Browse Topic: Environment

Items (42,489)
Zhang, YinXue, LeileiGuo, LiqiangFu, XiaoZhang, XiaofangLiu, ZhihaoHan, Guoxin
Quadrotors (UAVs) are widely used in intelligent inspection, environmental monitoring, and logistics due to their simple structure, strong maneuverability, and vertical take-off and landing capabilities. However, their highly nonlinear, strongly coupled, and highly constrained dynamic characteristics make trajectory tracking control a challenging task. To improve trajectory tracking accuracy and control robustness, this paper proposes a quadrotor trajectory tracking method based on model predictive control (MPC). First, a six-degree-of-freedom dynamic model of the quadrotor is established and linearized with small disturbances to transform it into a state-space model suitable for MPC design. An MPC optimization controller is then constructed, with an objective function that minimizes state error and imposes an input energy penalty, while explicitly considering the system's input and state constraints. Simulation results demonstrate that this method exhibits good tracking accuracy and control smoothness for typical trajectory tracking tasks (such as circular and spiral trajectory tracking). Compared with traditional PID and LQR controllers, the proposed method significantly improves maximum error, mean square error, and interference rejection. This study provides an engineering-feasible optimization control framework for UAV trajectory control.
Peng, FeiTao, ZhongGao, QiangJia, Bobo
The structural stiffness of a manned lunar vehicle is a core indicator ensuring its stable operation in the complex lunar environment. The vehicle’s body structure must meet multiple requirements, including high stiffness, lightweight design, and adaptability to lunar surface conditions. Since lunar gravity is only 1/6 of Earth’s and the terrain is rugged and dusty, the body structure must employ a high-stiffness design to withstand driving impacts and resist deformation, thereby preventing mechanical failures or safety hazards for crew members caused by excessive structural distortion. However, excessive structural stiffness would result in an overweight vehicle body, conflicting with the spacecraft’s lightweight requirements. Thus, the structural stiffness index should be optimized to a lower value while ensuring safe operation during lunar surface driving without compromising performance. This paper calculates and determines the structural bending and torsional stiffness indicators for the manned lunar vehicle’s body through simplified model calculation and the FEA method.
Shen, ZhenghuiWu, YingjiaYang, JianfengWang, WeijunZhang, ChongfengHan, Liangliang
Public transportation serves as a crucial component of urban mobility, contributing to the alleviation of urban congestion, reduction of travel expenses, and mitigation of air pollution. Nonetheless, the dynamic passenger demand and the complex traffic conditions render traditional bus timetables inadequate, leading to ineffective allocation of public transportation resources. Consequently, it is essential to create bus timetables that are responsive to actual traffic scenarios and fluctuating passenger demand. This study regards the bus timetable planning problem as a Markov decision-making process within a discrete time framework, proposing a deep reinforcement learning-based optimization model for bus timetables. In particular, the model is designed to account for both bus companies and passengers, incorporating a state space and reward calculation method that emphasizes passenger comfort. Then Deep Q-Network (DQN) methodology is employed to issue instructions on whether a bus departure at each time, and bus timetable is generated gradually over time. Experimental results indicate that the proposed approach significantly reduces bus travel costs and enhances the overall travel experience for passengers in comparison to traditional methods.
Xu, JieXia, DongYang, JianxiWang, Bing
Thermal shock, space combined irradiation test, and humidity test were carried out on one type of multilayer insulation. We summarized and analyzed the change in solar absorptance and hemispheric emittance before and after the environmental test. At the same time, the thermal stability and vacuum pollution characteristics were investigated by thermal weightlessness test and thermal vacuum outgassing test. The results show that the change in thermal radiation performance before and after the environmental test is no more than 0.02, the heat resistance is 350 °C, TML is 0.50%, and CVCM is 0.05% at 135 °C. It is observed that the thermal radiation performance of the material is hardly degraded by thermal shock, and humidity and space combined irradiation. The multi-layer insulation shows good thermal radiation characteristics, thermal stability, and low space pollution characteristics.
Li, WeiyuLiu, YangLi, XiujieSun, ShuHuang, FeiyuYang, Yaodong
This study addresses the insufficient tractive trafficability of four-track unmanned amphibious tracked vehicles (UATV) in beach terrain by proposing an optimization strategy based on coordinated suspension height and hitch point adjustment. A mathematical model of vehicle drawbar pull was established to systematically analyze the influence mechanisms of vertical load distribution, suspension adjustment, and hitch point elevation on tractive trafficability. DEM-MBD coupling simulations revealed differentiated traction laws under sandy loam and clay conditions, particularly regarding track overlap effects. Results demonstrate that in sandy loam, rear-axle traversal over front-axle tracks reduces drawbar pull due to soil loosening, whereas track overlap enhances drawbar pull in clay through soil compaction. Nine suspension-hitch configurations were tested, validating optimization strategies: increased front-axle loading (Configuration a) in sandy loam and reduced front-axle loading (Configuration f) in clay. These configurations significantly improved tractive trafficability.
Chen, YaoyaoGao, XueWang, WenhaoXu, Xiaojun
To mitigate the risks of runway incursions during aircraft transitions between closely spaced parallel runways, major hub airports globally have implemented End-Around Taxiway (EAT) as an effective safety solution. Operational data from leading international airports confirms that EAT installations have successfully enhanced surface safety while maintaining operational efficiency. However, the EAT involves a longer taxiing route, resulting in higher fuel consumption and pollutant emissions. This study takes the example of a set of closely spaced parallel runways at a domestic airport to analyze the ground taxiing process of arrival and departure flights, proposing a dynamic allocation strategy for EAT operations that can achieve energy conservation and emission reduction during the taxiing process. Through simulation, its effective operational performance is studied.
