1. A method for determining a representative average root mean square value for a generator, the method comprising:

identifying at least one generator waveform;

detecting a first event of the at least one generator waveform;

identifying a second event of the at least one generator waveform;

determining a time interval between the first event and the second event,

wherein the time interval spans less than half a cycle of the at least one generator waveform; and

calculating a representative amplitude value for the at least one generator waveform based on the time interval.

2. The method of claim 1, wherein the at least one generator waveform comprises a single phase waveform,

wherein the first event is located at a first position along the single phase waveform, an

Wherein the second event is located at a second position along the single phase waveform.

3. The method of claim 1, wherein the at least one generator waveform comprises a three-phase waveform,

wherein the first event is located along a first waveform of the three-phase waveforms,

wherein the second event is located along a second waveform of the three-phase waveforms.

4. The method of claim 1, wherein the first event or the second event corresponds to a geometric property of the at least one generator waveform.

5. The method of claim 4, wherein the geometric attribute comprises a zero crossing value, a maximum value, a minimum value, or a knee value.

6. The method of claim 1, wherein the first event corresponds to a first geometric property of the at least one generator waveform and the second event corresponds to a second geometric property of the at least one generator waveform.

7. The method of claim 6, wherein the first geometric property comprises one value of a group comprising a zero crossing value, a maximum value, a minimum value, or a knee value, and the second geometric property comprises another value of the group.

8. The method of claim 1, wherein the first event or the second event is defined according to a line-to-neutral value of the at least one generator waveform, or wherein the first event or the second event is defined according to a line-to-line value of the at least one generator waveform.

9. The method of claim 1, wherein the representative amplitude is a root mean square amplitude over time between the first event and the second event, the method further comprising:

in response to the root mean square amplitude for the at least one generator waveform based on the time interval, a generator command is calculated.

10. An apparatus for iteratively analyzing generator operation, the apparatus comprising:

an event circuit configured to identify a first event and a second event of at least one generator waveform;

a waveform calculator configured to determine a time interval between the first event and the second event, wherein the time interval spans less than half a cycle of the at least one generator waveform, the waveform calculator further configured to calculate a representative root mean square value for the at least one generator waveform based on the time interval; and

a generator command module configured to calculate a generator command in response to the representative root mean square value for the at least one generator waveform based on the time interval.

11. The apparatus of claim 10, wherein the at least one generator waveform comprises a single phase waveform,

wherein the first event is located at a first position along the single phase waveform, an

Wherein the second event is located at a second position along the single phase waveform.

12. The apparatus of claim 10, wherein the at least one generator waveform comprises a three-phase waveform,

wherein the first event is located along a first waveform of the three-phase waveforms,

wherein the second event is located along a second waveform of the three-phase waveforms.

13. The apparatus of claim 10, wherein the first event or the second event corresponds to a geometric property of the at least one generator waveform.

14. The apparatus of claim 13, wherein the geometric attribute comprises a zero crossing value, a maximum value, a minimum value, or a knee value.

15. The apparatus of claim 10, wherein the first event corresponds to a first geometric property of the at least one generator waveform and the second event corresponds to a second geometric property of the at least one generator waveform.

16. The apparatus of claim 15, wherein the first geometric property comprises one value of a group comprising a zero crossing value, a maximum value, a minimum value, or an inflection value, and the second geometric property comprises another value of the group.

17. The apparatus of claim 10, wherein the first event or the second event is defined according to a line-to-neutral value of the at least one generator waveform, or wherein the first event or the second event is defined according to a line-to-line value of the at least one generator waveform.

Background

An engine-generator set, also referred to as a generator or generator set (genset), may include a power source (e.g., an engine) and an alternator or other device for generating electrical energy or power from mechanical energy. The generator may provide backup power in the event of an interruption of the power utility service. Other generator users may rely on the generator as the primary power source.

Both such primary and backup power facilities include multiple generators, which may be connected in parallel or synchronized. When one of the parallel generators goes down line, the other generators tend to compensate or eliminate the fault. For example, other generators may turn off parallel control and operate independently based on the current load of the system. The synchronization of the generators requires measuring electrical parameters of the output of one or more generators. In addition, the output of the generator may be measured during maintenance or control operations of the system. Improvements in techniques for measuring waveforms in generator systems remain a challenge.

Drawings

Exemplary implementations are described herein with reference to the drawings.

Fig. 1 shows an exemplary phasor diagram.

Fig. 2 illustrates an exemplary generator.

FIG. 3 illustrates an exemplary set of templates for measuring a generator waveform.

FIG. 4 illustrates another exemplary set of templates for measuring a generator waveform.

FIG. 5 illustrates another exemplary set of templates for measuring a generator waveform.

FIG. 6 illustrates another exemplary set of templates for measuring a generator waveform.

FIG. 7 illustrates an exemplary measured generator waveform.

Fig. 8 shows a comparison between phase angle calculations using a template and phase calculations using a finite transform.

Fig. 9 shows output signals for alternators having different pitches.

Fig. 10 illustrates another exemplary generator.

Fig. 11 shows a three-phase sinusoidal signal.

Fig. 12 shows a time slice of the three-phase sinusoidal signal of fig. 11.

Fig. 13 shows line-to-line values and line-to-neutral values of three-phase sinusoidal signal lines.

FIG. 14 illustrates an exemplary graph of a one-twelfth cycle RMS calculation and a full cycle RMS calculation.

FIG. 15 illustrates another exemplary graph of a one-twelfth cycle RMS calculation and a full cycle RMS calculation.

FIG. 16 shows an exemplary control system response using a one-tenth cycle RMS calculation and a full cycle RMS calculation.

FIG. 17 illustrates an exemplary generator controller.

FIG. 18 illustrates an exemplary flow chart for operation of the generator controller of FIG. 17.

FIG. 19 illustrates another exemplary flow chart for operation of the generator controller of FIG. 17.

Detailed Description

Various feedback control systems or algorithms in the generator system utilize generator waveform measurements. Examples include phase identification, generator parallel or synchronization, energy production calculations, reactive power calculations, generator monitoring, troubleshooting, and other examples.

Phase identification includes techniques and algorithms for identifying phases in a multi-phase system. Phase identification can determine the order of the three phases in a three-phase system. Phase identification may identify which of the three outputs (e.g., a-phase, B-phase, C-phase) corresponds to a particular phase in the generator system. Phase identification may determine which of a plurality of outputs of the generator should be connected to a bus, load, or other particular phase of the generator.

In generator parallel or synchronization, the speed or frequency of one generator is matched to the speed or frequency at the bus or another generator. The waveform is measured to control a generator to have the same voltage, frequency, phase sequence and phase angle as another generator or bus.

The generator waveform measurements may be used to determine the sign of the reactive power. Reactive power can be calculated from the square root of the squared difference of the active power and the apparent power (e.g., the vector of apparent power is the hypotenuse of a right triangle having the vector of active power and reactive power as legs, where the sum of the squares of the leg lengths is equal to the square of the hypotenuse length). Since the reactive power is derived from a square calculation (i.e. by calculating the square root), its sign, i.e. whether the value of the reactive power is positive or negative, is uncertain. The sign of the reactive power used to determine whether the engine voltage leads or lags the generator current can be calculated from the generator waveform measurements described herein, including the offset angle. A positive bias angle corresponds to a current lagging the voltage and a negative bias angle corresponds to a current leading the voltage.

The calculation of the sign of the reactive power is particularly challenging when significant harmonics appear in the output. In the presence of harmonics, the signal in the output may be three, five or other multiples of the fundamental frequency. These harmonic signals cause the current to appear to lead and lag the voltage simultaneously when zero-crossings are used to determine the phase between the current and voltage, because the current zero-crossings occur both before and after the voltage zero-crossings. However, the phase offset of the generator waveform templates described herein is based only on the fundamental frequency and is independent of the number or amplitude of other harmonics.

