CHAPTER 5
Using MCUs/DSPs to Increase Sensor IQ
Backed by an increasingly powerful array of solid-state process technologies, integrated sensors are expected to be widely applied to extend microcomputer-based
control in a variety of areas.
—Kensall D. Wise, 1982 [1]
5.1
Introduction
Several semiconductor technologies are available to improve the accuracy and quality of the measurements and to add diagnostics and other intelligence to any type
of sensor. Foremost among these technologies are MCUs, DSPs, DSCs, ASICs, and
FPGAs. Dedicated sensor signal processors are usually adaptations of one of these
approaches. Some of these technologies also have the potential to allow for a fully
integrated (monolithic) smart sensor. Before taking this step, it is important to understand the technologies that are available, their contribution to smart sensors,
and their ability to provide a higher level of intelligence (and value) to sensors.
5.1.1 Other IC Technologies
ASIC technology utilizes computer aided design (CAD) software tools to achieve
custom circuit designs. ASIC technology consists of programmable logic devices
(PLDs) for low-circuit density, gate arrays for medium density, and standard cells
for high-end custom circuits. ASIC devices combine high density and integration
of full custom designs with relatively low cost and fast design turn-around. A
custom highly-integrated chip utilizing core microprocessor cells, combined with
analog, memory, and additional logic functions, can address specific sensing requirements, such as fluid level sensing. Mixed-signal ASICs combine analog with
digital capability.
Field-programmable gate arrays (FPGAs) and field-programmable analog arrays (FPAA), analog versions of FPGAs, are attractive as sensor interfaces because
they can minimize development time and they can be reconfigured after they have
been in service. Both the FPGA and FPAA use a front-end circuit design program
[2]. A circuit design is transferred to the FPGA (or FPAA) by either downloading
converted serial data directly to the on-chip static random access memory (RAM)
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Using MCUs/DSPs to Increase Sensor IQ
in the FPGA or to the serial EPROM. A digital core incorporated in the FPGA design gives it the same kind of computing capability as an MCU with the advantages
of field programmability. FPGAs are especially useful when rapid circuit prototyping and flexibility are required.
The term system on a chip (SOC or SoC) is frequently used to describe a highly
integrated circuit, ASIC, MCU, DSP, or DSC that incorporates considerably more
hardware options than previously available versions. These chips frequently incorporate application-specific software that is closely linked to the hardware that is
on the chip. These chips include a large and increasing amount of the system, and
reduce they the total chip count. In only the more simple systems are they actually
the whole system. This is especially true with the sensor portion of the system. The
added complexity of adding the sensor to the SOC makes a sensor system on a
chip more difficult but the difficulty is minimized with CMOS compatible MEMS
processes.
5.1.2 Logic Requirements
The shift of the logic requirements from a centralized computer to nodes in decentralized systems is creating the need for smart sensors. Sensor-driven process control
systems that eliminate human operators and increase the precision of the process
will play an important role in the manufacturing of the semiconductors that control
them. Essential aspects of any sensor system include amplification, A/D conversion, a communications interface, and the computing portion. Amplification and
A/D conversion were discussed in Chapter 4. The communications interface will be
covered in Chapter 7. This chapter will use existing MCU, DSP, DSC, and FPGA
products to demonstrate the remaining elements.
5.2
MCU Control
Single-chip MCUs combine microprocessor unit (MPU) computing capability, various forms of memory, a clock oscillator, and I/O capability on a monolithic structure as shown in Figure 5.1 [3]. MCUs provide flexibility and quick time-to-market
for numerous embedded control systems and for smarter sensing solutions. The
programmability and wide variety of peripheral options available in the microcontroller provide design options. These options can offset the cost of the additional
circuitry by eliminating other components or by providing features that would otherwise require far more components. In addition, high-volume MCUs enable systems to achieve low cost, high quality, and excellent reliability.
To provide increasingly higher performance without sacrificing excessive power consumption, many suppliers offer MCUs with more than one core. The cores
can either be identical or different. With their higher capability, multicore MCUs
typically target more complex system controls. Within the overall control strategy,
a sensor (or multiple sensors that need their data measured and analyzed with tight
constraints) can take advantage of multicore MCUs.
5.3
MCUs for Sensor Interface
87
Figure 5.1 Basic microcontroller block diagram.
