Search Results (213)

High-power-density insulated gate bipolar transistor (IGBT) modules in new energy vehicles require efficient heat dissipation and good temperature uniformity. This study proposes a tri-objective topology optimization method for a liquid-cooled heat sink using average temperature, temperature variance, and flow dissipation as the objective functions. A two-dimensional model was established in COMSOL to investigate the effects of the fluid volume fraction, inlet pressure, and optimization-weight distribution on the optimized topology and thermo-hydraulic performance. The results show that a fluid volume fraction of 0.4 and an inlet pressure of 15 Pa provide the best overall performance. Compared with the bi-objective design, introducing temperature variance as a third objective reduces temperature variance by 50.23%, with only a 1.08% increase in average temperature. Three-dimensional simulations further verify the optimized design. Compared with a conventional pin-fin heat sink, the topology-optimized structure reduces the average temperature by 10.43% and the temperature variance by 44.37%, while increasing the flow dissipation by 49.57%. These results show that tri-objective topology optimization is an effective method for improving the thermal management of high-power-density IGBT modules. Full article

Remaining useful life (RUL) prediction for power semiconductor devices such as insulated-gate bipolar transistors (IGBTs) is central to reliable power-electronics operation, yet remains challenging because degradation is non-stationary and electro-thermal precursors are strongly coupled. Here, we propose a physics-informed incremental learning framework (PIILF), which models aging as a latent incremental state-evolution process rather than static trajectory fitting. PIILF integrates an incremental state evolution network (ISEN) for state-wise degradation updates, task-adaptive parameter sharing (TAPS) for mitigating cross-task interference among coupled precursors, and a physics-informed observation decoder (PIOD) that reconstructs observables through electro-thermal coupling relations. On the NASA IGBT accelerated aging dataset, evaluated over 100 random seeds, PIILF achieves lower RMSE and MAE than TimesNet, TimeXer, and DeepHPM, while retaining competitive MAPE, a slightly better $R^2$, and higher parameter efficiency. When the training data are reduced to 50% and 25%, PIILF exhibits smaller error increases than the baselines, indicating greater robustness in data-scarce settings. These findings suggest that embedding physical consistency directly into incremental representation learning provides an effective and efficient route to robust semiconductor RUL prediction. Full article

Direct Torque Control (DTC) for induction motors (IMs) is an advanced method derived from Field-Oriented Control (FOC). In DTC, a voltage source inverter (VSI) is employed to directly regulate the stator flux linkage and electromagnetic torque through space vector modulation (VSM), where the optimal switching vector is selected for the VSI. Similarly to FOC, the stator flux and electromagnetic torque are independently controlled to deliver enhanced dynamic performance. However, DTC still suffers from certain drawbacks, such as slow transient response, limited dynamic performance, and high ripples in torque and flux. In this paper, an improved DTC method is proposed for a three-phase squirrel-cage induction motor. Specifically, a Type-2 fuzzy logic controller is employed to regulate both the stator flux and electromagnetic torque (T2FLC). The proposed method (FLCDTC) combines a three-level VSI with dual-band hysteresis (DBHW) switching to generate the gating signals for the insulated gate bipolar transistors (IGBTs). This approach effectively reduces the total harmonic distortion (THD) in torque and stator current, lowers the common-mode voltage (CMV), and enhances the overall motor performance. Simulation results under random noise distribution demonstrate the robustness of the proposed controller, even at low operating speeds. Finally, the effectiveness of the algorithm is validated in real-time through hardware-in-the-loop (HIL) implementation. Full article

A Controllable Line-Commutated Converter (CLCC) is a novel piece of equipment for enhancing the commutation failure resistance of High-Voltage Direct Current (HVDC) transmission systems. Traditional lumped parameter models ignore the high-frequency coupling effects of internal distributed stray capacitances, resulting in insufficient transient simulation accuracy and restricting refined engineering design. Taking the CLCC in the HVDC transformation project as the research object, this paper analyzes the distribution characteristics of stray parameters in a press-pack Insulated Gate Bipolar Transistor (IGBT) under stacked structures. By integrating distributed stray parameter networks with the nonlinear characteristics of the devices, an improved IGBT equivalent circuit model is established, with key parameters identified based on field-measured data. Furthermore, an LCC-CLCC simulation model is built and used to replace the improved IGBT model to conduct short-circuit fault simulation verification. The results demonstrate that the high-fidelity model accurately reproduces transient waveforms under Alternating Current (AC) voltage disturbance and faithfully reflects the actual operating characteristics of a surge arrester and IGBT, thereby effectively compensating for the idealized errors inherent in traditional models. This modeling methodology provides a robust theoretical and simulation foundation for parameter optimization, valve control system design, and the secure operation of a CLCC. Full article