In other examples, the generator waveform may be monitored to present a graphical chart (e.g., a phasor graph) to a user to illustrate the relationship between the current and voltage output by the generator. An exemplary phasor diagram is shown in fig. 1. The phasor diagram includes a two-dimensional or three-dimensional diagram including a vector for current and a vector for voltage. An angle between the current vector and the voltage vector may be determined based on the phase angle. The phasor diagram indicates whether the current leads or lags the voltage, and vice versa, and also indicates the magnitude by which the current leads or lags the voltage.

The generator waveform may be measured in order to monitor the generator or generator system. The output waveform of the generator may be monitored to identify anomalies in the output. The anomaly may include an output voltage or current below a threshold, an output voltage or current above a threshold, or a threshold change in frequency. Troubleshooting of the generator system may be performed based on detection of these anomalies to identify faulty components of the generator system.

The following embodiments present techniques for measuring generator waveforms. In these techniques, specific algorithms are applied to the output of the generator system in order to minimize the computer resources required to measure the generator waveform. For example, in some techniques, a small sample of the generator output is required in order to produce a reliable and accurate measurement of the generator waveform. In other examples, only a short sample time, less than a signal cycle, is required to produce a reliable and accurate measurement of the generator waveform.

FIG. 2 illustrates one example of a generator 10 including an alternator 15, an engine 19, and a controller 100, the controller 100 including a template module 11, a template comparator 13, and a generator command module 14. Template module 11 may include hardware or circuitry for generating and storing templates, including a waveform generator as a separate hardware block or integrated circuit dedicated to producing waveforms and specific amplitude, frequency and/or phase offsets. The template comparator 13 may comprise hardware or comparator circuitry including one or more operational amplifiers and resistors whose resistance values may be selected to compare one voltage with another. The generator command module 14 may include hardware or circuitry for generating generator commands. The command module circuit may be a digital or analog circuit that receives an input of the selected template from the template comparator 13 and outputs a command for the generator system. Additional, different or fewer components may be included.

The engine 19 includes one or more cylinders and a combustion chamber that receives fuel and combusts the fuel to move the cylinders in a reciprocating motion to rotate a shaft mechanically coupled to the alternator 15. The fuel may be diesel, compressed natural gas, propane, or other exemplary fuels. The controller 100 may provide an ignition control signal (e.g., a spark module signal) for initiating combustion in the combustion chamber to cause reciprocation. The alternator 15 may be a controllably excited alternator in which the field current is actively controlled by the controller 100 to adjust the output (e.g., amplitude, current, frequency, or phase) of the alternator 15. In addition, the controller 100 may control the generator's protection functions or simply meter the output from the alternator. The alternator 15 may be configured to generate a multi-phase signal or a single-phase signal. As the exciter portion of the alternator rotates relative to the armature, the magnetic flux passes through and across the alternator armature winding which produces a time-varying voltage. The output of the alternator 15 may be a three-phase signal. The phases of the multi-phase signals may be offset from each other by a predetermined angle (e.g., 120 ° or 2 π/3 radians). The multi-phase signal may vary in amplitude and frequency.

The template comparator 13 of the controller 100 compares the measured generator waveform with one or more templates of generator waveforms generated by the template module 11 or stored by the template module 11. The measured generator waveform may correspond to the output of the alternator 15. The output may include one or more voltage waveforms, one or more current waveforms, or one or more power waveforms.

The controller 100 is configured to identify the measured generator waveform and perform a discrete analysis of the generator waveform. For example, the controller 100 may include a sampling circuit including a timer and a sensor for determining sampled values of the generator waveform at preset time intervals. The sampling circuit may be an analog-to-digital conversion circuit, such as a sigma-delta or successive approximation register. It may also be an analog sample and hold (sample and hold) circuit, including resistors and switches, among other technologies. By means of the switch, the resistor can be connected to the input signal only at certain moments.

The template module 11 may include various templates corresponding to preset phase angles for the generator waveforms. In some examples, the templates are generated on the fly by the controller 100. In other examples, template module 11 includes templates at a particular frequency and a particular phase angle. In either example, template module 11 may associate a phase angle value with each of the templates.

The template comparator 13 of the controller 110 is configured to perform a series of iterative comparisons between the measured generator waveform and the sets of templates. The first iteration of templates may include any number of templates. Fig. 3 shows an exemplary set of two templates 16a and 16b for measuring the generator waveform. In this example, the two templates are 180 degrees out of phase with each other (e.g., template 16a has a phase offset of 0 degrees and template 16b has a phase offset of 180 degrees), but the templates may be separated by any value of phase angle.

The controller 100 performs a first comparison between a first set of phase templates or waveform templates and the results of a discrete analysis of the generator waveform. The comparison includes a comparison between sampled values from the measured generator waveform and values from the first set of phase templates. The controller 100 may identify a first array A1 of values of the measured generator waveform, and second and third arrays B of values identifying a first set of waveform templates₁And B₂：

A₁＝[X1,X2,X3,X4,X5]；

B₁＝[Y1,Y2,Y3,Y4,Y5]；

B₂＝[Z1,Z2,Z3,Z4,Z5].

The controller 100 is configured to determine for the first array A₁And a second array B₁Difference array A of differences between₁-B₁And for the first array A₁And a third array B₂Difference array A of differences between₁-B₂. The difference may be an absolute value.

A₁-B₁＝[X1-Y1,X2-Y2,X3-Y3,X4-Y4,X5-Y5]；

A₁-B₂＝[X1-Z1,X2-Z2,X3-Z3,X4-Z4,X5-Z5].

The controller 100 may be configured to calculate a difference value for the difference array a₁-B₁Sum of amplitude or components A₁B₁And a difference array A₁-B₂Sum of amplitude or components A₁B₂. The component sum may comprise the sum of each component vector of the difference array:

A₁B₁＝[X1-Y1+X2-Y2+X3-Y3+X4-Y4+X5-Y5]；

A₁B₂＝[X1-Z1+X2-Z2+X3-Z3+X4-Z4+X5-Z5].

the magnitude of the difference array may comprise the square root (sqrt) of the sum of the squares of the vector components of the difference array:

|A₁B₁|＝sqrt((X1-Y1)²+(X2-Y2)²+(X3-Y3)²+(X4-Y4)²+(X5-Y5)²)；

|A₁B₂|＝sqrt((X1-Z1)²+(X2-Z2)²+(X3-Z3)²+(X4-Z4)²+(X5-Z5)²).

the controller 100 may be configured to select one of the first set of phase templates based on the first comparison. The controller 100 may select the template that is closest to the measured generator waveform. For example, the controller 100 may compare the magnitudes of the difference arrays. For example, for the measured generator waveform associated with array A1, when | A₁B₁| is less than | A₁B₂When | the controller 100 selects and array B₁Associated template, and when | A₁B₁| is greater than | A₁B₂When | the controller 100 selects and array B₂An associated template.

The controller 100 may iteratively perform one or more comparisons with the measured generator waveform. The second iteration may be determined based on the results of the first iteration. In the above example, when | A₁B₁| is less than | A₁B₂When | A, the controller 100 selects the first set of the second templates, and when | A₁B₁| is greater than | A₁B₂In | the controller 100 selects the second set of second templates.

