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Reddit:Electronics - Sat, 03/30/2024 - 17:00

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Understanding the Benefits of Power-Focused Regression Testing

AAC - Sat, 03/30/2024 - 01:00
By including power consumption measurement in your regression testing, you can ensure the reliability and efficiency of your IoT device design throughout its lifecycle.

A Q&A With Renowned Neuromorphic Chip Designer Chiara Bartolozzi

AAC - Fri, 03/29/2024 - 19:00
For our final feature celebrating Women’s History Month, we interviewed Chiara Bartolozzi, a senior researcher moving the needle in neuromorphic engineering.

I built Rem-RC's self balancing cube robot. I found it somewhat hard to follow, so this is my supplemental guide to try to help other novices like myself.

Reddit:Electronics - Fri, 03/29/2024 - 17:45

The following guide is how I managed to build my cube. I am a novice in many of the aspects of this project so this was a really fun challenge. As a novice I thought it would be good to put together a "from scratch" approach for this guide as not everyone has all the tools and parts available on hand. I hate being nearly finished and then discovering I don't have everything I need, it really kills my momentum.

All credit for the project and MANY THANKS to Rem-RC (Youtube / Github / Thingiverse).

#0 - Parts / Hardware / Tools List / etc

I noticed that there were parts mentioned, but there was no all encompassing list for everything needed in order to assemble a working cube.

Parts

  • ESP32-WROOM-32 - Microcontroller (30 pin version)
  • MPU6050 - Accelerometer/Gyro
  • 11.1V 3S1P LiPo Battery ~500mAh (I could only find 450 or 550 mAh batteries. Also note the type of connector and buy a compatible connector that you can terminate to the breadboard)
  • 5cm x 7cm Solderable Breadboard
  • (3x) Nidec 24h Brushless servo motors (Ebay)
  • PCB Mount Screw Terminal Block Connector
  • 2N2222 transistor
  • 5v Active Buzzer
  • 0.1µF ceramic capacitor (sometimes called 100nF or 104 capacitor)
  • 35V 100µF electrolytic capacitor (I could only find 50V, higher voltage rating will still work fine, just don’t go lower)
  • 7805 Voltage regulator
  • 6.8k Ω resistor
  • 33k Ω resistor
  • 10k Ω resistor

Hardware

  • Solder, Solder wick, flux, etc
  • 22awg solid wire
  • 6awg solid wire (for the battery connector, you might be able to use smaller gauge wire)
  • Breadboard header pins (break apart type is good)
  • Breadboard female header pin sockets (I got a pack of 15 pin header sockets and cut them apart as needed)
  • (~40x) M3 x 10mm screws
  • (~10x) M3 x 12mm screws
  • (~50x) M3 hex nuts
  • (~60x) M4 x 8mm screws
  • (~120x) M4 nuts (You want to make each reaction wheel’s mass around 70 grams, after 3d printing the wheels they came out to ~20g each, so I needed 50g of M4 hardware)

3D Printed Parts (from Rem-RC's Thingiverse)

  • (3x) reaction_wheel_cube_1 (these are the bottom sides of the cube)
  • (3x) reaction_wheel_cube_2 (these are the top sides of the cube)
  • (3x) reaction_wheel_cube_3 (these are the reaction wheels)
  • (3x) reaction_wheel_cube_4 (these are the motor mounts)
  • (1x) reaction_wheel_cube_5 (this is the triangular mount between the top sides)
  • (3x) reaction_wheel_cube_6 (these are the mounting brackets between the cube sides and the triangular mount)
  • (2x) reaction_wheel_cube_7 (these are the battery holder sides)
  • (1x) reaction_wheel_cube_8 (this is the battery holder backstop)
  • (1x) reaction_wheel_cube_9 (this is the breadboard mount)

