ADC Basics (Part 1): Does your ADC fit into the real-world?

ADC Basics (Part 1): Does your ADC fit into the real-world?

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By eeNews Europe

Real-world environmental occurrences such as temperature, pressure, flow or light usually require a specialized sensor to adequately capture an ecological status or change. Although sensors can convert these physical occurrences adequately to a small signal resistance, voltage, or current, they lack the ability to convert their output electrical signals to a final digital representation, let alone perform amplification, filtering, offset adjustments, or other electrical conditioning functions.

Designers use a variety of devices to bring analog signal to an accessible level with processing functions. However, at the end of the signal path an ADC usually helps tie the sensor information into a final digital result. This article is the first of a multi-part series that discusses SAR and delta-sigma ADC topologies, appropriate systems for these devices, and a comprehensive error analysis in various application circuits.

Where sensors touch the real-world
The most common type of physical data collected from the environment is temperature. The temperature ranges of these systems span from our environment here on Earth to out-of-this-world, ultra-hot or ultra-cold environments. Numerous sensors can respond to absolute temperature or changes in temperature. A short list of these types of sensors includes Integrated silicon, thermocouples, resistive-temperature-devices (RTD), thermistors, infrared, and thermopiles. As shown in Figure 1, the actual temperature in various test environments changes at a relatively slow pace (below 10 Hz). However, designers are interested in a range of accuracy and precision from a few bits up to 20 bits. Twenty-bits of noise free resolution means that the converter in the system generates 220 (1,048,576) clean, unvarying bits of data.   

Figure 1. Real-world entities in relation to noise-free resolution versus bandwidth.

Pressure sensors monitor air or gas pressure. A sub-class of the pressure sensor is the load cell. Load cells can sense the weight of various objects, from multi-tons to the weight of an eye lash (or smaller). For these sensors, models basically are diamond-shaped, four-element resistive network. The frequency range of these sensors is higher than the temperature sensors; up to ~100 Hz.

Temperature, pressure, or audio sensors (microphones) effectively sense the flow of fluids, gasses, or liquids. Figure 1 shows that physical changes in the flow of gases or liquids are relatively slow and noise-free-bit requirements are relaxed.

The output signals produced from the above sensors can come in the form or resistance, voltage, and current. In most cases these sensors create small level signals that may require further signal conditioning.

As you move to higher bandwidths (Figure 1), displacement, proximity, and photo-sensing circuits have lower precision requirements. Photosensing applications can range from low-frequency, high noise-free-bit requirements (medical scans) to higher frequency digital sensing, such as a bar code scanner. The photodetector signal path requires higher frequency converters, such as SAR or high-speed delta-sigma converters.

If a system designer requires a finished digital representation of these physical occurrences, these entities and consequently these sensors have successive-approximation-register (SAR) ADCs or delta-sigma (Δ∑) ADCs at the end of their signal paths. You can see this relationship in the next section of this article.

Tying sensors to an ADC

The most common ADCs for the frequency bandwidths that cater to the sensors described earlier are delta-sigma and SAR. Figure 2 shows the relationship between the delta-sigma and SAR converter architectures regarding converter resolution and conversion rate. Delta-sigma converters operate in the lower frequency ranges; up to approximately 10 kHz. Most engineers know these converters for their extremely high resolution.

Figure 2. Converter resolution versus conversion rate for the delta-sigma and SAR ADCs.

Delta-sigma ADCs determines its digital output word by oversampling the analog input signal. The delta-sigma input modulator stage oversamples the analog input signal and converts it to a 1-bit digital data stream. Next a digital filter samples by collecting the data from this 1-bit data stream and converts it to a multibit output word.

Delta-sigma converters are capable of producing output bit ranges from 16 to 24, which in and of itself is impressive. The advantages of the delta-sigma converter include low power, extremely high resolution, and high stability, at a low cost. The overall performance of the delta-sigma ADC allows the designer to reduce the number of analog signal-conditioning chips prior to ADC input. The disadvantages for this type of converter usually include low speed. In some converters, there is a greater than zero cycle-latency. We will learn more about this converter and its inner workings in a future article. SAR-DAC
In contrast, the SAR-ADC acquires a snap-shot of the analog signal. After acquiring this sample, the SAR converter uses an internal iterative process to finally determine the equivalent digital output value. The SAR-ADC’s output resolutions typically range from eight to 18 bits.

SAR converters are used for moderate speed conversions while providing medium-to-high resolutions. SAR converters are the back bone of general purpose application circuits that need to change analog signals to digital. The SAR converter resolution generally is lower than the delta-sigma converter. However, the SAR converter has a zero-cycle latency (or single cycle settling) while operating at higher speeds. SAR converters are used in many data acquisition applications like control loops, power monitoring, and low-to-medium frequency analysis. We will learn more about this converter and its inner workings in another future article.

SAR converters perform with zero-cycle latency and high DC / AC accuracy. These types of converters live well in low-power applications because they power-down automatically when not converting an analog signal. Today, the fastest sample rate of a SAR converter is approximately 5 MHz. However, this converter fills the gap in speed between the delta-sigma converter and the higher-speed converters, such as the pipeline.

Which converter is best for your application?
As you get ready to select your ADC for your application, Table 1 may be useful. This table compares the SAR and delta-sigma converter families in terms of conversion frequency and converter resolution.

Table 1. Conversion frequency and resolution for delta-sigma and SAR ADCs.

The maximum conversion rate of SAR converters on the market today is around 5 Msps. Their resolution can go as high as 18 bits. However, the majority of SAR ADCs in applications across industry are 8- to 12-bit converters. The conversion rate of a delta-sigma converter is generally below 625 ksps. With this speed it is possible to have a converter that produces up to 24 bits of data. The resolution for delta-sigma devices, that convert a less than 10 Msps, is lower that its 24-bit cousin.  

Table 2 ranks these two architectures for throughput, resolution, latency, and power consumption.

Table 2. A ranking of characteristics between the SAR and delta-sigma ADCs.

Table 2 shows that the SAR converter is a better work horse in terms of speed (throughput), low-latency, multiplexing, and power consumption. The distinct advantage of the delta-sigma converter over the SAR converter is high resolution.


We initiated this series of articles with a general overview of the frequency and resolution ranges of sensors, then compared that to the SAR and delta-sigma converters. As you make temperature, pressure, or optical measurements, keep in mind that the converter architectures of choice are the SAR and delta-sigma. In next month’s article, I will dig into the details for what a delta-sigma converter is and how it is successful in generating very high resolution.


1. Baker, B. “Temperature Sensing Technologies,” Application note (DS00679A), Microchip Technology, 1998
2. “Understanding data converters,” Application Report (SLAA013), Texas Instruments, 1995.
3. Baker, B. “A Baker’s Dozen: Real analog solutions for digital designers.” Burlington, MA: Elsevier/Newnes, 2005.

About the Author

Bonnie Baker is a Senior Applications Engineer with the WEBENCH team for Texas Instruments and has been involved with analog and digital designs and systems for over 25 years. In addition to her fascination with circuit design, Bonnie has a drive to share her knowledge and experience. She has written hundreds of articles, design and application notes, conference papers, and authored a book: “A Baker’s Dozen: Real Analog Solutions for Digital Designers.” Bonnie can be reached at  

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