Wang, ZinanYe, Bojia
With the rapid development of China’s civil aviation industry, the problem of airport noise has attracted widespread social attention. The requirement for the real-time monitoring and evaluation of acoustic environment around airports is becoming more and more intense. The identification of aircraft noise events in the complex acoustic environment surrounding the airport is the most critical technical problem in airport noise monitoring. However, the traditional noise source identification technology is difficult to be widely used in real-time monitoring system due to its large errors and complex deployment conditions. This paper presented an aircraft noise source identification technique based on a single acoustic vector sensor. The azimuth parameters of the noise source were estimated by the three-dimensional spatial positioning algorithm of sound pressure and particle vibration velocity combined with information processing, and the three-dimensional footprint of the noise event in the complex acoustic environment was described. Finally, the event was judged as an aircraft noise event by matching the noise footprint with the aircraft flight path. By monitored and analyzed the actual noise events of aircraft departure, the results show that this method can only use a single acoustic vector sensor to locate the aircraft noise source and distinguish the aircraft noise event from the background noise event, which provide a new lightweight method for the real-time airport noise monitoring system to locate the noise source and identify the aircraft noise event
Hou, JiayuHe, TianlunZhu, LinChen, YingLiu, YinhuiLv, LeiWang, YuhaoChen, Da
To investigate the disaster evolution characteristics and associated risks of heavy rainfall and flooding on urban transportation infrastructure, this study takes the extreme rainstorm event in Zhengzhou as a typical case. A multidimensional dynamic risk assessment model is employed to analyze the disaster evolution process and conduct risk evaluation. First, the three-stage evolution process and its characteristics are systematically examined. Then, based on the theory of natural disaster risk elements, a dynamic risk assessment model is constructed. The improved Order of Priority Approach (OPA) is used to determine the weights of multidimensional risk factors, and interval type-1 fuzzy logic is introduced to address the uncertainty of fuzzy indicators. Finally, the overall risk level of the heavy rainfall–flooding disaster chain is calculated and evaluated. The results indicate a high-risk level, which is consistent with the findings of the field investigation report, thereby validating the feasibility of the proposed disaster chain evaluation method combining multiple models. This analysis provides a theoretical basis for future studies on similar urban storm flood risk scenarios.
Zhang, YongchengWang, JianweiWu, ZiyiWang, YanLuo, QingKang, Pingping
With the development of manned spaceflight and deep space exploration, TC4 alloy has been used for the structure design of aircraft due to its excellent characteristics. Thermal radiation properties (solar absorptance and hemispheric emittance) of TC4 alloy are becoming important design indices. We investigated TC4 alloys with different surface morphologies and the effect of micro-morphology on thermal radiation properties. The results show that the solar absorptance of the alloys is sensitive to surface roughness and microstructure. As the surface roughness or crack increases, solar absorptance increases. Hemispheric emittance of the alloys increases as surface roughness is added, but it is insensitive to the micro-nanostructure of the alloys.
Liu, YangZhu, XiaoxiRen, ChaolongLi, DasongWan, LeiHuang, Feiyu
Methanol use in marine engines has the potential to reduce nitrogen oxide emissions, particulates, and greenhouse gas emissions. A turbocharged four-stroke marine diesel powerplant was converted to run as a double-DI (direct injection) diesel-methanol hybrid engine. Experimental studies using a non-premixed combustion scheme showed that higher methanol substitution ratios (MSR) led to increased peak heat release rates. The combustion process displayed distinctive two-phase behaviors. Increasing MSR caused retarded ignition timing, shortened combustion duration, and improved thermal efficiency. Combustion stability was significantly improved at higher MSR. Emissions results showed NOX and HC were increased in proportion to MSR, whilst particulate emissions and CO concentrations were inversely reduced. Methanol enrichment was found to enhance NOX and HC formation processes but also accelerate soot particulate decomposition and CO oxidation mechanisms.
Li, XiaoJiang, YuqiYan, PingZheng, LiangLi, HongmeiZhang, WenzhengChen, ChaoMan, Zhongguo
Zero-gravity seats alleviate prolonged sitting fatigue by optimizing human body pressure distribution, but the correlation mechanism between body size parameters and pressure distribution remains unclear. This study proposes a deep learning model based on multimodal data fusion, combining pressure matrices and postural angle data to construct a convolutional neural network (CNN) with a height prediction error ⩽3 cm. Experiments collected pressure and posture data from 100 participants with diverse anthropometric percentiles. Through the fusion of features and the optimization of the model, the study managed to quantify how height and weight impact pressure gradients. The results indicate that the model achieved a prediction R2 value of 0.73, which confirms that there is a strong correlation between pressure distribution and body size parameters. The findings offer theoretical and technical support for the adaptive adjustment systems within intelligent cabins.
Bi, TengfeiNie, JiachengDu, ChangjiangJi, YuechenWang, SongSun, Jiawei
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, PhilipBause, KatharinaSpohn, HannesAlbers, Albert
The mitigation of Greenhouse Gas (GHG) emissions poses a major challenge for the transportation sector, driving the need for renewable fuels. Bioethanol represents a promising fuel for Spark-Ignition (SI) engines, combining a reduced life-cycle CO₂ impact with advantageous combustion properties. However, despite its proven performance under steady-state conditions, the widespread of fuels with high ethanol content is still constrained by significant difficulties during engine cold-start operation. This study aims to experimentally assess the effect of ethanol concentration on cold-start performance and warm-up transient behavior of a Naturally Aspirated (NA), Port Fuel Injected (PFI) SI engine. Warm-up tests were conducted at an operating condition of 2000 rpm engine speed and 20 Nm torque using three fuels with increasing ethanol content: commercial gasoline (E5), E30 and E60. In addition, dedicated startability tests were carried out for E60 and neat ethanol (E100) at different initial engine wall temperatures to evaluate fuel sensitivity to thermal conditions during engine start. The experimental results indicate that increasing ethanol concentration has a negligible effect on the overall duration of the warm-up process, while leading to a modest reduction in both engine wall and exhaust gas temperatures. At the same time, E100 displays severe startability limitations at low initial wall temperatures, requiring repeated cranking attempts before stable operation can be achieved. The same startability issues have been observed for E60 but with limited intensity. Two minimum engine wall temperature ranges were identified for reliable cold-start operation at 20-25 °C for E60 and 25-30°C for E100. Overall, these findings experimentally confirm the dominant influence of engine thermal conditions on the reliable startability of ethanol-fueled spark-ignition engines.
Falbo, LuigiFalbo, BiagioPerrone, DiegoCastiglione, Teresa
The transition toward climate-neutral transportation requires powertrain concepts that combine high efficiency with low pollutant emissions. In this context, hydrogen-fueled internal combustion engines represent a promising solution when hydrogen is produced from renewable energy sources. Owing to its specific molecular properties, hydrogen offers new possibilities for influencing and optimizing the combustion process and reducing the emission formation. This paper presents a numerical approach for characterizing the NOx formation in a single-cylinder research engine equipped with port fuel injection and a passive pre-chamber ignition system. The single-cylinder is operated over a wide range of engine loads and speeds, covering air-to-fuel ratios from λ=1.5 to 2.5 and achieving up to 23 bar indicated mean effective pressure. The study focuses on the influence of engine load and mixture composition on NOx emissions. A dedicated look-up table approach in combination with several reaction parameters based on the extended Zeldovich mechanism are evaluated through comparison with experimental data. Furthermore, multiple sampling positions within the CFD mesh are examined. The simulations reproduce measured trends across variations in load and air-to-fuel ratio with good accuracy. At high load and λ=1.5, NOx emissions of up to 6000 ppm are produced, decreasing exponentially with increasing excess air. Finally, potential NOx reduction strategies for the single-cylinder are examined. While influencing the mixture homogenization shows limited effectiveness, temperature-based actions prove to be more effective. Among the investigated approaches, a Miller intake valve strategy yields the largest benefit, achieving approximately 10% NOx reduction by lowering end-of-compression temperatures and increasing residual gas dilution under otherwise identical operating conditions.
