Browse Topic: Fuels and Energy Sources

Items (37,534)
Flexible cables are widely used in aircraft and are essential for ensuring the proper functioning of critical systems and flight safety. The design and validation of these cables represent a foundational technology in enabling the transmission of electrical power and signals throughout the entire aircraft. To achieve their intended service life, appropriate protective measures and experimental verification must be implemented. Drawing on the development experience of flexible cables for a specific domestic aircraft model, this paper proposes a combined protection method designed to extend the service life of flexible cables. Experimental analysis demonstrates the practicality and reference value of this approach.
Shi, LiqingHu, HuanghuaGe, Zengwen
To address the orbital design problem for cooperative observations with multiple spacecraft in small bodies exploration, this paper proposes an orbital design method that accounts for cooperative observation effectiveness, given the primary spacecraft’s orbital parameters and observation schedule. First, to accurately compute the visible regions on the small body surface, we develop a polyhedral equal-solid-angle resampling scheme based on the Hierarchical Equal Area iso-Latitude Pixelization (HEALPix), thereby constructing a pixel-based surface grid of the small body. Then, by taking the cooperative observed area ratio and the mean instantaneous field-of-view overlap ratio as effectiveness metrics, and the maneuver ΔV as a constraint, we formulate an optimization-based search strategy to solve for the optimal orbital configuration parameters within the search space. Numerical simulations show that the proposed method produces near-circular, non-coplanar configurations that satisfy both propellant use constraints and cooperative observation requirements, providing a useful reference for engineering design.
Cao, YilinZhu, Shengying
This paper solves the problem of resource and energy constraints on orbit computing for LEO satellites. By combining MADDPG reinforcement learning and Lyapunov optimization, the paper proposes a computing framework and implements an adaptive task offloading model for space flight using a multi-agent deep actor critic algorithm, MADDPG. The joint optimization mechanism is implemented by multi-agent dynamic task offloading. Through the transformation from the state with long-term constraints into optimization of the status of queue stability, the load scheduling under threshold energy in accordance with the characteristics of energy constraints was realized by introducing Lyapunov virtual queues into the process of policy evaluation of deep reinforcement learning. The experimental results show that the proposed framework enables a lightweight preliminary calculation, balanced energy consumption to reduce resource allocation, and realizes the stable queues through adaptability of tasks under energy balance conditions, which can provide high-efficiency computing assistance and support for space orbit tasks such as monitoring remote sensing of Earth.
Yan, MingZhao, LiangXu, LexiZhou, XiaofeiHawbani, AmmarSun, Yunhe
To solve a problem that ignition anomaly can’t be detected in time, based on the thermal equilibrium equation, the space heat flow, heater heating, propellant combustion, and thermal radiation to cryogenic space are considered to build an accurate ignition temperature method for the 10 N thruster by using on-orbit true temperature. Further, considering the error of measuring the thermistor, an envelope model for the 10 N thruster ignition temperature is established. Based on the above, a detection method for the 10 N thruster ignition anomaly of on-orbit satellites is proposed. The accuracy of the method is relatively high, and the absolute error is less than 3 degrees Celsius. An anomaly can be quickly detected when the 10N thruster ignition temperature deviates from the normal trend by 3–5 degrees celsius. The method is applied to a DFH-3 satellite, and the maximum difference of 10 N thruster ignition temperature between the theoretical values calculated by the proposed method and the measured values is only 2.72 degrees celsius. It has been proven that the prediction accuracy of the proposed method is high. It plays an important role in discovering the 10N thruster ignition anomaly in time and ensuring the success of satellite orbit or attitude control.
Li, LilingTian, HuadongWei, YuboFei, DiXing, Chao
This document defines the technical guidelines for the safe integration of Proton Exchange Membrane (PEM) Fuel Cell Systems (FCS), fuel (considered to be liquid and compressed hydrogen storage types only), fuel storage, fuel distribution and appropriate electrical systems into the aircraft. Editorial Note: Today PEM systems and fuel storage represent the most mature FCS technology and currently forms the basis for this standard. Other types of fuel cell systems and fuels (including reforming technologies and electrolyzers), may be covered by a further update to this document.
AE-7F Hydrogen and Fuel Cells
This method is intended to evaluate the thermal and oxidative stability of synthetic, ester-based aviation lubricants under defined conditions of time and temperature. This method is applicable to lubricants meeting the compositional and performance requirements of AS5780.
E-34 Propulsion Lubricants Committee
In this study, high-speed back-illuminated imaging and laser-induced fluorescence (LIF) methods were employed to investigate the impingement behavior of millimeter-sized single isooctane drops on a dry solid wall and various liquid films, including isooctane and glycerol solution films of different concentrations. Various fuel spray impingement scenarios in gasoline direct injection engines were examined. High-speed back-illuminated imaging was primarily used to examine the impact of fuel drops on a dry wall and a fuel film of the same composition as the drops. The LIF method was used to examine the impact of fuel drops on the glycerol solution film, allowing for the distinction between fuel drops and the glycerol solution film. The impingement behavior varied depending on the Weber number of the incident drop and the wall condition. When fuel drops impacted the solid dry wall vertically, they spread into a circular liquid film. The outer edge of the liquid film folded and bulged, and upon reaching the maximum spreading diameter, it maintained equilibrium and did not retract. When isooctane fuel drops impacted the isooctane film, they broke and splashed, with thinner films producing stronger splashes. Additionally, the Weber number of the fuel drops significantly influenced the crown shape and splashing after impact. The impingement behavior of fuel drops on the glycerol solution film was also investigated, focusing on the liquid film morphology after impact. Based on the experimental data, empirical correlations were established between the critical Weber numbers for transitions among different crown morphologies and the dimensionless film thickness under varying film viscosities.
