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SIL3-certified software is released for RA and RX microcontrollers

Thu, Mar 10, 2022

Functional safety software that meets the IEC 61508 standard for Renesas Electronics’ RA and RX families of microcontrollers (MCUs) are now available. Renesas offers IEC 61508 SIL3-certified self-test software for both Arm Cortex-M23 and -M33-based MCUs. Renesas also announced the IEC 61508 SIL3 certified PROFIsafe Application Software for RX MCUs. Renesas added that it is the industry’s first semiconductor supplier to offer these hardware-software solutions.

When building a safety critical system using an MCU, it is required to provide device-level diagnostics. With Renesas’ SIL3 certified Self-Test Software, customers can leverage IEC 61508 certifications for the MCUs CPU, ROM and RAM when certifying the overall system. Renesas Self-Test Software kit currently supports Arm Cortex-M23 and -M33-based RA2, RA4, and RA6 series MCUs.

To address the need for safe network communication in applications that use industrial Ethernet, Renesas introduced the PROFIsafe Application Software. The SIL3-certified PROFIsafe Application Software Kit realises PROFIsafe functionalities on ProfiNet slave devices and eliminates the certification step for network communications. It works with Renesas’ certified SIL3 System Software kit for RX MCUs. The PROFIsafe Application Software supports RX200, RX600 and RX700 series MCUs. Self-Test Software is already available for RX MCUs.

Both the Self-test Software for the RA Family and the PROFIsafe Application Software for the RX Family have been certified by TÜV Rheinland.

Both the IEC 61508 SIL3-certified Self-Test software kit and PROFIsafe Application Software kit are available today. In addition, Renesas offers reference documentation, an evaluation board for the RX family, and an IEC 61508 Certification Kit for RX compilers.

Renesas Electronics delivers trusted embedded design innovation with complete semiconductor solutions that enable billions of connected, intelligent devices. It produces microcontrollers, analogue, power and SoC products, for a broad range of automotive, industrial, infrastructure and IoT applications.

http://www.renesas.com

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Rad-hard ICs are for cost-conscious satellites, says ST

Thu, Mar 10, 2022

Radiation-hardened (rad-hard) components by STMicroelectronics help low earth orbit (LEO) satellites expand communication and earth observation services. ST said it is simplifying the design and volume production of the new generation of reliable small, inexpensive satellites to deliver services like earth observation and broadband internet from LEOs.

The new series of rad-hard power analogue and logic ICs are supplied in inexpensive plastic packages. The initial nine devices have been released and include a data converter, a voltage regulator, an LVDS transceiver, a line driver, and five logic gates that are used throughout systems like power generation and distribution, on-board computers, telemetry star trackers, and transceivers.

The nine parts are the LEO3910 2A adjustable low-dropout voltage regulator, the LEOAD128 eight-channel, 1Mssample per second 12-bit ADC, the LEOLVDSRD 400Mbits per second LVDS driver-receiver, LEOAC00 quad two-input NAND gate, LEOAC14 hex inverter with Schmitt-trigger input, LEOA244 octal bus buffer with tri-state outputs, LEOAC74 dual D-type flip-flop, LEOAC08 quad two-input AND gate and LEOAC32 quad two inputs OR gates.

The LEO rad-hard plastic parts are ready to use in ‘New Space’ applications, with optimised qualification and production flows and economies of scale. They require no additional qualification or up-screening from their users, and therefore eliminate significant cost and risk, ST confirmed.

The series ensures a radiation hardness match to the LEO mission profile, with a total ionisation dose immunity up to 50krad(Si), high immunity to total non ionising dose and single event latch-up (SEL) immunity up to 62.5MeV.cm²/mg. The parts are assembled on the same production line used for ST’s AEC-Q100 automotive-qualified ICs.

The parts outgassing is characterised to ensure it stays within the commonly accepted limits of New Space. External terminations’ finishing ensures the absence of whiskers in space, while being compatible with both leaded (Pb) and pure tin mounting processes as well as REACH-compliant.

ST said it continue to grow the series adding more functions in the coming months to further expand designers’ choices.

http://www.st.com

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R-Car V4H SoC achieves deep learning for automated driving

Wed, Mar 09, 2022

For central processing in advanced driver assistance systems (ADAS) and automated driving systems, the R-Car V4H SoC achieves deep learning up to to 34 tera operations per second (TOPS). This equips it for high speed image recognition and processing surrounding objects using automotive cameras, radar and lidar, said Renesas Electronics.

