Brushless DC (BLDC) motors are one of the electrical drives that are rapidly gaining popularity, due to their high efficiency, good dynamic response and low maintenance. In this paper, Existing and evolving techniques in the design of integrated circuits for brushless DC motor control are reviewed, with particular emphasis on the requirements for automotive applications. When system engineers implement BLDC motor control with a microcontroller (MCU), they have to select a control algorithm and then choose the best MCU to run it. Various technical resources have been analyzed to wrap up a design selection approach for BLDC motor control.
Since the late 1980's new design concepts of brushless DC motors has been commercial. The economic constraints and new standards legislated by governments place increasingly stringent requirements on electrical systems. Present day equipment must have higher performance such as better efficiency and reduced electromagnetic interference. System flexibility must be high to ease market modifications and to reduce development time. All these enhancements must be achieved while, at the same time, reducing system cost.
Brushless DC motor technology makes it possible to achieve these specifications. These motors combine high reliability with high efficiency, and for a lower cost. With improvements in silicon technology, design techniques and packaging the overall cost effectiveness of the BLDC motor solution is matching or exceeding brush DC motor solutions. Also the invention of modern solid state devices like MOSFET, IGBT and high energy have widen the application scope of BLDC motors.
Because of their increased use, there is a consequent need for low-cost methods to control them. BLDC motors are used in consumer electronics applications such as power tools and air conditioning units, in transportation vehicles such as electric scooters and bicycles, and in industrial machines that are replacing multiple brushed DC, AC, and universal motors with electronically controlled BLDC motors. (BLDC) motors are rapidly gaining popularity. BLDC motors are used in industries such as Appliances, HVAC industry, medical, electric traction, road vehicles, aircrafts, military equipment, hard disk drive, etc.
To drive these motors, many manufacturer offer new controller family and solutions, specifically designed for the needs of motor control. In a single chip solution, these devices combine a (DSP core) with microcontroller peripherals. These components are able to perform sophisticated control schemes as well as efficient algorithms. This paper illustrates the general selection of MCU's / Control Algorithm for Brushless DC Motor (BLDC) control with specific automotive applications.
CHAPTER 1
BLDC - CONTROL DESIGN REQUIREMENTS (Y.R.Sashikumar)
1.1 Introduction
Applications for brushless DC motors have increased significantly in recent years. Performance and construction advantages over other industrial motors like efficiency, response time, speed to torque characteristics are significant. Apart from these, brushless DC motors have other salient features like low emissions, low acoustics noise, "on demand operation" which are heading them to GO GREEN.
Continuing improvements in power semiconductors and controller IC's as well as the permanent-magnet brushless motor production have made it possible to manufacture reliable cost-effective solutions for a broad range of adjustable speed applications.
Usually, BLDC motor control requires Microcontroller based electronic control for commutation. MCU must make available required resources, in particular enough computing bandwidth to execute control algorithm, sensor interface, and interface to the power driving circuits. As a system designer it is necessary to select the best combination of control algorithm and MCU, satisfying the performance and cost budget. The information presented in this chapter is intended to aid the process of identifying optimum solutions.
1.2 Challenges for Selecting BLDC Motor Control
BLDC motor applications have risen over time due to its cost effectiveness.
Cost effectiveness can be achieved to a great extent based on the design solution.
BLDC motor control methods can come in various forms;
Figure 1.1: (Courtesy Freescale Technology)
Using sensor feedback - Sensors are used for providing a commutation signal and position information.
Sensorless- Back EMF method used to measure the rotor position when the motor is in free phase.
Without using above techniques another method for measurement is using a motor with digital encoder or resolver for obtaining position information and a tachometer for speed detection.
For efficient and optimal use of BLDC motors which can be cost effective, proper selection of microcontrollers play a major role.
Some of the criteria that need to be considered for MCU selection are listed below:
Number of pulse width modulation (PWM) outputs
Type of PWM waveforms
Number of ADC channels
Simultaneous AD conversions
Total number of pins
Number of emergency shutdown pins, interrupt pins, and sensor input pins
Timers for sensors
ADC range and sensitivity
CPU bandwidth on control type
Code size for flash and RAM
A more detailed understanding can be obtained from the below flow chart.