Yang, TianLu, LiliGuo, ZongweiSong, EnzheYao, ChongNing, YilinKe, Yun
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
In order to improve the transportation efficiency of high-speed trains, reduce the operational energy consumption and ensure the on-time arrival of trains, the operation curve optimization is regarded as a key way to achieve the above objectives. In this paper, a distributed control method and system for grouped trains based on multi-objective running curve optimization is introduced. Firstly, the train dynamics equations are established by considering the combined forces during train operation and the train driving maneuvering strategy, combining with the line conditions, and dividing the train operating conditions; secondly, combining with the virtual grouping technology, the train units are kept in a high safety and smooth tracking operation with small intervals between the train units; and then the constraints, such as setting up safety protection distance and Then, the constraints of safety protection distance and space-time safety protection are set, and with energy-saving and comfort as the optimization goals, the multi-objective hiking optimization algorithm (MOHOA) is adopted to optimize the operation curve according to the train's working conditions; finally, the high-speed train tracking and operation system model is considered to have nonlinear and parameter-variable characteristics, and is susceptible to external factors. Finally, considering that the high-speed train tracking system model has nonlinear and time-varying characteristics and is easily affected by external disturbances, a distributed control law is designed for the optimized running curve, and a sliding mode control method is adopted for tracking operation. By optimizing the running curve of the train and realizing the precise protection strategy, the control method established based on the optimized curve can ensure the smooth running of the train while improving the efficiency of railroad transportation.
Jiang, QiqiChen, GuangwuShi, JianqiangWang, DongSi, YongboLi, PengZhang, WentaoYang, Yang
This study looks into the performance traits of a pure electric car that has a continuously variable transmission (CVT) system by doing careful simulations. The research is mostly about checking how well it performs dynamically and how much better its energy efficiency is compared to regular designs. With the help of AVL Cruise software, a detailed drivetrain model was made to test things like how fast it can accelerate, its top speed, how well it climbs hills, and how much energy it uses when driven in standard ways. The simulation results show some big improvements: the CVT car can go from 0 to 100 km/h in 12.92 seconds, which is 14% quicker than expected; it can reach a top speed of 179 km/h, 15% higher than planned; and it can climb really steep hills at a 41.33% gradient. The energy efficiency analysis also found that it uses less power, consuming just 15.88 kWh per 100km under NEDC conditions and 13.72 kWh per 100km in UDC cycles, which are 21% and 24% less than before. These results prove that the CVT works well in keeping the motor running efficiently by changing ratios all the time. The study points out the technical benefits of CVT systems in making performance and energy saving balanced, but it also finds some practical problems like environmental factors and system integration issues. This work gives useful ideas for making new electric vehicle transmission systems and hints at good ways to improve them in the future.
Chen, HaishanGong, NaifaPan, YulongCai, ZhichengGao, YujieShen, XiaobingFu, XianlanChen, Keren
To minimize energy input and preheating time, this study first analyzed the energy consumption of intake air, lubricating oil, and coolant preheating through simulations. Temperature rise data were collected under various heating parameters. Next, simulations evaluated the hybrid power system’s resistance characteristics immediately after startup and the combustion parameters during the first cycle post-ignition under different temperatures. The temperature thresholds for successful start-up were identified, defining the feasible domain for optimization. Optimization calculations aimed to minimize preheating time and energy input, constrained by maximum preheating power. Results show that intake air heating has the greatest impact on start-up success, followed by lubricating oil heating. It is recommended to increase energy allocation to intake air and lubricating oil heating. This optimized strategy reduces preheating time and energy input by approximately 26% without changing the preheating equipment.
Wei, ShengchenZhao, Zhenfeng
The vehicles often accompanied by a huge impact in the collision process, high-quality and high-strength car-seats can better protect the safety of passengers. However, in the call for vehicle energy saving and emission reduction, the lightweight design of car-seats is imminent. Therefore, it is necessary to achieve lightweight seat weight while ensuring vehicle safety. Based on the dynamic condition of vehicle collision, this paper takes the rear seat of a certain model as the research object, takes multiple responses of the seat skeleton system as the target, establishes a multi-objective optimization model of the seat skeleton, determines the optimization result with the greatest comprehensive satisfaction, verifies the optimization result of the seat skeleton. The correctness and feasibility of the design method are proved.
Shao, YoulinNi, WeiyuChen, DaojiongCheng, Zhiqing
Coal is an important component of China's energy structure, mainly transported by three modes: railway, waterway, and highway. In regional coal transportation, highway transport undertakes numerous collection-distribution tasks and medium-short distance transport, playing a vital and indispensable role. Considering the characteristics of the coal highway transportation market and the demand for price indices, a three-tiered coal highway freight price index system has been established, including individual indices, classified indices, and an overall index. Using order data from the logistics platform of the Coal Big Data Center, the coal highway freight price index is compiled by adopting the internationally Laspeyres chain method. The methodological selection has passed the ADF stationarity test. Economically, the coal highway freight price index is closely correlated with coal prices, with the correlation coefficient reaching over 0.7, which can reflect about the coal highway freight market and fill the gap in market highway freight price monitoring.
