The Experts below are selected from a list of 92337 Experts worldwide ranked by ideXlab platform
Thomas G. Habetler - One of the best experts on this subject based on the ideXlab platform.
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stator Temperature Estimation of direct torque controlled induction machines via active flux or torque injection
IEEE Transactions on Power Electronics, 2015Co-Authors: Siwei Cheng, Ronald G Harley, Thomas G. HabetlerAbstract:This paper proposes two thermal monitoring methods for induction machines with direct torque control (DTC). The stator resistance $R_{s}$ is used as a direct indicator of average winding Temperature and is estimated via a dc current offset in the stator winding. In a DTC drive system, the major challenge is how to excite the dc current offset via the only existing flux and torque control loops. The quantitative relationship between the desired dc current offset and the corresponding changes in flux linkage and torque is derived, and this shows that the dc current offset can be achieved either by superimposing flux linkage bias command $[\matrix{{\bf \Delta \Psi} _{{\bm s\alpha},{\rm ref}}\cr {\bf \Delta\Psi}_{{\bm s\beta},{\rm ref}}}]$ in the flux control loop (method 1) or torque ripple command ${\bf \Delta }T_{em,{\rm ref}} $ in the torque control loop (method 2), both shown in Fig. 1 . Simulation results confirm the analytical analysis of the two proposed methods; while the experimental data prove that both methods achieve accurate Temperature Estimation under various operating conditions. The proposed simple and efficient signal-injection-based Temperature Estimation technique is particularly advantageous since it eliminates the need for embedded Temperature sensors, requires no hardware change to conventional DTC drive systems, and has a minimal impact on the induction machine's normal operation.
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An active stator Temperature Estimation technique for thermal protection of inverter-fed induction motors with considerations of impaired cooling detection
IEEE Transactions on Industry Applications, 2010Co-Authors: Pinjia Zhang, Bin Lu, Thomas G. HabetlerAbstract:Thermal protection is one of the most important aspects of any motor control system. This paper proposes a stator winding Temperature Estimation method for the thermal protection of inverter-fed electric motors. By modifying the space vector pulsewidth modulation in an open-loop motor drive, a dc voltage can be intermittently injected into the motor. The stator Temperature can be estimated by measuring only the dc component of the phase current under both constant- and variable-load conditions. The evaluation of the resultant torque pulsation and the compensation for serial resistances are also discussed. The proposed stator Temperature Estimation method is validated from experimental results under variable-load conditions and both healthy and impaired cooling conditions. The error in the stator Temperature Estimation is within 8 °C under different operating conditions. The significance of this method lies in its non-intrusive nature: only current sensors are required for implementation the normal operation of the motor is not interrupted.
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rotor Temperature Estimation of squirrel cage induction motors by means of a combined scheme of parameter Estimation and a thermal equivalent model
International Electric Machines and Drives Conference, 2003Co-Authors: C Kral, Thomas G. Habetler, Ronald G Harley, F Pirker, G Pascoli, H Oberguggenberger, C J M FenzAbstract:This paper deals with a rotor Temperature Estimation scheme for fan-cooled, mains-fed squirrel cage induction motors. The proposed technique combines a rotor resistance Estimation method with a thermal equivalent circuit. Usually, rotor resistance Estimation works quite well under rated load conditions. By contrast, if the motor is slightly loaded, rotor resistance Estimation becomes inaccurate due to the small slip. Therefore, rotor Temperature Estimation under low load conditions may be estimate by a thermal equivalent model. In order to determine the rotor resistance and thus rotor Temperature accurately, several machine parameters have to be obtained in advance. Load tests provide the leakage reactance and the iron losses of the induction machine. The stator resistance has to be measured separately. The parameters of the thermal equivalent model are a thermal resistance and a thermal capacitance. These parameters are derived from a heating test, where the reference Temperature is provided from the parameter model in the time domain. This lumped thermal parameter model is based on the assumption that the total rotor Temperature increase is caused by the total sum of the losses in the induction machine. Measuring results of a 1.5 kW and a 18.5 kW four pole, low voltage motor and a 210 kW, four pole high voltage motor are presented and compared.
David A Howey - One of the best experts on this subject based on the ideXlab platform.