Figure 1.2 (Courtesy Microchip)
Various control algorithms are available based on study done by Renesas [1].
Each of the methods has different MCU resources and CPU bandwidth requirement.
The various methods are as listed below:
- Six-step trapezoidal with Hall sensors
- Six-step trapezoidal with back-EMF commutation
- Sinusoidal control by open loop (V/f)
- Sinusoidal control with closed speed loop and speed sensor
- Vector control with encoder
- Vector control without encoder (two current measurements)
- Vector control with one-shunt current detection
A table indicating the conclusion for comparison [1] of control methods in terms of CPU bandwidth and approximate costs is listed below.
S.No.
Control Method
Comments
1
6-step Trapezoidal with Hall sensors
Good for constant load; control has torque ripple
2
6-step Trapezoidal with back-EMF commutation
Good for constant load; control has torque ripple
3
Sinusoidal control by open loop (V/f)
Smooth control; constant load
4
Sinusoidal control with closed speed loop with speed sensor
Smooth and accurate control
5
Vector control with encoder
Very accurate control and good dynamic performance; known as best control method
6
Vector control without encoder
Accurate control & good dynamic performance; requires more CPU computing
7
Vector control with one shunt current detection
Accurate control & good dynamic performance; requires more CPU computing
Above can be summarised as:
6-step trapezoidal control:
In this method the current loop, commutation switching and speed loop tasks are speed-dependent, maximum CPU bandwidth is thus required when the motor is running at its highest speed.
Sinusoidal control method
The carrier frequency selection plays an important role in CPU bandwidth selection. Higher the frequency, more the CPU bandwidth required. Carrier frequency can be decided based upon the performance of control method during motor operation.
Vector control methods
The CPU bandwidth is proportional to the current loop which varies depending on system performance.
If speed sensors are used additional bandwidth is required but this will be considerably less. Control system performance will be better with sensors but may be a bit expensive for some applications.
1.3 Improvisation
Back EMF method has a duty cycle limitation as it requires high switching during PWM off-time to do the detection of back EMF. This limitation can be eliminated by sensing the back EMF during PWM on-time high side switching. Both of the above configurations can be used to derive at an optimal system solution.
Sensor based control algorithm uses minimum CPU resources for detection and control as compared to the sensorless control algorithm. This is because in sensor based control specialized hardware is being used and detection can begin at zero rpm itself.
BLDC motor control is best using hall sensors because more CPU resources are available for performing other tasks unlike sensorless control.
Further maximum speed can be attained using sensors as time taken for calculating the control outputs is reduced.
The selection of control algorithm should thus be based on total system cost and desired performance output.
MCU OR DSP?
MCU and DSP controllers both offer the same features.
Correct selection of controller and control algorithm purely depends upon the designer based on the control application wherein the processor is being used and execution speed required.
In general for open loop controls or systems used for controlling speed or position MCU's are the best choice in terms of cost effectiveness and performance.
For applications which involve high speed with complex motor construction, one MCU may not be sufficient. In such a scenario a DSP controller is preferred.
Apart from this for closed loop control applications and high speed motors DSP controllers are a preferred choice. DSP controllers also offer high response time.
Whichever is the controller or algorithm proper selection by designer plays a key role for client and customer benefits.
1.4 Summary
The Application where the motor is being used demands the control requirement
Some typical examples of application and control algorithm are:
Speed Control - 6 step trapezoidal method
Position control - Sinusoidal method
Torque control - Vector Control Method
Application environment & other factors which plays a key role in selecting the controller and algorithm are listed below:
Cost / Budget of project
Development Platform
Power requirements
EMC requirements
Application level communication protocol
Temperature
Size & Weight of motor and controller unit
References
[1] MCU Performance for Various Control Algorithms of BLDC Motors by Kevin King , Robert Proctor , Huangsheng Xu PhD and Yashvant Jani PhD , Renesas Technology America Inc.
CHAPTER 2
BLDC - Sensor Based Control Applications (Lee Shang Ping)
2.1 What is Sensor-based Control?
Sensor-based control of BLDC motors refers to the use of Hall-effect sensors (and sometimes, optical encoders too) to measure the speed and relative position of the rotor with respect to the stator (the other is sensorless control, which make use of the back e.m.f across the un-driven stator terminal)
To better understand sensor-based control, it is important to first study the structures and working principles of BLDC motor and also the sensing techniques.