Zhao, NanxiWang, XinziRong, Haoyu
The global trend towards green and low-carbon development is that hydrogen fuel cells, as a new type of green power device, have the characteristics of zero emissions and no pollution. Its basic principle is that hydrogen fuel directly converts chemical energy into electrical energy through electrochemical reactions, achieving energy conversion between fuel cells and internal combustion engines, thereby providing sustained and stable power. The PEMFC has attracted significant attention due to advantages such as fast start-up times and long lifespans. However, excessive temperature during the reaction process of solid-state hydrogen proton fuel cells can lead to a decrease in efficiency. This article studies the temperature control device of solid-state hydrogen fuel cells and finds that active temperature control technology can achieve precise temperature regulation, but it consumes more energy; the passive temperature control scheme can reduce energy consumption, but the response speed to low-temperature start-up is limited; The application of intelligent algorithm fuzzy PID significantly improves the temperature control accuracy under dynamic loads and effectively enhances the hydrogen release rate.
Ma, YueyueLiu, JingyiShi, JianLu, ZhaonaBao, Xueqin
The turbine hybrid electric propulsion system is an important form of green aviation. Unlike the single form of aviation power scheme, the hybrid energy system is flexible in architecture, uses two or more energy forms, and has diverse energy sources. Under different mission requirements, it needs to meet the requirements of mass balance, energy balance, and power demand, etc. Therefore, The control and distribution management between different energy systems have become the key to hybrid power, and power management technology is one of the key challenges in the development of aviation hybrid power control systems. This paper reviews the current structural forms of aviation turbine hybrid electric propulsion systems, analyzes the current research status of power management technology for aviation hybrid systems, and points out that the online power management method based on optimization is the best power management technology solution for turbine hybrid electric propulsion systems. Establishing a high-precision and realtime on-board power calculation model, breaking through the power management method based on the integrated flight and engine, and improving the applicability of the power management method throughout the service life are important directions for promoting the development of online power management technology.
Cai, ChangpengLiu, HaoGu, JiangweiLi, ShunmingZhang, Haibo
The way we drive has a big effect on how much energy electric cars use, so making better driving habits can help make electric cars use less energy. By utilizing a set of real EV driving data, this paper classifies and analyzes EVs from the perspective of energy consumption, and establishes an intelligent scoring system for EV driving behavior based on a decision tree model. Experimental results show that this method is able to successfully distinguish different driving behaviours and the critical driving behavior factors, such as vehicle speed, accelerator pedal change rate, etc., and braking behavior are identified. Use intelligent scoring to give driver suggestions; this way, they can improve on their driving techniques and lower their energy consumption.
Liang, YongkaiZhang, HaoLiu, YuYu, Hanzhengnan
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
Series hybrid electric vehicles (HEVs) employ an electric motor for propulsion, while the internal combustion engine operates solely as a generator under energy-efficient speed and load conditions. Owing to this architecture, series HEVs can achieve high fuel efficiency with a relatively simple control structure. However, conventional energy management systems (EMSs) often prioritize battery state-of-charge (SOC) stabilization, which can lead to frequent engine start–stop operations and unnecessary fuel consumption, particularly in short-trip driving. This study aims to enhance energy management performance in series HEVs by optimizing engine power generation timing based on predicted short-trip duration. A computationally efficient, rule-based prediction model is developed using real-world driving data, in which short-trip duration is estimated from vehicle speed and acceleration. Due to its low computational load, the proposed model is suitable for implementation in an onboard electronic control unit (ECU). The proposed control strategy initiates engine power generation when the battery SOC is low and the predicted trip duration is long, and suppresses generation when the SOC is sufficiently high or the predicted trip is short. A detailed vehicle model incorporating an engine, generator, electric motor, inverter, and battery is developed in Modelica to evaluate the proposed strategy. Simulation results demonstrate that the proposed EMS significantly reduces the frequency of engine start–stop events, leading to fuel economy improvements of 3.6% under the WLTC (excluding the extra-high phase) and 13.4% in a real-world urban–rural driving cycle, compared with a commercialized baseline vehicle. These results confirm the effectiveness and practical applicability of the proposed EMS for passenger vehicle applications.
Mizushima, NorifumiSato, AkiraKuboyama, TatsuyaMoriyoshi, Yasuo
The virtualization of powertrain systems is a key enabler for modern powertrain development. While physics-based 0D/1D simulation models provide accuracy and interpretability, these models are typically computationally demanding, prolonging the development process and usage throughout the V-cycle. Moreover, achieving real-time-capable simulation models through model simplifications remains challenging, as it often leads to significant losses in accuracy. In contrast, data-driven approaches can achieve high computational efficiency without significantly compromising model accuracy. This opens the possibility for not only online control applications, such as model predictive control or reinforcement learning, but also for computational expensive offline control prototyping using ultrafast-running data-driven digital twins. This work focuses on the elaboration of a scalable methodology for the development of ultrafast-running powertrain models for stationary and transient engine operation. This includes the efficient generation of training data with great variance, data analysis, and preparation, an optimized partitioning method using the Jensen–Shannon distance, feature engineering, model training of a multilayer perceptron (MLP), a long short-term memory (LSTM), and gated recurrent unit (GRU) network, followed by the model evaluation using test data and the concluding model deployment. In order to demonstrate the concept, a calibrated 0D/1D model of a dual-fuel marine main engine provided by WinGD Ltd. for a pure car and truck carrier is utilized as the reference physics-based model. The case study provides a comprehensive examination of the development of ultrafast-running data-driven fuel consumption models in both stationary and transient engine operation. The results show that the proposed methodology yields robust results and minimizes the loss of accuracy to 1.80%–2.14% for the MLP predicting the steady-state fuel consumption and to 0.67%–0.96% (GRU) and 1.52%–1.68% (LSTM) for predicting the transient fuel consumption, while achieving a multiple 104-fold reduction of the real-time factor (RTF) on an identical CPU.
