Browse Topic: Telecommunications

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The vigorous rate of new spacecraft being launched has made the accurate estimation of in-orbit environmental disturbances torques paramount to reducing attitude control performance corrosion. Leveraging telemetry from an asset in low-earth-orbit, we present a novel Adaptive Super-Twisting Sliding-Mode Observer, which interlinks three techniques heretofore decoupled: 1) saturation-constrained angular-acceleration adaptation; 2) Kalman-filter preconditioning of angular velocity; and 3) state-weighted logarithmic gain with dual leakage. Denoising of raw Euler angle sequences and detection of quasi-steady epochs are achieved with a customized Kalman update, while an adaptive band-pass stage isolates the torque-related acceleration signature. Casting these filtered data into the super-twisting form, we update the log gain on-the-fly, and twin leakage terms remove excess energy with accompanying chatter rejection—without compromising bandwidth. Head-to-head telemetry tests show a positive margin headroom on noise attenuation that has to be compared with the power-gain type counterpart and that increases with the signal roughness, thereby validating the fact that this technique refines environment torque estimates and hence strengthens robustness design envelopes in next-generation attitude-control systems.
Yin, XuDeng, YuhuiChi, Dongxiang
High-performance composite materials are widely used in the main structural components of satellites. Various cylindrical components will hit the satellite at the time. The cartridge is fixed and unchanging. Honeycomb structure and ceramic honeycomb structure are the same, the cylindrical component is lighter and can attack satellites at a greater speed under the same conditions as the propellant. In terms of mass quality, the speed can reach over 1.6 times, and ceramic honeycomb structure can have minimal kinetic energy loss and can face enemies in combat with thicker steel plates, allowing for continuous destruction. Cylindrical component remaining kinetic energy (∆E) is 3.2968e3 J, but ceramic cylindrical component ∆E is 2.082e3 J, and ceramic cylindrical component have more advantages, and there are fewer arbitrary steel balls flying.
Xu, JianYang, ZhenChang, XuefangLi, QiangZhang, KunQu, Dandan
This SAE Information Report defines the diagnostic communication protocol TP1.6. This document should be used in conjunction with SAE J2534-2 in order to fully implement the communication protocol in an SAE J2534 interface. Some Volkswagen of America and Audi of America vehicles are equipped with ECU(s), in which a TP1.6 proprietary diagnostic communication protocol is implemented. The purpose of this document is to specify the requirements necessary to implement the communication protocol in an SAE J2534 interface. This SAE Information Report describes how a tester can be connected to a vehicle to perform diagnostics using the TP1.6 protocol. Details regarding ECU to ECU communication have been left out.
Vehicle E E System Diagnostic Standards Committee
In complex urban environments, vehicle positioning based on Global Navigation Satellite Systems (GNSS) is prone to failure or accuracy degradation due to signal blockage and multipath effects. To address this issue, this article proposes a vehicle–road cooperative positioning method based on factor graph optimization for GNSS-denied environments and evaluates its performance through both simulation and real-vehicle experiments. In the proposed approach, road codes deployed on the road surface serve as absolute position references on the road surface, and high-precision vehicle position estimates are obtained in real time by fusing roadside positioning information with onboard sensor measurements using factor graph optimization. Furthermore, to reduce the experimental cost and development cycle of the vehicle–road cooperative positioning method, a performance simulation platform is developed based on the CARLA simulator, RoadRunner, and the CARLA-ROS (Robot Operating System) bridge for real-time communication between simulation and positioning modules. The platform supports road code generation and deployment, customized scenario construction, and positioning performance simulation, and a multi-objective optimization approach is employed to obtain an optimal deployment scheme for road code spacing. Finally, the effectiveness of the proposed vehicle–road cooperative positioning method is validated through both simulation and real-vehicle experiments. Real-vehicle experiments show that the proposed method reduces the average RMSE (Root Mean Square Error) by 26.6% compared with the ESKF (Error State Kalman Filter) baseline, achieving an RMSE of 0.25 m and a maximum error of 0.95 m at a vehicle speed of 60 km/h and a 10 m code spacing, thereby confirming decimeter-level continuous accuracy in GNSS-denied environments.
Shen, ChuanfuZhao, ZhiguoYan, DanshuLing, Yubin
The primary objective of this recommended practice is to confirm that vehicles can communicate a minimum set of information in accordance with diagnostic test services specified in SAE J1979-2, or the equivalent ISO 14229-1:2013 (Ed. 2) and SAE J1979-3 documents. A successful result using the SAE J1699-5 Automotive Alliance for Innovation (AAI) software for OBD-II testing indicates that the main aspects of UDS communication have been examined, but it does not provide assurance of complete compliance with all aspects of SAE J1979-2 or SAE J1979-3. SAE J1699-5 tests run with a SAE J2534 device hardware and API that is not fully compliant will result in a test failure. This specification takes precedence over all conflicts in the documents cited in this section.
