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Ammonia Combustion with Active Pre-Chamber Spark Plug - a CO2-free Combustion Process2025-01-0527To be published on 11/25/2025
As a zero carbon fuel, ammonia has the potential to completely defossilize combustion engines. Due to the inert nitrogen present in the molecule, ammonia is difficult to ignite or burn. Even if the ammonia can be successfully ignited, combustion will be very slow and there is a risk of flame quenching, i.e. the flame going out before the ammonia-air mixture has been almost completely converted. Both the difficult flammability and the slow combustion result in high ammonia slip, which should be avoided at all costs. The engine efficiency is also greatly reduced. Safe ignition and burn-through can be achieved by drastically increasing the ignition energy and/or using a reaction accelerator such as hydrogen. The planned paper will use detailed 1D and 3D CFD calculations to show how high the potential of ammonia combustion in an internal combustion engine is when an active pre-chamber is used as the ignition system. As a result of the flare jets penetrating into the main combustion chamber
Sens, Marc, von Roemer, Lorenz, Rieß, Michael, Fandakov, Alexander, Casal Kulzer, Andre
Development of an Accelerated Stress Test for Fuel Cell Freeze Start Durability Using Real-World Driving Data of Light-Duty FCEVs2025-01-0526To be published on 11/25/2025
The reliability and durability of vehicles are crucial for the acceptance of new technologies by customers. Realistic test methods are necessary to ensure the lifespan of vehicles and their components, particularly regarding freeze start. This article provides an overview of the current state of research on the effects of freeze starts on the degradation of fuel cells. With this knowledge, relevant operating and boundary conditions for potential damage of the fuel cell are identified (e.g., start temperature, duration in subzero operation, dehydration). Based on these findings, the field data from the BMW demonstrator fleet of iX5 Hydrogen Next were analyzed to gain insights into realistic freeze start related stress to the fuel cells. It was found that the dynamics of heating rates and the influence of the operating strategy are best represented on a FCS. An experimental setup for a stack centered test on a fuel cell system was developed including a climatic chamber and a subzero
Schwarz, Markus, Albert, Albert, Eichel, Rüdiger-A.
Potential and Challenges of Next Generation Fuel Cell Powered Heavy-Duty Long Haul Trucks2025-01-0525To be published on 11/25/2025
Vehicle manufacturers are to reduce the CO₂ emissions of new trucks dramatically within the next decade. That requires to consider emission-free/neutral vehicles in the fleet mix. Especially for the application of heavy-duty (HD) long haul trucks, fuel cell powered trucks demand a holistic concept for the integration of the entire powertrain, its auxiliaries and the complete vehicle’s energy management. Key topics and takeaways: - Challenges of mechanical, thermal, EE and functional integration - Importance of predictive energy management for cost-efficient operation and lifetime optimization - Achievements in the latest fuel cell system developments and its impact on truck integration - Potential of further fuel cell stack improvements
Döbereiner, Rolf, Schörghuber, Christoph, Schenk, Alexander, Schubert, Thomas, Stöckl, Bernhard
Knock Phenomenon Investigation In SI Engine fuelled with Ammonia-Hydrogen mixture2025-01-0532To be published on 11/25/2025
Ammonia is one of the most promising carbon-free fuels for decarbonizing sectors relying on thermal conversion processes, such as energy production and transportation. However, ammonia exhibits combustion properties that differ significantly from conventional fuels, including a low laminar burning velocity, narrow flammability limits, and a high autoignition temperature. To enhance the efficiency and stability of ammonia combustion in internal combustion engines (ICEs), high compression ratio engines are often combined with ignition promoters such as hydrogen, which can be obtained through on-board ammonia cracking. Nevertheless, the addition of hydrogen to ammonia fuel can promote the occurrence of knock. The objective of this study is to investigate knock propensity as a function of engine parameters as combustion chamber geometries and compression ratios. Experiments were conducted at different engine speeds (1000, 1500, and 2000 RPM), across several intake pressure conditions (from
Hurault, Florian, Brequigny, Pierre, Foucher, Fabrice, Rousselle, Christine
Thermal Model of a Traction Inverter for an Automotive Application including DC-link capacitor, power modules and electrical connections2025-01-0519To be published on 11/25/2025
In automotive applications a traction inverter is used for energy conversion between battery and electrical machine. For high performance drives lightweight design is demanded. Additionally, higher efficiency of the inverter results in lower cooling requirements but is often achieved by increasing component weight. Hence, thermal modelling of the components and their interactions is essential to determine the best compromise between weight, efficiency and cooling requirements. In traction inverters the DC-link capacitors, power modules, high voltage electrical connections and low voltage devices dissipate power. In this paper the focus is on the thermal modelling of the DC-link capacitor, power modules and high voltage electrical connections and their system, as the performance of the inverter is defined by these components. The thermal models are derived based on geometries and physical properties. First, the DC-link capacitor thermal model is presented and considers the anisotropic
Blaschke, Wolfgang Maximilian, Mengoni, Leonard, Pflüger, Robin, Kulzer, André Casal
Multi-Objective Optimization of Oxyfuel Gas Engine Using Stochastic Engine Model and Detailed Chemistry2025-01-0529To be published on 11/25/2025
The energy transition initiatives in Germany’s renown coal mining region Lusatia have driven research into Power-to-X-to-Power (P2X2P) technologies, where synthetic fuel is produced from renewably sourced hydrogen and captured CO2, and converted to electricity and heat through oxyfuel combustion. This work investigates the multi-objective optimization of oxyfuel gas engine using stochastic engine model (SEM) and detailed chemistry. EGR rate, initial cylinder temperature and pressure, spark timing, piston bowl radius and depth are selected as design parameters to minimize the exhaust temperature at exhaust valve opening (EVO) and indicated specific fuel consumption (ISFC) corresponding to oxyfuel operation with different dry and wet exhaust gas recirculation (EGR) rates. The optimization problem is solved for a dry EGR and four wet EGR cases with various CO2 / H2O fractions, aiming to achieve comparable performance as in conventional natural gas / air operation, along with an energy
