Electro-thermal Model Research Articles

A control-oriented comprehensive model of PEM electrolyzer considering double-layer capacitance

The modeling of electrochemical and thermal characteristics of proton exchange membrane (PEM) electrolyzer is significant in the hydrogen production process. However, the calculation of electrode impedance and double-layer capacitance during operation is not accurate enough currently, and the electrothermal coupling characteristics of hydrogen production devices are not fully considered. In this paper, the multi-stage equivalent circuit of the PEM electrolyzer is designed using electrochemical impedance spectroscopy (EIS) and the time-constant fitting method. In addition, according to the temperature control system of the actual hydrogen production device, the electro-thermal model of the PEM electrolyzer is established, in which the fuzzy PID control is used to maintain the temperature stability. Moreover, the electrical characteristics and temperature characteristics are simulated in different time scales. Finally, compared to the existing models, the proposed model is more accurate, and it indicates that the proposed model has better accuracy against the existing models.

Applicability assessment of equivalent circuit-thermal coupling models on LiFePO4 batteries operated under wide-temperature and high-rate pulse discharge conditions

In military scenario, high-power lithium iron phosphate (LFP) batteries are frequently used under wide-temperature and high-rate pulse discharge conditions. An accurate electro-thermal coupling model (ETCM) is crucial for the safe operations. Equivalent circuit-thermal coupling model (ECTCM), which combines equivalent circuit model (ECM) and lumped thermal model, is the most widely used type of ETCM in applications. However, the applicability of ECTCM under wide-temperature and high-rate pulse discharge conditions is not clear. To assess the applicability of ECTCM under these special conditions, this study establishes six typical ECTCMs and accurately identify their corresponding model parameters. Then, these models are tested under high-rate pulse discharge conditions from -40oC to 50oC. The results indicate that ECTCMs are effective for pulse discharge at ambient and high temperatures, but not suitable for low-temperature conditions below 0oC. When the temperature is below 0oC, the pulse discharge voltage of the batteries can not be accurately simulated by ECTCMs. This work provides guidance for electro-thermal coupling modeling under high-rate pulse discharge conditions, and also points out the direction for the development of high-precision ETCM capable of handling wide-temperature and high-rate pulse discharge in the future.

Core temperature estimation of lithium-ion battery based on numerical model fusion deep learning

Temperature has a critical impact on the lifespan and safety of lithium batteries. This paper proposes a battery core temperature estimation method based on numerical model fused with long short-term memory (LSTM) neural network. The proposed technique extracts features from the numerical model, estimates the volume-averaged temperature by electrochemical impedance spectroscopy (EIS), uses an LSTM neural network to learn thermodynamic parameters and complex calculations, which takes advantage of the strengths of each method, and achieves accurate core temperature estimation. The effects of state of charge (SOC) and temperature on EIS are explored, impedance properties are selected on the criteria of robustness and rapidity, and the estimation of the volume-averaged temperature is achieved using the imaginary part of the impedance. The proposed method can achieve root mean squared error (RMSE) of less than 0.28 °C and mean absolute error (MAE) of less than 0.23 °C. The proposed method has advantages of high estimation accuracy and does not require an electrothermal model. It also considers the effect of ambient temperature and has a good generalization capability.

Signature of electrothermal transport in 18 nm vertical junctionless gate-all-around nanowire field effect transistors

Abstract Addressing temperature hot-spots resulting from self-heating effects (SHE) poses a significant challenge in the design of emerging nanoscale transistors, such as vertical junctionless nanowire field-effect transistors (VNWFETs), due to reduced thermal conductivity. Consequently, electrothermal modeling becomes crucial for a comprehensive understanding of the underlying physical mechanisms governing carrier degradation and thermal conduction in these nanoscale devices. In this study, we present an enhanced drift-diffusion model coupled with nonlocal Guyer-Krumhansl (GK) equations to accurately capture carrier-phonon interactions and explore the electrothermal characteristics of gate-all-around (GAA) VNWFETs. Pulsed current-voltage (I–V) measurements are employed to investigate the performance of a state-of-the-art 18nm VNWFET technology. Furthermore, we report on the influences of both trapping and SHE under high-bias conditions for varying pulse widths. Our findings reveal that optimization of mobility degradation mechanisms allows for improved control over the physical behavior of carrier transport in these emerging technologies. Through careful consideration of these factors, it becomes possible to enhance the overall performance of GAA VNWFETs, particularly in mitigating temperature hot-spots and addressing challenges associated with self-heating effects.

