Search Results (36)

Energy harvesting (EH) is a rapidly evolving domain that is primarily focused on capturing and converting ambient energy sources into more convenient and usable forms. These sources, which range from traditional renewable sources such as solar or wind power to thermal gradients and vibrations, present an alternative to typical power generation. The temptation to use energy harvesting systems is in their potential to power low-power devices, such as environment monitoring devices, without relying on conventional power grids or standard battery implementations. This improves the sustainability and self-sufficiency of IoT devices and reduces the environmental impact of conventional power systems. Applications of EH include wearable health monitors, wireless sensor networks, and remote structural sensors, where frequent battery replacement is impractical. However, these systems also face challenges such as intermittent energy availability, limited storage capacity, and low power density, which require innovative design approaches and efficient energy management. The paper provides a general overview of the subsystems present in the energy harvesting systems and a comprehensive overview of the energy transducer technologies used in energy harvesting systems. Full article

With the continuous expansion of data centers, their carbon emission has become a serious issue. A number of studies are committing to reduce the carbon emission of data centers. Carbon trading, carbon capture, and power-to-gas technologies are promising emission reduction techniques which are, however, seldom applied to data centers. To bridge this gap, we propose a carbon-neutral architecture for distributed data centers, where each data center consists of three subsystems, i.e., an energy subsystem for energy supply, thermal subsystem for data center cooling, and carbon subsystem for carbon trading. Then, we formulate the energy management problem as a Decentralized Partially Observable Markov Decision Process (Dec-POMDP) and develop a distributed solution framework using Multi-Agent Deep Deterministic Policy Gradient (MADDPG). Finally, simulations using real-world data show that a cost saving of 20.3% is provided. Full article

The multi-stack fuel cell system (MFCS) has advantages such as a wide range, long life, and high efficiency; however, its multiple heat sources impose higher requirements on the thermal management system, especially for different stacks. In order to control each stack temperature in an MFCS, the model predictive control (MPC) algorithm based on the backpropagation (BP) neural network is proposed. Firstly, dynamic characteristics have been obtained experimentally for selected PEMFC stacks of different powers. Based on experimental data, a parallel multi-stack fuel cell thermal management subsystem with different stack powers model is established and a system prediction model of the BP neural network is trained by applying the MFCS thermal management subsystem model simulation data. Then, the step response matrix of the system prediction model is obtained at typical operating conditions, and a dynamic matrix controller (DMC) is designed. Finally, a test operating condition is designed for simulation analysis. The results show that the DMC based on BP neural network can quickly and accurately control each stack temperature of the MFCS, while having the characteristics of small overshoot and short regulation time. Full article

Today’s systems are becoming increasingly complex due to the multitude of interactions between subsystems. This is also true for the electromechanical drivetrain and its physically interacting cooling system. In order to provide a virtual representation of such systems, including system architecture and product behaviour, model-based systems engineering (MBSE) introduces system models. System models are built using system elements and reoccurring models. MBSE, therefore, enhances the efficient development of complex systems by promoting model reuse in interdisciplinary architectural modelling. The reuse of models, such as calculation models, reduces redundancy, accelerates development iterations, and streamlines consistency. However, there is a lack of standardised and reusable model libraries to facilitate this reuse. In the approach in this paper, the reusability of those models is facilitated by the system elements, referred to as “solution elements”. MBSE system elements enable the structuring, reuse, and organization of models within model libraries. The identification of these system elements for heat-exchanging systems, however, remains an open challenge. Consequently, the aim of this paper is to develop a method for systematically identifying system elements in heat-exchanging systems, providing a formalized approach to reusing thermal models. The method focuses on functional and heat-transfer processes at the contact level referred to here as thermal contacts. The developed method is demonstrated through a case study of a thermal management system (TMS) of an electric truck. It is shown that a small set of recurring system elements can be used to represent a large number of individual thermal interactions, within TMS components and, therefore, streamline modelling efficiency significantly. Full article

