A portable crimping type power module current distribution test system and test method

Abstract

This application relates to a portable crimp-type power module current distribution testing system and method. The method includes: attaching a magnetic field sensor probe to the device under test (DUT) and reliably connecting it; synchronously calibrating each core module of the testing system; automatically switching between simulated test conditions, including basic and extreme test conditions, optimizing test parameters and preventing electromagnetic interference; selecting a trigger mode suitable for the test conditions, synchronously collecting current distribution and temperature data, preprocessing to remove invalid data, and obtaining valid data; and completing the health level assessment, graded early warning, and remaining service life prediction of the DUT. This invention adopts a non-invasive flexible testing design, allowing the magnetic field sensor probe to be directly attached to the surface of the DUT without disassembling the device or requiring additional fixing fixtures. This ensures the airtightness and insulation structure of the DUT, enabling coordinated monitoring of current and temperature parameters, and accurately capturing hidden dangers such as localized current congestion and excessive thermal stress.

Description

Technical Field

[0001] This application relates to the field of energy storage system technology, specifically to a portable crimp-type power module current distribution testing system and testing method. Background Technology

[0002] As high-power power electronic systems, centered on flexible DC transmission and high-voltage frequency conversion drives, evolve towards higher reliability, the long-term operational health of press-fit power devices, such as IGBTs / IGCTs, has become a critical bottleneck for system safety. These devices employ multi-chip parallel packaging to carry large currents, theoretically requiring uniform current distribution among the chips. However, due to factors such as manufacturing tolerances, parameter dispersion, uneven packaging stress, and long-term aging, an imbalance between dynamic and static current distribution is prevalent within the devices, leading to some chips being in a state of overcurrent and localized overheating for extended periods. Currently, online monitoring and field testing technologies for power modules, whether based on port electrical quantity measurement or controller status feedback, remain at the "functional verification" level, only determining whether a submodule can function, but failing to reveal the health of its internal parallel structure.

[0003] Existing patent 1: Patent No.: 201310407363.2, Title: A Portable Power Module Testing System and Method. It provides a multi-winding isolation transformer, which connects to single-phase mains power on the primary side and generates DC and AC outputs on the secondary side to power the power module under test. The system communicates with the control unit of the module under test via optical fiber and acquires external port voltages, realizing an automated functional testing process.

[0004] Existing patent 2: Patent No.: 201810810698.1, Title: A General-Purpose Power Module Test Circuit, System and Test Method. It provides an adjustable AC power supply unit composed of rectifier and inverter circuits, capable of outputting AC power with adjustable voltage and frequency to directly power the AC side of the module under test. The system also communicates with the module under test through a control unit and monitors external electrical quantities, achieving automated testing.

[0005] However, the existing technology has obvious defects: the technical defect of existing patent 1 is that its test logic relies entirely on the status information reported by the controller of the module under test and the total port voltage / current measured externally. It can only determine whether the module "can respond to commands", "whether the external electrical parameters meet the standards", and "whether it can work normally", but cannot assess the health status of the device. The transformer and modular design improve portability and automation, but do not change its "black box test" nature.

[0006] In summary, a prominent characteristic of hidden degradation is that the electrical quantities at the external ports of the device may still be within the "normal" range, such as terminal voltage and total current. Engineering experience shows that, after excluding extreme events such as external overvoltage breakdown and dynamic avalanche, the more common failure chain for press-fit devices in the field is a positive feedback accumulation of "local current congestion → local temperature rise → further parameter drift → further current congestion," ultimately leading to the early failure of a single chip or a few sub-units. This failure may then extend to multi-sub-unit cascading damage under stress redistribution, shoot-through / discharge circuits, etc., triggering sub-module bypass, redundancy consumption, and unplanned maintenance. Therefore, it is necessary to obtain the current distribution of parallel chips to obtain the "health status" of the sub-modules. Existing methods are completely blind to core physical quantities that determine reliability, such as chip-level current distribution, forming a critical blind spot in state perception.