Weller, LouisZanelli, AlessandroYang, QiruiBrutsche, MartinGrill, MichaelKulzer, André Casal
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
Hybrid-electric (xHEV) and fuel cell electric vehicles (FCEVs) are expected to play a crucial role in the transition towards sustainable mobility in both the individual and commercial transportation sectors. As their market share increases, there is a need for advanced research to enhance overall vehicle efficiency – particularly through optimized energy management systems. For FCEVs, an optimal energy management strategy is essential to ensure safe and durable operation. For xHEVs, thermal management serves as a central lever for improving efficiency and controlling emissions, making it an integral part of the overall powertrain development process. Considering today’s regulatory landscape, these aspects must be addressed early in development. Consequently, a holistic methodological framework is required, enabling not only technical robustness but also economic benefits, such as reducing engineering effort through effective frontloading. This methodology is composed of integrated simulation and testing approaches to develop components, systems, and operation strategies for future vehicles. Building on component- and system-level evaluations conducted at a dedicated thermal system testbed (ThermoLab), vehicle-level testing is required to calibrate and validate the laboratory results. To bridge the gap between the testbed and real driving events, an innovative approach is developed to replicate essential real-world boundary conditions, with particular focus on thermal and hydraulic conditions. The combination of a dedicated low-temperature extension chamber and an innovative dynamic coolant conditioning unit enables the energy-efficient transfer of thermal and hydraulic boundary conditions to a classic chassis dynamometer that was previously incapable of low-temperature testing. While the dedicated low temperature extension chamber transfers low temperature boundary conditions to the vehicles surrounding, the dynamic conditioning unit (Dynamic Module III) enables the accurate reproduction of relevant temperatures within the vehicle’s powertrain. This study demonstrates an innovative approach for the energy-efficient transfer of real-world low-temperature boundary conditions on a chassis dynamometer incorporating low-temperature extension and dynamic conditioning units as part of a holistic development methodology.
Lavall, PhilippBeidl, ChristianFiore, LuisPapavasileiou, IoannisHohenberg, GünterKalski, Christian
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
Polymer electrolyte membrane (PEM) fuel cells represent one of the most promising solutions for decarbonizing powertrain technologies, as they can be employed as carbon-free electrical power source. However, performance degradation during their operating lifetime - caused among other factors by non-uniform reactant distribution and improper membrane humidification, which may lead to the formation of local hot spots - remains a significant challenge. Computational fluid dynamics (CFD) tools represent an effective approach for investigating the transport of oxygen and hydrogen within the cell and for optimizing the geometry of PEM fuel cell flow distributors. Thus, they can be exploited in order to improve the uniformity of current density and temperature distributions over the cell active area. In this work, a serpentine flow field PEM fuel cell is considered as test case. The distributor consists of a multi-pass serpentine flow-field composed of repeated sets of five parallel channels interconnected by transverse manifolds. First, an open-source simulation library based on the OpenFOAM framework is validated against the cell polarization curve experimental data. Subsequently, a parametric analysis of the most relevant geometric parameters characterizing the flow distributor, such as channel width, channel height and manifold geometry, is carried out to assess their influence on the overall cell performance, reactants and current density distribution. The results demonstrate that appropriate optimization of the manifold geometry leads to a more uniform flow field within adjacent channels in both the anodic and cathodic distributors, resulting in an overall optimization of the pressure drop over the manifold, resulting in more efficient cell considering a balance of plant point of view.
Bulgarini, MargheritaDella Torre, AugustoMontenegro, GianlucaBaricci, AndreaMereu, RiccardoLalangui Gallegos, Jose A.De La Morena, Joaquin
This paper assesses the efficiency limits of light-duty vehicle propulsion systems based on reciprocating internal combustion engines (ICE) in the current state of the art and in the next five-year horizon, considering their combination with technologies such as electric turbocharging and hybridization, while excluding plug-in hybrid configurations so that fuel remains the primary onboard energy source. A systematic methodology is applied to evaluate the influence of key variables—heat transfer, air–fuel ratio, and compression ratio—on engine performance, integrating these variations into a simulation model to capture their interactions and effects. The resulting parametric study enables the generation of new engine maps that exploit synergies between parameters and enhance the prediction of engine behaviour across different operating conditions, forming the basis for assessing potential advancements in hybrid powertrain architectures. These maps are then used to define performance expectations for hybrid vehicles, identifying optimal parameter combinations to guide future technology development and improve efficiency in hybrid powertrain design. The proposed powertrain architectures are integrated into a representative vehicle model, considering two vehicle typologies: a compact passenger car and a sport utility vehicle (SUV). To quantify the potential fuel-consumption benefits, an intelligent energy-management algorithm is implemented to supervise and optimize system operation over a WLTC driving cycle. The results indicate that the proposed configurations can achieve fuel-consumption reductions exceeding 20%, demonstrating the effectiveness of both the powertrain designs and the control strategies. Overall, the findings highlight the significant efficiency potential of advanced ICE-based propulsion systems when combined with near-term technologies such as electric boosting and hybridization, confirming the viability of these improvements and providing a robust basis for future hybrid vehicle development focused on maximizing energy efficiency in transportation.
