WO2017134484A1

WO2017134484A1 - Method of estimating an operating characteristic of a power converter

Info

Publication number: WO2017134484A1
Application number: PCT/IB2016/050509
Authority: WO
Inventors: Magnus Karlsson; Oleg Volfson; Andrzej WOJTASIK
Original assignee: Telefonaktiebolaget Lm Ericsson (Publ)
Priority date: 2016-02-01
Filing date: 2016-02-01
Publication date: 2017-08-10

Abstract

A system and method of estimating an operating characteristic of a power converter including a power switch. In an embodiment, the method includes generating a duty cycle to control the power switch to control an output characteristic of the power converter. The method also includes producing an estimate of an output current of the power converter employing the duty cycle and an input voltage of the power converter.

Description

METHOD OF ESTIMATING AN OPERATING CHARACTERISTIC

OF A POWER CONVERTER

TECHNICAL FIELD

The present invention is directed, in general, to power electronics and, in particular, to a method of estimating an operating characteristic of a power converter.

BACKGROUND

As electronic systems consume higher power, new challenges are being encountered for acquiring an accurate measurement of an operating characteristic (e.g. , an output current) of a power converter that supplies power to the electronic systems. For instance, a measurement of an output power level of a power converter is often employed to facilitate current sharing among a plurality of power converters and to select an operating mode for a power converter such as a sleep mode of operation. Existing measurement methods, which now often employ digital elements, use an analog-to-digital converter ("ADC") with fixed quantization steps to acquire a measurement value. The quantization steps are generally a constant level over the full scale of measurement values and inherently yield a level-independent measurement inaccuracy. This yields an increasing relative error when measuring small incremental levels with a fixed quantization step size. When measuring the output current, the small incremental current levels are important values to more accurately control the power converter including light- and sleep-modes of operation. Today's solutions employing analog-to-digital converters and other digital techniques lead to poor measurement certainty at low measurement values.

Despite continued efforts to improve relative measurement accuracy employing a digital component such as an analog-to-digital converter with its inherent measurement quantization, a system and method is needed to overcome the resulting hindrances for managing system energy consumption, particularly at the less intense levels of operation such as a sleep mode of operation. What is needed in the art, therefore, is a system and method that can estimate an operating characteristic of a power converter to more efficiently electronic systems and the like. SUMMARY

These and other problems are generally solved or circumvented, and technical advantages are generally achieved, by advantageous embodiments of the present invention for a system and method of estimating an operating characteristic of a power converter including a power switch. In an embodiment, the method includes generating a duty cycle to control the power switch to control an output characteristic of the power converter. The method also includes producing an estimate of the output current of the power converter employing the duty cycle and an input voltage of the power converter.

In another embodiment, a power converter includes a power switch and a controller. The controller is configured to generate a duty cycle to control the power switch to control an output characteristic of the power converter, and produce an estimate of an output current of the power converter employing the duty cycle and an input voltage of the power converter.

In another embodiment, a controller for use with a power converter having a power switch includes a processor; and memory including computer program code. The memory and the computer program code is configured to, with the processor, cause the controller to generate a duty cycle (via, e.g. , a pulse-width modulator) to control the power switch to control an output characteristic of the power converter. The memory and the computer program code is also configured to, with the processor, cause the controller to produce an estimate of an output current (via, e.g. , a power management subsystem) of the power converter employing the duty cycle and an input voltage of the power converter.

The foregoing has outlined rather broadly the features and technical advantages of the present invention in order that the detailed description of the invention that follows may be better understood. Additional features and advantages of the invention will be described hereinafter, which form the subject of the claims of the invention. It should be appreciated by those skilled in the art that the conception and specific embodiment disclosed may be readily utilized as a basis for modifying or designing other structures or processes for carrying out the same purposes of the present invention. It should also be realized by those skilled in the art that such equivalent constructions do not depart from the spirit and scope of the invention as set forth in the appended claims. BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the present invention, reference is now made to the following descriptions taken in conjunction with the accompanying drawings, in which:

FIGURE 1 illustrates a schematic diagram of an embodiment of a power converter;

FIGURE 2 illustrates a block drawing of an embodiment of a power converter;

FIGUREs 3 and 4 illustrate graphical representations of embodiments of operational characteristics of a power converter;

FIGURE 5 illustrates a simplified circuit diagram of an embodiment of a power converter coupled to a load through external resistances;

FIGUREs 6 and 7 illustrate graphical representations of embodiments of operational characteristics of a power converter; and

FIGURE 8 illustrates a flow diagram of an embodiment of a method of operating a power converter.

Corresponding numerals and symbols in the different figures generally refer to corresponding parts unless otherwise indicated, and may not be redescribed in the interest of brevity after the first instance. The FIGUREs are drawn to illustrate the relevant aspects of exemplary embodiments.

DETAILED DESCRIPTION

The making and using of the present exemplary embodiments are discussed in detail below. It should be appreciated, however, that the embodiments provide many applicable inventive concepts that can be embodied in a wide variety of specific contexts. The specific embodiments discussed are merely illustrative of specific ways to make and use the systems, subsystems, and modules associated with estimating an operating characteristic (e.g. , an output current) of a power converter.

A process will be described herein with respect to exemplary embodiments in a specific context, namely, a system and method of estimating an operating characteristic of a power converter. While the principles will be described in the environment of a power converter, any environment such as a motor controller that may benefit from such a system and method that enables these functionalities is well within the broad scope of the present disclosure.

