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Digital Twin Simulation and Verification System Design and Implementation for Satellite Production Lines2026-99-18047/17/2026
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
Greedy Satellite Scheduling Method with Minimal Switching Based on Interacting Multiple Model2026-99-18207/17/2026
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, Sirui, Liu, Chengzhe, Wang, Yandong
On-orbit Computing Framework for LEO Satellites Based on MADDPG and Lyapunov Optimization2026-99-18117/17/2026
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, Ming, Zhao, Liang, Xu, Lexi, Zhou, Xiaofei, Hawbani, Ammar, Sun, Yunhe
Research on Multi-Model Fusion Method for Small Satellite Abnormal State Detection Based on Machine Learning2026-99-18177/17/2026
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, Biyan, Chen, Ye, Guo, Qi
A Detection Method for 10N Thruster Ignition Anomaly Based on the Temperature Model2026-99-18147/17/2026
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, Liling, Tian, Huadong, Wei, Yubo, Fei, Di, Xing, Chao
Cooperative Edge Extension for Automated Driving Level 4 and Beyond2026-01-07767/1/2026
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, Vitus, Lukezic, Nikola, Kraus, David, Seidel, Luca, Beck, Maximilian, Schindewolf, Marc, Sax, Eric
Towards a Smarter E-Bike: Enhancing Energy Efficiency through Adaptive Speed Control2026-01-07367/1/2026
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, Yannick, Simmann, Gabriel, Schneider, Manuel, Goss, Christian, Kriesten, Reiner
J1939 Digital AnnexJ1939DA_202606 (Current)6/29/2026
This document is intended to supplement the J1939 documents by offering the J1939 information in a form that can be sorted and searched for easier use.
Truck and Bus Control and Communications Network Committee
Impact of Network-Induced Delays on Autonomous Vehicle Steering Stability10-10-03-00246/25/2026
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, Jialin, Lu, Jianwei, Wei, Heng, Ao, Di
Use Cases for Wireless Charging Communication for Plug-in Electric VehiclesJ2836/6_202606 (Current)6/24/2026
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
NoiseSphere: An AI-Based Approach for Dynamic and Large-Scale Noise Mapping2026-01-07196/20/2026
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
857 Securing Non-Safety SATCOM CommunicationsARINC857 (Current)6/15/2026
This document provides comprehensive guidance on cybersecurity practices, threat assessment, and security controls for non-safety satellite communication (Satcom) systems onboard commercial aircraft, emphasizing protection of data, system integrity, and privacy.
Airlines Electronic Engineering Committee
Enabling Flexibility Services through Interoperable V2X Infrastructures: Advanced Modeling and Operational Validation in the FLEXV2X Project2026-37-00246/9/2026
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, Giovanni, Barater, Davide, Ceraolo, Massimo, Fera, Cesare, Leaver, Ian, Pasini, Gianluca
Impact Study of Terrestrial Jamming on GNSS Receiver On-Board Launch Vehicles and Mitigation Technique Using RF Switch2026-26-07666/1/2026
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 Basim, O T, Anand Shankara, V S, Biju, V Gopal, Biju, V S, Vinoj, K, Balan, C, Radhakrishna Pillai
A GenAI-Based Approach for Real-Time Multilingual In-Flight Communication Systems2026-26-07846/1/2026
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, Ashwini, Kature, Kartik, Patil, Ashish
Implementation of Wireless IoT Technology for Enhanced Communication and Monitoring in EVAC Slide Emergency Systems2026-26-07926/1/2026
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, Rajkumar, Talore, Suresh
Unified and Certifiable Cybersecurity Management Framework for IVHM2026-26-07676/1/2026
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, Ramakrishna, Ramamurthy, Prasanna
Comparative Study between MQTT 3.1 and MQTT 5.0: Evaluating Theoretical Enhancements Through Practical Throughput Benchmarks for Aerospace IoT Systems2026-26-07116/1/2026
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, Prabhudev, M, Meghana, Kaniraja, Christina, Thomas, Tinto
Commercial Satellite Manufacturing Scales Up as LEO Demand Drives New Production Lines26AERP06_046/1/2026
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.
Space Systems Command Looks Ahead to New Era of GPS Success26AERP06_076/1/2026
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.”
Edge Computing Advances Enable Smarter Spacecraft and Satellites in Orbit26AERP06_026/1/2026
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.
Glaring Vulnerabilities Discovered in Satellite Communications26AERP06_096/1/2026
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.
