ICs & Semiconductors Archives - Page 6 of 235

Microchip enhances their digital signal controller lineup

Wed, Jun 18, 2025

Evolving security and functional safety demands, coupled with the growing complexity of real-time embedded applications, are driving designers to seek innovative solutions that deliver greater accuracy, improved reliability and compliance with industry standards. To address these challenges, Microchip Technology has added the dsPIC33AK512MPS512 and dsPIC33AK512MC510 Digital Signal Controller (DSC) families to its dsPIC33A DSC product line. The devices enable the implementation of computation-intensive control algorithms for improved energy efficiency in motor control, AI server power supplies, energy storage systems and complex sensor signal processing with Machine Learning (ML)-based inferencing.

The dsPIC33AK512MPS family delivers precise, high-speed control through 78 ps high-resolution Pulse Width Modulations (PWMs) and low-latency 40 Msps ADCs, enabling fast and accurate control loops essential for optimising the performance of Silicon Carbide (SiC) and Gallium Nitride (GaN)-based DC-DC converters. Additionally, dsPIC33AK512MPS devices include advanced security features, an integrated touch controller and a high pin count of up to 128 pins. The dsPIC33AK512MC family is designed to offer low-latency, 40 Msps ADCs and 1.25 ns PWM resolution, providing a feature- and cost-optimised solution for multi-motor control and complex embedded applications.

The dsPIC33A DSC families, with up to 512 KB Flash and a rich peripheral set, integrate a double precision floating-point unit to accelerate mathematical computations and leverage a 32-bit architecture for seamless adoption of model-based design code. Their enhanced instruction set and Digital Signal Processing (DSP) capabilities, including single-cycle MAC operations and a 200 MHz core speed, make these devices highly efficient for low-latency, real-time control applications. Supported by MPLAB Machine Learning Development Suite, dsPIC33A devices streamline the ML workflow by automating data preparation, feature extraction, training, validation and firmware conversion of optimized models.

With a range of hardware safety features, dsPIC33AK512MPS/MC DSCs are compliant with functional safety standards and are developed in accordance with International Organisation for Standardisation (ISO) 26262 and International Electrotechnical Commission (IEC) 61508 processes, making them suitable for safety-critical automotive and industrial applications. To further enhance system-level security, the dsPIC33AK512MPS DSC family includes integrated crypto accelerators and a Flash security module, enabling immutable root of trust, secure boot, secure firmware upgrades and secure debug capabilities.

https://www.microchip.com

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Infineon expands ID portfolio for enhanced flexibility and faster time-to-market

Mon, Jun 16, 2025

Electronic identification (eID) documents are seeing growing demand worldwide as governments push ahead with their digitalisation efforts. To meet these rapidly evolving requirements more quickly and flexibly, Infineon has introduced two new solutions, SECORA ID V2 and the eID-OS. These solutions offer local security printers and card manufacturers greater flexibility in selecting the right solution for their specific project requirements, while helping to reduce development time and accelerate deployment.

SECORA ID V2 is the successor to the SECORA ID V1 Java Card solution for electronic ID and authentication applications in the public sector. The V2 version of SECORA ID increases transaction speed by up to 80 percent compared to its predecessor. It is based on a 40 nm hardware architecture and can transfer data at speeds of up to 6.8 MBit/s. This enables faster personalisation and processing of ID documents and allows for quick and smooth identity checks at borders and security checkpoints. SECORA ID V2 is based on the latest Java Card 3.1 standard and supports biometric match-on-card functions to increase user data protection. Customers benefit from Infineon’s broad applet toolset. It also supports payment tools such as Visa, Mastercard, and Calypso as well as the crypto vision ePasslet Suite. This wide range of applets enables developers to easily integrate and quickly deploy highly customised ID solutions. Furthermore, the sandbox enables the integration of native code without compromising security standards. The SECORA ID V2 platform is Common Criteria EAL6+(high) certified and EMVCo approved.

