Browse Topic: Sustainable development

Items (1,005)
Waste heat recovery has become a critical research area in the quest for improving automotive energy efficiency. Internal combustion engines lose a large amount of their energy as heat through exhaust gases. Thermoelectric generation technology presents a promising approach to capturing and converting this waste heat into useful electrical energy. In this work, a theoretical study on the application of thermoelectric generators (TEGs) for battery charging by converting waste heat from internal combustion engine exhaust into usable electrical energy is proposed. A prototype system incorporating TEG modules was designed focusing on the minimization of back pressure; flow of exhaust gas is ensured through a circular internal cross-section. Thermal simulations were performed using Ansys Workbench, and computational fluid dynamics (CFD) analysis was conducted to quantify the back pressure. Two heat exchanger materials, aluminum and copper alloys, were evaluated for their heat transfer performance. The results indicate that copper achieves superior heat transfer, with hot-side temperatures approximately 8.6% to 23.9% higher than aluminum. However, aluminum remains a viable alternative due to its lightweight and cost-effectiveness. With the cold side being maintained at 91°C to simulate realistic engine coolant conditions, the experiment shows that a series-parallel configuration of six TEG modules (three in series × two in parallel) can effectively generate the necessary voltage (13–15 V) and current (3.5–7 A) to charge a 12-V automotive battery. CFD analysis confirmed that the circular internal geometry produces low back pressure, with pressure drops of 28 Pa, 63 Pa, and 168 Pa for inlet velocities of 25 m/s, 40 m/s, and 70 m/s, respectively. This research underscores the potential of TEG-based battery charging systems in enhancing energy efficiency, though further development is required for real-world automotive integration. Future work could focus on on-vehicle testing, optimizing thermoelectric materials, and integrating advanced cooling mechanisms and maximum power point tracking controllers to improve overall system viability.
Satheesh, Amal, Satheesh, Akul, Pillai, Ashwin S., Mahisankar, J.S., Sreejith, B.J.
Crowdshipping has recently attracted significant attention as a potentially sustainable solution for urban logistics, as it leverages individuals’ underutilized travel capacity to perform last-mile deliveries. While existing research has extensively examined crowdshipper participation through motivational patterns, considerably less attention has been devoted to the governance and policy implications emerging from crowdshipper behavior. This represents a critical gap, particularly in the context of sustainable urban mobility, where logistics innovations are often implicitly assumed to generate positive externalities without adequate regulatory design. This paper addresses this gap by translating crowdshipper motivational evidence into policy-relevant insights for sustainable urban mobility planning. The analysis is based on data collected through a structured questionnaire administered to potential and active crowdshippers. The survey collected information on socio-demographic characteristics, mobility habits, motivations, risk perception, trust, and willingness to participate under alternative crowdshipping conditions. While such conditions are commonly used to estimate participation patterns, this study reinterprets them through a governance-oriented lens to explore trade-offs between economic incentives, environmental motivations, and mobility-related impacts. Using a governance-oriented interpretation of survey data, the analysis highlights how different incentive structures activate heterogeneous crowdshipper participation patterns, with distinct mobility impacts. Results show that participation driven by strong economic incentives and operational flexibility may encourage additional vehicle-kilometers traveled, while participation embedded within routine trips and influenced by environmental considerations tends to operate within more limited spatial and temporal constraints. Taken together, these findings indicate that crowdshipping outcomes are not inherently aligned with sustainable urban mobility objectives, but critically depend on incentive design and regulatory integration within Sustainable Urban Mobility Plans (SUMPs).
Comi, Antonio, Idone, Ippolita
With continuous advancements in load-side resources such as distributed photovoltaic systems, electric vehicles, and virtual power plants, the low-carbon and sustainable development attributes of power systems have been significantly enhanced. Meanwhile, the coupling intensity between sustainable power systems and meteorological conditions has been further consolidated. Considerable impacts are exerted by weather variations, particularly extreme weather events, on the dispatching and operation of sustainable power systems. Accurate load forecasting is critical for enabling sustainable power systems operators to optimize power generation strategy, ensuring supply stability and resilience against extreme weather-induced disruptions. However, the intrinsic non-stationarity and volatility of extreme weather events present significant challenges to conventional forecasting approaches. Herein, we introduce a hybrid algorithm integrating Newton–Raphson-based optimizer (NRBO) with extreme gradient boosting (XGBoost) to enhance short-term load predictions under such conditions. The model uses optimally selected meteorological and load features as inputs, while NRBO systematically tunes XGBoost’s hyper-parameters to maximize performance. Evaluated on an Irish dataset, the proposed framework is quantitatively compared against five baseline models, including traditional decision trees and neural networks. The case studies show that the mean absolute percentage error (MAPE) of the proposed model is 2.57%, which is the lowest among these decision tree and neural network algorithms.
Wang, Yi, Zhou, Jian, Wu, Gang, Ma, Tiannan, Ma, Ruiguang, He, Chuan, Zhu, Huixian
Planting concrete has drawn much attention due to its great potential in highway slope protection and ecological restoration. However, its practical application has been limited as its highly alkaline environment imposes severe restrictions on the germination of plant seeds and the growth of seedlings. To address this key issue, this paper conducted a systematic study on planting concrete preparation and alkali reduction technology. First, planting concrete samples that meet the basic physical and mechanical property requirements are prepared by optimizing the raw material ratio, mixing, molding, and curing processes. On this basis, the post-molding concrete samples are soaked in calcium superphosphate solution, so that the phosphate ions in it can have chemical reactions with the free calcium hydroxide in the concrete to make insoluble calcium phosphate salts, thus realizing chemical alkali reduction.
Liu, Ying, Yang, Wanting, Ma, Lijie
The scheme of photocatalysis of water, a way of hydrogen generation as a clean, high-efficiency fuel source for aircraft and long-range transport systems has received considerable interest. The development of the covalent organic framework (COF) - derived materials for hydrogen evolution reaction (HER) has since become a research highlight. Compared to traditional methods, photocatalytic hydrogen evolution systems based on COFs can provide ways of generating hydrogen gas without depending upon noble metal catalysts, thereby enhancing the sustainability and prospects of this technology for future aerospace energy applications.In this work, two covalent organic frameworks (COFs) with distinct linkages—a vinylene-linked COF A (via Knoevenagel condensation) and an imine-linked COF B (via Schiff-base reaction)—were designed and synthesized to compare their performance in the photocatalystic hydrogen evolution reaction (HER). Structural and electrochemical characterizations confirmed that, despite lower crystallinity and specific surface area due to pore blockage, COF A exhibited a suitable band structure for photocatalysis and achieved an HER rate of 56 μmol h^–1 g^–1 under simulated sunlight. In contrast, COF B was ineffective. This study experimentally validates the superior photocatalytic potential of vinylene-linked COFs over imine-linked counterparts for HER, highlighting their potential as non-noble-metal catalysts for aerospace and transport-oriented fuel generation.
