Artificial intelligence algorithm acceleration system and method for IGBT real-time junction temperature prediction

By employing the Zynq7000 series FPGA SoC architecture and dedicated neural network processor in the IGBT system, combined with mixed-precision computing and multi-level cache design, the problems of high accuracy, low latency and energy efficiency in IGBT junction temperature prediction are solved, and efficient junction temperature monitoring at the edge is achieved.

CN122086703APending Publication Date: 2026-05-26STATE GRID FUJIAN ELECTRIC POWER CO LTD +1
0 Cites 0 Cited by

Patent Information

Application Number
CN202610150760.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-02-03
Publication Date
2026-05-26

AI Technical Summary

Technical Problem

Existing technologies lack a solution for online prediction of IGBT junction temperature that can achieve high accuracy, low latency, and high energy efficiency at the edge of large-scale power systems, and also suffer from high computational load, high communication costs, and data privacy issues.

Method used

It adopts a SoC architecture based on Zynq7000 series FPGA, integrating a dual-core ARM Cortex-A9 processor and a dedicated neural network processor NPU. It combines mixed-precision vector inner product units and three-dimensional matrix inner product operation units to design a multi-level cache system, realize hardware and software co-optimization, and filter effective operations through the approximate prior vector inner product method (AVIP) to reduce computation latency and memory access.

Benefits of technology

It achieves high-precision, low-latency, and low-energy-consumption IGBT junction temperature prediction at the edge, with an average prediction error of less than 3°C, adapting to the needs of large-scale distributed deployment and avoiding high communication costs and data privacy leakage risks.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The invention provides an artificial intelligence algorithm acceleration system and method for IGBT real-time junction temperature prediction. The artificial intelligence algorithm acceleration system comprises a parameter acquisition module, an artificial intelligence algorithm acceleration module and an upper computer. The parameter acquisition module is used for acquiring a saturated on-state collector-emitter voltage VCE (Sat), a collector current IC and a substrate temperature TC when the IGBT operates; according to the artificial intelligence algorithm acceleration module, an SoC architecture is constructed based on a Zynq7000 series FPGA, and a dual-core ARMCortex-A9 processor and a special neural network processor NPU are integrated. And the upper computer is used for receiving the junction temperature prediction result and the original acquisition parameters transmitted by the artificial intelligence algorithm acceleration module, and realizing real-time data display, historical data storage, junction temperature abnormity alarm and model parameter calibration. The invention aims to solve the problems of high delay, high communication cost and data privacy of a cloud computing scheme through collaborative optimization design of an algorithm and hardware, and breaks through the bottlenecks of an existing edge computing platform in computing power, energy efficiency and precision.
Need to check novelty before this filing date? Find Prior Art