The integration of more-electric technologies into aero-engines has revolutionized their multi-power architectures, substantially improving system maintainability and operational reliability. This advancement has established more-electric systems as a cornerstone of modern aerospace electrification research. Concurrently, liquid hydrogen (LH₂) emerges as a transformative solution for next-generation power generation systems, particularly in enabling the transition from 100 kW to megawatt-class propulsion systems. Beyond its superior energy density, LH₂ demonstrates dual functionality in thermal management: it serves as both an efficient coolant for power electronics (e.g., controllers) and a cryogenic source for superconducting motor applications. This study systematically investigates the electrification pathway for LH₂-fueled aero-engine multi-electric systems. First, we delineate the technical framework, elucidating its architectural characteristics and associated challenges. Subsequently, we conduct a comprehensive analysis of three critical subsystems including LH₂ storage and delivery systems, cryogenic cooling systems for superconducting motors, and Thermal management systems for high-power electronics. Finally, we synthesize current research progress and propose strategic directions to accelerate the development of LH₂-powered more-electric aero-engines, addressing both technical bottlenecks and future implementation scenarios. Full article

A novel approach for the robust integration of Functional Mock-up Units (FMUs) into Modelica is proposed, which maintains the computational robustness of the Modelica base model and minimizes the simulation time. Using a control-like approach, the base model is retained and mimics the FMU outputs. On the one hand, the controller can be interpreted as a numerical tool designed to provide a correct steady-state solution and minimize transient errors. On the other hand, the additional low-pass filter can also be used to represent the inertia of a system. The application of this easy-to-implement approach is demonstrated for a digital twin of the overall thermal management system (TMS) of a future hybrid electrical regional aircraft, which aims at identifying critical conditions and flight cases in advance of hardware tests and virtually demonstrating the behavior of the TMS during complete flight missions. To this end, a base model of the TMS is first set up using the Thermofluid Stream Modelica Library, which focuses on computational robustness, in order to define the boundaries and interfaces of the different subsystems. Then, the subsystems are gradually replaced by validated FMUs to enable virtual demonstrations, where the novel control-like approach proves to be crucial. Full article

To reduce dependence on fossil fuels, cope with the growing energy demand, and reduce greenhouse gas emissions, this paper innovatively designs a novel integrated energy system integrating anaerobic digestion of animal manure, fuel cell technology, gas turbine, and tire pyrolysis. The system maximizes the energy potential of biogas while synergistically treating waste tires, improving waste management’s flexibility, efficiency, and economic viability through multiple outputs such as electricity and by-products, subsystem synergies, equipment sharing, and economies of scale. Thermodynamic performance and economic feasibility are analyzed using Aspen Plus V14 simulation modeling, ensuring the system’s technical and economic viability. In this study, the simulation model of the system is established, and the techno-economic benefits of the system are analyzed. The simulation results show that the net electric power output of the system is 444.79 kW. Combined with the contribution of pyrolysis products, the system’s total efficiency reaches 70.88%. In only 4.79 years, the initial investment can be recovered, and in its 25-year service life, the system has realized a profit of 2,939,130 USD. The system realizes the energy and quality matching between different thermal processes through indirect collaborative treatment of different solid wastes, improves the conversion efficiency of biogas energy, co-treats waste tires, and reduces environmental pollution. Full article

The temperature field of an electronic optical instrument can affect the image quality realised by the instrument and, in extreme cases, lead to damage. This is particularly true for instruments operating in harsh environments such as space. The hyperspectral imaging optical instrument (OI) designed for the Intuition-1 (I-1) nanosatellite, currently in low Earth orbit, has been subjected to a numerical analysis of its thermal state under different operating conditions, and some preliminary experimental tests have been carried out to determine the maximum operating temperatures of its sensitive components and the risk of thermal damage. This work was part of a testing campaign prior to the deployment of Intuition-1. Three operational cases were analysed: (1) behaviour in the Earth’s atmospheric conditions when the OI is pointed at the Sun, (2) the end of the de-tumbling process in orbit with the Sun crossing the diagonal of the OI’s field of view, and (3) identification of the maximum possible number of consecutive Earth imaging cycles in orbit. The ultimate goal of this work was to validate the numerical approach used for these cases and to deepen the understanding of the thermal safety of the CMOS image sensor placed in the OI. For these cases, transient thermal field analyses were performed for the OI to determine the temperature distribution and its variability in the most thermally sensitive CMOS image sensor. The components of the OI and its overall structure were experimentally tested, and the results were used to validate the numerical models. The study showed that the built-in temperature sensor does not always reflect the actual CMOS temperature, and in some extreme cases the current temperature monitoring does not ensure its safe operation. Full article