Gal, ThomasVacca, AntoninoChiodi, MarcoSchmelcher, RobinKulzer, Andre Casal
Hydrogen Internal Combustion Engines have emerged as an option for decarbonizing heavy-duty transportation. However, injecting high-pressure hydrogen gas into pressurized combustion chambers induces complex compressible flow phenomena, including choked flow and under-expanded supersonic jet structures, which challenge conventional modeling approaches for optimizing engine performance and emissions. This study conducts a numerical investigation of transient hydrogen injection into a high-pressure argon environment, benchmarking a 2D axisymmetric Computational Fluid Dynamics (CFD) model against high-fidelity experimental optical measurements. Utilizing Ansys Fluent with a density-based solver, coupled with the k-ω SST turbulence model and species transport equations, simulations were performed at injection pressures of 6 MPa and 10 MPa into a 1 MPa ambient chamber. The simulation successfully captured fundamental compressible physics, including Mach disk formation and significant expansion cooling near the nozzle exit. Validation results revealed a strong dependency on the nozzle pressure ratio (nPR). At 6 MPa (nPR=6), the model achieved good agreement with experimental data, predicting tip penetration depth within 10% . However, at 10 MPa (nPR=10), while axial penetration depth predictions remained within the 10% error margin, they were consistently underestimated, and radial dispersion was significantly under-predicted. These discrepancies at high energy levels highlight the challenges of predicting turbulent entrainment within the current modeling framework. The results suggests that the observed deviations are likely to be caused by combined limitations related to the RANS turbulence model, the potential shortcomings of the 2D axisymmetric assumption in resolving highly transient mixing phenomena, the meshing strategy used, the constant assumption made about the coefficient of discharge, and the crucial role of the Turbulent Schmidt number (SCt).
Castilla Batun, Uriel IsaacAlzahrani, Fahad
Current lithium-ion batteries should generally only be charged above 0 °C, as charging below this temperature can promote lithium plating and irreversible degradation. However, conventional pack-level heating elements increase system mass and design complexity. In addition, heat is transferred from outside into the cell, causing the temperature inside the cell to rise slowly. This study evaluates internal Joule heating of cylindrical Li-ion cells using a zero-mean square-wave current excitation and quantifies the associated aging impact. LG INR21700-M50L cells were tested at 0 °C, −10 °C, and −20 °C with three excitation frequencies (50 Hz, 1 Hz, 10 mHz) at 5 A amplitude. Each cycle consisted of 30 min heating followed by 60 min cooling; reference capacity-based state of health (SOH) was assessed every 50 cycles up to 400 cycles. A maximum surface temperature rise of 14.3 K was achieved, with larger temperature rise at lower ambient temperature and lower excitation frequency. Capacity fade remained below approximately 1% for most conditions; however, at −20 °C and 10 mHz a pronounced SOH decrease to 87% was observed, indicating a critical operating regime. The results provide practical guidance for pulse-heating parameter selection and highlight the need for safeguards and further diagnostics in extreme low-frequency excitation at very low temperatures. This heating approach is particularly suitable for simpler battery-electric applications without thermal management, such as e-bikes or power tools. However, it may also be relevant for applications with existing thermal management systems, as it simplifies battery pack design.
Raiber, StefanAllmendinger, FrankDegler, DavidParschau, Anke
Biodiesel blends (B7, B20, B100) were evaluated in a Stage V-compliant SCR on Filter (SCRoF) system for heavy-duty applications to quantify soot reactivity and filter regeneration capability. Compared to conventional diesel (B7), B20 showed slightly faster regeneration performance under real-driving conditions, while B100 resulted in reduced particulate formation and higher soot reactivity, with more intense exothermic events requiring careful management. These differences are attributed to the distinct physical-chemical properties of the fuels (oxygen content, lower heating value) and their interaction with Diesel Oxidation Catalyst (DOC)/SCRoF. All tests were conducted on an engine dynamometer with a Cursor 9 FPT (Fiat Powertrain). Findings are discussed in the context of EU Stage V limits and practical control strategies for heavy-duty applications.
Costa, Simone
The goal of reducing global CO2 emissions requires actions especially for the transportation sector. To achieve the goal, electric traction motors are frequently implemented in passenger vehicles, as well as in commercial vehicles like heavy-duty trucks or buses. Particularly electric city buses have the potential to reduce the local emissions in urban areas and provide local exhaust-emission-free mobility. While their number of registrations rises, research focusses on the improvement of the overall system in order to increase energy efficiency. High importance is gained by the thermal management of the whole system. This research investigates a simulative approach to improve the thermal management and therefore the energy efficiency of an electric city bus. The different thermal components of an electric city bus like drive system, battery system and heating, ventilation and air conditioning system (HVAC system) are modelled. Their thermal behavior has been validated in previous research. Based on the validated model, this study proposes an improved thermal management that, state-dependent, combines the thermal circuits of the single components to reduce the overall energy demand. Cooling or heating is provided by the HVAC system. Furthermore, the simulation utilizes real driving cycles of a city bus in the Hamburg area. Measurement data from an entire year are examined by a cluster analysis that results in typical application profiles for urban bus traffic. These profiles are used as basis for further research. An operating strategy for the thermal management of an electric city bus under real driving conditions is developed using the simulation model. Results are presented, which show that the overall energy demand decreases due to an improved, application profile-dependent thermal management system.
Schäfer, HenrikHellberg, TobiasMeywerk, Martin
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.
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, BalagopalMannar, Vignesh
The increasing regulatory complexity in automotive development places significant pressure on engineering teams to derive complete and correct requirements. This paper presents a multi-agent-based large language model (LLM) workflow designed to support requirement extraction from technical specifications and regulatory documents in compliance with automotive requirement guidelines. The approach structures the requirement derivation process across collaborating agents that interpret specification and regulatory text, generate candidate requirements for the early engineering activities, and cross-validate their outputs to improve consistency and traceability. To evaluate the applicability of the workflow in an industrial context, we applied it to the draft Euro 7 emissions regulation. The agents produced requirements for relevant functional domains, which were subsequently reviewed by domain experts at FEV. The evaluation focused on correctness, completeness, and coverage. Results indicate that the agentic workflow can achieve high alignment with expert expectations, demonstrates robust coverage of regulatory intent, and reduces manual effort in the early requirements engineering phase. The findings highlight the potential of structured multi-agent LLM systems to accelerate compliant software development processes and to enhance the reproducibility and quality of regulatory requirement interpretation in the automotive domain.