Asgarzade, Rufat, Franken, Tim, Mauss, Fabian
Energy and Mobility – The Illustrated Energy Primer for Modern Drivers2025-01-0517To be published on 11/25/2025
The path to carbon-neutral mobility is one of the greatest cultural transformations. Caught between industrial tradition, innovative mobility solutions, and energy providers are the drivers of 1.5 million motor vehicles. Conflicting publications on resource availability, energy efficiency, and the climate impact of different propulsion technologies add to their uncertainty. This led to the motivation to an energy guide for consumers, the „Illustrated Energy Primer for Modern Drivers“. The target audience focusses on technically interested individuals, whether as engaged citizens or as professionals. The guide presents the fundamentals of energy and power in a clear and accessible way. Typical energy demands of motor vehicles and households—both in personal use and scaled to a national level—complete this section of the guide. The guide then presents examples of energy generation systems. From coal-fired power plants to wind turbines, solar farms, and even balcony-mounted mini solar
Daberkow, Andreas
Feasibility of Ammonia as a Spark-Ignition Engine Fuel: Strategies for Combustion Stability and Engine Efficiency2025-01-0531To be published on 11/25/2025
Ammonia (NH3) is a promising energy carrier and a potentially alternative fuel to selected sectors due to its carbon-free nature and its relatively high energy density. However, its low reactivity and slow flame propagation pose significant challenges for a direct use in an internal combustion engine, and stable operation at all engine’s conditions. This study investigates three combustion strategies for utilizing NH3 in an adapted four-cylinder 2L turbocharged, compression-ignition engine, adapted for spark-ignition (SI) operation. Initially, the engine was tested using pure ammonia as fuel, obtaining high efficiencies and acceptable stability at medium/high loads. Nevertheless, intense combustion instabilities could not be avoided below a minimum load level (which increases with engine speed), making engine operation unfeasible in approximately 30% of its operating map. To address these limitations, two enhancement strategies are explored: Firstly, hydrogen (H2) doping pre-mixed with
Karageorgiou, Dimitrios, Myslivecek, Matej, Gaillard, Patrick, Gomez-Soriano, Josep, González-Domínguez, David, Lujan, Jose, Alcarria Laserna, Gerardo
Development of a Comprehensive Predictive QD Knock Simulation Model for Hydrogen, Methanol, and an Ammonia–Hydrogen Blend2025-01-0528To be published on 11/25/2025
This work presents a comprehensive predictive 0D simulation model for the knock behavior of hydrogen, methanol, and an ammonia-hydrogen blend. With the increasing focus on carbon neutrality, synthetic fuels are gaining attention as viable alternatives to fossil fuels. Their potential applications include land and marine transport, construction machinery, and automotive powertrains, sectors with high carbon dioxide emissions. As their development requires extensive experimental validation, simulations offer a cost- and time-efficient alternative. In particular, 0D simulations offer a good balance between predictive capability and computational effort, making them well suited for concept evaluations and parametric studies. In spark-ignition engines, knock is a major limitation to achieving high thermal efficiency, emphasizing the need for accurate and fuel-specific knock prediction methods. The objective of this work is to enable a predictive and versatile 0D knock modeling framework for
Benzinger, Steffen, Yang, Qirui, Grill, Michael, Kulzer, Andre Casal, Plum, Lukas, Hermsen, Philipp, Günther, Marco, Pischinger, Stefan, Hurault, Florian, Foucher, Fabrice, Rousselle, Christine
Visualisation of Ammonia Engine by prechamber igniter2025-01-0530To be published on 11/25/2025
Ammonia is considered more and more as a promising carbon-free fuel for internal combustion engines to contribute to the decarbonization of several sectors where replacing conventional engines with batteries or fuel cells remain unsuitable. However, ammonia properties can induce some challenges for efficient and stable combustion. The objective of this study is to investigate ammonia ignition and combustion development by means of passive prechamber igniter in a single-cylinder spark ignition engine with optical accesses based on natural chemiluminescence imaging to analyze flame development. The engine has a compression ratio of 9.5 and the experiments were conducted at 1000, 1500 and 2000 rpm. The experiments are focused on the lean operating limit as equivalence ratio as a function of the load, just before strong cycle-to-cycle variations and misfiring occurrence. By examining the effects of these strategies on ignition delay, flame propagation and stability, this study aims to
Rousselle, Christine Mounaim, Brequigny, Pierre, Gelé, Raphaël, Moreau, Bruno
Road Test Emulation: A Data-Driven Calibration Approach2025-01-0521To be published on 11/25/2025
The resource-intensive process of road testing constitutes an elementary part of the development of vehicle software. A significant proportion of explorative tests and adjustments for use in service are conducted during the vehicle test phase. However, the observed trends of decreasing development cycles and increasing system complexity generate a field of conflicts. In order to address this issue, this paper proposes road test emulation as a data-driven approach for continuously adapting vehicle software to the evolving overall system. Therefore, test scenarios equivalent to in-service conditions are determined based on customer data and test drives. These test scenarios enable an emulation of road testing and the analysis of the system in a real-world operational context from the early stages of the product development process. Sensitivity analyses are utilised to generate system-specific data for the vehicle under development, which is then employed to define initial parameter
Martini, Tim, Kempf, André, Winke, Florian, Auerbach, Michael, Kulzer, André Casal
Simulative temperature determination of an electric machine from test bench tests2025-01-0520To be published on 11/25/2025