2.2 BLDC Motor - How does it Work?
A BLDC motor has three important components: the rotor, the stator and the Hall-effect sensors. The functionality of each of these components is described as follows.
Structures of BLDC Motor
The rotor of a brushless dc motor consists of permanent magnet pole pairs. Each pole pair contributes an N-S magnetic field. On the stator is 3-phase electrical winding, with either slot or slot less configuration. Each phase winding usually consists of several full-pitch coils adjacent to each other. Figure 2.1 below depicts a 12-slot, 2 pole pair motor.
Figure 2.1: A BLDC with 12 slots and 2 pole-pair
Notice that in this configuration, there are four slots per phase, a1A1 and a2A2 being the two coils of phase A.
Hall-effect Sensors
Three Hall-effect sensors, which generate three electrical trains of pulses when detecting change in magnetic field, are embedded within the motor enclosure and located around the permanent magnets 120o electrical degree apart. Therefore as the motor rotates, the three pulses generated are also phase shifted by 120o. Figure 2.2 shows the output of Hall-effect sensors.
0o 60o 120o 180o 240o 300o 360o
Hall A
Hall C
Hall B
Figure 2.2: Output of the 3 Hall-effect sensors
Phase Commutation
BLDC motor works on the principle of phase commutation of an inverter circuit which is triggered by digital signals, typically the Hall-effect sensors. The stator phase windings of the motor are connected to an inverter circuit on the controller board. The output of the Hall-effect sensors are fed to a timing and base drive circuit and based on a pre-defined look-up table, the inverter's transistors fire in sequence and hence rotate the motor. Figure 2.3 presents the commutation look-up table for clockwise rotation of the motor.
Figure 2.3: Commutation look-up table
TAH, TBH, TCH are the high leg transistors in the 3-phase inverter. A '1' denotes the transistor turns on and a '0' denotes it turns off. HA, HB and HC are the Hall-effect sensor signals.
Optical Encoder
Optical encoder is not an essential part of the sensorless BLDC control system, however it is usually included (attached) with the motor for the purpose of motor speed measurement. Usually there will be 2-channel digital outputs which generate trains of square pulses as the motor rotates. Optical encoder is used in application for high precision speed control.
2.3 The Complete System
The typical system diagram of the BLDC motor with embedded controller is shown in Figure 2.4.
QEP /
Capture
Encoder (channel A)
Encoder (channel B)
Figure 2.4: The system block diagram of BLDC control
Control Loop
A generic control loop of a motor can be illustrated in Figure 2.5.
Figure 2.5: Various control loop configuration (top to bottom): close-loop with speed PI controller; Outer speed PI controller provides current demand for inner current PID; open-loop; close-loop with only current PI controller
The main components are:
1. Sensing:
Current sensing: The current is usually sensed by using an analog-to-digital converter (ADC) on the embedded controller.
Speed sensing: This is usually done by using the output signals from the optical encoder. The embedded controller should be able to capture the digital pulse trains from the encoder and count the number of pulses within a pre-determined period of time.
Position sensing: The output signals from the Hall-effect sensor determines the current position of the rotor. It is this signal which prompts the commutation
2. Feedback controller:
Speed PI controller: The input to the controller is the difference between the reference speed and the speed feedback from the optical encoder, and the output is the activation signals for PWM or a current PI controller (if there is one). The PI algorithm is implemented as difference equations in an embedded controller CPU.
Current PI controller: This is used to control the torque of the motor. In some case the current controller is not implemented. The implementation of PI algorithm by the CPU is also a set of difference equations.
3. Actuation:
Commutation: As discussed previously.
PWM: the firing signals for the inverters are switched on and off at a very high frequency in order to vary the "apparent" output voltage to the motor.
2.4 High Speed Measurement
The speed sampling rate (i.e. sampling the optical encoder) affects the resolution of the result. The reason is that when the motor rotates at high speed, the number of pulses (n) within a fixed period of time (T) would be larger than that of a motor rotating at a low speed.