Cao, Yijie, Luo, Xin
Steady advancement is observed in global research on eco-friendly and sustainable transportation. Rapid technological evolution of hybrid electric vehicles (HEVs) is documented. Lower overall noise output and more compact structures are achieved in HEV engines relative to conventional internal combustion engines. The perceptibility of harmonic impulsive sounds is significantly enhanced by these design characteristics. A close correlation is observed between these acoustic phenomena and negative human auditory perceptions. These events are treated as a core focus for HEV noise, vibration, and harshness optimization. Accurate quantification of harmonic impulsive sounds is not achieved by conventional objective indicators. A favorable balance between reliability and accuracy is not established by existing subjective prediction models. Practical engineering applications of these methods are severely restricted. A novel objective quantification method for harmonic impulsive sounds is proposed in this study. The method is established based on time–frequency masking theory and tonal strength. Bench tests in a semi-anechoic chamber and subjective evaluation experiments with standardized rating scales are performed for data collection. Collected sound signals are decomposed through an integrated approach of wavelet transform and variational mode decomposition. Targeted feature extraction is completed for harmonic impulsive sounds. A quantitative index incorporating human auditory temporal and frequency masking effects is developed. The proposed index exhibits a significantly stronger correlation with subjective evaluation results than traditional objective metrics, confirming its superior ability to reflect actual perceived sound quality. An interval prediction model for sound quality evaluation is established based on support vector machines and kernel density estimation. Traditional objective metrics and the proposed index are introduced as key input parameters. Effective and reliable prediction of HEV engine noise subjective satisfaction is achieved by the model.
Lin, Xu, Liang, Xingyu, Shi, Zhiyuan
Cashew nut shell oil–based biodiesel (BD) is an environmentally friendly and sustainable alternative energy source that can help decrease the depletion of fossil fuels and reduce environmental pollution. In this research, the BD extracted from cashew nut shell was enriched with green-synthesized nanoparticles with various blends and evaluated for its performance. The BD20A blend recorded the best thermal efficiency of the brake, 29.5%, which was a boost of about 20.4% over diesel when using a medium load of 2.7 kW. Furthermore, the decrease in brake-specific fuel consumption was 36.2%, and exhaust gas temperature improved by 26.1% due to enhanced combustion, indicating better combustion and utilization of heat. The BD10A and BD20A recorded a considerable decrease in emissions compared to diesel under full-load conditions, with carbon monoxide and hydrocarbons reducing by 35.7% and 33.3%, respectively, and a moderate increase of nitrogen oxides. Among the multi-objective optimization approaches, the Jaya algorithm exhibited the fastest convergence rate and identified the optimum operating condition that achieved the best trade-off between engine performance and exhaust emissions. BD blends, particularly BD20A, provide greater thermal performance and better combustion behavior as well as lower exhaust emissions, making them viable as green alternatives to the traditional diesel fuel.
Victor Soosai Irudayaraj, S., Thanigaivelan, V., Brucely, Y., Lenin, N.
SAE TOMORROW TODAY - SAE JA1016: Scaling the Future of UAVs with Battery Interoperability135798/6/2026
From drone delivery to public safety and defense, the next generation of uncrewed aerial vehicles (UAVs) will be powered not just by better batteries, but by better battery standards. Listen in as we sit down with Jeff Yambrick, Chair of the SAE Battery Cell Size Standardization Committee, and Lisa King, Director of Advanced Battery Strategy at Leap Manufacturing, to discuss SAE JA1016 -- a new standard designed to simplify battery integration, accelerate commercialization, and strengthen the UAV supply chain. During this conversation, you'll learn why common battery formats are essential for reducing development costs and creating greater interoperability across commercial and defense applications. We also explore the importance of domestic battery manufacturing, supply chain resilience, and how standardization can accelerate innovation without limiting future battery technologies. To join the SAE Battery Cell Size Standardization Committee, email Dante Rahdar at Dante.Rahdar@sae.org. We'd love to hear from you! Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today--a podcast where we discuss emerging technology and trends in mobility with the leaders, innovators and strategists making it all happen--and give us a review on your preferred podcasting platform. Follow SAE on LinkedIn, Instagram, Facebook, X, and YouTube. Follow host Grayson Brulte on LinkedIn, X, and Instagram.
Patterson, Lori
In the race to combat climate change, scientists are developing technologies to turn carbon dioxide (CO2) into valuable fuels and chemicals. These innovations help curb greenhouse gases while providing a low-carbon fuel to power our future. As the U.S. shifts to a low-carbon economy, we need environmentally friendly fuels to power vehicles that are hard to electrify, like planes, ships and trains. Scientists are developing the technology to convert CO2 to fuel. However, this conversion requires a lot of energy and water.
Led by Dr. Marina Freitag, a research group from the School of Natural and Environmental Sciences created dye-sensitized photovoltaic cells based on a copper (II/I) electrolyte, achieving an unprecedented power conversion efficiency of 38 percent and 1.0V open-circuit voltage at 1,000 lux (fluorescent lamp). The cells are non-toxic and environmentally friendly — setting a new standard for sustainable energy sources in ambient environments.
This study carefully designed and successfully developed a mechanical voltage stabilizing control device. The device uses silicone oil as the key component material of the liquid spring and 1Cr13 as the main material of the pressure control unit, enhancing its high-pressure resistance (up to 35 MPa), oxidation resistance, and acid-alkali corrosion resistance. By optimizing the transmission mechanism and simplifying the pressure regulation module, the device achieves a pressure regulation range of 0.1–21 MPa with an accuracy of ±0.01 MPa, significantly broader and more precise than traditional devices. To address manufacturing challenges, advanced CNC machine tools, ceramic cutting tools, and optimized heat treatment processes (e.g., quenching and tempering) were adopted, ensuring component machining accuracy within ±0.02 mm. Field applications in 13 oil wells demonstrated a 15.6% increase in daily oil production (from 25.5 t/d to 29.5 t/d) and a 17.9% increase in daily gas production (from 2800 m^3/d to 3300 m^3/d), with stable casing pressure control at 5.3 MPa. The device has created 1.225 million yuan in economic benefits while eliminating safety hazards, providing critical technical support for efficient and environmentally friendly oil and gas production.
Wang, Gang, Liu, Cuicui, Tong, Deshui, Cao, Jian, Mu, Taiji, Han, Baidong
With the advance of high-end manufacturing and the rise of green design, lightweight structures have become a central concern in aerospace. Topology optimization offers a principled route to shed mass while preserving performance, yet most additive manufacturing (AM) studies still emphasize process tuning and new materials rather than structural layouts constrained by AM realities. This work targets a representative wing rib from a specific unmanned aerial vehicle (UAV) and formulates a multi-objective topology optimization that explicitly embeds AM constraints. Using the Solid Isotropic Material with Penalization (SIMP) variable-density framework, we couple static stiffness and strength measures with modal objectives so that the optimized rib not only resists deformation and limits stress but also improves the first three natural frequencies, thereby mitigating adverse vibration interactions at the wing level. A compromise-programming strategy balances these competing objectives under volume and manufacturability requirements, including AM-driven minimum feature scales and related geometric restrictions. Finite-element analyses are used throughout the loop to evaluate displacement, von Mises stress, and eigenfrequencies, ensuring that the emerging material distribution is both efficient and physically meaningful. The resulting topology exhibits clearer load paths and smoother stress flow, reduces peak displacements, and delivers a marked rise in the first three natural frequencies. Overall mass is lowered by approximately 55% while meeting all imposed constraints, achieving the dual aims of structural optimization and lightweighting. The study demonstrates that integrating AM constraints directly into the optimization stage yields designs that are performance-robust and fabrication-ready, and it provides a reusable workflow for thin-walled aerospace components such as wing ribs where stiffness, strength, and vibration behavior must be jointly considered.
