Magnet Temperature Estimation in Surface PM ... - IEEE Xplore

IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. 48, NO. 6, NOVEMBER/DECEMBER 2012

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Magnet Temperature Estimation in Surface PM Machines During Six-Step Operation David Díaz Reigosa, Member, IEEE, Fernando Briz, Senior Member, IEEE, Michael W. Degner, Senior Member, IEEE, Pablo García, and Juan Manuel Guerrero, Member, IEEE

Abstract—This paper presents a method for estimating the magnet temperature in surface permanent-magnet (PM) synchronous machines during six-step operation. Six-step operation allows the maximum available dc-bus voltage to be applied to a machine, which maximizes its torque and speed range. This can be of importance in electric traction applications, including railway as well as electric and hybrid electric vehicles. However, six-step operation produces current harmonics that induce additional losses in the PMs and can therefore increase their temperature. An increase of magnet temperature can result in a reduced torque capability and eventually in a risk of demagnetization if excessive values are reached, with real-time rotor magnet temperature monitoring being therefore advisable. Six-step operation provides opportunities for rotor temperature monitoring from the electrical terminal variables (voltages and currents) of the motor. To achieve this goal, the rotor high-frequency resistance is measured using the harmonic voltages and currents due to six-step operation, from which the magnet temperature can be estimated. Index Terms—Magnet temperature estimation, permanentmagnet (PM) synchronous machines (PMSMs), six steps.

I. I NTRODUCTION

I

N THE LAST two decades, the design and control of permanent-magnet (PM) synchronous machines (PMSMs) have been the focus of significant research effort due to their ability to provide higher performance and higher efficiency when compared to other machine types [1]–[8]. Reducing the machine losses has consequently become a major focus from a design perspective [4], [9], [12]. The machine losses can be divided into stator and rotor losses. The stator losses can

Manuscript received November 22, 2011; revised February 7, 2012 and February 23, 2012; accepted March 12, 2012. Date of publication November 16, 2012; date of current version December 31, 2012. Paper 2011-IDC-687.R2, presented at the 2011 IEEE Energy Conversion Congress and Exposition, Phoenix, AZ, September 17–22, and approved for publication in the IEEE T RANSACTIONS ON I NDUSTRY A PPLICATIONS by the Industrial Drives Committee of the IEEE Industry Applications Society. This work was supported in part by the Research, Technological Development, and Innovation Programs of the Spanish Ministry of Science and Innovation–ERDF under Grant MICINN10-ENE2010-14941 and in part by the Ministry of Science and Innovation under Grant MICINN-10-CSD2009-00046. D. D. Reigosa, F. Briz, P. García, and J. M. Guerrero are with the Department of Electrical, Computer, and System Engineering, University of Oviedo, 33204 Gijón, Spain (e-mail: [email protected]; [email protected]; [email protected]; [email protected]; guerrero@ isa.uniovi.es). M. W. Degner is with the Department of Electric Machine Drive Systems, Hybrid Electric Vehicle and Fuel Cell Vehicle Laboratory, Ford Research and Advanced Engineering, Ford Motor Company, Dearborn, MI 48121-2053 USA (e-mail: [email protected]). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TIA.2012.2227097

