Infineon and Eaton collaborate to advance automotive battery management systems

     Infineon Technologies and Eatron Technologies have partnered to integrate sophisticated machine learning algorithms and solutions into the AURIX TC4x microcontroller (MCU). The partnership aims to advance battery management systems (BMS) for automobiles. Eatron is able to maximize the performance and accuracy of its AI-powered battery management software by utilizing the cutting-edge machine learning capabilities of the MCU family with integrated parallel processing unit (PPU).

     Together, the two companies are assisting electric vehicle (EV) manufacturers in overcoming three technological obstacles that have impeded customer adoption of EVs thus far: range anxiety, charging speed, and battery health.

     According to Eatron, Infineon’s AURIX TC4x PPU enables them to provide AI-based battery diagnostics, including lithium plating detection, and prognostics, including state of health (SoH) and aging trajectory, and remaining useful life (RUL) prediction at the periphery. Coupled with Eaton’s state of everything (SoX) solution, which provides the most accurate and robust cell-level estimation of available charge, power, and battery health, users of the TC4x will have access to machine learning-enabled battery management systems.

     The PPU, a single instruction, multiple data (SIMD) vector digital signal processor (DSP) on-chip, reduces computation time significantly when compared to conventional CPUs. Within its ecosystem, Infineon offers an automated toolchain to facilitate the PPU’s handling in the most efficient and expedient manner possible. For instance, an automated toolchain enables customers to convert existing models into vectorized code automatically.