The controller 100 may be configured to perform an iterative series of comparisons between the measured generator waveform and the plurality of sets of templates based on discrete analysis results of the generator waveform. The controller 100 may perform a first comparison of the first set of phase templates with results of a discrete analysis of the generator waveform. The comparison may include a comparison between sampled values from the measured generator waveform and values from each of the second set of phase templates. The controller 100 may be configured to determine a difference array based on the measured generator waveform and each of the second set of waveform templates. The controller 100 may calculate the magnitude of the difference array as the square root of the sum of squares of the vector components of the difference array (sqrt) or calculate the sum of the components of the vector components. The controller 100 may be configured to select one of the second phase templates based on the comparison. The controller 100 may select the template that is closest to the measured generator waveform, and this sequence may be repeated for one or more iterations.

The controller 100 may select each phase template at the midpoint between the two previously compared templates having the lowest difference. The previous midpoint template may become an end template determined for the subsequent midpoint template. The midpoint template may be iteratively selected until a desired accuracy is achieved for the number of measurements.

The controller 100 may identify a characteristic value of the generator waveform based on a selected one of the second set of phase templates. The controller 100 may take a phase angle value from the template module 11 and assign the phase angle value as a characteristic value of the measured generator waveform.

The generator command module 14 of the controller 100 may include calculating a generator parameter based on a characteristic value from a selected one of the second set of phase templates. The generator parameters may include a phase angle of the measured generated waveform, a power factor of the measured generated waveform, a reactive power value of the measured generated waveform, a user profile of the measured generated waveform, or a generator command based on the measured generated waveform.

FIG. 4 illustrates another example set of templates for generator waveform measurement. In one example, the controller 100 may perform only a single iteration of the template comparison. The controller 100 may compare the measured generator waveform to the template to estimate the phase angle. For example, the controller 100 may identify whether the measured generator waveform is associated with or closest to one of the three phases. For example, the generator system may output three phases (e.g., a-phase, B-phase, C-phase) that are separated by an angle of approximately 120 °. Each of the templates may correspond to one of the facies (e.g., template 17a corresponds to facies a, template 17B corresponds to facies B, and template 17C corresponds to facies C).

Using the above exemplary calculations, controller 100 may calculate a difference array based on the measured generator waveform and each of template 17a, template 17b, and template 17 c. The controller 100 may compare the differences and select a template and corresponding phase with the smallest difference from the measured waveform. The controller 100 designates the phase of the measured waveform as, for example, the a-phase.

In response to a determined phase angle, controller 100 may generate a phase display indicating the determined phase angle. The phase display may instruct the user to connect the measured generator output to the bus, the load, or the a-phase of another generator. In response to the determined phase angle, the controller 100 may generate a breaker command to cause a breaker associated with the measured generator output to open the connection with phase a. For example, the command may be a generator parallel command instructing one or more generators in the generator system to be connected in parallel with each other. One of the generators may be instructed to start based on a generator parallel command, or in the alternative, one or more running generators may be instructed to operate at a particular speed (e.g., increase or decrease the current speed based on a speed bias command), operate at a particular voltage (e.g., increase or decrease the current voltage based on a voltage bias command), or a breaker control signal to open or close a breaker to connect the generator to the bus.

FIG. 5 illustrates another exemplary set of templates for generator waveform measurement. The controller 100 may perform multiple iterations in the template comparison. Templates 18a, 18b, 18c, and 18d illustrate an example that includes four templates for the first iteration of the template comparison. The template 18a may correspond to a phase offset of 0 °, the template 18b may correspond to a phase offset of 90 °, the template 18c may correspond to a phase offset of 180 °, and the template 18a may correspond to a phase offset of 270 °.

Consider an example in which the measured generator waveform has an offset of 120 °. The controller 100 compares the templates 18a, 18b, 18c, and 18d to the measured generator waveform. Two-by-two differences between each of the templates and the measured generator waveform are calculated. The sum of each of the differences is compared in the template to identify the template that is closest to the measured generator waveform. The controller 100 selects a template for the second iteration based on the sum of the closest differences.

In the example where the measured waveform is at a 120 ° offset, the second set of templates is between template 18b at a 90 ° offset and template 18c at a 180 ° offset. The second set of templates may include templates at 135 offset and templates 18b at 90. In a second iteration, pairwise differences between the second set of templates and the measured generator waveform are calculated. The sum of each of the differences is compared in the template to identify the template that is closest to the measured generator waveform. If the process ends after two iterations, the controller 100 selects the closest template as the estimated phase angle. If the iteration continues more than two, the controller 100 selects the template for the third iteration based on the closest sum of the differences.

In the example where the measured waveform is at 120 ° offset, the closest template in the second iteration is the template at 135 ° offset. The controller 100 selects the third iteration based on the 135 offset. For example, the controller 100 selects a template at a 112.5 offset from the neutral position between the second set of templates. In a third iteration, pairwise differences between the third set of templates and the measured generator waveform are calculated. The sum of each of the differences is compared in the template to identify the template that is closest to the measured generator waveform. If the process ends after three iterations, the controller 100 selects the closest template as the estimated phase angle. If the iteration continues beyond three, the controller 100 selects a template for the fourth iteration based on the closest sum of the differences.

In the example where the measured waveform is at 120 ° offset, the closest template in the third iteration is the template at 112.5 ° offset. The controller 100 selects the fourth iteration based on the 112.5 ° offset. For example, controller 100 selects a template at an offset of 123.75 ° from the neutral position between the templates of the third set. If the process ends after four iterations, the controller 100 selects the closest template as the estimated phase angle. If the iteration continues beyond four, the controller 100 selects the template for the fifth iteration based on the closest sum of differences. The process may have any number of iterations.

The template may be pre-computed and stored in memory, generated during a startup sequence, generated on demand, or generated at other times. It may be generated as an array of samples, or each sample may be generated in turn without storing the other samples. The templates may be generated or stored in hardware or software, and the subtraction between templates may be performed in hardware or software.

FIG. 6 illustrates another example set of templates 19a-19p for measuring generator waveforms. In one example, there may be more than four initial templates, e.g., 16 initial templates 19a-19p may include successive offset phase angles of 22.5 °, 45 °, 67.5 °, 90 °, 112.5 °, 135 °, 157.5 °, 180 °, 202.5 °, 225 °, 247.5 °, 270 °, 292.5 °, 315 °, 337.5 °, and 360 ° (0 °). Between each of the 16 initial templates 19a-19p, the second set of templates may include a template midway between successive templates that is paired with one of the 16 initial templates to form the second set of templates for the second iteration.

In other words, the second set of templates may include fewer templates (e.g., a smaller or smaller number) than the first set of templates (e.g., a larger or larger number). The example of fig. 6 includes 16 templates for the first set of templates and 2 templates for the second set of templates.

A larger number of templates for the first set of templates (first iteration) may be selected as an efficient application of computer resources. The first set of templates is applied to all possible measured waveforms. In other words, the first step in the process is to apply the first set of templates, regardless of the phase offset of the measured waveform. Subsequent sets of templates are only used when the measured waveform falls within a particular range of these templates. Therefore, it would be less advantageous to include more templates in the second set of templates. In other words, when 16 templates are used in the first set of templates, these templates are for each measured waveform, but assuming that the phase offsets of the measured waveforms are evenly distributed, any given template in the second set of templates is for 1/16 measured waveforms only.

Fig. 7 shows an example of a measured generator waveform 41 illustrating the advantages of the iterative template matching method described herein. When modeled by a sine wave, the output of the generator is different from the mathematically ideal sine wave. The noise causes the output of the generator to fluctuate on a mathematically perfect sine wave. In addition, thyristors or other switches that allow a large amount of current to flow in a non-linear manner result in asymmetry in the generator waveform due to sub-cycle current changes. The thyristor or SCR may cause the output voltage to drop to near 0 or even below 0 when the output current is changed by inductance in the stator of the alternator 15 due to first conduction by resistance. In addition, after the generated voltage of the alternator 15 passes through 0, the thyristors may continue to allow current to flow due to the inductance of the stator, resulting in a flat portion of the waveform near a typical zero crossing.