Tools

  • Digital Multimeter (You need to check your battery voltage, and it helps with checking circuit continuity)
  • 3D Printer (or a friend that’s willing to print stuff for you)
  • Soldering Iron, Wire Strippers, screwdrivers, etc
  • LiPo Battery Charger (I recommend a balance charger like the SkyRC iMAX B6AC, it was recommended by the FPV drone and RC Planes communities)

#1 - Schematic

I saw that there were two different schematics, one for an “Arduino nano” and one for an “ESP32”, but they have essentially the same components with the exception of the buzzer circuit. The ESP32 schematic shows a P-type transistor with the Emitter, Collector, and Base in a different orientation to the N-type transistor on the Arduino nano schematic. I ended up using an N-type transistor “2n2222” on the ESP32 and had to switch the orientation to match.

I also got really easily confused as I am not great at mapping a schematic to a solderable breadboard. So I have re-drawn the schematic to “color code” it a little bit. Many components share a ground and many others share a 5V output of the 7805 voltage regulator. I won’t show you a picture of my board, because it is hideous and I won’t inflict that upon you, but I will show you a rough drawing of how my board is wired.

#2 - Circuit Assembly and Testing

I started by building everything on a regular breadboard, it made checking everything a lot easier than trying to solder and un-solder every incorrect component. First up was checking the voltage into and out of the 7805 to confirm it was 11.1V in and ~5V. I then made sure the MPU6050 was outputting appropriately (I fried at least one board because I accidentally gave it 11V straight off the LiPo battery, oopsies). The 7805 can get HOT if you’ve mis-wired anything, so don't burn yourself. I moved on to test that each motor worked with the “motors_test” file. This file basically makes Motor 1 spin clockwise, then counter-clockwise, then Motor 2, and then Motor 3.

#3 - 3D Printing and Initial Assembly

All of my parts were printed in PLA with .2mm layer height and 50% infill. Everything is pretty forgiving in terms of fit and tolerances. If you print the reaction wheels with more walls or higher infill, you may end up with more mass, and therefore need fewer screws and/or nuts. Make sure all of your screws have good clearance with each other when they rotate. I followed the assembly video on Rem-RC's youtube channel, and that should get you going. This video is what made me want to start the project in the first place.

#4 - Code and Calibration

I haven’t done many Arduino or microcontroller programming projects, so I had to start from basically scratch. Download the Arduino IDE, the USB driver for the ESP32, and plug in the ESP32. You will need to download the ESP32 plugin to be able to connect to it. Once done select ESP32 Dev Kit and the COM port that it shows up on (I found mine on COM 5).

I found that the existing code inside the functions.ino section didn’t work with what my MPU6050 was outputting during the calibration process. Basically the code is expecting the MPU6050 to balance between two values for each balance point.

With the USB cable disconnected and the battery connected, connect to it with a serial bluetooth terminal (I just found one on the google play store). Follow the process of calibration in the assembly video, essentially it is outputting the different X/Y values to the terminal which you will then need to add to your code. These are my values which will not be the same as yours, but you can use it as an example of what to look for in your own troubleshooting and calibration process.

Edge 1

Measured values: X= -33.71, Y= -1.57

Expected values range: -45 < X < -25, -30 < Y < -10

Corrected values range: -45 < X < -25, -30 < Y < -1

(My value was outside the expected range)

Edge 2

Measured values: X= 30.06, Y=-1.35

Expected values range: 20 < X < 40 , -30 < Y < -10

Corrected values range: 20 < X < 40 , -30 < Y < -1

(My value was outside the expected range)

Edge 3

Measured values: X= -3.33, Y= 49.98

Expected values range: |X|< 15 , 30 < Y < 50

Corrected values range: |X|< 15 , Y < 50

(My value was fine)

Vertex

Measured values: X= -2.54, Y= 17.04

Expected values range: |X| < 10 , |Y|< 10

Corrected values range: |X| < 10 , |Y|< 20

(My value was outside the expected range)

Once all of the balance points have been calibrated and it is held close to one of the balance point it will beep once and begin spinning the appropriate motor(s).

