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Obtaining the Current-Flux Relations of the Saturated PMSM by Signal Injection Pascal Combes * , Fran¸cois Malrait * , Philippe Martin and Pierre Rouchon * Schneider Toshiba Inverter Europe, 27120 Pacy-sur-Eure, France Email: {pascal.combes, francois.malrait}@schneider-electric.com Centre Automatique et Syst` emes, MINES ParisTech, PSL Research University, 75006 Paris, France Email: {philippe.martin, pierre.rouchon}@mines-paristech.fr Abstract —This paper proposes a method based on signal injection to obtain the saturated current-flux relations of a PMSM from locked-rotor experiments. With respect to the classical method based on time integration, it has the main advantage of being com- pletely independent of the stator resistance; moreover, it is less sensitive to voltage biases due to the power inverter, as the injected signal may be fairly large. I. Introduction Good models are usually paramount to design good control laws. This is the case for Permanent Magnet Syn- chronous Motors (PMSM), especially when “sensorless” control is considered. In this mode of operation, neither the rotor position nor its velocity is measured, and the control law must make do with only current measure- ments; a suitable model is therefore essential to relate the currents to the other variables. When operating above moderately low speed, i.e., above about 10% of the rated speed, models neglecting magnetic saturation are usually accurate enough for control purposes; but at low speed, magnetic (cross-)saturation must be taken into account, in particular when high-frequency signal injection is used, and the more so for motors with little geometric saliency, see e.g. [1]–[6]. However, motor manufacturers very seldom provide sat- uration data, which means the saturated current-flux rela- tions must be experimentally determined. The “classical” method to get these data is to integrate over time the time derivative of the flux as given by the stator model of the motor, see [7] for a detailed account. Unfortunately, this method is very sensitive to the value of the stator resistance R s , which may significantly vary during a long experiment; it also requires a good knowledge of the actu- ally impressed potentials (voltage sensors may be required because of the not very well-known voltage drops in the power stage), and of course of the resulting currents (which are in practice always measured). It is thus not easy to implement this method on a commercial variable speed drive for use in the field. The goal of this paper is to propose an alternative approach to obtain the saturated current-flux relations, which is completely independent on the knowledge of the stator resistance R s ; it is also less sensitive to the voltage drops of the power stage. It is based on high-frequency signal injection. It is based on signal injection, a technique that was originally introduced for sensorless control at low velocity [8], but that can also be used for identification [9]. The key idea, thanks to a suitable analysis of the effects of signal injection, is to recover the flux-current relations by integrating over paths in the plane of direct and quadrature currents; it generalizes a cruder procedure used in [10]. Notice that the required experimental data can be obtained with only experiments where the rotor is locked in a known position, which is reasonable for industrial use in the field (the classical method also works in similar conditions). The paper runs as follows: section II presents the struc- ture of the model, based on an energy approach; section III applies the classical method to a test PMSM; section IV details the proposed approach, and applies it to the same test PMSM. The following conventions are used: if x ij , ij being αβ or DQ, is the vector with coordinates x i and x j , we write indifferently x ij and (x i ,x j ) T ; if f is a function of several variables, k f denotes its partial derivative with respect to the k th variable, and 2 kl f = 2 lk f the second partial derivative with respect to the k th and l th variables. Lastly, the rotation matrix of angle α is denoted by R(α) := cos α - sin α sin α cos α ; of course, R(α)R T (α)= 1 0 0 1 , where R T (α) is the transpose of R(α). II. Energy-based model of the PMSM To write a model of the star-connected saturated si- nusoidal PMSM in the DQ frame, we follow the energy- based approach of [11], [12]. All the motor specific infor- mation is encoded in the scalar magnetic energy function H DQ m (φ DQ s ), where φ DQ s is the flux linkage vector. H DQ m is independent of the (electrical) rotor angle θ by the assumption of sinusoidal windings, and independent of the (electrical) rotor velocity ω as in any conventional elec- tromechanical device. The state equations of the PMSM then read DQ s dt = v DQ s - R s ı DQ s - ωJ φ DQ s (1) J l n dt = -DQ s T J ı DQ s - T l (2) arXiv:1705.04605v1 [cs.SY] 12 May 2017
Transcript
Page 1: Obtaining the Current-Flux Relations of the Saturated PMSM by … › pdf › 1705.04605.pdf · but matters for implementation on industrial drives, which are usually not equipped