The automotive industry is experiencing a surge in system complexity driven by the ever-growing number of interacting components, subsystems, and control systems. This complexity is further amplified by the expanding range of component options available to original equipment manufacturers (OEMs). OEMs work in parallel on more than one vehicle model, with multiple vehicle variants for each vehicle model. With the increasing number of vehicle variants needed to cater to diverse regional needs, development complexity escalates. To address this challenge, modern techniques like Model-Based Systems Engineering (MBSE), digitalization, and Artificial Intelligence (AI) are becoming essential tools. These advancements can streamline concept development, optimize thermal and HVAC system design across variants, and accelerate the time-to-market for next-generation EVs. The development of battery electric vehicles (BEVs) needs a strong focus on thermal management systems (TMSs) and heating, ventilation, and air conditioning (HVAC) systems. These systems play a critical role in maintaining optimal battery temperature, maximizing range and efficiency, and ensuring passenger comfort. This article proposes a digital prototype (DP) and AI-based methodology to specify BEV thermal system and HVAC system components in the concept phase. This methodology uses system and variant thinking in combination with digital prototype (DP) and AI to verify BEV thermal system architecture component specifications for future variants without extensive simulation. A BEV cabin cooling requirement of 22 °C to be achieved within 1800s at a high ambient temperature (45 °C) is required, and its verification is used to prove this methodology. Full article

In some scenarios, electric heavy-duty trucks with battery swapping mode (ETBSm) are more cost-effective than battery charging mode. The viability of battery swapping stations is contingent upon the operational requirements and range capabilities of the ETBSm. Low temperatures have the effect of reducing the range of the ETBSm, thereby creating difficulties for battery swapping. This article proposes the use of motor waste heat recovery (MWHR) to heat batteries, which would improve range. A number of subsystem models have been established, including the ETBSm, battery, motor, and thermal management system (TMS). The calibration of battery temperature and motor efficiency is achieved with a model error of less than 5%. Comparison of performance, such as temperature, energy consumption, and range, when using only positive temperature coefficient (PTC) heating and when using both PTC heating and motor waste heat. The results indicate a 15% increase in the rate of rise in battery temperature and a 10.64 kW·h reduction in energy consumption under Chinese heavy-duty vehicle commercial vehicle test cycle (CHTC) conditions. Then, the motor waste heat percentage, energy consumption, and range are analyzed at different ambient temperatures. At an ambient temperature of −20 °C, −10 °C, and 0 °C, the percentage of the motor waste heat is 32.1%, 35%, and 40.5%; when 75% of the state of charge (SOC) is consumed, the range is improved by 6.55%, 4.37%, and 4.49%. Additionally, the effect of the PTC heater on temperature characteristics and power consumption is investigated by changing the target temperature of the coolant at the battery inlet. In accordance with the stipulated conditions of an ambient temperature of −20 °C and a target coolant temperature of 40 °C at the battery inlet, the simulation results indicated a battery temperature rise rate of 0.85 °C/min, accompanied by a PTC power consumption of 15.6 kW·h. This study demonstrates that as the ambient temperature increases, the utilization of motor waste heat becomes more effective in reducing PTC heating power consumption. At the lowest ambient temperature tested, the greatest improvement in driving range is observed. It is important to note that while an increase in the target heating temperature of the PTC helps to raise the battery temperature more rapidly, this is accompanied by a higher energy consumption. This article provides a reference for the ETBSm with MWHR. Full article

This paper presents an innovative thermally coupled system architecture with a parallel coolant-heated metal hydride tank (MHT) designed to satisfy the hydrogen supply requirements of proton exchange membrane fuel cell s(PEMFCs). This design solves a problem by revolutionising the cold start capability of PEMFCs at low temperatures. During the design process, LaNi₅ was selected as the hydrogen storage material, with thermodynamic and kinetic properties matching the PEMFC operating conditions. Afterwards, the MHT and thermal management subsystem were customised to integrate with the 70 kW PEMFC system to ensure optimal performance. Given the limitations of conventional high-pressure gaseous hydrogen storage for cold starting, this paper provides insights into the challenges faced by the PEMFC-MH system and proposes an innovative cold start methodology that combines internal self-heating and externally assisted preheating techniques, aiming to optimise cold start time, energy consumption, and hydrogen utilisation. The results show that the PEMFC-MH system utilises the heat generated during hydrogen absorption by the MHT to preheat the PEMFC stack, and the cold start time is only 101 s, which is 59.3% shorter compared to that of the conventional method. Meanwhile, the cold start energy consumption is reduced by 62.4%, achieving a significant improvement in energy efficiency. In conclusion, this paper presents a PEMFC-MH system design that achieves significant progress in terms of time saving, energy consumption, and hydrogen utilisation. Full article