[0007] Therefore, this invention, in conjunction with a magnetic field sensing probe, develops a non-invasive device for assessing the health status of submodules, addressing the urgent need to transition from scheduled maintenance to predictive maintenance and ensure the safe and stable operation of critical power electronic equipment. Specifically, it proposes a portable press-fit power module current distribution testing system and method. Summary of the Invention

[0008] To overcome the shortcomings of the prior art, this application provides a portable crimp-type power module current distribution testing system and testing method, specifically adopting the following technical solution.

[0009] A portable crimp-type power module current distribution testing system includes a detection device, a data collection module, a power management module, a current generator, a signal acquisition module, a data encryption transmission module, a magnetic field sensor, an adaptive calibration module, a life cycle management module, an electromagnetic shielding module, a health status prediction module, a controller, and a multi-condition adaptation module, with each module working in concert.

[0010] Testing device: Adopting a portable and modular design, it caters to both fixed laboratory testing and mobile on-site maintenance needs. The device includes a data collection module, power management module, current generator, signal acquisition module, data encryption transmission module, magnetic field sensor, adaptive calibration module, lifecycle management module, electromagnetic shielding module, health status prediction module, controller, and multi-condition adaptation module.

[0011] Data collection module: Enables full-dimensional data acquisition and traceability, specifically collecting operating parameters of each hardware module of the test system, real-time current distribution data of different specifications of press-fit power modules, and temperature synchronization data. At the same time, it automatically captures historical test data and industry benchmark data of similar devices to build a multi-dimensional database.

[0012] Power Management Module: While ensuring a stable basic power supply, it achieves a triple improvement in energy saving, intelligence, and high reliability. Core functions include adaptive voltage regulation, seamless backup power switching, independent power supply control for multiple modules, comprehensive protection, and adaptive power consumption adjustment.

[0013] Current generator: Based on the classic dual-pulse topology, it integrates an intelligent load adjustment unit and a topology reconfiguration module. It can automatically match load parameters according to the rated current, rated voltage and package specifications of the pressure-connected power module under test, without the need for manual load replacement, and adapts to the testing needs of different manufacturers and different models of devices.

[0014] Signal acquisition module: Configured with eight independent acquisition channels, supporting expansion to sixteen channels, of which six channels are used for current signal acquisition and two channels are used for temperature signal acquisition. The sampling rate is ≥100MS / s, the bandwidth is ≥20MHz, and the synchronization delay is ≤10ns, ensuring synchronous acquisition of multi-channel data.

[0015] Magnetic field sensor: The probe uses a highly flexible PCB material, which can be bent freely and perfectly adapts to press-fit power modules of different shapes and sizes. It can be directly attached to the device surface to complete the test without the need for additional fixing fixtures. The probe head integrates an integrated sensing unit with a built-in high-sensitivity magnetic field sensor and a high-precision temperature sensor. It can simultaneously collect magnetic field signals and device surface temperature, and indirectly convert the current distribution through the magnetic field signal to achieve coordinated monitoring of current and temperature dual parameters.

[0016] Adaptive calibration module: Creates a real-time, automated, and remote calibration system that allows for simultaneous calibration of all modules without disassembling the device.

[0017] Electromagnetic shielding module: Addressing the core issue of decreased test accuracy and data distortion caused by electromagnetic interference under high-frequency operating conditions, it adopts a layered shielding and fully enclosed integrated design, covering all internal hardware modules, external interfaces and connecting cables of the device. The shielding effectiveness is ≥80dB, which can effectively suppress mid-to-high frequency electromagnetic interference in the 10MHz-1GHz frequency band and ensure data stability in high-frequency test scenarios.

[0018] Multi-condition adaptation module: Creates a full-scenario, multi-condition adaptive testing system that supports three basic test conditions: low frequency, medium-high frequency, and high and low temperature. It can automatically identify device specifications and test requirements according to the actual working conditions of the device under test, switch test modes, and adaptively adjust acquisition parameters, trigger parameters, and load parameters without manual settings, greatly improving test efficiency.

