MATLAB | Calibrating Optimal IPMSM Control Using Model-Based Calibration @MATLAB | Uploaded January 2024 | Updated October 2024, 1 week ago.
Controlling the torque of a interior permanent magnet synchronous machine (IPMSM) to achieve high levels of accuracy and efficiency is one of the most important targets in high-performance electrified powertrain design. Just like IC engine control, IPMSM control also requires calibration.
Typically, during IPMSM calibration, motor characterization tests are conducted on the dyno, and motor data is collected to feed through a calibration workflow. This workflow calculates optimal id/iq combinations for IPMSM flux weakening and torque control.
Watch how to use statistical and optimization methods and Model-Based Calibration Toolbox™ to help design IPMSM characterization experiments and automate the calibration of optimal torque control id/iq lookup tables. This workflow demo was created using new features available in MATLAB® R2023b.
Related Resources:
- Try example: bit.ly/3LFQDTP
- Calibrating Optimal PMSM Torque Control with Field-Weakening Using Model-Based Calibration: bit.ly/48xv0yG
Chapters:
0:00 Introduction to MBC Workflow Demo
0:30 Different IPMSM Torque Control Tables
2:18 Preprocessing IPMSM Data
4:17 Importing IPMSM Data into MBC Toolbox
4:55 Filtering IPMSM Data
6:17 Fitting Models to IPMSM data
9:23 Importing Fitted Models to CAGE
10:08 Creating Function Models
12:07 Creating an Optimization for Torque Envelope
19:50 Creating an Optimization for Id/Iq Lookup Tables
25:07 MBC Process Summary
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© 2023 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc.
See mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.
Controlling the torque of a interior permanent magnet synchronous machine (IPMSM) to achieve high levels of accuracy and efficiency is one of the most important targets in high-performance electrified powertrain design. Just like IC engine control, IPMSM control also requires calibration.
Typically, during IPMSM calibration, motor characterization tests are conducted on the dyno, and motor data is collected to feed through a calibration workflow. This workflow calculates optimal id/iq combinations for IPMSM flux weakening and torque control.
Watch how to use statistical and optimization methods and Model-Based Calibration Toolbox™ to help design IPMSM characterization experiments and automate the calibration of optimal torque control id/iq lookup tables. This workflow demo was created using new features available in MATLAB® R2023b.
Related Resources:
- Try example: bit.ly/3LFQDTP
- Calibrating Optimal PMSM Torque Control with Field-Weakening Using Model-Based Calibration: bit.ly/48xv0yG
Chapters:
0:00 Introduction to MBC Workflow Demo
0:30 Different IPMSM Torque Control Tables
2:18 Preprocessing IPMSM Data
4:17 Importing IPMSM Data into MBC Toolbox
4:55 Filtering IPMSM Data
6:17 Fitting Models to IPMSM data
9:23 Importing Fitted Models to CAGE
10:08 Creating Function Models
12:07 Creating an Optimization for Torque Envelope
19:50 Creating an Optimization for Id/Iq Lookup Tables
25:07 MBC Process Summary
--------------------------------------------------------------------------------------------------------
Get a free product trial: goo.gl/ZHFb5u
Learn more about MATLAB: goo.gl/8QV7ZZ
Learn more about Simulink: goo.gl/nqnbLe
See what's new in MATLAB and Simulink: goo.gl/pgGtod
© 2023 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc.
See mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.