Obtaining the Current-Flux Relations of theSaturated PMSM by Signal Injection

Pascal Combes∗, Francois Malrait∗, Philippe Martin† and Pierre Rouchon†∗Schneider Toshiba Inverter Europe, 27120 Pacy-sur-Eure, FranceEmail: pascal.combes, [email protected]

†Centre Automatique et Systemes, MINES ParisTech, PSL Research University, 75006 Paris, FranceEmail: philippe.martin, [email protected]

Abstract—This paper proposes a method based onsignal injection to obtain the saturated current-fluxrelations of a PMSM from locked-rotor experiments.With respect to the classical method based on timeintegration, it has the main advantage of being com-pletely independent of the stator resistance; moreover,it is less sensitive to voltage biases due to the powerinverter, as the injected signal may be fairly large.

I. Introduction

Good models are usually paramount to design goodcontrol laws. This is the case for Permanent Magnet Syn-chronous Motors (PMSM), especially when “sensorless”control is considered. In this mode of operation, neitherthe rotor position nor its velocity is measured, and thecontrol law must make do with only current measure-ments; a suitable model is therefore essential to relatethe currents to the other variables. When operating abovemoderately low speed, i.e., above about 10% of the ratedspeed, models neglecting magnetic saturation are usuallyaccurate enough for control purposes; but at low speed,magnetic (cross-)saturation must be taken into account,in particular when high-frequency signal injection is used,and the more so for motors with little geometric saliency,see e.g. [1]–[6].

However, motor manufacturers very seldom provide sat-uration data, which means the saturated current-flux rela-tions must be experimentally determined. The “classical”method to get these data is to integrate over time thetime derivative of the flux as given by the stator model ofthe motor, see [7] for a detailed account. Unfortunately,this method is very sensitive to the value of the statorresistance Rs, which may significantly vary during a longexperiment; it also requires a good knowledge of the actu-ally impressed potentials (voltage sensors may be requiredbecause of the not very well-known voltage drops in thepower stage), and of course of the resulting currents (whichare in practice always measured). It is thus not easy toimplement this method on a commercial variable speeddrive for use in the field.

The goal of this paper is to propose an alternativeapproach to obtain the saturated current-flux relations,which is completely independent on the knowledge of thestator resistance Rs; it is also less sensitive to the voltage

drops of the power stage. It is based on high-frequencysignal injection. It is based on signal injection, a techniquethat was originally introduced for sensorless control at lowvelocity [8], but that can also be used for identification [9].The key idea, thanks to a suitable analysis of the effectsof signal injection, is to recover the flux-current relationsby integrating over paths in the plane of direct andquadrature currents; it generalizes a cruder procedure usedin [10]. Notice that the required experimental data can beobtained with only experiments where the rotor is lockedin a known position, which is reasonable for industrial usein the field (the classical method also works in similarconditions).

The paper runs as follows: section II presents the struc-ture of the model, based on an energy approach; section IIIapplies the classical method to a test PMSM; section IVdetails the proposed approach, and applies it to the sametest PMSM.

The following conventions are used: if xij , ij being αβor DQ, is the vector with coordinates xi and xj , wewrite indifferently xij and (xi, xj)T ; if f is a functionof several variables, ∂kf denotes its partial derivativewith respect to the kth variable, and ∂2

klf = ∂2lkf the

second partial derivative with respect to the kth and lth

variables. Lastly, the rotation matrix of angle α is denoted

by R(α) :=

(cosα − sinαsinα cosα

); of course, R(α)RT (α) =

(1 00 1

),

where RT (α) is the transpose of R(α).

II. Energy-based model of the PMSM

To write a model of the star-connected saturated si-nusoidal PMSM in the DQ frame, we follow the energy-based approach of [11], [12]. All the motor specific infor-mation is encoded in the scalar magnetic energy functionHDQm (φDQs ), where φDQs is the flux linkage vector. HDQmis independent of the (electrical) rotor angle θ by theassumption of sinusoidal windings, and independent of the(electrical) rotor velocity ω as in any conventional elec-tromechanical device. The state equations of the PMSMthen read

dφDQsdt

= vDQs −RsıDQs − ωJ φDQs (1)

Jln

dt= −nφDQs

TJ ıDQs − Tl (2)

arX

iv:1

705.