The higher the number n, the better the "indication" of the speed of the motor is. Assuming an optical encoder of 1024 gratings, and a desired motor speed of 6000rpm. Therefore the expected number of optical encoder pulse is:
1024 x 6000/60 = 102,400 pulses per second
At a speed sampling of 10Hz, the number of pulses per sampling period is 10,240. The speed resolution is therefore
= 0.59rpm
The resolution of 0.59rpm for speed set-point of 6000rpm is reasonably good (0.01% error). However if the desired motor speed is 6rpm (for instance), the error would be 10%. This speed measurement strategy is clearly not good for speed calculation. One possible solution is to reduce the speed sampling rate (say from 10Hz to 1Hz) but this will cause instability as the control loop gets very slow feedback from the speed measurement module. A better method is to use specialized hardware module in the embedded controller - the Capture unit, which will be addressed in the low speed measurement section next.
2.5 Low Speed Measurement
The method above is not accurate for low speed measurement. The reason is that at low speed, the total number of encoder pulses is much less and hence the speed resolution derived from that method is very low.
A different methodology is therefore required to calculate at very low speed. We could make use of a single square pulse and calculate the time elapsed between the rising and the following falling edge. Special hardware module called the Capture unit enables us to do very accurate low speed measurement. It is a module which will automatically log the timer readings at each subsequent rising and falling edge of the encoder signals, without intervention from the CPU (thus reducing the overhead). And since we know that a single pulse correspond to 0.352o (assuming a 1024 gratings optical encoder, 360o/1024 = 0.352o), we could calculate the speed.
Figure 2.6: Low speed measuring methodology
Speed is therefore d/t. This method is particularly accurate for very low speed. In fact, the lower the speed is, the higher the speed resolution because t gets larger as speed is lower.
2.6 Application in Automobile
Sensor-based control of BLDC motors find itself many application in automobile, own to its excellent capability in low speed control. Some examples are:
head-lamp
power windows
windscreen wiper
CHAPTER 3
BLDC - SENSOR-LESS CONTROL (K.P. Ajit Kumar)
3.1 Introduction to Sensor-less control technique
There are several Sensor-less control techniques that have been developed and put into practice in the past. A Permanent Magnet Brushless motor drive that does not use any sensors (Hall sensors/position sensors) for commutation, instead uses the Back EMF of the machine is called a Sensor-less control drive.
The elimination of the sensors (Encoders or Resolvers) from the design results in several advantages such as reliability cost reduction, durability (Lesser Maintenance) and size reduction for variable speed and constant load applications. However, due to the nature of the Back EMF it becomes difficult to use this technique for low speed control and abruptly varying loads.
During the commutation of BLDC motors at any instant of time, only two of the three terminals are excited. The third terminal produces BEMF, and sensing this BEMF provides a low cost solution for the commutation of the motor. The BEMF is zero initially when the motor is standstill and increases with the increase in speed, hence at low speeds since the BEMF signal is not very prominent open loop start up techniques are used. A basic Microcontroller based Sensor-less BEMF control technique is shown in Figure 3.1.
Figure 3.1: Microcontroller based BEMF control technique
As it can be seen from the Figure 3.2, the time elapsed between two successive zero crossings is effectively the time taken for one commutation sector. By continuously detecting the zero crossings the position of the rotor can be detected and hence the full commutation sequence can be obtained.
Figure 3.2: BEMF waveforms (Courtesy: Microchip)
Typically the Sensor-less technique involves a complex hardware circuitry involving several filters, comparators, voltage dividers and other discrete components in order to perform the Zero crossing detection of the BEMF signal. This technique results in a lot of hardware over head accompanied with several disadvantages such as noise, commutation delay, reliability issues and aging etc.
The applications of the BLDC motor vary from soft to hard real time. Sensor-less control is extensively used in applications such as Fuel and Water pumps, HVACs, Engine cooling fans, Active suspension, electrical throttle control, ABS etc. in the Automotive domain. In order to deliver real time responsiveness, control precision, reliability, robustness and high performance the embedded systems have to be carefully scrutinized.
3.2 Digital Signal Processers for Sensor-less Control
The drawbacks of the conventional Analog systems as mentioned are myriad. The use of programmable Microcontrollers has innumerous advantages over the Analog systems. Going even further integrating the standard microcontroller peripherals with a DSP core provides a high performance and cost effective single chip solutions for BLDC motor control.
