Browse Topic: On-board diagnostics (OBD)
The problem of monitoring the parametric failures of a traction electric drive unit consisting of an inverter, a traction machine and a gearbox when interacting with a battery management system has been solved. The strategy for solving the problem is considered for an electric drive with three-phase synchronous and induction machines. The drive power elements perform electromechanical energy conversion with additional losses. The losses are caused by deviations of the element parameters from the nominal values during operation. Monitoring gradual failures by additional losses is adopted as a key concept of on-board diagnostics. Deviation monitoring places increased demands on the information support and accuracy of mathematical models of power elements. We take into account that the first harmonics of currents and voltages of a three-phase circuit are the dominant energy source, higher harmonics of PWM appear as harmonic losses, and mechanical losses in the rotor and gearbox can be
The term Software-Defined Vehicle (SDV) describes the vision of software-driven automotive development, where new features, such as improved autonomous driving, are added through software updates. Groups like SOAFEE advocate cloud-native approaches – i.e., service-oriented architectures and distributed workloads – in vehicles. However, monitoring and diagnosing such vehicle architectures remain largely unaddressed. ASAM’s SOVD API (ISO 17978) fills this gap by providing a foundation for diagnosing vehicles with service-oriented architectures and connected vehicles based on high-performance computing units (HPCs). For service-oriented architectures, aspects like the execution environment, service orchestration, functionalities, dependencies, and execution times must be diagnosable. Since SDVs depend on cloud services, diagnostic functionality must extend beyond the vehicle to include the cloud for identifying the root cause of a malfunction. Due to SDVs’ dynamic nature, vehicle systems
This SAE Information Report describes the collection of IUMPR data required by the heavy-duty onboard diagnostic regulation 13 CCR § 1971.1 (l)(2.3.3), using SAE J1939-defined messages incorporated in a suite of software functions.
This SAE Recommended Practice supersedes SAE J1930 MAR2017 and is technically equivalent to ISO 15031-2. This document is applicable to all light-duty gasoline and diesel passenger vehicles and trucks, and to heavy-duty gasoline vehicles. Specific applications of this document include diagnostic, service and repair manuals, bulletins and updates, training manuals, repair databases, underhood emission labels, and emission certification applications. This document should be used in conjunction with SAE J1930DA Digital Annexes, which contain all of the information previously contained within the SAE J1930 tables. These documents focus on diagnostic terms applicable to electrical/electronic systems, and therefore also contain related mechanical terms, definitions, abbreviations, and acronyms. Even though the use and appropriate updating of these documents is strongly encouraged, nothing in these documents should be construed as prohibiting the introduction of a term, abbreviation, or
The University of Detroit Mercy Vehicle Cyber Engineering (VCE) Laboratory together with The University of Arizona is supporting Secure Vehicle Embedded Systems research work and course projects. The University of Detroit Mercy VCE Laboratory has established several testbeds to cover experimental techniques to ensure the security of an embedded design that includes: data isolation, memory protection, virtual memory, secure scheduling, access control and capabilities, hypervisors and system virtualization, input/output virtualization, embedded cryptography implementation, authentication and access control, hacking techniques, malware, trusted computing, intrusion detection systems, cryptography, programming security and secure software/firmware updates. The VCE Laboratory testbeds are connected with an Amazon Web Services (AWS) cloud-based Cyber-security Labs as a Service (CLaaS) system, which allows students and researchers to access the testbeds from any place that has a secure
Sumitomo Rubber Industries first announced its Sensing Core technology in 2017. But it wasn't until 2024 that the Japanese tire maker used its debut appearance at CES to promote the sensor-free signal analyzer. Sumitomo president and CEO Satoru Yamamoto said the company exhibited at CES, “to expand our partner companies and to get more drivers and companies to know about this sensing core technology.”
Recent legislations require very low soot emissions downstream of the particulate filter in diesel vehicles. It will be difficult to meet the new more stringent OBD requirements with standard diagnostic methods based on differential sensors. The use of inexpensive and reliable soot sensors has become the focus of several academic and industrial works over the past decade. In this context, several diagnostic strategies have been developed to detect DPF malfunction based on the soot sensor loading time. This work proposes an advanced online diagnostic method based on soot sensor signal projection. The proposed method is model-free and exclusively uses soot sensor signal without the need for subsystem models or to estimate engine-out soot emissions. It provides a comprehensive and efficient filter monitoring scheme with light calibration efforts. The proposed diagnostic algorithm has been tested on an experimentally validated simulation platform. 2D signatures are generated from soot
This document is intended to satisfy the data reporting requirements of standardization regulations in the United States and Europe, and any other market that may adopt similar requirements in the future. This document specifies: a Message formats for request and response messages. b Timing requirements between request messages from external test equipment and response messages from vehicles, and between those messages and subsequent request messages. c Behavior of both the vehicle and external test equipment if data is not available. d A set of diagnostic services, with corresponding content of request and response messages. e Standardized source and target addresses for clients and vehicle. This document includes capabilities required to satisfy OBD requirements for multiple regions, model years, engine types, and vehicle types. At the time of publication many regional regulations are not yet final and are expected to change in the future. This document makes no attempt to interpret
Next-generation vehicle electrical architectures will be based on highly sophisticated domain controllers called HPCs (high-performance computers). These HPCs are more alike gaming PCs than as the traditional ECUs (electronic control units). Today’s diagnostic communication protocol, e.g., UDS (Unified Diagnostic Services, ISO 14229-1) was developed for ECUs and is not fit to be used for HPCs. There is a new protocol being developed within ASAM, SOVD (service-oriented vehicle diagnostics), which is based on a RESTful API (REpresentational State Transfer Application Programming Interface) sent over http (hypertext transfer protocol). But OBD (OnBoard Diagnostic) under the emissions regulation is not yet updated for this shift of protocols and therefore vehicle manufacturers must support older OBD protocols (e.g., SAE J1979-2) during the transition phase. Another problem is that some of the software packages may fall under the DEC-ECU (diagnostic or emission critical electronic control
On-board diagnostics (OBD) systems support the protection of the environment against harmful pollutants such as carbon monoxide (CO), nitrogen oxide (NOx), hydrocarbons (HC) and particulate matters (PM) emitted by combustion engines. 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. For the purpose of communication, both the test equipment and the vehicle must support the same communication protocol stack. The communication protocol SAE J1979, also known as ISO 15031, that has been in use for decades will be replaced by SAE J1979-2 for vehicles with combustion engines and by SAE J1979-3 for zero-emission-vehicle (ZEV) propulsion systems.
The LEV IV FTP PM limit in the recently approved CARB ACC II regulations for passenger cars and light duty trucks will be 1 mg/mile starting in 2025. Gravimetric PM measurement at these levels is very challenging as the net mass of PM on the filter in full flow tunnel testing ranges between 8 to 32 micrograms depending on amount of dilution. This is approaching tunnel background levels which, in combination with filter handling, static charge removal and microbalance instability, compounds the uncertainty. One major source of the uncertainty at these low levels is the tunnel contamination resulting in high variability from test to test and cell to cell. This tunnel background is mostly HC artifact which cannot be easily controlled and can be significantly higher than the 5-μg CFR allowable correction limit in some test cells. Items that might affect the PM background include the type of testing being run on the tunnel prior to measuring the background such as OBD, cold and diesel
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