Referring initially to FIGURE 1, illustrated is a schematic diagram of an embodiment of a power converter. The power converter includes a power train 110, a controller 120 and a driver 130 including control circuit elements, and provides power to electronic systems. While in the illustrated embodiment, the power train 1 10 employs a buck converter topology, those skilled in the art should understand that other converter topologies such as a forward converter topology are well within the broad scope of the present invention. The power converter produces an output current I_out and an output voltage Vout for a load coupled to output terminals of the power converter.

The power train 1 10 receives an input voltage Vi_n from a source of electrical power (represented by a battery) at an input thereof and provides the regulated output voltage Vout to power, for instance, an electronic system at an output thereof. In keeping with the principles of a buck converter topology, the output voltage V_out is generally less than the input voltage Vi_n such that a switching operation of the power converter can regulate the output voltage V_out- An active element such as a switch (e.g., a main switch Qmn) is enabled to conduct for a primary interval (generally co-existent with a primary duty cycle "D" of the main switch Qmn) and couples the input voltage V_m to an output filter inductor L_out. During the primary interval, an inductor current I_Lout flowing through the output filter inductor L_out increases as a current flows from the input to the output of the power train 1 10. A portion of the inductor current ILout is filtered by the output filter capacitor C_out-

During a complementary interval (generally co-existent with a complementary duty cycle "1-D" of the main switch Q_mn), the main switch Q_mn is transitioned to a nonconducting state and another active element such as another switch (e.g. , an auxiliary switch Qaux) is enabled to conduct. The auxiliary switch Q_aux provides a path to maintain a continuity of the inductor current I_Lout flowing through the output filter inductor L_out. During the complementary interval, the inductor current I_Lout through the output filter inductor L_out decreases. In general, the duty cycle of the main and auxiliary switches Qmn Qaux may be adjusted to maintain a regulation of the output voltage V_out of the power converter. Those skilled in the art should understand, however, that the conduction periods for the main and auxiliary switches Q_mn, Q_aux may be separated by a small time interval to avoid cross conduction therebetween and beneficially to reduce the switching losses associated with the power converter.

The controller 120 including a processor 123 and memory 126 receives a desired output characteristic such as a desired system voltage V_system from an internal or external source associated with the electronic system, and the output voltage V_out of the power converter. Accordingly, the controller 120 senses the output voltage V_out with an output voltage sensor 140. The controller 120 is also coupled to the input voltage Vi_n of the power converter and a return lead of the source of electrical power (again, represented by a battery) to provide a ground connection therefor. Accordingly, the controller 120 senses the input voltage Vi_n with an input voltage sensor 150. A decoupling capacitor C_dec is coupled to the path from the input voltage Vi_n to the controller 120. The decoupling capacitor C_dec is configured to absorb high frequency noise signals associated with the source of electrical power to protect the controller 120.

In accordance with the aforementioned characteristics, the controller 120 provides a signal (e.g. , a pulse width modulated signal SPWM) to control a duty cycle and a frequency of the main and auxiliary switches Q_mn, Q_aux of the power train 110 to regulate an output characteristic thereof. The controller 120 may also provide a complement of the signal (e.g., a complementary pulse width modulated signal S I-PWM) in accordance with the aforementioned characteristics. Any controller adapted to control at least one switch of the power converter is well within the broad scope of the present invention. Accordingly, the controller 120 generates a duty cycle to control the main and auxiliary switches Q_mn, Q_aux to control an output characteristic of the power converter such as the output voltage V_out- In addition, the controller 120 obtains the input voltage Vi_n of the power converter and produces an estimate of the output current I_out of the power converter employing the duty cycle D and the input voltage Vi_n as described herein.

The processor 123 may be embodied as any type of processor and associated circuitry configured to perform one or more of the functions described herein. For example, the processor 123 may be embodied as or otherwise include a single or multi- core processor, an application specific integrated circuit, a collection of logic devices, or other circuits. The memory 126 may be embodied as read-only memory devices and/or random access memory devices. For example, the memory 126 may be embodied as or otherwise include dynamic random access memory devices ("DRAM"), synchronous dynamic random access memory devices ("SDRAM"), double-data rate dynamic random access memory devices ("DDR SDRAM"), and/or other volatile or non-volatile memory devices. The memory 126 may have stored therein programs including a plurality of instructions or computer program code for execution by the processor 123 to control particular functions of the power converter as discussed in more detail below.

The power converter also includes the driver 130 configured to provide drive signals SDRVI, SDRV₂ to the main and auxiliary switches Q_mn, Q_aux, respectively, based on the signals SPWM, SI_PWM provided by the controller 120. There are a number of viable alternatives to implement a driver 130 that include techniques to provide sufficient signal delays to prevent crosscurrents when controlling multiple switches in the power converter. The driver 130 typically includes active elements such as switching circuitry incorporating a plurality of driver switches that cooperate to provide the drive signals SDRVI, SDRV2 to the main and auxiliary switches Qmn, Qaux- Of course, any driver 130 capable of providing the drive signals SDRVI, SDRV₂ to control a switch is well within the broad scope of the present invention.

Turning now to FIGURE 2, illustrated is a block diagram of an embodiment of a power converter. A power train includes main and auxiliary switches Qmn, Q_aux coupled to an output filter inductor Lout and output filter capacitor Cout configured to regulate an output voltage V_out of the power converter A controller 210 produces a pulse width modulated signal SPWM for a driver 270 coupled to control terminals of the main and auxiliary switches Qmn, Qaux- The output voltage V_out produced by the power train is sensed by a multiplexer

260, an output of which is converted to a digital signal by an analog-to-digital converter ADC, which in turn is coupled to a power management subsystem 220. The power management subsystem 220 is employed to produce an estimate of an operating characteristic such as an output current lout (also referred to herein as a load current) of the power converter employing a duty cycle D associated with the main and auxiliary switches Q_m¾ Qaux and an input voltage Vi_n supplied on input voltage bus and measured by an input voltage sensor 215. Alternatively, the input voltage Vi_nmay be obtained by the power management subsystem 220 as a pre-set (or pre-measured, pre-determined, etc.) value from, for instance, a regulated voltage bus to estimate the output current lout.