DSPs enable the implementation of complex control algorithms with minimum loop delay and High resolution. These efficient control strategies will in turn result in drastic reduction in the torque ripple and Harmonics. All these factors when culminate will result in reduction of the BOM and TTM.
The Figure 3.3 shows the TMS320C240 by Texas Instruments as an example of a SOC for motor control.
Figure 3.3: TMS320C240 Architecture (Courtesy: Texas Instruments)
Salient features of this architecture: Texas Instruments [3]
Harvard architecture boosting performance
20 MIPS 16 bit fixed point DSP core
Single cycle execution of MAC operations(Useful for implementation of PID control loops and other complex calculations)
Dedicated peripherals for motor control such as:
Timers and capture compare units for speed calculation
PWM units supporting Symmetric, Asymmetric and space vector modulation, with programmable dead band.
QEP for position and direction sensing of rotor
Two 8 channel, 10 bit ADCs with simultaneous sample/hold
3.3 Typical Sensor-less Application: Automotive Fuel Pump
Pumps are used in a wide range of automotive applications such as fuel/Oil/water pumps. BLDC motors are being used invariably for fuel pumps in spite of their higher production cost, due to the fuel economy improvements they offer. Owing to their Electronic control fuel efficiency is much higher since just the right amount of fuel is pumped in when required.
Embedded systems Requirement Analysis:
Figure 3.4: Automotive Fuel Pump and Controller (Courtesy: Google Images)
Since the motor is usually immersed in the fuel, Sensors have to be discarded from the motor assembly. Hence the Sensor-less control.
All the features of a high performance DSP core with standard motor control peripherals
Typically the operating voltage for fuel pumps is 8v-16v
Communication Interfaces such as LIN, CAN, SPI or I2C are imperative.
Fault detection techniques with PWM disabling for over temperature, over current, over voltage protection and Watch dog timers for software reset.
Minimum delay during open loop start up
Compactness: High integration on a small PCB size
Heat sink and cooling for MOSFETs
3.4 MLX81200-BLDC Motor Controller for Fuel Pumps
The Figure 3.5 shows the MelexisCM Dual Core CPU having separate communication and Application CPUs.
This is a complete SOC solution integrating a LIN transceiver, a Microcontroller and all the standard motor control peripherals. It also supports CAN protocol as the CAN transceiver and Controller can be interfaced externally.
The Dual core CPU has independent register sets that can handle the LIN communication protocol and the motor control as two distinct tasks without any interference from each other.
This kind of a Dual core system performs the functions of an RTOS without having to incur the cost and complexity of one.
Figure 3.5: MLX81200 Architecture (Courtesy: Melexis)
3.5 An RTOS based Motor Control Application
System Overview:
The Figure 3.6 shows an RTOS based Robotic Arm controller architecture.
The system consists of several DC motors, Servo motors, Communication support through Ethernet and SPI.
The Hardware which consists of the DC and servo motor controllers, hand held device controller (SPI peripheral), Ethernet peripheral device is designed on a Cyclone II Altera FPGA.
Figure 3.6: Robotic Arm controller architecture (Courtesy: Altera)
The software consists of the uC/OS-II RTOS which runs on a NiOS-II soft core. The RTOS basically implements the protocol stack for TCP/IP, creates packets for SPI and Ethernet and also implements various Device drivers.
The OS supports all the functions required by the high level code. The motor control software receives commands such as direction and velocity from the High level code and generates the required pulses to drive the motor.
This kind of a system is much more complex than a fuel pump controller. Each of the individual CPU has to generate control signals to control the motor, at the same time communicate with each other and also receive signals from the Master controller.
The Conventional systems with multi core CPUs will be able to handle so many tasks in parallel with synchronization of movements. There will be multitude of issues such as complexity of design, unsynchronized movements, time delays etc. And hence it is imperative to use RTOS for such complicated systems.