A multi-stack fuel cell system (MFCS) is a promising solution for high-power PEM fuel cell applications. This paper proposes an optimized stack allocation approach for power allocation, considering economy and dynamics to establish integrated subsystems with added functional components. The results show that an MFCS with target powers of 20 kW, 70 kW, and 120 kW satisfies lifetime and efficiency factors. The common rail buffer at the air supply subsystem inlet stabilizes pressure, buffers, and diverts. By adjusting the volume of the common rail buffer, it is possible to reduce the maximum instantaneous power and consumption of the air compressor. The integrated hydrogen supply subsystem improves hydrogen utilization and reduces parasitic power consumption. However, the integrated thermal subsystem does not have the advantages of integrated gas supply subsystems, and its thermal management performance is worse than that of a distributed thermal subsystem. This MFCS provides a solution for high-power non-average distribution PEM fuel cell systems. Full article

Solid Oxide Fuel Cells (SOFCs) are emerging as a leading solution in sustainable power generation, boasting high power-to-energy density and minimal emissions. With efficiencies potentially exceeding 60% for electricity generation alone and up to 85% when in cogeneration applications, SOFCs significantly outperform traditional combustion-based technologies, which typically achieve efficiencies of around 35–40%. Operating effectively at elevated temperatures (600 °C to 1000 °C), SOFCs not only offer superior efficiency but also generate high-grade waste heat, making them ideal for cogeneration applications. However, these high operational temperatures pose significant thermal management challenges, necessitating innovative solutions to maintain system stability and longevity. This review aims to address these challenges by offering an exhaustive analysis of the latest advancements in SOFC thermal management. We begin by contextualizing the significance of thermal management in SOFC performance, focusing on its role in enhancing operational stability and minimizing thermal stresses. The core of this review delves into various thermal management subsystems such as afterburners, heat exchangers, and advanced thermal regulation strategies. A comprehensive examination of the recent literature is presented, highlighting innovations in subsystem design, fuel management, flow channel configuration, heat pipe integration, and efficient waste heat recovery techniques. In conclusion, we provide a forward-looking perspective on the state of research in SOFC thermal management, identifying potential avenues for future advancements and their implications for the broader field of sustainable energy technologies. Full article

In the present work, the operating results from an innovative, renewable, energy-based space-heating and domestic hot water (DHW) system are shown. The system used solar thermal energy as its primary source and was assisted by a shallow geothermal application in order to accommodate the space-heating and DHW needs of a domestic building in Austria. The system incorporated phase-change materials (PCMs) in specially designed containers to function as heat-storage modules and provide an energy storage capability for both the space-heating and DHW subsystems. This system was designed, implemented, and tested under real operating conditions in a building for a period of one year. The operating and energy results for the system are demonstrated in this work. The system was compared with a conventional one, and a reduction in the primary energy consumption equal to 84.3% was achieved. The maintenance and operating costs of the system were reduced by 79.7% compared to the conventional system, thus significantly contributing to the NZEB target of the building. The newly proposed system, although presenting an increased operating complexity, utilizes an innovative self-learning control system that manages all of its operations. The combination of a solar thermal energy source with thermal energy storage increases the use of renewable energy by extending the capacity of the system beyond the solar hours and using excess solar energy for space-heating needs. The thermal energy storage unit also increases the energy and economic efficiency of the geothermal heat pump by operating it during the hours of a reduced electricity tariff and using the stored energy during hours of a high electricity demand. The cost for the installation of such a system is higher than a conventional one, but due to the significantly decreased operating costs, the pay-back period was calculated to be 8.7 years. Full article

The thermal management system (TMS) for aircraft fuel is a critical component of integrated TMSs in aircraft. As such, its optimal design is necessary to ensure the efficient completion of flight missions. This study presents the model building of a numerical simulation model for the fuel TMS, with the objective of minimizing fuel return flow. Sensitivity analysis was performed using variance analysis. The genetic algorithm was utilized for the optimization of the model building, taking into consideration the system’s geometric structure and performance parameters, which include the pipe length, the ram air-fuel HX’s efficiency, and the ram air’s volume flow rate in the ram air cooling subsystem, as design variables. The optimization solution for system design variables yielded a design scheme with the highest working efficiency for the fuel TMS. In this paper, the genetic algorithm in AMEsim software is adopted, which can also effectively optimize the design parameters and achieve the optimization objective. Compared with the original TMS structure, the heat dissipation capacity of the fuel TMS is improved and reduced the return fuel flow by 67.4% after the optimization of system structure parameters. Full article