Using one analysis, the measured generator waveform is analyzed based on the zero crossings. The zero crossings are detected in the measured generator waveform as occurring at a first time and compared to zero crossings of the ideal sinusoidal waveform at a second time. The time period of one cycle is calculated based on the measured waveform. The difference between the first time and the second time is divided by the time of the cycle or cycle and, optionally, multiplied by 360 ° to calculate the phase angle between the measured generator waveform and the ideal waveform. While this technique may provide accurate results in many cases, noise or other phenomena may cause the zero crossings of the measured generator waveform to occur at irregular times, and the calculation of the period or time between waveforms is therefore affected, resulting in an incorrect calculation of the phase angle.

One technique for overcoming this erroneous calculation of the phase angle includes fourier transform or Fast Fourier Transform (FFT) of the two signals. One example may include 200 milliseconds (ms) (i.e., 12 cycles at 60 Hz) of data from a measured waveform that is subjected to complex matrix analysis to convert it into the frequency domain. The FFT of the data includes frequency components derived from the amplitudes of the complex components in the synthesis matrix after conversion to the frequency domain.

Each component, including the base waveform, is computed as a complex number, allowing illustration as amplitude and phase. The phase of each base waveform may be obtained by synthesizing matrices, providing phase angles associated with the virtual reference signals. The phase angle obtained by taking the fourier transform of the signal can be subtracted to remove the virtual reference signal from consideration and to provide the phase between the signals. However, the phase angle indicated in this case is actually the phase angle between the average phases of the two signals, which may be significantly different from the actual phase angle between the signals at the time of calculation, even if the calculation is performed within a relatively short period of time than the cycle of the alternator waveform.

However, the difference between the waveforms is actually the difference in the average over the analyzed time period. For example, when the sampling period provided to the fourier transform or FFT is 200ms, the average phase angle is closest to the phase angle between the signals in the middle of the sampling window, or 100ms prior to the signal measurement.

While a multi-cycle fourier transform or FFT can provide a very accurate phase angle between signals of the same frequency (where the phase angle between the signals does not change), the measured phase angle is delayed relative to the actual phase between the signals at the time of calculation. Although it is possible to establish the signal phase angle using FFT on a single cycle, the required sampling rate for this calculation and the corresponding number of calculations required may require special, dedicated hardware, such as FPGA or ASIC.

The computation required for a fourier transform or FFT increases linearly as the sampling window size decreases in time due to the need to bring a given number of data set samples to a given accuracy. To reduce the sampling window size in time while maintaining a similar number of samples as the algorithm, the sampling rate is increased. In addition, the calculation also requires the same number of operations, so increasing the calculation frequency will certainly result in a linear increase in the number of instructions per second that have to be executed in the processor, FPGA or ASIC.

The computation required for a fourier transform or FFT increases linearly as the sampling window size decreases in time due to the need to bring a given number of data set samples to a given accuracy. In order to reduce the sampling window size in time while maintaining a similar number of samples as the algorithm, the sampling rate must be increased. In addition, the calculation also requires the same number of operations, so increasing the calculation frequency will certainly result in a linear increase in the number of instructions per second that have to be executed in the processor, FPGA or ASIC.

If the sampling rate is increased to establish 10,000 samples (600,000 samples/second) in one single cycle of a 60Hz waveform, the calculation will still require 4,000,000 instructions, but run 60 times per second, requiring 240,000,000 instructions per second for a single volatility calculation processor.

By comparison, the template matching technique is able to maintain a similar or identical sampling rate when the sampling window is reduced in time, meaning that the number of elements in the template will be reduced. Although the calculations are performed more frequently, the operations required to perform the method will be reduced.

For example, at a sampling rate of 6,000 samples per second, a single cycle template will include 100 samples of a 60Hz waveform. If the computation iterates 15 times, the template subtraction will be computed 16 times, resulting in 1600 subtractions in the processor, plus the lookup time for the template. This may require few instructions per second in the processor, such as 60 x 1600, i.e. 96,000 instructions.

If the calculation is performed 10 times per cycle, the template size is only 10 cycles long, so even if it is performed 600 times per second, only 10 subtractions are needed for template subtraction, so the total subtraction can be very few, e.g. 600 × 160 — 96.000. This means that only the increase in load from the increase in sampling rate can be correlated to processor cycles that query the appropriate template.

Fig. 8 shows a comparison between phase angle calculations using a template and phase angle calculations using a finite transform (e.g., fourier transform). Fig. 20 includes a comparison between an "input" waveform 21 shown in solid lines and a "run" waveform 23 shown in dashed lines, such that the run frequency and the input frequency are different, and thus the phase angle between them varies with time. By visually comparing the solid and dashed lines, the phase offset between the waveforms can be estimated. When the solid and dashed lines overlap, the phase offset is close to 0. Fig. 20 also includes a first phase angle calculation 25 using standard FFT calculations and a second phase angle calculation 27 using template matching techniques.

For example, a first phase angle calculation 25 based on FFT requires 12 cycles at 60Hz, 10 cycles at 50Hz (200ms period). The result of the first phase angle calculation 25 experiences an observable delay of half the total cycle time (6 cycles of a 100ms or 60Hz waveform). Fig. 20 shows that the first phase angle calculation 25 reports a phase angle much greater than 0 when the two waveforms are synchronized at the synchronization point 28. The level at the synchronization point 28 corresponds to the phase angle average of the last 12 cycles, but most closely symbolizes the actual phase angle of the past 100 ms.

Using the first phase angle calculation 25, the result is often delayed by at least this theoretical minimum. Fig. 20 shows that the first phase angle calculation 25 is much higher than 0 at the actual Zero Crossing (ZC). The level of ZC corresponds to the average of the previous 6 cycles.

On the other hand, the second phase angle calculation 27 using real-time FFT or template matching techniques is instantaneous or substantially instantaneous. Fig. 20 shows that the second phase angle calculation 27 is at or near 0 when the comparison indicates that the waveforms 21 and 23 substantially overlap at the synchronization point 28.

Fig. 9 shows the output signals for alternators with different pitches and, if connected in parallel, also with current passing between them. The techniques for template matching may also accurately measure the phase angle for a generator waveform when two or more generators with different pitches are connected together in parallel. The term pitch refers to the percentage of each pole of the alternator that is filled with windings. The spacing describes how much of the available magnetic area the coil surrounds. Spacing on alternators dedicated to generating AC for distribution is rarely uniform due to physical limitations and Total Harmonic Distortion (THD) requirements. Examples of alternator spacing include 5/6 spacing or 2/3 spacing. A higher fraction for the alternator spacing is associated with more energy from a given amount of iron and copper, but consumes more harmonic content, and therefore more THD.

In fig. 9, fig. 35 includes a high pitch waveform 37 (e.g., 5/6 output pitch) and a low pitch waveform 36 (e.g., 2/3 output pitch). The harmonic current waveform 38 shows harmonics caused by current flow when a high-pitch alternator and a low-pitch alternator are connected in parallel. The output voltages of two generators of different spacing have different shapes, and when connected in parallel, the output voltage of the parallel system is the average of the output voltages of the two generators.

When two generators of different spacing are connected in parallel, one or more harmonic currents may flow between the generators (e.g., third harmonic, fifth harmonic, etc.). In one example, two generators (generator 1 and generator 2) are electrically coupled in parallel or in parallel. Two generators may produce one or more harmonics and different voltage levels, causing the current associated with these harmonics to flow between the parallel generators.