Vehicle E E System Diagnostic Standards Committee
Connected and Automated Vehicles (CAVs) represent a transformative innovation poised to revolutionize roadway transportation by leveraging automated driving systems equipped with advanced sensors, high-performance computing, and communication technologies. While urban areas are the primary focus of current CAV developments, rural transportation systems risk being left behind despite the significant benefits that CAVs can bring to these regions. This article, therefore, explores the physical and digital infrastructure requirements for the safe deployment of CAVs in rural areas, drawing insights from standards, recommendations, and guidelines developed by leading standard organizations. The study highlights the specific design of physical infrastructure, including traffic signs, traffic signals, and pavement markings, and digital infrastructure, including communication, sensing, and mapping, to ensure rural communities are effectively prepared to benefit from the potential of CAVs. As its primary contribution, this article provides a comprehensive review of existing standards and guidelines relevant to rural CAV deployment. By synthesizing guidance across multiple standard-setting organizations, this review delivers a structured analytical assessment of existing standards, revealing their limitations and misalignment with rural transportation contexts while highlighting emerging good practices. The article clarifies the applicability of current guidance to rural infrastructure, identifies systemic infrastructure-related failure modes, and informs context-aware planning considerations for efficient and scalable CAV deployment in rural areas.
Zakaria, MohammedGetahun, TesfamichaelTavasoli, MahsaPandey, VenkteshSarrafzadeh, AbdolhosseinKarimoddini, Ali
This paper investigates the tracking of highly maneuverable targets during flight and the corresponding satellite scheduling problem in a space-based observation system. Based on dual-satellite measurements, a nonlinear observation equation was formulated. The J2 perturbation model and the current statistical model were utilized within an Interacting Multiple Model filtering framework to achieve adaptive estimation of the target states of the boost-glide vehicles. Building upon this framework, a greedy satellite scheduling algorithm based on IMM model probabilities is proposed. This method dynamically selects the optimal measurement set within a given prediction window to maximize observation performance. The proposed strategy is compared against rolling-horizon scheduling and fast-slow timescale scheduling approaches. Simulation results demonstrate that the proposed method effectively adjusts model weights in response to target maneuvers, enhancing adaptability during highly maneuverable phases. Meanwhile, it reduces the number of satellite switches while maintaining estimation accuracy, significantly improving scheduling efficiency and tracking continuity.
Deng, SiruiLiu, ChengzheWang, Yandong
In this paper, we focus on satellite production lines and design and implement a digital twin simulation and verification system for them. This is to improve manual documentation efficiency and provide sufficient process controllability in the small satellites’ batch production and assembly testing. We built a layered architecture. This allows the system to dynamically interact with AIT data management systems, structured process systems, and equipment data by fusing multi-source data. We also develop functional modules that combine lightweight 3D model visualization, dynamic simulation engines, and hybrid scheduling optimization algorithms. These modules can perform twin simulation, execute processes, intelligently schedule production, manage work reporting, conduct intelligent analysis, trigger anomaly alarms, and perform system management. We also dynamically simulate complex workflows like satellite transfer and automated assembly. These workflows are then verified using 3D virtual scene modeling and physical engines. We use time-series analysis to improve scheduling accuracy and multidimensional dynamic monitoring and hierarchical response to enhance production stability. In practice, the system can provide visualized control over the full process of satellite production. This greatly improves assembly efficiency and process controllability. It can also be an extensible digital way for aerospace manufacturing. The use of hierarchical architecture design and multimodal data fusion can be further applied in the complex equipment intelligent manufacturing.
Zhao, Fenghua
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
Aiming at problems such as low efficiency and poor accuracy in fault identification for traditional small satellites, this paper proposes a multi-model fusion method based on machine learning. By constructing a telemetry data preprocessing module based on the Data Generation Adversarial Network, it effectively deals with outliers and fills missing values. Combining single model methods such as polynomial curve fitting, the grey model, and the ARMA model, and introducing the Long Short-Term Memory network and Gated Recurrent Unit to fuse with these models enhance the ability to process complex data features. The prediction results of each model are fused using machine learning methods, and finally, the fused value is taken as the final prediction result. The numerical simulation results show that this prediction method can predict the anomalies of different types of satellite telemetry parameters and has achieved good results.