5.3
MCUs for Sensor Interface
In addition to the basic features of a microcontroller, a number of custom modules
are integrated on the same chip in order to increase the utilization of the process,
reduce printed circuit board space, and increase the functionality for a specific
application. MCU features that have a significant impact on sensor system performance will be discussed in this section. These include analog input capabilities, A/D
conversion techniques, processing bandwidth, on-board memory, power conservation, and improved electromagnetic compatibility (EMC) and control of radio frequency interference (RFI). The same features, possibly with different specifications,
perform similarly on 8-bit families of MCUs and higher performance 16-bit and
32-bit products as well.
5.3.1 Peripherals
Existing MCU technology contains a variety of peripherals or hardware options
that enhance the capability of the MCU. Peripherals enable the MCU to obtain
information from sensors and control output devices. Some of the most common
peripherals are general purpose input/output (I/O) ports, timers, and serial ports.
Timers usually measure time relative to the internal clock on the chip or an
externally provided clock signal. An on-chip oscillator that operates up to 4.0 MHz
at 5V or 1 MHz at 3V controls the clock on the chip. A more complex timer can
generate one or more PWM (pulse width modulated) signals, measure the pulse
width, and generate additional output pulse trains.
Three basic serial ports are the serial communications interface (SCI), the serial peripheral interface (SPI) and the Inter-Integrated Circuit (I2C) bus. The SCI
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Using MCUs/DSPs to Increase Sensor IQ
is a simple 2-pin interface that operates asynchronously. Data is transmitted on
one pin and received on the other. Start and stop bits synchronize communications
between two devices. The SCI port is a universal asynchronous receiver transmitter (UART) that can be used with an RS-232 level translator to communicate with
personal or other types of computers over fairly long distances.
The SPI port requires a third pin to provide the synchronizing signal between
the control chip and an external peripheral. This type of communication is usually
on the same board. Standard SPI peripherals are available from many manufacturers and include A/D converters, display drivers, electrically erasable programmable
ROM (EEPROM), and shift registers.
The I2C bus is a patented interface developed by NXP Semiconductors (formerly Philips Semiconductors) [4]. The half-duplex, synchronous, multimaster bus
requires only two wires to transmit data (SDA) and clock (SCL) signals. The master
communicates with individual slaves by using a 7-bit or 10-bit address. Initially defined with a maximum of 100 kbit per second (standard), a 400 kbit fast-mode and
high-speed 3.4 Mbit option are now available, as well as a fast-mode plus transfer
rate between the latter two.
5.3.2 Memory
Various types of memory can be integrated on a chip, including RAM, ROM,
EPROM, EEPROM, and flash memory. Semiconductor memory is based on a single
transistor or cell that is on or off to generate a bit that is either a one or a zero.
Memory is classified as either volatile or nonvolatile. Volatile memory is not stored
when the power is disconnected to the MCU. Nonvolatile memory is stored when
power is disconnected. The amount of memory in a chip is usually rated in kilobytes
(1 KB = 1024 bits). Increasing the amount of memory increases the chip size and the
chip cost. Some types of memory, such as EEPROM, can significantly increase the
process complexity and also add to the cost.
Random access memory (RAM) can be read or written (changed) by the central
processing unit (CPU) and is volatile [3]. Read only memory (ROM) can be read
but not changed. This nonvolatile memory is included in the design (masked layout)
of the chip. Reprogramming a chip once it has been designed is a common practice
to correct errors in the original software, to upgrade in order to improve system
performance, or to adjust for variation that could have occurred since the system
was initially installed. Erasable programmable ROM (EPROM) can be changed by
erasing the contents with an ultraviolet light and then reprogramming new values.
This nonvolatile memory has a limited number of erasure and reprogramming operations. One-time programmable ROM (OTP ROM) is the same as EPROM, except that it is packaged in a lower cost opaque package. Since ultraviolet light cannot penetrate the package, this memory cannot be erased after it is programmed.
Electrically erasable programmable ROM (EEPROM), and frequently E2ROM, is
a nonvolatile memory that can be changed by using electrical signals. Typically, an
EEPROM location can be erased and reprogrammed thousands of times before it
wears out due to field stress.
The most common memory for control applications is flash memory. Nonvolatile flash memory is easily reprogrammed in the application and is done faster than
EEPROM. Once it is programmed, flash memory contents remain intact until an
5.3
MCUs for Sensor Interface
89
erase cycle is initiated by the software. Program and erase voltages for EEPROM
and flash are performed at approximately 12V.