be further divided into copper losses, iron hysteresis losses, and iron eddy current losses, while the rotor losses can be split into eddy current losses and hysteresis losses in both the iron and the PMs [4], [9]–[14]. The stator losses are a result of the fundamental excitation, harmonics of the fundamental excitation, and the inverter switching ripple, while the rotor losses are a result of only the switching ripple and fundamental excitation harmonics that do not rotate synchronously with the rotor [4], [9]–[14]. Saying this in another way, the stator losses are the results of all components of excitation [10], [12], [14], while rotor losses are only caused by flux harmonics that do not rotate synchronously with the rotor or change in amplitude [3], [4], [10], [11], [13], [14]. The temperature increase caused by these losses in both the stator and rotor [4], [9], [10] can have several adverse effects. An excessive increase of the stator winding temperature can degrade the winding insulation. Increases of the magnet temperature can result in a reduction of magnet strength, either transiently or permanently, which translates into a reduced torque production capability of the machine [14]–[16], [32]. Therefore, having accurate measurement or estimates of the magnet temperature is highly desirable in many applications. Although direct measurement of magnet temperature is possible, it is not practical in most applications for the following reasons. Contact-type temperature sensors, e.g., thermistors, transmit the measurement signal electrically, which makes them difficult to use on the rotor without some sort of slip ring or telemetry device to transmit the measurement from the rotor to the stationary frame [10]. Noncontact sensors, e.g., infrared, can be used directly to measure the rotor temperature at a distance but are more expensive, less accurate, and difficult to package, particularly in production applications. In addition, measurement of the magnet temperature requires that the magnets be visible, which is impractical in many applications. An alternative to the measurement of the magnet temperature is to estimate it from other quantities that are normally available in electric machine drives like the stator currents, stator voltages, and rotor speed. The methods to estimate the magnet temperature can be divided into thermal models [17]–[19] and methods based on the injection of a high-frequency signal [10]. Methods of the first type model the heat transfer characteristic of the machine. Since this depends on the geometry and cooling system, these methods normally require the development of a thermal model for each machine design and application. The second type of method estimates the magnet temperature from the variation of the equivalent high-frequency rotor resistance, which can be obtained from the estimated

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high-frequency impedance of the machine [10]. These methods require the prior knowledge of the high-frequency impedance of the machine at the room temperature. However, they do not require the knowledge of the machine design or cooling system. Measurement of the high-frequency impedance is most easily achieved through the injection of some form of high-frequency excitation (either current or voltage), with the resulting voltage or current then being used to estimate the impedance. Furthermore, for the method to work online, this signal needs to be superimposed on the fundamental excitation. The injection of a high-frequency small-magnitude carrier signal voltage, which was superimposed on the fundamental voltage, for temperature estimation purposes was proposed in [10] and [34]. The injection of a high-frequency signal requires a slight modification of the modulation pattern and sufficient voltage margin between the fundamental component of the applied voltage and the voltage limit of the inverter feeding the machine in order for the carrier signal to be generated. This margin may not be available under certain working conditions. For example, when the machine operates at high speeds at or near the overmodulation region, the available voltage margin will be significantly reduced. However, overmodulation, more specifically, six-step operation, produces fundamental excitation harmonics [28]–[31], which can be used for temperature estimation purposes. Sixstep operation is commonly used in traction drives for railway, electric vehicle (EV), and hybrid EV applications [29], [31], [35]–[40] to maximize the torque and speed range, and can also be found in many other applications [41], [42]. Magnet temperature estimation in surface PMSMs (SPMSMs) working in six-step operation is the focus of this paper. Six-step operation, as well as the analytical formulation of temperature estimation using a high-frequency signal, is presented first, with implementation issues being discussed later. Experimental results are provided to demonstrate the viability of the proposed method.

II. ROTOR T EMPERATURE E STIMATION U SING THE H IGH -F REQUENCY R ESISTANCE This section briefly discusses the principles of rotor temperature estimation from the high-frequency impedance. More detailed discussion can be found in [10]. The electromagnetic behavior of a PMSM depends on its temperature. Changes of the rotor temperature will cause the flux density of the PMs to vary (1) [10], [27]. Similarly,

changes in both the stator and rotor temperatures will cause their resistances to change according to [10], [27] B(T ) = Br0 (1 + ΔT αB (T ))

(1)

R(T ) = R0 (1 + αΔT )

(2)

where R(T ) is the stator/rotor resistance, B(T ) is the PM magnetic flux density, R0 and Br0 are the stator/rotor resistance and the PM magnetic flux density at room temperature, respectively, α is the copper resistive thermal coefficient (stator resistance) or the magnet resistive thermal coefficient (rotor resistance), αB is the PM magnetic flux thermal coefficient, and ΔT is temperature variation [10]. When there is voltage excitation (3) present in a machine at frequencies sufficiently higher than that of the fundamental excitation, the resulting currents (4) can be calculated using the machine’s high-frequency impedance s = Vc ejωct vdqsc

