Transportation

Enhanced safety and lifetime of e-assisted bikes with Panasonic

Tire pressure monitoring solution to improve rider safety and convenience.

Enhanced safety and lifetime of e-assisted bikes with Panasonic
Contact us to learn more

Transportation

STM32Cube.AI

Predictive maintenance

Current sensor

Contact us to learn more
Panasonic, a leading producer of e-assisted bikes in Japan, offers a wide variety of products for various uses to the Japanese market. The company has implemented a tire pressure monitoring system for their TiMO A e-assisted bike, which combines the STM32F3 microcontroller and STM32Cube.AI.

Based on information from the motor and the bicycle speed sensor, the system generates a warning to inflate the tires if necessary. Their solution leverages an advanced AI function that simplifies tire air-pressure maintenance, enhances rider safety, and prolongs the life of tires and other cycle components.
By combining the STM32F3 MCU with STM32Cube.AI, we were able to implement the innovative AI function without the need to change hardware. We will continue to increase the range of models with AI functions and strive to fulfill our mission by leveraging STs edge AI solutions.
Hiroyuki KAMO
SW Dev Section Manager at Panasonic Cycle Technology

Approach

The STM32F3 MCU adopted for the TiMO A is based on the Arm Cortex-M4 and features 128 Kbytes of flash memory, along with various high-performance analog and digital peripherals optimal for motor control. In addition to the new inflation warning function, the MCU also determines the electric assistance level and controls the motor.
Panasonic used STM32Cube.AI to reduce the size of the neural network (NN) model they developed, optimizing memory allocation throughout the development of this AI function. The tool enabled Panasonic to quickly and easily optimize their NN model for implementation in the flash memory, which has a limited capacity.

Sensor

Motor current and wheel speed sensing.

Model optimized with

STM32Cube.AI

Model optimized with

Running on

STM32F3 Series

Running on

Resources

Model optimized with STM32Cube.AI

A free STM32Cube expansion package, X-CUBE-AI allows developers to convert pretrained AI algorithms automatically, such as neural network and machine learning models, into optimized C code for STM32.

Model optimized with STM32Cube.AI

Running on STM32F3 Series

The STM32 family of 32-bit microcontrollers based on the Arm Cortex®-M processor is designed to offer new degrees of freedom to MCU users. It offers products combining very high performance, real-time capabilities, digital signal processing, low-power / low-voltage operation, and connectivity, while maintaining full integration and ease of development.

Running on STM32F3 Series

You also might be interested by

Industrial | Transportation

Smart asset tracking

Packages condition classification on sensors.

Industrial | Transportation

Estimating torque and rotor temperature for improved motor performance

Using AI to extrapolate torque and rotor temperature values to improve motor performance.

Industrial | Transportation

Motor fault detection and classification

Detection and classification of motor faults for predictive maintenance.