In one example, the generator 1 may produce a high output (e.g., 120 volts) at the fundamental or first harmonic, a near no output or 0 volts (e.g., 0.1 volts) at the higher harmonics (e.g., third harmonic), and an approximately medium output (e.g., 5 volts) at the highest significant harmonic (e.g., fifth harmonic). In contrast, the generator 2 may produce a high output (e.g., 120 volts) at the fundamental or first harmonic, an approximately medium output (e.g., 6 volts) at the higher harmonic (e.g., third harmonic), and near no output or 0 volts (e.g., 0.1 volts) at the highest significant harmonic (e.g., fifth harmonic).

In operation, the generator 2 provides a short circuit of the generator 1 at the fifth harmonic and the generator 1 provides a short circuit of the generator 2 at the third harmonic. The generator 1 operates as a short circuit at the third harmonic, while the generator 2 operates as a short circuit at the fifth harmonic. Thus, there is a current flowing between the two generators having a frequency of approximately 180 hertz, and there is a current flowing between the two generators having a frequency of approximately 300 hertz.

Third and fifth harmonics can corrupt the detection of the phase angle of the fundamental harmonic. When the current of the fundamental harmonic is weak, the current flowing between the generators for the third and fifth harmonics can be detected, and particularly, the zero-crossing points of the third and fifth harmonics can be detected. In calculating the phase angle based on the zero crossing, the phase angle may be erroneously calculated based on the third harmonic and the fifth harmonic, resulting in an erroneous estimation of the phase angle. Due to the multiple zero crossings, the current may appear to both lead and lag the voltage. For example, comparing zero crossings in current waveform 38 in FIG. 35 with zero crossings in voltage waveforms 36 and 37, current 38 includes zero crossings that simultaneously lead and lag voltage waveforms 36 and 37.

The template matching technique described herein does not rely on the accuracy of zero crossing detection. Thus, the template matching technique overcomes the problems caused by zero crossings in the third and fifth harmonics, since the fundamental phase angle can be detected even though the current has a significantly higher amplitude due to the higher order harmonics compared to the fundamental waveform.

Advantages of the template matching techniques described herein include reaction to required time, reduction of noise phenomena, reduction of Total Harmonic Distortion (THD) phenomena, flexibility of sample size, flexibility of sample selection, reduction of processor load, and other advantages.

In the zero crossing technique, at least one complete cycle or cycle of the measured waveform is required. The phase angle is calculated based on the time period of the cycle calculated by detecting the cycle duration of the measured waveform. Therefore, the reaction time of the zero crossing technique cannot be less than one cycle of the measurement waveform. In the template matching technique, the reaction time is significantly reduced because much less generator waveforms are required. In some examples, template matching is achieved by using half a cycle of the measurement waveform. In other examples, a smaller portion of the cycle of the measured waveform may provide suitable data for comparison with the template. Examples of the smaller portion may be 1/10, 1/20, or 1/30 of the cycle of the measured waveform. Template matching is also flexible in sample size. Different sample sizes may be used for different scenarios.

Template matching techniques may be used to establish the fundamental frequency, the fundamental voltage, the fundamental phase angle, or any combination of the three. Template matching techniques may also be used to count harmonic amplitudes and phases.

The template matching technique is also flexible in sample selection. I.e. various parts of the generator waveform can be used. The sampling selection need not include a zero crossing of the measurement waveform. The portions of the samples may be randomly selected in time. The choice of sampling may vary depending on the difference between the measured waveform and the closest template. In the event that the difference between each template and the measured waveform exceeds a threshold, the controller 100 may adjust the sampling selection or make another sampling selection. In some examples, the portion of the cycle sampled for template matching may be selected based on waveform peaks, inflection points, zero crossings, maximum slopes, minimum slopes, zero slopes, irregularities, or at fixed intervals regardless of input waveform characteristics.

The template matching technique can reduce the influence of noise. Noise on the measured waveform can cause the measured waveform to float above or below zero near the zero crossing. Noise corrupts the calculation when the phase offset is judged by means of the zero crossing. However, in the template matching technique described herein, zero crossings are not used, which minimizes the effect of noise. Similarly, THD also affects phase offset in zero crossing calculation and can be minimized by template matching.

In another example, a template matching technique is used to measure THD. The controller 100 may estimate THD based on the difference between the measured generator waveform and the base amplitude established by the closest template. Consider an example of multiple iterations of template matching. The controller 100 may designate a particular iteration (e.g., the third iteration) as having had enough fine-tuning to approximate the measured waveform. Remember that when the first iteration includes 16 template partitions, the second iteration includes 2 template partitions, and the third iteration includes 2 template partitions, the resolution of the third iteration may be about 0.2% (10%/16/2/2 ═ 0.156%). When the difference between the generator waveform measured in the third iteration and the closest template changes over time and for multiple instances of template matching, the closest template may be different for each test. The composite amplitude determined by the template matching technique corresponds to the base amplitude of the waveform, which can be compared to the measured RMS amplitude to determine THD.

The controller 100 may also determine a sample size for template matching based on the THD estimate. For example, when the THD estimate is greater than a threshold, the sample size increases, and when the THD estimate is less than the threshold, the sample size decreases. The sample size may be increased or decreased by increasing or decreasing the sampling interval between samples or by increasing or decreasing the time span used for sampling.

Fig. 10 illustrates an exemplary generator 110. As described above, the generator 110 may include the alternator 15, the engine 19, and the controller 100. The controller 100 may include an event detector 111, a waveform calculator 113, and a generator command module 114. The event detector 111 may include hardware or circuitry for measuring events in a waveform defined by curvature changes or zero crossings. The waveform calculator 113 may be used to measure electrical parameters of the waveform, such as amplitude, frequency, and/or phase offset. The generator command module 114 may include hardware or circuitry for generating generator instructions. The command module circuit may be a digital or analog circuit that receives an input of the selected measured waveform from the waveform calculator 113 and outputs a command to the generator system. The controller 100 of fig. 9 may incorporate the features described above, particularly in conjunction with the features of fig. 2. For example, the event detector 111 and the waveform calculator 113 may be combined with the template module 11 and the template comparator 13. Additional, different or fewer components may be included.

The controller 100 is configured to calculate statistical parameters of the measured generator waveform. The generator waveform may be the output of the alternator 15 and include a single phase waveform or multiple phase waveforms. The statistical parameter may be a Root Mean Square (RMS) value. The RMS value is the square root of the sum of the mean of the squares of a sampled set of the cycles or cycles across the generator waveform. The RMS value may be estimated using less than one complete cycle of the generator waveform. In some examples, the RMS value is based on less than 1/2 of the period of the waveform. The RMS value may be calculated as one-twelfth of the period of the three-phase waveform.

The controller 100 identifies at least one generator waveform. The generator waveform may include a matrix of numbers describing the electrical values of the output of the generator. The generator waveform may be monitored using a sensor, such as a voltage sensing circuit or a current sensing circuit. The matrix of numbers may be samples collected by a sampling circuit. The at least one generator waveform may include a single phase or multiple phases. At least one generator waveform may be output from a line level to a neutral point or measured from between lines (e.g., imagine one another).

The event detector 111 of the controller 100 detects a first event of at least one generator waveform. The first event may be a critical point of the generator waveform (e.g., an algebraic critical point of an algebraic function closest to the generator waveform). The first event or critical point may be a zero crossing of the waveform, a local maximum of the waveform, a local minimum of the waveform, or an inflection point of the waveform. A zero-crossing is a point along the generator waveform where the generator waveform crosses a zero point (e.g., the x-axis) such that points before the point are all negative numbers and points after the point are all positive numbers, or vice versa.