(3)

s vdqsc

(4)

= Zdqsc isdqsc

where Vc is the magnitude of the high-frequency voltage vector, ωc is its frequency, and Zdqsc is the high-frequency impedance of the machine [10]. Substituting the temperature-dependent terms in (1) and (2) into (3) and (4), the resulting high-frequency current can be obtained (5) and (6), with the temperature dependence explicitly shown isdqsc (Ts , Tr ) =

Vc R2 (Ts , Tr ) + (ωc )2 L2 (Tr )

∗ ej (ωc t−ϕZdqsc (Ts ,Tr )) (ωc )2 L2 (Tr ) ϕZdqsc (Ts , Tr ) = a tan R2 (Ts , Tr )

(5) (6)

where R is the high-frequency resistance, L is the highfrequency inductance, and Ts and Tr are the stator and rotor temperatures, respectively. The high-frequency impedance (7), shown at the bottom of the page, can be obtained from (4) and (5), with its resistive component being (8). The magnet temperature, which can be obtained from (8), shown at the bottom of the page, using (2), is given by (9), shown at the bottom of the page, where αcu is the copper thermal resistivity coefficient, αmag is the PM thermal resistivity coefficient, T0 is the room temperature, and

Zdqsc (Ts , Tr ) = R(Ts , Tr ) + jωc L(Tr ) =

s vdqsc isdqsc

(7)

R(Ts , Tr ) = |Z(Ts , Tr )| cos ϕZdqsc (Ts , Tr ) = Rs (T0 ) [1 + αcu (T0 − Ts )] + Rr (T0 ) [1 + αmag (T0 − Tr )] Tr = T 0 +

R(Ts , Tr ) − Rr (T0 ) − Rr (T0 ) [1 + αcu (T0 − Ts )] Rr (T0 )αmag

(8) (9)

REIGOSA et al.: MAGNET TEMPERATURE ESTIMATION IN PM MACHINES DURING SIX-STEP OPERATION

Fig. 1.

Simplified representation of the controller for a PMSM.

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Fig. 3. Voltage waveforms during six-step operation.

Fig. 4. Voltage complex vector spectrum under six-step operation.

Fig. 2. Voltage space vectors and limits of linear modulation, nonlinear modulation, and six-step operation.

Rs and Rr are the stator and rotor high-frequency resistances [10], [27], respectively. III. H IGH -F REQUENCY I MPEDANCE M EASUREMENT IN S IX -S TEP O PERATION The highest possible fundamental voltage from a three-phase inverter (see Fig. 1) is obtained during six-step operation, with the modulation index being defined as m = 1 for this case (see Fig. 2) [30]. Fig. 3 shows the phase voltages (va , vb , and vc ) applied to the machine during six-step operation and the resulting voltage complex vectors (vd and vq ), with the transformation of a generic three-phase quantity (voltage or current) f to a dq quantity being defined as j2π s = fd + jfq = 2/3 fa + fb e 3 + fc ej4π/3 . (10) fdq The injected voltage complex vector shown in Fig. 3 can be expressed using a Fourier series as s = bn ej(nω0 t+θ) (11) fdq n=1,−5,7, −11,13,...

where θ = π when n < 0, θ = −π when n > 0, ω0 is the fundamental excitation frequency, and bn is defined by bn =

2 ∗ fmax [−2 cos(nπ) − cos (n2π/3) + cos (nπ/3)] nπ (12)

where fmax is the maximum value of the phase voltage (see Fig. 3). The resulting frequency spectrum of the voltage complex vector in six-step operation is shown in Fig. 4. Six-step operation creates harmonics having the following orders: −5, 7, −11, 13, . . .(11), with the harmonic magnitudes being inversely proportional to the harmonic order (12) (Fig. 4). These voltage harmonics can be modeled as shown in (13), s is the harmonic voltage where n is the harmonic order, vdqsn space vector, and Vn is the amplitude of the “nth” harmonic. Each harmonic present in the voltage will produce a corresponding harmonic in the current isdqsn . The magnitude of these current harmonics due to six-step can be calculated using a simplified high-frequency model (14) of the electric machine, where Zdqsn is the high-frequency impedance of the machine at the frequency of nω0 s vdqsn = Vn ejnω0 t

(13)

s vdqsn

(14)

= Zdqsn isdqsn .