Liu, BiyanChen, YeGuo, Qi
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 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
Electrical/Electronic Architectures (EEAs) are continuously evolving to meet newly emerging demands. In recent years, major drivers of this evolution have been the increasing software-defined nature of vehicles and the push toward automated driving. Key technologies such as edge-enhanced functions, vehicle-to-vehicle communication, and service-oriented architectures are therefore the focus of current research efforts. This paper presents a vision of how these technologies can be used to enable cooperation between vehicles, illustrated by using parked vehicles as edge nodes. These are typically seen as obstructions, as they significantly increase the risk of missing or misinterpreting vulnerable road users such as pedestrians or cyclists. Our proposed approach to counteract this problem is the use of the parked vehicles themselves as edge nodes that support object detection or even trajectory planning. Current research primarily considers smart traffic infrastructure, roadside units, and other vehicles as potential edge nodes. Including parked vehicles as edge nodes means that, instead of acting solely as obstacles, we leverage their built-in sensors to contribute to cooperative awareness. While such cooperation will enhance the safety of automated vehicles in urban areas, several challenges arise. In this paper, we discuss how data traceability, decision-making in the presence of conflicting information, and incentive mechanisms for owners of parked vehicles can be addressed. Based on these challenges, the paper outlines requirements for future cooperative architecture and highlights the role of edge-enhanced functions, Vehicle-to-Vehicle (V2V) communication, and service-oriented architectures in enabling fully automated driving.
Lüntzel, VitusLukezic, NikolaKraus, DavidSeidel, LucaBeck, MaximilianSchindewolf, MarcSax, Eric
This article presents a cross-layer framework that integrates realistic vehicle-to-network-to-vehicle (V2N2V) delay characterization with a rigorous stability analysis of automated vehicle steering control. Both constant and network-induced time-varying delays modeled via deterministic bounds are addressed. For constant delays, delay-independent stability regions within the controller gain space are analytically derived. For time-varying delays with stochastic network origins, modeled using deterministic bounds, a refined Lyapunov–Krasovskii functional (LKF) incorporating augmented single- and double-integral terms is constructed. To establish delay-dependent linear matrix inequality (LMI) conditions, a reciprocally convex combination approach is employed to handle the delay interval partitioning, and the second-order Bessel–Legendre inequality is applied to tighten the integral quadratic bounds. The resulting LMI conditions explicitly capture the coupled effects of delay magnitude, delay variation rate, and control gains on closed-loop stability. Simulations of a lane-keeping scenario confirm that the predicted stability boundaries accurately match the closed-loop system behavior. Notably, incorporating a realistic time-varying V2N2V delay profile into the controller design reduces the lateral-state root-mean-square error (RMSE) by over 54% and decreases the settling time by a factor of 10 compared to designs relying on an average-delay assumption. However, high packet loss rates are shown to still induce residual oscillations due to information scarcity. Ultimately, these results elucidate delay-induced instability mechanisms and provide practical guidelines for designing delay-robust steering controllers for connected and automated vehicles.
Li, JialinLu, JianweiWei, HengAo, Di
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
Noise pollution is a major environmental and health challenge, yet its strong spatial and temporal variability makes comprehensive mapping highly complex. Current approaches under the European Noise Directive (END) provide only partial coverage and often lack temporal dynamics. The NoiseSphere project, funded by the Austrian Research Promotion Agency FFG, develops an AI-based methodology for dynamic, large-scale noise prediction and mapping. A machine learning model is trained on heterogeneous data sources, including semantically enriched open Sentinel-2 satellite imagery, OpenStreetMap road data and existing noise maps. The model is refined through integration of noise emission data and validated using targeted in-situ measurements. A case study in an urban environment (Graz, Austria) demonstrates the model’s applicability. By combining remote sensing, traffic dynamics, and machine learning, NoiseSphere enables predictive noise mapping even in regions not covered by current legislation. This approach provides a scalable tool for evidence-based environmental planning, health risk assessment, and policy support.
Girstmair, Josef
The integration of Electric Vehicles (EVs) as active grid resources represents a pivotal shift towards decarbonization. However, the implementation of effective Vehicle-to-Everything (V2X) services faces technical challenges regarding interoperability, predictive management, and battery health preservation. This work presents a comprehensive system design and research methodology developed within the framework of the FLEXV2X project, aimed at addressing interdependencies within a unified bidirectional charging ecosystem. The proposed scientific framework addresses two complementary timescales. At the device level, the study details the modelling and optimization of bidirectional converters, focusing on control algorithms designed to ensure robust dynamic response and efficiency. Building upon this hardware foundation, the paper describes a system-level optimization strategy. By employing open-source cyber-physical modelling, the architecture simulates complex EV-grid interactions. This layer integrates Artificial Intelligence (AI) algorithms to forecast stochastic variables such as renewable generation and fleet availability, driving a rule-based optimization engine. This dispatching logic will also be constrained by novel battery aging models, calibrated through experimental cycling stress-tests, balancing grid flexibility services with the preservation of the vehicle’s asset value. The effectiveness of this multi-layered design is assessed through a validation roadmap involving real-world deployment of a corporate mobility hub connected to a 10 MW wind farm, and a large-scale urban car-sharing fleet.