The R-Car V4H allows customers to develop cost-competitive, single-chip, ADAS electric control units (ECUs), said Renesas. It combines IP and hardware optimisation, to support driving systems appropriate for automated driving levels 2+ and 3, which are responsible for managing the highest volume of processing, including full NCAP 2025 support. The R-Car V4H also supports surround view and automatic parking functions with 3D visualisation effects such as realistic rendering.

The SoC development process targets ASIL D systematic capability for all safety relevant IP for ISO 26262 functional safety. The signal processing portion of the R-Car V4H is expected to achieve ASIL B and D metrics for the real time domain.

Renesas provides a dedicated power management for the R-Car V4H based around the RAA271041 pre-regulator and the RAA271005 power management IC (PMIC). This enables a power supply for the R-Car V4H and peripheral memories from the 12V supply of the vehicle battery at low power operation while targeting ASIL D compliance for systematic and random hardware faults with a low bill of materials cost, confirmed Renesas.

An R-Car V4H software development kit (SDK) is available for initial device evaluation, and software development including deep learning. The SDK offers full functionality for machine learning development, and optimisation of embedded systems for performance, power efficiency, and functional safety. Complete simulation models are available. The software is operating system-agnostic, pointed out Renesas. When developing from scratch, Fixstars’ Genesis platform enables engineers to evaluate R-Car from anywhere via their cloud solution and can provide CNN benchmark results.

The SoC has four Arm Cortex-A76 cores operating at 1.8Ghz for a total of 49kDMIPS of general compute, three lockstep Arm Cortex-R52 cores at 1.4Ghz, for a total of 9kDMIPS to support ASIL D real time operation and eliminate the need for external microcontrollers. There is also dedicated deep learning and computer vision IP, and image signal processor (ISP) with parallel processing for machine and human vision, image renderer (IMR) for fisheye distortion correction or other mathematical operation and an AXM-8-256 GPU operating at 600MHz, for a total of over 150 GFLOPS. There are also dedicated automotive interfaces (CAN, Ethernet AVB, TSN and FlexRay) and two fourth generation PCIe interfaces.

Samples of the R-Car V4H SoC are available now, with mass production scheduled for the second quarter of 2024.

http://www.renesas.com

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AI software provides insight into productivity

Tue, Mar 08, 2022

Integrated manufacturing software has been released by MicroAI which extends edge native AI into the manufacturing environment. MicroAI Factory provides real time analysis and deep insight into machine and human productivity, says the company.

The software suite leverages edge-native AI to ingest manufacturing floor data from existing systems and sensors to improve overall equipment effectiveness, real time cycle time analysis and predictive maintenance, confirmed MicroAI.

For local deployment within an industrial computing appliance at a manufacturing or industrial site, MicroAI Factory ingests data from programmable logic controllers (PLCs) and sensors associated with machinery or humans within the production site. It uses an edge-native AI engine to auto-develop cycle time analysis and behavioural models that provide deep insight into the operations of machines and human behaviour. This modelling provides real time analysis of performance, productivity, and uptime, while detecting operating anomalies and enabling alarms, ticketing, and maintenance scheduling from pre-set thresholds.

“MicroAI Factory improves overall equipment effectiveness for manufacturers by providing a holistic, real-time cycle-time analysis of operations and providing advanced, early anomaly detection to predict potential failures and performance issues,” said Yasser Khan, CEO of MicroAI. “Ultimately, MicroAI Factory will transform equipment from human-managed to self-managed.”

MicroAI Factory is deployed at the edge within a small form factor computing appliance and is connected to PLCs and sensor systems within the factory or industrial facility. All processing, analysis, and storage of the data occurs in the facility premises, eliminating the data security and connection reliability challenges associated with cloud computing.

Operation management is provided as single point of command and control, while dashboards can be accessed in the facility via local area network (LAN), or offsite via the internet. Servers can be networked across multiple facilities to share insight without exposing data. MicroAI Factory can be deployed as a point solution within a single facility, or at multiple sites that operate independently for an overview while still maintaining data integrity at each individual site.

Based in Dallas, Texas, USA, MicroAI specialises in edge-native AI and machine learning (ML). The company’s mission is to automate the management of machines, enable them to self-monitor and self-report, and provide the most accurate information on machine health. The company’s software is deployed within edge appliances aggregating data from multiple machines, as well as embedded on microcontrollers (MCUs) and microprocessors (MPUs) within an individual machine. MicroAI’s software is used by manufacturing and industrial processing companies, original equipment manufacturers (OEMs), and asset owners to predict failures, identify security issues, and improve life-cycle management and overall equipment effectiveness (OEE).

http://www.micro.ai

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SIL3-certified software is released for RA and RX microcontrollers

Rad-hard ICs are for cost-conscious satellites, says ST

R-Car V4H SoC achieves deep learning for automated driving

AI software provides insight into productivity

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