3.6 Summary
Sensor-less control techniques for BLDC motor control have their pros and cons. Hence the decision for choosing a control technique should depend on several factors such as:
The application type:
Fuel Pumps cannot work with sensors and low speed applications cannot use Sensor-less technique
Sensor-less is best suited for constant load applications
Cost and TTM: Sensor-less is cost effective and also lesser TTM
Size: Elimination of Sensors reduces the mechanical package size
DSPs are very powerful in dealing with real world signals (Voltage/Current) and are high performance engines capable of implementing complex algorithms efficiently. A combination of a DSP core with robust motor control peripherals results in complete system for Sensor-less control (Eg: Hybrid and Electric vehicles).
Multi-core processors can be used in order to achieve the functionalities of a RTOS in systems which are not hard real time (eg: Fuel Pumps) and the number of tasks are limited (i.e Motor Control and Communication).
For Complex Systems which demand Real time response, Multitasking, synchronization and Reliability, a RTOS is imperative (Eg: Robotic arms in Aircrafts).
References
[3] Microchip Technology Inc., Using dsPIC for Sensorless BLDC control
AN901 Application notes, 2004
Texas Instruments, DSP Solutions for BLDC motors BPRA055.pdf, 1997
Melexis, MLX81200.pdf, 2008
NiOS II Embedded Processor design contest-Outstanding Designs, 2006
CHAPTER 4
RECENT TRENDS - (K.V. Nishin)
4.1 FPGA Control of BLDC Motors
4.1.1 Introduction:
For a long time the motor control involved in industrial and automotive applications mainly used microcontrollers for the control. Also the decreasing costs of microcontrollers made it possible to have good motor control with certain limitations at lower prices. However, on the other hand the complexity involved in motor control and its algorithms is gradually increasing, putting more demand on the microcontroller to provide more features and enhanced performance. Hence the focus shifted to the Field Programmable Gate Arrays (FPGA). This section gives an insight about the role of FPGA in motor control.
4.1.2 Why consider FPGA for motor control?
FPGAs are devices which are known for their flexibility and ability to be reconfigured on the field. The microcontrollers are available with hardware which cannot be modified later, i.e. it is not flexible. Performance enhancement is bounded to software. FPGA consists of several logic blocks which can be designed individually to obtain the necessary interface or functionality, which then can be easily integrated into a single chip thus providing a System-on-Chip architecture.
Even though initially the large scale production of FPGAs were costly, it is now been reduced to an acceptable value due to advancements in technology. But developing these modules from the scratch is very time consuming and will not make the use of FPGAs any beneficial.
The various modules are available in the form of Intellectual Property (IP), which can be readily used thus easing the motor control design phase and shortening the time to market (TTM). Advanced tools are readily available that facilitate the easy integration of the various modules. Also the PWM modules and other modules involving signal processing can be modified or already available so as to fit the needs of the required control algorithm to provide more precise control.
The various control algorithms are also directly implemented in the hardware (already available as IP), which in turn makes the calculations involved to become faster as dedicated parallel architectures can be created within the FPGA. This will greatly reduce execution time when compared to that involved in MCUs.
Commutation
Block
PWM
Block
Communication
Block
FPGA
Motor Control
Block
Processor
Block
I/O Block
Figure 4.1: Basic FPGA motor control system with the various blocks
The above figure shows the basic FPGA used for motor control, depicting the various blocks that are present integrated on a single chip. The various blocks are generally implemented in any of the hardware description language such as VHDL, Verilog HDL etc. There are several tools provided by the FPGA vendors with enhanced GUI which ease the development and integration of the various blocks. The designer can use these tools to integrate and simulate the various modules and check if the desired results and fine tune them to increase the performance. The below figure depicts one such PWM module provided by the tool. It basically consists of a comparator and timer that are used to provide the required duty cycle and the period. The timer can be dynamically reconfigured to modify the range of the PWM period.
Figure 4.2: PWM block (Source Ref [4]*)
It has been observed that using customized FPGA based PWMs led to a 50% reduction in the total harmonic distortion when compared to a DSP or a MCU. This is mainly due to the fact that the switching losses are much lesser in a FPGA due to the efficient parallel implementation of the various control algorithms. Its performance is nearly as good as that of the analog controllers thus making it more favorable for motor control.
Another feature of FPGA is the possibility of the mixed signal FPGAs in which various analog signals can be handled and manipulated by an analog module within the FPGA. These analog signals will be digitized by an ADC module within the FPGA thus providing the digital components with their inputs.