[0019] Health status prediction module: Constructs a full-link health management system of detection-assessment-early warning-prediction, breaking through the limitations of traditional methods that can only detect current distribution, and integrates multi-dimensional indicators and AI intelligent algorithms to achieve full life cycle health management of the device under test.

[0020] Data encryption transmission module: It adopts the AES-256 encryption algorithm to build a full-process encryption system for acquisition, storage and transmission, ensuring that test data is not leaked, tampered with and traceable.

[0021] Lifecycle Management Module: Constructs a full lifecycle data management system for the device under test, creating a unique full lifecycle file for each device under test, recording detailed information such as device model, specifications, test data, health assessment results, maintenance records, fault records, calibration records, and other comprehensive information.

[0022] Controller: It adopts an architecture of ARM Cortex-A9 dual-core processor and FPGA logic control unit to realize the triple functions of high-speed response, intelligent control and massive data processing.

[0023] This invention provides a portable method for testing the current distribution of a crimp-type power module, comprising the following steps.

[0024] Step 1: System initialization. Select a suitable magnetic field sensor probe, attach it to the device under test, and reliably connect it without damaging the device structure. After starting the system, the power management module completes self-test and power supply adaptation and monitors the power supply status in real time. After inputting the basic parameters of the device, the controller initially matches the test parameters and activates basic electromagnetic shielding, laying the foundation for subsequent testing.

[0025] Step 2: Adaptive full-module synchronous calibration, used to ensure test accuracy and eliminate equipment errors. The system recommends an appropriate calibration mode based on test requirements, supports remote calibration to reduce maintenance costs, and utilizes a high-precision standard source to synchronously calibrate each core module.

[0026] Step 3: Multi-condition adaptive matching and test parameter optimization to adapt to real-world scenarios and improve testing efficiency. The system automatically identifies and switches to the appropriate basic test conditions, and can also manually simulate extreme conditions. The controller, in conjunction with relevant modules, automatically optimizes various test parameters while simultaneously preventing electromagnetic interference in real time.

[0027] Step 4: Multi-parameter synchronous acquisition and data preprocessing are used to obtain core data and ensure data validity. Select the appropriate trigger mode to start acquisition, simultaneously acquiring multi-dimensional core data such as device current distribution and temperature. Perform preprocessing on the acquired data, including normalization, filtering, and verification, to remove invalid data and ensure data accuracy, preparing for subsequent analysis.

[0028] Step 5: Data encryption transmission, storage and multi-dimensional analysis. The AES-256 algorithm is used to encrypt the effective data throughout the entire process. Data security is ensured by transmitting through multiple channels and implementing dual backup. The AI ​​fusion algorithm is called to analyze the data, calculate core indicators, and complete device health level assessment, early warning and life prediction.

[0029] Step 6: Full lifecycle management. Establish a dedicated file for the device under test, record detailed test and evaluation data throughout the entire process and support multi-condition queries, centrally manage and compare devices in the same batch, link with relevant systems to achieve predictive maintenance, and finally complete the test closing to facilitate subsequent repeated testing.

[0030] The technical solution of this application has achieved the following beneficial effects.

[0031] 1. The testing device adopts a portable structure, equipped with a foldable high-strength pull rod, non-slip rubber feet and rotatable casters, which takes into account both the ease of handling and the stability of placement. It completely solves the pain points of traditional testing equipment being bulky and inconvenient to move on site, and realizes bidirectional adaptability between fixed laboratory testing and on-site maintenance mobile testing, greatly improving the flexibility of testing scenarios.

