This paper investigates enhancing the performance of vector control to make it comparable to direct torque control (DTC) by implementing the model on an FPGA using Spartan 6. The vector control model is simulated and results show lower torque ripple and faster response compared to DTC. The vector control model is then implemented on a Spartan 6 FPGA, which provides benefits like higher speed, lower power, and more. Simulation results of the FPGA implementation show a response comparable to DTC but faster, with potential to reduce ripple further. The paper compares vector control and DTC, showing how FPGA implementation can improve vector control performance.

1. Enhancement of Vector Control and making it comparable with
output of DTC using FPGA
Abstract
This paper investigates on enhancing the performance of vector control to make it comparable with
the performance DTC by implementing the model in FPGA using Spartan 6. The objective is to
have lower torque pulsation, higher torque density, stability, high efficiency and lower current
ripple of PMSM using the vector model which is by far the simplest model and one of the earliest
model. Simulation results strengthen this fact. The paper is a comparison between vector model
and DTC model and lays emphasis on how vector model can be made more comparable to DTC
model using FPGA Spartan 6. The D-Q vector control model is been implemented in FPGA using
Spartan 6 board which is the latest offering from Xilinx. Through this, the efficiency of the D-Q
model drives that are used in hoists or elevators will be enhanced in a much more effective way.
Since the working principle of vector control is much simpler than that of DTC, it can be used in
places where less technicality is required, and would provide a better results.
Keywords: D-Q control, DTC, PMSM, Digital signal processing, FPGA
I. INTRODUCTION
The outstanding performance of PMSM such as immediate response, accuracy of output,
compactness, robustness, efficiency, reliability and construction are so wide that helps to expand
its field of applications in industries as well as general use [1]-[2]. PMSM are used in many
application that require rapid torque response and high-performance operations. Due to the
problem of sensors such as, cost and maintenance, complication and so on, the sensorless control
techniques was proposed which makes the PMSM more well-known. In recent years a lot of papers
have appears. Some use a torque controller as long as current controllers [3, 4] and others are using
a torque controller to replace one of the current controllers [5]. In D-Q model of PMSM, the torque
is controlled by D-Q axis’s currents only. As the torque is directly proportional to the current, D-
Q model is easier than any other torque controlling methods [6]. Using PI controllers to control
the toque is another method. Fuzzy logic controller has been introduced in many controller for
PMSM [7]. Direct torque control (DTC), which has become popular in various motor drives, can
be implemented based on digital signal processing (DSP). This method has the advantages over
the torque response type of control is limited by time-constant of motor winding.
This paper elaborates the implementation of D-Q model in one of the most advanced digital
signal processors, FPGA, the result that obtained are almost similar to DTC of PMSM. The reasons
that makes FPGA more widespread are programmable hard-wired feature, fast time-to-market,
shorter design cycle, embedding processor low power consumption and higher density for the
implementation of the digital system [8]. FPGA provides a compromise between the special-
purpose applications specified integrated circuit (ASIC) hardware and general-purpose processors
[9]. Many previous researcher used FPGA either directly or within optimization techniques such
as fuzzy logic or for controlling various types of machines [10-14].

2. This paper is proposed to implement D-Q model of PMSM using the most recent and advanced
Xilinx FPGA board “Spartan-6”. It consists XC6SLX45 chip and its family package is CSG324C.
However, the basic of Spartan 6 is the same as the previous models, when more complex computation
is desired, the 6-input look-up table structure of the Spartan 6 will reduce the number of logic levels
and therefore increase the maximum clock speed of the design. There are many other advantages
which are mentioned in the rest. The paper focuses on vector control model of PMSM that is
controlling D-Q axis’s current to control torque and compare it with DTC model using Simulink.
II. SYSTEM DESCRIPTION: VECTOR CONTROL VS DTC
The principle of direct torque control, as one of the most famous control method, is to directly
select stator voltage vectors according to the differences between the reference and actual torque
and stator flux linkage. The current controller followed by a pulse width modulation (PWM)
comparator is not used in DTC systems, and the parameters of the motor are also not used, except
the stator resistance. Therefore, the DTC possesses advantages such as lesser parameter
dependence and fast torque response when compared with the torque control via PWM current
control [15]. DTC is very fast, does not requires, PI controller and has many other advantages.
However, DTC strategies require an inverter to convert the low voltage control signals to high
voltage to drive the motor which makes the system more controllable but because of switching
effect, the harmonic and inter-harmonic orders would be added to the waveforms [16]. Moreover,
DTC needs sensor for low speed. In DTC, the speed regulators requires precise math model of the
system and appropriate value of constants to achieve high performance drive. Therefore,
unexpected change in load conditions or environmental factors would produce overshoot,
oscillation of the motor speed, oscillation of the torque, long settling time and causes deterioration
of drive performance. The selected voltage vector is applied for the entire switching period, and
thus allows electromagnetic torque and stator flux to vary for the whole switching period. This
causes high torque and flux ripples.
On the other hand, the D-Q vector control has high control cycle time and needs current control,
and PWM modulator. This paper is trying to implement these parts on the newest generation of
FPGA to increase the speed and stability of controller, and decrease the noise and harmonics.
A. Results and discussions for DTC model
To examine the performance of DTC, simulations on a PMSM under DTC control is carried out.
For DTC, the stator flux linkage is kept at its rated value. The reference torque is changed abruptly
from (-10.0) to (10.0) Nm. As shown in Fig. 1 and 2, the speed and torque response with DTC
fluctuating initially but after cycles, it becomes constant and contain very less ripple.
Fig. 1. Torque and speed response of DTC (a) with Tref: -10 N.m, (b) Tref: 10 N.m