Research on temperature rise performance of DC universal disconnect switch at high altitude

Abstract Low Voltage appliances are used more and more widely in high altitude areas, but the research on their temperature rise performance is still insufficient. Aiming at this problem, a high altitude temperature rise simulation model is established and verified by experiment, and the temperature rise performance is studied. Firstly, a DC universal isolation switch with a rated current of 1600A was used as the carrier to build an electro-thermal coupling calculation model of high-altitude temperature rise. Secondly, the temperature rise experiment of the isolation switch in high altitude environment was carried out to verify the effectiveness of the simulation model. Finally, the temperature fields of the DC universal isolation switch at different altitudes are simulated, and the change of convective heat transfer coefficient is calculated, and the temperature rise performance of the isolation switch at high altitudes is analyzed. With the increase of altitude, the temperature rise of the conductor is significantly higher than that of the insulation shell, and the heat dissipation capacity of the aluminum radiator decreases significantly at high altitude. The model and conclusion can provide reference for the use of low voltage electrical apparatus in high altitude environment.

Analytical Electro-Thermal Model and 3-D Thermal Resistance Network for SMD-Based Printed Circuit Board Power Converters

Analytical Electro-Thermal Model and 3-D Thermal Resistance Network for SMD-Based Printed Circuit Board Power Converters

An efficient two-stage heating strategy for embedded heat pipe system considering power and energy requirements from battery

The battery thermal management system (BTMS) embedded heat pipe system cannot only quickly heat the battery, but also improve its temperature consistency. In order to accurate predict the electro-thermal performance of the battery pack with such a BTMS, an electro-thermal model integrating heat pipe model is established for the pack. This model extends the traditional RC model to a dual-RC model at the cell level for predicting the cell anode potential, which clearly senses the status of lithium plating during the heating process. At the pack level, a distributed electro-thermal model combined with a thermal resistance network-based heat pipe model is proposed for the precise determination of the overall pack temperature. To further enhance the accurate monitoring of lithium plating status and control of the heating process for each cell within the pack, the control criterion is based on the terminal voltage rather than the state of charge (SOC). Additionally, an absolute SOC is defined to unify the SOC calculation across different low-temperature scenarios. With the assistance of the model frameworks above, a two-stage heating strategy is proposed for the BTMS, including the power requirement stage to ensure the heating rate and energy requirement for more available depth of discharge (DoD). In the stage of power requirement, air parameters are determined as Vair = 9 m/s and Tair = 60 °C, and the corresponding temperature rising rates are 1.05 °C/min under discharge and 1.08 °C/min under charge condition, respectively. Additionally, in order to ensure the high heating rate and 98 % available DoD, the second stage heats the pack with the air parameters of Vair = 5 m/s and Tair = 60 °C, with the temperature rising rates of 1.02°C/min under discharge and 1.74°C/min under charge condition. Unlike the air parameters used in the first phase, those in second phase also considers the energy conservation of the BTMS and temperature homogeneity inside the pack. The energy consumptions of BTMS are 0.323 kW·h for the discharging and 0.133 kW·h for the charging. Moreover, the tested temperature difference among cells in the whole heating process is no more than 1.3 °C.