The output of analog-to-digital converter ADC is also coupled to communication subsystem 240 that is configured to produce a communication signal COMM that may be communicated to external subsystems such as a remote control and monitoring subsystem. The output voltage V_out of the power converter is also coupled to a digital compensator 230 and to a digital pulse-width modulator D-PWM in the controller 210. The digital pulse-width modulator D-PWM produces the pulse width modulated signal SPWM- The digital compensator 230 can be employed to stabilize the control process employed by the controller 210 to regulate the output voltage V_out- The multiplexer 260 is also coupled to a local temperature sensor 250 such as a thermistor and to an external temperature sensor XTEMP, which may be used to estimate the power converter output current I_out. Analogous to the controller 120 of FIGURE 1, the subsystems, or portions thereof, of the controller 210 may be embodied in a processor and memory to perform the respective functions thereof.

As introduced herein, a controller for a power converter employs a duty cycle of a control loop of the power converter and an input voltage thereto to estimate an operating characteristic such as an output current therefrom. In an embodiment, the controller may also employ an output voltage or other characteristic of the power converter to estimate the output current. In an embodiment, the control loop can be a digital control loop. The process can be used as a complement to a normal measurement of an operating characteristic of the power converter to provide a high level of accuracy of the corresponding measurement. Thus, a process is employed for acquiring a digital value of the operating characteristic that maintains accuracy at low measurement values.

A number of measurements acquired during different power converter operating conditions including an input voltage Vin, an output voltage V_out and an output current I_out are used to produce observations for a regression fit, such as a least-squares regression fit, to calculate coefficients in a nonlinear model that represents the duty cycle D and/or the output current I_out of the power converter. Different models can be used with varying complexity and the number of measurements is adjusted according to an operational region and measurement certainty desired. In order to compensate for an external resistance between an output of the power converter and a load coupled thereto, a method is introduced that employs an interpolation of the duty cycle data for multiple (e.g. , two) constant output voltages V_out- During ideal conditions, the output voltage V_out of a power converter such as a buck power converter is dependent on a duty cycle D of the power converter, and the input voltage Vm. A first-order relationship between the output voltage V_out and the input voltage Vin of the buck power converter is dependent on a duty cycle D as set forth by Equation 1 below:

An improved first-order model is produced by adding a current-dependent voltage loss Rioss that represents an equivalent total loss resistance of the power converter on the power converter side of a remote voltage sense point as illustrated below by Equation 2 below:

Vout ⁼ D Vin - Rloss lout-

Equation 2 can be inverted so that the output current I_out can be expressed in terms of the duty cycle D, the input voltage Vi_n and the output voltage V_out as indicated by Equation 3 below:

lout ⁼ (D Vin - Vout) Rloss ·

The model represented by Equation 3 remains linear with respect to the duty cycle D.

Turning now to FIGURE 3, illustrated is a graphical representation of an embodiment of operational characteristics of a power converter. In particular, FIGURE 3 illustrates a duty cycle D versus output current I_out (designated load current in amperes ("A")) for the power converter. The graphical representation of the operational characteristics of the power converter assumes a maximum output current of 40 amperes and constant input and output voltages Vin, V_out- It can be observed from the graphical representation illustrated in FIGURE 3 that a linear model is not sufficient to estimate duty cycle D from the output current I_out with high accuracy. Since it is desirable to increase the level of accuracy of a current measurement, more measurements with different current levels may also be included. Turning now to FIGURE 4, illustrated is a graphical representation of an embodiment of operational characteristics of a power converter. In particular, FIGURE 4 illustrates a change in duty cycle D versus output current I_out (designated load current in amperes ("A")) for the power converter. The change in duty cycle D represents a gradient (i.e., the first derivative) of the duty cycle D and the power converter is assumed to be operating at constant input and output voltages Vm, V_out- It can be observed from FIGURE 4 that measurements should be taken more closely at current levels below 10 amperes. At current levels above 10 amperes where the gradient is more constant, fewer measurement points are needed. In theory, the graphical representation illustrated in FIGURE 4 would be substantially monotonic with changes in load current. Since the duty cycle supporting this graphical representation was measured with a limited resolution, a discontinuous appearance is produced. With finer duty cycle quantization, the graphical representation would be a smoother, continuous curve.

For example, a good set of current levels for determining an output current I_out is:

[0, 0.5, 1, 2, 4, 6, 8, 10, 10, 15, 20, 30, 40].

In the case of a very tightly regulated input voltage Vi_n of the power converter, the parameter does not necessarily need to be included in the model, but treated only as a constant input voltage V;_n. Looking again at the duty cycle plot illustrated in FIGURE 3, the linear model represented by Equation 3 does not work accurately for small currents.

If the order of the model is increased up to a value "n," a model/power series representation of the output current I_out of order "n" with coefficients bo, ... b_n at constant input and output voltages Vin, V_out is set forth below in Equation 4:

I₀ut = bo + b₁ D + b₂ D² +... b_n Dⁿ,

which assumes that the input voltage Vi_n and output voltage V_out are constants.