0460

5v1

[cs

.SY

] 1

2 M

ay 2

017

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dt= ω, (3)

where vDQs is the impressed potential vector, Rs the statorresistance, n the number of pole pairs, Tl the load torque

and J :=(

0 −11 0

); the stator current vector ıDQs is the

gradient of HDQm , i.e.,

ıDQs := ∇HDQm (φDQs ) =

(∂1HDQm (φDs , φ

Qs )

∂2HDQm (φDs , φQs )

). (4)

The physical control input is the potential vector vαβs :=R(θ)vDQs impressed in the αβ frame, i.e., the (fictitious)potential vector vDQs rotated by R(θ). Similarly, the mea-sured current vector is ıαβs := R(θ)ıDQs ; in sensorlesscontrol, this is the only available measurement.

Taking advantage of the construction symmetries ofthe PMSM (the stator and the rotor of the PMSM aresymmetric with respect to a plane), see [12] for details, wecan moreover write

HDQm (φDs ,−φQs ) = HDQm (φDs , φQs ), (5)

i.e., the magnetic energy function HDQm of a PMSM is evenwith respect to the q-axis flux linkage φQs .

Notice that thanks to the assumption of sinusoidalwindings, all that is needed to close the model (1)–(3) arethe flux-current relations (4); this is no longer the case fornon-sinusoidal windings, since the electro-magnetic torquein (3) explicitly depends on HDQm . Notice also that thesimplest acceptable function is the quadratic form

HDQm (φDQs ) :=1

2LD(φDs − ΦM )2 +

1

2LQφQs

2,

which yields the current-flux relations

ıDs =φDs − ΦM

LD

ıQs =φQsLQ

and the electro-magnetic torque

Te =n

LDΦMφ

Qs + n

(1

LQ− 1

LD

)φDs φ

Qs ;

in other words, the simplest acceptable magnetic energyfunction represents the unsaturated PMSM. The unsatu-rated model is usually sufficient for control above moder-ately low speed.

This energy approach enjoys several interesting features:

• it naturally enforces the reciprocity conditions∂ıDs∂φQ

s=

∂ıQs∂φD

s[13], since ∂2

12HDQm (φDs , φQs ) = ∂2

21HDQm (φDs , φQs )

• it yields a valid expression for the magnetic torque,even in the presence of magnetic saturation

• it justifies the modeling of saturation in the ficti-tious rotor DQ frame for a star-connected motor.Though this point is usually taken for granted, it isnot completely obvious because of the nonlinearitiesdue to saturation that: i) the transformation from

the physical abc-frame to the fictitious DQ0-framebehaves well; ii) the decoupling between the DQ- andthe 0-axes is still valid

• it requires only a very basic knowledge of the motorinternal layout

• finally, it is particularly amenable to an analysis ofthe effects of signal injection.

In all the experiments, the rotor will be locked in aknown position, so that (1)–(3) reduces to

dφDQsdt

= RT (θlr)vαβs −RsıDQs , (6)

with θlr constant and known. Notice that since θlr isknown, we can consider that vDQs := RT (θlr)v

αβs is

the impressed potential, and ıDQs := RT (θlr)ıαβs is the

available measurement.

III. Classical method

The most widely used method to obtain the current-flux relations, see [7], assumes that an impressed potentialtrajectory t 7→ vDQs (t) is known, together with the result-ing current trajectory t 7→ ıDQs (t). The corresponding fluxlinkage is obtained by time integrating (6), i.e.,

φDQs (t) = φDQs (0) +

∫ t

0

(vDQs (τ)−RsıDQs (τ)

)dτ, (7)

the unknown initial value φDQs (0) being yet to determine.A pair

(ıDQs (t), φDQs (t)

)is thus obtained for each time t;

provided the current trajectory t 7→ ıDQs (t) covers asufficient area of the current plane, this yields the desiredcurrent-flux relations. The initial value φDQs (0) is chosenso as the flux linkage is zero when the current is zero.