Lutzemberger, GiovanniBarater, DavideCeraolo, MassimoFera, CesareLeaver, IanPasini, Gianluca
Researchers discover texts, phone calls, military communication, internal corporate networks all easily eavesdropped on using off-the-shelf equipment. University of California San Diego, La Jolla, CA With $800 of off-the-shelf equipment and months' worth of patience, a team of U.S. computer scientists set out to find out how well geostationary satellite communications are encrypted. And what they found was shocking. Close to half of the communications beamed from satellites to the ground that the researchers were able to listen in on were not encrypted. This included sensitive data including cellular text messages, voice calls, as well as sensitive military information, data from internal corporate and bank networks, and the in-flight online activity of airline passengers.
In today’s global aviation industry, passenger experience is strongly influenced by effective communication. In-flight announcements, often limited to English and a single local language, can create confusion and stress for international travelers who may not be fluent in either. This communication gap not only impacts passenger comfort but also poses potential risks in conveying time-sensitive or safety-critical information. Recent advances in Generative Artificial Intelligence (GenAI), particularly in speech recognition, neural machine translation, and naturalistic text-to-speech, provide a pathway to overcome these challenges. This paper explores the concept of real-time multilingual in-flight announcements delivered in each passenger’s preferred language through connected headphones or personal devices. The proposed system architecture integrates speech-to-text conversion, language translation, and speech synthesis with aircraft infotainment platforms. Potential applications range from pre-generated multilingual safety messages to long-term visions of fully personalized, real-time translations with minimal latency. Benefits include improved inclusivity, accessibility for hearing-impaired passengers, and enhanced brand differentiation for airlines. Challenges such as regulatory certification, translation accuracy, latency constraints, and hardware integration must be addressed. Beyond aerospace, this capability has cross-domain relevance in automotive, railways, and public services, making it a promising area for future customer experience innovations.
Mishra, AshwiniKature, KartikPatil, Ashish
Global Navigation Satellite System (GNSS) receivers are widely being used in aerospace as well as automotive applications primarily for navigation applications. ISRO uses indigenously developed GNSS receivers in its Launch vehicles (LV) mainly for POD (Preliminary Orbit Determination) and for INS aiding in long duration missions. Advanced GNSS receivers are being developed and used in ISRO’s new generation launch vehicles for closed loop guidance (CLG) applications. Being used in CLG, continuous solution availability and robustness of GNSS solutions are of paramount importance. From April 2023 onwards, GNSS receivers on-board ISRO’s LV missions have shown degraded performance in terms of reduction in no. of satellites tracked and in some cases loss of GNSS solution as well. This was seen in multiple missions and was analyzed in detail. It was observed that there is nearly 3-4dB reduction in carrier to noise density (C/No) ratio and corresponding change in RF AGC gain is also observed. The issue is seen when the LV’s ground trace is over a particular terrestrial area (latitude 7degN-10degN longitude 95degE-110degE). A survey on internet indicated presence of GPS interference/jamming signals from nearby region and aircraft pilots have also reported similar observations. This paper addresses the performance degradation observed due to terrestrial jamming in ISRO’s GNSS receiver and analysis of observation w.r.t reduction in carrier to noise ratio and RF AGC gains. Further details on anti-jamming techniques implemented in LV GNSS receivers using trajectory based jamming signal isolation using RF switch is also addressed in this paper. Future developments being pursued towards building resilience towards different threats including jamming and spoofing using dual RF-front end & other software techniques are also discussed in this paper.
A, Mohammed BasimO T, Anand ShankaraV S, BijuV Gopal, BijuV S, VinojK, BalanC, Radhakrishna Pillai
Emergency evacuation slides (EVAC slides) are critical safety devices used on aircraft to enable rapid egress during emergencies. While these slides provide a quick and reliable escape route, communication between separated slides during evacuation remains a challenge. Often, during raft deployment over water, slides may drift apart impeding communication among evacuees and rescue personnel potentially compromising safety. Existing aircraft EVAC systems lack integrated wireless communication relying on visual or voice signals that are unreliable in chaotic conditions. This paper explores the integration of wireless IoT technology into EVAC slide systems to facilitate inter-slide communication and monitor critical parameters such as slide air pressure and the floating weight of stranded passengers through embedded sensors. It proposes the adoption of Long Range (LoRa) modulation technology for wireless communication chosen for its low-power, long-range performance and license-free operation in emergency evacuation scenarios. In addition, the usage of this proposed technology can be further extended to locate the aircraft when other existing locating mechanisms fail.