3. III. IMPLEMENTATION OF VECTOR CONTROL MODEL ON FPGA
A field-programmable gate array (FPGA) is an integrated circuit designed to be configured by a
customer or a designer after manufacturing. The FPGA configuration (fig. 2) is generally specified
using a Hardware Description Language (HDL). Contemporary FPGAs have large resources of
Logic Gates, RAM Blocks. Every FPGA chip is made up of a finite number of predefined resources
with programmable interconnects to implement a reconfigurable digital circuit and I/O blocks to
allow the circuit to access the outside world.
Fig. 2: FPGA Spartan 6 logic blocks
The Xilinx’s Spartan-6 FPGA is used in this paper due to be advantageous over other FPGA
family board. The Design Platform merges industry leading process and programmable logic
technology with transceiver capabilities and controllers for advanced memory support in high
performance and cost sensitive application. The most innovative option that is included with
Spartan-6 is its operation in low power environment. Low power like 1.0V core option enable the
new Spartan-6 FPGA family to achieve 65% lower power than previous Spartan families.
After programming using in Simulink, Xilinx ISE is used as software tool for the synthesis and
analysis of HDL designs. For implementing the D-Q Simulink model on FPGA, the vector control
Simulink model is converted to XILINX block and the final model is given below.
Fig. 3. D-Q vector control model using FPGA

4. This figure contains the total block diagram of D-Q model using Xilinx block set. Here PWM
generator is shown in a separate block that is generating continuous pulse for the inverter. Another
Torque speed comparator block is shown in PMSM model that is using two current (id, iq) to
generate estimated torque from the PMSM machine. In detail, fig. 4 is a complete representation
of Id-q to Iabc transformation using Xilinx block set.
Fig. 4. ID-Q to Iabc
To examine the performance of vector control on a PMSM with no saliency, the current control
have been carried out in the following specification under D-Q and under PWM. For D-Q, d-axis
current id is kept at zero and reference q-axis current is changed abruptly. Initially constant
reference iq current is imposed and then step reference iq current is given and response is observed.
The torque and speed response with D-Q model becomes constant after sometime which is shown
in fig. 5. It’s faster than DTC; however, the response contains ripple. It’s planed in the full version
of the paper to decrease these ripples The PMSM model that is been used in this paper has the
following parameters.
Table I. PMSM model parameters for D-Q Vector Control
Parameter Name Values Unit
Stator Resistance R 1.4 ohm
Inductance Ld 0.0066 H
Inductance Lq 0.0058 H
Rotor Flux Constant Yaf 0.1546 V/rad/s
Moment of Inertia J 0.00176 Kgm2
Friction Vicious Gain B 0.00038818 Nm/rad/s
Fig. 5. Simulink result with step reference speed (a) speed (RPM) (b) torque (N.M)

5. IV. CONCLUSION AND FUTURE WORK
The enhancement of the performance of vector control of PMSM using new generation of FPGA
is achieved. Spartan 6 as the newest technology of FPGA has higher performance of calculation,
low power assumption, higher memory, high logic cell density which enables implementing
complicated algorithms. The differences between the vector control and DTC technique, as one of
the most prestigious method for the PMSM, have been investigated. The D-Q vector control model
is implemented on a Spartan 6 FPGA board and a comparable output of DTC has been obtained.
The Simulink results of DTC and experimental result of vector control prove that the results are
not only comparable but the response is faster in the proposed model. The simulation results verify
both vector and DTC control and also show that the torque response under vector is much faster
and contain fewer ripples than DTC control. The effort for the full paper is to add adaptive control
section to decrease the noise and have less harmonics and inter-harmonics.
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