Although it could be concluded from (7)–(9) and (13) and (14) that any harmonic present in the applied voltage due to six-step operation could be used for the measurement of the high-frequency resistance, this is not true in practice due to implementation issues. As the harmonic order increases, the magnitude of the corresponding voltage harmonic decreases, which, combined with the high-frequency impedance increase due to its inductive nature, result in a significant reduction of the resulting harmonic current and, consequently, in a reduction the signal-to-noise ratio. Furthermore, the relative ratio of the resistive term to the inductive terms in the high-frequency impedance decreases as the frequency increases (Fig. 5) further complicating the measurement of the high-frequency

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Fig. 5. (a) Magnitude and (b) phase of the high-frequency impedance as a function of frequency.

Fig. 7. Block diagram for the magnet temperature estimation under six-step operation.

TABLE I M ACHINE PARAMETERS

Fig. 8. (a) Detail of the drill in the cover of the machine and (b) infrared thermometer.

resistance. It can be concluded from this that using lower order harmonics would be preferred. It should be noted, however, that lower order harmonics are closer to the fundamental component and may not have sufficient spectral separation, increasing the risk of spectral interference and making the signal processing more difficult. The selection of the harmonic used for resistance estimation is discussed further in the next section.

contribution to the overall high-frequency impedance (9). The stator resistance at room temperature can be easily measured and stored for use during operation of the algorithm using a wide variety of temperature devices. For this paper, a positive temperature coefficient thermistor was used. To evaluate the performance of the proposed method, the magnet temperature was also measured during machine operation using an infrared noncontact-type thermometer. A window was drilled in the cover of the machine [Fig. 8(a)] to place the thermometer [Fig. 8(b)]. The infrared thermometer covers a temperature range from 40 ◦ C to 1030 ◦ C, with a resolution of 0.1 ◦ C, an accuracy of ±1.5 ◦ C, an optical resolution of 15 : 1, a spectral range of 8–14 μm, and a minimum spot of 8–10 mm. It should be noted that the magnet width is 10 mm.

IV. I MPLEMENTATION

V. E XPERIMENTAL R ESULTS

This section discusses the implementation of the proposed temperature estimation method for an SPMSM. The test machine’s parameters are shown in Table I. The test machine has a magnet pole arc of 150 electrical degrees (Fig. 6). The schematic representation of the signal processing used for magnet temperature estimation is shown in Fig. 7. The high-frequency impedance (7) is estimated from the selected harmonic voltage (13) and the measured resulting harmonic current (14) which are obtained from the measured current complex vector (isdqs ) and from the commanded voltage s∗ ) by a filtering process. The magnet complex vector (vdqs temperature is estimated continuously whenever the machine is operated in six steps from the estimated high-frequency impedance using (8) and (9). It should be noted that the stator temperature and the stator high-frequency resistance at room temperature are needed to decouple the stator resistance

Experimental results showing the viability of the proposed method are presented in this section. Although six-step operation is normally used at high speeds to maximize the output voltage capabilities of a voltage source inverter with a fixed dc-bus voltage [28]–[31], there could be applications where the dc-bus voltage is not fixed and the six-step operation is not restricted to high-speed operation. An example of such applications is EVs where the dc-bus voltage of the inverter either is directly equal to the battery voltage, which varies with current and state of charge, or set by a boost converter from the battery voltage, with the boost converter output voltage varying depending on the operating point of the system [33]. In cases like these, the machine can work in six steps at rotor speeds significantly below rated speed. To show the feasibility of the proposed method for such applications, experimental results at various speeds and dc-bus voltages are included in this section.

Fig. 6. Photographs of the test machine.