Sengodan, RajkumarTalore, Suresh
Commercial and military aircraft increasingly rely on Integrated Vehicle Health Management (IVHM) as a critical enabler for predictive maintenance, operational efficiency, and mission availability. The evolution of IVHM data communication architecture- from legacy wire-based networks to more wireless based architecture involving onboard wireless sensor networks (WSN) and IP-based air to ground communication networks introduces multidomain cyber-physical attack surfaces that challenge both functional safety and continued airworthiness. DO-326A/ED-202A and DO-356A/ED-203A standards define aviation cybersecurity requirements within a safety-driven assurance context, and IEC 62443 standard offers a defense-in-depth, lifecycle-based control framework for industrial systems. A unified approach by mapping and harmonizing the complimentary aspects of these two standards has the potential to simplify and expedite the security assurance and certification process for the IVHM and other digital avionic systems. The proposed work is a unified, standard-aligned cybersecurity assurance framework for aircraft IVHM systems covering both airborne ground segments as a single integrated entity. The novel methodology evaluates risks by performing Fundamental Requirements (FR) analysis, mapping IEC 62443 to DO-326A/ED-202A requirements through qualitative risk assessment, protocol vulnerability analysis, and attack tree modelling on zone-conduits as per the Security Level (SL) requirements. The resulting risk treatment plan demonstrates a verifiable and auditable method to achieve security assurance and certification of aircraft IVHM system which is extendable to other digital avionic systems.
Samudrala, RamakrishnaRamamurthy, Prasanna
As aerospace platforms adopt increasingly interconnected architectures for avionics, telemetry, and predictive diagnostics, lightweight publish–subscribe protocols have become integral to communication efficiency. The Message Queuing Telemetry Transport (MQTT) protocol is widely employed due to its small footprint and low network overhead. The release of MQTT 5.0 introduces new control features—reason codes, session expiry, user properties, topic aliasing, shared subscriptions, and improved error feedback—aimed at enhancing scalability and diagnostic reliability. However, these benefits come with trade-offs in complexity and potential overhead, particularly in real-time and resource-constrained environments typical in aerospace. This paper evaluates MQTT 3.1 and MQTT 5.0 within aerospace IoT contexts using a Raspberry Pi–based experimental framework. The analysis is done using practical throughput benchmarks implemented via popular open-source tools like Eclipse Mosquitto Clients. Realistic aerospace communication scenarios are modeled for inter-module messaging, under varying QoS levels and payload conditions. Comparative throughput, latency, and broker resource utilization benchmarks were conducted under multiple QoS levels and payload sizes to quantify the trade-offs between functionality and efficiency. This research aims to empirically validate the theoretical improvements of MQTT 5.0 on realistic embedded hardware and under controlled network constraints, replicating operational aerospace environments. Results show that MQTT 5.0 provides measurable advantages in complex, multi-tenant environments but introduces moderate processing overhead. Recommendations are proposed for selecting the optimal MQTT version for aerospace deployments and strategies for seamless migration from legacy systems [8].
Bhuyar, PrabhudevM, MeghanaKaniraja, ChristinaThomas, Tinto
Mercury Systems, Inc. Andover, MA
With the successful launch of the 10th Global Positioning System III satellite on April 21 from Cape Canaveral Space Force Base, Space Systems Command is celebrating the start of a new era for the world’s premier GPS constellation.
With $800 of off-the-shelf equipment and months’ worth of patience, a team of U.S. computer scientists set out to find out how well geostationary satellite communications are encrypted. And what they found was shocking.
As satellites take on more onboard processing - from Earth imaging to autonomy - spacecraft computing designers are pushing for higher performance under tight thermal and radiation constraints. Here's how suppliers are approaching heat removal, radiation mitigation and production-scale space-grade computing for LEO and beyond.
Space vehicle and satellite development programs are driving demand for new small- and medium-sized satellites across commercial and defense imaging, data collection, and other space-based applications.
The successful launch of the final GPS-III satellite into orbit makes 32 total satellites in the GPS-III constellation, and paves the way for production and launch of GPS-IIIF satellites. Space Systems Command, El Segundo, CA With the successful launch of the 10th Global Positioning System III satellite on April 21 from Cape Canaveral Space Force Base, Space Systems Command is celebrating the start of a new era for the world's premier GPS constellation. “This milestone satellite launch completes GPS Block III,” said Erin Carper, Acting Portfolio Acquisition Executive for Satellite Communications and Positioning, Navigation, and Timing (PNT) at SSC. “Providing critical military and civil signal accuracy 24/7, GPS continues to underpin global military operations for our warfighters.”