[0032] 2. Adopting a non-invasive flexible testing design, the magnetic field sensor probe is made of highly flexible PCB material, which can be directly attached to the surface of the device under test without disassembling the device or requiring additional fixing fixtures. This ensures the airtightness and insulation structure of the device under test. At the same time, it realizes the coordinated monitoring of current and temperature dual parameters, which can accurately capture hidden dangers such as local current congestion and thermal stress exceeding limits, and prevent single chip failure from spreading into chain damage. Attached Figure Description

[0033] Figure 1 This is a flowchart illustrating the portable crimp-type power module current distribution testing method in an embodiment of this application.

[0034] Figure 2 This is a current distribution cloud map in this embodiment of the application when the standard deviation of the chip current distribution is 0.4 and the maximum offset of the chip current is 1.2.

[0035] Figure 3 This is a current distribution cloud map in this embodiment of the application when the standard deviation of the chip current distribution is 0.5 and the maximum offset of the chip current is 1.6.

[0036] Figure 4 This is a schematic diagram of a portable crimp-type power module current distribution testing system in an embodiment of this application.

[0037] Reference numerals: 1. Cabinet; 2. Cabinet cover; 3. Touch screen display; 4. Measurement terminal; 5. USB network port; 6. Connection terminal; 7. Fiber optic drive terminal; 8. Casters; 9. Pull rod; 10. Intelligent cooling fan. Detailed Implementation

[0038] The present application will now be further described with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present application and should not be construed as limiting the scope of protection of the present application. It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of the present application.

[0039] like Figure 1 and Figure 4 As shown, this invention discloses a portable crimp-type power module current distribution testing system, including a detection device, a data collection module, a power management module, a current generator, a signal acquisition module, a data encryption transmission module, a magnetic field sensor, an adaptive calibration module, a life cycle management module, an electromagnetic shielding module, a health status prediction module, a controller, and a multi-condition adaptation module, all of which work together.

[0040] Testing Device: The device features a portable and modular design, accommodating both fixed laboratory testing and mobile on-site maintenance needs. The overall structure is a rectangular portable unit, equipped with a foldable high-strength pull rod and four anti-slip rubber feet located at the bottom for easy handling and stable placement. The outer shell is made of cold-rolled steel plate with an anti-static and anti-corrosion coating, achieving an IP54 protection rating, suitable for complex on-site maintenance environments such as dust and minor water stains. The shell has pre-drilled ventilation louvers on the sides and a built-in intelligent cooling fan (10) with an adaptive speed adjustment based on internal temperature (0-3000 rpm) to prevent overheating during prolonged testing and ensure device stability. Multiple casters are mounted on the bottom of the shell. A front panel is fixed inside the shell. The testing device includes a data collection module, power management module, current generator, signal acquisition module, data encryption transmission module, magnetic field sensor, adaptive calibration module, lifecycle management module, electromagnetic shielding module, health status prediction module, controller, and multi-condition adaptation module.

[0041] Data Collection Module: Enables comprehensive data acquisition and traceability. Specifically, it collects operating parameters of each hardware module in the testing system, real-time current distribution data of different specifications of press-fit power modules, and synchronized temperature data. Simultaneously, it automatically captures historical test data and industry benchmark data for similar devices to construct a multi-dimensional database. Employing a dual-mode approach of automatic annotation and manual supplementation, it combines information such as power module model, test conditions, and environmental parameters to complete data labeling and generate standardized reference samples. It features a data anomaly pre-identification function, quickly filtering invalid data through threshold comparison to reduce redundant storage. It also supports self-updating of the sample library and, in conjunction with massive cloud-based data, provides high-precision data support for subsequent health prediction and parameter calibration.

[0042] Power Management Module: Ensuring a stable basic power supply while achieving triple improvements in energy efficiency, intelligence, and high reliability. Core functions include adaptive voltage regulation, seamless backup power switching, independent power supply control for multiple modules, comprehensive protection, and adaptive power consumption adjustment. It features real-time power status monitoring, displaying power parameters for each module intuitively on a touchscreen, and supports early warning of power anomalies, mitigating the impact of voltage fluctuations on test accuracy from the source, and adapting to the low-power requirements of portable outdoor testing.

