Systems and methods for improved root mean square (RMS) measurement
Systems and methods are provided for improving the operation of a computer or other electronic device that utilizes root-mean-square (RMS) measurements, e.g., RMS current measurements, by reducing error in the RMS measurement. A series of measurement samples are received at a processor, which executes a noise-decorrelated RMS algorithm including: calculating a current-squared value for each measurement sample by multiplying the measurement sample by a prior measurement sample in the series (rather by simply squaring each measurement sample as in conventional techniques), summing the current-squared values, and calculating an RMS value based on the summed values. The processor may also execute a frequency-dependent magnitude correction filter to correct for frequency-dependent attenuation associated with the noise-decorrelated RMS algorithm. The calculated RMS value has a reduced error, particularly for lower-end current measurements, which may improve the operation of the computer or electronic device that utilizes the RMS value.
1. A method for improving the operation of a computer or other electronic device that utilizes root-mean-square (RMS) measurements, by reducing error in the RMS measurement, the method comprising:
receiving, at the computer or other electronic device, a series of measurement samples;
executing, by the computer or other electronic device, a gain correction filter to the series of measurement samples to pre-correct for a frequency-dependent attenuation associated with a noise-decorrelated RMS algorithm; and
executing, by the computer or other electronic device, the noise-decorrelated RMS algorithm including:
for each received measurement sample, calculating an adjusted sample value as a function of (a) the respective measurement sample and (b) a prior measurement sample in the sequence;
summing the adjusted sample values for the sequence of measurement samples; and
calculating an RMS value based on the summed adjusted sample values; and
controlling at least one component of the computer or other electronic device based on the calculated RMS value.
2. The method of claim 1 , wherein the series of measurement samples comprise a series of current measurement samples, and the RMS value calculated by execution of the noise-decorrelated RMS algorithm is an RMS current value.
3. The method of claim 1 , wherein calculating an adjusted sample value for each received measurement sample comprises calculating an adjusted sample value for each received measurement sample by a mathematical combination step comprising multiplying each respective measurement sample by a prior measurement sample in the sequence.
4. The method of claim 3 , wherein multiplying each respective measurement sample by a prior measurement sample in the sequence comprises multiplying each received measurement sample by the immediately previous measurement sample in the sequence to calculate a current-squared value.
5. The method of claim 1 , wherein the gain correction filter comprises an infinite impulse response (IIR) filter.
6. The method of claim 1 , wherein the gain correction filter is configured to achieve a stable pole and zero placement using a single multiplication and two additions.
7. The method of claim 1 , wherein the computer or other electronic device that utilizes root-mean-square (RMS) measurements comprises a microcontroller.
8. The method of claim 1 , wherein the computer or other electronic device that utilizes root-mean-square (RMS) measurements comprises a microprocessor.
9. The method of claim 1 , wherein the computer or other electronic device that utilizes root-mean-square (RMS) measurements comprises a computer including at least one microcontroller or microprocessor.
10. A system for improving the operation of a computer or other electronic device that utilizes root-mean-square (RMS) measurements, by reducing error in the RMS current, the system comprising:
a memory device storing a noise-decorrelated RMS algorithm; and
electronics configured to:
receive a series of measurement samples;
execute a gain correction filter to the series of measurement samples to pre-correct for a frequency-dependent attenuation associated with the noise-decorrelated RMS algorithm; and
execute the noise-decorrelated RMS algorithm including:
for each received measurement sample, calculating an adjusted sample value as a function of (a) the respective measurement sample and (b) a prior measurement sample in the sequence;
summing the adjusted sample values for the sequence of measurement samples; and
calculating the RMS value based on the summed adjusted sample values; and
control at least one component of the computer or other electronic device based on the calculated RMS value.
11. The system of claim 10 , wherein the series of measurement samples comprise a series of current measurement samples, and the RMS value calculated by execution of the noise-decorrelated RMS algorithm is an RMS current value.
12. The system of claim 10 , wherein the electronics comprise a microcontroller.
13. The system of claim 10 , wherein the electronics comprise a microprocessor.
14. The system of claim 10 , wherein calculating an adjusted sample value for each received measurement sample comprises calculating an adjusted sample value for each received measurement sample by a mathematical combination step comprising multiplying each respective measurement sample by a prior measurement sample in the sequence.
15. The system of claim 14 , wherein multiplying each respective measurement sample by a prior measurement sample in the sequence multiplying each received measurement sample by the immediately previous measurement sample in the sequence to calculate a current-squared value.
16. The system of claim 10 , wherein the gain correction filter comprises an infinite impulse response (IIR) filter.
17. The system of claim 10 , wherein the gain correction filter is configured to achieve a stable pole and zero placement using a single multiplication and two additions.
18. A method for improving the operation of a computer or other electronic device that utilizes root-mean-square (RMS) measurements, by reducing error in the RMS measurement, the method comprising:
receiving, at the computer or other electronic device, a series of measurement samples;
executing, by the computer or other electronic device, a noise-decorrelated RMS algorithm to calculate RMS values from the series of measurement samples, wherein executing the noise-decorrelated RMS algorithm including includes:
executing a gain correction filter to pre-correct for a frequency-dependent attenuation introduced by a noise-decorrelated RMS algorithm; and
executing the noise-decorrelated RMS routine to decorrelate noise in the measurement samples; and
controlling at least one component of the computer or other electronic device based on the calculated RMS values.
19. The method of claim 18 , wherein the noise-decorrelated RMS routine includes multiplying each measurement sample in the series of measurement samples by a prior measurement sample in the series of measurement samples.
20. The method of claim 18 , wherein the noise-decorrelated RMS routine includes calculating an adjusted sample value for each respective measurement sample as a function of (a) the respective measurement sample and (b) a prior measurement sample in the sequence.