Thanks to the filtering effect of the integration, themethod is rather insensitive to measurement noise. How-ever, it is strongly affected by biases in:

• the impressed potential. The power stage is usually anIGBT bridge commuted with PWM; owing to voltagedrops in the transistors and dead times, the actuallyimpressed potential somewhat differs from the desiredone, see e.g. [14]. This is not a problem if voltagesensors are available, as in a laboratory experiment,but matters for implementation on industrial drives,which are usually not equipped with such sensors

• the stator resistance Rs estimation; this is the mainproblem, since the value of the resistance can signifi-cantly vary during a long experiment.

A. Experimental results

The method was used to obtain the current-flux curvesof a 400 W PMSM (rated parameters in table I). The mo-tor is fed by an 1.5 kW ATV71 (ATV71HU15N4) inverterbridge driven by a dSpace board (DS1005). The rotorwas first aligned so that the αβ and DQ frames coincide,and then locked with a mechanical brake. To check theconsistency of the results, three trajectories were used:

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Table IRated parameters of test PMSM.

Rated power 400 WRated voltage (RMS) 139.3 VRated current (RMS) 1.66 ARated frequency 60 HzRated speed 1800 rpmRated torque 2.12 N m

Number of pole pairs n 2Stator resistance Rs 4.25 ΩD-axis inductance LD 43.25 mHQ-axis inductance LQ 69.05 mH

Time (s)

0 5 10 15 20Curr

ent

ref.

(A)

-4

-2

0

2

4

Time (s)

0 5 10 15 20Curr

ent

ref.

(A)

-4

-2

0

2

4

Time (s)

0 5 10 15 20Curr

ent

ref.

(A)

-4

-2

0

2

4

Figure 1. The three current trajectories on D- (—) and Q-axis (—)used in the experiment.

• constant ıDs , 2 s-periodic trapezoidal ıQs with ampli-tude 3 A, see fig. 1(top); the experiment was repeatedfor ıDs := −3 A, −2 A, −1 A, 0 A, 1 A, 2 A and 3 A

• constant ıQs , 2 s-periodic trapezoidal ıDswith amplitude 3 A, see fig. 1(middle);the experiment was repeated for ıQs :=−3 A, −2 A, −1 A, 0 A, 1 A, 2 A and 3 A

• proportional 2 s-periodic trapezoidal currents on bothaxes with total amplitude 3 A, see fig. 1(bottom).

To enforce these trajectories, the currents were controlledwith Proportional-Integral controllers on the D- and Q-axes (damping ratio ξ := 1√

2; bandwidth ω0 := 25 Hz).

The stator resistance is evaluated by computing theratio between the voltage and the current during thephases when the current is constant; it is found to varyfrom 4.5 A to 5.25 A over the whole experiment.

The flux linkage is then computed according to (7). Thesensitivity to voltage biases is illustrated in fig. 2: when thetime integration is performed over several identical similarpatterns (10 in our case), the shape of the experimental

Current (A)

-3 -2 -1 0 1 2 3

Flu

x(W

b)

-0.25

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

0.2

Figure 2. Experimental current-flux curves φDs (ıDs , 0) − ΦM (—)

and φQs (0, ıQs ) (—); solid lines: uncompensated voltage drops; dashedlines: compensated voltage drops; dotted line: averaged curve.

current-flux curve is altered, especially when the currentis small; with uncompensated inverter voltage drops anddead times, the result is very bad (solid lines); withcompensation by a suitable model, the loop in the current-flux curve is much smaller, but still present (dashed lines);the final current-flux curve is then obtained by averagingall the flux linkages points obtained for a current point(dotted line).

The full 3D current-flux relations are displayed in fig. 3.The magnetic saturation is clearly visible. As expectedfrom (5), which implies

∂1HDQm (φDs ,−φQs ) = ∂1HDQm (φDs , φQs )

∂2HDQm (φDs ,−φQs ) = −∂1HDQm (φDs , φQs ),

it can be seen that φDs is even with respect to ıQs , and φQsodd with respect to ıQs .

