This invention provides an
artificial intelligence algorithm acceleration
system and method for real-time
junction temperature prediction of IGBTs, including a parameter acquisition module, an
artificial intelligence algorithm acceleration module, and a host computer. The parameter acquisition module is used to acquire the saturated on-state collector-emitter
voltage VCE(Sat), collector current IC, and substrate temperature TC during IGBT operation. The
artificial intelligence algorithm acceleration module is based on a Zynq7000 series FPGA to build a SoC architecture, integrating a dual-core ARM Cortex-A9 processor and a dedicated neural
network processor (NPU). The host computer is used to receive the
junction temperature prediction results and raw acquired parameters transmitted by the artificial intelligence
algorithm acceleration module, enabling real-
time data display, historical data storage,
junction temperature anomaly alarms, and
model parameter calibration. This invention aims to solve the high latency, high communication cost, and data privacy issues of
cloud computing solutions through collaborative optimization design of algorithms and hardware, while simultaneously overcoming the bottlenecks in computing power, energy efficiency, and accuracy of existing
edge computing platforms.