Modeling the Influence of Thermal Phenomena in Inductors and Capacitors on the Characteristics of the SEPIC Converter

The paper presents the results of measurements and calculations of the SEPIC converter characteristics, taking into account thermal phenomena in semiconductor devices and passive elements. Compact electrothermal models of the MOSFET transistor, diode, capacitor, and inductor are proposed. Parasitic phenomena are also included in these models. The form of the developed models and the method of determining the values of their parameters are presented. The correctness of the formulated models was verified experimentally. Calculations and measurements of the characteristics of SEPIC converters containing inductors with ferromagnetic cores made of different materials were carried out. The obtained results of the investigations are discussed, and the range of applicability of the formulated models is described. It was shown that, at the considered operating conditions at an ambient temperature equal to 22 °C, the temperature of capacitors can exceed 40 °C, whereas the temperatures of inductors can even reach 50 °C.

Electrothermal Modeling of Photovoltaic Modules for the Detection of Hot-Spots Caused by Soiling

Solar energy plays a major role in the transition to renewable energy. To ensure that large-scale photovoltaic (PV) power plants operate at their full potential, their monitoring is essential. It is common practice to utilize drones equipped with infrared thermography (IRT) cameras to detect defects in modules, as the latter can lead to deviating thermal behavior. However, IRT images can also show temperature hot-spots caused by inhomogeneous soiling on the module’s surface. Hence, the method does not differentiate between defective and soiled modules, which may cause false identification and economic and resource loss when replacing soiled but intact modules. To avoid this, we propose to detect spatially inhomogeneous soiling losses and model temperature variations explained by soiling. The spatially resolved soiling information can be obtained, for example, using aerial images captured with ordinary RGB cameras during drone flights. This paper presents an electrothermal model that translates the spatially resolved soiling losses of PV modules into temperature maps. By comparing such temperature maps with IRT images, it can be determined whether the module is soiled or defective. The proposed solution consists of an electrical model and a thermal model which influence each other. The electrical model of Bishop is used which is based on the single-diode model and replicates the power output or consumption of each cell, whereas the thermal model calculates the individual cell temperatures. Both models consider the given soiling and weather conditions. The developed model is capable of calculating the module temperature for a variety of different weather conditions. Furthermore, the model is capable of predicting which soiling pattern can cause critical hot-spots.

An electro-thermal finite element method (FEM) model for local hotspot kinetics in Cu(In, Ga)Se2 thin-film solar modules

Partial shading can significantly impair the efficiency of thin-film solar cells. When exposed to partial shading, cells within the array tend to become reverse biased, leading to thermal runaway events and the emergence of hotspots. In Cu(In,Ga)Se2 (CIGS) solar cells such hotspots are also associated with so-called worm-like defects. Both theoretical and experimental studies have shown that in CIGS, a positive-feedback loop leads to instability and thermal runaway events. However, we observe an inconsistency between published simulation results and recently published experimental work. In a recent experimental study, it was shown that under certain conditions, a hotspot develops within 1ms, showing signs of melting of the CIGS in an area with a 5μm radius. However, in published simulation results, the time for such high temperatures to develop is in the order of seconds, a discrepancy of three orders of magnitude. In this work, we argue that this discrepancy is explained by the size of the seed defect, demonstrating that the origin of these experimentally observed, fast-developing hotspots is likely microscopic defects. To this end, we developed an electro-thermal finite element model, with very high temporal and spatial resolution. We demonstrate that, assuming a seed defect with a 10nm radius, we can reproduce the experimental results with respect to the size of the defect and the time it took to develop.

Electrothermal Averaged Model of a Half-Bridge DC–DC Converter Containing a Power Module

This article proposes an electrothermal averaged model of a half-bridge DC–DC converter containing a power module. This kind of model enables the computation of characteristics of DC–DC converters using DC analysis. The form of the elaborated model is presented. Both the electrical and thermal properties of the analyzed DC–DC converter are included in this model. This is the first averaged electrothermal model of a DC–DC converter which makes it possible to compute the junction temperature of all the semiconductor devices and magnetic components. The accuracy of the model was experimentally verified in a wide range of switching frequencies and output currents. Particularly, the influence of mutual thermal couplings between the transistors contained in the considered module on the characteristics of the converter and the junction temperature of the transistors is analyzed.

