Displaying posts in the categoryAutomotive
Automotive articles
SoC Design
Sooner or later, an automotive customer sends a chip team a list of requests: an FMEDA, a safety manual, a dependent failure analysis, and a statement of which ASIL the part can support. ISO 26262 sits behind that list, and it was written for road vehicle systems, not for silicon. A semiconductor team has to work out what the standard means for a block of RTL that has no vehicle attached to it yet. This post goes through what Part 5 and Part 1…
by
Murugavel Ganesan
November 11, 2026
Special Reports
From electronic mirrors to predictive perception: how cameras, silicon, connectivity and AI are reshaping the intelligent vehicle. Automotive cameras have moved from simple reversing aids to the main source of meaning in ADAS perception: lanes, signs, traffic lights and road users. Over five overlapping generations they went from one camera serving one function to many cameras feeding a central AI platform alongside radar and LiDAR. The next …
by
Murugavel Ganesan
October 28, 2026
Tutorials
Automotive electronics work as one control loop: sensors measure what is happening in and around the car, microcontrollers and processors decide what to do, vehicle networks carry the data and commands, and actuators and power electronics carry out the decision. In an electric vehicle the same electronics also convert and manage the energy that moves the car. No single part is useful on its own; reliability comes from designing the whole chain t…
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The Editor's Desk
October 26, 2026
Video
Time-Sensitive Networking (TSN) is a set of IEEE 802.1 standards that make standard Ethernet deterministic. It gives every device a shared sense of time, schedules time-critical traffic into reserved windows, lets urgent frames interrupt long ones, and can send critical streams over two paths at once. The result is bounded latency, low jitter and high reliability, so control traffic and ordinary data can share one network in cars, factories and …
by
Murugavel Ganesan
February 17, 2026
Top 50
The hardest part of automotive edge AI is not the chip itself but everything around it: power and heat in a sealed enclosure, safety certification of models that do not behave deterministically, security of over-the-air updates, and the cost of putting data-centre class compute into a mass-market car. Implementing edge AI in a vehicle is not just about fitting a faster processor; it means rebuilding the vehicle architecture so the car acts as a …
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Murugavel Ganesan
February 02, 2026
Process Technology
Building an automotive chip on a commercial wafer process and then qualifying it to AEC-Q100 is sometimes the only option, but on mature nodes it is usually a false saving. AEC-Q100 shows that sampled parts survived a set of stress tests; it does not make the silicon as robust as a process built for automotive. What you save on wafers you tend to spend again on screening, yield loss, test time and field reliability risk. In the semiconductor w…
by
Murugavel Ganesan
December 12, 2025
