TIDUF67 April   2024  – December 2024

 

  1.   1
  2.   Description
  3.   Resources
  4.   Features
  5.   Applications
  6.   6
  7. 1System Description
    1. 1.1 Terminology
    2. 1.2 Key System Specifications
  8. 2System Overview
    1. 2.1 Block Diagram
    2. 2.2 Highlighted Products
      1. 2.2.1 AM263x Microcontrollers
        1. 2.2.1.1 TMDSCNCD263
        2. 2.2.1.2 LP-AM263
  9. 3System Design Theory
    1. 3.1 Three-Phase PMSM Drive
      1. 3.1.1 Mathematical Model and FOC Structure of PMSM
      2. 3.1.2 Field Oriented Control of PM Synchronous Motor
        1. 3.1.2.1 The (a, b) → (α, β) Clarke Transformation
        2. 3.1.2.2 The (α, β) → (d, q) Park Transformation
        3. 3.1.2.3 The Basic Scheme of FOC for AC Motor
        4. 3.1.2.4 Rotor Flux Position
      3. 3.1.3 Sensorless Control of PM Synchronous Motor
        1. 3.1.3.1 Enhanced Sliding Mode Observer With Phase Locked Loop
          1. 3.1.3.1.1 Design of ESMO for PMSM
          2. 3.1.3.1.2 Rotor Position and Speed Estimation with PLL
      4. 3.1.4 Hardware Prerequisites for Motor Drive
      5. 3.1.5 Additional Control Features
        1. 3.1.5.1 Field Weakening (FW) and Maximum Torque Per Ampere (MTPA) Control
        2. 3.1.5.2 Flying Start
  10. 4Hardware, Software, Testing Requirements, and Test Results
    1. 4.1 Hardware Requirements
    2. 4.2 Software Requirements
      1. 4.2.1 Importing and Configuring Project
      2. 4.2.2 Project Structure
      3. 4.2.3 Lab Software Overview
    3. 4.3 Test Setup
      1. 4.3.1 LP-AM263 Setup
      2. 4.3.2 BOOSTXL-3PHGANINV Setup
      3. 4.3.3 TMDSCNCD263 Setup
      4. 4.3.4 TMDSADAP180TO100 Setup
      5. 4.3.5 TMDSHVMTRINSPIN Setup
    4. 4.4 Test Results
      1. 4.4.1 Level 1 Incremental Build
        1. 4.4.1.1 Build and Load Project
        2. 4.4.1.2 Setup Debug Environment Windows
        3. 4.4.1.3 Run the Code
      2. 4.4.2 Level 2 Incremental Build
        1. 4.4.2.1 Build and Load Project
        2. 4.4.2.2 Setup Debug Environment Windows
        3. 4.4.2.3 Run the Code
      3. 4.4.3 Level 3 Incremental Build
        1. 4.4.3.1 Build and Load Project
        2. 4.4.3.2 Setup Debug Environment Windows
        3. 4.4.3.3 Run the Code
      4. 4.4.4 Level 4 Incremental Build
        1. 4.4.4.1 Build and Load Project
        2. 4.4.4.2 Setup Debug Environment Windows
        3. 4.4.4.3 Run the Code
    5. 4.5 Adding Additional Functionality to Motor Control Project
      1. 4.5.1 Using DATALOG Function
      2. 4.5.2 Using PWMDAC Function
      3. 4.5.3 Adding CAN Functionality
      4. 4.5.4 Adding SFRA Functionality
        1. 4.5.4.1 Principle of Operation
        2. 4.5.4.2 Object Definition
        3. 4.5.4.3 Module Interface Definition
        4. 4.5.4.4 Using SFRA
    6. 4.6 Building a Custom Board
      1. 4.6.1 Building a New Custom Board
        1. 4.6.1.1 Hardware Setup
        2. 4.6.1.2 Migrating Reference Code to a Custom Board
          1. 4.6.1.2.1 Setting Hardware Board Parameters
          2. 4.6.1.2.2 Modifying Motor Control Parameters
          3. 4.6.1.2.3 Changing Pin Assignment
          4. 4.6.1.2.4 Configuring the PWM Module
          5. 4.6.1.2.5 Configuring the ADC Module
          6. 4.6.1.2.6 Configuring the CMPSS Module
  11. 5General Texas Instruments High Voltage Evaluation (TI HV EVM) User Safety Guidelines
  12. 6Design and Documentation Support
    1. 6.1 Design Files
      1. 6.1.1 Schematics
      2. 6.1.2 BOM
      3. 6.1.3 PCB Layout Recommendations
        1. 6.1.3.1 Layout Prints
    2. 6.2 Tools and Software
    3. 6.3 Documentation Support
    4. 6.4 Support Resources
    5. 6.5 Trademarks
  13. 7About the Author