[0043] Current Generator: Based on the classic dual-pulse topology, it integrates an intelligent load adjustment unit and a topology reconfiguration module. It can automatically match load parameters according to the rated current, rated voltage, and package specifications of the pressure-connected power module under test, eliminating the need for manual load replacement and adapting to the testing needs of devices from different manufacturers and models. It supports three triggering modes: fiber optic triggering, wireless triggering, and manual triggering, with a trigger delay ≤10ns and trigger accuracy ±0.5ns. It is compatible with mainstream valve drive control protocols, such as IEC 61850 and Modbus, and can be linked with field maintenance systems and cloud management platforms to achieve remote test command issuance, real-time monitoring of the test process, and synchronous upload of test data. It features a self-diagnostic function, automatically identifying trigger anomalies and topology matching faults, quickly providing feedback, and automatically adjusting parameters to improve testing efficiency and reliability.

[0044] Signal Acquisition Module: Configured with eight independent acquisition channels, expandable to sixteen channels. Six channels are used for current signal acquisition, and two channels are used for temperature signal acquisition. The sampling rate is ≥100MS / s, bandwidth ≥20MHz, and synchronization delay ≤10ns, ensuring synchronous acquisition of multi-channel data. A dual filtering mechanism is employed: hardware low-pass filtering + software adaptive noise reduction filtering. The analog filtering uses a low-pass filter with a cutoff frequency of 50MHz, while the digital filtering uses an adaptive Kalman filter algorithm, effectively filtering high-frequency electromagnetic interference signals and reducing noise impact. A real-time acquisition error calibration function is integrated, linked with the adaptive calibration module, automatically completing error calibration every 30 seconds, improving acquisition accuracy to ±0.2%. It supports synchronous acquisition and linked analysis of current and temperature dual parameters, capturing potential localized overheating hazards caused by current congestion. It features real-time data preprocessing, quickly completing data normalization and peak extraction, reducing the data processing burden on the controller. It also supports adaptive adjustment of acquisition parameters, automatically optimizing the sampling rate and filtering parameters according to test conditions without manual intervention. Shielded cables are used between the acquisition module and the measurement terminals to further reduce interference.

[0045] Magnetic field sensor: The probe uses a highly flexible PCB material, allowing for free bending and perfect adaptation to press-fit power modules of different shapes and sizes. It can be directly attached to the device surface for testing without the need for additional fixing fixtures. The probe head integrates a single sensing unit, housing a high-sensitivity magnetic field sensor and a high-precision temperature sensor. It can simultaneously acquire magnetic field signals and device surface temperature, indirectly converting the current distribution through the magnetic field signal to achieve coordinated monitoring of current and temperature dual parameters. The probe cable features a double-layer shielding design: a metal shielding mesh and an insulating shielding layer, effectively suppressing electromagnetic interference. The cable length is adjustable, allowing for flexible adjustments according to the testing scenario. The probe interface features a foolproof design to prevent mis-insertion, ensuring easy plugging and unplugging. It is also waterproof and dustproof, with an IP65 protection rating, suitable for complex testing environments such as outdoor and industrial sites.

[0046] Adaptive Calibration Module: Creates a real-time, automated, and remote calibration system, enabling synchronous calibration of all modules without disassembly. It features built-in high-precision standard current and temperature sources, automatically identifying calibration requirements and adjusting parameters based on the specifications of the device under test and test conditions, achieving synchronous calibration of the acquisition channel, current generation unit, and magnetic field sensor. Remote calibration functionality allows for cross-regional calibration via cloud-based standard source integration, significantly reducing maintenance costs. Built-in automatic calibration log recording meticulously documents calibration time, parameters, and results, ensuring traceability and meeting industry compliance requirements. A calibration anomaly warning function immediately triggers audible and visual alerts and provides adjustment suggestions if calibration results exceed thresholds. The calibration cycle is adaptively adjustable, balancing calibration accuracy and testing efficiency. It supports three modes: automatic calibration upon power-on, automatic calibration after every 10 tests, and manual calibration. Calibration data is automatically stored in the controller and can be accessed in real-time.