IV. Proposed method

A. Data acquisition with signal injection

Signal injection was originally introduced for sensorlesscontrol at low velocity [8], but it can also be used for identi-fication [9]. We follow the quantitative analysis introducedin [6], [9] and studied in detail in [15]; it is valid even inthe presence of nonlinearities due to magnetic saturation,and whatever the shape of the (periodic) injected signal.Impressing in (6) a potential vector of the form

vαβs = vαβs + vαβs f(Ωt), (8)

where f a 1-periodic function and Ω is a “large” frequency,the analysis shows that the actual flux linkage is

φDQs = φDQs +1

ΩRT (θlr)v

αβs F (Ωt) +O

(1

Ω2

), (9)

where F is the primitive of f with zero mean, and O is the

“big-O”symbol of analysis; φDQs is the flux linkage withoutsignal injection, i.e., the solution of

dφDQsdt

= RT (θlr)vαβs −RsıDQs .

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2

Ds (A)0-2-2

0Qs (A)

2

-0.2

-0.1

0

0.1

0.2

-0.3

?D s!)

M(W

b)

(a) D-axis flux linkage in function of ıDQs

20

Qs (A)-22

0Ds (A)

-2

-0.3

-0.2

-0.1

0

0.1

0.2

?Q s

(Wb)

(b) Q-axis flux linkage in function of ıDQs

Figure 3. Current-flux relations obtained by the classical method.

Plugging (9) into (4) and expanding then yields

ıαβs = ıαβs +1

ΩγαβF (Ωt) +O

(1

Ω2

), (10)

where γαβ := S(θlr, φ

DQs

)vαβs and

S(θ, φ) := R(θ)

(∂2

11HDQm (φ) ∂212HDQm (φ)

∂212HDQm (φ) ∂2

22HDQm (φ)

)RT (θ).

We call S(θlr, φ

DQs

)the “saliency matrix”; indeed, it ef-

fectively depends on θlr if the motor exhibits saliency,whether geometric or induced by magnetic saturation. Inother words, (10) shows that a small ripple of amplitude

ıαβs := 1Ω γ

αβ , produced by the injected signal vαβs f(Ωt), is

superimposed to the current without signal injection ıαβs ,

produced by vαβs . As explained in [15], both ıαβs and ıαβs

can be extracted from the actual measurement ıαβs usingthe estimations

ıαβs (t) = Ω

∫ t

t− 1Ω

ıαβs (τ)dτ

ıαβs (t) = Ω

∫ tt− 1

Ω

(ıαβs(τ − 1

)− ıαβs (τ)

)F (Ωτ)dτ∫ t

t− 1ΩF 2(Ωt)dt

.

In other words, the “virtual” measurement ıαβs has been

made available besides the “actual” measurement ıαβs .

Notice that since θlr is known, we can consider that

vDQs := RT (θlr)vαβs and vDQs := RT (θlr)v

αβs are the

impressed potentials, and that ıDQs := RT (θlr)ıαβs and

ıDQs := RT (θlr)ıαβs , are the available measurements. It is

then possible to experimentally acquire the six expressions

Experimentally, it is possible to apply any desired

current ıDQs by a suitable choice of vDQs ; by signal in-

jection with at least two independent vectors vDQs and

extraction of the corresponding ıDQs , it is then possible to

obtain the complete saliency matrix, hence ∂211HDQm (φDQs ),

∂222HDQm (φDQs ) and ∂2

12HDQm (φDQs ).

Since the flux linkage φDQs is unknown, what is actually

obtained is H11(ıDQs ), H12(ıDQs ) and H22(ıDQs ), whereHkl(ı

DQs ) := ∂2

klHDQm(ΦDQs (ıDQs )

)and ΦDQs is the inverse

of the flux-current relation (4).

B. Obtaining the current-flux relations from the Hkl(ıDQs )

By the very definition of ΦDQs , we can write ıDQs =∇HDQm

(ΦDQs (ıDQs )

), or, more explicitly,

ıDs = ∂1HDQm(ΦDs (ıDs , ı

Qs ),ΦQs (ıDs , ı

Qs ))

ıQs = ∂2HDQm(ΦDs (ıDs , ı

Qs ),ΦQs (ıDs , ı

Qs )).