A model of the nonlinear graphical representation shown in FIGURE 4 can be constructed using a regression process such as a least-squares regression process. In a practical case, a model order up to three will often work with sufficient accuracy. Model orders above three can produce ill-conditioned least-square estimates. Such models can be unnecessarily complex. Although a power-series representation is provided hereinabove in Equation 4 and in other instances described hereinbelow, it is anticipated that other analytic and piecewise approximations such as, without limitation, ratios of analytic functions and partial-fraction expansions can be employed for Equation 4 and in the other instances described below. An example of a third-order model illustrating estimated coefficients bo, ... , b3 is provided in the TABLE I below,

TABLE I

wherein the terms:

Estimate = estimated coefficients bo, ... b_n;

SE = standard deviation for the estimated coefficients;

tStat = t-test value, which can be used to determine if two sets of data are significantly different from each other and the amplitude shows how much that parameter effects the final result; and

pValue = the probability that the constant is equal to zero.

In the example above, the number of observations is 12, and the error degrees of freedom is 8. The resulting root mean square ("RMS") error is 0.465, R-squared value is 0.999, adjusted R-squared value is 0.999, the F-statistic versus constant model is 2.75e+03, and the statistical p-value = 2.17e-12.

This particular model yields a RMS error of 0.465 A, yielding a +/-3 sigma error of +/-1.5 A. In many cases, this does not provide a sufficiently accurate estimate.

Accordingly, more measurements may be employed in the model. Using measurements at currents of 0, 1, 2, 3, 4 45 A (46 measurements) reduces the RMS error to 0.175 A, which is an improvement over the previous RMS error of 0.465 A. Models of the output current I_out can be produced for the power converter using internal sensing of the output voltage V_out- A problem occurs in applications where the model should be compensated for the external resistance Rext- (also referred to as "series-load resistances") that is coupled between the power converter and output voltage sense points, which are usually placed near the load.

Turning now to FIGURE 5, illustrated is a simplified circuit diagram of an embodiment of a power converter 510 coupled to a load through external resistances Rext+, Rext- The external lines including the external resistances Rext+, Rext- represent external droop resistances between the power converter 510 and a load 520 and, again, are also referred to as "series-load resistances." The power converter 510 is coupled to an input voltage Vi_n and provides an output voltage V_out to power the load 520 at a load voltage Vioad- The power converter 510 also includes sense points sense+, sense- for sensing the load voltage Vi_oad-

A process to estimate the output current I_out employs duty cycle data from multiple (e.g. , two) data sets with different, fixed output voltages V_out, for example and without limitation, a nominal output voltageV_outn that corresponds to zero load and/or zero external resistance, and an incremented output voltage V_outH = V_out+M percent (i. e., an increment of M percent over the nominal output voltageV_outn) that corresponds to a maximum load current with non-zero external resistance. The duty cycle data are interpolated between their respective results using the estimated/measured external droop resistances to obtain a model that compensates for the duty cycle change due to external resistances Rext+, Rext- The parameter M can be, for example, 10 percent, at a nominal output voltage V_outn = 1 volt ("V") which yields an incremented output voltage V_outH = 1.1 V. For a maximum output current Imax = 40 A, this corresponds to an external droop resistance represented by a maximum droop resistance Rexmax = (0.1 V)/(40 A) = 2.5 milliohms ("mH"). That is, the external resistances R^†, Rext- represented by the maximum droop resistance Rexmax can be constrained to be less than 2.5 πιΩ together.

To implement and test the model, the maximum droop resistance Rexmax corresponding to the incremented output voltage V_outH is calculated as set forth below in Equation 5 :

Re xmax^— (VoutH " V₀utn)/ Imax- Next, a droop scaling factor represented by the parameter Droopscale is calculated using the estimated/measured external resistances Rext- as set forth below in Equation 6:

Droopscale = (Rext+ + Rext-V ¾ xmax-

Then, an interpolated duty cycle D_mt for different output voltages V_out is obtained by interpolation using Equation 7 below with the two duty cycles D_L (corresponding to the nominal output voltage V_outn) and DH (corresponding to the incremented output voltage VoutH) and a current I of current values:

Dim = D_L + Droopscale (D_H -D_L) I/I_max.

Turning now to FIGURE 6, illustrated is a graphical representation of an embodiment of operational characteristics of a power converter. In particular, FIGURE 6 illustrates duty cycle shape difference measurements versus output current I_out (designated load current in amperes ("A")) for the power converter. The duty cycle shape difference measurements include interpolated duty cycle data D_mt for droop compensation, wherein two external resistances R^, Rext- are each half of the maximum droop resistance Droopmax. The interpolated duty cycle data D_mt for different output voltages V_out are used in least-squares modeling with Equation 4 and with interpolation using Equation 7 to obtain the following estimated model coefficients bo, ... , b₃ for a power-series expansion as set forth in TABLE II below.

TABLE II

The coefficients bo, ... , b₃ obtained in the model illustrated in TABLE II use an observation current vector:

[0, 1, 2, 3, 4,... , 45] A. The number of observations is 46, the error degrees of freedom is 42, the RMS error is 0.176, the R-squared is 1, the adjusted R-squared is 1, the F-statistic versus constant model is 8.67e+04, and the p-value is 1.23e-79. Hence, this model describes the interpolated data very well with a RMS error of only 0.176 A.

The model can be further expanded to include data representing variable input voltages Vi_n. In the expanded model of using variable input voltages Vi_n and duty cycle D, the terms up to the quadratic are usable in a practical application. Nonetheless, mixed variable terms can be included in the model. Using higher order, cubic terms in a single variable can make the analysis ill-conditioned. The following complex model including terms in (interpolated) duty cycle D;_nt, input voltage Vin, and mixed-variable terms results in Equation 8 as set forth below:

lout = bo ₊biD + b₂D² + b₃V_in + b₄V_in ² + b₅V_inD + b₆V_inD² + b₇V_in ²D.