One of the most important components of an electric vehicle is the drive motor. Induction motors are often used for this purpose. Power losses occur during the operation of these motors, particularly at high speeds. Among other things, this power loss corresponds to the sum of winding losses, iron core losses and mechanical losses. The power losses generate heat, causing the temperature in the rotor and stator to rise. The increase in temperature of the components inside the motor can lead to premature wear and fatigue failure. To prevent overheating, the motors are air or water cooled. Water cooling can be achieved by jacket cooling, for example. In this case, the heat generated is dissipated directly by forced convection. However, the cooling jacket makes it difficult to determine the temperature inside the motor. Determining these temperatures is necessary to prevent the motor from fatiguing prematurely. The temperatures that occur inside the motor during operation are of particular
Schamberger, Stephanie, Reuss, Hans-Christian
In-Flight Evaluation of Sustainable Hydrocarbon Fuels in Compression Ignition Aircraft Engines2025-01-0533To be published on 11/25/2025
With global air traffic projected to increase significantly in the coming decades, reducing the associated climate impact requires scalable solutions. While alternative propulsion technologies such as electric and hybrid-electric systems might offer long-term potential, their current applicability remains limited due to low energy density, limited range and scalability, and system complexity. Consequently, thermodynamic propulsion systems—such as gas turbines and piston engines—are expected to remain dominant in the medium term. In this context, sustainable hydrocarbon-based aviation fuels represent a practical and necessary solution. Certified sustainable aviation fuel (SAF) pathways are currently approved exclusively for use in gas turbines, with certification standards tailored to turbine-specific requirements. Consequently, fuel properties such as cetane number and evaporation behavior are not included in existing specifications. However, when SAF-kerosene blends are used in
Kleissner, Florian, Hofmann, Peter, Vogd, Philipp, Vauhkonen, Ville, Käkölä, Jaana, Greve, Alina
Electrode-Level Modeling of Thermal Decomposition Reactions as a Foundation for Multiscale Thermal Runaway Analysis in Lithium-Ion Batteries2025-01-0523To be published on 11/25/2025
Thermal runaway in lithium-ion batteries represents a critical safety challenge, particularly in high-voltage battery systems used in electric vehicles and stationary energy storage. A comprehensive understanding of the multi-scale processes that initiate and propagate thermal runaway is essential for the development of effective safety measures and design strategies. This study provides a structured theoretical overview of the thermal runaway phenomenon across four hierarchical levels: electrode, single cell, module, and high-voltage battery system. At the electrode level, thermal runaway initiation is linked to electrochemical and chemical degradation mechanisms such as solid electrolyte interphase decomposition, separator breakdown, and internal short circuits. These processes lead to highly exothermic reactions that, at the cell scale, can result in rapid temperature increases, gas generation, and overpressure. On the module and system levels, thermal runaway can propagate through
Ceylan, Deniz, Kulzer, André Casal, Winterholler, Nina, Weinmann, Johannes, Schiek, Werner
Safety Model for Battery Resistance Monitoring and Lifecycle Optimization2025-01-0515To be published on 11/25/2025
This paper presents a risk assessment framework to evaluate the safety implications of internal resistance growth in EV batteries, focusing on NMC and LFP chemistries. How the resistance growth affects performance, efficiency, and thermal stability, posing safety risks during the battery lifecycle. The framework integrates empirical and model-based estimation methods, including DCIR, EIS, historical regression, equivalent circuit models, and physics-based approaches. Simulations incorporate temperature, depth-of-discharge, and cycle count to predict resistance trends and their impact on power output and efficiency. A scoring system that evaluates safety risks based on state-of-resistance, state-of-health, and risk indicators, aiding battery pack selection for second and third life applications. Results show that NMC and LFP cells exhibit distinct resistance growth patterns, emphasizing the need for chemistry-specific safety strategies. The scoring system is a weightage based equation
Prakashkumar, Balagopal
Sustainable Engines with carbon-neutral fuels – Fast Adaptation for Efficient Multi-Fuel Operation by tailored charge motion design2025-01-0534To be published on 11/25/2025
As a fundamental element of global measures to reduce the carbon footprint of the commercial transport and the mobile machinery and equipment sector, carbon-neutral fuels are increasingly coming into focus for heavy applications where electrification is seems to be actually not a viable option. In addition to diesel substitute fuels, alternative energy carriers like natural gas, hydrogen, methanol and ammonia are gaining increasing attention worldwide. The energy conversion of these fuels is typically taking place on the principle of premixed combustion, which places different demands on fuel injection and mixture formation, supported by proper in-cylinder charge motion and turbulence, compared to current highly optimized diesel-like combustion. Accordingly, the demand to layout multi-fuel capable engine designs centers to a high share on the above mentioned cylinder head design that can burn these different fuels with high efficiency and at the same time support a high degree of
Koerfer, Thomas, Dhongde, Avnish, Boberic, Aleksandar, Zimmer, Pascal, Pischinger, Stefan
ANALYSIS OF FACTORS INFLUENCING THE EFFICIENCY IMPROVEMENT POTENTIAL OF A WINDING CHANGEOVER IN AN ELECTRIC MACHINE2025-01-0518To be published on 11/25/2025
The winding configuration of an electric machine has a decisive influence on the properties of a traction drive. When designing the electric drive, the optimum compromise must be found between maximum torque, maximum power and high efficiency over a wide operating range. A decisive factor in this design conflict is the choice of the winding configuration. The concept of winding switching offers a way of solving the design conflict and improving the characteristics of the drive through the additional degree of freedom of the variable winding configuration. Switching the number of parallel winding branches in a serial and parallel configuration is a promising approach to overcome the challenge of a high spread between maximum power and high efficiency in customer related driving scenarios of an electric vehicle. The aim of this study is to identify factors influencing the efficiency improvement potential of the winding switching topology under consideration compared to a reference drive
Oestreicher, Raphael, Koenen, Christian, Kulzer, André Casal
Investigation of Active Pre-Chamber Ignition on an Optically Accessible Ultra-Lean DI Hydrogen Engine2025-01-0524To be published on 11/25/2025