Two of the newest memory types are ferroelectric random-access memory (FeRAM or FRAM) and magnetoresistive random-access memory (MRAM). Both can
be embedded in controllers. Unlike FeRAM, which is based on charge, MRAM
uses the magnetic properties of materials. Table 5.1 compares four different types
of memory [5].
The ferroelectric effect is the tendency of dipoles within a crystal to align in
the presence of an electric field and to remain polarized after the field is removed
[6]. Reversing the field causes polarization in the opposite direction. No current is
required to maintain either state, which provides a binary memory capacitor with
low power consumption. Advantages of FeRAM for sensing applications include:
•
Very fast write times (up to 20 times faster than EEPROM;
•
Write/erase endurance up to 10 million times greater than EEPROM;
•
Arrays up to eight times larger than prior versions;
•
Lower voltage, lower power operation to conserve battery life.
One company has developed its MRAM process specifically for integration in
SOC products, such as the combination of microcontrollers and MRAM on one
chip [7]. MRAM can replace flash, EEPROM, and SRAM with a single nonvolatile
fast memory with essentially unlimited endurance. Using a few added mask steps,
MRAM can be embedded in the last two metal layers of standard CMOS logic
processes.
5.3.3 Input/Output
Input/output (I/O) is a special type of memory that senses or changes based on
external digital elements and not the CPU [3]. I/O ports connect these external elements to the CPU and provide control capability for the system. I/O can be either
parallel, transferring eight data bits at a time to the MCU, or serial, transferring
data one bit at a time.
Table 5.1 Comparison of Semiconductor Memories
Property/Design
DRAM
Flash
FeRAM
MRAM
Nonvolatility
No
Yes
Yes
Yes
Storage layer
Capacitor
Floating gate
Capacitor
Magnetic tunnel junction
Storage type
Charge
Charge
Polarization
Resistance
Data retention
0
10 yr
10 yr
10 yr
Write time
50 ns
1–2 μs
50–100 ns
10–50 ns
Read time
50 ns
20–110 ns
50–100 ns
10–50 ns
Cell size (relative) 1
0.8
1.3
<1
Endurance
10^5
10^12 – 10^15
10^12
(After: [5].)
10^15
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Using MCUs/DSPs to Increase Sensor IQ
General purpose I/O connections (pins) can either be used as an input or an
output. A number of pins is typically grouped together and called a port. The program determines the function of each pin. Program instructions evaluate the logic
state of each input and drive outputs to logic one or zero in order to implement the
control strategy. Input-capture and output-compare functions in the MCU simplify
the design of the control strategy.
Input-capture is used to record the time that an event occurred. By recording
the time for successive edges on an input signal, software can determine the period
and/or the pulse width of the signal. Two successive edges of the same polarity are
captured to measure a period. Two alternate polarity edges are captured to measure
a pulse width [8].
Output-compare is used to program an action at a specified time. For example,
an output is generated when the output-compare register matches the value of a
16-bit counter. Specific duration pulses and time-delay are easy to implement with
this function.
5.3.4 On-Board A/D Conversion
Various types of ADCs were discussed in Chapter 4. An ADC is frequently integrated with the MCU. For MCUs, the successive approximation register (SAR) is
the most popular method of performing A/D conversions due to its fast conversion
speed and ease of use with multiplexed input signals. An 8-bit ADC in 8-bit MCUs
has a theoretical resolution of about 0.39%.
For those instances where higher resolution is required, the SPI port of an
MCU allows external circuitry to be interfaced. For example, an integrated circuit
such as Linear Technologies’ LTC1290 connected to the SPI clock, data in, data
out, and one additional programmable output pin of an MCU provides a 4-wire
interface for a 12-bit data conversion. The data are transferred in two 8-bit shifts to
the MCU in 40 μs. By adding the 12-bit capability, the resolution is improved from
0.39% to 0.0244%. Many modern 8-bit MCUs have higher resolution ADCs, including 10-bit, 12-bit, and even two independent 16-bit SARs.
A 32-bit MCU demonstrates the additional capability and flexibility of higherperformance controllers. Designed to address the touch-screen controller (TSC)
requirements of consumer electronic products, Freescale Semiconductor’s i.MX25
multimedia applications processor has an embedded 12-bit successive-approximation ADC. Figure 5.2 shows the clock diagram for generating the clock to the ADC.