4.1.3 Support for Communication:
This section gives a brief idea about the communication support that has to be provided by the BLDC controllers taking in consideration both the FPGAs and other controllers. For BLDC controllers used for industrial applications the controllers need to have support for various industrial bus standards such as Ethernet, Profinet, and Devicenet etc.
In automobiles, the entire system is currently highly distributed with ECUs spread out across the body of the automobile. Hence the need for reduction of intensive wiring led to the demand for a high speed communication network with less wiring, which is met by the two intelligent protocols namely Controller Area Network (CAN) and Local Interconnect Network (LIN). Hence the BLDC motor controllers used in automobiles must come with support for either of these protocols. The interfaces for these protocols can be easily implemented while using a FPGA. The following table gives an idea of the differences between the two protocols and their applications with reference to a BLDC controller in an automobile.
CAN
LIN
Speed
1.0 MBPS for a distance of 40m with maximum 32 nodes
20 KBPS for a distance of 40m with maximum 16 nodes
Wire
Two wire line
Single wire
Data Field
8 bytes maximum
8 bytes maximum
Communication
Multi-Master
Single-Master
Applications
Used for more critical applications such as electric traction, power steering and fuel pumps
Used for less critical applications such as wiper control, power windows, seat adjustment
4.1.4 Summary:
With flexibility and life time of a design becoming critical design considerations, there is a definite shift to FPGA for various applications. BLDC motor control is definitely one among them. The control algorithms are becoming complex and efficient, thus parallel execution is required for reducing the execution time of these algorithms. But there is still hesitation while considering FPGA as a solution, because of the belief that the software solutions are tried and tested, less complicated. However the vendors are coming up with highly simplified, interactive design tools and IPs that make the task of a motor control designer much easier. The designer has to like any other development has to carefully choose the IP which best suites his design considering the proper methodology and application requirements.
4.2 - Reference Designs and Platforms
4.2.1 Introduction:
While creating any application, one of the most critical phase is the verification and validation of the application. This phase will even lead to optimizations in the design thus making it more important. The semiconductor manufacturers have taken this into consideration and trying their best to provide the best possible platforms for the evaluation and testing of various motor control solutions. Such platforms and designs are referred to as Reference platform or design.
4.2.2 Brief Description of the reference platform:
The reference platform is made up of three components - the power stage component, the isolation component and the controller component. There are two types of the power stage components, one the Low Voltage Component which is a part of the platform that are used for mainly automotive application, and the High voltage component that is used for the industrial applications. Power isolation basically isolates the higher voltage components from the controller and the communications interfaces.
4.2.3 Reference Design libraries and GUIs:
The reference platform comes along with pre-loaded libraries/ software which contain the implementation of the various control algorithms. The designer can choose the motor control library which suits his application and develop it to efficiently meet his required specifications, rather than developing it from scratch. Certain semiconductor manufacturers are competing to provide the best solution for a particular algorithm so the entire motor control unit can be taken directly from off the shelf and used for a particular application, but it does come at a price.
Another main feature of the reference platforms is the Graphical User Interface (GUI). The GUI allows the designer to enter the various input parameters to test the various motor control solutions. They monitor the various output parameters at real time, and through the communication interfaces. The designer can keep track of the various parameters such as the values of speed, direction, temperature, PWM duty cycle, control loop parameters, current, voltage and can also view the various waveforms corresponding to the parameters. This becomes very essential to verify the application and also makes it easy to debug in the case of any unwarranted behavior.
Further the reference platform also plays a vital role in the transfer of knowledge within designers. The beginners can easily understand the various motor control algorithms with the help of the reference platforms. This will eliminate the risk of the increase in cost incurred due to training of the resources within an industry.
4.2.4 Summary:
Semiconductor manufacturers are coming out with the best reference platforms and GUIs that the designer can utilize to develop his application with ease and less turnaround. They have acknowledged the fact that reference platforms does play a role in shortening the time to market (TTM) and reducing the costs of a BLDC motor control application. The designer while choosing a particular controller for his application will have to now consider not only performance criteria of the controller alone, but certainly keep in mind the reference platform, libraries and GUIs that come as a package with it. Only then he will able to leverage the TTM, cost and performance