This Surface Vehicle & Aerospace Recommended Practice offers best practices and a methodology by which IVHM functionality relating to components and subsystems should be integrated into vehicle or platform level applications. The intent of the document is to provide practitioners with a structured methodology for specifying, characterizing and exposing the inherent IVHM functionality of a component or subsystem using a common functional reference model, i.e., through the exchange of design-time data and the application of standard vehicle data communications interfaces. This document includes best practices and guidance related to the specification of the information that must be exchanged between the functional layers in the IVHM system or between lower-level components/subsystems and the higher-level control system to enable health monitoring and tracking of system degradation severity. The intent is to provide an IVHM system that can robustly report the degradation of a given component before it reaches the point where it goes outside its operational performance envelope by providing sufficient advance notice to deal with the issue. This document does not specify or address how each layer in the IVHM system produces or uses the data available for exchange.
HM-1 Integrated Vehicle Health Management Committee
As an emerging innovative mode of public transportation, electric modular buses (EMBs) offer a novel solution to the problems of existing public transportation systems, due to the coupling-decoupling processes. In this paper, we study the energy consumption characteristics of EMBs by joining vehicle-to-vehicle (V2V) charging and reduction in aerodynamic drag due to coupling. For the pursuit of energy economy, ride comfort, and operational efficiency, we constructed an optimization scheme based on the simulated annealing (SA) algorithm to facilitate the coupling-decoupling process. The simulation results show that EMBs can meet 82.5 % of service requests compared with 61.8 % for the benchmark group, and V2V presents a significant contribution to energy efficiency, especially at low battery state of charge (SOC). Additionally, sensitivity analysis is conducted to study the impact of initial SOC, operation interval, and route type. The results provide insights for optimizing EMBs’ operations and emphasize the potential role of EMBs in supporting low-carbon and sustainable urban mobility systems.
Liao, PengGuo, JiaheNing, DonghongLi, SijiaWang, Tao
The race to develop sixth-generation (6G) mobile networks is accelerating, with commercialization expected by 2030. According to the International Telecommunication Union (ITU), 6G will introduce new usage scenarios such as “integrated artificial intelligence (AI) and communication” and “ubiquitous connectivity.” In this context, a recent article published in Engineering titled “Space– Ground Fluid AI for 6G Edge Intelligence” explores the integration of edge AI and space–ground integrated networks (SGINs) to extend AI services globally.
Sixth-generation, or 6G, cellular networks are the next step in wireless communication, and electromagnetic terahertz waves are seen as crucial to its development. However, terahertz waves, with their higher frequency and shorter wavelength, are subject to greater interference from electromagnetic noise, making clear and secure transmission a challenge.
Researchers at Lawrence Livermore National Laboratory (LLNL) have optimized and 3D-printed helix structures as optical materials for Terahertz (THz) frequencies, a potential way to address a technology gap for next-generation telecommunications, non-destructive evaluation, chemical/biological sensing and more.
The convergence of highly capable edge AI models and advanced commercial-off-the-shelf (COTS) edge AI accelerators is reshaping how computation is deployed across defense, aerospace, and commercial platforms. Mission-critical decisions increasingly must be made at the edge, onboard vehicles, satellites, and infrastructure nodes, where latency, connectivity, and power availability are constrained.
SAE J1979-2 describes the communication between the vehicle’s OBD systems and test equipment required by OBD regulations. OBD regulations require passenger cars and light-, medium-, and heavy-duty trucks to support a minimum set of diagnostic information to external (off-board) “generic” test equipment.
Vehicle E E System Diagnostic Standards Committee
SAE J1978-1 specifies a complementary set of functions to be provided by an OBD-II scan tool. These functions provide complete, efficient, and safe access to all regulated OBD (on-board diagnostic) services on any vehicle which complies to SAE J1979. The content of this document is intended to satisfy the requirements of an OBD-II scan tool as required by current U.S. OBD regulations. This document specifies: A means of establishing communications between an OBD-equipped vehicle and an OBD-II scan tool. A set of diagnostic services to be provided by an OBD-II scan tool in order to exercise the services defined in SAE J1979. In addition, SAE J1978-1 covers first generation protocol functionality defined in SAE J1979 plus automatic protocol determination for all SAE J1979/J1979-2/J1979-3 application content. The presentation of the SAE J1978 document family, where SAE J1978-1 covers first generation protocol functionality defined in SAE J1979 and protocol determination for SAE J1979, SAE J1979-2, and SAE J1979-3, and SAE J1978-2 covers second generation protocol functionality defined in SAE J1979-2. The SAE J1978 document family does not preclude the inclusion of additional capabilities or functions in an OBD-II scan tool. However, it is the responsibility of the OBD-II scan tool designer to ensure that no such capability or function can adversely affect either an OBD-equipped vehicle, which may be connected to the OBD-II scan tool, or to the OBD-II scan tool itself.