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Sensorless Battery Internal Temperature Estimation Using a Kalman Filter With Impedance Measurement
IEEE Transactions on Sustainable Energy, 2015Co-Authors: Robert R. Richardson, David A HoweyAbstract:This study presents a method of estimating battery- cell core and surface Temperature using a thermal model coupled with electrical impedance measurement, rather than using direct surface Temperature measurements. This is advantageous over previous methods of estimating Temperature from impedance, which only estimate the average internal Temperature. The performance of the method is demonstrated experimentally on a 2.3-Ah lithium-ion iron phosphate cell fitted with surface and core thermocouples for validation. An extended Kalman filter (EKF), consisting of a reduced-order thermal model coupled with current, voltage, and impedance measurements, is shown to accurately predict core and surface Temperatures for a current excitation profile based on a vehicle drive cycle. A dual-extended Kalman filter (DEKF) based on the same thermal model and impedance measurement input is capable of estimating the convection coefficient at the cell surface when the latter is unknown. The performance of the DEKF using impedance as the measurement input is comparable to an equivalent dual Kalman filter (DKF) using a conventional surface Temperature sensor as measurement input.
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battery internal Temperature Estimation by combined impedance and surface Temperature measurement
Journal of Power Sources, 2014Co-Authors: Robert R. Richardson, P T Ireland, David A HoweyAbstract:Abstract A new approach, suitable for real-time implementation, is introduced for Estimation of non-uniform internal Temperature distribution in cylindrical lithium-ion cells. A radial 1-D model is used to estimate the distribution using two inputs: the real or imaginary part of the electrochemical impedance of the cell at a single frequency, and the surface Temperature. The approach does not require knowledge of cell thermal properties, heat generation or thermal boundary conditions. The model is validated experimentally, the first time for such an approach, using a cylindrical 26650 cell fitted with an internal thermocouple. The cell is heated by applying (1) current pulses of up to ±20 A and (2) a 3500 s HEV drive cycle current profile, whilst monitoring the surface and core Temperatures and measuring impedance at 215 Hz. During the drive cycle test, the battery core Temperature increases by 20 °C and the surface Temperature increases by 14 °C. The mean absolute error in the predicted maximum Temperature throughout the cycle is 0.6 °C (3% of the total core Temperature increase), in contrast to a mean absolute error of 2.6 °C if the Temperature is assumed to be uniform (13% of the total core Temperature increase).
David Reigosa - One of the best experts on this subject based on the ideXlab platform.
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comparative analysis of bemf and pulsating high frequency current injection methods for pm Temperature Estimation in pmsms
IEEE Transactions on Power Electronics, 2017Co-Authors: David Reigosa, Takashi Kato, Daniel Fernandez, Tsutomu Tanimoto, Fernando BrizAbstract:Permanent magnet synchronous machines performance is highly dependent on the permanent magnets (PMs) Temperature. However, PM Temperature measurement is not easy and is not normally implemented in standard machines. Alternatively, PM Temperature can be estimated. PM Temperature Estimation methods can be divided into three major groups: thermal model-based methods, BEMF-based methods, and methods based on the injection of some form of high-frequency signal into the stator terminals of the machine. One concern for thermal model-based methods is that the model often needs to be adjusted for each machine design and application, knowledge of the machine geometry, materials, and cooling system being, therefore, required. On the contrary, BEMF methods and methods based on high-frequency signal injection estimate the magnet Temperature from measurable electrical variables, knowledge of the geometry or cooling system not being required. Though they use the same type of signals, BEMF and high-frequency signal injection methods present relevant differences. This paper realizes a comparative analysis of both methods. Physical principles, performance, and implementation will be addressed.
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rotor Temperature Estimation in doubly fed induction machines using rotating high frequency signal injection
IEEE Transactions on Industry Applications, 2017Co-Authors: David Reigosa, J.m. Guerrero, A Diez, Fernando BrizAbstract:Thermal monitoring is a common feature in most electric machine drives since thermal overloading is one of the most common causes of motor failures. Contact-type sensors are normally used to measure the stator Temperature in electric machines. However, use of this type of sensor is not advisable in the rotor as it requires cabling to a rotating part or the use of a wireless transmission system. Consequently, measurement of the rotor Temperature is not easy in practice and is not normally implemented in standard machines. An alternative to rotor Temperature measurement is rotor Temperature Estimation. To date, only thermal models have been used for rotor Temperature Estimation in doubly-fed induction machines (DFIMs). This paper proposes rotor Temperature Estimation in DFIMs using high-frequency signal injection. The proposed method estimates the rotor Temperature from the rotor high frequency resistance, which is a function of the rotor windings Temperature. The method does not interfere with the normal operation of the drive and can be implemented in existing DFIM drives without requiring additional hardware.