To eliminate the complexity of a multiclock domain, the ADC module uses
only one root clock generated from the i.MX25 IPG clock. The i.MX25’s IPG root
clock is typically 66.67 MHz, but in low-power mode, it can be reduced to 33.33
MHz or 16.66 MHz. Also, the clock control module (CCM), can gate the ADC
module root clock on or off or the ADC clock can be gated off within the ADC
module.
5.3.5 Power Saving Capability
An advantage of the combination of MCU hardware and software is a variety of
power saving approaches. Varying the processing speed or stopping processing
5.3
MCUs for Sensor Interface
91
Figure 5.2 ADC clock generation for the i.MX25 multimedia applications processor. (© Freescale, Inc. Used
with permission [9].)
altogether can have a significant impact on overall power consumption. In addition, the ability to operate at lower voltages also reduces the power consumption.
Reducing the power consumption involves more than reducing the supply current
while running processor code. For example, extending the life of battery-powered
sensors and other circuitry requires keeping the average current consumption as
low as possible [10]. As show in Figure 5.3, through short activation time for periodic measurements, an application can draw much more current and still have
the average current consumption remain quite low and very close to the standby
current level.
Figure 5.3 The average current consumption increases only 1 µA with 1 mA activity for 1 ms.
(Courtesy of Texas Instruments [10].)
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Using MCUs/DSPs to Increase Sensor IQ
5.3.6 Local Voltage or Current Regulation
On-board voltage or current regulation is important to sensors that are not ratiometric since the variation in supply voltage over a –40°C to 125°C operating range
can be greater than ±5%. The availability of analog control circuitry with high voltage (e.g., 40V or higher) standoff capability allows the integration of a series pass
5V regulator on the MCU [11]. Availability of a similar shunt regulator allows a
two-wire self-protected and self-powered system to be designed using only a sensor
and an MCU. At higher levels of integration, such as analog voltage and/or current
regulation, can both reduce component count and improve accuracy. Furthermore,
these regulation schemes can be dynamically altered to improve functionality or
reduce power consumption.
5.4
DSP Control
DSPs have a hardware arithmetic capability that allows the real-time execution of
feedback filter algorithms. In contrast, MCUs use look-up tables to approximate
filter algorithms with inherent limitations of flexibility and accuracy. A DSP that
executes instructions in less than 100 ns allows a peak execution rate of 20 millions
of instructions (or integer operations) per second (MIPS). DSPs are also rated in
millions of operations per second (MOPS), where the MOPS rating is several times
the MIPS rating.
Initial distinguishing characteristics of DSPs include a multiplier or multiply accumulator (MAC) for arithmetic calculations and floating-point unit processing for
high dynamic range. However, this has changed over the years. Fixed-point DSPs
are quite common today. While many DSPs address high processing power, some
also target low-power, cost-sensitive applications, such as portable products [12].
With performance up to 300 MHz for 600 MIPS, Texas Instruments’s C5000 DSP
platform provides low power consumption, a high level of peripheral integration,
and large on-chip memory to reduce overall system cost. The fixed-point 16-bit
DSP includes:
•
Total active core power at less than 0.15 mW/MHz at 1.05V;
•
1–3 low-dropout regulators (LDOs) enable integrated power management;
•
Standby power at less than 0.15 mW;
•
On-chip memory options ranging from 64 KB to 320 KB.
The need for real-time processing in several systems dictates the need for DSP
technology for that portion of the control function. This growing class of functions cannot work effectively with traditional table look-up and interpolate functions to make the control decision. Instead, the MAC unit allows state estimator
functions to be implemented with an algorithm defining the state. However, MCUs
historically excelled at system control, especially related to timing and sequencing
operations. With the increasing need for the capabilities of both an MCU and a
DSP, the line between the two has somewhat blurred. For example, Analog Devices
Blackfin 16/32-bit processor family is classified both as an MCU and a DSP. The
family combines a 32-bit reduced instruction set computing (RISC)-like instruction
5.4
DSP Control
93
set to perform smaller number of instructions at higher speeds and dual 16-bit
MAC [13].
Many devices combine an MCU core with a DSP core, such as Texas Instruments’s DaVinci TMS320DM644x and TMS320DM646x, which are both DSPbased devices that are optimized for video/display applications with an ARM9
processor for control functions. The use of the MCU versus the DSP portion can
impact the performance of an integrated MCU-DSP. For example, Infineon’s 32bit TriCore MCU-DSP with a 100 MHz core has a sustained 130 MIPs rating and
delivers 80 MCU MIPs plus 50 DSP MIPs, or 40 MCU MIPs plus 90 DSP MIPs,
depending on the implementation of load sharing in software [14].