Infineon eID-OS is the latest addition to the portfolio of native solutions, combining the latest TEGRION security controller with a native operating system. Designed for basic ID application projects, it offers a performance and cost-optimised solution with fast time-to-market. The standards compliant solution is targeting CC EAL 5+ eMRTD (Common Criteria Evaluation Assurance Level for electronic Machine Readable Travel Document) certification and is housed in advanced packaging technology. It optimises the development process, enables rapid deployment, and reduces maintenance costs. Featuring a powerful 32-bit CPU, advanced cryptography accelerators, and the robust Integrity Guard 32 security architecture, eID-OS enables fast and secured transactions with processing times of less than 0.5 seconds. Thanks to simplified implementation, personalisation, and administration, as well as a secured chain of trust and automatic data size detection, customers benefit from low total cost of ownership. In addition, Infineon’s ultra-thin contactless coil-on-module package supports thinner electronic data pages, reducing document costs and the carbon footprint. The space saved can alternatively be used for an additional security layer, making this solution ideal for modern eID projects.

http://www.infineon.com

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ST announces mass production for turnkey Bluetooth/Wi-Fi modules developed with Qualcomm

Thu, Jun 05, 2025

STMicroelectronics has announced mass-production start for its ST67W611M1 combined Wi-Fi 6 and Bluetooth Low Energy 5.4 module, describing the early success of Siana, a lead customer for its fast-to-market connectivity.

The module is the first product of ST’s collaboration with Qualcomm Technologies, announced by the two companies in 2024, to simplify implementing wireless connectivity in systems containing STM32 microcontrollers (MCUs). Their vision, now realised in silicon, fuses ST’s expertise in embedded design and the STM32 ecosystem of microcontrollers, software, and development tools integrated with Qualcomm Technologies’ wireless connectivity technologies.

“Wireless connectivity is a key enabler for the cloud-connected intelligent edge and demand for smart, connected devices continues to expand and accelerate throughout consumer and industrial markets,” said Jerome Vanthournout, Connectivity Business Line Director, STMicroelectronics. “Mastering the complex Wi-Fi and Bluetooth protocols, and bringing that connectivity to devices and IoT applications, are huge challenges. Our modular solution, created with industry-leading knowhow of all aspects, lets product developers focus their resources at the application level and bring new products to market quickly.”

Shishir Gupta, Senior Director, Product Management at Qualcomm Technologies added, “Qualcomm Technologies is thrilled to see the impact of our collaboration with STMicroelectronics through the ST67W module. This module, which contains Qualcomm Technologies’ wireless connectivity components, not only simplifies the integration of Wi-Fi and Bluetooth into a wide range of devices powered by STM32 microcontrollers but also offers incredible flexibility and scalability. This module is a testament to our joint commitment to driving innovation and excellence in the IoT space.”

The ST67W module is ready to integrate with any STM32 MCU and contains a Qualcomm Technologies multiprotocol network coprocessor and 2.4GHz radio. All RF front-end circuitry is built-in, including power/low-noise amplifiers, the RF switch, balun, and integrated PCB antenna, with 4Mbyte Flash for code and data storage and a 40MHz crystal. The module comes pre-loaded with Wi-Fi 6 and Bluetooth 5.4 and is pre-certified according to mandatory specifications. Thread and Matter will be supported soon via software update. There is also an optional coaxial antenna or board-level connections for an external antenna. Security is handled with cryptographic accelerators and services including secure boot and secure debug reaching PSA Certified Level 1, making it easy for customers to comply with the upcoming Cyber Resilience Act and RED directives.

Product developers need no RF design expertise to create a working solution using this module. Highly integrated in a 32-lead LGA package, it is ready to place on the board and permits simple, low-cost PCB designs with as few as two layers.

Siana Systems is among the first IoT technology companies to explore the opportunities this wireless connectivity module brings to enhance product performance and accelerate time to market.

“The ST67W module expands opportunities to add Wi-Fi to devices powered by various STM32 microcontrollers and worry less about the minimum requirements. We can simply integrate the module and quickly get Bluetooth and Wi-Fi connectivity, with minimal additional engineering, which provides us with a simple go-to solution for our next generation designs,” said Sylvain Bernard, Founder and Solution Architect, Siana Systems. “The module’s RF performance, with the radio and front-end circuitry integrated, is very strong, and the flexible power management with fast wake-up times lets us create extremely energy-efficient new products.”