Zhao, Fei, Zhang, Heran, Li, Xiaoting, Shi, Bowen, Kong, Xiangwei
In conventional braking systems, the kinetic energy of a vehicle is predominantly converted into heat through friction, a thermodynamically inefficient process. This not only causes progressive wear of components but also leads to the release of various materials, including heavy metals and organic compounds. With increasing concern over non-exhaust emissions, the search for innovative solutions becomes imperative. In electrified vehicles (xEVs), regenerative braking emerges as a strategic technology, converting kinetic energy into electrical energy to recharge the battery and extend range. This process not only enhances the vehicle's energy efficiency but also results in reduced frequency and intensity of mechanical brake usage. Consequently, there is a direct reduction in the wear of friction braking components, which translates into a significant mitigation of particulate matter emissions associated with this wear. The optimization of these systems occurs through Cooperative Regenerative Braking (CRB), which intelligently integrates with hydraulic braking. The primary challenge lies in managing the transition between modes to recover maximum energy without compromising safety and driver comfort. This technical paper explores how CRB employs 'torque blending' via advanced ECUs and software to adjust in real-time the proportion of each braking type, aiming for maximum energy recovery in diverse driving scenarios. To verify the effectiveness of this system, practical tests were conducted on a vehicle. The results obtained from these tests were conclusive, demonstrating significant gains in energy efficiency, with an increased battery recharging capacity during decelerations, optimized by the braking system. This improvement in efficiency directly impacts the reduction in the use of the conventional friction brake system and, consequently, a sharp decrease in particulate matter emissions. In this context, the intelligent and cooperative management of regenerative braking is a strategic and fundamental component for building a more sustainable future in vehicular mobility.
Batagini, Emerson, Romão, Bruno
Amid growing society concerns about environmental sustainability, fuel consumption has become a key factor in mitigating greenhouse gas emissions. As a result, modern vehicle design increasingly prioritizes aerodynamic drag reduction. However, aerodynamic enhancements can significantly affect brake cooling, since airflow distribution plays a crucial role in braking performance. This study explores the interplay between underbody aerodynamic features and brake cooling efficiency in production vehicles. Three body styles—compact sedan, midsize SUV, and minivan—were evaluated to determine how varying aerodynamic configurations influence airflow around the wheel assemblies. The findings highlight critical trade-offs between aerodynamic optimization and thermal management, offering valuable insights for achieving balanced vehicle development strategies.
Batista, Lorena, Motta, Daniel, Seren, Ericson, Bergel, André, Sarmento, Alisson, Terra, Rafael
Aerodynamicists around the globe are developing mechanisms and structures inspired by nature that enable variable camber morphing (VCM) for aerodynamic surfaces. The implementation of the VCM mechanism in an airplane wing enhances the performance and stability during various flight segments. The present review article is focused mainly on the up-to-date VCM methods in a qualitative as well as quantitative approach that are specific to Aircraft/unmanned aerial vehicle (UAV) wing configurations. Initial literature discussions are confined to the conventional mechanisms that enable VCM in different aircraft configurations and the added aerodynamic advantages such as lift enhancement, drag reduction, boundary layer separation, and flow control. However, those designs need either external shape optimization or internal structural refinements to ensure the factor of safety (FoS). The modern aviation industry is also focused on bioinspired technology because of the adaptive flying capabilities and stall-delay characteristics. Therefore, a review of bioinspired VCM methods that are assessed based on the aerodynamic potentials is sequentially organized in the article. Additionally, considerations are motivated by the application of various compliant structural patterns for VCM in the aircraft industry. The discussion indicates the prospective benefits of morphing toward the future of the Green Aviation industry.
Manjunath, S. V., Jini Raj, R.
Despite advances in CFD, wind tunnel testing remains indispensable for aerodynamic validation, correlation, and homologation. Increasing configuration complexity, shortened development cycles, and stringent result robustness and documentation requirements demand a shift from isolated facilities to integrated, data-driven ecosystems within the overall development and company-wide test processes. We present a software-centric approach integrating wind tunnel operations into a strategic element of the Digital Thread. By orchestrating test planning, execution, data acquisition, and documentation within a unified framework, experimental data becomes reusable across projects and traceable for compliance and homologation. The interaction between CFD and physical testing is important. Such approach systematically improves simulation models with wind tunnel tests. And CFD results guide efficient test matrix definition. Extended measurement methodologies include automated actuation of active aerodynamic components in test sequences, while BEVs introduce further aerodynamic and thermal aspects for range and efficiency. Thus, extended and automated test definition down to the step-level of test sequences is introduced. Within such integrated environment, AI can be a supporting engineering tool to enhance testing. AI-based methods can assist in identifying relevant test points within complex parameter spaces and in correlating experimental and simulated results, assisting but not replacing established engineering judgment. Also, for the operating department, analyzing process data for maintenance predictions and efficiency optimizations can be assisted by AI-based methods and supporting AI-agents. The approach boosts efficiency by reducing test effort and tedious manual tasks, leading to shorter development cycles, supporting improved time-to-market. Structured workflows and standardized data handling enhance data quality, improve comparability of results, and ensure robust documentation for reliable audit trails. By combining physical testing, simulation, and intelligent processing, the wind tunnel becomes a reproducible, innovation-enabling element in modern product development, positioning software as the backbone of efficient, future-proof aerodynamic testing.
Jacob, Jan D.
Electrification using battery systems is one of the most relevant solutions regarding ecological challenges within multiple application cases such as mobility, power tools or stationary power supply. Nonetheless besides recent achievements in some cases battery systems are still lacking behind operational requirements compared to conventional propulsion systems, therefore limiting the potential of electrification. Especially when purpose design possibilities are limited. Besides improving properties of cell materials, better usage of the available installation space offers potential for optimization of the battery system. The development of battery systems is complex, as it involves multiple system levels and domains, along with a wide range of design options and architectures. Battery cells that can be manufactured in flexible formats enable possibilities to make more efficient use of available installation spaces. At the same time, these additional degrees of freedom increase design complexity and significantly expand the solution space. For example, numerous options for sizing and positioning of the cells are available that are interacting with the cooling system and housing design. Also, additional challenges regarding electrical and thermal load distribution occur using format flexible cells. To support developers, new methods and tools are necessary to handle this complexity. Therefore, the authors present a methodology that includes an installation space optimization using format-flexibly produced pouch cells that generates different possible layouts of cells and modules, an approach for electrical and thermal modeling of the battery system that is applicable for varying cell arrangements as well as possibilities for a fast criteria-based evaluation of different cell and module arrangements that can be used for an overall optimization of the battery system. Finally, the authors are discussing benefits and disadvantages of the presented methodology as well as the usage of format flexibly produced pouch cells using an illustrative case study.
Müller-Welt, Philip, Bause, Katharina, Spohn, Hannes, Albers, Albert
This paper presents Stochastic Gradient Pulse Adaptation (SGPA), a real-time adaptive pulse-charging system for rechargeable electrochemical batteries that dynamically adjusts charging aggressiveness based on the battery's internal response, as opposed to predetermined CC–CV or fixed pulse profiles. SGPA is different from traditional charging methods that use static current de-rating and conservative voltage limits. Instead, SGPA uses gradient-based feedback from terminal voltage behaviour, temperature changes, internal resistance changes, and state of charge to continuously adapt pulse amplitude and duty cycle. This algorithm boosts the charging intensity when the electrochemical circumstances are good. It lowers the pulses slowly when signs of thermal or impedance-related stress show up. Simulation-based proof-of-concept experiments on a heavy-duty multi-battery system show that charging time is less than with multi-CCCV charging, while still keeping the current distribution across packs balanced. The suggested SGPA method adds an adaptive charging algorithm that is easy to understand and ready to use. It makes fast charging more efficient without lowering voltage and thermal safety limits.