#5 - Other

Make sure your micro USB cable is good, no really, double check it. I tried to troubleshoot my ESP32 board for like 2 days straight before figuring out that BOTH of my micro USB cables were bad. They could pass power and turn on the LED, but no data.

Links:

remrc's github - https://github.com/remrc/Self-Balancing-Cube

3D Print Files - https://www.thingiverse.com/thing:5380306/files

Rem-RC's youtube assembly guide video - https://www.youtube.com/watch?v=AJQZFHJzwt4

Rem-RC's youtube tips video - https://www.youtube.com/watch?v=Nkm9PoihZOI

Arduino IDE - https://www.arduino.cc/en/software

ESP32 USB to UART Bridge (drivers) - https://www.silabs.com/developers/usb-to-uart-bridge-vcp-drivers

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Mojo Vision appoints Achin Bhowmik to board

Semiconductor today - Fri, 03/29/2024 - 15:47
Mojo Vision Inc of Saratoga, CA, USA — which is developing and commercializing micro-LED display technology for consumer, enterprise and government applications — has appointed Dr Achin Bhowmik to its board of directors. Bhowmik, chief technology officer at Starkey, a former executive at Intel, and currently the president of the Society for Information Display (SID), joins as an independent board member to provide guidance and oversight for Mojo Vision as it accelerates the development of next-generation micro-LED technology. With his appointment, Mojo Vision is tapping 23 years of industry experience in perceptual computing, display and semiconductor business...

Nuvoton Technology for Green Energy, Endpoint AI, and Automotive Applications at Embedded World 2024

ELE Times - Fri, 03/29/2024 - 11:52

Energy saving and power management systems are the next green generation

Nuvoton will be showing green tech, endpoint AI, and automotive products at Embedded World 2024, booth 3A-418 in Germany. These products provide solutions for energy-saving cooling and ventilation, automotive AI guidance and safety challenges, and AI-based manufacturing and smart home demands.

Ultra-Low-Power USB Type-C PD 3.0 MCU, Hydrogen Sensors, Energy-Saving Solutions

Nuvoton’s NuMicro M2L31 microcontroller, with an Arm Cortex-M23 core featuring 64 to 512 Kbytes of ReRAM (Resistive Random-Access Memory), is an ultra-low-power product designed with a commitment to sustainability and energy efficiency. The M2L31 series not only supports two CAN FD and two USB Type-C PD 3.0 connections but also prioritizes robust security features to safeguard valuable data.

Nuvoton’s reference design for a NuMicro M2L31 MCU-based DC fan system compliant with USB Power Delivery 3.0 includes motor drive capability and a user interface to control the fan and upload or display system information. Highlights include BOM cost savings due to integrated features, simplified PCB layout, and flexible input voltage – together, these energy and resource-saving features not only reduce costs but also help create a greener product.

Nuvoton’s other eco-friendly offerings include the KM1M7AF digital power control microcontroller with security features; a compact high-efficiency, low-vibration industrial 48V fan motor driver (KA44370A); a one-chip AC impedance measurement design for efficiency and safety in battery management systems; and an ultra-low power hydrogen sensor that is ideal for monitoring green energy applications such as hydrogen stations, fuel cells, and hydrogen pipelines.

Automotive HMI and Safety ICs Enable Next-Generation Automotive Applications

In the automotive sector, Nuvoton has an automotive Human Machine Interface (HMI) processing IC based around the Gerda graphic processor series. This HMI IC supports fast booting and attractive 2.5D graphics. Its optimized system cost and external component integration are ideal for low-to-mid-end automotive applications.

For automotive safety and AI driving scenarios, Nuvoton’s Multi-Sensing Bridge IC can aggregate and synchronize data from image, audio, depth sensors, and signal processing ICs. This single-package IC with internal DRAM also has XR/VR/AR and drone applications. In addition, Nuvoton will be showing an automotive battery monitoring IC and pack monitoring IC at Embedded World 2024.