Pla, BenjaminDolz, VicenteSerrano, Jose R.Gómez-Vilanova, AlejandroOliva, FerminCardenas, MariaAriztegui, Javier
Fuel cell electric vehicles are described on cell, stack and system levels. In driving operation, multi-physics coupling across subsystems (reactant supply, humidification, thermal management, etc.) reshapes cell- and stack-level boundary conditions, impacting performance and degradation mechanisms. Isolated single-topic approaches on one specific level may have limited transferability, as cross-level interdependencies under changing operating conditions can negate improvements or shift limiting factors. This underscores the development of validation environments (VEs) that represent cross-level interactions and evolve as experimental evidence redirects research questions. Models such as the V-Model provide phase-oriented logic for developing VEs when validation scope, boundary conditions and acceptance criteria can be specified upfront and remain stable. However, in PEMFC VE development, experimental conclusions frequently reshape hypotheses, operating conditions and research topics across successive cycles. Consequently, existing approaches often provide limited methodological support for a traceable and repeatable evolution of VEs where iterative reconfiguration is essential. To address this need, we developed the Development Model of the Validation Environment (eMVU, German for Entwicklungsmodell der Validierungsumgebung) for PEMFC technology to enable a structured, model-based and iterative evolution of VEs. Embedded in the system triple of product engineering, the eMVU guides the iterative transformation of objectives into validation configurations (VCs) through model-based derivation of boundary conditions, test requirements and extension measures. It structures each development cycle into the five phases design, specification, implementation and commissioning, experiments and results processing, as well as derivation of measures with feedback of the resulting insights into the objectives of the subsequent cycle. The framework is demonstrated by realizing a fully functional baseline VE and deriving an additional VC enabling semi-automated operation across eMVU cycles. Their implementation and operation provide experimental evidence that both the eMVU and the resulting VE enable traceable, repeatable and targeted assessment of cross-level interdependencies with measurable impact on cell and stack behavior.
Knaier, JohannesBause, KatharinaAlbers, 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, BalagopalMannar, Vignesh
Numerical analysis was conducted to investigate abnormal combustion, a major challenge in efforts to improve hydrogen engine efficiency. Focusing on two factors that induce abnormal combustion—surface reactions and lubricating oil—numerical analysis examined the potential for each to trigger abnormal combustion. Furthermore, since it was confirmed that the autoignition prediction using a detailed chemical reaction mechanism deviates from experiments at temperatures around 800K, attempts were made to improve this issue. As a result, it was confirmed that surface reactions affect the chemical species ratio near the wall surface but have little effect on flame propagation. Regarding lubricating oil, two possibilities were investigated: the lubricating oil itself self-igniting and becoming an ignition source for the hydrogen mixture, and deposits generated from the lubricating oil generating heat and becoming an ignition source. The results of these investigations showed that autoignition occurs before top dead center in both cases: when lubricating oil is present in the mixture during the compression stroke and when deposits heated to high temperatures are present. This indicates that engine oil can induce pre-ignition. Furthermore, the effect of water vapor on ignition delay was investigated. Finally, it was confirmed that incorporating corrections for molecules possessing kinetic energy deviating from the Maxwell distribution under low-temperature, high-pressure conditions into the reaction rate calculation improves the prediction accuracy of autoignition around 800 K.
Moriyoshi, YasuoYamane, TaichiWang, ZhiyuanKuboyama, Tatsuya
In permanent magnet synchronous machines (PMSMs) ohmic losses occur in the stator windings. Reducing these losses contributes to a higher efficiency and increases the vehicles range. An effective approach to reduce frequency-dependent AC conduction loss is the use of litz wires. In addition, direct cooling helps to reduce DC conduction loss and winding temperatures. Therefore, this work presents a multiphysical modeling approach of a direct-cooled litz wire winding in a PMSM. It combines loss modeling of the winding with novel thermal and hydraulic calculation methods. AC conduction loss due to skin and proximity effect and DC conduction loss are modeled temperature dependent. Scaled-down conjugate heat transfer simulations are used to determine the heat transfer coefficient (HTC) between wires and coolant. Additionally, the pressure drop is derived and converted into parameters for use in a porous media model. The derived parameters are used to generate surrogate models to enable computationally efficient predictions. Using the developed methods a case study is carried out. The influence of the number of turns per slot, litz wire diameter and number of parallel litz wires is investigated. In order to isolate the influence of the winding configuration, the geometry of the PMSM and the coolant volume flow remain constant. Performance indicators are energy consumption during a duty cycle, winding mass and pressure drop. Based on this study it is shown that the stator winding design is a multiphysical compromise. The method enables a targeted design of the winding configuration with respect to various objectives and facilitates the assessment of their influencing factors on the overall machine characteristics under conflicting performance requirements.
Blaschke, Wolfgang MaximilianMengoni, LeonardList, AdrianKulzer, André Casal
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 optimization of energy management strategies for hybrid electric vehicles is crucial for minimizing fuel and electrical energy consumption while maintaining the energetic stability of the electrical system. Conventional heuristic, rule-based approaches typically rely on classical optimization techniques and manual calibration by experienced engineers. These methods often suffer from simplified assumptions, sub-optimality, and are increasingly time-consuming given the growing complexity of modern hybrid powertrain architectures. This research proposes a novel methodology for the development of a learning-based energy management strategy (EMS) via deep reinforcement learning (DRL) to transition toward highly automated, data-based, and optimization-based development approaches. The methodology utilizes the Soft Actor-Critic (SAC) algorithm, an off-policy actor-critic method, to train an agent through experiences by interacting with an environment. The environment consists of a backward-looking, quasi-static vehicle longitudinal dynamics simulation model of an exemplary P2 plug-in hybrid electric vehicle (PHEV) combined with a database of customer-representative driving profiles. The agent learns optimal control policies through defined states and actions, optimizing a multi-criteria reward function that balances fuel efficiency against energetic stability. The framework permits the definition of both non-predictive and predictive states. Additionally, a shield function is implemented to consider hard constraints ensuring safe and stable operation. Variation calculations and sensitivity analyses regarding reward function shaping and hyperparameter tuning are conducted. The agent is trained in an offline simulation environment, and the learned policy of the trained deep neural network (DNN) is transferred into deterministic control maps, applicable to vehicle control units, ensuring interpretability, reproducibility, and compliance with certification requirements. Finally, exemplary simulation results of the DRL-EMS approach are presented and compared to benchmark equivalent consumption minimization strategy (ECMS). In conclusion, the proposed methodology enables a generally valid approach for the development of learning-based energy management strategies towards close-to-optimal strategies while reducing manual calibration effort.