The local minimum is a point along the generator waveform that makes the points before and after in time larger than that point. The local maxima are points along the generator waveform that are such that the points before and after in time are smaller than this point. The local maxima or minima may be identified as zero crossings of the first derivative of the algebraic function of the generator waveform. An inflection point is a point along the generator waveform that has a positive curvature at a point prior in time and a negative curvature at a point subsequent in time, or a negative curvature at a point prior in time and a positive curvature at a point subsequent in time. The inflection point may be identified as a zero crossing of the second derivative of the algebraic function of the generator waveform.

The controller 100 identifies a second event of the at least one generator waveform. The second event may be a critical point of the generator waveform. The second event may be a zero crossing of the waveform, a local maximum of the waveform, a local minimum of the waveform, or an inflection point of the waveform.

The first event and the second event may be critical points in the same signal or critical points in different phases of the generator waveform. Consider a generator waveform having three phases (e.g., a-phase, B-phase, and C-phase). The first event may be a critical point in one of the phases and the second event may be a critical point in another of the phases. For example, the first event may be a zero crossing in phase a and the second event may be an inflection point in phase B, the first event may be a local maximum in phase C and the second event may be a local minimum in phase a, or the first event may be a local maximum in phase B and the second event may be an inflection point in phase C. Other combinations are also possible.

The controller 100 determines a time interval between the first event and the second event. The time interval spans less than half a cycle of the at least one generator waveform. In some examples, the time interval is 1/12 or less of a cycle. Examples of time intervals include 5/12 cycles, 1/3 cycles, 1/4 cycles, 1/6 cycles, and 1/12 cycles.

The waveform calculator 113 of the controller 100 calculates a representative root mean square value of at least one generator waveform over a time interval. In the calculation of the RMS value, the controller 100 may combine portions of the generator waveform from the various phases to estimate the RMS value for the entire generator waveform. Alternatively, in the calculation of the RMS value, the controller 100 replicates or extrapolates a portion of the single phase waveform at intervals less than half a cycle of the generator waveform. Using a portion of the waveform that is waveform symmetric, extrapolating a portion using the shape of the stored wave or waveform, comparing the waveform to a template, or limiting the sampling window to a representative portion of the entire cycle. This can be performed on a single phase or three phase waveform.

Fig. 11 shows an example of a generator waveform comprising three phases, e.g. a first phase 24 (shown by solid lines), a second phase 26 (shown by dotted lines) and a third phase 28 (shown by dashed lines). The generator waveform is divided into slices with a time interval equal to 1/12 of the period. Each of the 12 slices 22A-22L represents a time interval that can be used to calculate an RMS value representative of the overall generator waveform 30.

Fig. 12 shows 3 exemplary time slices (time slices 22A, 22F, 22K). The time slice 22A includes a first portion 31a corresponding to the a-phase of the generator waveform, a second portion 31B corresponding to the B-phase of the generator waveform, and a third portion 31C corresponding to the C-phase of the generator waveform.

The absolute values of the first, second and third portions 31a, 31b, 31c correspond to a quarter of a cycle of the generator waveform. Consider an example of a map of the first phase 24 extending between zero crossings near the slices 22D-22J. The absolute value of the half cycle includes all values in the sine wave. That is, the absolute value of the sine wave comprises a repeating pattern at half the initial period. Thus, a half cycle of a sine wave already includes all the data needed to describe the entire sine wave. Closer examination revealed that the half cycle was also symmetric about the vertical line and included two sets of data, where half of the data was sufficient to describe a sine wave. Thus, 1/4 of a cycle of sine waves includes enough data to individually depict a sine wave.

Similar principles may also be applied to multiphase generator waveforms, where each phase is substantially similar to the other. When the two phases of the sine wave are located in one time slice of 1/4 cycles of the sine wave, each phase includes enough data to uniquely describe the sine wave. Only half of the data is needed. For a two-phase signal, a time slice of 1/8 cycles of the sine wave is sufficient to describe the sine wave. When the three phases of the sine wave are in one and the same time slice of the 1/4 cycles of the sine wave, each phase also includes enough data to uniquely describe the sine wave. Only one third of the data is needed. For a three-phase signal, a time slice of 1/12 cycles of the sine wave is sufficient to describe the sine wave.

The waveform calculator 113 of the controller 100 may include a sampling circuit or a detection circuit for collecting measurements of the generator waveform. The measurement or sampling may be for a single phase or multiple phases. In the case of multiple phases, the waveform calculator 113 may include a sampling circuit for each phase, or a three-phase sampling circuit, so that data is collected simultaneously or near simultaneously. Near-simultaneous may be defined as within a mutual time period, and the time period may be in the range of 1 to 20 microseconds.

The waveform calculator 113 of the controller 100 may aggregate measurements from each of the phases of the generator waveform. That is, the waveform generator 113 may identify a plurality of measurements from a first phase of the generator waveform, a plurality of measurements from a second phase of the generator waveform, and a plurality of measurements from a third phase of the generator waveform. The waveform calculator 113 may square the measurements from each phase, sum the squares and perform an open square root operation of the sum of squares.

Measurements from the first phase, measurements from the second phase, and measurements from the third phase are collected during a preset time period. The time period may be a fractional portion of a cycle of the generator waveform. The time period may be greater than zero and less than half of a cycle of the generator waveform. The time period may extend from a critical point of one phase of the generator waveform to a critical point of a second phase of the generator waveform. The time period may extend from a critical point for one phase of the alternator waveform, through a critical point for a second phase of the alternator waveform, to a critical point for a third phase of the alternator waveform.

The generator command module 114 analyzes the RMS value to generate a command for the generator system. The command may be an instruction for adjusting the field current of the alternator 15. The command may be an instruction to close the generator to the bus when the amplitude of the measured waveform is within a preset range. The command may be a throttle command to adjust a throttle of the engine 15 when the measured waveform has an RMS value outside a preset range.

Fig. 13 shows line-to-line and line-to-neutral point values for a three-phase sinusoidal signal. Referring ahead to slices 22A-22L in fig. 11, the partitioning of the slices may result from zero crossings occurring between line values or line to neutral values. For example, the line-to-line voltage 43a crosses zero twice, the line-to-line voltage 43b crosses zero twice, and the line-to-line voltage 43c crosses zero twice. Similarly, line-to-neutral voltage 41a crosses zero twice, line-to-neutral voltage 41b crosses zero twice, and line-to-neutral 41c crosses zero twice. The 12 zero crossings define the slices 22A-22L.

FIG. 14 shows an exemplary plot 150 of a one-twelfth cycle RMS calculation as well as a full cycle RMS calculation. FIG. 15 illustrates another exemplary graph of one-twelfth cycle RMS calculation and full cycle RMS calculation after a load is applied and the generator waveform is restored. Waveform 151 corresponds to the output of the generator. Square wave 157 corresponds to the RMS calculation from the full cycle RMS calculation. Square waves 153 and 155 correspond to RMS calculations measured using the generator waveforms described herein. Square wave 153 corresponds to a single phase example or quarter cycle RMS calculation and square wave 155 corresponds to a three phase example or a twelfth cycle RMS calculation. Square wave 157, calculated over the entire cycle of waveform 151. The square wave 153 is calculated by one quarter cycle of the waveform 151. Square wave 155 is calculated over one-twelfth of a cycle of waveform 151.