Design and Run-Time Information Exchange for Health-Ready ComponentsJA6268_202303 (Current)5/26/2026
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
An Energy-Saving Coupling-Decoupling Optimization Strategy for Electric Modular Buses Considering Vehicle to Vehicle Charging2026-99-07305/15/2026
As an emerging innovative mode of public transportation, electric modular buses (EMBs) offer a novel solution to the problems of existing public transportation systems, due to the coupling-decoupling processes. In this paper, we study the energy consumption characteristics of EMBs by joining vehicle-to-vehicle (V2V) charging and reduction in aerodynamic drag due to coupling. For the pursuit of energy economy, ride comfort, and operational efficiency, we constructed an optimization scheme based on the simulated annealing (SA) algorithm to facilitate the coupling-decoupling process. The simulation results show that EMBs can meet 82.5 % of service requests compared with 61.8 % for the benchmark group, and V2V presents a significant contribution to energy efficiency, especially at low battery state of charge (SOC). Additionally, sensitivity analysis is conducted to study the impact of initial SOC, operation interval, and route type. The results provide insights for optimizing EMBs’ operations and emphasize the potential role of EMBs in supporting low-carbon and sustainable urban mobility systems.
Liao, Peng, Guo, Jiahe, Ning, Donghong, Li, Sijia, Wang, Tao
COTS Edge AI Accelerators for SWaP-C Constrained Defense and Space SystemsTBMG-550825/1/2026
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.
E/E Diagnostic Test Modes: OBDonUDSJ1979-2_202604 (Current)4/21/2026
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
OBD-II Scan Tool: First Generation ProtocolsJ1978-1_202604 (Current)4/20/2026
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
Automated Vehicle Marshalling SystemJ3292_202604 (Current)4/13/2026
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
J1939 Digital AnnexJ1939DA_202604 (Historical)4/9/2026
This document is intended to supplement the J1939 documents by offering the J1939 information in a form that can be sorted and searched for easier use.
Truck and Bus Control and Communications Network Committee
New Era of Automotive Cybersecurity2026-01-00864/7/2026
The automotive industry is evolving from a reactive, independently self-determined approach to cybersecurity, complicated by a complex supply chain. Over time, this has resulted in a fragmented industry comprised of any number of proprietary solutions verses a standardized, regulated paradigm to facilitate a platform-oriented approach. This document, an update on collaborative work from the SAE Vehicle Electrical Hardware Security Task Force (TEVEES18B) and GlobalPlatform Automotive Task Force, outlines this transition strategy. An extensible number of additional examples of use cases of Global Platform Technologies are explored in this document.
Mazzara, Bill, Rawlings, Craig
Impact of User-Adjustable Vehicle-Dynamics Tuning on Vehicle Durability2026-01-01944/7/2026
Software-defined vehicles offer customers a greater degree of customization of vehicle controls and driving experience. One such feature is user-adjustable tuning of vehicle ride and handling, where customers can vary ride height, damper stiffness, front-rear torque balance, and other aspects of vehicle dynamics. While promising a great customer experience, such a feature can expose the vehicle to a wider range of structural loads than those in the nominal design condition, particularly when such tuning is extended to cover spirited “sport” mode driving, off-road driving, etc. In this paper we present a novel methodology combining Road Load Data Acquisition (RLDA) data and real-world telemetry data to estimate the impact of user-adjustable vehicle-dynamics tuning on structural durability. In doing so, the method combines the physics of damage accumulation (from RLDA data) with user behavior (from telemetry data) to present an accurate assessment of the impact on durability, moving beyond traditional durability methods that do not model a range of real-world usage behavior. The study has been conducted using one instrumented vehicle (RLDA) and de-identified telemetry data from over 20,000 Rivian customer vehicles. The study analyzes the impact of variations in ride height, damper stiffness of active dampers, and roll stiffness of the suspension on vehicle structural durability. By combining usage frequency of the different settings with the damage accrued in these settings, the methodology estimates the high-cycle fatigue pseudo-damage variation for a wide range of customers and compares real world damage risk with the damage accounted for in the baseline durability testing. Through the analysis, we recommend a way to optimize the Accelerated Duty Cycle (ADC) for Over the Road (OTR) testing to minimize real-world risk, while keeping the duty cycle simple and practical for testing, i.e., test for an optimized combination of a few dominant settings and not a wide range of settings. The approach also suggests a path to a real-time fleet monitoring system to identify high-durability-risk customers and develop mitigation strategies.