Metzler, SebastianWinke, FlorianJungen, MarioSchmiedler, StefanHofmann, PeterGeringer, Bernhard
Knocking combustions in an Internal Combustion Engine (ICE) are engine damaging combustions, and reliable detection of each knocking event is very critical. Engines usually rely on piezo-electric knock sensors to monitor structure-borne noise, which outputs a complex, continuous time series signal. Typically, knock combustions have an additional noise component along with the regular combustion signal, but differentiation of knocking vs non knocking signal (signal to noise ratio) based on visual inspection of this signal alone is challenging and requires computationally intense signal processing such as Fast Fourier Transforms (FFT) or Wavelet transforms followed by manual calibration [1]. In this paper, we propose an alternative to replace traditional knock detection with more reliable time-domain alternative signal decomposition technique. Here we decompose the raw sensor signal into seasonality, trend, and residual, and use the residual component as it is seen to retain abnormalities in the signal during knocking combustion. Further, based on the amplitude of the residual, we can easily classify the combustions as low, medium, high or very high knocking events thus providing a precise and reliable detection.
Parulekar, Tushar A.Chilukuri, SandeepMahmood, Haneefa
This paper presents the development of a speed controller for e-bikes, designed as part of an energy-adaptive assistance system. The controller provides riders with appropriate support along planned routes, based on the available battery capacity. The control concept is intended for integration into existing commercial e-bikes without requiring extensive modifications to the drive system. Therefore, the rider remains part of the control loop, adjusting the support mode according to instructions from the controller. The speed controller is implemented as a rule-based state machine, enabling comprehensible design and parameterization. Since the rider must manually switch between support modes while riding, the control logic incorporates hysteresis and dead times to ensure stability, prevent oscillations, and avoid frequent mode switching. The user interface is a smartphone application that issues visual and audio instructions for switching support modes. An initial, system-independent version that relied on GPS-based speed measurement was found to be insufficiently accurate for the control task. Furthermore, it was found that detection of the pedaling state was essential for proper operation. To address these issues, a Bluetooth-based hardware adapter was developed to access relevant signals from the e-bike’s CAN bus communication system. These include pedal power, cadence and speed, which are made accessible through reverse engineering of the CAN bus. The proposed concept is evaluated in a chassis dynamometer study with 13 participants on two test profiles: a synthetic gradient profile for assessing control stability and a realistic elevation profile for dynamic evaluation. Additional measurements taken with one of the test riders at different speeds demonstrate the system’s reliability and its potential to improve the energy efficiency. The results show that, with approximately the same power brought in by the rider, only 27% more electrical energy is required to increase the average speed by 45%.
Rauch, YannickSimmann, GabrielSchneider, ManuelGoss, ChristianKriesten, Reiner
Hybrid electric vehicles rely heavily on battery pack power capability, which is often compromised by non-uniform aging and thermal gradients. Conventional battery models typically use bulk state-of-health metrics, failing to capture localized degradation that leads to current imbalances and reduced pack utility. This paper presents a multi-scale modelling framework that integrates Electrochemical Impedance Spectroscopy data into a fractional-order equivalent circuit model to simulate localized degradation in Lithium Iron Phosphate cells. Results show that the terminal voltage of LFP cells can be accurately modelled using the proposed fractional-order equivalent circuit with a discrete transfer-function implementation, maintaining root-mean-square errors below 20 mV across most state-of-health and state-of-charge conditions. The validated cell model is then extended to a degradation-aware battery pack representation. The battery pack in this work utilizes a 200-kWh, 800 V architecture consisting of five modules connected in parallel, each module composed of 13 parallel strings of 250 series cells, evaluated under multiple degradation scenarios. By integrating this pack model into a Class-8 series hybrid powertrain simulation, this study quantifies how cell-to-cell heterogeneity impacts vehicle performance under the VECTO regional delivery drive cycle. At the vehicle level, these battery constraints influence engine duty cycles and battery pack stress metrics. When localized degradation reaches up to 40% in one module while the remaining modules degrade up to 20% to 30%, such inhomogeneous degradation reduces the minimum pack terminal voltage by approximately 27% and increases peak discharge current by more than 30%, resulting in more rapid degradation. These battery-level limitations translate into higher fuel consumption by up to 6% in a charge-sustaining scenario.