For this expanded model, the following estimated coefficients bo,... , be and statistical results were obtained for a power converter as set forth in TABLE III below.

TABLE III

The model used for the TABLE III employs 46 output current levels I_out, three input voltages Vi_n (nominal +/-10 percent for each output voltage V_out), and yields 138 measurements at each output voltage V_out- The number of observations is 138, the error degrees of freedom are 130, the RMS error is 0.64, the R-squared is 0.998, the adjusted R-squared is 0.998, the F-statistic versus constant model is 8.44e+03, and the p-value is 1.68e-169.

To reduce model complexity, the constant bo and the b3^«Vi_n terms are removed since they have the highest p-value (i.e., the probability that the respective value equals zero) yielding Equation 9 as set forth below:

lout = biD + bjD² + b₂Vin² + b₃V_inD + b₄V_inD² + b₅V_in ²D.

The data illustrated in TABLE IV below shows the resulting estimated coefficients bo, ...

TABLE IV

The number of observations is 138, the error degrees of freedom are 132, the RMS error is 0.673, the R-squared is 0.998, the adjusted R-squared is 0.997, the F-statistic versus constant model is 3.46e+04, and the p-value is 2.35e-208. This model still using 138 measurements for each output voltage V_out is simpler with maintained R-squared value, and the RMS error is not increased much compared with the former model's error.

If the number of observations is reduced down to 46 for each output voltage V_out, the resulting estimated coefficients bo, ... , bs are set forth in TABLE V. Coefficients Estimate SE tStat pValue bo 56.868 8.5638 6.6405 5.9572e-08 bi -5.2246 0.63139 -8.2748 3.3661e-10 b₂ 0.57427 0.10219 5.6198 1.6169e-06 b₃ -9.3141 1.1205 -8.3126 2.9945e-10 b₄ 0.69731 0.068858 10.127 1.3415e-12 b₅ 0.13979 0.022088 6.3287 1.6309e-07

TABLE V

The number of observations is now 46, the error degrees of freedom are 40, the RMS error is 0.678, the R-squared is 0.998, the adjusted R-squared is 0.997, the F-statistic versus constant model is 1.13e+04, and the p-value is 5.63e-63. Hence, the number of measurements can be reduced without increasing the model uncertainty.

In an embodiment, a representation of power converter output current I_out as a function of duty cycle D and power converter input voltage V;_n such as, without limitation, by Equation 8 or by Equation 9, can include an adjustment for a local temperature that may be internal or external to the power converter. The adjustment for temperature can be a linear or higher order temperature adjustment. Instead of storing a full table of measurements for multiple output voltages V_out, models can be stored describing the duty cycle D versus output current I_out for given input and output voltages

Using a model of the order of four is enough in a practical application, as illustrated by Equation 10 below for duty cycle D_L for a nominal output voltage V_outn:

D_L = bo + bil + b₂I² + b₃I³ + b₄I⁴.

Using the data above, the model for the nominal output voltage V_outn is set forth in TABLE VI. Coefficients Estimate SE tStat pValue bo 7.3927 0.0095857 771.22 6.0274e-87 bi 0.10714 0.0030252 35.415 2.2838e-32 b₂ -0.0050043 0.00027819 -17.989 4.5928e-21 b₃ 0.00012973 9.3504e-06 13.874 4.417e-17 b₄ -1.1853e-06 1.0319e-07 -11.487 2.1537e-14

TABLE VI

The number of observations is 46, the error degrees of freedom are 41, the RMS error is 0.0147, the R-squared is 0.999, the adjusted R-squared is 0.999, the F-statistic versus constant model is le+04, and the p-value is 1.05e-60. The models can thus be used to generate duty cycle data.

Using an equation corresponding to Equation 10, the model for an incremented output voltage V_outH is set forth in TABLE VII.

TABLE VII

The number of observations is 46, the error degrees of freedom are 41, the RMS error is 0.0138, the R-squared is 0.999, the adjusted R-squared is 0.999, the F-statistic versus constant model is 1.16e+04, and the p-value is 5.43e-62. The nominal and high voltage model parameters are compared in the TABLE VIII below. The parameters 1-4 have overlapping ranges, since the curve forms are very similar. Coefficient Nominal High voltage a Average

Number voltage b

with standard

dev.

0 7.3927 8.2354

0.0095857 0.0089973

1 0.10714 0.10428 0.10571

0.0030252 0.0028396

2 -5.0043e-3 -4.6363e-3 -4.8203e-3

0.027819e-3 0.026112e-3

3 1.2973e-4 1.1729e-4 1.235 le-4

0.093504e-04 0.087767e-04

4 -1.1853e-06 -1.0585e-06 -1.1219e-6

0.10319e-06 0.096858e-06

TABLE VIII

Turning now to FIGURE 7, illustrated is a graphical representation of an embodiment of operational characteristics of a power converter. In particular, FIGURE 7 illustrates differences in duty cycle D when coefficients ao and bo are set to zero versus current (designated current in amperes ("A")) for the power converter. The curves corresponding to the nominal output voltage V_outn and the incremented output voltage outH (i.e., an increment of M percent ( 10 %) over the nominal output voltage V_outn) are very similar in shape, and are just shifted by the constants ao and bo. Also, the curves for duty cycle D scaled with a maximum droop resistance Droopmax and half the maximum droop resistance Droopmax are also illustrated in FIGURE 7. The curve scaled with the maximum droop resistance Droopmax intersects the curves corresponding to the nominal output voltage V_outn and the incremented output voltage V_outH at zero and 45 amperes, respectively.