Vehicle E E System Diagnostic Standards Committee
The scope of this standard is Automated Vehicle Marshalling (AVM) of vehicles to enable remote control functionality for achieving SAE Level 4 (High Driving Automation according to the Surface Vehicle Recommended Practice SAE J3016) driving capabilities at controlled speeds within geofenced private controlled environments utilizing infrastructure-assisted sensing. It specifies a concept of operations which includes a reference-system architecture and use cases, system functional and performance requirements, multiple wireless communications protocols, and associated wireless messages to support AVM. AVM use cases such as plant marshalling, depot marshalling, valet parking, electric vehicle charging, etc. The Automated Vehicle Marshalling Central Server (AVM CS) infrastructure does detect objects, vehicles, vulnerable road users, and any obstructions that help guide the Automated Vehicle (AV) starting from uninitiated, activation, identification, automated control, unavailable and deactivation states of the respective feature lifecycle of AVM use cases by using only two wireless messages named Infrastructure Marshalling Message (IMM) and Vehicle Marshalling Message (VMM). This standard specifies the minimum requirements for the Vehicle-to-Everything (V2X) messages, such as IMM and VMM, and the corresponding data frames and elements which are defined to support Infrastructure guided AVM use cases over Direct (LTE-V2X) and Network-based wireless communications technologies. These messages are utilized to achieve desired interoperability, safety, and data integrity. This standard focuses on an infrastructure-led implementation of an AVM system analogue to a Type 2 Automated Vehicle Parking (AVP) system implementation as described in International Organization for Standardization (ISO) 23374-1; the functional allocations listed below are part of the Type 2 AVP System where AVM CS of infrastructure carries out most of the operation functions including AV Identification and Emergency Stopping: Destination Assignment Route Planning Object and Event Detection and Response (OEDR) AV Localization Path Determination Trajectory Calculation Vehicle Motion Control (VMC) NOTE 1: Functional Safety rating Automotive Safety Integrity Level (ASIL) related requirements are outside the scope of this standard. NOTE 2: This standard could be utilized as a base for human operator assisted AVM. The implementation details from human operator assistance without Infrastructure assistance is outside the scope of this standard. NOTE 3: Unless otherwise marked as Informative, all material in this standard is to be considered normative.
V2X Core Technical Committee
The SAE J3216 standard defines Cooperative Driving Automation (CDA), which has received increasing attention in recent years as an umbrella framework encompassing a wide range of automated vehicle applications enabled by Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) technologies. Despite this growing interest, limited research has investigated the impact of Cellular Vehicle-to-Everything (C-V2X) on CDA applications, particularly with respect to agreement-seeking operations. This work presents a hardware-in-the-loop (HIL) experimental study designed to evaluate an Argonne National Laboratory designed CDA controller under different message configurations and varying C-V2X PC5 radio transmission frequencies. A three-vehicle car-following scenario was implemented in the Argonne-developed Roadrunner simulator, incorporating CDA agreement-seeking logic, vehicle powertrain models, and V2V communication modules. CDA messages were exchanged through two physical C-V2X PC5 radios, capturing realistic communication impairment caused by the hardware characteristics. Packet loss and cooperation ratio were evaluated as functions of transmission frequency and message scheduling strategy. To further investigate the role of packet loss in the agreement-seeking process, a four-state Markov chain model was applied to characterize mechanisms that reduce cooperation ratio. The results indicate that synchronous transmission of CDA messages introduces half-duplex constraints, leading to increased packet loss and reduced cooperative driving duration. Increasing the message transmission frequency improves overall cooperation time, although it results in higher packet loss rates. These findings provide insight into the behavior of C-V2X radios and their impact on CDA applications, with a particular emphasis on cooperation duration, while remaining agnostic to specific controller performance characteristics.