Hydrogen is a promising alternative to conventional fuels for decarbonizing the commercial vehicle sector due to its carbon-free nature. This study investigates the ignition and flame propagation characteristics of hydrogen in a 2-liter single-cylinder optical research engine representative of the commercial vehicle sector. The main objective was to enable high power density operation while minimizing NOx emissions. For that, ultra-lean combustion was employed to lower in-cylinder temperatures, addressing the challenge of NOx formation. To counteract delayed and unstable combustion under lean conditions, an active pre-chamber ignition system was implemented. It uses a gas-purged pre-chamber with separate hydrogen injection and spark plug ignition. Turbulent hot gas jets from the pre-chamber ignite the fresh mixture in the main combustion chamber, enabling faster and more stable ignition compared to conventional spark plugs. Additionally, the low volumetric energy density of hydrogen
Borken, Philipp, Bill, Daniel, Link, Lukas, Dinkelacker, Friedrich, Hansen, Hauke
Cellular energy architecture to secure resilient energy supply for critical infrastructure2025-01-0516To be published on 11/25/2025
Introduction of renewable energy systems offers the opportunity to achieve energy self-sufficiency or autarky in addition to contributing towards carbon neutrality by reducing the dependency on energy logistics. Amidst growing geo-political conflicts, the scenario of energy shortage or disruption of energy logistics is a major threat, especially for Europe due to the significant reliance on import of primary energy. Achieving autarky, however, requires a distinction between energy consumers that need uninterrupted energy supply and consumers that could potentially be cut-off during energy shortages to avoid prohibitive costs resulting from over sizing the system. Critical infrastructure such as hospitals, communication systems, emergency services and key mobility nodes like fuelling stations and charging points needed to sustain the services provided by them, always need uninterrupted energy supply. The architecture in current tools for optimising the design and operation of
Vijay, Arjun, Thaler, Bernhard, Köcheler, Valentin, Oppl, Thomas, Trapp, Christian
Data-Based Modeling of Power-Split Hybrids Using Cascaded Neural Networks2025-01-0522To be published on 11/25/2025
Power-split hybrid powertrains represent one of the most advanced and complex types of powertrain systems. The combination of multiple energy sources and power paths offers great potential but results in complex interactions that require improved strategies for optimal efficiency and emission control. The development and optimization of such operating strategies typically involve algorithms that demand fast computational environments. Traditional high-accuracy numerical simulations of such a complex system are computationally expensive, limiting their applicability for extensive iterative optimizations and real-time applications. This paper introduces a data-based approach designed specifically to address this challenge by efficiently modeling the dynamic behavior of power-split hybrid powertrains using cascaded neural networks. Cascaded neural networks consist of interconnected subnetworks, each specifically trained to represent individual drivetrain components or subsystems. This
Frey, Markus, Itzen, Dirk, Yang, Qirui, Grill, Michael, Kulzer, André Casal
Software Radio Based ASM Signal Ranging Delay Measurement System2025-99-0121To be published on 11/11/2025
In contemporary society, where Global Navigation Satellite Systems (GNSS) are utilised extensively, their inherent fragility gives rise to potential hazards with respect to the safety of ship navigation. In order to address this issue, the present study focuses on an ASM signal delay measurement system based on software defined radio peripherals. The system comprises two distinct components: a transmitting end and a receiving end. At the transmitting end, a signal generator, a first time-frequency synchronisation device, and a VHF transmitting antenna are employed to transmit ASM signals comprising dual Barker 13 code training sequences. At the receiving end, signals are received via software-defined radio equipment, a second time-frequency synchronisation device, a computing host, and a VHF receiving antenna. Utilising sliding correlation algorithms enables accurate time delay estimation. The present study leverages the high performance and low cost advantages of the universal
Li, Hao, Sun, Xiaowen, Wang, Tianqi, Zhou, Zeliang, Wang, Xiaoye
Intelligent Decision-Making and Trajectory Planning of Semi-Trailer Trains Under Multi-Vehicle Interference2025-99-0125To be published on 11/11/2025
Semi-trailer trains are the main force of highway freight. In a complex environment with multiple vehicles, accidents are easily caused by complex structures and driver operation problems. Intelligent technology is urgently needed to improve safety. In view of the shortcomings of existing research on its dedicated models and algorithms, this paper studies the intelligent decision-making and trajectory planning of semi-trailer trains under multiple vehicles. A local trajectory planning method based on global path planning and Frenet coordinate decoupling based on the improved A* algorithm is proposed. The smooth weight transition function and B-spline curve are introduced to optimize the global path. The polynomial function is combined with the acceleration rate to optimize the local trajectory. TruckSim, Prescan and Simulink are used to build a joint simulation platform for multi-condition verification. The simulation results show that the search efficiency of the improved A* algorithm
Song, Zeyuan, Geng, Shuai
Design and Application of UAV Disaster Reconnaissance System2025-99-0122To be published on 11/11/2025
The geological disasters along the Sichuan-Tibet Highway are frequent, and the traffic environment is complex. Traditional disaster reconnaissance methods struggle to meet the timeliness and accuracy requirements of emergency response. With the development of unmanned aerial vehicle (UAV) technology, it has significant advantages in rapid disaster information acquisition and complex terrain coverage. Considering the large elevation fluctuations, variable climate, and limited communication conditions in the study area, this paper focuses on UAV disaster reconnaissance in complex mountainous environments. By systematically summarizing and categorizing existing UAV disaster reconnaissance methods, this paper designs a UAV disaster reconnaissance system and applies it in practical engineering projects, providing technical support for disaster reconnaissance and emergency management along the Sichuan-Tibet Highway.