Demiri, Albion, Ramakrishnan, Sankaran, White, Dylan, Khapane, Prashant, Borton, Zackery
The Simple Complexity of Reverse Engineering a Vehicle CAN Bus2026-01-00704/7/2026
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, Emmanuel, Peters, Diane
A Simple Analytical Model for Predicting Cooperative Ratio in Agreement-Seeking Cooperative Driving Automation with C-V2X Communication2026-01-00784/7/2026
Cooperative Driving Automation (CDA) has emerged as an active research area in recent years, categorized into four classes of operations with varying levels of cooperation as defined in the SAE J3216 standard. Among these, Class C CDA, referred to as Agreement-Seeking Cooperation (ASC), has received limited attention in literature. Unlike Cooperative Adaptive Cruise Control (CACC), which typically engages when lead vehicles are identified as cooperative and disagree under manual override or safety-critical conditions, ASC requires agents to exchange messages interactively to reach consensus on a proposed plan and its implementation. This necessitates more sophisticated communication and control designs, which in turn influences customized ASC efficiency. Previous work has examined, through simulation, the impact of three key parameters on ASC system performance: CDA message transmission frequency, Packet Drop Ratio (PDR), and Cooperation Duration Length (CDL). In this paper, we extend that investigation by conducting Hardware-in-the-Loop (HIL) experiments in a scenario-based simulation environment, integrating the ASC controller with vehicle-to-vehicle (V2V) communication enabled by PC5-based Cellular Vehicle-to-Everything (C-V2X) radios. Using HIL test data, we derived a simple analytical model based on Pascal Distribution to predict the Cooperative Ratio (CR), which is a key index defined by cooperative time over the total scenario time. The model explores the fundamental mechanism of how transmission frequency, total trip time, instance CDA engagement probability and CDL collaboratively impact Cooperative Ratio. The validation of the model with experimental data reports the relative error is less than 5% for scenarios with CDA message transmission frequency higher than 5 HZ. Furthermore, because the model is independent of specific control logic assumptions, it provides a practical tool for guiding the design of ASC communication protocols and control strategies.
Zhan, Lu, Di Russo, Miriam, Das, Debashis, Stutenberg, Kevin, Misra, Priyash, Jeong, Jongryeol, Hyeon, Eunjeong
Integrated DBSCAN-Based Segmentation of Tractor Activity into Productive and Non-Productive States from GPS Data2026-01-01694/7/2026
Accurate identification of Productive and Non-Productive States or tractor duty cycles—comprising working, idle, and transport states—is critical for performance analysis, fuel optimization, and emissions modeling in agriculture machinery and fleet monitoring. This study explores the application of integrated unsupervised machine learning (ML) techniques to classify duty cycles using GPS-derived parameters such as speed, location variance, and temporal patterns. Unlike supervised approaches, the proposed method does not rely on several labeled engine and vehicle parameters, making it scalable and adaptable across diverse operational contexts. Clustering algorithm DBSCAN (Density-Based Spatial Clustering of Applications with Noise) in integration with hybrid rule-based and a road feature is employed to segment GPS data into distinct behavioral states. Feature engineering focuses on extracting motion signatures and spatial-temporal features that correlate with operational modes. Validation against manually annotated datasets demonstrates high accuracy in distinguishing idle, working, and transport phases. Furthermore, the present study demonstrates that by accurately determining the operational status of the tractor, unnecessary idling can be prevented through an idle avoidance system. Additionally, after assessing transport and working conditions, a movement-based control system for tire pressure adjustment is proposed. Both strategies have the potential to reduce fuel consumption by approximately 5-7%; however, this lies outside the scope of the present work. The framework offers a robust, data-driven solution for duty cycle monitoring and can be integrated into telematics systems for predictive maintenance and operational efficiency of the tractors.
