pyleecan.Classes.LossModelWinding module¶
Method code available at https://github.com/Eomys/pyleecan/tree/master/pyleecan/Methods/Loss/LossModelWinding
- class LossModelWinding(type_skin_effect=1, name='', group='', is_show_fig=False, coeff_dict=None, init_dict=None, init_str=None)[source]¶
Bases:
LossModel
Winding loss model
- VERSION = 1¶
- comp_loss()¶
Calculate joule losses in stator windings
- Parameters:
self (LossModelWinding) – a LossModelWinding 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 (LossModelWinding) – a LossModelWinding 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.
- property type_skin_effect¶
0 to ignore skin effect, 1 to consider it
- Type:
int