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TABLE II M ACHINE O PERATING P OINTS

Fig. 11. Exp.#1. (a) (◦) Measured magnet temperature, estimated magnet temperature using the () −5th harmonic, and estimated magnet temperature using the () seventh harmonic. (b) Magnet temperature estimate error using the () −5th harmonic and using the () seventh harmonic to estimate the magnet temperature. Fig. 9. (a) Measured phase-to-neutral voltages under six-step operation and (b) spectrum. DC-bus voltage = 55 V; ωr = 150 r/min.

Fig. 10. (a) Measured phase currents under six-step operation and (b) spectrum. DC-bus voltage = 55 V; ωr = 150 r/min.

The machine’s operating points for the experimental results are shown in Table II. It can be seen that they cover a wide range of rotor speeds and dc-bus voltages. In all the cases, the machine was operated in six steps.The results presented in this section used both the −5th and the 7th harmonics for the magnet temperature estimation as a comparison. The corresponding frequencies and magnitudes of these harmonics for each operating condition are shown in Table II. Figs. 9(a) and 10(a) show the phase-to-neutral voltages and the measured phase currents under six-step operation, while Figs. 9(b) and 10(b) show the frequency spectra of both signals versus harmonic order for Exp.#1 in Table II.

Fig. 12. Exp.#2. (a) (◦) Measured magnet temperature, estimated magnet temperature using the () −5th harmonic, and estimated magnet temperature using the () seventh harmonic. (b) Magnet temperature estimate error using the () −5th harmonic and using the () seventh harmonic to estimate the magnet temperature.

Figs. 11–15 show the experimental results of the temperature estimation method, the measured rotor temperature, and the temperature error versus the stator temperature, using the −5th and 7th harmonics.

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It can be noted from Fig. 11 (low speed) and Figs. 12–14 (medium speed) that the accuracy of the temperature estimation with the −5th harmonic is slightly better compared with that


with the seventh harmonic. As already mentioned, this can be explained by the fact that the magnitude of the injected harmonic voltage decreases inversely proportional to the harmonic order (Fig. 9 and (12)) and the resulting harmonic current magnitude decreases even faster (Fig. 10). This translates into a reduced signal-to-noise ratio when the seventh harmonic is used, which is further compounded by the reduced sensitivity to the resistance as the frequency increases, as can be observed from Fig. 5, i.e., the impedance becomes more inductive in nature. For high-speed operation (Fig. 15), the estimation with the −5th harmonic is significantly better compared to that with the seventh harmonic. This can be explained by the increased significance of the factors mentioned earlier for the low-speed and medium-speed cases. It can also be observed from Figs. 12 and 13 that the results for Exp.#3, using the −5th harmonic, and the experimental results for Exp.#2, using the seventh harmonic, are almost identical. Under these conditions, the frequency of the two harmonics is the same (see Table II), which confirms that the primary difference between the use of the two harmonics is primarily due to the reduced sensitivity to resistance and decreased signal-to-noise ratio as frequency increases. The same behavior can be observed comparing Exp.#3, using the seventh harmonic, and Exp.#4, using the −5th harmonic (Figs. 13 and 14), although the accuracy of the estimation using the −5th harmonic is always slightly better. Although not presented in this paper, the use of the −11th harmonic was found to be unviable for temperature estimation purpose at any speed due to its reduced magnitude.


TABLE III AVERAGE M AGNET T EMPERATURE E RROR

TABLE IV D IFFERENCE B ETWEEN THE F INAL M EASURED T EMPERATURE AND THE ROOM T EMPERATURE

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to support the viability of the method. It has been shown that the temperature estimation using the −5th harmonic is slightly better at low-/medium-speed conditions compared with that using the seventh harmonic and that the estimation at highspeed condition is better when the −5th harmonic is used.

ACKNOWLEDGMENT The authors would like to thank the University of Oviedo and the Ford Motor Company for the motivation and support that they provided.