FIG. 16 shows an exemplary control system response using a one-tenth cycle RMS calculation and a full cycle RMS calculation. The delay in feedback is reduced by using a one-tenth (or one-quarter) cycle RMS calculation. The minimization of the delay in the feedback is shown by the response of the control system. Graph 170 includes a response 171 from the control system for a full cycle RMS calculation. Graph 172 includes a response 173 of the control system from a one-tenth (or one-fourth) RMS calculation.

Graphs 170 and 172 are from a control system with the same gain; only the sensing technology changes. When a load is applied, for example, in region a, plot 172 dips below plot 170. As shown in region B, graph 172 recovers more stable and has less overshoot when stabilized after the load as compared to graph 170. When the load is removed as shown by region C, graph 172 does not overshoot as much as graph 170.

Thus, the plot 172 of one-twelfth or one-quarter cycles provides an increased response time, which corresponds to less overshoot and faster settling in response to load changes of the generator. The increased response time provides advantages, such as an improved user experience for dimness or flickering of light. The increased response time improves the stability of the control system, which avoids oscillations for some loads.

Fig. 17 illustrates an exemplary controller (e.g., generator controller 100). The controller may include a processor 200, a memory 201, and a communication interface 203. The communication interface 203 may communicate with a parallel input signal 210, a sensor input signal 212, a display device 214, an input device 204, an excitation coil control device 216, and a parallel control device 218. Additional, different, or fewer components may be included.

FIG. 18 illustrates an exemplary flow chart for operation of the controller of FIG. 17 for iteratively analyzing operation of the generator. Additional, different, or fewer acts may be included.

At action S101, the processor 200 identifies a generator waveform. The generator waveform may be received by the sensor input signal 212 from a sensor associated with the generator output. Alternatively, the generator waveform may be received by the sensor input signal 212 from a sensor associated with the field current of the alternator or the magnetic field induced by the stator or rotor of the alternator. The generator waveform may be received from another generator from the parallel input signal 210. The generator waveform from the parallel input signal 210 is used to connect two or more generators in parallel or in synchronization. To identify the sensed signal as a generator waveform, the processor may compare the waveform amplitude to a positive threshold and a negative threshold to determine that the amplitude is greater than the positive threshold and less than the negative threshold simultaneously for a preset period of time.

At action S103, the processor 200 performs a discrete analysis on the generator waveform. The discrete analysis may include sampling the generator waveform and creating a matrix of sensor data representative of the generator waveform. The samples may be collected at a sample rate, which may be accessed from memory 201 or received via input device 204. Exemplary sampling rates include 600Hz, 1000Hz, 10,000Hz, or 44,100 Hz. Discrete analysis of the generator waveform may include a screening process that removes anomalies or noise from the sampled data. The discrete analysis may adjust the data to a preset format.

The processor 200 may identify one or more phase templates to analyze the measured generator waveform. At each phase offset, fundamental frequency, amplitude or harmonic frequency, the template is an ideal sine wave or a template data matrix representing an ideal sine wave.

The entire set of templates may include arrays offset for each possible integer degree. That is, the template set may include a1 ° offset waveform, a 2 ° offset waveform, a 3 ° offset waveform, and so on. Alternatively, the template set may include offset-spaced waveforms (e.g., 10 intervals), including 0 offset waveforms, 10 offset waveforms, 20 offset waveforms, and so forth. Each template may be associated in memory with a data value for phase offset, amplitude or frequency. Alternatively, the template may be computed on demand at startup, when the processor has available computational overhead, or at other times. The template and comparison may be done in hardware. The phase, frequency and amplitude may be controlled by software or entirely included in hardware.

In operation S105, the processor 200 performs a first comparison of the first set of phase templates with the results of the discrete analysis of the generator waveform. The first set of phase templates may span any interval of possible waveform offsets. In a minimum example, the first set of phase templates includes 0 ° and 180 ° templates. In one useful example, the first set of templates includes 16 templates, evenly distributed at offset intervals between 0 ° and 360 °.

The first comparison of the first set of phase templates to the generator waveform may be a geometric or algebraic comparison to determine how similar each of the first set of phase templates is to the generator waveform. The comparison may include a summation of the differences at individual points of the sensor data matrix and the template.

In act S107, the processor 200 selects one of a first set of phase templates based on the first comparison. The selected phase template is the template with the greatest similarity to the generator waveform. The difference between the selected phase template and the generator waveform is minimized in the analysis of the S107 action. The processor 200 selects a phase template for the second set of phase templates from the first set of templates based on the selected phase template. The second set of phase templates may include one template to any number of templates. The second set of phase templates includes at least one template that is closest to a phase template selected from the first set of templates. The templates in the second set of templates are spaced apart less than the time intervals of the templates in the first set of templates.

In act S109, the processor 200 makes a second comparison of the second set of phase templates with the results of the discrete analysis of the generator waveform. The second comparison may comprise a sum of differences in individual points in the sensor data matrix and the one or more second templates.

In act S111, the processor 200 selects one of a second set of waveform templates based on the second comparison. The processor 200 may compare the difference between the points in each of the second set of templates and determine which template has the smallest difference. Acts S109 and S111 may be repeated for any number of iterations using subsequent sets of templates with progressively smaller feature (e.g., phase, frequency, or amplitude) spacing between the templates. The waveform selected from the second set of waveforms, or the final set of waveforms when more iterations are used, is designated as an estimate of the measured generator waveform.

In action S113, the processor 200 identifies an estimated characteristic value for the generator waveform based on the selected one of the second set of phase templates. The eigenvalues estimate the bias of the measured generator waveform. The processor 200 may read the values associated with the selected waveform from the memory 201.

In action S115, the processor 200 calculates a generator parameter based on the eigenvalues of the selected one of the second set of phase templates. The generator parameter may be an indication of whether the generator is operating properly. For example, the processor 200 may compare the characteristic value to a normal range of phase values based on the operation of the engine 19 and alternator 15. When the characteristic value is outside the normal range, the generator parameter indicates a fault. The processor 200 may vary an operating parameter of the engine 19 or the alternator 15 based on the generator parameter.

The generator parameter may be an instruction to connect the generator in parallel with the bus. When the characteristic value is within the normal range for closing to the bus, the processor 200 generates an instruction for the circuit breaker to close to the bus. The generator parameter may be a command to adjust the field current. When the characteristic value is greater than the expected value for the phase offset, the processor 200 may increase the frequency of the field current, and when the characteristic value is less than the expected value for the phase offset, the processor 200 may decrease the frequency of the field current.

FIG. 19 illustrates an exemplary flow chart of the operation of the controller of FIG. 17 for determining a representative average root mean square value for a generator. Additional, different, or fewer acts may be included.

In action S201, the processor 200 identifies at least one generator waveform. The generator waveform may be received by the sensor input signal 212 from a sensor associated with the generator output. Alternatively, the generator waveform may be received by the sensor input signal 212 from a sensor associated with the field current of the alternator or the magnetic field induced by the stator or rotor of the alternator. To identify the sensed signal as a generator waveform, the processor may compare the amplitude of the waveform to a positive threshold and a negative threshold to determine that the amplitude is greater than the positive threshold and less than the negative threshold simultaneously during a preset time.

In action S203, the processor 200 identifies a first event of at least one generator waveform. In action S205, the processor 200 identifies a second event of at least one generator waveform. The first event and the second event may be a characteristic of the same phase of the generator waveform or a characteristic of different phases of the generator waveform. The waveform may be characterized by a change in curvature of the waveform or any other type of critical point described above.

In action S207, the processor 200 determines a time interval between the first event and the second event. The time interval spans less than half a cycle of the at least one generator waveform. In action S209, the processor 200 calculates a representative average root mean square value of at least one generator waveform based on the time interval.

