Application of Kalman filter to estimate junction temperature in IGBT power modules

Knowledge of instantaneous junction temperature is essential for effective health management of power converters, enabling safe operation of the power semiconductors under all operating conditions. Methods based on fixed thermal models are typically unable to compensate for degradation of the thermal path resulting from aging and the effect of variable cooling conditions. Thermosensitive electrical parameters (TSEPs), on the other hand, can give an estimate of junction temperature TJ, but measurement inaccuracies and the masking effect of varying operating conditions can corrupt the estimate. This paper presents a robust and noninvasive real-time estimate of junction temperature that can provide enhanced accuracy under all operating and cooling conditions when compared to model-based or TSEP-based methods alone. The proposed method uses a Kalman filter to fuse the advantages of model-based estimates and an online measurement of TSEPs. Junction temperature measurements are obtained from an online measurement of the on-state voltage, VCE(ON) , at high current and processed by a Kalman filter, which implements a predict-correct mechanism to generate an adaptive estimate of TJ. It is shown that the residual signal from the Kalman filter may be used to detect changes in thermal model parameters, thus allowing the assessment of thermal path degradation. The algorithm is implemented on a full-bridge inverter and the results verified with an IR camer

In-service diagnostics for wire-bond lift-off and solder fatigue of power semiconductor packages

Wire-bond lift-off and Solder fatigue are degradation mechanisms that dominate the lifetime of power semiconductor packages. Although their lifetime is commonly estimated at the design stage, based on mission profiles and Physics-of-Failure models, there are many uncertainties associated with such lifetime estimates, emerging, for example, from model calibration errors, manufacturing tolerances, etc. These uncertainties, combined with the diverse working environments of power semiconductor packages result in inaccurate lifetime estimates. This paper presents an approach for estimating the extent of degradation in power semiconductor packages based on online monitoring of key parameters of the semiconductor, namely, the thermal resistance Rthja and the electrical resistance RCE. Using these two parameters, solder fatigue and wire-bond lift-off can be detected during normal converter operation. In order to estimate these two parameters, two techniques are introduced: a residual obtained from a Kalman filter which estimates the change in the thermal resistance Rthja and a Recursive Least-Squares (RLS) algorithm which is used to estimate the electrical resistance. Both methods are implemented online and validated experimentally

Investigating the impact of varying the number of distributed energy resources on controlling the power flow within a microgrid

The electrification of heat and transport in addition to integration of intermittent renewable resources into the existing electricity network is expected to occur in near future. Such a transformation is expected to force the operation of the electricity power system at different levels to its limits and would require reinforcement of the network assets at different levels. The incorporation of active management and control within microgrids and across the low voltage distribution network is thought as a cost effective solution which would facilitate wide scale integration of the emerging distributed energy resources. However since increasing the microgrid size at a certain DER penetration level would increase the total dispatchable power it is expected to affect the effectiveness of any control algorithm that operates at that level. This paper presents the findings obtained from of an investigation into the relationship between microgrid size and the effectiveness of a deterministic control algorithm implemented at that level

Power flow control for power and voltage management in future smart energy communities

The Community Power Flow Control (CPFC) Algorithm has been proposed as a technique for managing electrical power and energy within small communities. The CPFC manages the resources in the community (DSM, energy storage, RES) in order to control the community’s instantaneous power flow according to a target set by a higher-level management system. This paper investigates the capability of the CPFC to manage local distribution voltage levels. The power flow data for a community has been used together with transformer and cable impedance models to demonstrate the variation of the distribution voltage in a community with significant penetration of PV and EV. The CPFC is shown to manage the voltage levels along a feeder within the statutory limits, even when there is significant export

A novel stochastic modelling approach for electric vehicle charging power and energy requirements

Electrification of heat and transport in addition to integration of intermittent renewable resources into the existing electricity network is expected to occur in near future. Such a transformation is expected to force the operation of the electricity power system at different levels to its limits. A novel bottom up modelling approach for quantifying temporal variation of electric vehicle charging power and energy is presented in this paper which can be used to accurately investigate the effect of charging different penetration levels of electric vehicles within the low voltage distribution network. This EV charging model is further used for development of a deterministic control algorithm for regulating power flows at the low voltage level