Maharana, Devi prasad, Gangsar, Purushottam, Dharmadhikari, Nitin, Pandey, Anand Kumar
Electric Vehicles & the Grid - Synergy or Strain?2026-01-03984/7/2026
As the demand for electrical power has surged over recent years due to the increasing popularity of data centers for Artificial Intelligence (AI) and Electric Vehicles (EVs), it is becoming evident that the aging electrical grid infrastructure is struggling to keep up. Some of the problems this aging infrastructure has resulted in include frequent blackouts due to weather related events, reduced efficiency resulting in higher maintenance costs and outdated communication systems causing poor monitoring and response times. Modernization of the grid in conjunction with integration of the transportation sector with the grid is essential to ensure the reliability and resiliency of the grid. Electric vehicles have dramatically increased in popularity, with most vehicle manufacturers offering at least one electric option in their lineups. Looking at recent developments in vehicle-to-grid (V2G) technology, a new possibility becomes evident; instead of straining the power grid, the electric vehicle can synergize with it. This becomes possible when EVs can facilitate charging during off-peak (low demand) hours and supplying power back to the grid during on-peak (high demand) hours. There are quite a few challenges associated with this approach, lack of standardized charging infrastructure and higher install costs, regulatory and policy hurdles, gaps in technological know-how particularly in relation to impact of power supplied by EVs on grid and effect of V2G on EV battery degradation in the long run, to name a few. This paper reviews the current power demand and supply along with existing and projected power consumption metrics. We also discuss the V2G strategy to effectively manage load requirements, incentives that can be provided to facilitate the execution, and the challenges associated with its widespread implementation. Finally, we discuss case studies of vehicles that incorporate V2G capability and their implications.
Dahlmann, Alexander Drake, Lele, Sneha
Mitigation of Sensor-Level Cyber-Physical Attacks on Electric Vehicle Powertrains: A Simulation-Based Study2026-01-00914/7/2026
Electric vehicles (EVs) rely extensively on sensor feedback for safe and efficient powertrain operation. However, this dependency introduces cyber-physical vulnerabilities, especially when sensor signals are maliciously manipulated. This paper presents a simulation-based investigation into sensor-level cyberattacks on a mid-sized EV powertrain model developed in MATLAB/Simulink. The study quantifies mechanical consequences and evaluates mitigation strategies to enhance system resilience. Four representative attack scenarios were simulated. Speed sensor spoofing led the controller to misinterpret vehicle velocity, causing a 41% overshoot beyond the 50 km/h setpoint. False data injection into torque/current sensors triggered an unintended torque surge of approximately 20%, resulting in inverter current saturation within 2 seconds. Battery temperature spoofing delayed thermal protection, allowing a deviation of 1.5 °C/min beyond safe operating limits. A hybrid attack combining frozen speed feedback with a forced 100% throttle input caused runaway acceleration and actuator saturation lasting over 10 seconds. These scenarios demonstrate how localized sensor attacks can propagate through control loops, destabilizing vehicle dynamics. To counter these threats, we implemented signal plausibility checks, observer-based anomaly detection, and fail-safe torque limiting. These measures collectively reduced overshoot by more than 50% in spoofing cases. Beyond simulation, we propose a multi-layered defense framework incorporating cross-sensor validation, statistical and machine learning-based anomaly detection, guided by ISO/SAE 21434 cybersecurity engineering principles, signal-level defenses, and conservative fallback controls. By linking cyber intrusions to tangible mechanical instabilities and validating countermeasures through simulation, this work offers actionable insights for engineers developing robust and secure EV powertrains. It underscores the necessity of integrating mgechanical and cybersecurity disciplines to ensure the safety and reliability of future electric mobility systems.
Tariq, Usama, Sahandabadi, Sahereh, Dianat, Ali
Characterizing the Impact of C-V2X PC5 Radio on Cooperative Driving Automation in Hardware-in-the-Loop Experiments2026-01-00774/7/2026
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, Lu, Di Russo, Miriam, Das, Debashis, Stutenberg, Kevin, Misra, Priyash, Jeong, Jongryeol, Hyeon, Eunjeong
Techno-Economic Evaluation of Electrified Vehicle Options in Drayage Fleets2026-01-04544/7/2026
The electrification of drayage fleets offers potential economic and operational benefits, but the financial viability of electrified vehicles remains sensitive to battery cost, energy price, and fleet usage patterns. While total cost of ownership (TCO) is a useful benchmark, fleet operators and investors are equally concerned with investment performance metrics such as payback period (PB) and Internal Rate of Return (IRR), which better reflect financial risks and investment return timelines. This study develops a unified techno-economic framework that jointly evaluates TCO, PB, and IRR to determine when electrified trucks become cost-effective alternatives to diesel trucks. Building on a previously developed cost modeling tool and using real-world telematics data from a Class 8 drayage fleet at the Port of Savannah, the analysis incorporates projected battery cost trajectories, electricity and diesel price trends, vehicle efficiency improvements, and multiple battery capacities. Parameter ranges reflect widely cited projections and observed drayage-duty-cycle variability. A surrogate-modeling method approximates economic performance across thousands of battery cost–electricity price combinations, enabling high-resolution identification of conditions that achieve TCO parity, acceptable PB thresholds, and target IRR levels. Additionally, the study estimates the evolving share of the fleet that can feasibly electrify over time under multiple economic metrics. This integrated framework offers a novel, data-driven approach to inform risk-aware decision-making for fleet electrification and supports investment planning under evolving cost and operational conditions.