The processor 200 may determine the generator command from the root mean square value. The generator command may be an alternator command that regulates operation of the alternator 15, an engine command that regulates the engine 19, or a generator system command that regulates interaction of multiple generators of the generator system.

One exemplary alternator command adjusts the field current of the alternator 15. The field coil control device 216 may generate a field current for driving a field coil of the alternator 15. The magnitude of the field current or the frequency of the field current may be adjusted by the field coil control device 216. The field coil control device 216 may include an amplifier circuit and/or an oscillator for controlling the field current. The input to the field coil control 216 may be a battery, an inductive source, or other power source.

The output device 214 may present a root mean square value or a generator parameter. The output device 214 may include a digital readout, an analog meter, or a graphical display for displaying root mean square values or generator parameters. The graphical display may show a phasor diagram including phase offset and amplitude for the measured waveform. The phasor diagram may include vectors of voltage and/or current representing the measured waveforms.

The shunt control 218 may provide a shunt signal based on a root mean square value or a generator parameter. The parallel signal may instruct the circuit breaker to electrically connect the generator with another generator or with the bus. The processor 200 may compare the root mean square value to an amplitude threshold, compare the eigenvalue to an offset threshold, and generate a shunt signal for the shunt control 218 based on the comparison.

The processor 200 may record the values of the generator parameters from the estimated offset values and/or root mean square values in a data log stored in the memory 201. The noted value may be associated with a timestamp. The recorded values may be reported to a remote monitoring system or a remote control system via the communication interface 203. The processor 200 may also execute a protection function based on generator parameters from the estimated bias value and/or root mean square value. The processor 200 may perform a comparison with a normal range for the bias value or the root mean square value and generate an alert when the measured value falls outside the normal range. Alternatively, the processor 200 may generate a shutdown command to disconnect the generator from the bus or ground the ignition of the engine when the measured value falls outside of the normal range.

The processor 200 may include a general processor, digital signal processor, Application Specific Integrated Circuit (ASIC), Field Programmable Gate Array (FPGA), analog circuit, digital circuit, combinations thereof or other now known or later developed processor. The processor 200 may be a single device or a combination of devices, such as associated with a network, distributed processing, or cloud computing.

The memory 201 may be a volatile memory or a non-volatile memory. The memory 201 may include one or more of the following: read Only Memory (ROM), Random Access Memory (RAM), flash memory, Electrically Erasable Programmable Read Only Memory (EEPROM), or other types of memory. The memory 201 may be removable from the network device, such as a Secure Digital (SD) memory card.

In addition to the ingress and egress ports, the communication interface 303 may include any operable connection. An operable connection may be a connection in which signals, physical communications, and/or logical communications may be sent and/or received. The operable connection may include a physical interface, an electrical interface, and/or a data interface.

The communication interface 203 may be connected to a network. The network may include a wired network (e.g., ethernet), a wireless network, or a combination of both. The wireless network may be a cellular telephone network, an 802.11, 802.16, 802.20, or WiMax network. In addition, the network may be a public network, such as the Internet, a private network, such as an Intranet (Intranet), or a combination of both, and is capable of using a variety of network protocols that are currently available or to be developed, including but not limited to TCP/IP based network protocols.

While the computer-readable medium (e.g., memory 201) is shown to be a single medium, the term "computer-readable medium" includes a single medium or multiple media, such as a centralized or distributed database, and/or associated caches and servers that store the one or more sets of instructions. The term "computer-readable medium" shall also be taken to include any medium that is capable of storing, encoding or carrying a set of instructions for execution by a processor or that cause a computer system to perform any one or more of the methodologies or operations disclosed herein.

In a particular non-limiting, exemplary embodiment, the computer-readable medium can include a solid-state memory, such as a memory card or other package that houses one or more non-volatile read-only memories. Additionally, the computer-readable medium can be random access memory or other non-volatile rewritable memory. Additionally, the computer readable medium can include a magneto-optical or optical medium, such as a disk or tape or other storage device that captures a carrier wave signal (e.g., a signal communicated via a transmission medium). A digital file attachment to an email or other self-contained information document or collection of documents may be considered a distribution medium that may serve as a tangible storage medium. Accordingly, the disclosure is considered to include any one or more of the following: a computer readable medium or distribution medium or other equivalent or subsequent medium having stored therein data or instructions. The computer-readable medium may be non-transitory and includes all tangible computer-readable media.

In alternative embodiments, dedicated hardware arrangements, such as application specific integrated circuits, programmable logic arrays and other hardware devices, can be constructed to implement one or more of the methods described herein. Applications that may include the apparatus and methods of various embodiments can broadly include a variety of electronic and computer systems. One or more embodiments described herein may implement functions using two or more specific interconnected hardware modules or devices and related control and data signals capable of communication between and through the modules, or as portions of an application-specific integrated circuit. Accordingly, the present system includes software, firmware, and hardware arrangements.

According to various embodiments of the present disclosure, the methods depicted herein may be implemented by software programs executed by a computer system. Additionally, in exemplary, non-limiting embodiments, the implementation can include distributed processing, component/object distributed processing, and parallel processing. Alternatively, virtual computer system processing may be constructed to implement one or more methods or functions as described herein.

Processors suitable for executing computer programs include by way of example: a general or special purpose microprocessor, and any one or more processors of any kind of digital computer. Generally, a processor can receive instructions or data from a read-only memory or a random access memory or both. The essential elements of a computer are a processor for executing instructions and one or more memory devices for storing instructions and data. In general, a computer may also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g.: magnetic, magneto-optical disks, or optical disks. Computer-readable media suitable for storing computer program instructions and data include all forms of non-volatile storage, media and memory devices, including by way of example: semiconductor memory devices such as EPROM, EEPROM, and flash memory devices; magnetic disks, such as internal hard disks or removable disks; magneto-optical disks; and CD ROM and DVD-ROM disks. The processor and the memory can be supplemented by, or incorporated in, special purpose logic circuitry

The illustrations of the embodiments described herein are intended to provide a general understanding of the structure of the various embodiments. The illustrations are not intended to serve as a complete description of all of the elements and features of apparatus and systems that utilize the structures or methods described herein. Many other embodiments may be apparent to those of skill in the art upon reading this disclosure. Other embodiments may use or be derived from the disclosure, and therefore structural and logical substitutions and changes may be made without departing from the scope of the disclosure. Additionally, the illustration is merely schematic and not drawn to scale. Some proportions in this illustration may be exaggerated, while other proportions may be minimized. The present disclosure and the figures are accordingly to be regarded as illustrative rather than restrictive.

While this specification contains many specifics, these should not be construed as limitations on the scope of the invention or of what may be claimed, but rather as descriptions of features specific to particular embodiments of the invention. Some of the features described in this specification in the context of separate embodiments may also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination. In addition, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination, and the claimed combination may be directed to a subcombination or variation of a subcombination.

One or more embodiments of the present disclosure are referred to herein, individually or collectively, by the word "invention" merely for convenience and without intending to voluntarily limit the scope of this application to any particular invention or inventive concept. Additionally, although specific embodiments have been illustrated and described herein, it should be appreciated that any subsequent arrangement calculated to achieve the same or similar purpose may be substituted for the specific embodiments shown. This disclosure is intended to cover any and all subsequent adaptations or variations of various embodiments. Combinations of the above embodiments, and other embodiments not specifically described herein, will be apparent to those of skill in the art upon reviewing the description.

It is intended that the following detailed description be regarded as illustrative rather than limiting, and that it be understood that it is the following claims, including all equivalents, that are intended to define the scope of this invention. The claims should not be read as limited to the described order or elements unless stated to that effect. Therefore, all embodiments that come within the scope and spirit of the following claims and equivalents thereto are claimed as the invention.