Prakashkumar, Balagopal, Mannar, Vignesh
Vehicle sound packages are usually designed to provide a given level of vehicle Noise, Vibration, and Harshness (NVH) comfort, within weight and cost constraints. Optimal comfort results can be obtained by considering the interaction of all the parts as a full physical system. So far, extensive research has already been performed and published on optimizing vehicle sound packages to achieve effective noise reduction at lowest cost and weight. Nowadays, due to the urgency of the transition to carbon neutrality, sound packages must also address the reduction of the full vehicle life cycle carbon emissions. Sound package components should use materials that have a low emission impact during production and that are suitable for recycling at the end of the vehicle’s life. This entails reconsidering the material solutions chosen for the sound package as a whole, rather than for each individual component. This article describes possible differentiations in the design of a sound package involving NVH, sustainability, and weight/cost requirements. The study examines how interior and exterior trim components were combined to achieve both optimal NVH and polymer rationalization, through the introduction of mono-material parts and focusing in particular on the use of a new polyester fiber-based floor decoupler, which achieves comparable NVH performance to polyurethane foam without affecting static compression. The article summarizes the vehicle-level performance related to NVH, sustainability, and weight for three sound packages prioritizing either NVH, sustainability or material cost, including a breakdown to analyze the contributions of various components to the overall outcome. A simple metric is introduced to evaluate sustainability, including material, production, use-phase and end-of-life related Greenhouse Gas (GHG) emissions [7–10]. The NVH evaluation involves measuring airborne transfer functions (ATF), complemented by indoor road noise tests. NVH improvements were achieved without an increase in weight, and weight reduction was also possible without negatively impacting NVH performance, both results enhancing the carbon footprint.
Courtois, Theophane, Cardillo, Marco, Criscione, Mattia, Gerges, Youssef, Massocco, Andrea
As acoustic requirements for NVH trim components become increasingly constrained by mass, cost, and sustainability targets, traditional approaches to inner dash design based on spatially averaged Transmission Loss (TL) metrics are reaching their practical limits. In fully built vehicles, the acoustic performance of the inner dash is governed by its global insulation capability but also by strong spatial heterogeneity and its interaction with spatially distributed noise sources such as the power unit, gearbox, and tyre-road excitation. This paper presents a test-based methodology for the spatial optimisation of inner dash acoustic performance using reciprocal holography. By applying a calibrated sound power source within the vehicle cabin and measuring the reciprocal response in the engine bay and wheel-arch regions, a high-resolution spatial Transmission Loss “hologram” of the inner dash is obtained under in-situ conditions. The resulting spatial data enables the identification of localised acoustic weak points that are not observable using conventional testing methods. To bridge the gap between passive component characterisation and real-world vehicle operation, the spatial TL hologram is subsequently evaluated using representative operational source sound power data to prioritise acoustically relevant regions. This enables the transmitted acoustic energy to be evaluated under realistic driving conditions. The holographic data is then coupled with a parametric acoustic model of the inner dash system, allowing localised mass redistribution to be optimised using a genetic algorithm while respecting packaging and manufacturing constraints.
Harry, Evan, Eandi, Giacomo
The increasing electrification of vehicles means that heating, ventilation and air conditioning systems have a broader range of tasks and a different priority assessment. In electric cars, air conditioning systems are not only responsible for cooling the passenger compartment, but also for controlling the battery temperature, particularly during rapid charging, which represents a high-load operating point. Furthermore, achieving high thermodynamic efficiency is desirable, as this directly impacts the range of electric cars. The elimination of the combustion engine as a major source of noise prioritizes the noise, vibration and harshness behavior of the refrigerant compressor for product selection. To investigate the vibration and acoustic behavior, as well as the fluid dynamic forces resulting from the cyclic compression principle of an electric refrigerant compressor, a test rig was developed that allows compressors to be operated and measured in isolation in an anechoic chamber under various defined operating conditions. This test rig has been expanded in two ways within the scope of this work. Firstly, the compressor can be either rigidly attached to a dead mass using a VDA mount or measured while suspended freely. Secondly, a new R744-compatible refrigeration circuit has been added to the test rig, enabling compressors operating with the environmentally friendly refrigerant CO₂, which has so far only been used by a few manufacturers in selected models, to be tested. Measurement results obtained using this test rig provide valuable insight into the vibration behavior and sound spectra of the refrigerant compressor's fluid, structural, and airborne noise when operating at different points.
Beer, Gabriel, Saur, Lukas, Schwarz, Manuel, Zemsch, Stefan, Becker, Stefan
Large language models (LLMs) have shown remarkable capabilities for perceiving driving environments and making interpretable, logical decisions for autonomous driving. However, their potential for more comprehensive driving strategies, especially concerning energy efficiency, remains underexplored. Most existing studies primarily focus on driving safety, which may inadvertently increase energy consumption. To address this issue, this study explores the use of LLMs as high-level controllers to jointly optimize driving safety and energy efficiency. A textual prompt is designed for the LLM, incorporating few-shot examples that describe scenarios, states, and actions. The LLM processes the scenario and state prompts describing the surrounding traffic environment. It generates a high-level control signal, which is then translated into low-level vehicle motion commands in a high-fidelity traffic simulator with realistic physics, vehicle dynamics, road slopes, and network topology. Experiments in campus-scale digital twin car-following scenarios demonstrate that the proposed LLM-based framework achieves an average reduction of 4.16% in energy consumption compared to the reinforcement learning paradigm, while maintaining driving safety and providing interpretable high-level decision-making. This study highlights the potential of LLMs for longitudinal eco-driving applications under the evaluated simulation settings, extending previous LLM-based autonomous driving research that primarily focused on safety to also consider energy efficiency.
Wang, Haoyu, Li, Zhenning, Wang, Siying, Zhou, Zijing, Zhang, Xiang, Yang, Zhifeng, Ou, Shiqi (Shawn), Qi, Hao
This work investigates the integration of a Sorption Thermal Energy Storage (TES) into the Heating, Ventilation and Air Conditioning (HVAC) system of electric vehicles. The proposed device reduces the energy demand for cabin heating under winter conditions, leading to a driving range increase. The TES dehumidifies the cabin air through a desiccant bed (zeolite 4A), preventing window fogging, enabling higher air recirculation rates, and consequently reducing the required heating power. An experimentally validated numerical model was used to analyze the adsorption and regeneration processes and to identify suitable operating conditions. Regeneration was found to be effective at moderate temperatures (from 120°C), with a counter-current airflow configuration providing faster and more efficient desorption compared to parallel-flow one. A simplified model integrating TES, HVAC unit and cabin was developed and used to compare different configurations. Heating energy consumption with and without TES under different ambient conditions, passenger loads, airflow rates, and regeneration states was evaluated. Heating energy savings ranged from 19% to 71%, increasing with higher external humidity. Considering the desiccant bed volume, equal to 1.65 L, electric energy savings up to 1.7 kWh L-1 for heat pump systems and 3.3 kWh L-1 for electric heaters were estimated, corresponding to a potential driving range increase of 13.4 km L-1 and 33.5 km L-1, respectively. Preliminary TES tests on a mock-up vehicle confirmed the effective dehumidification capacity of the proposed technology.
