyleecan/Methods/Loss/LossModelJoule

class LossModelJoule(type_skin_effect=1, name='', group='', is_show_fig=False, coeff_dict=None, init_dict=None, init_str=None)[source]

Bases: LossModel

Joule loss model

VERSION = 1
comp_loss()

Calculate joule losses in stator windings

Parameters:

self (LossModelJoule) – a LossModelJoule object

Returns:

  • Pjoule_density (ndarray) – Joule loss density function of frequency and elements [W/m3]

  • freqs (ndarray) – frequency vector [Hz]

comp_coeff(T_op=20, T_ref=20)

Compute the skin effect factor on resistance for the conductors from “Design of Rotating Electrical Machines”, J. Pyrhonen, second edition All parameters are defined p.270 / 271 In this method, the returned value is the one from the reference divided by the frequency, as the effect of frequency will be taken into account in the coeff_dict

Parameters:

  • self (LossModelJoule) – a LossModelJoule object

  • T_op (float) – Conductor operational temperature [degC]

  • T_ref (float) – Conductor reference temperature [degC]

Returns:

kr_skin – skin effect coeff for resistance at given frequency and temperature

Return type:

float

save(save_path='', is_folder=False, type_handle_old=2, type_compression=0)

Save the object to the save_path

Parameters:

  • self – A pyleecan object

  • save_path (str) – path to the folder to save the object

  • is_folder (bool) – to split the object in different files: separate simulation machine and materials (json only)

  • type_handle_old (int) – How to handle old file in folder mode (0:Nothing, 1:Delete, 2:Move to “Backup” folder)

  • type_compression (int) – Available only for json, 0: no compression, 1: gzip

get_logger()

Get the object logger or its parent’s one

Parameters:

obj – A pyleecan object

Returns:

logger – Pyleecan object dedicated logger

Return type:

logging.Logger

compare(other, name='self', ignore_list=None, is_add_value=False)[source]

Compare two objects and return list of differences

as_dict(type_handle_ndarray=0, keep_function=False, **kwargs)[source]

Convert this object in a json serializable dict (can be use in __init__). type_handle_ndarray: int

How to handle ndarray (0: tolist, 1: copy, 2: nothing)

keep_functionbool

True to keep the function object, else return str

Optional keyword input parameter is for internal use only and may prevent json serializability.

copy()[source]

Creates a deepcopy of the object

property type_skin_effect

0 to ignore skin effect, 1 to consider it

Type:

int