Sun, Ruixiao, Sujan, Vivek, Goulet, Nathan, Wang, Qixing
Data-Driven Objective Road-Driving Classification for Durable Design of Vehicles2026-01-01814/7/2026
Design for durability in the automotive industry depends on a clear understanding of how road surfaces and driving characteristics affect structural road loads and fatigue. Traditionally, road surface classification has been subjective (e.g., city, highway, rural), and done through driving instrumented vehicles over a small selection of roads. The variations in driving characteristics that are often consequent to the road surface quality are rarely accounted for in designing vehicle level durability tests. This makes it difficult to establish targets for durability testing that accurately match the wide variations in real-world roads and driving. This paper presents a data-driven approach to objectively classify road surface and driving characteristics using metrics derived from existing road response metrics like Vibration Dose Value (VDV) and statistical estimates of vehicle speed and acceleration. Data collected at the proving grounds on gravel roads, smooth roads, city-like roads, etc., is used to identify classifiers that categorize road-driving combinations into groups correlating with structural fatigue damage. This correlation between fatigue damage and road-driving classification is developed using Wheel Force Transducer (WFT) measurements from instrumented vehicles. This method shows promise to develop structural fatigue estimates directly from telemetry data. The method provides a path to replacing subjective road classification with a vehicle-sensor and signal-based, objective classification for developing durability targets and tests. This method is also scalable in terms of application on vehicle fleet data in uncontrolled environments, to develop an accurate understanding of real-world use of vehicles by customers.
Shaurya, Shubham, Ramakrishnan, Sankaran, Demiri, Albion, Khapane, Prashant
Quantifying the Impact of Towing on BEV Energy Use: Instrumented On Road Testing and Chassis Dynamometer Reproduction2026-01-04314/7/2026
Electrification is rapidly entering all vehicle classes, including light- and heavy-duty trucks designed for heavy towing capabilities. Still, the quantitative impact of towing on battery-electric vehicle (BEV) energy use and range remains under-characterized. We conducted controlled towing tests with a Ford F-150 Lightning using two trailers of different sizes and varying payloads to isolate aerodynamic and mass effects and to span the full range of towable payloads within the vehicle’s rated capacity. The vehicle was instrumented at the CAN bus level, capturing motor power, torque, speed, and related internal signals from different control modules. On-road testing consisted of repeated back-and-forth passes on level, straight road segments at set speeds focusing on highway operation, where aerodynamic drag is stronger and real-world towing use cases occur. From these data, we extracted road load equations and dynamometer coefficients for each trailer combination, then reproduced equivalent conditions on a four-wheel drive chassis dynamometer across several standard cycles. Results were consistent across runs, showing a significant increase in the vehicle’s overall energy consumption and a corresponding range penalty. Additional impacts on vehicle systems due to towing, including thermal management of the motors and battery, were quantified. Dynamometer tests of varying characteristics (highway, urban, steady state speeds and accelerations) allow isolation of specific behaviors in functions like regenerative braking operation and torque-split strategy. Dynamometer results aligned with on-road measurements, enabling repeatable laboratory evaluation of towing scenarios. These findings provide a validated methodology and dataset to quantify towing impacts on BEVs, inform range prediction and route planning, support labeling and consumer guidance, and characterize sustained, high load real world operation of vehicle components.
