Zero To Hero Guide For Selection Of ADC For Embedded Product

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Introduction to ADC

ADC stands for Analog-to-Digital Converter. In the world of embedded systems, most of the real-world phenomena such as temperature, light, sound, voltage, current etc., exist as an analog signals. These signals are continuous and have infinite possible values. But in the digital systems, such as microcontrollers or microprocessors operates with discrete digital values (i.e. Zero or One). To interface with this analog world and to process analog signals, an ADC is used to convert analog signals into digital representations.

We find ADCs in most of the embedded systems. So, in any embedded system where we convert the real-world inputs to the digital world, you will find the ADC doing this stuff. The ADC could be internal peripherals in the MCU, or it could be external IC. There are many types of ADC’s available in the marketplace from different-different manufacturers. Each type of ADCs has its own strength or weakness. In this blog, we will learn different types of ADC’s, the selection criteria for your embedded project and the best practices regarding ADC’s.

Types of ADC

The architecture of an ADC determines the measurement capability i.e. resolution, output data type i.e. serial or parallel, latency and accuracy. In some applications latency is more important than the resolution while in others the speed is not important but the accuracy plays vital role. There are mainly 5 types of ADCs

Delta-Sigma ADC

The Delta-Sigma Analog to Digital converters are widely used in applications that require high-resolution conversion and excellent noise performance. They achieve this by oversampling the analog input signal and employing noise-shaping techniques. Please click here to read the Delta-Sigma ADC in detail.

Successive approximation (SAR) ADC

The Successive Approximation Register (SAR) ADC is a common type of analog-to-digital converter (ADC) known for its moderate speed and good resolution. It uses a binary search algorithm to determine the digital value that closely matches the input analog signal. Please click here to read the SAR ADC in detail.

SAR ADCs strike a balance between resolution, speed, and power consumption, making them a popular choice for many embedded systems and precision measurement applications.

Dual-slope ADC

Dual-slope ADC (Analog-to-Digital Converter) is a type of integrating ADC that works by measuring the time it takes for an integrator to charge and discharge based on the input analog voltage. Dual-slope ADCs are known for their noise rejection capabilities and are commonly used in applications that require high accuracy, such as digital multimeters. Please click here to read how a dual-slope ADC works.

It’s worth noting that dual-slope ADCs are slower compared to some other types of ADCs, which makes them more suitable for applications that prioritize accuracy over speed.

Pipelined

A pipelined ADC (Analog-to-Digital Converter) is a high-speed ADC architecture that breaks down the conversion process into multiple stages or pipeline phases. Each stage performs a portion of the conversion, allowing for faster overall conversion rates. Pipelined ADCs are known for their excellent speed and are commonly used in applications that require high-speed and high-resolution analog-to-digital conversion. Please click here to know in detail how a pipelined ADC works.

Pipelined ADCs provide a balance between speed and resolution, making them well-suited for high-speed applications that demand both accuracy and fast conversion rates. However, it’s important to consider factors such as power consumption, complexity, and cost when selecting an appropriate ADC architecture for a specific application.

Flash

A Flash ADC (Analog-to-Digital Converter) is a type of ADC known for its high-speed conversion capability. It utilizes a parallel architecture and is capable of converting an analog input signal into a digital output in a single step. Flash ADCs are widely used in applications that require fast conversion rates but typically have limited resolution. Let’s delve into how a Flash ADC works:

Flash ADCs are ideal for applications that demand high-speed conversion with relatively lower resolution requirements. However, their power consumption and complexity increase significantly with higher resolutions, which should be considered when selecting the appropriate ADC architecture for a given application.

