In most cases, it is actually sufficient to look at the ECU’s inputs and outputs to functionally test a component (Figure 1). However, this becomes difficult when state machines are used in the ECU. Their current states can only be derived indirectly by their effects at the ECU’s outputs. In the case of sensors whose values are not transmitted over the network system, it is also very difficult for the test engineer to localize errors to the software interface. From outside the ECU, it is not clear exactly where the sensor value was incorrectly processed.

Different methods that offer access to internal ECU data are used, depending on the phase of ECU development. In early phases, for example, internal ECU values are often output in so-called “reserved development messages” (Figure 1). For the functional developer at a supplier, this is an effective and quick method that precisely targets a specific objective. However, these supplemental messages must be removed for later development phases, especially for system integration and series production. They induce additional bus load, and in the worst case they might even collide with messages of other system components. Another way to access internal values is through diagnostics (Figure 1). Some information is available directly via diagnostics, e.g. diagnostics offers access to fault memory. Special diagnostic services are also provided to read the required values from memory. The advantage here is that a standardized access method is used. The only precondition is full integration of the diagnostic driver; this is generally provided in today’s ECUs. The disadvantage of this method is that a lot of unnecessary diagnostic protocol information is transmitted along with the actual measured values, and this adds load to the network system interface. A data flow analysis of many values is not possible, especially since the measured values do not contain time stamp information.

XCP For Test Access

If network interface load needs to be kept low, an alternative is to use a calibration protocol. Originally, such protocols were developed for the ECU calibrator. They let calibrators modify parameters or characteristic maps in the ECU to optimize their algorithms. With the XCP protocol standardized by ASAM, the user can read individual values directly from the ECU as needed. The protocol can also periodically supply a defined set of measured values from the ECU via so-called Data Acquisition (DAQ) lists. The XCP protocol was defined for efficient provision of data over the network medium. As an example, after configuration the DAQ lists can be transmitted in response to a single identifier from the test system. In addition, measurement times of the DAQ lists can be synchronized to internal ECU processes. Automated test systems place similar requirements on the system. Use of the XCP protocol makes it possible to integrate internal values in test sequences without excessive loading of the ECU or the network system used. Another reason that a widely used standard like XCP is ideal is that it is very easy to configure in the tool chain. All necessary information is already in the A2L file such as internal program memory locations with their names and communication parameters. Depending on the development environment, the A2L file is either automatically generated, or it may need to be generated in a separate step from the linker-map information. In the test tool, the user only has to configure this file once for each ECU used in the test. In a second step, the user selects the symbols needed for the test sequences from the A2L file.

CANoe Option .AMD/XCP

Option .AMD/XCP supplements the CANoe test tool from Vector with the convenient option of reading and writing internal ECU values. Besides supporting the XCP standard, it also supports the previous protocol CCP. Once the A2L file has been configured and the necessary values selected, CANoe automatically acquires them and maps them as system variables. The user can then use these variables in any of the testing tasks. Besides offering access to ECU inputs and outputs, they also provide an in-depth look into the ECU’s memory (Figure 2).

In simple analysis tasks, users can display the data in the Trace or Graphic Window and use panels to evaluate the results. For more complex test sequences, CANoe’s Test Feature Set offers extensive options for creating test cases and automatically evaluating them. For example, this enables checking of the Network Management state machine for correct functionality. The necessary stimulation is performed in the CANoe rest-of-bus simulation, and the ECU’s reaction is not just measurable on the network; it is directly measurable in the ECU over XCP. The effort required to execute test cases is also significantly reduced, e.g. for test cases that require sensors. The test system writes the sensor values directly to memory cells in the ECU over XCP. This eliminates the need to connect and control original sensors at the ECU inputs – a demanding task. The ECU is notified that the sensor and associated hardware driver have measured the values correctly. The same approach can be used in the other direction. Here it is assumed that the output stage and actuator have been tested and accepted. In this case, the test system measures the value that the application prescribes to the driver stage over XCP.

Access With Large Quantities Of Data

If large quantities of data need to be exchanged between the test system and the ECU in a test case, or if especially quick processes need to be monitored, an XCP connection over a CAN network is no longer effective. In such cases, direct access to the ECU’s debug interfaces is recommended. This could be implemented via a NEXUS or JTAG interface, for example. These protocols directly access the ECU memory − partly without load on the microcontroller. Taking this approach, the user can quickly read out very large quantities of data from the system without loading the network and the ECU.

Vector VX hardware, for example, offers direct access to an ECU’s NEXUS or JTAG interface (Figure 2). Since this hardware communicates with the test system via XCP-on-Ethernet, integration in CANoe is as easy as integration for XCP access over CAN. Combining VX hardware with the CANoe test system further improves test system performance, without any negative effects on the communication medium. (MT)

NB: Oliver Falkner is group leader at Vector in product management of the Networks and Distributed Systems product line. Views expressed are personal.

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Bengaluru-headquartered ER&D company L&T Technology Services (LTTS) has announced a multi-year engagement within its mobility segment from an automotive manufacturer. The agreement involves software, connectivity and digital engineering services across vehicle technology domains. This win follows the company’s investments in R&D labs and mobility infrastructure designed for programs with global manufacturers.

The engagement covers mobility engineering capabilities, including embedded systems, digital platforms, verification and validation, cloud integration and cybersecurity. LTTS intends to use its engineering expertise and delivery frameworks to support the customer's technology roadmap. 

At present, LTTS operates 22 design centres and 100 innovation labs globally.