Timermans Ladero, Inigo
Optimizing Custom Hybrid Solutions for Low-Volume Specialist Equipment2026-01-04794/7/2026
Off-road vehicles are typically powered by diesel engines, sized to cover the highest peak loads in their dutycycles. Such applications can be designed with downsized engines, using hybridization to supplement engine power with electrical power for short periods. However, many applications are low-volume and specialized, making it impractical to deploy heavy engineering resources to optimize each one. For this reason, manufacturers tend to produce maid-of-all-work vehicles to cover every situation. This paper demonstrates the benefits of custom hybridization for specialist applications, and addresses the lack of accessible software tools for evaluating such opportunities. Analysis is applied with a fast, low-cost, Concept-based software tool named “ePOP Concept”, suited to original equipment manufacturers (OEMs) who seek to provide custom low-volume vehicles. It allows many different powertrain architectures to be evaluated rapidly at the product planning stage, and can be quickly set up and used by non-specialists in simulation. Agricultural load cases are analyzed, showing the benefits of adding hybridization through electric motors and stored energy, supplementing engine power for demand peaks to enable engine downsizing. Use cases for four Fendt diesel tractors were taken from a dataset generated by Götz et al, at the agricultural facilities of the Technical University of Munich, which has been made publicly available by the authors to address the absence of standard load cycle data for the analysis of tractor electrification. The results show benefits for a customizable hybridization architecture to accommodate specific use cases, and the benefits of quick, accessible analysis methods for small engineering teams, to support early product decisions and what-if analyses.
De Salis, Rupert, Fons, Daniel
Optimization of Road Reference Profiles Based on Highway Design for Connected and Automated Vehicles2026-01-00964/7/2026
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 Osmar, Stolle, Cody, Grispos, George
Integration and Validation of Adaptive Cruise Control across Different Modes2026-01-00764/7/2026
This paper presents the integration and validation of Adaptive Cruise Control (ACC) algorithms on a student-team-developed vehicle as part of the U.S. Department of Energy EcoCAR EV Challenge. The competition provided each team with a 2023 Cadillac Lyriq, which was modified to an all-wheel-drive configuration and re-architected to support the development of SAE Level 3 autonomous features including Adaptive Cruise Control (ACC), Automatic Intersection Navigation (AIN), Lane Centering Control (LCC), and Automatic Parking (AP). The scope of this paper, however, is limited to the development, implementation, and validation of a Level 2 longitudinal ADAS function. Higher-level automation requirements such as Operational Design Domain (ODD) definition and Driver Monitoring System (DMS) enforcement are addressed at the vehicle architecture and competition level but are not the focus of this work. The major contribution of this work is the development of ACC with Vehicle-to-Infrastructure (V2I) integration, highlighting the end-to-end implementation of the ACC algorithm and its interaction with key actuation systems in the modified vehicle architecture. The ACC algorithm encompassed multiple applications: conventional cruise control to maintain speed, adaptive cruise control to respond to a lead vehicle, and initial deceleration handling for intersection navigation in a single straight lane. By implementing a unified algorithm, transitions between these modes were smooth and more efficient compared to developing separate algorithms for each application. Track-based testing and calibration were conducted to validate these modes under real-world scenarios, ensuring safe operation while addressing the challenges of blended actuation. Multiple track tests were used to measure stopping distances at intersections for different entry speeds, evaluate controller performance during different driving scenarios, and identify system limitations. Results demonstrated that the controller maintained steady-state speed error within +/- 1 km/hr, preserved a minimum following distance of 8 m at a complete stop, and limited acceleration within +/- 2 m/s2 to support driver comfort. The work demonstrates the progression from simulation to real-world deployment using an empirical approach to system-level validation of ACC with V2I integration. The findings provide insights into calibration methodology, mode transition, and the benefits of a unified control framework for advancing software-defined vehicle features.
Gupta, Ishika, Estrada, Tyler, Tambolkar, Pooja, Midlam-Mohler, Shawn
Embedded Real-Time Control of a Distributed Trailer Propulsion System with Regenerative Braking for Net Neutral Load Towing2026-01-00654/7/2026
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, Gaurav, Adelman, Ian, Liu, Jun, Donnaway, Ruthie
Predictive Maintenance of EV Drive Unit Oil Pumps through Machine Learning on Fleet Telemetry Data2026-01-01614/7/2026
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, Jingman, Yao, Mengqi, Rahimi, Sahil, Lin, Joanne
Signal Integrity in Distributed BMS: Reliable SPI and Ethernet Communication for Next-Gen Evs2026-01-01714/7/2026
Distributed battery management systems (BMS) are critical for scaling electric vehicle packs to hundreds of cells, but reliable high-speed communication between modules remains a challenge. Daisy-chained SPI and CAN FD are widely deployed today, while Ethernet is being evaluated for next-generation systems that require higher bandwidth, synchronization, and diagnostics. This paper examines the signal integrity (SI) challenges facing distributed BMS communication, including skew, jitter, crosstalk, and electromagnetic interference (EMI) across PCB traces and wiring harnesses. HyperLynx and SPICE-based simulations are combined with experimental results on a 192-cell test platform to quantify the impact of layout constraints, impedance mismatches, and harness parasitic. Results show that poor SI design can reduce signal margins by more than 18 dB, leading to data corruption and diagnostic failures. Results show poor SI design can reduce signal margins by 18 dB, causing data errors. Measured BER is ≤1×10-12, jitter decreases up to 30%, and Ethernet latency stays below 120 ns under worst-case EMI. Additional testing confirmed SPI and Ethernet maintain stable communication across 192-cell BMS platform. Co-design strategies for PCB routing, termination, and shielding are proposed, achieving up to 30% reduction in jitter and error rates under worst-case EMI conditions. By addressing both current SPI-based systems and future Ethernet implementations, this paper provides practical guidelines for engineers developing distributed BMS architectures that meet ISO 26262 functional safety while enabling scalable and reliable next-generation EV platforms.
