Browse Topic: Communication protocols
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.
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.
Modern vehicles require sophisticated, secure communication systems to handle the growing complexity of automotive technology. As in-vehicle networks become more integrated with external wireless services, they face increasing cybersecurity vulnerabilities. This paper introduces a specialized Proxy based security architecture designed specifically for Internet Protocol (IP) based communication within vehicles. The framework utilizes proxy servers as security gatekeepers that mediate data exchanges between Electronic Control Units (ECUs) and outside networks. At its foundation, this architecture implements comprehensive traffic management capabilities including filtering, validation, and encryption to ensure only legitimate data traverses the vehicle's internal systems. By embedding proxies within the automotive middleware layer, the framework enables advanced protective measures such as intrusion detection systems, granular access controls, and protected over-the-air (OTA) update channels. This strategy enhances both data security and system isolation, creating protective boundaries between critical vehicle operations and potential external attacks. The architecture particularly excels in supporting Vehicle-to-Everything (V2X) connectivity, facilitating seamless information exchange between vehicles, roadside infrastructure, and pedestrians. This capability is essential for enhancing roadway safety, optimizing traffic flow, and supporting autonomous driving technologies. The system incorporates dedicated proxy modules for specialized protocols including Trivial File Transfer Protocol (TFTP), Diagnostic Over Internet Protocol (Doip), and Message Queuing Telemetry Transport (MQTT), each fulfilling specific functions in vehicle diagnostics, software updates, and telemetry data management. Performance evaluations will measure latency and throughput metrics to validate the architecture's efficiency and reliability. The framework's modular design aims to provide scalability and adaptability to accommodate both technological advancements and emerging security challenges. The proxy-based security framework presented offers a holistic and forward-looking approach to safeguarding in-vehicle networks. It provides automotive manufacturers with the tools to develop connected vehicles that combine intelligence and efficiency with robust protection against diverse cybersecurity threats.
Electric vehicle (EV) transmissions play a vital role in powering EVs by channeling energy from the electric motor to the wheels. Recently, the focus has shifted to multi-speed transmissions in the EV sector due to their potential to improve efficiency and performance. By utilizing various gear ratios, these transmissions enable the motor to function within its most efficient range across different speeds. Most of these transmissions need electric control unit (ECU) with software for optimal functionality and smoother gear shifting. These controllers incorporate controller area network (CAN) communication protocol to operate along with other ECUs. Thus validation of these transmissions is a challenge as they are clutch less, motor has to be controlled for speed matching and have electro mechanical systems replacing conventional systems for operation. This paper proposes a methodology to validate multispeed EV transmissions on a test bench. The validation setup consists of electric motor at the input of a two speed EV transmission and inertia at the output of the transmission to simulate vehicle along with control unit flashed with vehicle level software. Scripts based on C-language and panels are developed which use CAN database (dbc) file of the vehicle to communicate between electric motor, transmission and vehicle control unit. Using the panels the user either controls the gear shift actuation manually or automate the gear shifting process as per vehicle operating conditions for evaluating the gear shift process. Using the mentioned methodology various vehicle scenarios can be simulated and validated on test bench at early stages, thus providing important feedback in development stage for software refinement for optimal operation of the motor and transmission actuator during gear shift process. The developed scripts can be modified to match for other vehicle configurations.
With the rapid adoption of electric vehicles (EVs), ensuring the reliability, safety, and cost-effectiveness of power electronic subsystems such as onboard chargers, DC-DC converters, and vehicle control units (VCUs) has become a critical engineering focus. These components require thorough validation using precise calibration and communication protocols. This paper presents the development and implementation of an optimized software stack for the Universal Measurement and Calibration Protocol (XCP), aimed at real-time validation of VCUs using next-generation communication methods such as CAN, CAN-FD, and Ethernet. The stack facilitates read/write access to the ECU’s internal memory in runtime, enabling efficient diagnostics, calibration, and parameter tuning without hardware modifications. It is designed to be modular, platform-independent, and compatible with microcontrollers across different EV platforms. By utilizing the ASAM-compliant protocol architecture, the proposed system significantly reduces dependency on expensive proprietary tools, offering a cost-effective alternative for the Indian EV industry.