Bidirectional power converters generate significant heat losses during high-frequency operation, posing a severe challenge to the performance of heat dissipation systems. Traditional thermal design methods often struggle to balance multiple objectives, such as cooling efficiency, cost, weight, and size, thereby limiting the reliability and safety of the system. To address these challenges, this paper proposes a novel Multi-Objective Exponential Distribution Optimizer algorithm based on the Exponential Distribution Optimizer. Subsequently, key design variables of the heat dissipation system are selected. Next, the Optimal Latin Hypercube Sampling method is employed to generate sample points, and a second-order response surface surrogate model for the heat pipe radiator’s volume and temperature is developed. Lastly, by integrating elite non-dominated sorting, crowding distance mechanisms, and an information feedback mechanism, the multi-objective challenge is decomposed into subproblems, thereby enhancing optimization efficiency. Through comparative simulation experiments on benchmark functions, the Wilcoxon signed-rank test results for the MOEDO algorithm on the majority of the three metrics are denoted as ‘+’, indicating statistically significant advantages over the compared algorithms, thereby demonstrating its superior performance in addressing multi-objective optimization problems. The study further conducts simulation verification of the heat pipe heat dissipation system before and after optimization using ANSYS Icepak. The simulation results demonstrate that, compared with the conventional design, the maximum Insulated Gate Bipolar Transistor (IGBT) temperature is reduced by 17.12% and the heat sink volume is reduced by 14.61%. Full article

One of the main causes of failure in Insulated Gate Bipolar Transistor (IGBT) modules used in high-power conversion applications is thermal-stress-induced degradation. In this paper, an experimental testing setup for thermal stress and real-time degradation monitoring, as well as a deep neural network (DNN)-based lifetime prediction of IGBT modules under thermo-electrically stressed inverter operation, is proposed. A two-level SVPWM inverter is implemented to create a hybrid power cycling test platform that imposes well-defined junction-temperature swings representative of real-world operation by combining controlled electrical loading and active induction heating with water cooling. Throughout the aging process, on-state voltage and module temperature are constantly monitored to identify degradation precursors associated with thermo-mechanical fatigue. A physics-based Coffin–Manson lifetime model is fitted using failure datasets to characterize temperature-dependent lifetime behavior. An offline deep neural network (DNN) is trained on degradation trajectories derived from on-state collector–emitter voltage (V_ce,on) to predict remaining useful lifetime. This approach uses partial degradation histories for accurate early-life prediction. The proposed DNN model for competitive and computationally efficient lifetime prediction is validated experimentally on several IGBT modules under different thermal stresses, and its accuracy is compared with other prediction methods. Full article

A novel modular multilevel converter (MMC)-based spark-gap trigger generator for high-voltage pulsed-power applications has been developed and presented in this work. It fully exploits the inherent modularity of MMC topology to generate high-voltage trigger pulses in a flexible and scalable manner. A prototype based on insulated gate bipolar transistors (IGBTs) was constructed to effectively trigger the breakdown of the spark gaps of a Marx Bank consisting of four capacitors charged to 50 kV. It is characterized by a fast rise time and produces pulses of 15 kV with a duration of ~200 ns. Using semiconductors and foil capacitors, the new trigger generator successfully replaces the thyratron-based generator. Full article

Modular multilevel converters (MMCs) for high-voltage direct current (HVDC) transmission require substantial submodule (SM) capacitance to limit capacitor voltage ripple, resulting in bulky and costly converter valves. The integrated gate-commutated thyristor (IGCT), with its higher voltage rating and lower conduction loss compared to the insulated-gate bipolar transistor (IGBT), enables a significant reduction in the number of SMs per arm, offering a pathway toward compact converter design. This paper investigates how the reduced SM count of IGCT-based MMCs affects the feasibility and benefit of operating with elevated capacitor voltage ripple to further decrease SM capacitance. An analytical framework is developed to evaluate the modulation boundary under increased ripple, explicitly accounting for the voltage ripple coupling (CVR) effect and circulating-current suppression. A ripple-tolerance coefficient κ is introduced, and its optimal value is determined by identifying the inflection point beyond which the achievable AC voltage output begins to decline. For a ±500 kV/2000 MW IGCT-MMC case study using 6.5 kV devices with 250 SMs per arm, the proposed method reduces the per-unit energy storage requirement by up to 39.4% compared with conventional-ripple operation. Simulation and prototype experimental results on a 400 V, 3 kW, 4-SM/arm test bench validate the analytical predictions and confirm the practical feasibility of the approach. Full article

