DAC DC Measurement

Measure DC performance metrics of DAC output

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Libraries:
Mixed-Signal Blockset / DAC / Measurements & Testbenches

Description

The DAC DC Measurement block measures DAC DC performance metrics such as offset error, gain error, integral nonlinearity (INL), and differential nonlinearity (DNL) errors. You can use the DAC DC Measurement block to validate the DAC architecture models provided in Mixed-Signal Blockset™, or you can use a DAC of your own implementation.

Examples

Measure DC Performance Metrics Using DAC DC Measurement

This example shows how to find DC performance metrics such as offset error, gain error, INL, and DNL.

Open the model dac_dc_measure. The model consists of a Signal Generator, a Flash ADC, a Binary Weighted DAC block, and a DAC AC Measurement block.

model = 'dac_dc_measure';
open_system(model)

The Flash ADC acts as the input to the Binary Weighted DAC. The ADC uses an internal start clock whose Conversion start frequency (Hz) is 1e6 and RMS aperture jitter (s) is 1e-12. The input analog frequency to the Flash ADC from the Signal generator is 900 Hz.

The Number of bits of the Binary Weighted DAC is set to 10. The impairments are enabled in the Impairments tab, and the value of the offset error and gain error are set to 2 LSB and 1 LSB, respectively. All other parameters are kept at their default values.

The Number of bits and Conversion start frequency (Hz) of the DAC DC Measurement block are 10 and 1e6, respectively. The Settling time (s) of the DAC DC Measurement block is set to 4e-7, twice the Settling time (s) of the Binary Weighted DAC to ensure the entire transition period is not considered as part of the steady-state DC measurements.

Run the simulation for 0.02558 s. The measured AC performance metrics are displayed on the DAC AC Measurement block.

Ports

Input

digital — Digital input signal from DAC

scalar

Digital signal from a DAC, specified as a scalar.

Data Types: fixed point | single | double | int8 | int16 | int32 | uint8 | uint16 | uint32

analog — Converted analog signal from DAC

scalar

Converted analog signal from a DAC, specified as a scalar.

Data Types: double

start — External clock to start conversion

scalar

External clock to start conversion, specified as a scalar. This port determines when digital-to-analog conversion process starts.

Data Types: double

Parameters

Input polarity — Polarity of input signal to DAC

Bipolar (default) | Unipolar

Polarity of the input signal to the DAC.

Programmatic Use

Block parameter: Polarity

Type: character vector

Values: Bipolar|Unipolar

Default: Bipolar

Reference (V) — Reference voltage

2 (default) | real scalar

Reference voltage of the DAC, specified as a real scalar in volts. Reference (V) helps determine the output from the input digital code, Number of bits, and Bias (V) using the equation:

$$\text{DAC output = }\left(\left(\frac{\text{Digital input code}}{2^{\text{Number of bits}}}\right)\text{Reference}\right)+\text{Bias}$$.

Programmatic Use

Block parameter: Ref

Type: character vector

Values: real scalar

Default: 2

Data Types: double

Bias (V) — Bias voltage added to output

0 (default) | real scalar

Bias voltage added to the output of the DAC, specified as a real scalar in volts. Bias (V) helps determine the output from the input digital code, Number of bits, and Reference (V) using the equation:

$$\text{DAC output = }\left(\left(\frac{\text{Digital input code}}{2^{\text{Number of bits}}}\right)\text{Reference}\right)+\text{Bias}$$.

Programmatic Use

Block parameter: Bias

Type: character vector

Values: real scalar

Default: 0

Data Types: double

Settling time (s) — Time required for output to settle

3e-7 (default) | nonnegative real scalar

The time required for the output of the DAC to settle to within some fraction of its final value, specified as a nonnegative real scalar in seconds.

Programmatic Use

Block parameter: SettlingTime

Type: character vector

Values: real scalar

Default: 3e-7

Data Types: double

Hold off time (s) — Delay before measurement analysis

1e-3 (default) | nonnegative real scalar

Delay before measurement analysis to avoid corruption by transients, specified as a nonnegative real scalar in seconds.

Programmatic Use

Block parameter: HoldOffTime

Type: character vector

Values: nonnegative real scalar

Default: 1e-3

Data Types: double

Number of bits — Number of bits in input word

10 (default) | positive real integer

Number of bits in the input word, specified as a unitless positive real integer. Number of bits determines the resolution of the DAC.

Programmatic Use

Block parameter: NBits

Type: character vector

Values: positive real integer

Default: 10

Data Types: double

Start conversion frequency (Hz) — Frequency of internal start conversion clock

1e6 (default) | positive real scalar

Frequency of the internal start conversion clock, specified as a real scalar in Hz. The Start conversion frequency parameter determines the conversion rate at the start of conversion.

Programmatic Use

Block parameter: StartFreq

Type: character vector

Values: positive real scalar

Default: 1e6

Data Types: double

Recommended simulation stop time (s) — Minimum time simulation must run for meaningful result

0.02148 (default) | positive real scalar

Minimum time the simulation must run to obtain meaningful results, specified as a positive real scalar in seconds.

To measure DC performance, the simulation must run so that the DAC can sample each digital code 20 times. Based on this assumption, the Recommended simulation stop time (s) T is given by:

$$T=\frac{\text{Samples per bit}}{\left(StartFreq/2^{Nbits+1}\right)}+\text{Hold off time}$$,

where StartFreq is the frequency of the conversion start clock and Nbits is the resolution of the DAC.

The number of samples per bit is calculated using the equation:

$$\text{Samples per bit = }\max \left(\frac{1}{\text{Error tolerance}},10\right)$$.

This parameter is only reported by the block and is not editable.

Data Types: double

Endpoint — Measure DNL, INL using endpoint method

on (default) | off

Measure the differential nonlinearity (DNL) error and integral nonlinearity (INL) error using the endpoint method. This method uses the endpoints of the actual transfer function to measure the DNL and INL errors.

Best fit — Measure DNL, INL using best fit method

on (default) | off

Measure the differential nonlinearity (DNL) error and integral nonlinearity (INL) error using the best fit method. This method uses a standard curve-fitting technique to find the best fit to measure the DNL and INL errors.

Output result to base workspace — Store detailed test results to base workspace

off (default) | on

Select to store detailed test results to a struct in the base workspace for further processing at the end of simulation. By default, this parameter is deselected.

Workspace variable name — Name of the variable that stores detailed test results

dac_dc_out (default) | character string

Name of the variable that stores detailed test results, specified as a character string.

Dependencies

To enable this parameter, select Output result to base workspace parameter.

Programmatic Use

Block parameter: VariableName

Type: character vector

Values: character string

Default: dac_dc_out

Plot — Plot measurement results

button

Click to plot measurement result for further analysis.

More About

Offset Error

Offset error represents the offset of the DAC transfer function curve from it ideal value at a single point.

Gain Error

Gain error represents the deviation of the slope of the DAC transfer function curve from its ideal value.

INL Error

Integral nonlinearity (INL) error, also termed as relative accuracy, is the maximum deviation of the measured transfer function from a straight line. The straight line can either be a best fit using standard-curve fitting technique, or be drawn between the endpoints of the actual transfer function after gain adjustment.

The best fit method gives a better prediction of distortion in AC applications, and a lower value of linearity error. The endpoint method is mostly used in the measurement applications of data converters, since the error budget depends on actual deviation from the ideal transfer function.

DNL Error

Differential nonlinearity (DNL) is the deviation from the ideal difference (1 LSB) between analog input levels that trigger any two successive digital output levels. The DNL error is the maximum value of DNL found at any transition.

Version History

Introduced in R2020a