This paper presents a comprehensive testing framework and safety evaluation for Vehicle-to-Vehicle (V2V) charging systems, incorporating advanced theoretical modeling and experimental validation of a modern, integrated 3-in-1 combo unit (PDU, DCDC, OBC). The proliferation of electric vehicles has necessitated the development of resilient and flexible charging solutions, with V2V technology emerging as a critical decentralized infrastructure component. This study establishes a rigorous mathematical framework for power flow analysis, develops novel safety protocols based on IEC 61508 and ISO 26262 functional safety standards, and presents comprehensive experimental validation across 47 test scenarios. The framework encompasses five primary test categories: functional performance validation, power conversion efficiency optimization, electromagnetic compatibility (EMC) assessment, thermal management evaluation, and comprehensive fault-injection testing including Byzantine fault scenarios. Through systematic experimental validation using advanced power electronics simulation and hardware-in-the-loop (HIL) testing, we demonstrate 98.2% power conversion efficiency, sub-50ms fault detection response times, and compliance with automotive safety integrity level ASIL-D requirements. Our results establish the theoretical foundations and practical validation methodologies essential for next-generation V2V charging infrastructure deployment.
The automotive industry is undergoing a transformational shift with the addition of Virtual ECU in the development of software and validation. The Level 3 Virtual ECU concept will lead to the transformation in the SDLC process, as early detection of defects will have a significant impact on cost and effort reduction. This paper explains the application of a Level 3 virtual ECU which can enable to perform testing in initial period considering the Shift Left Strategy, which will significantly reduce development time. This paper demonstrates various development and validation strategies of virtual ECU and how it can impact project timeline.
The rapid evolution of intelligent transportation systems has made drivers’ attentiveness and adherence to safety protocols more critical than ever. Traditional monitoring solutions often lack the adaptability to detect subtle behavioral changes in real time. This paper presents an advanced AI-powered Driver Monitoring System designed to continuously assess driver behavior, fatigue, distractions, and emotional state across various driving conditions. By providing real-time alerts and insights to vehicle owners, fleet operators, and safety personnel, the system significantly enhances road safety. The system integrates lightweight AI/ML algorithms, image processing techniques, perception models, and rule-based engines to deliver a comprehensive monitoring solution for multiple transportation modes, including automotive, rail, aerospace, and off-highway vehicles. Optimized for edge devices, the models ensure real-time processing with minimal computational overhead. Alerts are communicated through web and mobile platforms, supplemented by audio-visual cues for prompt user responses. Data from multi-camera setups, auditory sensors, and vehicle CAN bus inputs are processed by a real-time analytics engine that detects abnormal behaviors and safety violations, improving situational awareness and enabling timely interventions. For both individual drivers and fleet managers, the platform serves as an intelligence hub that boosts situational awareness, operational efficiency, and safety compliance. Drivers receive real-time feedback on their behavior, allowing them to make proactive adjustments and reduce risks. Fleet managers can leverage cloud-based connectivity to access predictive analytics, real-time monitoring, and detailed historical behavior data. This enables the identification of unsafe driving patterns, enforcement of safety protocols, and optimization of fleet performance. The system also simplifies regulatory reporting and auditing processes, ensuring compliance with safety standards. By continuously monitoring driver behavior, managers can foster a culture of safety and performance while improving overall fleet operations.
The rapid evolution of in-vehicle electronic systems toward zonal based architectures introduces a new layer of complexity in automotive diagnostics. Traditional architectures, built on Controller Area Network (CAN) and Local Interconnect Network (LIN) protocols, operate on a uniform Real-Time Operating System (RTOS), enabling simplified and consistent diagnostic workflows across Electronic Control Units (ECUs). However, next-generation platforms must accommodate diverse communication protocols (e.g., CAN, LIN, DoIP, SOME/IP) and heterogeneous operating systems (e.g., RTOS, Linux, QNX), resulting in fragmented and inflexible diagnostic processes. This paper presents a Diagnostic controller that addresses these challenges by enabling unified, scalable, and adaptive diagnostic capabilities across modern vehicle platforms. The proposed system consolidates protocol handling at the application level, abstracts diagnostic complexities, and allows cross-platform communication through hypervisor-based services. Diagnostic configurations are decoupled from static software builds and delivered dynamically as configuration files, supporting real-time adaptability to software updates and Over-The-Air (OTA) changes. This architecture also facilitates seamless interoperability across operating systems and enables service-based diagnostics in line with the industry’s move toward software-defined vehicles. The result is a robust, future-ready diagnostic solution optimized for high software variability, platform heterogeneity, and increasing system complexity in modern automotive ecosystems.
This article suggests a validation methodology for autonomous driving. The goal is to validate front camera sensors in advanced driver-assist systems (ADAS) based on virtually generated scenarios. The outcome is the CARLA-based hardware-in-the-loop (HIL) simulation environment (CHASE). It allows the rapid prototyping and validation of the ADAS software. We tested this general approach on a specific experimental application/setup for a vehicle front camera sensor. The setup results were then proven to be comparable to real-world sensor performance. The CARLA simulation environment was used in tandem with a vehicle CAN bus interface. This introduced a significantly improved realism to user-defined test scenarios and their results. The approach benefits from almost unlimited variability of traffic scenarios and the cost-efficient generation of massive testing data.
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