pmsm-pm-temp-predict 0.0.6

Permanent magnet temperature prediction

PMSM_PM_Temp_Predict

PMSM_PM_Temp_Predict is a project aimed at predicting the temperature of the permanent magnet in a Permanent Magnet Synchronous Motor (PMSM). The temperature of the permanent magnet is an important parameter that affects the performance and reliability of the motor

Description

This project utilizes machine learning techniques to develop a predictive model for estimating the temperature of the permanent magnet in a PMSM. The model takes into account various input parameters such as motor operating conditions, electrical voltages and currents, and environmental factors to make accurate temperature predictions. More specifically: the Random Forest Regressor is used for this project.

Features

• API integration: The project provides an API that exposes the trained model, allowing other applications or systems to make temperature predictions programmatically
• Feature scaling: input data is normalized to meet regression model requirements
• Single sample processing: API contains the function to predict single temperature value based on current motor state
• Data frame processing: API allows you to process pandas DataFrame and get results for a huge amount of samples with one function call.

Getting Started

To get started with the PMSM_PM_Temp_Predict project, follow these simple steps:

1. Install package with pip install pmsm-pm-temp-predict This command will install this python package and all required dependencies.
2. Integrate the trained model into your application using the provided API
3. Start making temperature predictions using the API and your collected data

For detailed instructions and usage examples, please refer to the documentation included in the repository.

Contributing

Contributions to the PMSM_PM_Temp_Predict project are welcome. If you encounter any issues or have suggestions for improvements, please open an issue in the repository or submit a pull request with your proposed changes.

API

Two functions are provided by API of this package:

Single sample processing

temp_predict(u_q, u_d, i_d, i_q, coolant, stator_winding)

parameter	type	description
u_q	float	q-component of the motor voltage in V
u_d	float	d-component of motor voltage in V
i_d	float	q-component of the motor current in A
i_q	float	d-component of the motor current in A
coolant	float	coolant temperature in В°C
stator_winding	float	stator winding temperature in В°C

return value is a single float value which represents predicted temperature of the motor's permanent magnet.

Code example

import pmsm_pm_temp_predict as pms
print("Predicted permanent magnet temperature is: ", temp_predict(-0.450682,
                                                                   -0.350055,
                                                                   0.004419,
                                                                   0.000328,
                                                                   18.805172,
                                                                   19.086670))

Output: Predicted permanent magnet temperature is: 24.849657903061008

DataFrame processing

temp_predict_df(df)

parameter	type	description
df	pandas DataFrame	a pandas DataFrame object containing columns similar to the parameters of the temp_predict function

return value is an array of predicted temperatures of the motor's permanent magnet.

Code example

import pmsm_pm_temp_predict as pms
print("Predicted permanent magnet temperature is: ", temp_predict(-0.450682,
                                                                   -0.350055,
                                                                   0.004419,
                                                                   0.000328,
                                                                   18.805172,
                                                                   19.086670))

print("Predicted permanent magnet temperature is: ", temp_predict_df(pd.DataFrame({'coolant': [18.805172], 
                                                                                   'stator_winding': [19.086670],
                                                                                   'u_q': [-0.450682],
                                                                                   'u_d': [-0.350055],
                                                                                   'i_d': [0.004419],
                                                                                   'i_q': [0.000328]})))

Output: Predicted permanent magnet temperature is: [24.8496579]