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1. About the Drive-On-Chip Design Example for Intel® MAX® 10 Devices
2. Features of the Drive-on-Chip Design Example for Intel® MAX® 10 Devices
3. Getting Started with the Drive-On-Chip Design Example for Intel® MAX® 10 Devices
4. Rebuilding the Drive-On-Chip Design Example for Intel® MAX® 10 Devices
5. About the Scaling of Feedback Signals
6. Motor Control Software
7. Functional Description of the Drive-on-Chip Design Example
8. Achieving Timing Closure on a Motor Control Design
9. Design Security Recommendations
10. Reference Documents for the Drive-on-Chip Design Example
11. Document Revision History for AN 773: Drive-on-Chip Design Example for Intel® MAX® 10 Devices
3.1. Software Requirements for the Drive-On-Chip Design Example for Intel® MAX® 10 Devices
3.2. Hardware Requirements for the Drive-On-Chip Design Example for Intel® MAX® 10 Devices
3.3. Downloading and Installing the Design
3.4. Setting Up the Motor Control Board with your Development Board for the Drive-On-Chip Design Example for Intel® MAX® 10 Devices
3.5. Importing the Drive-On-Chip Design Example Software Project
3.6. Configuring the FPGA Hardware for the Drive-On-Chip Design Example for Intel® MAX® 10 Devices
3.7. Programming the Nios II Software to the Device for the Drive-On-Chip Design Example for Intel® MAX® 10 Devices
3.8. Applying Power to the Power Board
3.9. Debugging and Monitoring the Drive-On-Chip Design Example with System Console
3.10. System Console GUI Upper Pane for the Drive-On-Chip Design Example
3.11. System Console GUI Lower Pane for the Drive-On-Chip Design Example
3.12. Controlling the DC-DC Converter
3.13. Tuning the PI Controller Gains
3.14. Controlling the Speed and Position Demonstrations
3.15. Monitoring Performance
4.1. Changing the Intel® MAX® 10 ADC Thresholds or Conversion Sequence
4.2. Generating the Qsys System
4.3. Compiling the Hardware in the Intel Quartus Prime Software
4.4. Generating and Building the Nios II BSP for the Drive-On-Chip Design Example
4.5. Software Application Configuration Files
4.6. Compiling the Software Application for the Drive-On-Chip Design Example
4.7. Programming the Design into Flash Memory
7.1. Processor Subsystem
7.2. Six-channel PWM Interface
7.3. DC Link Monitor
7.4. Drive System Monitor
7.5. Quadrature Encoder Interface
7.6. Sigma-Delta ADC Interface for Drive Axes
7.7. Intel® MAX® 10 ADCs
7.8. ADC Threshold Sink
7.9. DC-DC Converter
7.10. Motor Control Modes
7.11. FOC Subsystem
7.12. DEKF Technique
7.13. Signals
7.14. Registers
7.11.1. DSP Builder for Intel FPGAs Model for the Drive-on-Chip Designs
7.11.2. Avalon Memory-Mapped Interface
7.11.3. About DSP Builder for Intel FPGAs
7.11.4. DSP Builder for Intel FPGAs Folding
7.11.5. DSP Builder for Intel FPGAs Model Resource Usage
7.11.6. DSP Builder for Intel FPGAs Design Guidelines
7.11.7. Generating VHDL for the DSP Builder Models for the Drive-on-Chip Designs
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7.12. DEKF Technique
In the DEKF technique, the design simultaneously executes two cooperating Kalman filters for nonlinear systems: one to estimate the states and the other to estimate the parameters.
The dual Kalman filter approach reduces the computation requirements compared to considering parameter changes as additional states in a single larger Kalman filter.
Equation 1. Parameter EvolutionThis equation describes the parameter evolution that with the measurement equation builds the first EKF.
Equation 2. State of EvolutionThis equation represents the state evolution that combines with the measurement equation to form the second EKF.
Equation 3. Measurement Equation
The measurement equation is the same for both filters. In the above equations:
- vT(k) is the vector of measurements at time k
- k is the discrete time
- iL(k) is the load current at time k
- p is parameters vector
- x = [SOC; VRC1] is the battery state vector
- χ, ξ and ψ are the parameters, the state and measurement noise, with zero mean and covariance matrix Σχ, Σξ and Σψ, respectively.
Equation 4. Circuit EquationsThe circuit equation describes the actual circuit. OCV(SOC) is the open circuit voltage - the voltage that is measured externally on the battery. It is related to the internal state of charge by the empirical polynomial equation with fixed parameters P1 to P8.
Equation 5. DEKF Matrix EquationsThe matrix equations are derived from the circuit equations.
The following equations are standard Kalman filter equations, which you can calculate after you define the standard Kalman filter variables in terms of the specific variables of the battery model.
Equation 6. Initialization Equation
Equation 7. Prediction Equations
Equation 8. Correction Equation