[0047] Electromagnetic Shielding Module: Addressing the core issue of decreased test accuracy and data distortion caused by electromagnetic interference under high-frequency operating conditions, this module employs a layered shielding and fully enclosed integrated design, covering all internal hardware modules, external interfaces, and connecting cables. With a shielding effectiveness of ≥80dB, it effectively suppresses mid-to-high frequency electromagnetic interference in the 10MHz-1GHz band, ensuring data stability in high-frequency testing scenarios. The shielding cover is made of lightweight, high-strength alloy material, balancing shielding effectiveness with portability. Its detachable modular design facilitates maintenance, upgrades, and replacement of internal modules, adapting to the electromagnetic environment requirements of different testing scenarios, such as industrial high-interference environments and precise laboratory testing environments. It features real-time shielding effectiveness monitoring with a built-in electromagnetic interference sensor that monitors the intensity of electromagnetic interference around the device. When interference exceeds a threshold, it automatically activates an enhanced shielding mode, adjusts internal shielding circuit parameters, and triggers an early warning to remind personnel to adjust the testing position. The shielding cover surface has a non-slip, wear-resistant coating and built-in heat dissipation holes, ensuring effective shielding while preventing overheating of internal modules and extending the equipment's lifespan.

[0048] Multi-condition adaptation module: Creates a full-scenario, multi-condition adaptive testing system, supporting three basic test conditions: low frequency, medium-high frequency, and high-low temperature. It can automatically identify device specifications and testing requirements based on the actual operating conditions of the device under test (DUT), switching test modes and adaptively adjusting acquisition parameters, trigger parameters, and load parameters without manual settings, significantly improving testing efficiency. It features extreme condition simulation capabilities, simulating complex conditions such as instantaneous overload, sudden temperature changes, electromagnetic interference mutations, and voltage fluctuations in actual operation of the DUT. This enables testing that more closely resembles real-world application scenarios, allowing for early detection of abnormal current distribution and hidden faults under extreme conditions. Users can manually set test condition parameters to construct customized test scenarios according to their testing needs. It supports a condition switching buffer mechanism to prevent damage to the DUT and testing equipment caused by sudden parameter changes. It also features a condition test data comparison function, allowing synchronous comparison of test data under different conditions, intuitively demonstrating the impact of condition changes on the current distribution of the power module, providing data support for device optimization design.

[0049] Health Status Prediction Module: Constructs a full-chain health management system encompassing detection, assessment, early warning, and prediction. Breaking through the limitations of traditional methods that only detect current distribution, it integrates multi-dimensional indicators and AI intelligent algorithms to achieve full lifecycle health management of the tested devices. Core functions include: Multi-indicator fusion assessment, which not only calculates the maximum deviation rate and current dispersion but also combines temperature data, current drift data, and electromagnetic signal data to calculate multi-dimensional assessment indicators such as local thermal stress coefficient, current drift rate, device aging degree, and insulation performance degradation coefficient; AI intelligent prediction, employing a fusion algorithm of LSTM neural network and CNN convolutional neural network, using historical test data, industry benchmark data, and device maintenance records for model training to continuously optimize prediction accuracy, achieving a prediction error ≤5%; Hidden degradation early warning, identifying potential hidden degradation hazards within the device in advance, such as local current congestion, excessive thermal stress, decreased insulation performance, and aging of internal solder joints, triggering tiered early warnings to remind staff to perform timely maintenance; and lifespan prediction, combining full lifecycle data to predict the remaining lifespan of the device, providing a basis for the reliability management of critical equipment. It features a health status visualization function, which intuitively displays the health level and degradation trend of the device in the form of curves and charts through the touch screen. It supports the automatic generation of health reports and can also be connected to the full life cycle management module and cloud platform to realize remote monitoring of health status and maintenance reminders.