5.4.1 Digital Signal Controllers
DSCs are another evolution of DSP technology. In contrast to DSPs that address
high-speed processing, DSCs typically target low-speed processing. I/O specific peripherals in DSCs allow them to address sensing requirements in consumer electronics and motor control applications. Definitions of the capabilities of DSCs
vary from supplier to supplier. Texas Instruments defines DSCs as “processors that
combine the high-performance math and algorithmic capabilities of a DSP with
the peripheral, memory integration and ease-of use of traditional microcontrollers
(MCUs)” [15].
DSCs have become very popular for computationally-intense sensing applications. Using DSCs, engineers can more efficiently perform many system-level
tasks. These include: filtering sensor signal noise, improving signal-to-noise ratio,
compensating for sensor degradation over time, and dealing with sensor-to-sensor
variability [15]. However, the continued need for MCU functionality in control
systems has also blurred the distinction between these controllers. Figure 5.4 shows
a block diagram for Microchip Technology’s dsPIC33E DSC and PIC24E MCU for
motor control and general purpose applications where one aspect of the core of the
separates one device from the other [16]. In addition to the DSP engine that is only
in the DSC, the barrel shifter that manipulates data, especially in arithmetic operations associated with DSP operation, is not offered in the MCU.
5.4.2 Field Programmable Gate Arrays
FPGAs are another approach to obtain DSP functionality. The highly configurable
hardware of FPGAs can provide distributed DSP resources. As shown in Figure
5.5, four different tasks are handled by separate DSPs with their own memory and
I/O [17]. This level of computing power and the ability to have it quickly for both
development and production volumes has become an enabler for radar sensing
and vision sensing in high-end vehicles [18, 19]. For example, an FPGA evaluation
board with four cameras can provide a surround view system or can be decoupled
into multiple systems, including rear view parking and blind spot detection.
5.4.3 Algorithms Versus Look-Up Tables
MCUs use look-up tables to store values that are accessed when the program is
running. Algorithms are used to correct for variations from expected results and to
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Using MCUs/DSPs to Increase Sensor IQ
Figure 5.4 In this block diagram for an MCU and DSC, the only aspects separating the two are the DSP
engine and barrel shifters that are only in the DSC. (© Microchip Technology, Inc. [16]).
Figure 5.5 An FPGA’s DSP resources are allocated to separate tasks that run independently. (Source:
Altera [17].)
implement a control strategy. The speed of accessing the information from a table
or performing a calculation determines the response time of the sensor input to
the MCU/DSP portion of the system. This can be the limiting factor to initiating a
change to the output in an MCU/DSP-controlled system.
5.5
Techniques and Systems Considerations
95
A control/sensor combination can implement an electronically programmable
trim as an alternative to laser trimming. However, all trimming and calibration
processes for a sensor require some form of data conversion by the MCU or DSP.
The time it takes to perform these conversions by mathematical calculations or get
data from a look-up table must be within the control system’s ability to respond
to the sensed input. In the application, real-time trimming can be implemented in
order to allow adaptive control at the sensor level. This will improve the accuracy
of a sensor that has drifted after some time in operation.
5.5
Techniques and Systems Considerations
Increased precision can be obtained for sensors by characterizing devices over temperature and pressure (or acceleration, force, etc.) and storing correction algorithms
in MCU memory. The MCU can convert the measurement to display different units
(i.e., psi, kPa, mmHg, or inches of water for pressure measurements). Other techniques use the MCU’s capability to improve linearization, to provide PWM outputs
for control, and to provide auto-zeroing/auto-ranging. The operating frequency
and switching capability of the MCU must be considered in system design. Lastly,
the MCU’s computing capability can be used in place of sensor(s) when sufficient
information exists. These system aspects will be explored in this section.
5.5.1 Linearization
Sensor nonlinearity can be improved by the use of table look-up algorithms. The
variation in sensor signal caused by temperature can also be improved by using an
integrated temperature sensor and a look-up table to compensate for temperature
effects while linearizing the output, nulling offsets, and setting full-scale gain from
information stored in an EEPROM or flash memory. Look-up tables can be implemented in masked ROM, field programmable EPROM, onboard EEPROM, or
flash memory.
Compensation for nonlinearity and the number of measurements during the
test and calibration procedure can be simplified if a nonlinear output correlates
with a sensor design parameter. For example, a strong correlation was found between the span and linearity of a pressure sensor with a thin diaphragm [20]. As
Figure 5.6 shows, the nonlinearity increased to almost 5% with the highest span
units.