Differentiating these relations with respect to ıDs and ıQs ,we find that(

H11(ıDQs ) H12(ıDQs )H12(ıDQs ) H22(ıDQs )

)(∂1ΦDs (ıDQs ) ∂2ΦDs (ıDQs )∂1ΦQs (ıDQs ) ∂2ΦQs (ıDQs )

)is the identity matrix, which implies(∂1ΦDs (ıDQs ) ∂2ΦDs (ıDQs )∂1ΦQs (ıDQs ) ∂2ΦQs (ıDQs )

)=

(Hkl(ı

DQs ) Hkl(ı

DQs )

Hkl(ıDQs ) Hkl(ı

DQs )

)−1

=:

(Ldd(ı

DQs ) Ldq(ı

DQs )

Ldq(ıDQs ) Lqq(ı

DQs )

).

We thus know the partial derivatives of ΦDQs , or, equiva-lently, the integrable differential forms

dΦDs (ıDQs ) = Ldd(ıDQs )dıDs + Ldq(ı

DQs )dıQs

dΦQs (ıDQs ) = Ldq(ıDQs )dıDs + Lqq(ı

DQs )dıQs .

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To recover ΦDQs , we integrate these forms on paths κ 7→ıDQs = IDQs (κ) in the current plane. This yields

ΦDs(IDQs (κ)

)− ΦDs

(IDQs (κ0)

)=

∫ κ

κ0

dΦDsdζ

(IDQs (ζ)

)dζ

=

∫ κ

κ0

Ldd(IDQs (ζ)

)dIDsdζ

(ζ)dζ

+

∫ κ

κ0

Ldq(IDQs (ζ)

)dIQsdζ

(ζ)dζ, (11)

and a similar expression for ΦQs(IDQs (κ)

). Therefore, for

each κ, a couple(IDQs (κ),ΦDs

(IDQs (κ)

))is obtained; pro-

vided the current paths κ 7→ IDQs (κ) cover a sufficientarea of the current plane, this yields the desired current-flux relations. The initial value ΦDQs (IDQs (κa)

)is chosen

so as the flux linkage is zero when the current is zero.Notice the method is completely immune to errors in

the knowledge of the stator resistance Rs, since it neverexplicitly uses its value. Moreover, it is less sensitive thanthe classical method to imperfections of the power inverter

because the base potential vDQs does not need to be known,

whereas the injected potential vDQs can be fairly large.

C. Experimental results

The proposed approach was applied with the sameexperimental conditions as in section III-A, with similardesired currents paths. Nevertheless, the currents were notenforced by controllers not to disturb the signal injection.As a consequence the actual currents paths slightly differfrom the desired ones, see fig. 4; this is not a problem

since the true values of ıDQs are known. The current paths

were discretized with steps ∆ıDQs of about 0.1 A; for each

current point ıDQs , the injected signal was a 5 s long squaresignal of frequency Ω := 500 Hz and amplitude us := 40 V,slowly rotating at frequency fi := 1 Hz,

uDQs := us

(cos(2πfit)sin(2πfit)

).

The corresponding current ripple, namely

ıDQs =usΩ

(H11(ıDQs ) cos(2πfit) +H12(ıDQs ) sin(2πfit)

H12(ıDQs ) cos(2πfit) +H22(ıDQs ) sin(2πfit)

),

then directly yields H11(ıDQs ), H12(ıDQs ) and H22(ıDQs ).The interest of slowly rotating the injected signal is to

provide many measurements points ıDQs , hence an accurate

determination of H11(ıDQs ), H12(ıDQs ) and H22(ıDQs ).The flux linkage along a current path is then obtained

by discretizing the integrals in (11),

ΦDs(IDQs (κ)

)− ΦDs

(IDQs (κ0)

)≈

κ∑ζ=κ0+1

Ldd(IDQs (ζ)

)∆IDs (ζ) + Ldq

(IDQs (ζ)

)∆IQs (ζ),

where ∆IDQs (ζ) := IDQs (ζ)− IDQs (ζ− 1). The current-fluxcurves so obtained are displayed in fig. 5. The consistency

Measured d-axis current (A)

-3 -2 -1 0 1 2 3

Mea

sure

dq-

axis

curr

ent

(A)

-3

-2

-1

0

1

2

3

Figure 4. Actual ıDQs paths.

can be checked by computing the flux linkage difference atpoints where the current paths intersect, which should bezero in theory: the maximum relative error is 1.3 % for theD-axis flux and 2.9 % for the Q-axis. Moreover, as withthe classical method, φDs is even with respect to ıQs , andφQs odd with respect to ıQs .