The agreement strengthens the partnership between LTTS and the automotive manufacturer in the area of mobility engineering. The company provides design, development, and testing services across the mobility, sustainability, and tech segments. 

Alind Saxena, Executive Director and President, Mobility and Tech at L&T Technology Services, said, “We are proud to deepen our partnership with the valued customer through this strategic engagement. LTTS brings together domain-led engineering, secure development practices and excellence in global delivery to accelerate the future of premium mobility. The win reflects the trust placed in our teams and our commitment to delivering world-class engineering at scale”.

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French technology company Valeo and NATIX Network have announced a partnership to develop a multi-camera World Foundation Model (WFM). The project combines Valeo’s research in artificial intelligence and generative modelling with NATIX’s decentralised physical infrastructure network (DePIN) to create an open-source platform for autonomous driving and robotics.

The initiative aims to move beyond perception-based models by creating a system capable of predicting future states and reasoning about physical interactions in a four-dimensional environment. The model will be trained using NATIX’s data network, which has collected 600,000 hours of video data across the US, Europe and Asia over seven months. This data provides the multi-camera inputs necessary for the spatial perception required by autonomous vehicles and robots.

The partnership builds upon Valeo’s existing open-source frameworks, VaViM (Video Autoregressive Model) and VaVAM (Video-Action Model). While these frameworks were previously trained primarily on front-camera datasets, the integration of NATIX’s multi-camera network expands the AI’s field of vision to 360 degrees.

Under the open-source framework, the partners will release models, datasets and training tools. This approach is intended to allow the research community to fine-tune models and benchmark physical AI across various driving conditions and geographic regions. The collaboration seeks to accelerate the deployment of end-to-end AI models by learning from real-world edge cases captured by vehicles in operation.

Marc Vrecko, Chief Executive Officer, Valeo’s Brain Division, said, “Since our creation in 2018, Valeo’s AI research center has been at the forefront of AI research in the automotive industry, especially in the fields of assisted and autonomous driving. Our goal has always been to advance mobility intelligence safely and responsibly. By combining Valeo’s generative world modeling research expertise with NATIX’s global multi-camera data, we are accelerating both the quality and the accessibility of next-generation end-to-end AI models, enabling the research community to build upon strong open models.”

Alireza Ghods, CEO and Co-Founder, NATIX, added, “WFMs are a once-in-a-generation opportunity — similar to the rise of LLMs in 2017–2020. The teams that build the first scalable world models will define the foundation of the next AI wave: Physical AIs. With our distributed multi-camera network, NATIX has a clear advantage of being able to move faster than large OEMs.”

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Tata Technologies has announced the completion of the 3^rd edition of its innovation hackathon, InnoVent 2026, supported by Amazon Web Services (AWS). The initiative invited engineering students to develop solutions for mobility challenges in the automotive and manufacturing sectors. The programme received participation from 10,247 students across 404 colleges in India, resulting in 2,822 projects.

The competition focused on the theme of intelligence-driven mobility for the year 2030. Participants received over 650 hours of mentoring and training from subject matter experts to convert their concepts into prototypes. The top 10 teams presented their work at the company's Hinjewadi campus in Pune before a jury of industry leaders from Jaguar Land Rover, Air India and ES-Tec Group.

Team Drushti from CMR College of Engineering & Technology, Hyderabad, secured the first prize of INR 300,000 for a system that customises vehicle infotainment for visually impaired drivers. Second place went to Team The T-Factor from Vellore Institute of Technology, Chennai, for an AI-based breakdown prevention system. Team SwarmSync from the International Institute of Information Technology (I²IT), Pune, took third place for an intelligent fleet management solution using V2X communication.

Tata Technologies offered career opportunities to all 42 finalists involved in the top projects. Furthermore, all participants were granted one-year access to the iGETIT learning platform to study emerging technologies. The finalist projects covered areas such as blockchain for vehicle security, wireless charging for electric vehicles, and AI-led battery monitoring.

The event featured a humanoid robot that performed roles such as coordinating panel discussions and interacting with attendees. A panel of industry experts discussed the global demand for engineering talent and the impact of technology on future mobility.

Warren Harris, MD & CEO, Tata Technologies, said, "InnoVent at Tata Technologies represents our conviction that the future is shaped by those who combine engineering excellence with human purpose to engineer a better world".

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Kia India has announced the re-launch of its Kia Inspiring Drive (K.I.D) Program, debuting alongside the New Kia Seltos. The initiative is a driving score system designed to monitor real-time behaviour and provide insights into habits. Accessed via the Kia Connect app, the programme will be rolled out across the company’s connected vehicle portfolio in phases.

The K.I.D score is calculated using a three-month rolling average based on parameters including rapid acceleration, rapid deceleration and sudden starts. To ensure data accuracy, the system applies a weighted value based on the specific vehicle. This methodology aims to reflect long-term driving patterns rather than isolated incidents.

The programme incorporates community-based leaderboards, allowing owners to compare scores and track their standing within the Kia community. By turning road safety into an interactive experience, the manufacturer intends to encourage responsible driving through recognition and competition.

The behaviour-based scoring system provides data to help users understand the impact of their habits on road safety. Kia is supporting the re-launch with a digital and press campaign to increase awareness among its customer base.

Atul Sood, Senior Vice-President – Marketing & Sales, Kia India, said, “Safety remains at the core of Kia’s philosophy, and with the re-launch of the Kia Inspiring Drive program alongside the New Seltos, we are taking another meaningful step towards encouraging responsible driving behaviour. By offering customers clear, data-driven insights into their driving patterns, the KID program empowers them to make safer choices on the road, while also enhancing their overall ownership experience.”

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