Analytical techniques were investigated to improve the nonlinearity. A polynomial regression analysis was performed on 139 sensor samples ranging from 30 to
70 mV full scale span to determine the coefficients B0, B1, and B2 in the formula:
(
)
Vout = Voff + B0 + B1 * P + B2 * P 2 + B3 * P 3 + 
(5.1)
where B0, B1, B2, and B3 are sensitivity coefficients. The second order terms were
sufficient for calculations to agree with measured data with a worst case value for
calculated regression coefficient = 0.99999. The relationship of these values to the
span allowed a piece-wise linearization technique with four windows to reduce the
linearization error of most sensors to less than 0.5%. These calculations could be
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Using MCUs/DSPs to Increase Sensor IQ
Figure 5.6 Span versus linearity for pressure sensor output.
included in the MCU look-up table for improved accuracy in an application. Others
have also investigated linearization in great detail as a general means to improve
sensor accuracy [21, 22].
5.5.2 PWM Control
The pulse width modulation (PWM) output from the MCU can be used to convert
an analog sensor output to a digital format for signal transmission in remote sensing
or noisy environments [23]. Figure 5.7 shows the simple, inexpensive circuitry used
to create a duty cycle that is linear to the applied pressure. The MCU-generated
pulse train is applied to a ramp generator. The frequency and duration of the pulse
can be accurately controlled in software. The MCU requires input-capture and
output-compare timer channels. The output-capture pin is programmed to output
the pulse train that drives the ramp generator, while the input-capture pin detects
edge transitions to measure the PWM output pulse width. The pulse width changes
from 50 to almost 650 μs for zero to full scale output for this sensor.
5.5.3 Autozero and Autorange
Combining a sensor and an MCU to perform a measurement that otherwise would
be less accurate or more costly than other available alternatives is feasible today.
The cost of many MCUs is comparable or lower than the micromachined sensors
that provide their input signal. For example, a signal conditioned pressure sensor
has been combined with an MCU to measure 1.5 inch or less of water with an accuracy of 1% of the full scale reading [24]. The MCU provides software calibration,
software temperature compensation, and dynamic-zero capability. Also, a digital
output compatible with the SPI protocol is provided for the pressure measurement.
5.5
Techniques and Systems Considerations
97
Figure 5.7 PWM output pressure sensor schematic.
Auto referencing can be performed by the MCU to correct for common-mode
errors, especially with low-level signals. Auto referencing uses the MCU logic and
clock signal, combined with a digital-to-analog converter (DAC) and counter. A
signal from the MCU initiates the counter. The DAC provides a sample-and-hold
and programmable voltage source. The sensor output is summed with the autoreference correction at the input of an amplifier to obtain a corrected output to the
system.
A calibration-free method for pressure sensors has been designed using a calibrated pressure sensor, an MCU with integral A/D converter, and two additional
ICs [25]. As shown in Figure 5.8, two input channels (for V1 and V2) and one output port (P) are used in the calibration portion of this system. The analog switches
provide voltages V1 and V2 that are converted and stored in registers in the MCU.
The switches are then put in the opposite direction and the new values are stored.
The MCU adds the differential results that becomes and input to the A/D converter.
All errors from the instrument amplifier are canceled in this circuit using the differential conversion. For a measurement that only requires a full scale accuracy of
±2.5%, the offset of the pressure sensor can be neglected and the system does not
require any calibration procedure. For a ±1% measurement, the full scale output
is set at 25°C.
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Using MCUs/DSPs to Increase Sensor IQ
Figure 5.8 Calibration-free pressure sensor system. (© Freescale, Inc., 2012. Used with permission [25].)
5.5.4 Diagnostics
One of the more valuable contributions that digital control can make to the sensor’s functionality is the ability to self test, analyze status, diagnose, and report
problems to an operator or other systems that use the sensor’s output. The problem
could be as simple as a warning for maintenance, or calibration or an indication
of catastrophic failure that would not allow the system to function when required.
For example, an automotive air bag system may operate for years without requiring
deployment. However, knowing that the sensor is capable of providing the signal to
indicate a crash event is part of the safety that the system can routinely provide to
the driver and passenger. In the air bag system, a dash indicator lamp is activated
by the MCU to indicate that it has performed a system-ready analysis. A lamp that
stays on or flashes indicates that the MCU has detected a fault and that the system
needs servicing.