Safavi, Seyed RezaHomayouni, HoomanShoa, TinaWang, JasonMcTaggart-Cowan, Gordon
The rapid adoption of electric vehicles (EVs) with longer driving range demands high-power charging solutions that are efficient, scalable, and reliable. This work introduces a comprehensive simulation framework for megawatt-scale charging systems, focusing on the integration and control of multiple DC/DC converters. With the primary objective of maximizing overall system efficiency during megawatt-scale charging operations. A multi-agent adaptive control strategy is implemented to dynamically optimize operating points and allocate charging currents across converters in real time so that each participating converter operates at its optimal operating point where the maximum possible efficiency is delivered. This multi-agent adaptive control strategy allocates not only the individual optimal operating points of the multiple DC/DC converters but rather determines the optimal number of participating DC/DC converters at each time instance during the charging session. In addition to that, the strategy provides the option of delivering the optimal charging current during each time instance, so that maximized system efficiency is guaranteed during the charging process. Simulation results demonstrate that even a small efficiency improvement of 0.5% can yield substantial environmental benefits at a scale, where a 10 MW charging park avoids nearly 0.9 GWh of energy use and more than 350 t of CO₂ emissions over 10 years. By fully passing these efficiency gains to customers, charging becomes more affordable without compromising service provider margins, while the resulting climate benefits scale directly with utilization, installed capacity, electricity prices, and system lifetime. The proposed approach enables intelligent supervisory control for next-generation high-power charging stations, combining efficiency, cost-effectiveness, and sustainability. These findings support the development of modular, resource-efficient infrastructure for future EV ecosystems.
Salah, AliaAbu Mohareb, Omar
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
This SAE Information Report SAE J2836/6 establishes use cases for communication between plug-in electric vehicles and the EVSE for wireless energy transfer as specified in SAE J2954. It addresses the requirements for communications between the on-board charging system and the wireless EV supply equipment (WEVSE) in support of detection of the WEVSE, the charging process, and monitoring of the charging process. Since the communication to the charging infrastructure and the power grid for smart charging will also be communicated by the WEVSE to the EV over the wireless interface, these requirements are also covered. However, the processes and procedures are expected to be identical to those specified for V2G communications specified in SAE J2836/1. Where relevant, the specification notes interactions that may be required between the vehicle and vehicle operator, but does not formally specify them. Similarly, communications between the on-board charging sub-system and the on-board vehicle electronics is not formally specified in this document. This document will be published as a set of steps. The intent of step 1 was to record as much information on “what we think works” and publish. The intent of step 2 is to provide refinement and missing pieces to step 1, with a an eye to early testing. This version is step 2, with the aim of providing a communication protocol for home chargers.
Hybrid - EV Committee
Stochastic preignition (SPI) or low-speed preignition (LSPI) is an abnormal combustion phenomenon observed in downsized turbocharged direct-injection spark-ignition engines at highly boosted conditions. SPI results from the ignition of the air-fuel mixture from a fuel or oil droplet or a detached deposit before the spark discharge, and its occurrence can lead to extremely high peak pressures and severe knock, which can cause physical damage to the engine. This phenomenon limits the downsizing and boosting potential of direct-injection spark-ignition engines, thereby constraining the efficiency benefits that can be achieved. The propensity for SPI to occur is impacted by engine operating conditions as well as the properties of the fuel, fuel additives, lubricant, and lubricant additives. To mitigate its occurrence, it is important to understand the factors that impact the frequency of SPI events. As this abnormal combustion phenomenon is relatively recent, there was a lack of a standard procedure to detect the impact of a parameter on SPI frequency. This study details the development and validation of an engine dynamometer test procedure—the TOP TIER™ Standardized Dynamometer Test Method to Evaluate Additized Detergent Gasoline for SPI—approved by the Center for Quality Assurance (CQA), to evaluate gasoline additives for their impact on SPI. In this project, the newly validated SPI test protocol was used to compare the relative SPI tendencies of four TOP TIER™ fuel additives at maximum retail concentration against unadditized SPI test fuel, which served as the baseline. All four fuel additives were tested three times in randomized order. The results revealed that none of the TOP TIER™ additives tested had a statistically significant impact on the SPI rate.
Gopujkar, SiddharthDavis, RichardWorm, JeremyTuma, NicShukla, PrajwalReilly, VeronicaChapman, ElanaCiaravino, JosephSeyfried, Philipp
This study focuses on a hydrogen ejector for a proton exchange membrane fuel cell (PEMFC) with a maximum power of 150 kW. Experimental tests were conducted to obtain the operating parameters of the stack under 100 kW and 150 kW conditions, which were used as simulation boundary conditions. A three-dimensional numerical model of the ejector was established and validated. Based on this model, the effects of key structural parameters—including nozzle throat radius (Rnt ), nozzle position (NXP), mixing chamber radius (Rm ), diffuser outlet radius (Rde ), secondary flow inlet radius (Rs ), suction chamber radius (Rf ), and constant-pressure mixing chamber length (Lpm )—on ejector performance were systematically analyzed. The results indicate that Rnt and Rf are negatively correlated with ejector performance, while Rs and Lpm are positively correlated. In contrast, NXP, Rm , and Rde exhibit an optimal range, leading to a single-peak characteristic in ejector performance. This research provides a theoretical basis and design reference for the structural optimization of high-power fuel cell ejectors.
Liu, GuoqingTai, ShupengXi, FuqiangLi, ZongjiJi, ShaoboWang, XiuyuWei, Hui
Understanding the physiological impact of vehicle electrification on operators remains an important but underexplored issue in commercial vehicle research. This study quantitatively evaluates the physiological fatigue of drivers and onboard crew members during real-world operation of commercial refuse-collection vehicles by comparing a diesel-powered vehicle with a fuel cell electric vehicle (FCEV). Both vehicles were operated on the same routes under comparable real-world operating conditions, including similar time periods and operational tasks, during municipal waste collection service. Heart Rate Variability (HRV) metrics were obtained from R-R interval (RRI) data recorded using a Polar heart rate sensor. The Root Mean Square of Successive Differences (RMSSD), a time-domain index reflecting short-term parasympathetic activity, and Poincaré (Lorenz) plot area (LP area), a nonlinear HRV index reflecting overall autonomic nervous system modulation, were calculated. In-cabin vibration and noise levels were also measured as supplementary context to support the interpretation of physiological responses. The results indicate that both RMSSD and LP area were higher during FCEV operation than during diesel vehicle operation. For the driver, RMSSD increased by approximately 61.65% and the LP area by approximately 49.91%. For the onboard crew member, RMSSD increased by approximately 18.79% and the LP area by approximately 46.02%. These findings suggest a consistent association between reduced vibration and noise characteristics in the FCEV and increased HRV indices, indicating reduced physiological fatigue during operation. This study provides quantitative evidence that fuel cell electric commercial vehicles are associated with improved occupational conditions, extending beyond conventional environmental benefits.