Abdalla, AbdelrahmanSchäfers, LukasSchmidt, FabianSchaub, JoschkaLee, Sung-YongAndert, Jakob
The electrification of heavy-duty vehicles is a critical pathway toward improved energy efficiency in the freight sector. The current battery electric truck technology poses several challenges to commercial vehicle operations, such as limited driving range, sensitivity to climate conditions, and long recharging times. Estimating the energy consumption of heavy-duty electric trucks is crucial to assessing the feasibility of fleet electrification and its impact on the electric grid. This article focuses on developing a model-based simulation approach to predict and analyze the energy consumption of electric trucks by considering the impact of weather and geographical conditions on vehicle road load and auxiliary components power consumption, as well as the impact these factors have on driving range. Specifically, drayage trucks employed in logistics around maritime ports are used as a case study, with consideration of seasonal climate variations and geographical characteristics at different locations. The article includes results for three major container ports within the United States, providing region-specific insights into the energy requirements and driving range of the electric drayage trucks in these regions, which will inform decision-makers in integrating electric trucks into the existing drayage operations and plan investments for electric grid development.
Shiledar, AnkurVillani, ManfrediLucero, Joseph N. E.Sun, RuixiaoSujan, Vivek A.Onori, SimonaRizzoni, Giorgio
This study investigates Gasoline Compression Ignition (GCI), a family of advanced combustion strategies that can be used to achieve low engine-out criteria pollutant emissions in the heavy-duty transportation sector. In particular, high fuel stratification GCI (HFS-GCI) has been shown to have high thermal efficiencies while maintaining a highly controllable and responsive mixing-controlled combustion event. However, stable combustion at low loads has been shown to be the principal challenge to the implementation of HFS-GCI in production applications. It has also been observed that several strategies that achieve stable combustion at low loads result either in increased emissions or efficiency penalties. While the achievement and maintenance of high enough exhaust temperatures for efficient aftertreatment operation is a significant challenge at low loads even for traditional diesel engine operation, this challenge is exacerbated by the low reactivity and colder flame temperature of gasoline. In recent single-cylinder and 1D simulation studies, fuel cutout strategies have been proposed as an enabling strategy to simultaneously improve combustion stability at low loads and increase exhaust temperatures. In this study, fuel cutout strategies are studied in a prototype multicylinder heavy-duty GCI engine based on a Cummins ISX15 diesel engine. Steady-state engine studies are conducted at warm and cold idle conditions to identify combinations of cylinders that provide the most benefit. NOx and soot limits are set and the performance of cutout strategies are compared to a pre-optimized baseline. The most optimal strategies from steady-state testing are then implemented under transient test cycle conditions similar to those required under United States regulatory testing. The strategies were found to offer simultaneous improvements in stability, fuel consumption, criteria pollutants, and turbine outlet temperature. The choice of cylinders whose fuel supply was cut was seen to be important in realizing the observed benefits. The use of fuel cutout strategies offered optimal performance at all the conditions considered, offering an additional lever to improve the performance of HFS-GCI and highlighting a promising pathway to the use of gasoline-like fuels as alternatives to diesel in heavy-duty engines.
Viswanathan, Aravindh BabuZhang, YuMerritt, Brock
Passive fatigue can cause accidents with automated and regular vehicles. A proof-of-concept prototype [made with light-emitting diode (LED) matrices and white LED (WLED)] and a preliminary comparative usability test (N = 7) are used to study whether the active manipulation of simulated weather cues can be a potential countermeasure to passive fatigue. Participants rated system suitability, system impression, and their fatigue level similarly when they viewed a weather windshield heads-up display (HUD) versus a speedometer windshield HUD [no significant differences found and relatively small 95% confidence interval (CI) ranges around 0]. Qualitative analysis of interviews found that participants saw the potential value of the weather display and that display placement, dynamic graphics, and user activation were commonly mentioned themes. These results suggest the concept is theoretically possible, though further work is needed to prove the concept in practice.
Ensafjoo, MohsenLi, Jamy
SAE TOMORROW TODAY - What Baja SAE Teaches That College Can?t135746/26/2026
What does it really take to engineer under pressure? From mud-soaked vehicles and broken suspensions to team dynamics and split-second decisions, Baja SAE has become a proving ground for the next generation of engineering leaders. By challenging engineering students to design, build, and race single-seat off-road vehicles capable of surviving extreme terrain, Baja SAE requires every team to use the same 14 hp Kohler engine -- creating an even playing field and putting the focus on innovation, durability, and teamwork. Listen in as Honda's Adam Hussemann and TTX Company's Jason Rounds pull back the curtain on the intense, unpredictable world of Baja SAE competitions and how they prepare students for careers in manufacturing, mobility, and beyond. After hearing this conversation, you'll understand why more and more companies value Baja experience just as much as a perfect GPA. 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
As a contribution to the reduction of greenhouse gas emissions in the transportation sector, the indicated efficiency of SI engines can be increased via thermal swing coatings. Thereby, a decrease in greenhouse gas emissions can be achieved, although not at all operating conditions. Here, the often-observed increased hydrocarbon emission partially overcompensates the reduced wall heat losses. The main root cause is always attributed to the increased surface roughness and porosity, leading to an increased crevice volume. Further investigations were performed at a single-cylinder engine equipped with a FTIR for species analysis of hydrocarbon emissions. A comparison of direct injection and port fuel injection were performed for RON95 E10 and methanol to assess the influence of mixture preparation. 3D CFD was used to additionally investigate the in-cylinder processes. The comparison of port fuel injection and direct injection showed a significant influence on the fuel hydrocarbon emissions for the direct injection when the thermal swing coating was applied. The effect is more pronounced for methanol. For port fuel injection nearly the same or reduced fuel hydrocarbon emissions can be observed. This is mainly attributed to an increased wall film agglomeration at the piston for the thermal swing coating in case of direct injection, which can be observed in 3D CFD. Due to the low thermal effusivity of the coating, the droplet impingement leads to a notable decrease in the surface temperature. This results in lower evaporation of the fuel and a longer droplet lifetime. Consequently, a fuel wall film is still present at top dead center after ignition leading to additional hydrocarbon emissions.
Fischer, MarcusPischinger, Stefan
This document provides recommendations involving BEV battery data retention and battery design that enhance the potential for BEV battery reuse and serviceability and that can improve recyclability. These recommendations have been developed by a group of professionals skilled in the secondary-use of batteries and in the research, development, and manufacture of BEV batteries and battery systems.