Wu, Guorong, Xu, Huayan, Chen, Yunjin, Tang, Luwei, Mo, Shiying, Luo, Shuzhao, Huang, Ziyang, Liu, Xianxin
Research on Overspeed Vehicle Detection Based on Fusion of Millimeter-Wave Radar and Visual Images2025-99-0129To be published on 11/11/2025
To address the limitations of conventional overspeed detection methods, this study proposes a vehicle overspeed detection approach based on the fusion of millimeter-wave radar (MWR) and vision sensors. The MWR captures target position and velocity data, while the vision sensor acquires vehicle image information. Radar-detected points are mapped onto visual images through coordinate transformation, and the Intersection over Union (IoU) method is employed to associate radar points with vision-detected vehicle bounding boxes. Subsequently, for radar-detected points exceeding the speed threshold, the corresponding vehicle images are identified, enabling real-time overspeed detection and data acquisition. This method not only facilitates prompt identification of speeding behavior but also extracts the associated vehicle images, ensuring both accuracy and informational integrity in overspeed monitoring. Experimental results demonstrate that the proposed method achieves high speed measurement
Li, Yuanchen, Wu, Zhichao, Xu, Haibo, Song, Liangliang, Huang, Hao
Research on Ship Network Security Situation Awareness and Defense Mechanism Based on Improved Spatiotemporal Attention and Deep Reinforcement Learning2025-99-0126To be published on 11/11/2025
With the development of ship intelligence, network security threats are increasing day by day. This paper proposes a ship network security situation awareness algorithm based on an improved spatiotemporal attention mechanism, and constructs a supporting defense mechanism. The algorithm accurately captures changes in network security situation through dynamic weight allocation and multi-scale feature extraction. In the experimental simulation, OMNeT++ is combined with SUMO to build a ship network simulation environment, and Maritime - CPS - Dataset and other data sets are used for testing. The algorithm in this paper is compared with ARIMA, LSTM, GRU and other algorithms. The results show that in terms of situation awareness accuracy, the algorithm in this paper reaches 95.6%, which is 27.8% higher than ARIMA, 12.3% higher than LSTM, and 10.1% higher than GRU respectively; the average response time of the defense mechanism is shortened to 2.3 seconds, which is 40% faster than the
Kong, Zeyu, Zhou, Bofei, Wan, Shiyao
Research on Irregular ITS-Assisted Covert Communication in High-Speed Railway Environments2025-99-0141To be published on 11/11/2025
To address the high security demands of HSR communication, this letter proposes a covert communication scheme using irregular intelligent transparent surfaces (ITSs) deployed on train windows. A joint optimization framework is developed to enhance covert rate under element constraints, involving ATS for topology design and NECE for beamforming and phase shift. Gradient descent is used to handle covert constraints. Simulations confirm that the proposed irregular ITS outperforms regular ITS in performance and robustness, offering a promising solution for future HSR covert communication.
Jia, Jingwen, Gao, Yunbo, Xie, Jianli
Research on Workshop Virtual Monitoring Technology Driven by Digital Model2025-99-0120To be published on 11/11/2025
In order to meet the demand for the transformation of traditional manufacturing industries into intelligent manufacturing, a virtual monitoring system for the production workshops of nuclear - key products has been built. There are problems such as poor environment, long distance and remote collaborative office in this production workshop, and managers lack information tools to master the workshop status in real time. In order to minimize the harm of nuclear radiation to the human body, in view of the problems of low transparency, poor real - time performance and low data integration in traditional two - dimensional forms, configuration software and video monitoring, a remote monitoring system for virtual workshops driven by digital models has been developed. This system realizes the remote dynamic display of real - time information in the workshop based on data collection and three - dimensional modeling technologies. Virtual monitoring technology improves the management efficiency of
Wu, Yiming, Chen, Rui, Li, Na
A Rapid Carbon Verification System for Flight Emissions Based on Process Re-Engineering2025-99-0116To be published on 11/11/2025
Aviation carbon verification plays a crucial role in China’s achievement of its “dual carbon goals”. Traditional manual sampling methods are difficult to meet the timeliness requirements of the rapidly increasing volume of flight data. A rapid verification system for flight carbon emissions designed based on process reengineering relies on three spatio-temporal verification methods: weekly cycle verification, flight segment verification, and flight tail number verification. A comprehensive verification framework that can replace manual sampling has been constructed. The system adopts a modular architecture, integrating the functions of data management and rapid verification. Experimental results show that in scenarios with 100,000 flight data, the average verification time of the system is 0.12 hours. Compared with manual methods, the efficiency has been greatly improved, and the f1 score has remained stable at over 89.5%. These findings confirm that the system has advantages in both
Ding, Weichen, Chen, Jingjie
DriVE-Net: A Multi-Objective Framework for Generating Diverse, Realistic, and Hazard-Aware Driving Scenarios2025-99-0133To be published on 11/11/2025
The progress of the automatic driving system, namely ADS, requires rigorous testing in various safety-critical scenarios to ensure its reliability in a real environment. However, most of the existing scenario generation methods can’t balance multiple objectives, such as safety, reality, and diversity, and improve learning, namely RL utility, which limits their effectiveness in revealing system vulnerabilities. In order to deal with these problems, DriVE-Net is proposed, which is a brand-new multi-objective framework for generating diverse, realistic, and danger-aware driving. DriVE-Net integrates four core dimensions: one is safety, which is quantified by advanced risk indicators, such as ADI and TIS; the other is reality, which is guaranteed by aligning the data distribution of the scenario with the real world; the third is diversity, which is achieved by targeted parameter space sampling; and the fourth is learning effectiveness, which is optimized by the gradual difficulty level of
Xie, Dongxuan, Li, Dongyang, Zhang, Youkang, Zhao, Yingjie, Hong, Baofeng, Wang, Nan
STFCT: A Multi-Timescale Spatial-Temporal Transformer for Traffic Flow Prediction2025-99-0111To be published on 11/11/2025
Accurate traffic flow prediction plays a crucial role in modern transportation management systems, enabling extensive applications ranging from congestion warning to optimized route planning. While current approaches have achieved progress in specific areas, they continue to face challenges such as multi-scale dynamics and constrained spatiotemporal modeling capacity. Addressing these limitations, we introduce a innovative model termed the Spatial-Temporal Fusion Convolution Transformer (STFCT). This framework integrates periodic patterns and traffic characteristics via adaptive spatiotemporal embeddings to produce a unified representation capturing both spatial and temporal relationships. Our architecture incorporates a gating mechanism for dynamic spatiotemporal integration, along with a temporal convolution component to simultaneously capture both short- and medium-term patterns. Experimental results from three different traffic datasets reveal STFCT’s advantages over competing
Zhou, Junhao, Liu, Ting, Jiang, Yangwei
Prediction of Automotive Seat Response Based on IPSO-BP Neural Network2025-99-0124To be published on 11/11/2025