Since the duty cycle data is interpolated between the duty cycles D_L

(corresponding to the nominal output voltage V_outn) and D_H (corresponding to the incremented output voltage ν_ου«), the parameters 1-4 can be averaged (which corresponds to a resistance of half the value of the maximum droop resistance Rexmax according to Equation 7, which will not appreciably increase the error in the estimates).

Using averaged coefficients, the estimated model for power converter output current I_out versus duty cycle D is set forth below in TABLE IX.

TABLE IX

These results can be compared with the model obtained by using the raw data for the maximum droop resistance Droopmax illustrated previously hereinabove with respect to TABLE II.

As illustrated by the data in TABLE X below, the models are very similar.

TABLE X

The models that have been described, without limitation, assume that the output voltage Vout is fixed and known, and the test vector for the output current I_out is fixed and known. Turning now to FIGURE 8, illustrated is a flow diagram of an embodiment of a method of operating a power converter including a power switch. The method begins at a start step or module 800. At a step or module 810, the method generates a duty cycle to control the power switch to control an output characteristic (e.g. , an output voltage) of the power converter. The method continues by sensing an input voltage of the power converter at a step or module 820. Alternatively, the input voltage Vi_nmay be obtained as a pre-set (or pre-measured, pre-determined, etc. ) value from, for instance, a regulated voltage bus. At a step or module 830, the method produces an estimate of the output current of the power converter employing the duty cycle and the input voltage.

The estimate of the output current may be produced employing different and/or complementary processes. For instance, producing the estimate of the output current may include employing an analytic function dependent on the duty cycle and the input voltage. In accordance therewith, the estimate of the output current may include employing a sum of terms dependent on a constant, powers of the duty cycle, powers of the input voltage, and mixed-variable products of powers of the duty cycle and the input voltage. The estimate of the output current may include employing a series load resistance of the power converter before a remote sense point. The estimate of the output current can also be produced employing a spline linear or higher order approximation. The estimate of the output current may also include providing an adjustment for a temperature in an environment associated with the power converter.

In an embodiment, producing the estimate of the output current may include employing the duty cycle, the input voltage, and an output voltage of the power converter. In accordance therewith, producing the estimate of the output current may include measuring the output current produced over a range of duty cycles for at least two fixed values of the output voltage of the power converter, and employing a regression fit to form the estimate. The at least two fixed values of the output voltage may include a nominal output voltage and an incremented output voltage (e.g. , increased ten percent above the nominal output voltage). The regression fit can be performed by measuring the series load resistance of the power converter before the remote sense point, computing a parameter dependent on the series load resistance and a ratio of a difference between the at least two fixed values of the output voltage to a maximum current of the power converter, and interpolating a value of the duty cycle employing the parameter and the output current of the power converter. The method concludes at an end step or module 840. The method as described herein may be performed by a controller including a processor and memory, and modules and subsystems (e.g., a pulse-width modulator and power management system) as described above with respect to FIGUREs 1 and 2.

Thus, in an embodiment of a power converter, measurements of duty cycle versus output or load current are performed and stored for a nominal output voltage and an incremented output voltage. On site, for an application, the external resistance is measured. The duty cycle data are interpolated between nominal output voltage and incremented output voltage using the measured external resistance and the raw data from production. A least-squares regression model of load current versus duty cycle is constructed for the nominal output voltage and the incremented output voltage. The model with interpolation for output voltage is used to estimate load current. In an embodiment, model coefficients are stored instead of raw data.

During production of a power converter in an embodiment, data for duty cycle versus load current for nominal and incremented output voltage is measured and stored. A least-squares regression model for the duty cycle versus load current is constructed for the nominal output voltage and the incremented output voltage for given input voltages. On site, for an application, the external resistance is measured. Interpolated duty cycle data are generated using the measured external resistance and duty cycle models for the different input voltages. A least square regression model of load current versus duty cycle is built from the interpolated duty cycle data. The model with interpolation for output voltage is used to estimate load current.

As described above, the exemplary embodiment provides both a method and corresponding apparatus consisting of various modules providing functionality for performing the steps of the method. The modules may be implemented as hardware (embodied in one or more chips including an integrated circuit such as an application specific integrated circuit), or may be implemented as software or firmware for execution by a processor. In particular, in the case of firmware or software, the exemplary embodiment can be provided as a computer program product including a computer readable storage medium embodying computer program code (i. e., software or firmware) thereon for execution by the computer processor. The computer readable storage medium may be non-transitory (e.g., magnetic disks; optical disks; read only memory; flash memory devices; phase-change memory) or transitory (e.g., electrical, optical, acoustical or other forms of propagated signals-such as carrier waves, infrared signals, digital signals, etc.). The coupling of a processor and other components is typically through one or more busses or bridges (also termed bus controllers). The storage device and signals carrying digital traffic respectively represent one or more non-transitory or transitory computer readable storage medium. Thus, the storage device of a given electronic device typically stores code and/or data for execution on the set of one or more processors of that electronic device such as a controller.

Although the embodiments and its advantages have been described in detail, it should be understood that various changes, substitutions, and alterations can be made herein without departing from the spirit and scope thereof as defined by the appended claims. For example, many of the features and functions discussed above can be implemented in software, hardware, or firmware, or a combination thereof. Also, many of the features, functions, and steps of operating the same may be reordered, omitted, added, etc. , and still fall within the broad scope of the various embodiments.