Secondary Battery Use Committee
Sound source localization is a fundamental capability for environmental awareness in a wide range of applications, including automotive or automated vehicles. Microphone-array-based signal processing techniques are widely used for this task. However, achieving sufficient localization accuracy often requires a large number of microphones and wide array apertures, which can be incompatible with limited installation space and cost constraints. Moreover, standard array-processing methods often rely on free-field transfer functions. In environments with reflections, diffraction, and scattering, particularly under non-line-of-sight conditions, this mismatch can degrade both accuracy and interpretability. This paper presents a methodology for sound source localization in partially known environments that addresses these challenges by combining two ideas. First, the method reduces sensor requirements by exploiting sequential pressure measurements acquired at different spatial locations along a moving receiver trajectory. Second, environmental effects are incorporated through an approximate acoustic model derived from rough geometric cues assumed to be retrievable from visual sensing modalities. Geometric and acoustic parameters are treated as unknowns and estimated jointly with the source location, reducing the need for precise prior environmental knowledge. Numerical simulations validate the approach in two representative scenarios: (i) a single source in the presence of a wall with unknown absorbing properties and unknown distance, and (ii) a T-junction configuration where the source is not in direct line of sight. The case studies establish proof-of-concept feasibility and highlight the potential of jointly leveraging single or dual sequential measurements and approximate environmental information while maintaining low modeling and computational complexity.
Pirro, Giovanni BattistaNijman, EugeneDeckers, ElkeDenayer, Hervé
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, GabrielSaur, LukasSchwarz, ManuelZemsch, StefanBecker, Stefan
For analysing flow and acoustic induced structural vibration, a fully run time coupled framework combining a hybrid CFD-CAA approach with a modal response simulation was validated and presented at the ISVNH 2022 (SAE Technical Paper 2022-01-0938). In this paper i We apply this CFD–CAA–modal coupling method to a series-representative bonnet geometry and demonstrate its capability to capture flow and aeroacoustically driven vibration with two-way coupling. ii We analyse the modal properties of the bonnet and show that confined air volumes beneath the bonnet can introduce significant fluid loading effects, which are already embedded in experimentally validated FE modal models and must therefore be treated carefully in two-way coupled simulations. iii We validate the fully coupled aeroelastic simulation against wind-tunnel measurements with undisturbed inflow, show close agreement with the measured vibration response and analyse that the dominant excitation is in this case from below the bonnet due to acoustic pressure fluctuations.
Schwertfirm, FlorianOcker, JoergHartmann, Michael
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, EvanEandi, Giacomo
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, TheophaneCardillo, MarcoCriscione, MattiaGerges, YoussefMassocco, Andrea
This work presents a modular engineering methodology (DiPhyBa - Digital Physical Balance) for the virtual validation of Noise, Vibration, and Harshness (NVH) performance in automotive development. The approach addresses the inefficiency of repeated physical testing across vehicle variants by introducing a structured two-phase process—Launcher and Reskin—centered on quantitative performance indicators with formal acceptance thresholds. In the Launcher phase, a digital replica of the base vehicle is built and iteratively correlated with physical test data. Validation is governed by objective indicators of confidence, conformity, and correlation, each evaluated against predefined thresholds. Once validated, the model becomes a certified reference, enabling its reuse across derivative configurations in the Reskin phase. Physical testing is only required if indicators fall below threshold, with a final gate test on pre-series vehicles ensuring industrial robustness. DiPhyBa formalizes the decision to replace physical testing with simulation, introducing automation, traceability, and repeatability into the validation workflow. The method is scalable across platforms and adaptable to other technical domains such as durability, thermal, and safety. The long-term industrial ambition is to progressively minimize redundant NVH testing on vehicle variants. Early applications demonstrate significant reductions in development time and cost, while enhancing confidence in simulation-based decisions. DiPhyBa bridges the gap between digital simulation and industrial validation, offering a new standard for virtual engineering in the automotive sector.
Celiberti, LuciaCamia, Andrea
To minimize noise caused by interior components rubbing against each other, automotive materials are usually tested in advance with the established stick-slip method according to VDA standard 230-206. This procedure is widely used for soft materials, upholstery and plastics. However, it is limited to constant climatic and selected loading conditions. Contrary, in real application, changing climates and dynamic excitations can nevertheless trigger noise issues even in materials rated as suitable in the prior tests. To address this gap, a new test method has been developed that evaluates the stick-slip behavior of material combinations for a wide range of loading and climatic conditions. Conducted in a climate chamber with a standard stick-slip test bench, the procedure applies sinusoidal excitations, dynamic climatic shifts and advanced data analysis. In addition to the usual results the new method also evaluates realistic scenarios such as starting a vehicle in different seasons or sudden jolting movements with high excitation speeds. The result is a detailed map of stick-slip behavior as a function of excitation speed and climate. While requiring a similar level of effort as the traditional test, this approach delivers far greater insight. It enables a more reliable optimization of materials and facilitates targeted material selection for specific applications. In this manner, it can not only contribute to improve product quality but also to achieve quiet interiors and customer satisfaction.
Fritz, SusanneStrangfeld, Martin
Noise pollution is a major environmental and health challenge, yet its strong spatial and temporal variability makes comprehensive mapping highly complex. Current approaches under the European Noise Directive (END) provide only partial coverage and often lack temporal dynamics. The NoiseSphere project, funded by the Austrian Research Promotion Agency FFG, develops an AI-based methodology for dynamic, large-scale noise prediction and mapping. A machine learning model is trained on heterogeneous data sources, including semantically enriched open Sentinel-2 satellite imagery, OpenStreetMap road data and existing noise maps. The model is refined through integration of noise emission data and validated using targeted in-situ measurements. A case study in an urban environment (Graz, Austria) demonstrates the model’s applicability. By combining remote sensing, traffic dynamics, and machine learning, NoiseSphere enables predictive noise mapping even in regions not covered by current legislation. This approach provides a scalable tool for evidence-based environmental planning, health risk assessment, and policy support.