Abdul Karim, Abdul Salam
Quantifying Highway Flow Improvements via CACC-Based Truck Platooning: A Statistical Modeling Approach2026-01-04634/7/2026
The advancement of Cooperative Adaptive Cruise Control (CACC) technology enables vehicle platooning on public roads, offering significant potential to enhance urban mobility, driving safety, and energy efficiency. Among various applications, truck platooning has become a promising strategy to increase highway flow rates by reducing vehicle headways, improving coordination, and optimizing space utilization. This paper presents a quantitative assessment of a CACC-based truck platooning system, focusing on its effectiveness in enhancing highway mobility under varying traffic conditions. A statistical regression model is developed and calibrated using simulations of real-world highway networks to identify key influencing factors and evaluate the resulting improvements in traffic flow. The analysis considers five primary variables: desired platoon speed, platoon size, space headway, percentage of platooning trucks, and non-platoon traffic flow. The study systematically examines the impact of each parameter on overall traffic throughput. Results indicate that truck platooning can increase highway flow rates by up to 200%, particularly under conditions of high truck volumes and larger platoon sizes. Both platoon size and the percentage of platooning trucks show a positive correlation with flow rates, suggesting that greater coordination among vehicles enhances overall mobility. Conversely, higher desired speeds and larger space headways tend to diminish the benefits of platooning by reducing traffic density. Overall, this paper provides a comprehensive quantitative evaluation of the mobility benefits of truck platooning and highlights its potential to significantly improve highway operations. Future work will extend these findings to assess the energy and emission benefits of platooning and to evaluate the performance of large-scale platooning deployment strategies.
Karbasi, Amir Hossein, Wang, Jinghui, Yang, Hao
Accurate and Resilient GNSS Timing Modules for Critical Infrastructure26AERP04_054/1/2026
Precise time synchronization is the backbone of today's connected world, keeping telecom networks, data centers, and financial systems running seamlessly. Without accurate timing, our digital infrastructure would quickly fall out of sync. Septentrio designs and manufactures world recognized Global Navigation Satellite System (GNSS) timing receivers for critical infrastructure and leading industry organizations. The Septentrio mosaic-T timing module delivers nanosecond-level precision for synchronization and is trusted by companies such as Meinberg, VIAVI, and Saab. Built-in AIM+ technology protects against intentional and unintentional GNSS jamming and spoofing, ensuring maximum system uptime even in challenging or hostile conditions.
Application Layer - Generator Sets and IndustrialJ1939/75_202603 (Current)3/19/2026
SAE J1939-75 defines the set of data parameters (SPs) and messages (PGs) for information predominantly associated with monitoring and control generators and driven equipment in electric power generation and industrial applications. The data parameters (SPs) and messages (PGs) previously published within this document are published in SAE J1939DA. Applications using the SAE J1939-75 document must refer to SAE J1939DA for the SAE J1939 parameters and messages for monitoring and controlling the power units, e.g., engines and turbines, that power the generators and driven industrial equipment.
Truck and Bus Control and Communications Network Committee
Serial Control and Communications Heavy-Duty Vehicle Network - Top-Level DocumentJ1939_202603 (Current)3/17/2026
This top-level document provides a general overview of the SAE J1939 network and describes the subordinate document structure. This document includes definitions of terms and abbreviations which are used among the various SAE J1939 subordinate documents.
Truck and Bus Control and Communications Network Committee
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