Moreover, the scope of the various embodiments is not intended to be limited to the particular embodiments of the process, machine, manufacture, composition of matter, means, methods and steps described in the specification. As one of ordinary skill in the art will readily appreciate from the disclosure, processes, machines, manufacture, compositions of matter, means, methods, or steps, presently existing or later to be developed, that perform substantially the same function or achieve substantially the same result as the corresponding embodiments described herein may be utilized as well.

Accordingly, the appended claims are intended to include within their scope such processes, machines, manufacture, compositions of matter, means, methods, or steps.

Claims

CLAIMS:

1. A method operable with a power converter including a power switch (Qmn), comprising:

generating (810) a duty cycle (D) to control said power switch (Q_mn) to control an output characteristic of said power converter; and

producing (830) an estimate of an output current (I_out) of said power converter employing said duty cycle (D) and an input voltage (Vi_n) of said power converter.

2. The method as recited in Claim 1 further comprising sensing (820) said input voltage (Vi_n) of said power converter.

3. The method as recited in Claim 1 wherein producing (830) said estimate of said output current (I_out) further comprises employing an analytic function dependent on said duty cycle (D) and said input voltage (V;_n).

4. The method as recited in Claim 1 wherein producing (830) said estimate of said output current (I_out) further comprises employing a sum of terms dependent on a constant, powers of said duty cycle (D), powers of said input voltage (Vi_n), and mixed- variable products of powers of said duty cycle (D) and said input voltage (V;_n).

5. The method as recited in Claim 1 wherein producing (830) said estimate of said output current (I_out) further comprises employing a series load resistance (Rext₊, Rext-) of said power converter before a remote sense point (sense+, sense-).

6. The method as recited in Claim 1 wherein producing (830) said estimate of said output current (I_out) further comprises providing an adjustment for a temperature (XTEMP) in an environment associated with said power converter.

7. The method as recited in Claim 1 wherein said output characteristic is an output voltage (V_out) of said power converter and producing (830) said estimate of said output current (I_out) further comprises employing said duty cycle (D), said input voltage (Vin), and said output voltage (V_out)-

8. The method as recited in Claim 1 wherein said output characteristic is an output voltage (V_out) of said power converter and producing (830) said estimate of said output current (I_out) further comprises measuring said output current (I_out) produced over a range of duty cycles (D) for at least two fixed values of said output voltage (V_out) of said power converter, and employing a regression fit to form said estimate.

9. The method as recited in Claim 8 wherein said at least two fixed values of said output voltage (V_out) comprise a nominal output voltage (V_outn) and an incremented output voltage (V_outh)-

10. The method as recited in Claim 8 wherein said regression fit is produced by:

measuring a series load resistance (¾_¾+, R_ext-) of said power converter before a remote sense point (sense+, sense-);

computing a parameter dependent on said series load resistance (R_ex_t+, R_ex_t-) and a ratio of a difference between said at least two fixed values of said output voltage (V_out) to a maximum current (I_max) of said power converter, and

interpolating a value of said duty cycle (D) employing said parameter and said output current (I_out) of said power converter.

11. A power converter, comprising:

a power switch (Qmn); and

a controller (120, 210) configured to generate a duty cycle (D) to control said power switch (Qmn) to control an output characteristic of said power converter, and produce an estimate of an output current (I_out) of said power converter employing said duty cycle (D) and an input voltage (Vi_n) of said power converter.

12. The power converter as recited in Claim 11 further comprising an input voltage sensor (150, 215) configured to sense said input voltage (V_m) of said power converter.

13. The power converter as recited in Claim 11 wherein said controller (120, 210) is configured to produce said estimate of said output current (I_out) employing an analytic function dependent on said duty cycle (D) and said input voltage (Vi_n).

14. The power converter as recited in Claim 11 wherein said controller (120,

210) is configured to produce said estimate of said output current (I_out) employing a sum of terms dependent on a constant, powers of said duty cycle (D), powers of said input voltage (Vi_n), and mixed-variable products of powers of said duty cycle (D) and said input voltage (V_in).

15. The power converter as recited in Claim 11 wherein said controller (120,

210) is configured to produce said estimate of said output current (I_out) employing a series load resistance (Rext+, Rext-) of said power converter before a remote sense point (sense+, sense-).

16. The power converter as recited in Claim 1 1 wherein said controller (120, 210) is configured to produce said estimate of said output current (I_out) employing an adjustment for a temperature (XTEMP) in an environment associated with said power converter.

17. The power converter as recited in Claim 1 1 wherein said output characteristic is an output voltage (V_out) of said power converter and said controller (120, 210) is configured to produce said estimate of said output current (I_out) employing said duty cycle (D), said input voltage (V;_n), and said output voltage (V_out).

18. The power converter as recited in Claim 1 1 wherein said output characteristic is an output voltage (V_out) of said power converter and said controller (120, 210) is configured to produce said estimate of said output current (I_out) by measuring said output current (I_out) produced over a range of duty cycles (D) for at least two fixed values of said output voltage (V_out) of said power converter, and employing a regression fit to form said estimate.

19. The power converter as recited in Claim 18 wherein said at least two fixed values of said output voltage (V_out) comprise a nominal output voltage (V_outn) and an incremented output voltage (V_outh)-

20. The power converter as recited in Claim 18 wherein said regression fit is configured to be produced by:

measuring a series load resistance (Rext+, ext-) of said power converter before a remote sense point (sense+, sense-);

computing a parameter dependent on said series load resistance (Rext+, Rext-) and a ratio of a difference between said at least two fixed values of said output voltage (V_out) to a maximum current (Imax) of said power converter, and

21. A controller (120, 210) for use with a power converter including a power switch (Qmn), comprising:

a processor ( 123); and memory (126) including computer program code, said memory (126) and said computer program code configured to, with said processor (123), cause said controller (120, 210) to perform at least the following:

generate a duty cycle (D) to control said power switch (Qmn) to control an output characteristic of said power converter; and

produce an estimate of an output current (I_out) of said power converter employing said duty cycle (D) and an input voltage (Vi_n) of said power converter.