AI Vision Warehousing Solutions and Smart Home Technology ICs

Nuvoton displays two user-trainable AI systems for classifying camera data. The Arm Cortex-M55-based M55M1 Automatic Medicine Classifier uses a hardware-accelerated neural network to identify medicines based on visual input and user training. Based on related technology, the Arm Cortex-A35 MA35D1 Intelligent Warehouse Management System is a visual AI system for identifying different varieties of fruit in warehouses and similar environments. Both these systems support LCDs of appropriate size for the user interface.

For smart home products, Nuvoton presents the NAU83G60 Intelligent Smart Amplifier, which is ideal for consumer audio. The company will also be showing a smart ITO panel solution with touch keys and voice prompt capability. This solution is based on the M258 microcontroller with an Arm Cortex-M23 core and features Nuvoton’s fast LCD development and simulation tool, NuTool-LCDView.

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Are FinFETs coming to an end?

EDN Network - Fri, 03/29/2024 - 06:54

FinFETs redefined chip design when they came onto the scene more than a decade ago. While these nonplanar transistors are still the unofficial industry standard, they may be nearing the end of their life. So, electronics engineers may need to prepare for an incoming shift.

The first chips using FinFETs came out in 2011, letting semiconductors safely venture into sub-25-nm territory. At that time, this architecture was a sort of saving grace for Moore’s Law, because planar transistors led to too much current leakage for geometries below 100 nm to be sustainable.

Figure 1 FinFETs replaced the planar transistor design with a 3D architecture to overcome the limitations of traditional planar transistors. Source: AnySilicon

However, FinFETs are now facing a problem like the planar technologies that came before them. Power leakage and signal interference issues are becoming more common obstacles as device form factors continue to shrink and performance demands rise. Consequently, many key industry players are starting to consider alternate transistor architectures.

As helpful as FinFETs are compared to their predecessors, they have severe power routing constraints at smaller geometries. Engineers typically work around these restrictions through different channel widths and spacing. That works well in many applications, but this strategy has limits of its own.

Because gates must reach the insulator between fins, sufficient space between each channel must be available. As a result, engineers can quickly run into scalability issues since there are 15 nm to 20 nm between each fin. Adding more channels inherently means adding inactive areas, leading to a tradeoff between current routing and physical space.

Gate-all-around (GAA) transistors

A potential solution has emerged in the form of gate-all-around (GAA) transistors. GAA architecture reverts to planar form factors, but instead of using a flat channel flush with the insulator, it uses silicon ribbons surrounded by the gate on all sides.

Just as FinFETs let engineers place multiple fins next to each other, GAAs enable vertical channel stacking. Notably, this method still requires space between each ribbon. However, because it capitalizes on verticality, each one can cover a longer horizontal space. Alternatively, engineers could design taller but narrower transistors to leave more room on the chip for other components.

Another key advantage of GAA design is that the gate contacts the channel on all four sides. Consequently, it provides more control over higher currents, just as FinFETs did in relation to conventional planar architectures.

Figure 2 In GAA transistor structure, the gate can come into contact with the channel on all sides, which makes continuous scaling possible. Source: Lam Research

GAAs are still relatively new, but they’re already showing signs of becoming standard. Samsung led the charge, announcing a switch to GAAFETs in 2022. Intel, which put FinFETs on the map, will release its GAA technology later in 2024, along with a backside power technology.

Several obstacles remain. Some reports hold that Samsung is struggling to achieve high yields with its GAAFET technology. Other foundries have more long-term release windows for their GAA chips, so whether GAA technology will be able to overcome these challenges remains unclear.

Despite these road bumps, the industry is clearly moving toward GAAs. So, electronics designers should familiarize themselves with this technology before the shift happens to adapt to the changing market.

Transition on the gate

Just as FinFETs redefined semiconductor architecture in the 2010s, GAAFETs could do the same within the next decade. While much of this transition is still up in the air, most signs seem to be pointing that way.

Electronics engineering is a continually evolving field. Therefore, engineers must stay abreast of developments like this to ensure they can capitalize on the innovations that revolutionize the industry.