Power Semiconductor Junction Temperature and Lifetime Estimations: A Review

The lifetime of power electronic systems is the focus of both the academic and industrial worlds. Today, compact systems present high switching frequency and power dissipation density, causing high junction temperatures and strong thermal fluctuations that affect their performance and lifetime. This paper is a review of the existing techniques for the electro-thermal modelling of Mosfet and IGBT devices regarding lifetime estimation. The advantages and disadvantages of the methodologies used to achieve lifetime prediction are discussed, and their benefits are highlighted. All the factors required to predict power electronic device lifetime, including Mosfet and IGBT electrical models, the computation of power losses, thermal models, temperature measurement and management, lifetime models, mission profiles, cycle counting, and damage accumulation, are described and compared.

Comprehensive energy system planning with a focus on electric-thermal load correlations

Abstract Deepening research on electrothermal integrated energy systems has heightened the coupling between electric power and thermal systems. Accurate electrothermal load scenario modeling and thorough consideration of their interdependencies are crucial for effective planning and scheduling. The traditional method of generating scenarios cannot fully reflect the full complexity of the original power load. To address this, our paper introduces an enhanced clustering approach. Employing the Frank-Copula function to express the correlation between electric and thermal loads, we optimize the clustering and scene reduction sequence, yielding correlated typical electric and thermal load datasets. These refined load profiles serve as the foundation for comprehensive planning and analysis of the integrated energy system.

A non-destructive heating method for lithium-ion batteries at low temperatures

Low temperatures seriously affect the performance of lithium-ion batteries. This study proposes a non-destructive low-temperature bidirectional pulse current (BPC) heating method. Different from existing heating approaches, this method not only optimizes heating frequency and amplitude but also considers the optimization of the charge/discharge pulse duration ratio. To optimize the BPC heating strategy, a precise electro-thermal coupled model is established, and a neural network is employed to delineate the relationship among model parameters, temperature, and state of charge (SOC). Additionally, the interplay between the impedance of the graphite anode and that of the full cell is analyzed by constructing a three-electrode battery. Then, a novel full-cell-oriented lithium plating criterion is introduced. Finally, based on the constructed electro-thermal coupled model, lithium plating criterion, and terminal voltage constraint, a novel non-destructive BPC heating method is proposed. The results show a significant improvement in heating efficiency compared to conventional BPC heating. Especially for high SOCs, the heating power is increased at least 8 times. When the battery SOC is below 40 %, the average heating rate from −10 °C to 10 °C is 11.28 °C/min. Even at 90 % SOC, the heating rate remains at 2.88 °C/min. Furthermore, the capacity and impedance of a battery at 50 % SOC exhibit no significant changes after 60 heating cycles using the optimal BPC heating strategy at 100 Hz. These findings show that the optimized method proposed in this study has high heating efficiency and no damage to the battery.

On Fatigue Damage-Oriented Through-Life Optimization and Control of High-Power IGCT Converters in Wind Energy Systems

Integrated gate commutated thyristors (IGCTs) are critical components in high-voltage, high-current, and high-power conversion systems, particularly in offshore wind energy systems. However, the working environment of offshore wind energy conversion systems is extremely harsh. In this article, we propose an active damage control approach aiming at enhancing the reliability of the conversion system. By employing electro-thermal modeling for the equipment of the offshore wind energy conversion system, the junction temperature and fatigue damage of IGCT are simulated during the operation process. Using the improved model predictive current control (MPCC) method, active damage control effectively regulates the switching frequency of IGCT. IGCTs are symmetrically distributed on each leg of the converter, so the lifespan of the two IGCTs on each leg is also considered to be similar. This method balances the life of the IGCTs on the three legs of the converter and optimizes their utilization to the maximum extent. These measures effectively enhance the reliability of the conversion system and lower the operation and maintenance cost of high-power IGCT converters. The effectiveness of the proposed method is validated by co-simulation results by ANSYS and MATLAB/Simulink.