To enhance the predictive accuracy between seat structural parameters and crash performance, a hybrid model was constructed by coupling an Improved Particle Swarm Optimization (IPSO) algorithm with a Back Propagation Neural Network (BPNN). First, a finite element model for front and rear impact of automotive seats was established based on experimental data, and the model’s accuracy was verified. Subsequently, simulations were conducted, and the results were analyzed. The Energy Absorption Mass Ratio method was used to screen the design variables, ultimately selecting 10 thickness variables and 9 material variables as design variables. Latin Hypercube Sampling was employed to divide the dataset into a testing set and a training set. Then, the Particle Swarm Optimization (PSO) was enhanced with Levy flights and a local mutation strategy, utilizing the IPSO algorithm to optimize the initial weights and thresholds of the BPNN, resulting in the establishment of the IPSO-BPNN predictive
Qiu, Yufei, Long, Jiangqi
Optimization System of E-commerce Logistics Distribution Path Based on Data Analysis2025-99-0108To be published on 11/11/2025
With the rapid development of e-commerce, the logistics industry also presents new features such as multi-level, integrated upstream-downstream operations, increasingly perfect service quality and low logistics costs. The exponential growth in online transactions and consumer expectations for faster, more reliable deliveries intensifies the pressure on logistics systems. The last-mile service network refers to the logistics nodes that have direct contact with consumers, and its geographical location and quantity will directly affect the service level, cost and customer service mode of the distribution network. However, with the rapid growth in the number of online shoppers and their imbalance on the Internet, these factors have gradually become an important basis for influencing the layout of terminal outlets. This imbalance, coupled with dynamic urban traffic conditions, renders traditional distribution planning methods inadequate. Therefore, in the e-commerce environment, how to
Tong, Tong, Gu, Xuefei, Li, Lingxiao
Multimodal Intelligent Transportation Data Fusion and Application Methods in Heavy-Duty Vehicles2025-99-0139To be published on 11/11/2025
Heavy-duty commercial vehicles (HDCVs) are the key mobile nodes in intelligent transportation systems (ITS). However, their complex operating conditions and the diversity of data sources (such as road conditions, driver behavior, traffic signals, and on-board sensors) present considerable difficulties for accurately estimating the state and perceiving the environment using a single modality of data. This requires effective multi-modal data fusion to enhance the control and decision-making capabilities of HDCVs. This paper addresses this need by proposing a customized multi-modal intelligent transportation data fusion framework for intelligent HDCVs. This paper presents a solution for establishing a multi-modal intelligent transportation data collection platform, including real-scene collection methods and simulation scene collection methods based on the SUMO-MATLAB joint simulation platform. Through three representative case studies, the application methods of multi-modal traffic data
Chen, Zhengxian, Wang, Shaoqi, Jiang, Huiming, Zhou, Fojin, Wang, Mingqiang, Li, Jun
Big Data Trajectory Analysis and Traffic Flow Framework Construction for Ship Manipulation Decision-Making2025-99-0134To be published on 11/11/2025
We present a novel processing approach to extract a ship traffic flow framework in order to cope with problems such as large volume, high noise levels and complexity spatio-temporal nature of AIS data. We preprocess AIS data using covariance matrix-based abnormal data filtering, develop improved Douglas-Peucker (DP) algorithm for multi-granularity trajectory compression, identify navigation hotspots and intersections using density-based spatial clustering and visualize chart overlays using Mercator projection. In experiments with AIS data from the Laotieshan waters in the Bohai Bay, we achieve compression rate up to 97% while maintaining a key trajectory feature retention error less than 0.15 nautical miles. We identify critical areas such as waterway intersections and generate traffic flow heatmap for maritime management, route planning, etc.
Kong, Xiangyu, Shao, Guoyu
Research on Low-Power Control of Offshore Wind Sail Stabilization Devices Based on Single Pendulum Control Simulation2025-99-0131To be published on 11/11/2025
To tackle persistent operational instability and excessive energy consumption in marine observation platforms under wave-induced disturbances, this paper introduces a novel ultra-low-power stabilization system based on pendulum dynamics. The system employs an innovative mechanical configuration to deliberately decouple the rotation axis from the center of mass, creating controlled dynamic asymmetry. In this behavior, the fixed axis serves as a virtual suspension pivot while the camera payload functions as a concentrated mass block. This configuration generates intrinsic gravitational restoring torque, enabling passive disturbance attenuation. And its passive foundation is synergistically integrated with an actively controlled brushless DC motor system. During platform oscillation, embedded algorithms detect angular motion reversals. In addition, their detection triggers an instantaneous transition from motor drive to regenerative braking mode, and transition facilitates bidirectional
Zhang, Tianlin, Liu, Shixuan, Xu, Yuzhe
Micro-Circulation Bus Route Area Identification under the TOD Concept2025-99-0136To be published on 11/11/2025
Based on the TOD (Transit-Oriented Development) concept, this paper addresses the “last mile” issue in urban public transportation. It proposes a multidimensional decision-making model for identifying micro-circulation bus route areas. By integrating indicators such as the TOD comprehensive index, short-distance demand intensity, and branch network density, relevant data is processed using FME linking ArcGIS. The model combines entropy-weighted TOPSIS and unsupervised consensus clustering analysis techniques, utilizing ArcGIS spatial analysis functions to accurately identify priority deployment areas for micro-circulation buses. Taking Jiangbei District in Chongqing as an example, the model divides the study area into four types of traffic zones: (1) Core high-density areas, which require an increase in micro-circulation bus routes due to extremely high short-distance travel demand; (2) Periphery active population areas, which require flexible shuttle services due to transit gaps and
Jiang, Tao, Jia, Xiaoyan, Li, Jie
AI-Empowered Lightweight In-Vehicle Network Security Mechanisms: From Cryptographic Algorithms to Collaborative Defense Architectures2025-99-0132To be published on 11/11/2025
With the rapid development of Internet of Vehicles (IoV) and cyber-physical systems (CPS), connected autonomous vehicles (CAVs) have also developed rapidly. However, at the same time, in-vehicle networks also face more security challenges, mainly in terms of resource constraints, dynamic attacks, protocol heterogeneity, and high real-time requirements. Firstly, the trade-offs between lightweight encryption primitives and their software and hardware collaborative design in terms of performance, resource overhead, and security strength are analyzed. Secondly, the resource efficiency of AI-based intrusion detection system (IDS) is evaluated at the edge. Finally, we propose a dynamic adaptive collaborative defense framework (DACDF), which integrates federated learning with dynamic weight distillation, blockchain authentication with lightweight verifiable delay function (Light-VDF) and cross-domain IDS with hierarchical attention feature fusion to deal with collaborative attacks in resource
Zhou, You, Zhang, Jigui, Ding, Kani, Yang, Guozhi
Multi-Objective Optimization-Based Vehicle-Cargo Matching and Route Collaborative Decision Modeling2025-99-0119To be published on 11/11/2025
Aiming at the problem of efficiency loss caused by the independent optimization of traditional vehicle - cargo matching and route planning, this paper proposes a spatio - temporal collaborative optimization model. By constructing three - dimensional decision variables to describe the “vehicle - cargo - route” mapping relationship, a multi - objective mixed - integer programming model considering transportation costs, time - window constraints, and carbon emissions is established. An improved NSGA - II algorithm is designed to solve the Pareto optimal solution set, and the TOPSIS method is combined to achieve scheme optimization. Experiments show that the collaborative optimization model reduces the comprehensive cost by an average of 12.7% and the vehicle empty - running rate by 18.4% compared with the traditional two - stage method.