Verlingieri, Rebecca, Calabrese, Luigi, Freni, Angelo, Marocco, Luca, Scudeler, Gabriele, De Antonellis, Stefano
The rising concerns on climate change is accelerating the transition from fossil fuel-based technologies to sustainable energy systems. In this framework, Proton Exchange Membrane Fuel Cells (PEMFCs) are gaining an increasing interest due to their high efficiency and wide range of applications. Nevertheless, these systems experience significant performance losses under high loads, associated with significant heat generation, making thermal management a fundamental design aspect. In this study, a 200-kW low temperature PEMFC was investigated through the development of a 0D – 1D model of a simplified cooling circuit implemented in GT – SUITE environment. The model was used to evaluate the influence of design parameters on the effective efficiency of the system to dissipate the excessive heat. Additionally, a detailed stack-only model, comprehensive of the Membrane Electrode Assembly (MEA) subcomponents, was developed to verify the temperature differences between coolant fluid and membrane. Further, based on the stack-only model results, a temperature-based damage index formulation has been implemented to assess PEMFC performance along 25000 hours of service life. Considering an optimal operating range of the MEA between 60°C and 80°C, the results obtained indicate the need for a radiator capable of dissipating at least 75 kW of thermal power under critical conditions. The start-up phase was identified as particularly challenging, suggesting the implementation of a ramp-up strategy to mitigate the temperature gradient and overshooting before achieving stable conditions by the radiator. With the pump operating at maximum regime (5500 rpm), the stack-only model showed a temperature difference between the membrane and coolant fluid of approximately 2.8°C of the inner cells, while the external cells exhibited higher temperature differences up to 7.4°C, potentially leading to increased thermally induced stress mechanisms. Further, at the end of life (EOL) the single contributions of chemical degradation (83.5%) and thermal gradients (49.0%) were noted to dominate over other thermal aging mechanisms.
Cecere, Giovanni, Antetomaso, Christian, Irimescu, Adrian, Merola, Simona
Ammonia (NH3) fuelled engines have emerged as a promising route toward net-zero emission targets due to NH3’s carbon-free nature, ease of storage, and established handling infrastructure. However, the low laminar burning speed and narrow flammability limits of NH3 pose a significant combustion challenge, which can be addressed through hydrogen (H2) co-fuelling. For practical implementation, on-board H2 production via thermal catalytic cracking of NH3 is an attractive solution, as it eliminates the need for external H2 storage and associated handling and capital costs. Previous studies by the present authors identified a lean operating strategy that achieves an equimolar ratio of NOx and unburned NH3 (α NH3NOx ≈ 1), enabling complete conversion to nitrogen and water vapour when coupled with a Selective Catalytic Reduction (SCR) system. This strategy was further validated using cracked NH3 derived H2 in place of bottled H2 through an on-board cracker, thereby representing a practical system configuration. However, the required H2 fraction, and consequently the size and power demand of the onboard cracking system, is strongly influenced by engine architecture and operating conditions. The present study investigates the effect of compression ratio (CR) and stroke length, on H2 fraction requirements to achieve an optimum α of unity in an externally boosted SI engine. Results demonstrate that the high CR = 17.5, long stroke configuration reduces H2 enrichment by 50–60% compared to a low CR = 12.5, short-stroke engine architecture, allowing smaller onboard H2 generation systems. At high-speed, high-load conditions, it achieves over 45% thermal efficiency with stable NH3 combustion and no H2 supplementation, maintaining an α ≈ 1. Across the full operating map, NOx emissions comply with IMO Tier III and EPA Tier 4 norms, demonstrating near-zero-emission operation.
Yadav, Neeraj Kumar, Ambalakatte, Ajith, Geng, Sikai, Gopakumar Suja, Gagan, Birch, Alexander, Cairns, Alasdair, Harrington, Anthony, Hall, Jonathan
As the automotive industry faces increasingly rigorous environmental regulations and an approaching obligation for Digital Product Passports (DPPs), incorporating sustainability metrics into the early design phase has become a necessity. Traditionally, Life Cycle Assessment (LCA) and manufacturing cost estimation are performed during or after the design phase using specific methods and tools, resulting in costly iterations and delayed decision-making. This paper introduces a preliminary computational tool that combines 3D CAD and spreadsheet software via VBA integration. The framework automates the generation of an “Extended Bill of Materials” by extracting geometric and manufacturing data directly from CAD models. This tool’s classification logic is a key innovation that intelligently processes CAD features to identify component categories, such as sheet metal, machined parts, or plastic injections. This automated recognition allows the framework to implement specific algorithmic models for the preliminary estimation of production costs and environmental impact indicators. The gap between computer-aided design and sustainability analysis is partially bridged by the tool, enabling engineers to receive immediate feedback on the carbon footprint and recyclability of their designs during the early conceptual stage. Preliminary testing within automotive case studies shows a substantial decrease in lead times for technical estimation. Specifically, analysis time was reduced by at least 90%, with subsystems processed in under 10 minutes, a significant improvement over traditional manual calculations. This tool represents a pragmatic step toward “Circular Design” paradigms, supporting compliance with future legislative frameworks and fostering the transition toward a circular economy in transportation systems.
Guadagno, Maurizio, Cecconi, Leonardo, Berzi, Lorenzo, Delogu, Massimo
Thermal management in internal combustion engines (ICEs) strongly affects fuel consumption and pollutant emissions, especially during engine warm-up. Particularly, the oil temperature is strictly related to the organic efficiency of the vehicle: in the early phase of a driving cycle, the low temperature produces a high-viscous oil, which increases friction losses and increases fuel consumption, with respect to full thermal regimated oil. Usually, the oil and coolant thermal behaviours are interconnected, thanks to a coolant/oil heat exchanger in the engine. In this study, a prototyped electrical coolant pump has been applied and integrated in a small SUV vehicle, replacing the original mechanical unit. An off-board experimental campaign allowed a complete hydraulic characterization of the cooling system, including thermostat operation, and led to a physically based correlation between flow rates and pressure drops in each branch. Based on these results, the pump was designed and prototyped, enabling advanced flow management strategies on board. On-road Real Driving Emissions (RDE) tests were carried out using different pump control logics. Four different control strategies have been proposed in order to reduce the warm up time of the engine and the oil. Results show that the warm-up time reduction produces also a decrease in CO, NO, THC, CH₄, and PN emissions by 15–65%, particularly during cold-start conditions. The innovation proposed can be also combined to other technological options, to further improve the thermal behaviour of the engine and increase the temperature of the oil in the early phase of a common driving cycle. Electrification also reduces parasitic losses and facilitates integration with hybrid powertrains, confirming thermal management as an effective transitional technology for improving ICE efficiency and environmental performance under real driving conditions.
Di Battista, Davide, Di Bartolomeo, Marco, Cipollone, Roberto
With the United Kingdom’s goal to achieve a fully decarbonised energy sector by 2035 and achieve net zero greenhouse gas emissions by 2050, the transition of the UK’s passenger car fleet to battery electric vehicles (BEVs) plays a crucial role in reaching this goal. This study evaluates the environmental and energy impact of large-scale BEV adoption by modelling future uptake scenarios using historical fleet data combined with assumed impact of future policy such as the 2030 ban on the sale of new petrol and diesel vehicles. Three predictive models have been developed: fast uptake, in which approximately 100% of the passenger car fleet is replaced by BEVs; moderate uptake, where a large majority of passenger cars are BEVs; and slow uptake, in which BEV adoption does not reach a majority. The results have shown that, if a medium- or large-scale adoption is possible by 2040 predicting nearly 37 million BEVs on the road, the associated electricity demand is predicted to rise close to 110 TWh annually, signifying the need for rapid development in renewable energy generation. Although BEVs significantly reduce transport sector emissions, the overall climate impact is dependent on a continued effort of grid decarbonisation.
Burke, Bradley, Kateregga, Sunny, Sodre, Jose Ricardo
Over the last few years, there has been an uptick in the exploration and implementation of aluminum high-pressure die casting (HPDC) mega-castings as replacements for conventional stamped steel parts in vehicles. This trend is expected to increase with common justifications, including claims of reduced costs and lower environmental impacts associated with the replacement of dozens of individual parts with a single casted piece, along with reduced demands on associated tooling and machinery. However, the data and literature to support these claims are limited and at times contradictory, with some studies showing increased costs and energy demands for mega-casting technologies. This study presents the results of a literature review and a gate-to-gate life cycle inventory (LCI) adapted from conventional HPDC aluminum casting unit processes that may be used to quantify potential life cycle global warming potential (GWP), cumulative energy demand (CED), and other environmental impacts of aluminum mega-castings. A set of cradle-to-gate example calculations is also provided to demonstrate the application of the inventory and significance of the findings, which point to significantly higher GWP and CED for aluminum mega-castings versus stamped steel parts and warrant further study to inform vehicle design decision makers.