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permanent magnet Temperature Estimation in pmsms using pulsating high frequency current injection
IEEE Transactions on Industry Applications, 2015Co-Authors: David Reigosa, Takashi Kato, Daniel Fernandez, Hideo Yoshida, Fernando BrizAbstract:The injection of a high-frequency signal in the stator via inverter has been shown to be a viable option to estimate the magnet Temperature in permanent-magnet synchronous machines (PMSMs). The variation of the magnet resistance with Temperature is reflected in the stator high-frequency resistance, which can be measured from the resulting current when a high-frequency voltage is injected. However, this method is sensitive to $d$ - and $q$ -axis inductance ( $L_{d}$ and $L_{q} $ ) variations, as well as to the machine speed. In addition, it is only suitable for surface PMSMs (SPMSMs) and inadequate for interior PMSMs (IPMSMs) . In this paper, the use of a pulsating high-frequency current injection in the $d$ -axis of the machine for Temperature Estimation purposes is proposed. The proposed method will be shown to be insensitive to the speed, $L_{q}$ , and $L_{d} $ variations. Furthermore, it can be used with both SPMSMs and IPMSMs.
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magnet Temperature Estimation in surface pm machines during six step operation
IEEE Transactions on Industry Applications, 2012Co-Authors: David Reigosa, Fernando Briz, M.w. Degner, Pablo Garcia, J.m. GuerreroAbstract: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.
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magnet Temperature Estimation in surface pm machines during six step operation
Energy Conversion Congress and Exposition, 2011Co-Authors: David Reigosa, Fernando Briz, M.w. Degner, Pablo Garcia, J.m. GuerreroAbstract:This paper presents a method for estimating the magnet Temperature in surface permanent magnet synchronous machines (SPMSM's) 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. Six-step operation produces currents harmonics that induces additional losses in the permanent magnets and can therefore increase their Temperature. 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.1
Fernando Briz - One of the best experts on this subject based on the ideXlab platform.
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comparative analysis of bemf and pulsating high frequency current injection methods for pm Temperature Estimation in pmsms
IEEE Transactions on Power Electronics, 2017Co-Authors: David Reigosa, Takashi Kato, Daniel Fernandez, Tsutomu Tanimoto, Fernando BrizAbstract:Permanent magnet synchronous machines performance is highly dependent on the permanent magnets (PMs) Temperature. However, PM Temperature measurement is not easy and is not normally implemented in standard machines. Alternatively, PM Temperature can be estimated. PM Temperature Estimation methods can be divided into three major groups: thermal model-based methods, BEMF-based methods, and methods based on the injection of some form of high-frequency signal into the stator terminals of the machine. One concern for thermal model-based methods is that the model often needs to be adjusted for each machine design and application, knowledge of the machine geometry, materials, and cooling system being, therefore, required. On the contrary, BEMF methods and methods based on high-frequency signal injection estimate the magnet Temperature from measurable electrical variables, knowledge of the geometry or cooling system not being required. Though they use the same type of signals, BEMF and high-frequency signal injection methods present relevant differences. This paper realizes a comparative analysis of both methods. Physical principles, performance, and implementation will be addressed.
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rotor Temperature Estimation in doubly fed induction machines using rotating high frequency signal injection
IEEE Transactions on Industry Applications, 2017Co-Authors: David Reigosa, J.m. Guerrero, A Diez, Fernando BrizAbstract:Thermal monitoring is a common feature in most electric machine drives since thermal overloading is one of the most common causes of motor failures. Contact-type sensors are normally used to measure the stator Temperature in electric machines. However, use of this type of sensor is not advisable in the rotor as it requires cabling to a rotating part or the use of a wireless transmission system. Consequently, measurement of the rotor Temperature is not easy in practice and is not normally implemented in standard machines. An alternative to rotor Temperature measurement is rotor Temperature Estimation. To date, only thermal models have been used for rotor Temperature Estimation in doubly-fed induction machines (DFIMs). This paper proposes rotor Temperature Estimation in DFIMs using high-frequency signal injection. The proposed method estimates the rotor Temperature from the rotor high frequency resistance, which is a function of the rotor windings Temperature. The method does not interfere with the normal operation of the drive and can be implemented in existing DFIM drives without requiring additional hardware.