Zhan, LuDi Russo, MiriamDas, DebashisStutenberg, KevinMisra, PriyashJeong, JongryeolHyeon, Eunjeong
Towing imposes substantial efficiency penalties on both battery-electric vehicles (BEVs) and internal combustion engine (ICE) vehicles, reducing range by 30-50%. This paper presents a proof-of-concept embedded control architecture for distributed trailer propulsion that actively regulates drawbar force to reduce towing loads. Unlike proprietary e-trailer systems requiring specialized hardware, the proposed implementation demonstrates feasibility using commercial off-the-shelf (COTS) components and open-source software. The distributed architecture employs dual Raspberry Pi 4B single-board computers communicating via ROS 2 at 20 Hz. The trailer-mounted controller executes a Simulink-generated control node coordinating load cell acquisition (HX711 ADC), motor CAN bus telemetry, and throttle commands to a 5 kW BLDC traction motor powered by a 5 kWh LiFePO4 battery pack. A vehicle-mounted controller logs OBD-II/CAN validation data. The control pipeline implements cascaded EWMA/Hampel digital filtering with intentional phase lag for hitch-force regulation. The system was validated through on-road testing with an ICE towing vehicle pulling a 1,000-lb trailer over standardized 2.1 km segments following SAE J1321 Type II procedures. Preliminary trials demonstrated stable control performance with drawbar force regulation with no oscillatory behavior. Fuel consumption measurements showed promising improvements (9.4% lower fuel consumption in assisted vs. baseline conditions), though limited sample size precludes definitive causal claims. The primary contribution is establishing technical feasibility of cost-effective COTS implementation (USD 5,000 hardware cost) for trailer propulsion control, providing a foundation for expanded validation studies and commercial deployment pathways.
Joshi, GauravAdelman, IanLiu, JunDonnaway, Ruthie
Advances in Connected and Automated Vehicles (CAVs) have developed a level in which high-definition maps can be used to improve road safety. Data compactness and robustness on road characterization is essential for the proper handling of vehicles under curves. In this paper, an optimization scheme that relates highway-design road curvature and optimal speed of travel is defined to safely navigate through a given road. The scheme is divided in two main steps. First a nonlinear optimization problem, in which curvature profiles are fitted from a model that based on street design standards as per the American Association of State Highway and Transportation Officials (AASHTO). Secondly, the optimized curvature profile is subject to a secondary optimization problem that uses vehicle dynamics for both constraints and objective function derivation. Guidance reference parameters such as curvature and velocity, at different levels of friction are analyzed. Results show that, even in sparse datasets, the algorithm can leverage on highway design to generate proper velocity profiles. These profiles in turn can be used to enhance existing wireless communication infrastructure and autonomous vehicle technology.
Jacome, Ricardo OsmarStolle, CodyGrispos, George
Automotive Original Equipment Manufacturers (OEMs) closely guard information about their products due to the significant investment in vehicle research and development. However, advancing automotive innovation often requires insights from existing systems to improve safety, efficiency, and performance. The Controller Area Network (CAN) bus remains the industry standard for communication between electronic control units (ECUs), yet CAN message specifications are typically proprietary and undocumented. This paper presents a case study involving the reverse engineering of CAN messages from a 2024 Toyota Grand Highlander powertrain. By capturing and analyzing communication between a diagnostics tester and the vehicle’s ECUs and replicating the communication, substituting A CANcase and software in place of a diagnostics tester, we were able to reverse engineer the vehicle’s CAN bus, demonstrating a practical methodology for decoding and interpreting CAN traffic without prior access to proprietary data. The approach highlights both general principles and OEM-specific variations in message structure and encoding. The goal of this work is to support researchers and engineers in developing their own reverse engineering workflows. It illustrates that while the foundational techniques are consistent, adapting to vehicle-specific implementations is essential. The paper aims to provide a replicable process and to encourage further exploration in the field of automotive CAN analysis.
Bolarinwa, EmmanuelPeters, Diane
The reliability of Drive Unit (DU) oil pumps is critical to the performance and safety of electric vehicles, as these pumps provide essential lubrication and thermal management. In modern EV architectures, real-time health monitoring of these pumps typically relies on indirect signals than dedicated sensing hardware, a design choice optimized for cost, weight, and system complexity. This makes early fault detection a non-trivial challenge. To address this limitation, we present a novel, data-driven anomaly detection framework that leverages large-scale customer fleet telemetry and advanced machine learning to identify incipient pump degradation that traditional diagnostic methods often fail to capture. Specifically, we develop an XGBoost regression model trained on time-series features—including commanded pump speed, oil temperature, and historical pump current—to predict expected current behavior under nominal conditions. Deviations are quantified using the Mean Absolute Percentage Error (MAPE) between predicted and actual currents, providing a continuous and interpretable measure of anomaly severity. A fully automated pipeline ingests daily telemetry, performs session segmentation, executes predictive modeling, and records anomaly outcomes in backend databases for continuous monitoring and engineering review. The proposed framework enables continuous, fleet-wide predictive maintenance of DU oil pumps. It improves early detection of degradation, reduces vehicle downtime, enhances safety, and increases customer satisfaction. More broadly, it highlights the potential of large-scale data analytics and machine learning to advance predictive maintenance and reliability in electric vehicle (EV) systems.
Li, JingmanYao, MengqiRahimi, SahilLin, Joanne
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