Selection of an ADC (Analog to Digital converter)

The selection of ADC plays very important role in the embedded system. Depending on the requirement the appropriate ADC should be selected. There are some primary factors that should not be compromised while selecting the ADCs. The secondary factors are luxury to the embedded system designers, which are good to have but cannot majorly influence the selection of the ADCs

Primary factors:

Resolution

The resolution of an ADC (Analog-to-Digital Converter) refers to the number of distinct digital values or levels that the ADC can represent. It determines the smallest change in the input analog signal that the ADC can detect and convert into a distinct digital value. The resolution is typically expressed in bits and directly affects the level of detail or precision with which the ADC can represent the input signal.

The smallest incremental voltage that can be recognized is expressed in terms of LSB.

1 LSB = (V_REF – V_SS)/2ⁿ
Where LSB = Least-significant bit
n = Number of digital bits output by the ADC
V_REF = Reference voltage
V_SS = Analog ground
An ADC which has ‘n’ bit digital output provides 2ⁿ digital values. It includes both 0 and 2ⁿ-1.
With a 3.3 V reference voltage, & 12bit ADC, the resolution is 3.3/2¹² = 3.3/4096 = 0.805 (mV).

While resolution is an essential aspect for selection of an ADC but it is not the sole factor determining accuracy. The accuracy of an ADC is influenced by various other factors, including linearity, noise, offset, gain error, and more. The High resolution alone does not guarantee high accuracy; it’s crucial to consider the overall performance specifications of the ADC.

Accuracy

Accuracy is a crucial factor to consider when selecting an ADC (Analog-to-Digital Converter) for a particular application. The accuracy of an ADC determines the extent to which the digital representation of an analog input signal reflects the original analog signal. In other terms, the accuracy reflects how true the ADC’s output reflects the actual input. The accuracy of an ADC is determined by the specifications for gain, offset, integral nonlinearity and differential nonlinearity.

Offset Error

Offset error represents the deviation of the ADC’s output when the input analog signal is at its minimum or zero level. In an ideal ADC, the output should be zero when the input is at its minimum or zero level. However, in reality, due to imperfections, there may be an offset or non-zero output even when the input is at the minimum level.

The offset errors can occur due to mismatches or non-ideal characteristics in the amplifiers that are used within the ADC circuitry. These imperfections can introduce a non-zero output even when the real input is zero. Changes in temperature can also affect the behavior of components in the ADC. Which can lead to offset errors. The thermal drift can cause the offset to vary with temperature changes.

Offset error is commonly expressed as LSBs, volts or percentage of full-scale range (%FSR).

Gain Error

In an ideal scenario, the ADC would have a perfectly linear response, converting the analog input signal into digital values with precise gain. But, in practical implementations, there can be variations or deviations from the ideal gain due to several factors. So, the gain error is referred to the deviation or discrepancy between the actual gain of the ADC and the ideal or expected gain. The gain error can introduce inaccuracies in the converted digital output, impacting the reliability of the ADC’s measurements.

There are several factors contribute to gain errors in an ADCs, including component tolerances, non-idealities in the analog and digital circuitry, manufacturing variations, and environmental conditions. Variations in components, such as resistors, capacitors, and operational amplifiers can lead to differences in gain from the expected values. The magnitude of the gain error determines the extent of the inaccuracy introduced into the digital output.

Integral nonlinearity

An ADC’s transfer function should be perfectly linear, where each increment of the input analog voltage corresponds to an equal increment of the digital output code. But in practice, the actual transfer function may deviate from linearity due to various sources of error. So, Integral non-linearity (INL) is an error measure that quantifies the deviation of the ADC’s actual output from the ideal output, considering the entire input range.

Differential nonlinearity

Differential nonlinearity (DNL) is a type of error that can affect the accuracy of an Analog-to-Digital Converter (ADC). It measures the deviation of the actual step size of the ADC from the expected ideal step size. DNL is typically expressed in terms of LSB (Least Significant Bit) or percentage of the ideal step size.

DNL is typically calculated as the difference between the measured step size and the ideal step size, divided by the ideal step size.

DNL = (Actual Step Size – Ideal Step Size) / Ideal Step Size

As shown in below picture, at some places the DNF is 1 LSB while at other it is just 0.5 LSB.