Table III shows the average magnet temperature error when using the −5th and 7th harmonics, from 50 ◦ C to 85 ◦ C. It can be observed from Table III and also from Figs. 11–15 that the accuracy of the estimated temperature decreases as the speed increases. This can be seen from the slight increase of the temperature error from Exp.#1 to Exp.#4 (see Table III and Figs. 11–14) that becomes more obvious when the speed increases as shown in Exp.#5 (Table III and Fig. 15), which might by caused by the frequency increase of the additional harmonics and the reduction of the relative value of the highfrequency resistance effect over the high-frequency impedance as the speed does. Finally, Table IV shows the difference in temperature between the final measured temperature (see Figs. 11–15) and the room temperature, for the experiments shown in Table II. It can be observed that the differential temperature between the stator and rotor is higher as the speed increases. This can by explained by the fact that the core losses in the machine increase as the speed increases. Additionally, the increase of the impedance value (Fig. 5) does not match the increase of the dc-bus voltage (Table II) as the speed increases, and as a consequence, the induced harmonic currents (−5th , 7th , −11th , . . .) increase in value (12), which increases the induced losses and the final temperature. It should be noted from Table IV and Fig. 11 that the minimum temperature difference (low-speed condition) between the stator and rotor is ≈ 20 ◦ C, which is ≈ 5 ◦ C higher that the temperature difference obtained for the case of linear operation (sinusoidal excitation) in [10]. This can be explained by the fact that, in six-step operation, there are additional harmonics that do not rotate synchronously with the rotor, producing additional losses in both the stator and rotor [14]. VI. C ONCLUSION Magnet temperature estimation is a concern for the control and protection of PMSM. A method to estimate the magnet temperature in SPMSMs operated in six-step mode has been presented in this paper. The magnet temperature is obtained from the rotor high-frequency resistance, which is calculated from the high-frequency voltages and currents inherent to the six-step mode. Implementation of the method requires the measurement of either the stator winding temperature or the stator resistance for the compensation of the stator high-frequency resistance variations. Experimental results have been provided