5.5.5 Reducing EMC/RFI
Radiated radio frequency interference (RFI) and electromagnetic interference
(EMI)—both the transmitting and receiving of unwanted signals or electromagnetic compatibility (EMC)—of a device is becoming an important design consideration with increasingly higher levels of system integration and higher processing
bandwidths. These problems can be reduced at the component level with smaller
radiation loops and a smaller number of signal lines. Power management in the
MCU can also eliminate some self-induced effects that generate RFI to the sensor
element. An example of power management is called “quiet time sampling.” This
circuit technique performs analog switching when digital switching is not present
[26]. Cleaner samples of data are taken by halting high current, high frequency activity while the sensor input is being measured. Normal digital processing functions
continue once these values are in memory.
5.5.6 Indirect (Computed not Sensed) Versus Direct Sensing
Inputs to the MCU can be manipulated to provide additional data for a system. For
example, the MCU can use an input pressure signal to provide maximum pressure,
5.6
Software, Tools, and Support
99
minimum pressure, an integrated (averaged) pressure, and time-differentiated pressure data to a system. An accelerometer signal processed by a signal processor can
be integrated once to provide velocity and twice to provide displacement information. Also, a single sensor input to an MCU can replace several switches sensing the
same parameter and can provide programmable switch points for outputs.
The ability to compute rather than sense is among the solutions that MCUs
bring to control applications. For example, in three-phase motor control systems, a
Hall-effect sensor is used to sense the location of the magnetic field for each phase
or the rotor speed in induction motors. An MCU uses this signal to switch output
drivers for pulse-width modulated control. The sensors in this system have been a
target for cost reduction for many years. Popular solutions have eliminated the sensors (this is called a sensorless technique) by using the MCU to compute the rotor
speed and slip angular frequency from other available information, including the
primary resistance [27].
5.6
Software, Tools, and Support
Creating a new approach or alternative to existing control technologies requires
much more than the architecture. The software that is used to program the control
portion and tools that allow the system to be developed are equally important. Portable code (software compatibility) is essential if future end products may require
migration to a higher performance MCU or to a DSP/DSC. Keeping the sensor’s
design and process simple and separate from the MCU or DSP allows the implementation with several available processors.
One of the main advantages of using existing MCUs, DSCs, or DSPs is the
development tools that already exist and allow the designer to quickly and easily
develop both system hardware and software. In many cases, the tools and processor are familiar to experts in the design community; the capabilities and limitations
are well-understood. The tools include software tools, compliers, and debuggers.
Many suppliers offer USB design tools that can address sensor applications. The
development tools and the documentation that has been established over several
years of customer usage are available for many suppliers for MCUs, DSPs, and
DSCs. As a result, the capability exists to develop the smartest sensor that can be
defined today.
5.6.1 Design-in Support
Touch screen sensing is one of the increasingly popular techniques for human machine interface, especially on portable products. This capability is enabled specifically by MCUs. There are several approaches to perform the sensing.
As shown in Figure 5.9, a mutual capacitance approach to sensing provides
more sensors and more accurate results than a self-capacitance technique [28]. This
is because self-capacitance produces an ambiguity of the touch point, or what is
sometimes called a ghost pattern, because two fingers on one line provide the same
results as a single finger. In contrast, with the mutual capacitance design, each XY
intersection on the screen is individually addressed so all touch points are unam-
100
Using MCUs/DSPs to Increase Sensor IQ
Figure 5.9 Self-capacitance versus mutual capacitance in touch screen sensing. (Courtesy of Atmel
[28].)
biguously sensed. Implementing this technology requires an MCU such as Atmel’s
mXT224 maXTouch touchscreen controller.
The mXT224 is a 224-node highly configurable touchscreen controller with a
touch response greater than 250 Hz that delivers 12-bit × 12-bit resolution. The
EVK-mxt224A kit allows evaluation of the capacitive-to-digital conversion (CDC)
technique and the overall performance of the chip [29]. The modular kit includes a
4.3-inch touchscreen and printed circuit board with the mXT224 that can be connected to a PC through a USB connection. PC software allows the evaluation the
full range of configuration options including the device’s multitouch and built-in
gesture capabilities. In addition, the kit has comprehensive documentation and a
quick start guide to simplify the evaluation.