The ST67W611M1 leverages the STM32 ecosystem, which contains over 4,000 commercial part numbers, powerful STM32Cube tools and software, and enhancements that boost edge AI development. The STM32 family covers a broad spectrum from economical Arm® Cortex®-M0+ devices to variants with high-performing cores like Cortex-M55, Cortex-M4 with DSP extensions, and Cortex-A7 in the STM32MP1/2 MPUs.

http://www.st.com

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Rohm has developed a breakthrough in AI-equipped MCUs

Wed, Jun 04, 2025

Rohm has developed AI-equipped MCUs (AI MCUs) – ML63Q253x-NNNxx / ML63Q255x-NNNxx – that enable fault prediction and degradation forecasting using sensing data in a wide range of devices, including industrial equipment such as motors. According to Rohm these MCUs are the industry’s first to independently execute both learning and inference without relying on a network connection.

As the need for efficient operation of equipment and machinery continues to grow, early failure detection and enhanced maintenance efficiency have become key challenges. Equipment manufacturers are seeking solutions that allow real-time monitoring of operational status while avoiding the drawbacks of network latency and security risks. Standard AI processing models, however, typically depend on network connectivity and high-performance CPUs, which can be costly and difficult to install.

In response, Rohm has developed AI MCUs that enable standalone AI learning and inference directly on the device. These network-independent solutions support early anomaly detection before equipment failure – contributing to a more stable, efficient system operation by reducing maintenance costs and the risk of line stoppages.

The new products adopt a simple 3-layer neural network algorithm to implement Rohm’s proprietary on-device AI solution “Solist-AI™.” This enables the MCUs to perform learning and inference independently, without the need for cloud or network connectivity.

AI processing models are generally classified into three types: cloud-based, edge, and endpoint AI. Cloud-based AI performs both training and inference in the cloud, while edge AI utilises a combination of cloud and on-site systems － such as factory equipment and PLCs － connected via a network. Typical endpoint AI conducts training in the cloud and performs inference on local devices, so network connection is still required. Furthermore, these models typically perform inference via software, necessitating the use of GPUs or high-performance CPUs.

In contrast, Rohm’s AI MCUs, although categorised as endpoint AI, can independently carry out both learning and inference through on-device learning, allowing for flexible adaptation to different installation environments and unit-to-unit variations, even within the same equipment model. Equipped with Rohm’s proprietary AI accelerator “AxlCORE-ODL,” these MCUs deliver approximately 1,000 times faster AI processing compared to Rohm’s conventional software-based MCUs (theoretical value at 12MHz operation), enabling real-time detection and numerical output of anomalies that “deviate from the norm”. In addition, high-speed learning (on-site) at the point of installation is possible, making them ideal for retrofitting into existing equipment.

These AI MCUs feature a 32-bit Arm® Cortex-M0+ core, CAN FD controller, 3-phase motor control PWM, and dual A/D converters, achieving a low power consumption of approximately 40mW. As such, they are ideally suited for fault prediction and anomaly detection in industrial equipment, residential facilities, and home appliances.

The lineup will consist of 16 products in different memory sizes, package types, pin counts, and packaging specifications. Mass production of 8 models in the TQFP package began sequentially in February 2025. Among these, two models with 256KB of Code Flash memory and taping packaging are available for purchase, along with an MCU evaluation board, through online distributors.

Rohm has released an AI simulation tool (Solist-AI Sim) on its website that allows users to evaluate the effectiveness of learning and inference prior to deploying the AI MCU. The data generated by this tool can also serve as training data for the actual AI MCU, supporting pre-implementation validation and improving inference accuracy.

https://www.rohm.com

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Microchip enhances their digital signal controller lineup

Infineon expands ID portfolio for enhanced flexibility and faster time-to-market

ST announces mass production for turnkey Bluetooth/Wi-Fi modules developed with Qualcomm

Rohm has developed a breakthrough in AI-equipped MCUs

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