Ellie Gabel is a freelance writer as well as an associate editor at Revolutionized.

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4 Fiber Optic Networking Spotlights From the Optical Fiber Conference

AAC - Fri, 03/29/2024 - 01:00
Some of the leaders of the networking industry showed up to the Optical Fiber Conference, including Broadcom, MediaTek, Semtech, and MaxLinear.

Renesas builds RISC-V MCUs with own core

EDN Network - Thu, 03/28/2024 - 20:11

General-purpose 32-bit MCUs in the R9A02G021 group from Renesas employ an internally developed RISC-V CPU core. Renesas has designed and tested the new RISC-V core independently and implemented it in a commercial product that is available worldwide.

R9A02G021 MCUs enable embedded systems designers to develop low-power, cost-sensitive applications based on the RISC-V open-source instruction set architecture (ISA). The devices target such end markets as IoT sensors, consumer electronics, medical devices, small appliances, and industrial systems. They are also supported by a full-scale development environment and a network of toolchain partners.

The CPU core runs at 48 MHz and achieves a performance rating of 3.27 CoreMark/MHz. Power consumption is 162 µA/MHz when active, dropping to just 0.3 µA in standby with a wakeup time of 4 µs. Other features of the R9A02G021 group include:

  • Memory: 128 KB code flash, 16 KB SRAM, and 4 KB data flash
  • Serial communications interfaces: UART, SPI, I2C, SAU
  • Analog peripherals: 12-bit ADC and 8-bit DAC
  • Temperature range: -40°C to 125°C
  • Operating voltage range: 1.6 V to 5.5V

Packaging options for the R9A02G021 MCUs include 16-pin WLCSP and 24-pin, 32-pin, and 48-pin QFN. Devices are available now through global distributors.

R9A02G021 product page

Renesas Electronics 

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Motor control MCUs pack ample flash memory

EDN Network - Thu, 03/28/2024 - 20:10

Toshiba has added eight devices to the M4K group of TXZ+ 32-bit MCUs offering extended flash memory and four different packaging options. Outfitted with 512 kbytes or 1 Mbyte of code flash memory, the MCUs address the need for large program capacity in IoT motor control applications. They also offer firmware over-the-air updating.

With 1 Mbyte of code flash divided into two separate 512-kbyte areas, the MCUs enable firmware rotation using memory swapping. While instructions are being read from one area, updated code can be programmed into the other area simultaneously.

In addition to the expanded flash memory, the devices also boost RAM capacity to 64 kbytes. They are powered by an Arm Cortex-M4 core running at up to 160 MHz and provide UART, tSPI, and I2C interfaces. Three 12-bit ADCs, three advanced motor control circuits, and a vector engine allow the MCUs to control three motors, even in 64-pin packages.

M4K microcontrollers can be used to control AC motors, brushless DC motors, and inverters in home appliances, power tools, and industrial equipment. Packaging options include QFP100, LQFP100, and two different size LQFP64 types.

TXZ+ M4K group product page

Toshiba Electronic Devices & Storage 

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100-V Schottky rectifiers aid efficiency

EDN Network - Thu, 03/28/2024 - 20:10

Twenty-eight 100-V trench Schottky rectifiers from ST increase efficiency and power density in power converters operating at high switching frequencies. Target applications for the portfolio of devices include power supplies for telecom, server, and smart metering equipment, as well as automotive LED lighting and low-voltage DC/DC converters.

According to the manufacturer, the diodes reduce rectifier losses with forward-voltage and reverse-recovery characteristics that enable increased power density with high efficiency. Forward voltage is 50 mV to 100 mV better than comparable planar diodes, depending on current and temperature conditions. Changing to these new devices can increase efficiency by 0.5%.