Notice the method provides the Hessian matrix of theenergy function (

∂211HDQm ∂2

11HDQm∂2

11HDQm ∂211HDQm

),

in function of ıDQs or φDQs , i.e., the partial derivatives ofthe current-flux relations. It is a useful piece of informationfor fitting a parametric model to the current-flux relations;indeed, it is numerically better to fit the derivatives of afunction than the function itself. It also provides its inversematrix, (

Ldd LdqLdq Lqq

),

which is the inductance matrix. As expected from (5),which implies

∂211HDQm (φDs ,−φQs ) = ∂2

11HDQm (φDs , φQs )

∂222HDQm (φDs ,−φQs ) = ∂2

22HDQm (φDs , φQs )

∂212HDQm (φDs ,−φQs ) = −∂2

12HDQm (φDs , φQs ),

the parity/imparity relations are experimentally satisfied,both for the Hessian matrix and its inverse. This is illus-trated for the inductance matrix in in fig. 6; the (cross)-saturation is even more visible than in fig. 5.

D. Comparison with the classical method

Fig. 7 compares some current-flux curves obtained bythe classical and the proposed method. The two meth-ods yield similar curves, with nevertheless some small

Page 6: Obtaining the Current-Flux Relations of the Saturated PMSM by … › pdf › 1705.04605.pdf · but matters for implementation on industrial drives, which are usually not equipped

2

Ds (A)0-2-2

0Qs (A)

2

-0.3

-0.2

-0.1

0

0.1

0.2

?D s!)

M(W

b)

(a) D-axis flux linkage in function of ıDQs

20

Qs (A)-22

0Ds (A)

-2

0

0.1

0.2

-0.3

-0.1

-0.2

?Q s

(Wb)

(b) Q-axis flux linkage in function of ıDQs

Figure 5. Current-flux relations obtained by the proposed method.

differences. Some of the differences could be explainedby experimental errors, especially biases in the classicalmethod. Another possibility is that, owing to hysteresis,the flux linkage computed by signal injection is system-atically smaller than the flux linkage computed by theclassical method; this was noticed for the SynchronousReluctance Motor in [10], and raises the question of whichmodel should be used for sensorless control at low velocity.

V. Conclusion

We have proposed a method based on signal injectionto obtain the saturated current-flux relations of a PMSMfrom locked-rotor experiments. With respect to the clas-sical method based on time integration, it has the mainadvantage of being completely independent of the statorresistance; moreover, it is less sensitive to voltage biases

0.20.10

?Qs (Wb)

-0.1-0.20.1?Ds (Wb)

0-0.1

0

0.02

0.04

0.06

0.08

0.1

1 HD

Qm

@?

D s2

2 !1(H

)

(a) Ldd as a function of φDQs

0.20.10

?Qs (Wb)

-0.1-0.20.1?Ds (Wb)

0-0.1

0

0.02

0.04

0.06

0.08

0.1

3 HD

Qm

@?

Q s2

4 !1(H

)

(b) Lqq as a function of φDQs

0.2

?Qs (Wb)

0.10-0.1-0.20.1

0

?Ds (Wb)

-0.1

0

-5

-10

10

5

HD

Qm

@?

D s@?

Q s(H

!1)

(c) Lqq as a function of φDQs

Figure 6. Coefficients of inductance matrix obtained by the proposedmethod.

Page 7: Obtaining the Current-Flux Relations of the Saturated PMSM by … › pdf › 1705.04605.pdf · but matters for implementation on industrial drives, which are usually not equipped

Current (A)

-3 -2 -1 0 1 2 3

Flu

x(W

b)

-0.25

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

0.2

0.25

(a) ıDs 7→ ΦDs (ıDs , ı

Qs )− ΦM for ıQs = 0 A (—), ıQs = −2 A

(—), ıQs = 2 A (—)

Current (A)

-3 -2 -1 0 1 2 3

Flu

x(W

b)

-0.25

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

0.2

0.25

(b) ıQs 7→ ΦQs (ıDs , ı

Qs ) for ıDs = 0 A (—), ıDs = −2 A (—),

ıDs = 2 A (—)

Figure 7. Comparison of current-flux curves obtained with theclassical (dashed lines) and proposed method (solid lines).

due to the power inverter, as the injected signal may befairly large. Besides, the method provides the inductancematrix (as a function of the current or the flux linkage),which is an interesting piece of information by itself, andcan also be used to fit a parametric model to the current-flux relations; indeed, it is numerically better to fit thederivatives of a function than the function itself.