A novel framework for low-temperature fast charging of lithium-ion batteries without lithium plating

This paper proposes a novel framework for low-temperature fast charging of lithium-ion batteries (LIBs) without lithium plating. The framework includes three key components: modeling, constraints, and strategy design. In the modeling phase, a new electro-thermal coupled model is introduced, which integrates both frequency-domain and time-domain electro-thermal coupled models. They optimize the bidirectional pulsed current (BPC) heating parameters and charging current, respectively. Terminal voltage boundaries and lithium plating serve as constraints. Terminal voltage is confined within upper and lower limits to prevent battery overcharge and overdischarge. Lithium plating avoidance entails setting a minimum frequency for BPC heating. During charging, lithium plating is mitigated by maintaining negative potential above 0 V. To obtain calculated negative electrode potential, a three-electrode battery is employed to calibrate the electro-thermal coupled model parameters. Subsequently, a novel low-temperature fast charging strategy is devised. This strategy enables intelligent switching between BPC heating and charging, while also synergistically optimizing BPC heating parameters and charging current. The strategy also achieves optimization of both charging speed and energy consumption. Charging the battery SOC from 0.2 to 0.9 in 42 min at −10 °C, without triggering lithium plating, is feasible with this proposed strategy. Compared to strategies focusing solely on current amplitude optimization, heating followed by charging, and traditional methods, this heating strategy exhibits the highest charging speed.

Electro-thermal coupling modeling of energy storage station considering battery physical characteristics

Electro-thermal coupling modeling of energy storage station considering battery physical characteristics

Design of direct-drive permanent magnet synchronous motor for cryogenic valve

This paper presents a novel design of a low-speed and high-torque cryogenic direct-drive PMSM. A new simplified model is proposed to address the inaccuracy of the electro-thermal coupling model of the common cryogenic PMSM design. The coupling model focuses on the influence of the winding copper loss on the resistance, which improves the accuracy of calculating the temperature distribution and resistance value. Compared with FEM, the error of the calculation results is 4.8%. A new design method is proposed to address the problem that the common low-temperature PMSM designs lead to a rise in the copper loss. Measuring the improvement of the magnet performance in low temperature, the method reduces the turns of the coil, which significantly reduces the amount of copper loss. Compared with common methods, the amount of copper loss reduces 29.5%. Furthermore, a prototype is fabricated and tested, the results of which verifies the rationality of the design.

Electrothermal Modeling of Monolithically Integrated GaN-Based μLED Devices

Electrothermal Modeling of Monolithically Integrated GaN-Based μLED Devices

Joint Concern over Battery Health and Thermal Degradation in the Cruise Control of Intelligently Connected Electric Vehicles Using a Model-Assisted DRL Approach

Eco-driving aims to enhance vehicle efficiency by optimizing speed profiles and driving patterns. However, ensuring safe following distances during eco-driving can lead to excessive use of lithium-ion batteries (LIBs), causing accelerated battery wear and potential safety concerns. This study addresses this issue by proposing a novel, multi-physics-constrained cruise control strategy for intelligently connected electric vehicles (EVs) using deep reinforcement learning (DRL). Integrating a DRL framework with an electrothermal model to estimate unmeasurable states, this strategy simultaneously manages battery degradation and thermal safety while maintaining safe following distances. Results from hardware-in-the-loop simulation testing demonstrated that this approach reduced overall driving costs by 18.72%, decreased battery temperatures by 4 °C to 8 °C in high-temperature environments, and reduced state-of-health (SOH) degradation by up to 46.43%. These findings highlight the strategy’s superiority in convergence efficiency, battery thermal safety, and cost reduction compared to existing methods. This research contributes to the advancement of eco-driving practices, ensuring both vehicle efficiency and battery longevity.