Girstmair, Josef
The closed-cycle hydrogen-fueled argon power cycle is a zero emissions concept that combines a carbon-free fuel with argon as a diluent replacement for nitrogen. The lack of nitrogen in the argon power cycle results in zero NOx emissions on an internal combustion engine platform. There is also massive efficiency improvement because argon is monatomic and has a very high ratio of specific heats. However, this will also result in combustion temperatures and pressures exceeding those normally achieved on an air-standard engine platform. The literature shows conflict between modeling, which promises incredibly high efficiency gains, and experiment, which show more modest efficiency gains. This work combined thermodynamic modeling, literature analysis, and experiments to understand this discrepancy and ultimately understand what level of efficiency gain can be expected for the argon power cycle. It was found that while low compression ratio engines stand to see the largest relative efficiency improvement, high compression ratio engines are the ones that can ultimately achieve ~60%+ efficiency, corresponding to a 15–20% relative improvement in efficiency over an air-standard engine platform operating at or above 50% efficiency. The elevated temperatures and pressures of the cycle result in knock in spark ignition, so either a high compression ratio knock mitigation strategy or mixing-controlled operation is required. Experiments conducted using a diesel-fueled compression ignition engine showed that a 30% argon replacement resulted in ~6% and full nitrogen replacement with argon resulted in ~14% relative efficiency improvement at 8 bar gross indicated mean effective pressure (IMEPg) without intake boosting on a heavy-duty engine with a compression ratio of 20.0 and late intake valve closing, agreeing with modeling results. The key takeaway to match modeling and experimental trends is to accurately model heat transfer, which increases significantly for the argon power cycle.
Gainey, BrianAhrling, ChristofferTunestal, PerTuner, Martin
Mitigation of harmful emissions from oil-based engines is essential to avoid environmental pollution and comply with various NOx regulations across the globe. This can be partially achieved by injecting urea to produce ammonia (NH3), which reacts with NOx in a catalyst to produce harmless nitrogen (N2) and water vapor (H2O). However, urea deposition in a selective catalytic reduction (SCR) system poses a significant threat to the NOx removal process by not only reducing the urea conversion rate but also blocking the incoming flow and causing an additional pressure drop. Numerical modeling of this urea deposit formation involves multiphase flow physics coupled with accurate heat transfer calculations. Additionally, since urea decomposes into various by-products like biuret, cyanuric acid (CYA), and ammelide, detailed chemical kinetics modeling is equally important. Accurate and fast computational fluid dynamics (CFD) simulations can help accelerate SCR system design cycles, leading to a reduction in experimental cost. In this study, we employ CONVERGE CFD to model the whole process from urea–water solution (UWS) injection to droplet evaporation and decomposition (using 12-step detailed-chemistry), film formation, and final deposition as a solid. A new spray-wall interaction model is introduced based on published experimental observations. The efficacy of the numerical model is demonstrated using an S-bend tube, where the UWS is injected just at the end of the S-bend. The predicted deposit mass and patterns are compared with the experiments, and good agreement is observed for three different operating conditions. A novel boundary morphing feature is activated to model the deformation of the tube walls because of urea deposition. Finally, to accelerate the simulations, a spray database approach is introduced. Coupled with the fixed-flow feature, this results in around 58% reduction in computational time without compromising accuracy. The present work thus provides a numerical framework to accurately capture urea deposition with a fast turnaround time.
Morab, Sumant R.Khalate, SurajAnsari, ShoaibYang, Pengze
Knowing a detailed operating cycle is critical for developing and testing equipment. Operating cycles can be separated by two clear distinctions: (1) regulatory or non-regulatory and (2) application at the engine-only or full machine level. The Environmental Protection Agency’s (EPA) Nonroad Transient Cycle (NRTC) may be a good representation of engine use in many types of equipment, but there is a gap in standardized and validated drive cycles specifically for nonroad material handlers. Lacking a standardized drive cycle makes it difficult to accurately benchmark machine performance and validate new powertrain technologies. The objective of this investigation is to illustrate the development of a custom drive cycle augmented with real-world customer use data that serves multiple purposes: (1) understand the range of operation and utilization that formulated inputs for electrified architecture analysis and (2) develop a repetitive and consistent maneuver to establish baseline energy consumption enabling equivalent comparison to future electrified prototype builds. This article presents a solution specifically for a 23-ton nonroad material handler in which material handling, machine transport, and extended idle were homologated to form representative short cycles defined by machine velocity and hydraulic cylinder position. The most intensive material handling short cycles had a load factor of 40% and an average fuel rate of 16 L/h. Combined with a visual aid, the short cycles exhibited low variability, having less than 5% root mean square (RMS) error in lift and reach position with respect to the average. The machine’s performance on these short cycles at the Advanced Power Systems Research Center (APSRC) was compared to results from two real-world customer locations operating the instrumented test machine in a cyclical manner, and for similar ground conditions were found to be comparable in fuel consumption.
Czarnecki, AlexanderGoodenough, BryantWorm, JeremyRobinette, DarrellLaTendresse, PhilWestman, John
Agricultural vehicles operating in rough environments experience increased fatigue damage accumulation, which may decrease machine safety and reliability. Autonomous agricultural machines offer an opportunity to incorporate fatigue damage considerations into path planning. This work investigates whether machine learning can predict fatigue damage to a tractor chassis using light detection and ranging (LiDAR)-based terrain features, vehicle speed, and rotational vehicle state data (e.g., triaxial angle, angular velocity, and angular acceleration). Fatigue damage was estimated using the Rupp filter and the Durability Transfer Concept. Following poor predictive performance of the machine learning models, an exploratory analysis of damage histograms, dominant frequency, and acceleration magnitude was performed. Results indicated that most estimated fatigue damage occurred in the 0–2 Hz band, which coincides with the frequency range of terrain-induced acceleration. On-road driving led to the greatest fatigue damage, potentially due to the harder driving surface and increased vehicle speed. Differences between root mean square (RMS) acceleration magnitude and fatigue damage indicate that isolated high-magnitude events may have contributed to increased estimated fatigue damage. Several suggestions for future development were identified. Identification of the endurance limit of the tractor chassis will permit the removal of nondamaging events, improving label accuracy. Furthermore, the presence of a front-loader implement may have impacted chassis acceleration. Thus, a comprehensive dataset with multiple implement configurations is needed to determine the influence of implement configuration on dynamics and resultant damage.
Govers, Megan EmilyHamilton-Wright, AndrewHassan, MarwanOliver, Michele L.
Emissions reduction remains a major concern for internal combustion engines in view of increasingly stringent environmental regulations. To address these challenges while maintaining acceptable engine performance, a wide range of alternative fuels and fuel blends have been investigated to ensure the continued viability of CI engines. This study reports the effects of blending the oxygenated fuel diethylene glycol diethyl ether (DGDE) with hydrotreated vegetable oil biodiesel (HVO) on engine performance and emissions. The investigation is conducted on a 2.3-liter, four-cylinder, common-rail diesel engine, equipped with a variable geometry turbocharger and a high-pressure exhaust gas recirculation system. The objectives of this study are achieved by developing a one-dimensional predictive engine model using the commercial GT-SUITE software. The engine model is developed and experimentally validated, at various operating conditions and HVO–DGDE fuel blends, to predict their effects on combustion characteristics and emissions formation. The validation is performed against measurements collected at the engine test bed. The results indicate that increasing the blending ratio of oxygenated fuel leads to improvements in indicated mean effective pressure and a more favorable Soot–NOx emissions trade-off compared with neat HVO operation. The findings highlight the potential of oxygenated fuel blends to enhance CI engine performance while reducing emissions. This study demonstrates the effectiveness of combining experimental and numerical approaches to evaluate biodiesel–oxygenated fuel blends and provides insights for future research aimed at minimizing CI engine emissions.