To address the aging and failure issues that arise during the long-term operation of insulated gate bipolar transistors (IGBTs), this paper proposes a method for predicting their remaining useful life (RUL). The proposed method utilizes a genetic algorithm to optimize a hybrid model that combines a convolutional neural network (CNN) with a bidirectional long short-term memory (BiLSTM) network. First, based on the failure mechanism of IGBTs, various commonly used RUL prediction methods are analyzed and compared. Considering that CNNs are particularly effective at extracting spatial features, while LSTMs excel at capturing long-term dependencies in time-series data, a hybrid CNN-BiLSTM model is developed for RUL prediction, with hyperparameters, including the initial learning rate, optimized using a genetic algorithm. Experimental results demonstrate that the proposed CNN-BiLSTM model achieves superior performance across all metrics compared with benchmark algorithms, and the genetic algorithm significantly accelerates the parameter optimization process and enhances the overall training efficiency. Full article

This article presents an online additive fault-detection system for the speed sensor of a 200 W shunt-type direct current (DC) motor, integrated into a power module controlled by an Insulated Gate Bipolar Transistor (IGBT). The system is designed to trigger an alarm signal when an additive fault occurs by comparing the Kalman Filter (KF) residual against a predefined detection threshold. Three specific fault types in the speed sensor were analyzed: offset, disconnection, and sinusoidal noise. Experimental results demonstrate effective fault detection across a speed range of 80 to 690 rpm under no-load conditions. However, when a constant torque of 0.5 Nm is applied, both the detection threshold and the subset of reliably identifiable faults must be adjusted. The main contribution of this study is the development of a customized real-time fault detection framework and the characterization of residual variations caused by unmodeled load disturbances in actual hardware. This approach improves the monitoring and fault-diagnosis capabilities of sensor systems in DC motors by quantifying the stochastic behavior of residuals under different operating constraints. Full article

Insulated-gate bipolar transistor (IGBT) power modules suffer efficiency degradation at elevated operating junction temperatures. The thermal sensitivity of the collector–emitter saturation voltage (V_CEsat) induces thermal stress imbalance, constraining system efficiency and reliability. A multi-resistor cascade network model for carrier-storage trench-gate IGBTs (CS-IGBTs) is established. The simulation results agree with the measurements within 10% error. The model decomposes the temperature coefficient contributions of individual structural regions. Analysis reveals that the drift region resistance dominates the V_CEsat temperature coefficient. Based on this finding, a co-doping strategy is proposed through simultaneously increasing the doping concentration in the carrier-storage layer and P⁺ collector. This approach reduces the temperature sensitivity of carrier mobility in the drift region, thereby optimizing V_CEsat’s temperature sensitivity. For the fabricated 1200 V/40 A CS-IGBT, the V_CEsat temperature coefficient decreases from 2.38 mV/K to 1.76 mV/K over 300 K to 450 K, which represents a 25.4% reduction. The total switching loss at 450 K decreases from 9.32 mJ to 8.70 mJ, achieving a 6.7% improvement. This device-level optimization suppresses V_CEsat’s temperature sensitivity and switching losses, enhancing efficiency in high-temperature power module applications. Full article

While sustainability is set as a goal by a broad range of international organizations, its definition varies, and there is still a lack of practical criteria for product designers to evaluate the degree of (un)sustainability in the design phase. Life cycle assessment (LCA) can allow quantification of the environmental impacts of a product but is often carried out post-design, when the manufacturing process is already settled. Finally, while significant advances have been made towards standardizing LCA calculations by providing product category rules, large uncertainties remain in the calculation results due to a lack of transparency regarding the choices of databases, system boundaries, allocation, cut-off rules, and level of data granularity. A practical way to improve in those areas is to share with the semiconductor community a parametrizable life cycle inventory (LCI) model based on a target device to (1) identify knowledge gaps in LCA methods for such products, (2) identify the main process variables, and (3) provide a starting point for LCA calculations by the designers themselves. With this aim, a parametrizable cradle-to-gate manufacturing LCI model was developed based on the peer-reviewed process flow of a trench field-stop silicon insulated gate bipolar transistor (IGBT) semiconductor power device. The model allows computation of the environmental impacts of the IGBT manufacturing process based on different tunable parameters such as die size, wafer diameter, manufacturing yield, abatement efficiency, wafer fab throughput, wafer fab location, and associated electricity mix. Embedding a high level of data granularity, it helps identify, at elementary process levels, key environmental hotspots and associated technical levers for their reduction. Analysis of the IGBT manufacturing process tends to demonstrate the importance of an impact assessment approach considering multiple environmental categories, going beyond the sole focus on greenhouse gas emissions and accounting for potential transfers of impact. With an open-source mindset and in a continuous improvement prospective, the manufacturing inventory model and its associated tools are freely available from a public GitHub repository and open for comments and consolidation from users. Full article