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permanent magnet Temperature Estimation in pmsms using pulsating high frequency current injection
IEEE Transactions on Industry Applications, 2015Co-Authors: David Reigosa, Takashi Kato, Daniel Fernandez, Hideo Yoshida, Fernando BrizAbstract:The injection of a high-frequency signal in the stator via inverter has been shown to be a viable option to estimate the magnet Temperature in permanent-magnet synchronous machines (PMSMs). The variation of the magnet resistance with Temperature is reflected in the stator high-frequency resistance, which can be measured from the resulting current when a high-frequency voltage is injected. However, this method is sensitive to $d$ - and $q$ -axis inductance ( $L_{d}$ and $L_{q} $ ) variations, as well as to the machine speed. In addition, it is only suitable for surface PMSMs (SPMSMs) and inadequate for interior PMSMs (IPMSMs) . In this paper, the use of a pulsating high-frequency current injection in the $d$ -axis of the machine for Temperature Estimation purposes is proposed. The proposed method will be shown to be insensitive to the speed, $L_{q}$ , and $L_{d} $ variations. Furthermore, it can be used with both SPMSMs and IPMSMs.
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magnet Temperature Estimation in surface pm machines during six step operation
IEEE Transactions on Industry Applications, 2012Co-Authors: David Reigosa, Fernando Briz, M.w. Degner, Pablo Garcia, J.m. GuerreroAbstract: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.
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magnet Temperature Estimation in surface pm machines during six step operation
Energy Conversion Congress and Exposition, 2011Co-Authors: David Reigosa, Fernando Briz, M.w. Degner, Pablo Garcia, J.m. GuerreroAbstract:This paper presents a method for estimating the magnet Temperature in surface permanent magnet synchronous machines (SPMSM's) 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. Six-step operation produces currents harmonics that induces additional losses in the permanent magnets and can therefore increase their Temperature. 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.1
Haifeng Dai - One of the best experts on this subject based on the ideXlab platform.
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battery internal Temperature Estimation for lifepo4 battery based on impedance phase shift under operating conditions
Energies, 2017Co-Authors: Jiangong Zhu, Xuezhe Wei, Zechang Sun, Haifeng DaiAbstract:An impedance-based Temperature Estimation method is investigated considering the electrochemical non-equilibrium with short-term relaxation time for facilitating the vehicular application. Generally, sufficient relaxation time is required for battery electrochemical equilibrium before the impedance measurement. A detailed experiment is performed to investigate the regularity of the battery impedance in short-term relaxation time after switch-off current excitation, which indicates that the impedance can be measured and also has systematical decrement with the relaxation time growth. Based on the discussion of impedance variation in electrochemical perspective, as well as the monotonic relationship between impedance phase shift and battery internal Temperature in the electrochemical equilibrium state, an exponential equation that accounts for both measured phase shift and relaxation time is established to correct the measuring deviation caused by electrochemical non-equilibrium. Then, a multivariate linear equation coupled with ambient Temperature is derived considering the Temperature gradients between the active part and battery surface. Equations stated above are all identified with the embedded thermocouple experimentally. In conclusion, the Temperature Estimation method can be a valuable alternative for Temperature monitoring during cell operating, and serve the functionality as an efficient implementation in battery thermal management system for electric vehicles (EVs) and hybrid electric vehicles (HEVs).
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adaptive kalman filtering based internal Temperature Estimation with an equivalent electrical network thermal model for hard cased batteries
Journal of Power Sources, 2015Co-Authors: Haifeng Dai, Letao Zhu, Jiangong Zhu, Xuezhe Wei, Zechang SunAbstract:The accurate monitoring of battery cell Temperature is indispensible to the design of battery thermal management system. To obtain the internal Temperature of a battery cell online, an adaptive Temperature Estimation method based on Kalman filtering and an equivalent time-variant electrical network thermal (EENT) model is proposed. The EENT model uses electrical components to simulate the battery thermodynamics, and the model parameters are obtained with a least square algorithm. With a discrete state-space description of the EENT model, a Kalman filtering (KF) based internal Temperature estimator is developed. Moreover, considering the possible time-varying external heat exchange coefficient, a joint Kalman filtering (JKF) based estimator is designed to simultaneously estimate the internal Temperature and the external thermal resistance. Several experiments using the hard-cased LiFePO4 cells with embedded Temperature sensors have been conducted to validate the proposed method. Validation results show that, the EENT model expresses the battery thermodynamics well, the KF based Temperature estimator tracks the real central Temperature accurately even with a poor initialization, and the JKF based estimator can simultaneously estimate both central Temperature and external thermal resistance precisely. The maximum Estimation errors of the KF- and JKF-based estimators are less than 1.8 °C and 1 °C respectively.