Sebastian, Brandie, Balzer, Russ
We hear it often at industry events, in keynote speeches and during expert panel discussions: There is no silver bullet. Peter Voorhoeve, president of Volvo Trucks North America, says as much in this issue's Q&A (page 44). “Electric is one solution, but biodiesel is another solution, and hydrogen is, too. So we have these different fuel solutions to get to better sustainability.”
Gehm, Ryan
Circular-economy principles are increasingly central to aerospace sustainability strategies, aiming to extend asset life, improve asset valuations, and enhance benefits to stakeholders in the part ownership and maintenance lifecycle. In aircraft engines, achieving circularity hinges on safe reuse, repair, and recirculation of high-value components. Life-Limited Parts (LLPs) are among the most critical in this context, but their reuse is strictly contingent on complete Back-to-Birth (BtB) traceability. Any gap in BtB records—often due to fragmented data across multiple airline operators, shop visits, document formats, and time expanse—renders otherwise serviceable LLPs unusable, leading to premature scrappage and lost circular value. This paper presents a Generative AI (GenAI)-driven methodology to reconstruct and validate complete LLP BtB histories from heterogeneous, unstructured, and legacy maintenance datasets. By combining aerospace domain-trained language models with embedded life accounting logic and regulatory compliance reasoning, the approach produces audit-ready documentation that assists the asset owners in meeting regulatory standards from aviation authorities such as EASA and FAA. Enhancing traceability to LLPs enables their safe re-entry into operational service, supports the module swaps market, and optimizes part pooling strategies. The result is a digital enabler for circularity in the engine lifecycle—preserving material value and maintaining uncompromised safety and compliance in aviation.
Bhate, Ujwal, Jain, Dilip Kumar, Kulkarni, Ninad, Kalaiyarasan, Aravindh, Jha, Ashish, Shenoy, Karthik
Aerospace products operate within highly complex, safety-critical environments and endure extended lifecycles, often spanning decades. Sustaining their operational value requires rigorous management of Safety, Reliability, and Availability (SRA), while global Environmental, Social, and Governance (ESG) mandates demand parallel progress toward sustainability goals. This paper introduces an AI-driven strategy that integrates these dual imperatives—Sustenance Management and Sustainability Management—within a unified Product Lifecycle (PLC) framework. The proposed approach leverages Artificial Intelligence across five PLC phases: Generative Design, Detailed Design & Verification, Manufacturing & Industrialization, Operations & Maintenance, and End-of-Life Circularity. Anchored by a certified Digital Thread, this framework ensures seamless, auditable data flow from concept to disposal. Using Life-Limiting Parts (LLPs)—such as high-stress turbine discs—as a case study, the paper demonstrates how AI interventions enhance operational efficiency while reducing embedded carbon emissions. For example, Generative AI optimizes component geometry for performance and material efficiency, Physics-Informed Machine Learning (PIML) improves Remaining Useful Life (RUL) predictions for certification readiness, and predictive analytics extend Time-on-Wing (ToW), deferring Scope 3 emissions from replacement manufacturing. At end-of-life, AI-guided valuation of Used Serviceable Material (USM) enables circularity and compliance with ISO 14067 and ISO 14040/14044 standards. The paper also discusses sustainability metrics such as Design Simulation Energy Intensity (DSEI) and the Sustainable AI Quotient (SAIQ) [25], to address the AI-energy paradox, ensuring that digital transformation remains net-positive for environmental stewardship. By positioning sustenance as the most immediate lever for sustainability, this AI-led framework delivers measurable improvements in lifecycle cost, operational resilience, and carbon footprint reduction. The discussion concludes with challenges in data governance, regulatory compliance, and model explainability, offering mitigation strategies for safe and scalable adoption.
Srinivasan, Karthik, G.V.V., Ravi Kumar, Vaderahobli, Devaraja Holla, Bhate, Ujwal, Veluri, Sastry
Air Traffic Management (ATM) must be familiar with the exact Aircraft Take-off Weights (ATOWs) of airplanes to make the most use of runways, maintain safety margins high, and keep utilization and resources in balance. This paper aims to present a dependable ATOW forecasting methodology that can assist the air transport industry in enhancing operational decision-making. This research used datasets acquired from the EUROCONTROL Performance Review Commission (PRC) 2024 Aircraft Take-Off Weight Estimation dataset featuring 527,000 flights over Europe containing aircraft details, air trips and flight conditions. Technique comprises structured data input, inspection of missing data, timestamp aggregation to identify demand cycles over time, and domain-specific feature engineering using distance_per_minute, block_minutes, taxiout_ratio, and a strong wake turbulence metric The two supervised learning models used were Linear Regression (LR) for understanding and XGBoost for performance prediction In comparison to LR's 4,409 kg MAE (mean absolute error), 7,061 kg RMSE (root mean square error), and 0.9825 R2 value, XGBoost significantly excelled with validation results showing an R2 value of 0.9992 and an RMSE of 1,514 kg In the absence of labelled test targets, cross-validation nevertheless showed a constant degree of generalizability The residual diagnostics showed that the model was reliable for practical execution with low-variance deviations that were unbiased An accurate ATOW estimate improves the demand-capacity balance and On-Time Performance (OTP) in ATM, which in turn affects the runway schedule, wake turbulence diversion, slot allocation, and fuel planning The results highlight the need to include ATOW predictions in both tactical and strategic planning to reduce delays, increase airspace usage, and promote sustainable aviation operation and possesses significant improvements will consist of weather and runway conditions, stochastic ambiguity computation, and drift monitoring to keep up with ever-changing operating variables while maintaining accurate forecasts.
Senthilkumar, N., S, Gopalakrishnan, Gopinath, S
Materials innovations are shaping the next generation of medical devices. In this Q&A, Jeremy Schaffer, director of research and development at Fort Wayne Metals, discusses how advances in titanium, nickel-titanium, surface engineering, and smart materials are helping device developers improve performance, miniaturization, durability, and patient outcomes. He also addresses sustainability, scale-up challenges, and the collaborations needed to move promising materials from research into real-world medical use.
To reduce high NOx emissions from diesel-cyclohexanol blends, this study employed a marine medium-speed diesel engine as the experimental platform. An in-cylinder combustion model was developed and meshed using AVL - FIRE software, with model validity validated against experimental data. Tests were conducted at four load conditions (25%, 50%, 75%, and 100% load) with a 30% cyclohexanol blend (C30) and four EGR rates (0%, 7.5%, 10%, and 12.5%) to analyze combustion characteristics, emissions, and fuel economy. The results showed that the introduction of EGR had a striking inhibitory effect on NOx emissions. At 100% load with 12.5% EGR rate, NOx emissions were substantially reduced compared to baseline operation without EGR. However, EGR implementation led to delayed ignition timing, reduced in-cylinder pressure, and worsened fuel economy. Therefore, an appropriately calibrated EGR strategy can effectively reduce NOx emissions, though it requires optimization to mitigate adverse effects on combustion performance and efficiency.