References

[1] D. D. Reigosa, P. Garcia, D. Raca, F. Briz, and R. D. Lorenz,“Measurement and adaptive decoupling of cross-saturation ef-fects and secondary saliencies in sensorless controlled IPM syn-chronous machines,” IEEE Transactions on Industry Applica-tions, vol. 44, no. 6, pp. 1758–1767, Nov. 2008.

[2] Y. Li, Z. Zhu, D. Howe, C. Bingham, and D. Stone, “Improvedrotor-position estimation by signal injection in brushless AC mo-tors, accounting for cross-coupling magnetic saturation,” IEEETransactions on Industry Applications, vol. 45, pp. 1843–1850,2009.

[3] P. Sergeant, F. De Belie, and J. Melkebeek, “Effect of rotorgeometry and magnetic saturation in sensorless control of PMsynchronous machines,” IEEE Trans. Magnetics, vol. 45, no. 3,pp. 1756–1759, 2009.

[4] N. Bianchi, E. Fornasiero, and S. Bolognani,“Effect of stator androtor saturation on sensorless rotor position detection,” IEEETransactions on Industry Applications, vol. 49, no. 3, pp. 1333–1342, May 2013.

[5] J.-H. Jang, S.-K. Sul, J.-I. Ha, K. Ide, and M. Sawamura,“Sensorless drive of surface-mounted permanent-magnet motorby high-frequency signal injection based on magnetic saliency,”IEEE Trans. Industry Applications, vol. 39, pp. 1031–1039,2003.

[6] A. K. Jebai, F. Malrait, P. Martin, and P. Rouchon,“Sensorless position estimation and control of permanent-magnet synchronous motors using a saturation model,”International Journal of Control, vol. 89, no. 3, pp. 535–549, 2016.

[7] G. Stumberger, B. Polajzer, B. Stumberger, M. Toman, andD. Dolinar, “Evaluation of experimental methods for determin-ing the magnetically nonlinear characteristics of electromagneticdevices,” IEEE Transactions on Magnetics, vol. 41, no. 10, pp.4030–4032, Oct 2005.

[8] P. Jansen and R. Lorenz, “Transducerless position and velocityestimation in induction and salient AC machines,” IEEE Trans.Industry Applications, vol. 31, pp. 240–247, 1995.

[9] A. Jebai, F. Malrait, P. Martin, and P. Rouchon, “Estimationof saturation of permanent-magnet synchronous motors throughan energy-based model,” in IEEE International Electric Ma-chines & Drives Conference, 2011, pp. 1316–1321.

[10] P. Combes, F. Malrait, P. Martin, and P. Rouchon, “Modelingand identification of synchronous reluctance motors,” in IEEEInternational Electric Machines & Drives Conference, 2017.

[11] A. Jebai, P. Combes, F. Malrait, P. Martin, and P. Rouchon,“Energy-based modeling of electric motors,”in IEEE Conferenceon Decision and Control, 2014, pp. 6009–6016.

[12] P. Combes, A. K. Jebai, F. Malrait, P. Martin, and P. Rouchon,“Energy-based modeling of AC motors,” ArXiv e-prints, 2016,arXiv:1609.08050 [math.OC].

[13] J. Melkebeek and J. Willems, “Reciprocity relations for the mu-tual inductances between orthogonal axis windings in saturatedsalient-pole machines,” Industry Applications, IEEE Transac-tions on, vol. 26, no. 1, pp. 107–114, Jan 1990.

[14] A. R. Weber and G. Steiner, “An accurate identification andcompensation method for nonlinear inverter characteristics forac motor drives,” in 2012 IEEE International Instrumenta-tion and Measurement Technology Conference Proceedings, May2012, pp. 821–826.

[15] P. Combes, A. K. Jebai, F. Malrait, P. Martin, and P. Rouchon,“Adding virtual measurements by signal injection,” in AmericanControl Conference, 2016, pp. 999–1005.


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