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[18] N. Bianchi and T. M. Jahns, “Design, analysis, and control of interior PM synchronous machines,” in Conf. Rec. IEEE IAS Annu. Meeting, Oct. 2004, pp. 2532–2540. [19] Z. J. Liu, D. Howe, P. H. Mellor, and M. K. Jenkins, “Thermal analysis of permanent magnet machines,” in Proc. IEEE IEMDC, Sep. 1993, pp. 359–364. [20] J.-I. Ha, K. Ide, T. Sawa, and S.-K. Sul, “Sensorless rotor position estimation of an interior permanent-magnet motor from initial states,” IEEE Trans. Ind. Appl., vol. 39, no. 3, pp. 761–767, May/Jun. 2003. [21] A. Consoli, G. Scarcella, and A. Testa, “Industry application of zero-speed sensorless control techniques for PM synchronous motors,” IEEE Trans. Ind. Appl., vol. 37, no. 2, pp. 513–521, Mar./Apr. 2001. [22] P. L. Jansen and R. D. Lorenz, “Transducerless position and velocity estimation in induction and salient AC machines,” IEEE Trans. Ind. Appl., vol. 31, no. 2, pp. 240–247, Mar./Apr. 1995. [23] Y. Jeong, R. D. Lorenz, T. M. Jahns, and S.-K. Sul, “Initial rotor position estimation of an interior permanent-magnet synchronous machine using carrier-frequency injection methods,” IEEE Trans. Ind. Appl., vol. 41, no. 1, pp. 38–45, Jan./Feb. 2005. [24] P. García, F. Briz, M. W. Degner, and D. Díaz-Reigosa, “Accuracy and bandwidth limits of carrier signal injection-based sensorless control methods,” IEEE Trans. Ind. Appl., vol. 43, no. 4, pp. 990–1000, Jul./Aug. 2007. [25] D. Reigosa, P. García, D. Raca, F. Briz, and R. D. Lorenz, “Measurement and adaptive decoupling of cross-saturation effects and secondary saliencies in sensorless-controlled IPM synchronous machines,” IEEE Trans. Ind. Appl., vol. 44, no. 6, pp. 1758–1767, Nov./Dec. 2008. [26] D. Raca, P. García, D. Reigosa, F. Briz, and R. D. Lorenz, “Carrier signal selection for sensorless control of PM synchronous machines at very low and zero speeds,” IEEE Trans. Ind. Appl., vol. 46, no. 1, pp. 167–178, Jan./Feb. 2010. [27] D. Reigosa, P. García, F. Briz, D. Raca, and R. D. Lorenz, “Modeling and adaptive decoupling of high-frequency resistance and temperature effects in carrier-based sensorless control of PM synchronous machines,” IEEE Trans. Ind. Appl., vol. 46, no. 1, pp. 139–149, Jan./Feb. 2010. [28] X. Xu and G. Hirzinger, “Design of current control of fully integrated surface-mounted permanent magnet synchronous motor drive servo actuator,” in Proc. IEEE EPE, 2005, p. 9, [CD-ROM]. [29] S. Morimoto, Y. Inoue, T. F. Weng, and M. Sananda, “Position sensorless PMSM drive system including square-wave operation at high-speed,” in Conf. Rec. IEEE IAS Annu. Meeting, 2007, pp. 676–682. [30] T. S. Kwon, G. Y. Choi, M. S. Kwak, and S. K. Sul, “Novel fluxweakening control of an IPMSM for quasi-six-step operation,” IEEE Trans. Ind. Appl., vol. 44, no. 6, pp. 1722–1731, Nov./Dec. 2008. [31] J. I. Itoh and T. Ogura, “Evaluation of total loss for an inverter and motor by applying modulation strategies,” in Proc. IEEE EPE, 2010, pp. S1221–S12-28, [CD-ROM]. [32] S. Ruoho, J. Kolehmainen, J. Ikaheimo, and A. Arkkio, “Interdependence of demagnetization, loading, and temperature rise in a permanent-magnet synchronous motor,” IEEE Trans. Magn., vol. 46, no. 3, pp. 949–953, Mar. 2010. [33] M. Becherif and M. Y. Ayad, “Advantages of variable DC bus voltage for hybrid electrical vehicle,” in Proc. IEEE VPPC, 2010, pp. 1–6, [CD-ROM]. [34] F. Briz, M. W. Degner, J. M. Guerrero, and A. B. Diez, “Temperature estimation in inverter fed machines using high frequency carrier signal injection,” IEEE Trans. Ind. Appl., vol. 44, no. 3, pp. 799–808, May 2008. [35] K. Asano, Y. Inaguma, H. Ohtani, E. Sato, M. Okamura, and S. Sasaki, “High performance motor drive technologies for hybrid vehicles,” in Proc. PCC, Nagoya, Japan, 2007, pp. 1584–1589. [36] T. Yamakawa, S. Wakao, K. Kondo, and T. Yoneyama, “A new flux weakening operation of interior permanent magnet synchronous motors for railway vehicle traction,” in Proc. EPE, 2005, 6 pp., [CD-ROM]. [37] B. K. Bose and P. M. Szczesny, “A microcomputer-based control and simulation of an advanced IPM synchronous machine drive system for electric vehicle propulsion,” IEEE Trans. Ind. Electron., vol. 35, no. 4, pp. 547–559, Nov. 1998. [38] J. Lee, J. Choi, and Y. Nishida, “Overmodulation strategy of NPC type 3-level inverter for traction drives,” in Proc. ICPE, 2007, pp. 137–142. [39] T. Schoenen, A. Krings, D. van Treek, and R. W. De Doncker, “Maximum DC-link voltage utilization for optimal operation of IPMSM,” in Proc. IEEE IEMDC, 2009, pp. 1547–1550. [40] S. Hiti, B. M. Conlon, and C. C. Stancu, “Controlling electric vehicle DC bus voltage ripple under step mode of operation,” U.S. Patent 6 362 585, Mar. 26, 2002.