ADCs Differential nonlinearity Accuracy error

Conversion Speed (Sampling Frequency)

The sampling frequency is the speed to convert the analog signal to the digital signal. Therefore, the
ADC sampling frequency must be at least twice the analog signal frequency. Sampling the signal at twice the analog signal frequency will not result in a loss of information.

Two main elements to consider when selecting a sampling rate are the input signal bandwidth and the required update rate. When digitizing a signal, the Nyquist rule must be followed. The Nyquist rule states that sampling rate of the A/D must be at least twice that of the input signal bandwidth of interest. This does not mean the fundamental input frequency must be limited to one-half of the sample rate; it only refers to the bandwidth of the input signal. The ability to process fundamental input signals which are greater than Nyquist allow for undersampling.

Exercising an A/D converter at close to Nyquist rate has some drawbacks. Although the converter is capable of digitizing signal bandwidths between DC and one-half the sample rate, two new problems must be considered. First, the analog input bandwidth of the sampling mechanism may be inadequate to process the signal without introducing distortion. The second problem with Nyquist rate sampling is aliasing. Most input signals contain harmonics of the fundamental, which will be digitized by the converter.

Additionally, there may be interactions between the high-frequency input harmonics and the clock signals inside the converter, causing unwanted harmonics to be digitized. It is usually necessary to filter out the input harmonics using a low-pass or band-pass filter. Passing an input signal close to Nyquist while attempting to filter out harmonics above Nyquist requires a rigorous “brick wall” type of filter, which may be prohibitively expensive. It is preferable to select a converter whose sample rate is several times greater than the analog input bandwidth, to avoid expensive high-order input filters.

Reference Voltage

The ADC requires a reference voltage to which the analog input is compared to produce the digital
output. The digital output is the ratio of the analog input with respect to this reference voltage. The reference voltage should always be greater than the amplitude of the analog input. This is because the max digital value (e.g. for 12 bit ADC it will be 4096) will be referenced to the reference voltage. If the input signal will be more than reference volatge then the ADC will not be able to give correct value.

Analog Signal type

It is must to know the nature of the analog input signal before starting the selection of the ADC. We should know the amplitude of the input signal, the signal noise, the source impedance etc.

We should know if the signal contain discontinuities? If so, the choice of architecture is usually limited to “single-shot” type A/D converters (such as SAR, subranging, flash) since A/D converters which are continuous (deltasigma, integrating, VFC, dual slope) tend to integrate signal discontinuities, giving false outputs.
We should also know what the characteristic source impedance is of the signal. Most A/D converters require a low dynamic source impedance, which is discussed in detail in the “Drive Requirements” section of this application bulletin. There may be some advantages in matching the A/D converter’s input impedance to the source impedance to reduce distortion problems caused by reflections.

If the input signal is noisy, it may be best to consider using an integrating type of A/D, since the integration acts to reduce noise. However, most integrating converters have fairly slow sample rates and analog input bandwidth. If the input signal is both fast and noisy, the user has some options, such as driving the A/D with an integrating amplifier, using a bandpass filter to reduce input noise, using a high-speed A/D and averaging the results, or digitally filtering the results in DSP. Generally speaking, for slow input signals, using a type of integrating converter is a very cost-effective solution.

The amplitude of input signal should never be more than the capacity of the ADC pin. This could damage the ADC permanently. So, we should not forgot this point.

Quantization noise

It is a noise types that contribute to the device’s accuracy. The quantizing noise is unavoidable in analog-to-digital conversion. Simply put, when a continuous set converts to a discrete set, we can expect to lose some information. We refer to that lost information as quantizing noise, and it manifests as a sawtooth noise signal. With high enough resolution, it is possible to overcome quantizing noise functionally, but it remains an inherent part of the ADC process.

Zero to Hero guide for selection of ADC for embedded product

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