Mathematical Model and FOC Structure of PMSM

The FOC structure for a PMSM is illustrated in Figure 2-1. In this system, the eSMO is used for achieving the sensorless control an IPMSM system, and the eSMO model is designed by utilizing the back EMF model together with a PLL model for estimating the rotor position and speed.

An IPMSM consists of a three-phase stator winding (a, b, c axes), and permanent magnets (PM) rotor for excitation. The motor is controlled by a standard three-phase inverter. An IPMSM can be modeled by using phase a-b-c quantities. Through proper coordinate transformations, the dynamic PMSM models in the d-q rotor reference frame and the α-β stationary reference frame can be obtained. The relationship among these reference frames are illustrated in Equation 1. The dynamic model of a generic PMSM can be written in the d-q rotor reference frame as:

Equation 1. vdvq=Rs+pLd-ωeLqωeLdRs+pLqidiq+0ωeλpm

where

  • vd is the q-axis stator terminal voltage
  • vq is the d-axis stator terminal voltage
  • id is the d-axis stator current
  • iq is the q-axis stator current
  • Ld is the q-axis inductance
  • Lq is the d-axis inductance
  • p is the derivative operator
  • a short notation of Equation 2 is the flux linkage generated by the permanent magnets
  • RS is the resistance of the stator windings
  • ωe is the electrical angular velocity of the rotor
Equation 2. ddt;λpm
TIDM-02018 Definitions of Coordinate Reference Frames for PMSM ModelingFigure 3-2 Definitions of Coordinate Reference Frames for PMSM Modeling

By using the inverse Park transformation as shown in Figure 3-2, the dynamics of the PMSM can be modeled in the α-β stationary reference frame as:

Equation 3. vαvβ=Rs+pLdωe(Ld-Lq)-ωe(Ld-Lq)Rs+pLqiαiβ+eαeβ

Where the ea and eβ are components of extended electromotive force (EEMF) in the α-β axis and can be defined as:

Equation 4. eαeβ=λpm+Ld-Lqidωe-sin(θe)cos(θe)

According to Equation 3 and Equation 4, the rotor position information can be decoupled from the inductance matrix by means of the equivalent transformation and the introduction of the EEMF concept, so that the EEMF is the only term that contains the rotor pole position information. And then the EEMF phase information can be directly used to realize the rotor position observation. Rewrite the IPMSM voltage Equation 5 as a state equation using the stator current as a state variable:

Equation 5. i˙αi˙β=1Ld-Rs-ωe(Ld-Lq)ωe(Ld-Lq)-Rsiαiβ+1LdVα-eαVβ-eβ

Since the stator current is the only physical quantity that can be directly measured, the sliding surface is selected on the stator current path:

Equation 6. Sx=i^α-iαi^β-iβ=i~αi~β

where

  • Equation 7 and Equation 8 are the estimated currents
  • the superscript ^ indicates the estimated value
  • the superscript ˜ indicates the variable error which refers to the difference between the observed value and the actual measurement value
Equation 7. i^α
Equation 8. i^β