5.7
Sensor Integration
The fourth level in advancing integration (refer to Figure 1.7) combines a CMOScompatible sensor with integrated analog and digital circuitry. Through wafer-level
packaging, several companies have products that combine the digital computing
portion with a MEMS sensor. The die size does not increase if the MEMS structure is built over the CMOS logic used for the MCU or DSP as part of the CMOS
fabrication process. For example, the MEMSIC MXC6226XC dual-axis thermal
accelerometer has integrated signal conditioning circuitry including a DSP [30]. As
shown in Figure 5.10, in addition to the DSP, the integrated circuitry includes amplification and ADC, sensitivity thermal compensation and fine gain adjust control,
an I2C interface, and more. This is a sensor with an integrated DSP for improving
the sensors operation in the system and not a DSP with an integrated sensor.
An alternative approach to integrating digital control with the sensor is shown
in Figure 5.11. In this case, the MPL3115A2 has a separate pressure sensor and a
dedicated ASIC integrated side-by-side in the same package [32]. The digital signal
processing and control and trim logic blocks are the digital portion of the ASIC,
and the rest of the blocks are analog circuitry. For high accuracy in barometric
measurements, the circuitry has 20-bit resolution to detect altitude changes as low
as 0.3m. The I2C output operates up to 400 kHz. Power management in the control circuitry has a standby mode current draw of 2 μA or 8.5 μA at 1 Hz in the
5.8
Application Example
101
Figure 5.10 The block diagram of the MXC6226XC shows how a dual-axis sensor is combined with a DSP.
(Courtesy of MEMSIC, Inc., [31].)
low-power mode. Because the unit handles communications, power management,
and algorithms for the sensing application, these functions are offloaded from a
host MCU.
5.8
Application Example
Electrically-powered cars and trucks, such as electric vehicles (EVs), hybrid electric
vehicles (HEVs), and plug-in hybrid electric vehicles (PHEVs) require advanced
MCU technology to control their traction motors. For the highest overall efficiency,
the motors use Field Oriented Control (FOC) to generate sinusoidal commutation
[personal e-mail communication from Renesas, March 14, 2012]. This commutation process requires the transformation of two motor phase currents into the Iq
and Id components of the torque and flux vectors using Clarke and Park transforms. The Park transform and the inverse Park transform used in the PWM control algorithm require the current rotor position as an input.
While it is possible to use a sensorless design (see Section 5.5.6) and estimate
the rotor position fed to the Park transform, the inaccuracy would reduce the efficiency. Consequently, traction motor applications always use a position sensor.
Because a resolver (an electromagnetic induction-type angular sensor) generates
very accurate position information in fractions of a degree resolution, even when
stopped, it is usually the sensor of choice. To provide smooth operation, a traction
motor accelerating from stall under a high torque load requires very accurate rotor
position information that most encoders would be incapable of providing.
Figure 5.12 shows a block diagram of the inverter control circuit for the threephase motor [33]. An MCU designed specifically for the control of these motors
integrates the resolver to digital (RD) converter, as well as several additional application peripherals. These include excitation signal generating function timer
pattern buffer (TPBA), a high-precision motor control timer (TSG2), ADC with
102
Using MCUs/DSPs to Increase Sensor IQ
Figure 5.11 Package-level integration (a) combines sensing and (b) DSP/DSC capability. (Courtesy
of Freescale, Inc., 2012. Used with permission [32].)
synchronized sample-and-hold function, and three-phase PWM timer. The 32-bit
RISC MCU uses a dual-core lockstep system that continually calculates and detects failures to make it compliant with the newest ISO 26262 safety standard for
vehicles.
5.9
Summary
Trends in the development of microelectronics for MCUs, DSPs, DSCs, ASICs, and
FPGAs have been for faster, more complex signal processing and reduced feature
5.9
Summary
103
Figure 5.12 The V850E2/PJ4-E with an integrated resolver-digital (R/D) converter simplifies the system and
reduces design costs associated with accurately sensing rotor position. (Courtesy of Renesas [33].)
size (critical dimensions) into the sub-μm range. These goals have lead to lower
supply voltages (3.3V and less). In addition, customer requirements for increased
and more easily programmed memory and reduced development cost and system
design cycle time continue to affect the design and methodology used to create these
products. The resulting improvements can be useful in the development of smart
sensors and can be cost-effective by using other capabilities provided by the MCU,
DSP, DSC, ASIC, or FPGA. Communicating the data from smart sensors is among
the capabilities that can be integrated on chip and is such a critical part that Chapter 7 will be dedicated to this aspect of the control logic.
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