Arain, M Wajahat RasoolFoglia, AntonioFrasci, EmmanueleVitek, OldrichPianese, CesareArsie, Ivan
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, BradleyKateregga, SunnySodre, Jose Ricardo
Low-load natural gas–diesel reactivity controlled compression ignition (RCCI) in medium-speed marine engines is constrained by an insufficient charge thermal state. This limitation leads to partial fuel oxidation, producing high methane emissions. This work evaluates the use of negative valve overlap (NVO) combined with NVO diesel injection as an in-cylinder reactivity enhancement strategy. The simulation study was performed using the University of Vaasa’s advanced thermo-kinetic multi-zone model (UVATZ), extended for reactive simulations during NVO. The extended framework was validated against test-bench data from a prototype Wärtsilä 6L20 dual-fuel engine operating in RCCI mode. The baseline low-load operating point for reforming simulations was defined by reducing the intake manifold temperature to replicate conditions close to partial misfire with 52% combustion efficiency. The parametric sweeps of NVO injection timing and ratio showed that the strategy can be used for in-cycle fast thermal management, effectively restoring complete combustion on an individual cycle basis. In simulated conditions, the best performance was obtained with an NVO injection ratio of 0.3, with the injection scheduled before top dead center. In contrast, increasing the NVO fraction beyond ~0.3 provided no benefit and led to complete misfire due to excessive reduction of main-event high-reactivity fuel. The simulations revealed a coupled thermal–chemical control mechanism. Early NVO injections stabilize combustion through recompression heat release and an increased next-cycle intake valve closing temperature. Sufficiently late injections stabilize combustion by carrying unreacted diesel into the subsequent cycle. Injections near NVO TDC primarily undergo fuel conversion to CO, H2O, and unsaturated light/mid-range hydrocarbons with negligible thermal boost, yielding an overall reactivity deficit.
Soleimani, AmirNurmi, MikaelHunicz, JacekKim, JeyoungHyvonen, JariMikulski, Maciej
Regulators and policymakers have introduced increasingly stringent limits on tailpipe CO₂ and pollutant emissions to accelerate the decarbonization of heavy-duty vehicle applications. The development of innovative propulsion technologies — such as advanced combustion systems, low-friction reciprocating components, and improved aftertreatment solutions — combined with hybridization and the adoption of alternative fuels (e.g., biogas, HVO, green hydrogen), is a key pathway for meeting future emission and GHG targets. In this study, advanced combustion systems were developed for a 13-liter diesel engine for heavy-duty truck applications, with the objective of meeting forthcoming Euro VII regulations while maximizing thermal efficiency. The combustion system architecture—including open-bowl geometry with high aspect ratio, injector nozzle with wider spray opening angle, and reduced swirl ratio—was optimized using a Machine Learning–algorithm trained on high-fidelity 3D CFD combustion data. The method enabled the identification of two optimized combustion-system “recipes”, one of which was evaluated through engine tests, which refined nozzle specifications and injection strategies, using a structured Design of Experiments (DoE) approach. Results were benchmarked against a MY24 baseline combustion system, assessing efficiency, NOx–soot trade-offs, and combustion behaviors. Based on 3D-CFD results, the advanced combustion concept achieved an improvement in Brake Thermal Efficiency (BTE) of up to +0.8% points and delivered substantial NOx reductions of up to 45%, while maintaining smoke emissions at or below baseline levels. The experimental results indicate that the advanced combustion system developments designed for next-generation heavy-duty engines can further increase BTE by up to ~1% relative to the baseline combustion system, without deteriorating the soot–NOx trade-off.
Belgiorno, GiacomoCentini, Maria PiaPezza, VincenzoCozza, Ivan F.Pesce, Francesco C.Vassallo, AlbertoColombo, GiovanniGallo, AlessandroMirzaeian, MohsenBorg, Jonathan
Hydrogen internal combustion engines (H2ICE) have emerged as a promising solution for decarbonisation of the transport sector, due to low cost and potential for rapid deployment. However, abnormal combustion and high nitrogen oxide (NOx) emissions limit stoichiometric operation, making dilution strategies essential. While lean combustion has been widely studied, combined dilution strategies of air and exhaust gas recirculation (EGR) require further investigation. This work presents experimental results from a boosted 0.5-litre spark-ignition direct-injection single-cylinder research engine equipped with high-tumble ports and cooled high-pressure EGR. Relative air–fuel ratios (lambda) of 1 to 3 and EGR rates of 0 to 40% are evaluated at 5, 10, and 15 bar of indicated mean effective pressure (IMEP) at 2000 rpm to assess effects on net indicated thermal efficiency (nITE), combustion, and emissions. A peak nITE of 43.5% is achieved at 10 bar IMEP, λ = 2.5, and 30% EGR, which can be primarily attributed to low heat losses while maintaining lower combustion losses than at higher dilution levels. NOx emissions are effectively mitigated with increasing EGR and are largely independent of lambda at 5 bar IMEP under EGR dilution. At high load, EGR is shown to be beneficial to achieve high efficiency and lower NOx at lower dilution rates, thereby reducing boosting requirements. Equivalent dilution parameters are used to investigate combined effects of EGR and air dilution, from a mass dilution perspective with the mass dilution rate (MDR) and equivalent thermal reduction with the thermal dilution parameter (TDP). Indicated efficiency and unburned hydrogen emissions correlated strongly with MDR, while temperature-dependent parameters showed a high correlation with TDP. At constant engine speed, burn durations are shown to depend mainly on degree of thermal dilution, with no effect of load observed. At high dilution rates, combustion became increasingly insensitive to further dilution, indicating the presence of thermodiffusive instabilities under high levels of both EGR and air dilution.