SiC/GaN power semiconductor devices theoretical comparison and experimental evaluation

SiC and GaN power transistors conduction loss and switching losses are compared in this paper. In order to compare performance of the same power rating device, a theoretical analysis is given to compare SiC device conduction loss and switching losses change when device maximal blocking voltage reduces by half. Then static and dynamic characteristics of commercial SiC and GaN power transistors are compared and it is shown that GaN-HEMT would still have smaller ON-state resistance and inter-electrode capacitance in comparison with a 600V SiC device. After that, switching losses E8w of a GaN-HEMT is measured and compared with that of a 1200V SiC-JFET and a 600V SiC-MOSFET, in which it is shown that E8w of a GaN-HEMT is smaller than a SiC power transistor with the same power rating

SiC and GaN power transistors switching energy evaluation in hard and soft switching conditions

SiC and GaN power transistors switching energy are compared in this paper. In order to compare switching energy Esw of the same power rating device, a theoretical analysis is given to compare SiC device conduction loss and switching losses change when device maximal blocking voltage reduces by half. After that, Esw of a 650V GaN-HEMT is measured in hard switching condition and is compared with that of a 1200V SiC-MOSFET and a 650V SiC-MOSFET with the same current rating, in which it is shown that Esw of a GaN-HEMT is smaller than a 1200V SiC-MOSFET, which is smaller than 650V SiC-MOSFET. Following by that, in order to reduce device turn-ON switching energy, a zero voltage switching circuit is used to evaluate all the devices. Device output capacitance stored energy Eoss are measured and turn-OFF switching losses are obtained by subtracting Eoss, which shows that GaN-HEMT is sill better than SiC device in terms of switching losses and 1200V SiC-MOSFET has smaller switching losses than 650V SiC-MOSFET

Developing power semiconductor device model for virtual prototyping of power electronics systems

Virtual prototyping (VP) is very important for power electronics systems design. A virtual prototyping design tool based on different modelling technology and model order reduction is proposed in the paper. In order to combine circuit electromagnetic model with power semiconductor device models, a SiC-JFET behavioural model is presented and implemented in the design tool. A half bridge circuit using SiC-JFET devices is thus represented in the VP software. The presented SiC-JFET behavioural model is then validated by comparing with experimental measurements on switching waveforms

GaN-HEMT dynamic ON-state resistance characterisation and modelling

GaN-HEMTs suffer from trapping effects which might increase device ON-state resistance (RDS(on)) values. Thus, dynamic RDS(on) of a commercial GaN-HEMT is characterized at different bias voltages in the paper by a proposed measurement circuit. Based on the measurement results, a behavioural model is proposed to represent device dynamic RDS(on) values, in which trapping and detrapping time constant is represented by a series of RC network. The model is simulated in PSPICE, of which the simulation results of RDS(on) values are compared and validated with the measurement when device switches in a power converter with different duty cycles and switching voltages. The results show that RDS(on) values of this device would increase due to trapping effects

Characterisation and modeling of Gallium nitride power semiconductor devices dynamic on-state resistance

Gallium nitride high-electron-mobility transistors (GaN-HEMTs) suffer from trapping effects that increases device on-state resistance (RDS(on)) above its theoretical value. This increase is a function of the applied dc bias when the device is in its off state, and the time which the device is biased for. Thus, dynamic RDS(on) of different commercial GaN-HEMTs are characterised at different bias voltages in the paper by a proposed new measurement circuit. The time-constants associated with trapping and detrapping effects in the device are extracted using the proposed circuit and it is shown that variations in RDS(on) can be predicted using a series of RC circuit networks. A new methodology for integrating these RDS(on) predictions into existing gallium nitride-high-electron-mobility transistors models in standard SPICE simulators to improve model accuracy is then presented. Finally, device dynamic RDS(on) values of the model is compared and validated with the measurement when it switches in a power converter with different duty cycles and switching voltages