Variants in the family cover eight current ratings ranging from 1 A to 15 A. Multiple surface-mount package types are available in both industrial and automotive grades. Automotive parts are AEC-Q101 qualified for operation over a temperature range of -40°C to +175°C and manufactured in PPAP-capable facilities. Diodes are 100% avalanche tested in production to ensure device robustness and system reliability.

All of the parts are available now in DPAK, SOD123 flat, SOD128 flat, SMB flat, and PSMC (TO-227A) packages. Volume prices start at $0.107 for the 1-A STPST1H100ZF in the SMD123 flat package.

To access the datasheets for the 28 trench Schottky rectifiers, click here.

STMicroelectronics

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Buck-boost MOSFET meets USB PD 3.1 demands

EDN Network - Thu, 03/28/2024 - 20:09

Occupying a small footprint to ease PCB design, the AONZ66412 MOSFET from Alpha & Omega targets buck-boost converters in USB PD 3.1 EPR applications. While the 3.1 Extended Power Range specification enables power delivery up to 240 W over a USB Type-C cable and connector, the AONZ66412 addresses the most commonly used power range of up to 140 W at 28 V.

The AONZ66412 combines two 40-V N-channel MOSFETs arranged in a half-bridge configuration within a symmetric XSPairFET 5×6-mm package. When used to replace two single 5×6-mm DFN packages, the compact AONZ66412 reduces PCB area, improves efficiency, and simplifies the layout of a 4-switch buck-boost architecture.

Alpha & Omega’s XSPairFET DFN is a bottom-side source package. Each high-side and low-side MOSFET provides a maximum on-resistance of 3.8 mΩ. The source of the low-side MOSFET is directly linked to a large paddle on the lead frame. This setup enhances thermal performance by enabling direct connection of the paddle to the PCB’s ground plane. When tested, the AONZ66412 demonstrated 97% efficiency at 1 MHz under typical USB PD 3.1 EPR conditions with a 28-V input, 17.6-V output, and 8-A load.

The AONZ66412 dual MOSFET costs $1.56 each in lots of 1000 units. It is available now in production quantities with a lead time of 16 weeks.

AONZ66412 product page

Alpha & Omega Semiconductor 

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Aspinity strengthens AI-based automotive security

EDN Network - Thu, 03/28/2024 - 20:08

Aspinity has launched a dashcam evaluation kit and a suite of smart analogML algorithms for parked vehicle monitoring. The hardware/software offerings leverage the company’s always-on AML100 analog machine learning processor. The near-zero power AML100 enables continuous monitoring for extended periods without impacting the vehicle’s battery or requiring an external power source.

The company recently demonstrated a dashcam with a single microphone and an AML100 processor. The setup uses an acoustic-only trigger and analogML algorithms trained to identify automotive security events. According to Aspinity, the solution detects events more accurately than dashcams outfitted with a standard G-sensor. Surveillance algorithms detect such events as jiggling of the door handle, a neighboring car door opening into the vehicle, runaway shopping cart hitting the side of the car, and window glass breaking, while ignoring sounds from events unrelated to the vehicle.

Based on the AML100-REF-1 wireless, battery-operated reference module, the dashcam evaluation kit enables deployment and evaluation in the cabin of a vehicle. It consumes <50 µA in always-on mode and eliminates the video recording of false events that waste power.

To learn more about Aspinity’s AML100 monitoring solutions for automotive security, click here.

Aspinity

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With an Eye on On-Device AI, Qualcomm Rolls Out New Snapdragon SoC

AAC - Thu, 03/28/2024 - 19:00
The new Snapdragon 7+ Gen 3 processor comes with CPU and memory performance increases, Wi-Fi 7, and enhanced edge AI capabilities for mobile devices.

UK funding of £14m for open-access power semiconductor test & packaging equipment

Semiconductor today - Thu, 03/28/2024 - 18:54
The UK Government has announced a £16.6m investment to give semiconductor researchers and businesses access to new equipment helping them to test and make chips for use in high-energy machines such as electric vehicles and manufacturing equipment. Of the funding, £14m is targeted particularly at semiconductors used in power electronics...

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