Yang, Meiru, Liu, Jian
Research on Urban Traffic Congestion Optimisation Strategies Based on V2X Technology2025-99-0117To be published on 11/11/2025
This study investigates urban traffic congestion optimisation strategies based on V2X technology. V2X technology (Vehicles and Internet of Everything) aims to alleviate urban traffic congestion, improve access efficiency, and reduce tailpipe emissions through real-time collection and fusion of traffic data to optimise traffic signal control and path planning. The efficacy of the optimisation strategies under different V2X penetration rates is evaluated by conducting multi-factor orthogonal experiments in different typical congestion scenarios. The experimental results show that the V2X-based signal optimisation, path induction, and event response combination strategies exhibit significant optimisation effects in all three scenarios: node bottleneck, corridor congestion, and event induction. Under the condition of 100% penetration, the combined strategy reduces delay by 41.9% in the node bottleneck scenario, improves accessibility by 28.1% in the corridor congestion scenario, and
Xi, Chaohu, Li, Jiasheng, Qu, Fengzhen, Liu, Hongjun, Liu, Xiaorui, Wang, Chunpeng
Research on Methods for Quantitative Assessment of Vehicle Controllability Level2025-99-0101To be published on 11/11/2025
As one of the main indexes of functional safety evaluation, controllability is of critical significance. According to ISO26262 standard, by analyzing the impact of potential faults such as unexpected torque and regenerative braking force loss on vehicle controllability under different working conditions, this paper designs a vehicle controllability test scheme under abnormal motor function under multiple scenarios such as straights, lane changes and curves, and builds a test scheme under abnormal motor function. The mapping relationship between vehicle dynamic state data and controllability level provides a new idea for quantitative analysis of vehicle controllability.
Yang, Xuezhu, He, Lei, Li, Chao, Ren, Zhiqiang
Optimization of Variable Approach Lanes Using DDPG Under Real-Time Traffic Conditions2025-99-0115To be published on 11/11/2025
To better match lane usage with changing traffic needs at intersections, this study proposes a method that uses deep reinforcement learning to optimize variable guidance lanes. We apply the DDPG algorithm and introduce a feature weight adjustment mechanism that changes in real time. It reacts to key traffic indicators such as vehicle flow, average delay, and peak delay. This helps the model respond more flexibly and improves its ability to handle different situations. To make the output actions easier to manage, we revise the sigmoid function used for discretization. The reward function is also designed carefully, aiming to keep lane changes smooth and stable. We test our method in a SUMO-simulated intersection. The results show that it outperforms both fixed lane strategies and standard DDPG models. It reduces delays, lowers queue lengths, and moves more traffic through the intersection, proving its value in real-world-like settings.