Utsumi, AtsukoYakoh, Takahiro
The clearance between the impeller and pump head is a critical parameter of the hydrogen recirculation pump used in proton exchange membrane fuel cell (PEMFC) systems, and it significantly affects performance, efficiency, and reliability. This study investigates the impact of clearance on the performance of a hydrogen recirculation pump applied in PEMFC systems. Both numerical simulation and experimental methods are employed to systematically evaluate the effects of symmetric circular clearances ranging from 0 to 0.4 mm, as well as asymmetric clearance configurations representative of manufacturing tolerances and assembly deviations. According to the research results, the pressure rise increases with the clearance decreasing under a given flow rate, and a smaller clearance would show a stronger capability to cover a larger flow rate range. The clearance impact on the performance of the hydrogen recirculation pump is found to be in the lower flow rate zone. In addition, the pressure distribution inside the hydrogen recirculation pump shows that the pressure would increase from the inlet to the outlet and increase along the circumferential direction of the impeller. The flow pressure at the inlet side is different from the flow pressure at the outlet side, which results in asymmetric clearance. And this brings a negative impact on the flow performance of the hydrogen recirculation pump. The flow performance capability of the hydrogen recirculation pump with the asymmetric clearance condition is not as good as that with a base clearance of 0.2 mm, and it is better than that with a clearance of 0.3 mm. When the flow rate is higher than 450 LPM, the clearance impact and the asymmetric clearance impact on the performance become insignificant. Based on a combined assessment of hydraulic performance and pressure stability, a clearance of approximately 0.2 mm is suggested as a potential optimal design target based on simulation results and observed trends. The simulation results show good agreement with experimental data, with deviations within 10% across the investigated operating conditions.
Xie, LuZhong, HaoTsoi, Jeffrey
Ethanol requires elevated intake temperatures to initiate autoignition in Homogeneous Charge Compression Ignition (HCCI) as a high-octane single-stage fuel. To leverage the high thermal efficiency, low engine-out NOx, and near-zero soot inherent to HCCI with ethanol, a custom piston design was developed to enable high compression ratios (CR) up to 22.5:1. This study investigates HCCI combustion with ethanol at three CRs of 17.5, 20.0, and 22.5 through equivalence ratio and boost sweeps performed to assess the reduction in the intake temperature requirement at high CRs and the emissions and efficiency trade-offs. Results indicate a clear benefit with reduced intake temperature requirements with increasing CR. However, a combustion efficiency penalty was observed at high CRs. Three-dimensional Computational Fluid Dynamics (CFD) simulations were performed using Large Eddy Simulation (LES) coupled with a detailed chemistry model to investigate the underlying mechanisms of the combustion efficiency penalty. CFD results reveal that the combustion efficiency penalty at high CR is primarily due to increased crevice mass trapping unburned or partially oxidized species and a rapid expansion effect inhibiting complete carbon monoxide (CO) oxidation.
Vedpathak, KunalKumar, MohitMotwani, RahulDatar, AdityaGainey, BrianLawler, Benjamin
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
Many high-end electric vehicles use an automatic two-speed transmission. The ability of the drivetrain to switch between two gear ratios improves vehicle performance and increases driving range. The aim of the presented research work is to transfer these advantages to small and lightweight battery-electric vehicles, which face significant cost and weight constraints and therefore cannot rely on highly sophisticated electric motors. Direct-drive systems are widely used in this vehicle class due to their simplicity and high baseline efficiency. However, they offer limited flexibility in adapting the operating point of the electric motor under varying load conditions. A two-speed transmission can overcome this limitation by enabling load point shifting, allowing the motor to operate closer to its optimal efficiency region during both urban and extra-urban driving. This results in improved energy consumption without adding substantial system complexity. Currently, only actuated transmissions are offered on the market, with automation adding a high degree of complexity and representing a major cost driver. Therefore, the focus during the concept development phase was on designing a fully mechanical, self-shifting system to meet the cost pressures of the targeted vehicle classes. Hence, the team at ITnA developed and patented a solution that enables automatic gear changes solely based on output torque, which reflects the motor load and the current driving situation. In the present work, both the operating principle of the technology and the advantages regarding the performance and efficiency of electric vehicles are described. Owing to its simple architecture and the absence of electronics, the transmission is inherently robust and durable, making it a significant contribution to the development of sustainable and affordable e-mobility for the mass market.
Napetschnig, ChristofTromayer, JuergenStückler, David
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, HaoyuLi, ZhenningWang, SiyingZhou, ZijingZhang, XiangYang, ZhifengOu, Shiqi (Shawn)Qi, Hao
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 KumarAmbalakatte, AjithGeng, SikaiGopakumar Suja, GaganBirch, AlexanderCairns, AlasdairHarrington, AnthonyHall, Jonathan
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
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
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
Items per page:
1 – 50 of 37534