Liu, Yuchen, Yang, Chenxi, Fan, Jinyu, Chen, Ke, Ye, Zixiao, Huang, Jialiang
This paper presents a multi-physics modeling approach for a hybrid propulsion system designed for High-Altitude Long-Endurance Unmanned Aerial Vehicles (HALE UAVs), integrating solid oxide fuel cells (SOFCs), lithium-ion batteries, and a jet engine. A dynamic model was developed to analyze the coupled characteristics of pressure, temperature, and power under steady-state conditions. Simulation results demonstrate that the internally integrated system achieves efficient fuel and waste heat recovery, delivering a net power output of 300–700 kW, sufficient to meet the operational demands of HALE UAVs. Key innovations include a heat exchanger maintaining SOFC stack inlet temperatures above 850 K for optimal performance and a compressor-fan subsystem enhancing gas compression efficiency. Experimental validation confirmed the accuracy of the SOFC model, with simulated electrical characteristics aligning closely with empirical data. The proposed hybrid system addresses limitations in specific power and transient response while improving energy density, offering a viable solution for long-endurance flight missions. This study provides a foundational platform for advancing hybrid propulsion technologies in aviation.
Zhang, Lin, Zhang, Di, Zhao, Lulu, Li, Xi
As the global pursuit of carbon neutrality accelerates, carbon capture, utilization, and storage (CCUS) technology is emerging as a critical strategic pillar for achieving significant emission reductions and facilitating the transition to green development. This review systematically summarizes the principal technological pathways and recent advances in carbon capture, resource utilization, and storage within CCUS systems, with particular attention to innovative directions including advanced adsorption and separation materials, synergistic catalytic conversion, biological carbon sequestration, and mineralization-based storage. By examining representative engineering practices and industrialization cases both domestically and internationally, this paper summarizes the major challenges currently facing CCUS, including material costs, energy consumption, environmental risks, and large-scale deployment. The positive impacts of interdisciplinary integration, process system optimization, and policy coordination on the commercialization of CCUS are also discussed. The review indicates that overcoming bottlenecks in core materials and process technologies, improving regulatory frameworks and market mechanisms, and establishing clustered industrial ecosystems are essential for CCUS to spearhead the forthcoming low-carbon energy and green industrial revolutions. This paper envisions future development trends for CCUS technology, highlights its multidimensional strategic value for global carbon governance, energy security, and the circular economy, and offers theoretical references and cutting-edge insights for scientific research, policy formulation, and industrial decision-making in related fields.
Wang, Yingfei
In the context of the global active response to climate change and the strong advocacy of green development, China’s energy industry is demonstrating a steadfast commitment to low-carbon transformation. In this process, green power trading has gained significant development by virtue of its unique advantages and potential. In this process, green power trading has gained significant development by virtue of its unique advantages and potential. The core objective of the Pinglu Canal Project, a pivotal initiative promoting green and low-carbon development in the region, is to establish a “net-zero carbon” initiative by facilitating the supply of green energy throughout its entire life cycle. This initiative is designed to promote a green and low-carbon transition. This paper conducts an in-depth study on the green power supply path during the construction period of the Pinglu Canal project, and proposes four practicable options. In order to scientifically and objectively determine the optimal path, this paper constructs a comprehensive evaluation index system and a TOPSIS evaluation method based on comprehensive weights. The system encompasses the four dimensions of feasibility, economy, technology, and demonstration, enabling a comprehensive and precise evaluation of the advantages and disadvantages of each path. The findings of the empirical analysis demonstrate that the combined scores of Path 1 (participation in green power trading), Path 2 (purchase of thermal power with green certificates), Path 3 (rooftop distributed photovoltaic system and purchase of new energy power), and Path 4 (rooftop distributed PV system and purchase of thermal power with green certificates) are 0.8166, 0.7486, 0.2197, and 0.2885, respectively. The comparative analysis reveals that participation in green power trading is the optimal strategy for the project’s construction period.
Huang, Zeyi, Wei, Yuchen, Li, Xiayang, Wang, Cuixian
This article focuses on the problem of high labor cost, low processing efficiency and poor automation of the existing equipment in the postharvest processing of Chinese cabbage. It will design and produce an automated Chinese cabbage processing method called Smart Fresh Pack. Root removal, leaf removal, washing, loading, weighing, packaging and labeling functions were integrated, and smart dexterous intelligence was applied to core concepts and this can be used in the bulk production scenario of supermarkets in the city and countryside Compared with traditional assembly line equipment, obvious advantages in terms of structure, function and processing capacity: Key innovations include: Low-pressure air jet cleaning replaces water washing, which prevents a second contamination and weighing error due to surface moisture; pneumatic gripper and multi-DOF robotic arms combine to package and dynamically weigh simultaneously, streamlining these tasks; machine vision relies on an SSD-MobileNetV2 visual model with Sobel edge detection to locate and identify wilted leaves; and pairing with a multi-threaded control structure for millisecond level closed-loop response. I used Fischertechnik models to build and simulate, checking whether the motion logic of this design is reasonable, whether the stresses are safe, and whether the airflow cleaning is effective. This machine finishes the complete processing of one cabbage just within one minute, its modular and its maintainance and scalability aspects are also there, it gives small and medium size agricultural entities a low cost but also very effective clean vegetable processing route, this is truly good for making progress with the auto, standard and green developments within agric prd processing.
Chen, Yuhui, Zhang, Yixuan, Ruan, Jia, Zhu, Huayun, He, Lianzheng, Zhao, Ping
As an emerging innovative mode of public transportation, electric modular buses (EMBs) offer a novel solution to the problems of existing public transportation systems, due to the coupling-decoupling processes. In this paper, we study the energy consumption characteristics of EMBs by joining vehicle-to-vehicle (V2V) charging and reduction in aerodynamic drag due to coupling. For the pursuit of energy economy, ride comfort, and operational efficiency, we constructed an optimization scheme based on the simulated annealing (SA) algorithm to facilitate the coupling-decoupling process. The simulation results show that EMBs can meet 82.5 % of service requests compared with 61.8 % for the benchmark group, and V2V presents a significant contribution to energy efficiency, especially at low battery state of charge (SOC). Additionally, sensitivity analysis is conducted to study the impact of initial SOC, operation interval, and route type. The results provide insights for optimizing EMBs’ operations and emphasize the potential role of EMBs in supporting low-carbon and sustainable urban mobility systems.
Liao, Peng, Guo, Jiahe, Ning, Donghong, Li, Sijia, Wang, Tao
Variable Compression Systems for Future Engines and FuelsR-5534/30/2026
Variable Compression Engines: Enabling Net Zero explores variable compression ratio (VCR): one of the most promising—and historically elusive—advancements in internal combustion engine (ICE) technology. Long recognized for its thermodynamic benefits, VCR has challenged engineers for decades due to its mechanical complexity. Today, as the global mobility landscape demands ever higher efficiency, lower emissions, and greater fuel flexibility, VCR has emerged as a viable and transformative solution. This book delivers a comprehensive and authoritative examination of VCR technology, quantifying its efficiency and CO2-reduction potential while surveying the wide range of mechanisms conceived, developed, and tested over more than a century of engine innovation. By combining historical insight with modern analysis, the authors reveal the remarkable ingenuity of past and present engine designers—and demonstrate that VCR is not only feasible, but increasingly essential. Positioned squarely within the context of global decarbonization, the book argues for a realistic, inclusive pathway to net-zero emissions—one in which ICEs continue to play a critical role. VCR technology enables higher efficiency across almost all operating conditions, supports advanced combustion strategies, and allows engines to operate effectively on a broad spectrum of low- and zero-carbon fuels, from biofuels to synthetic e-fuels. With VCR now in high-volume production and poised for broader adoption across automotive, heavy-duty, and marine applications, this timely volume is an essential resource for OEMs, suppliers, policymakers, researchers, and students seeking practical, scalable solutions for a sustainable energy future. Chapter topics include: • compression ratios and fuels • compression ratio limits • cylinder head VCR • cylinder block VCR • connecting rod variable compression • piston VCR • cranktrain and linkages VCR • modulated crankshaft eccentricity VCR • axial or barrel engine VCRs • high power and downsized engines • impact of VCR systems on engines • VCR applications for the future • variable compression for future engines and fuels • VCR cost–benefit analysis
Pirault, Jean Pierre, Dingle, Philip, Flint, Martin
Accurate projection of Plug-in Electric Vehicle (PEV) market sales share is vital for evidence-based policymaking, yet existing studies employ diverse and often fragmented methodologies, creating a need for a systematic review to clarify their analytical foundations and comparative strengths. This study classifies mainstream approaches to market projections into theory-driven and data-driven categories and reviews the merits, limitations, and future directions of five representative models. Analysis reveals that leading approaches increasingly employ cross-scale model coupling, theory-data fusion, and modular design to harness complementary strengths, improving model robustness and predictive accuracy. Furthermore, the study compares PEV policies and market outlooks in China, the United States, and Europe—the world's three largest automotive markets. The findings indicate a strong linkage between projection convergence and policy stability. China demonstrates the highest policy consistency and institutional consensus, with an average projected PEV share of new-vehicle sales of 81.3% by 2030. Europe's projections average 62.8%, driven by binding emissions mandates, whereas the U.S. exhibits greater uncertainty, averaging 31.1% amid fragmented regulations and policy uncertainty. These disparities highlight the decisive role of policy coherence and regulatory predictability in shaping PEV market outlooks.