Zhang, Wei, Zhang, Fusheng
2025 International Conference on Big Data, Internet of Things and Intelligent Transportation (BDIT)2025-99-0100To be published on 11/11/2025
TOC
Tobolski, Sue
Research on Off-Road Performance Optimization Strategy for Agricultural Smart Vehicles Based on Traction Control System2025-99-0118To be published on 11/11/2025
(TC)The paper presents a designed and evaluated optimal traction control (TC) strategy for unmanned agriculture vehicle, where onboard sensors acquire various real-time information about wheel speed, load sharing, and terrain characteristics to achieve the precise control of the powertrain by establishing an optimal control command; moreover, the developed AMT-adaptive SMC combines the AMT adaptive control algorithm and the SMC to implement the dynamic gear shifting, torque output, and driving mode switching to obtain an optimal power distribution according to different speed demand and harvest load. Based on the establishment of models of the autonomous agriculture vehicle and corresponding tire model, a MATLAB/Simulink method based on dynamic simulation is adopted to simulate the unmanned agricultural vehicle traversing different terrains conditions. The results from comparison show that the energy saving reaches 19.0%, rising from 2. 1 kWh/km to 1. 7 kWh/km, an increase in
Feng, Zhenghao, Lu, Yunfan, Gao, Duan, An, Yi, Zhou, Chuanbo
Fed-BNGC: A Federated Clustering Algorithm to Solve the Problem of User Heterogeneity2025-99-0110To be published on 11/11/2025
Federated learning is an emerging distributed machine learning framework that allows edge devices to co-train global models without uploading their own data to a central server, which protects users’ data privacy. However, the problem of federated learning is that there is too much heterogeneity between users, including the size of the data, the different model structure, and the quality of the device. This problem leads to the need for more communication to train a better model, which also increases the cost of communication. To solve this problem, we developed the Fed-BNGC algorithm. First of all, the algorithm can perform the first screening according to the difference between the user’s system and the amount of data, and select the users with poor system evaluation value, and these users will not participate in this training. Secondly, the second screening is carried out according to the difference of the user’s model parameters, and the user with the greatest difference from other
Yang, Shuangyu, Kan, Zhongliang
PSF-Net: Uncertainty-Aware Fusion of TabPFN and SAINT for 5G Base-Station Electromagnetic Radiation Prediction2025-99-0127To be published on 11/11/2025
With more 5G base stations coming into play, making an accurate assessment of RF-EMF exposure currently faces increasing demand to check if they meet regulatory requirements and ensure people’s safety. We present here PSF-Net, a novel deep learning network by uniting TabPFN’s meta-learned prior knowledge and SAINT’s dual attention structure; its use makes it particularly suitable to deal with applications like prediction of downlink power density and radiation level classification under different conditions within various kinds of 5G cell. A major component in the design of this approach is an uncertainty-aware gating block that determines the optimal weighting for each model output—TabPFN or SAINT—based on the estimated prediction variance as quantified via Monte Carlo sampling during training or the prediction variance calculated using inference-time dropout. In addition, a residual multi-layer perceptron (MLP) is also included to extract refined fused features and maintain a steady
Zhang, Yanjin, Yu, Zefeng
Hydro-Pneumatic Suspension Optimization for Mining Explosion-Proof Vehicles in Underground Coal Mines2025-99-0106To be published on 11/11/2025
This study investigates the critical factors influencing the performance of hydro-pneumatic suspension systems (HPSS) in mining explosion-proof engineering vehicles operating in complex underground coal mine environments. To address challenges such as poor ride comfort and insufficient load-bearing capacity under harsh mining conditions, a two-stage pressure HPSS was analyzed through integrated numerical modeling and field validation. A mathematical model was established based on the structural principles of the suspension system, focusing on key parameters including cylinder bore (195–255 mm), piston area (170–210 mm), damping orifice diameter (7–8 mm), check valve flow area, and accumulator configurations (low-pressure: 1.2 MPa, high-pressure: 6 MPa). Experimental trials were conducted in active coal mines, simulating typical mining scenarios such as uneven road surfaces (120 mm obstacles), heavy-load gangue transportation, and confined-space operations in thin coal seams (<1.5 m
Song, Yan, Liang, Yufang
Optimization of Injection Parameters for a Free-Piston Engine Equipped with Flat-Head Combustion Chamber2025-01-5075To be published on 11/11/2025
The free-piston engine represents a paradigm shift in internal combustion engine technology, with its unique structure promising efficiency gains. However, injection parameters are one of the core elements of free-piston engine performance. This study employs computational fluid dynamics analysis to optimize the spray cone angle and start of injection timing for a two-stroke dual-piston opposed free-piston engine equipped with a flat-head combustion chamber. A three-dimensional transient model incorporating dynamic adaptive mesh refinement was constructed by using CONVERGE 3.0 software. The results indicate that a spray cone angle of 25° achieves optimal fuel distribution, yielding a peak indicated thermal efficiency of 42.14% and an indicated mean effective pressure of 9.08 bar. Crucially, advancing the ignition timing to 215°CA improves mixture homogeneity but simultaneously increases peak cylinder temperatures and NOx. Conversely, delayed start of injection timings reduces NO
Xu, Zhaoping, Yang, Shenao, Liu, Liang
Analysis and Optimization of Subsidy Scheme for China Europe Express2025-99-0123To be published on 11/11/2025
The analysis of the current subsidy scheme for China Europe Express shows that its effectiveness is limited to lines starting from inland cities and lines with unsaturated demand. A bi-level subsidy optimization model was constructed and Tabu Search algorithm was applied to solve the optimization subsidy plan. The evaluation results of the optimization subsidy scheme indicate that it can more effectively increase the market share of CRE, regulate the balance of freight supply and demand to a certain extent, reduce capacity vacancies, and alleviate line congestion.
Mai, Yuanyuan, Tian, Chunlin
Evaluation of Noise, Vibration, and Harshness–Optimized Cylinder Deactivation on a Class 8 Diesel Truck with Impact on Emissions and Fuel Consumption: A Development of Strategy to Reduce Emissions and Fuel Consumption with Cylinder Deactivation While Providing an Acceptable Cabin Environment2025-01-5074To be published on 11/10/2025
Anticipated NOX emission standards will require that selective catalytic reduction (SCR) systems sustain exhaust temperatures of 200°C or higher for effective conversion performance. Maintaining these temperatures becomes challenging during low-load conditions such as idling, deceleration, and coasting, which lower exhaust heat and must be addressed in both regulatory test cycles and day-to-day operation. Cylinder deactivation (CDA) has proven effective in elevating exhaust temperatures while also reducing fuel consumption. This study investigates a flexible 6-cylinder CDA system capable of operating across any combination of fixed firing modes and dynamic skip-firing patterns, where cylinders transition between activation states nearly cycle-by-cycle. This operational flexibility extends the CDA usable range beyond prior implementations. Data was primarily collected from a test cell engine equipped with the dynamic CDA system, while a matching engine in a 2018 long-haul sleeper cab
Baltrucki, Justin, Matheaus, Andrew Charles, Janak, Robb
Time‐Sensitive Networking for Aerospace Onboard Ethernet CommunicationsIEEE/SAEAS6675 (Current)11/07/2025
This standard specifies profiles of IEEE 802.1 Time-Sensitive Networking (TSN) and IEEE 802.1 Security standards for aerospace onboard bridged IEEE 802.3 Ethernet networks. The profiles select features, options, configurations, defaults, protocols, and procedures of bridges, end stations, and Local Area Networks to build deterministic networks for aerospace onboard communications.
AS-1A Avionic Networks Committee
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