ST helps Panasonic Cycle Technology bring AI to e-assisted bikes for affordable safety boost

ST has announced that Panasonic Cycle Technology has adopted the STM32F3 microcontroller (MCU) and edge AI development tool, STM32Cube.AI, for their TiMO A e-assisted bike. ST’s edge AI solutions provide a tyre pressure monitoring system (TPMS) that leverages an advanced AI function to improve rider safety and convenience.

Panasonic is a leading producer of e-assisted bikes in Japan and offers a wide variety of products for various uses to the Japanese market. Their electric assist bicycle for school commuting, TiMO A, runs an AI application on the STM32F3 MCU to infer the tyre air pressures without using pressure sensors. Based on information from the motor and the bicycle speed sensor, the system generates a warning to inflate the tyres if necessary. ST’s edge AI development tool, STM32Cube.AI, enabled Panasonic to implement this edge AI function while fitting into STM32F3 embedded memory space. This new function simplifies tyre air-pressure maintenance, which enhances rider safety and prolongs the life of tyres and other cycle components. It also helps to reduce the cost and design work, as there is no need for additional hardware such as an air pressure sensor.

ST will showcase edge AI solutions, including the STM32 MCU and a variety of AI development tools, at the AI Expo at Tokyo Big Sight (May 22-24, 2024). The e-assisted bike and the motor unit (cutaway sample) from Panasonic Cycle Technology, which feature the STM32F3 MCU and STM32Cube.AI, are also scheduled to be displayed at this expo.

The STM32F3 MCU adopted for the TIMO A is based on the Arm Cortex-M4 (with a maximum operating frequency of 72 MHz) and features a 128KB Flash, along with various high-performance analog and digital peripherals optimal for motor control. In addition to the new inflation warning function, the MCU determines the electric assistance level and controls the motor.

It leverages STM32Cube.AI to reduce the size of the neural network (NN) model and optimise memory allocation throughout the development of this AI function. STM32Cube.AI is ST’s free edge AI development tool that converts NN models learned by general AI frameworks into code for the STM32 MCU and optimises these models. The tool optimised the NN model developed by Panasonic Cycle Technology for the STM32F3 MCU quickly and easily, and implemented it in the flash memory, which has limited capacity.

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