Luo, Wei, Ou, Shiqi(Shawn), Zhou, Pan, Wang, Tianpeng, Qian, Xiaodong
The rapid adoption of electric vehicles (EVs) is a cornerstone of the transition to sustainable transportation. However, uncertainty regarding battery degradation remains a significant obstacle, hindering vehicle energy efficiency, operational safety, and the recovery of end-of-life value. Accurate estimation of the battery state of health (SOH) and prediction of the remaining useful life (RUL) are therefore critical for sustainable vehicle lifecycle management. This study proposes an edge–cloud collaborative intelligent framework for in-vehicle deployment that leverages a Transformer-based architecture to jointly model SOH and RUL. The cloud-side model retains the full configuration to capture long-term degradation trajectories for high-accuracy RUL prediction. A lightweight edge-side model, engineered via pruning and knowledge distillation, delivers millisecond-level inference for real-time SOH estimation onboard the vehicle. To ensure efficiency, only four core health indicators are extracted for end-to-end prediction. Experimental validation across 77 battery cells demonstrates that the framework achieves SOH estimation with a root mean square error (RMSE) of 1.41% and RUL prediction with an RMSE of 2.59% (78 cycles). Furthermore, a periodic cloud-side update and over-the-air deployment mechanism ensure long-term adaptability and cross-platform scalability without full local retraining. This intelligent prognostic framework directly enhances EV reliability and sustainability by providing health-informed decision support for optimal vehicle operation, maintenance scheduling, and the reuse of second-life batteries. Consequently, it serves as a vital tool for advancing resource optimization and circular economy principles within the E-mobility ecosystem.
Gao, Weimin, Lv, Zhilong, Ou, Shiqi(Shawn)
With the strong momentum of electric vehicles (EVs), the battery recycling industry is undergoing rapid growth. While the Chinese government has implemented a white-list mechanism under which only approved recyclers are allowed to process retired batteries, small-scale illegal battery recycling vendors have posed a serious challenge. This study compares the techno-economic performance of battery recycling between legal and illegal recyclers in China, and makes recommendations to eliminate illegal operations. Our research covers two battery chemistries: lithium nickel-manganese-cobalt oxide (NMC) and lithium iron phosphate (LFP), as well as two technological pathways: resource recycling and cascade utilization. For the general case, the costs of illegal vendors are 35-46% lower than that of legal companies. Although legal companies achieve high resource utilization, their overall economic performance lags behind due to their high costs associated with equipment, environmental protection, taxes, and materials. Such situation can be reversed with changes in economies of scale, tax incentives, and automation in the recycling process. Among different battery types and recycling pathways, the resource recycling of NMC 811 batteries is most likely to achieve a competitive advantage through policy support and economies of scale. In contrast, for the resource recycling of LFP batteries, legal companies are unlikely to surpass illegal vendors across all scenarios. To ensure sustainable development of the battery recycling industry, critical strategies should be comprehensively employed, alongside measures such as raising entry barriers, regulating recycling networks, and strengthening supervision to crack down on illegal vendors.
Du, Shilong, Li, Haoyang, Dou, Hao, Hao, Han
By the early 2020s, more than 4.5 billion people have been living in urban areas worldwide, compared to just 1 billion in 1960. Rising growth in urban populations present challenges to infrastructure and transportation systems. Higher traffic levels and reliance on conventional vehicles have contributed to heightened greenhouse gas (GHG) emissions, rising global temperatures, and irreversible environmental degradation. In response, emerging transportation solutions—including intelligent ridesharing, autonomous vehicles, zero-tailpipe-emission transport, and urban air mobility—offer opportunities for safer and more sustainable transportation ecosystems. However, their widespread adoption depends not only on technological performance and efficiency, but also on integration with current infrastructure, safety, resilience to unexpected disruptions, and economic viability. A dynamic agent-based System-of-Systems (SoS) transportation model is developed to simulate vehicle traffic and human movement for assessing mobility solutions against different demand scenarios and possible disruptions within a well-defined metropolitan area. The analysis adopts the concept of an airport city—a cluster of residential, commercial, and industrial spaces surrounding major airports—as a representative urban context. Using the Atlanta Aerotropolis as a case study, this work introduces an interactive, parametric decision-support methodology for evaluating the impact and benefits of future mobility options, as part of transportation master planning. Given the multi-objective and multi-stakeholder nature of transportation planning (e.g. local government, urban planners, engineers, and technology providers), the proposed approach leverages simulation-enabled digital twins of mobility solution alternatives to analyze traffic performance across multiple criteria, including energy consumption, emissions, affordability, accessibility, and connectivity within the broader urban infrastructure. The study reveals cost-benefit trade-offs among mobility solutions in the context of disruptive scenarios, such as the 2026 FIFA World Cup hosted by Atlanta, GA. The results highlight the importance of deploying a mix of mobility options over the city’s transportation network to maximize sustainability while maintaining resilient operations.
Rana, Vishva, Balchanos, Michael, Mavris, Dimitri, Valenzuela Del Rio, Jose
The increasing adoption of electric vehicles (EVs) introduces critical vulnerabilities associated with dependence on rare earth elements used in traction motors and battery systems, impacting supply chain stability, environmental sustainability, and cost scalability. This investigation focuses on simulation-optimized rare earth-free EV propulsion components, including induction-based and wound rotor electric motors employing ferrite and iron-nitride magnetic materials, in combination with lithium iron phosphate (LFP) battery chemistry recognized for enhanced safety and extended cycle life. An integrated multi-physics simulation framework coupled with targeted experimental validation is employed to evaluate efficiency, thermal behavior, and durability of the proposed motor–battery systems. The optimized configurations demonstrate automotive-grade performance, with motor efficiencies ranging from 90–96% and LFP batteries retaining over 84% of nominal capacity after 5,000 charge–discharge cycles. Simulation predictions exhibit strong correlation with experimental measurements within ±5%, confirming model fidelity. The findings indicate that rare earth-free propulsion systems and LFP batteries can meet EV performance and safety requirements while significantly reducing reliance on critical materials, supporting sustainable EV development.
Saraswat, Shubham, Vishe, Prashant
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