King, AidanIslam, RezaPickering, SimonYuan, HaoMudge, HenryGiles, KarlGoyal, HarshJones, PeterAkehurst, SamEsposito, Stefania
The automotive industry is facing increasingly stringent regulatory constraints, driving the need for faster and more efficient powertrain development. This results in higher systems complexity, making internal combustion engine calibration progressively more challenging to meet performance and emissions targets. This, combined with the manual nature of traditional calibration workflows, leads to a time-consuming process that heavily relies on human expertise. Although virtualization can reduce development time and costs, the overall workflow remains largely dependent on manual decision-making and iterative refinement. In this context, this work presents a virtual calibration framework based on a genetic algorithm, aimed at the automated optimization of engine calibration maps to satisfy performance and emissions constraints, while reducing manual effort. Each calibration map is represented through a polynomial parameterization. Specifically, a generic three-dimensional polynomial with map-specific order encodes the shape of each map, ensuring smoothness which directly impact on drivability. Accordingly, the calibration problem is reformulated as the optimization of a compact set of polynomial parameters that uniquely define the full set of calibration maps, rather than individual set-point. Each candidate solution is assessed by generating the corresponding calibration maps and simulating the engine behavior through a neural-network-based digital twin, providing predictions of operating conditions, hardware limits, performance metrics, and emissions. The proposed framework was validated on a passenger-car diesel engine, considering a reduced yet representative set of calibration maps, including main injection start of injection, air mass, boost pressure, and injection rail pressure. The objective of optimization was the minimization of brake mean fuel consumption, subject to an upper bound constraint on nitrogen oxides emissions. The global optimization process explored approximately 106 different calibration candidates within about 36 hours, leveraging parallel computation on a standard laptop. The results indicate that the procedure can deliver multiple near-optimal preliminary calibration solutions, providing an effective starting point for subsequent manual finetuning.
Romano, GianvitoAglietti, FilippoSpedicato, TonioCozza, Ivan FlaminioCapra, Andrea
The ongoing efforts for reduction of the traffic-related greenhouse gas emissions and, at the same time, the mitigation of harmful pollutant emissions from vehicle exhaust emissions are important development tasks for the entire automotive industry worldwide according to demand to provide clean and efficient products. Further tightened fleet average FE standards and ultra-low limits for exhaust emissions require the continuous development of new propulsion system types. Due to the given reluctance of the end customer and corresponding low acceptance of fully electrified vehicles, especially in the commercial vehicle segment, new and innovative topologies are needed to meet regulatory requirements and maintain the high versatility of today’s dominating solutions. For further optimization of operating conditions with enhanced fuel efficiency, the technical strategy is also determined by uplifting the attractiveness of electric driving incl. the avoidance of areas with poor ICE efficiency and as well as the coverage of emission-critical operations by electric propulsion. In this context, the support provided by an electric drive on board the vehicle in a combined drive system is becoming increasingly important. This article discusses accordingly various platform strategies for hybridized Diesel powertrains in different sectors of commercial vehicle applications and delivers a comprehensive comparative analysis of different hybrid drive concepts. Specifically, several hybrid powertrain configurations that extend an electric drive platform (hybridized BEVs), such as series and parallel-series topologies, are compared with traditional parallel hybrid powertrain topologies based on internal combustion engines (ICE). The study focuses mainly on two different cornerstone applications: a large light commercial vehicle, ranging from 3,5 to 6,5 to. and a heavy-duty long-haul truck with 40…44 to. gross vehicle weight. It evaluates the advantages in terms of CO2 emissions and Diesel fuel savings and investigates the effects on emission controls aspects. In addition to technical comparisons, the paper addresses also regulatory demands and end customer merits, assessing the integrational effort and commonalities in components with pure ICE and battery electric topologies. Furthermore, it explores the additional impact of advanced operational strategies for Hybrid Diesel powertrains, incorporating insights from innovative observations from executed hybrid technology demonstrator vehicles.
Koerfer, Thomas
This work presents the development of a user-oriented software tool for the cradle-to-grave Life Cycle Assessment (LCA) of passenger cars, enabling robust comparisons of greenhouse gas emissions across heterogeneous vehicle configurations. The tool supports informed decision-making by quantifying and visualizing environmental impacts associated with alternative mobility choices over the full vehicle life cycle, including production, use, maintenance, and end-of-life stages. The proposed framework allows key parameters describing both the vehicle and its usage to be explicitly defined, including powertrain type, dimensions and weight, ownership profile (new or second-hand vehicles, partial ownership periods, leasing scenarios), annual mileage, vehicle lifetime assumptions, and the carbon intensity of fuels or electricity sources. Country-specific energy mixes are incorporated, enabling the same vehicle to be assessed under different geographic contexts and highlighting the strong dependence of use-phase emissions on local energy systems. Results are reported both as total life-cycle emissions and as a phase-resolved breakdown, improving transparency and supporting a clear interpretation of trade-offs between production, operation, maintenance, and end-of-life stages. Representative scenarios demonstrate that, under a standard European context, battery electric vehicles (BEVs) achieve a reduction of approximately 32% in yearly greenhouse gas emissions compared to a baseline Euro 5 gasoline vehicle. However, this trend reverses for low-mileage users relying on second-hand vehicles, for which emissions can increase by about 15%, emphasizing the critical role of usage patterns and ownership strategies in determining environmental benefits. The tool is designed to accommodate updated datasets, emission factors, and evolving energy scenarios, ensuring long-term applicability and enabling forward-looking analyses. Its capabilities are demonstrated across scenarios covering short- and long-term usage, multiple national contexts, and different powertrain technologies. The result is a robust and transparent assessment platform that enables users and policymakers to evaluate vehicle replacement strategies, providing quantitative insights into the interplay between technology, usage, and sustainability in mobility transitions.
Gastaldi, ChiaraCibrario, Luca
Hydrogen-fueled rotary engines offer a promising zero-emission solution for compact commercial powertrains. This study reports experimental results from the further development of a naturally aspirated, direct-injection hydrogen rotary engine by HTM. Initial applications, such as an airport baggage tractor, demonstrated technical feasibility but revealed pre-ignition that limited maximum torque. To address this, mixture formation was investigated using an experimental setup with two independently controlled injectors feeding a single rotor injection channel. The effects on operating behavior, efficiency, and NOx emissions were evaluated. The dual-injector configuration significantly shortens injection duration and improves spatial distribution of hydrogen within the combustion chamber. Enhanced mixture control suppresses pre-ignition and enables higher mean effective pressure. Systematic variation of injection timing under representative steady-state conditions also shows potential for NOx reduction through differentiated injector operation. In-cylinder pressure analysis and exhaust gas measurements provide detailed insight into combustion characteristics and abnormal events. The dual-injector setup increases torque capability and operational robustness without additional mechanical complexity, supporting the use of hydrogen rotary engines in compact hybrid systems and stationary power applications.
Endres, JonasBeidl, ChristianHerold, TimLavall, PhilippSchmidt, MarvinHofmann, SilasKahl, Jonas
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