Nissan Technical Centre Europe (NTCE) has reduced vehicle software investigation time from two weeks to two days using AI-assisted diagnostics and event-driven data collection. Following a year of development and testing, the automaker is expanding the technology across its pre-production vehicle validation process.
The system, developed by Sonatus, will become part of NTCE’s standard validation workflow for future vehicle programs, including upcoming Nissan LEAF models.
Nissan’s vehicle validation process spans approximately 12 months from initial prototypes to the start of production. During this period, engineers must identify and resolve software faults across increasingly complex vehicle systems.
A problem detected in one subsystem may originate elsewhere, requiring engineers to examine data from multiple electronic control units to determine its source.
Traditionally, investigating these issues involved collecting large amounts of data during test drives and analyzing it afterward. If the information was insufficient to identify a fault, engineers often needed to repeat the test. This created delays and increased demand for prototype vehicles, which are costly to build and maintain.
Sonatus’ Fastlane platform changes that process by allowing engineers to configure targeted data-collection policies remotely. When a predefined event occurs during testing, the system automatically captures relevant vehicle data at the time of the fault.
The captured information is analyzed using Fastlane Insight, which correlates it with Nissan’s engineering specifications and diagnostic records to identify potential root causes. The system uses Anthropic’s Claude AI model through Amazon Web Services’ Bedrock platform and provides references to the engineering information supporting its findings.
To support testing on prototype vehicles, NTCE is deploying Fastlane Copilot, a plug-in hardware and software system that connects through a dedicated vehicle harness without requiring disassembly. The system supports in-vehicle fault detection and sends captured data to cloud-based diagnostic tools for further analysis.
According to the companies, the updated workflow has reduced vehicle setup time from more than an hour to minutes. Remote access to collected data also allows engineering teams to investigate different software issues using the same prototype vehicle without requiring separate test sessions.
The approach is intended to help NTCE manage increasing software complexity within the limited time available before production. By capturing fault-specific data as issues occur, engineers can reduce repeated testing and spend less time gathering the information needed to diagnose software problems.
The expanded deployment will support future Nissan vehicle programs, including the LEAF, although the companies have not specified which models were used to establish the reported time savings.
A detailed case study of Nissan’s vehicle validation process is available for download on Sonatus’ website.
Filed Under: Technology News, Testing and Safety