[0050] Data Encryption Transmission Module: Employing the AES-256 encryption algorithm, this module constructs a comprehensive encryption system across the entire process of data acquisition, storage, and transmission, ensuring that test data is not leaked, tampered with, or is traceable. It supports multiple transmission channels, including Ethernet and wireless modes, and can flexibly connect to host computers, on-site maintenance systems, and cloud databases to achieve real-time uploading and sharing of test data. It features adaptive transmission mode switching, automatically selecting the optimal transmission method based on network conditions: prioritizing wireless transmission when the network is stable and switching to wired transmission when the network is unstable, ensuring stable data transmission. It supports local data storage, capable of storing ≥1000 sets of test data with a retention period of over one year. Built-in data backup functionality automatically backs up data to both local storage and the cloud, providing dual protection for data traceability, subsequent analysis, and industry compliance checks. It also features data anomaly tracing capabilities; once data leakage or tampering is detected, transmission nodes and operation records can be quickly traced. Furthermore, it supports hierarchical data access management, granting different personnel different data viewing, editing, and export permissions, further ensuring data security.

[0051] Lifecycle Management Module: This module constructs a comprehensive data management system for the entire lifecycle of the device under test (DUT), creating a dedicated lifecycle profile for each DUT. It meticulously records detailed information including device model, specifications, test data, health assessment results, maintenance records, fault records, and calibration records. It supports rapid multi-condition queries, allowing users to search for relevant data by device model, test time, health level, and test conditions, offering convenient operation. It also supports automatic generation and export of test reports, which include test parameters, data curves, health assessments, and early warning suggestions, meeting the needs of test acceptance, maintenance reporting, and industry compliance. The module can interface with equipment maintenance systems and cloud management platforms to enable predictive maintenance, lifecycle assessment, and fault tracing for DUTs, providing complete data support for the reliability management of critical equipment. It features batch management capabilities, allowing centralized management of DUTs within the same batch, comparing and analyzing performance differences between batches, and providing a basis for device procurement and quality control. Finally, it supports long-term storage and export of profile data for easy traceability and analysis.

[0052] The controller adopts an architecture of a dual-core ARM Cortex-A9 processor and an FPGA logic control unit, with a main frequency of 1.0GHz, 2.0GB of memory, and 16.0GB of storage capacity, achieving high-speed response, intelligent control, and massive data processing. The dual-core processor is responsible for AI-assisted control, real-time command issuance, and anomaly warning handling, while the FPGA logic control unit is responsible for the rapid processing of massive amounts of acquired data, with a response latency of ≤50μs. It features a built-in test control algorithm that enables automatic switching of test modes, adaptive adjustment of acquired parameters, and real-time handling of abnormal situations. It is also equipped with a real-time clock module to record the time and parameters of each test, facilitating data traceability.

[0053] This invention provides a portable method for testing the current distribution of a crimp-type power module, comprising the following steps.

[0054] Step 1: System initialization. Select a suitable magnetic field sensor probe, attach it to the device under test, and reliably connect it without damaging the device structure. After starting the system, the power management module completes self-test and power supply adaptation and monitors the power supply status in real time. After inputting the basic parameters of the device, the controller initially matches the test parameters and activates basic electromagnetic shielding, laying the foundation for subsequent testing.

[0055] Step 2: Adaptive full-module synchronous calibration, used to ensure test accuracy and eliminate equipment errors. The system recommends an appropriate calibration mode based on test requirements, supports remote calibration to reduce maintenance costs, uses a high-precision standard source to synchronously calibrate each core module, and handles calibration anomalies in a targeted manner to ensure calibration is qualified.

[0056] Step 3: Multi-condition adaptive matching and test parameter optimization to adapt to real-world scenarios and improve testing efficiency. The system automatically identifies and switches to suitable basic test conditions, and can also manually simulate extreme conditions. The controller, in conjunction with relevant modules, automatically optimizes various test parameters while simultaneously controlling electromagnetic interference in real time to ensure efficient and accurate testing.