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David Díaz Reigosa (S’03–M’07) was born in Spain in 1979. He received the M.E. and Ph.D. degrees in electrical engineering from the University of Oviedo, Gijón, Spain, in 2003 and 2007, respectively. From 2004 to 2008, he was awarded the fellowship of the Personnel Research Training Program funded by the Regional Ministry of Education and Science of the Principality of Asturias. In 2007, he was a Visiting Scholar with the Wisconsin Electric Machines and Power Electronics Consortium, University of Wisconsin, Madison. He is currently an Associate Professor with the Department of Electrical, Computer and Systems Engineering, University of Oviedo. His research interests include sensorless control of induction motors, permanent-magnet synchronous motors, and digital signal processing. Prof. Reigosa was the recipient of the IEEE Industry Applications Society Conference Prize Award in 2007.

Fernando Briz (A’96–M’99–SM’06) received the M.S. and Ph.D. degrees from the University of Oviedo, Gijón, Spain, in 1990 and 1996, respectively. From June 1996 to March 1997, he was a Visiting Researcher with the University of Wisconsin, Madison. He is currently a Full Professor with the Department of Electrical, Computer and Systems Engineering, University of Oviedo. His topics of interest include control systems, power converters and ac drives, sensorless control of ac drives, magnetic levitation, diagnostics, and digital signal processing. Prof. Briz was the recipient of the 2005 IEEE T RANSACTIONS ON I NDUS TRY A PPLICATIONS Third Place Prize Paper Award and of three IEEE Industry Applications Society Conference Prize Paper awards in 1997, 2003, and 2007.

Michael W. Degner (S’95–A’98–M’99–SM’05) received the B.S., M.S., and Ph.D. degrees in mechanical engineering from the University of Wisconsin, Madison, in 1991, 1993, and 1998, respectively, with a focus on electric machines, power electronics, and control systems. His Ph.D. dissertation was on the estimation of rotor position and flux angle in electric machine drives. In 1998, he joined the Ford Research Laboratory, Dearborn, MI, where he worked on the application of electric machines and power electronics in the automotive industry. He is currently the Senior Technical Leader with the Department of Electric Machine Drive Systems, Hybrid Electric Vehicle and Fuel Cell Vehicle Laboratory, Ford Research and Advanced Engineering, Ford Motor Company, Dearbon, where he is responsible for the development of electric machines, power electronics, and their control systems for hybrid and fuel-cell vehicle applications. His research interests include control systems, machine drives, electric machines, power electronics, and mechatronics. Dr. Degner was a recipient of the 2005 IEEE T RANSACTIONS ON I NDUS TRY A PPLICATIONS Third Place Prize Paper Award and has been the recipient of several IEEE Industry Applications Society Conference Paper awards.


Pablo García received the M.S. and Ph.D. degrees in electrical engineering and control from the University of Oviedo, Gijon, Spain, in 2001 and 2006, respectively. For the period 2002–2006, he was awarded a fellowship of the Personnel Research Training Program funded by the Spanish Ministry of Education. In 2004, he was a Visiting Scholar with the Wisconsin Electric Machines and Power Electronics Consortium, University of Wisconsin, Madison. He is currently an Assistant Professor with the Department of Electrical, Computer and Systems Engineering, University of Oviedo. His research interests include sensorless control, diagnostics, magnetics bearings, and signal processing.

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Juan Manuel Guerrero (S’00–A’01–M’04) received the M.E. degree in industrial engineering and the Ph.D.degree in electrical and electronic engineering from the University of Oviedo, Gijón, Spain, in 1998 and 2003, respectively. Since 1999, he has occupied different teaching and research positions with the Department of Electrical, Computer and Systems Engineering, University of Oviedo, where he is currently an Associate Professor. From February to October 2002, he was a Visiting Scholar witth the University of Wisconsin, Madison. From June to December 2007, he was a Visiting Professor with the Tennessee Technological University, Cookeville. His research interests include parallelconnected motors fed by one inverter, sensorless control of induction motors, control systems, and digital signal processing. Prof. Guerrero was a recipient of an award from the College of Industrial Engineers of Asturias and León, Spain, for his M.E. thesis in 1999, an IEEE Industry Applications Society Conference Prize Paper Award in 2003, and the University of Oviedo Outstanding Ph.D. Thesis Award in 2004.