The high-frequency switching noise of insulated-gate bipolar transistors (IGBTs) limits the sensitivity of online partial discharge (PD) monitoring in ultra-high-voltage flexible DC (VSC-HVDC) transmission systems. To address this challenge, this study investigates the underlying mechanisms and evolution of this interference and develops an anti-interference signal separation method. Simulation and experimental results indicate that the energy of IGBT switching noise is concentrated in the 30–180 MHz range, which significantly overlaps with the ultra-high-frequency (UHF) band used for PD detection. This research further reveals the pronounced modulation effect of device aging on the interference spectrum: bond wire aging triggers “spectral reconstruction” via altered parasitic parameters, where severe collector aging leads to an abnormal surge in turn-off interference amplitude. In contrast, gate oxide layer degradation manifests as characteristic “global spectrum attenuation” and a shift in peak frequency toward lower bands. Confronted with the challenges of strong interference and spectrum drift induced by aging, this paper proposes an adaptive signal separation method based on feature optimization of the time–frequency cumulative energy function. This method constructs novel characteristic parameters—namely, oblique intercept width and morphological gradient steepness—to effectively capture the fundamental differences in the energy accumulation process of the signals. Experimental verification demonstrates that even under conditions of varying interference characteristics, the proposed method achieves high-precision separation of PD signals from IGBT noise, outperforming traditional equivalent time–frequency and wavelet principal component analysis methods. This research provides crucial theoretical and technical support for insulation condition monitoring and device aging diagnosis in VSC-HVDC converter valves. Full article

This paper presents an open-architecture mechatronic drive platform for operating a three-phase BLDC servomotor in an industrial robotic axis. A sequential and iterative mechatronic design methodology is adopted, integrating electronic design, digital control, mechanical development, and experimental prototyping, with emphasis on open-loop operation. The electronic circuit was designed using schematics and a PCB and validated in Proteus Design Suite 8.15 (Labcenter Electronics Ltd., London, UK) to verify switching sequences and inverter behavior. The power stage is based on a six-switch insulated-gate bipolar transistor (IGBT) inverter module, complemented by an independent snubber protection board and a dedicated digital gate-drive control board. The mechanical enclosure was designed using computer-aided design (CAD), CAD software tools (Shapr3D, version 5.911.0 (9224), Shapr3D Zrt., Budapest, Hungary), and fabricated via 3D printing. Switching behavior was simulated in Octave using parameters from a real industrial BLDC servomotor (Yaskawa SGMAH series) extracted from a Motoman robotic axis. The contribution is design-oriented in a mechatronic engineering sense, emphasizing accessibility, openness, and experimental enablement of industrial drive hardware rather than control-performance optimization. An industrial Yaskawa BLDC servomotor from the Motoman robot is used to determine switching sequences and safe operating parameters. Experimental open-loop tests were conducted by directly commanding the six inverter switching sectors, resulting in the stable synchronous rotation of the motor on the developed electromechanical platform. Full article

The operational reliability of Insulated Gate Bipolar Transistor (IGBT) modules in demanding transportation applications, such as traction systems, is critically challenged by solder layer and bond wire failures under cyclic thermal stress. To address this, this paper proposes a novel health monitoring framework that innovatively synergizes micro-scale spatial thermal analysis with microsecond electrical dynamics inversion. The method requires only non-invasive temperature measurements on the module baseplate and utilizes standard electrical signals (load current, duty cycle, switching frequency, DC-link voltage) readily available from the converter’s controller, enabling simultaneous diagnosis without dedicated voltage or high-bandwidth current sensors. First, a non-invasive assessment of solder layer fatigue is achieved by correlating the normalized thermal gradient ($\nabla T_{\mathrm{P}}$) on the baseplate with the underlying thermal impedance ($Z_{\mathrm{JC}}$). Second, for bond wire aging, a cost-effective inversion algorithm estimates the on-state voltage ($V_{\mathrm{ce},\mathrm{on}}$) by calculating the total power loss from temperature, isolating the conduction loss ($P_{\mathrm{cond}}$) with the aid of a Foster-model-based junction temperature ($T_{\mathrm{J}}$) estimate, and finally computing $V_{\mathrm{ce},\mathrm{on}}$ at a unique current inflection point ($I_{\mathrm{C},\inf }$) to nullify $T_{\mathrm{J}}$ dependency. Third, the health states from both failure modes are fused for comprehensive condition evaluation. Experimental validation confirms the method’s accuracy in tracking both degradation modes. This work provides a practical and economical solution for online IGBT condition monitoring, enhancing the predictive maintenance and operational safety of transportation electrification systems. Full article