22. The controller (120, 210) as recited in Claim 21 wherein said memory (126) and said computer program code are further configured to, with said processor (123), cause said controller (120, 210) to produce said estimate of said output current (lout) employing an analytic function dependent on said duty cycle (D) and said input voltage (V_in).

23. The controller (120, 210) as recited in Claim 21 wherein said memory (126) and said computer program code are further configured to, with said processor (123), cause said controller (120, 210) to produce said estimate of said output current (lout) employing a sum of terms dependent on a constant, powers of said duty cycle (D), powers of said input voltage (V;_n), and mixed-variable products of powers of said duty cycle (D) and said input voltage (V;_n).

24. The controller (120, 210) as recited in Claim 21 wherein said memory (126) and said computer program code are further configured to, with said processor

(123), cause said controller (120, 210) to produce said estimate of said output current (lout) employing a series load resistance

Rext-) of said power converter before a remote sense point (sense+, sense-).

25. The controller (120, 210) as recited in Claim 21 wherein said memory (126) and said computer program code are further configured to, with said processor

(123), cause said controller (120, 210) to produce said estimate of said output current (lout) employing an adjustment for a temperature (XTEMP) in an environment associated with said power converter.

26. The controller as recited in Claims 21to 25 wherein said output characteristic is an output voltage (V_out) of said power converter.

27. The controller (120, 210) as recited in Claim 26 wherein said memory (126) and said computer program code are further configured to, with said processor (123), cause said controller (120, 210) to produce said estimate of said output current (lout) employing said duty cycle (D), said input voltage (V;_n), and said output voltage

28. The controller (120, 210) as recited in Claim 26 wherein said memory (126) and said computer program code are further configured to, with said processor (123), cause said controller (120, 210) to produce said estimate of said output current (lout) by measuring said output current (I_out) produced over a range of duty cycles (D) for at least two fixed values of said output voltage (V_out) of said power converter, and employing a regression fit to form said estimate.

29. The controller (120, 210) as recited in Claim 28 wherein said at least two fixed values of said output voltage (V_out) comprise a nominal output voltage (V_outn) and an incremented output voltage (V_outh)-

30. The controller (120, 210) as recited in Claim 28 wherein said memory

(126) and said computer program code are further configured to, with said processor (123), cause said controller (120, 210) to produce said regression fit by:

measuring a series load resistance (¾_¾+, Rext-) of said power converter before a remote sense point (sense+, sense-);

computing a parameter dependent on said series load resistance (Rext+, Rext-) and a ratio of a difference between said at least two fixed values of said output voltage (V_out) to a maximum current (I_max) of said power converter, and

31. A controller (120, 210) for use with a power converter including a power switch (Qmn), comprising:

a pulse-width modulator (D-PWM) configured to generate a duty cycle (D) to control said power switch (Qmn) to control an output characteristic of said power converter; and

a power management subsystem (220) configured to produce an estimate of an output current (I_out) of said power converter employing said duty cycle (D) and an input voltage (Vi_n) of said power converter.

32. The controller (120, 210) as recited in Claim 31 wherein said power management subsystem (220) is configured to produce said estimate of said output current (I_out) employing an analytic function dependent on said duty cycle (D) and said input voltage (Vin).

33. The controller (120, 210) as recited in Claim 31 wherein said power management subsystem (220) is configured to produce said estimate of said output current (I_out) employing a sum of terms dependent on a constant, powers of said duty cycle (D), powers of said input voltage (Vi_n), and mixed-variable products of powers of said duty cycle (D) and said input voltage (Vi_n).

34. The controller (120, 210) as recited in Claim 31 wherein said power management subsystem (220) is configured to produce said estimate of said output current (I_out) employing a series load resistance (R_ex_t+, R_ex_t-) of said power converter before a remote sense point (sense+, sense-).

35. The controller (120, 210) as recited in Claim 31 wherein said power management subsystem (220) is configured to produce said estimate of said output current (I_out) employing an adjustment for a temperature (XTEMP) in an environment associated with said power converter.

36. The controller (120, 210) as recited in Claims 3 lto 35 wherein said output characteristic is an output voltage (V_out) of said power converter.

37. The controller (120, 210) as recited in Claim 36 wherein said power management subsystem (220) is configured to produce said estimate of said output current (I_out) employing said duty cycle (D), said input voltage (Vi_n), and said output voltage (V_out).

38. The controller (120, 210) as recited in Claim 36 wherein said power management subsystem (220) is configured to produce said estimate of said output current (I_out) by measuring said output current (I_out) produced over a range of duty cycles (D) for at least two fixed values of said output voltage (V_out) of said power converter, and employing a regression fit to form said estimate.

39. The controller as recited in Claim 38 wherein said at least two fixed values of said output voltage (V_out) comprise a nominal output voltage (V_outn) and an incremented output voltage (V_out_h)-

40. The controller (120, 210) as recited in Claim 38 wherein said power management subsystem (220) is configured to produce said regression fit by:

computing a parameter dependent on said series load resistance (Rext₊, R«xt-) and a ratio of a difference between said at least two fixed values of said output voltage (V_out) to a maximum current (I_max) of said power converter, and