[0057] Step 4: Multi-parameter synchronous acquisition and data preprocessing are used to obtain core data and ensure data validity. Select the appropriate trigger mode to start acquisition, simultaneously acquiring multi-dimensional core data such as device current distribution and temperature. Perform preprocessing on the acquired data, including normalization, filtering, and verification, to remove invalid data and ensure data accuracy, preparing for subsequent analysis.

[0058] Step 5: Data encryption transmission, storage and multi-dimensional analysis. The AES-256 algorithm is used to encrypt the effective data throughout the entire process. Data security is ensured by transmitting through multiple channels and implementing dual backup. The AI ​​fusion algorithm is called to analyze the data, calculate core indicators, and complete device health level assessment, early warning and life prediction.

[0059] Step 6: Full lifecycle management. Establish a dedicated file for the device under test, record detailed test and evaluation data throughout the entire process and support multi-condition queries, centrally manage and compare devices in the same batch, link with relevant systems to achieve predictive maintenance, and finally complete the test closing to facilitate subsequent repeated testing.

[0060] This invention employs a non-invasive flexible test design, eliminating the need to damage the structure of the device under test and adapting to devices of various specifications. It integrates AI intelligent optimization and adaptive calibration technology to achieve automatic adaptation of test parameters, operating modes, and calibration cycles, significantly improving test efficiency and accuracy. It constructs a full-link system of test-analysis-early warning-management, breaking through the limitations of traditional methods that can only detect current distribution, and realizing full life-cycle health management of devices. Combining multi-channel encrypted transmission and lightweight design, it balances data security and portability, adapting to the testing needs of multiple scenarios.

[0061] Example 1.

[0062] This embodiment 1 discloses a portable crimp-type power module current distribution testing system, wherein step 1 includes the following steps.

[0063] 1.1 Device Adaptor Preparation: No disassembly of the pressure-fit power module under test is required. Based on its shape and size, select a non-invasive magnetic field sensor probe made of highly flexible PCB material and directly attach the probe to the surface of the device under test. The probe's own flexibility enables a seamless fit without the need for additional fixing fixtures. Adjust the probe cable length according to the test scenario and connect it to the measurement terminals on the front panel of the test system through the anti-misinsertion and foolproof interface to ensure reliable connection while ensuring that the airtightness and insulation structure of the device under test are not damaged.

[0064] 1.2 System Startup and Power Supply Adaptation: Upon powering on the test system, the power management module automatically starts and enters self-test mode, intelligently identifying the test scenario, such as outdoor / indoor, and automatically switching the power supply mode, including mains power / built-in lithium battery. If it is an outdoor scenario without power supply, it automatically switches to backup lithium battery power supply. At the same time, it starts real-time monitoring of power supply status, intuitively displaying the power supply parameters of each module through the touch screen, and completing the initialization of overcurrent / overvoltage / overheat protection to avoid the risk of power supply abnormalities.

[0065] 1.3 System Parameter Initialization: The user inputs basic parameters such as the model, rated current, rated voltage, and package specifications of the pressure-connected power module under test via the touch screen. After receiving the parameters, the controller automatically calls up commonly used parameters from the built-in instruction memory function and, combined with AI-assisted optimization algorithms, initially matches the test parameters. At the same time, the electromagnetic shielding module is activated to enter the basic shielding mode, ensuring that the initialization process is not subject to electromagnetic interference.

[0066] This technical solution uses a non-invasive magnetic field sensor probe made of highly flexible PCB material, which can be freely attached to press-fit power modules of different shapes and sizes without the need for additional fixing fixtures, and does not damage the airtight and insulating structure of the device under test, thus solving the problems of poor compatibility and the need to disassemble the device in traditional probes.

[0067] Example 2.

[0068] This embodiment 2 discloses a portable crimp-type power module current distribution testing system, wherein step 2 includes the following steps.

[0069] 2.1 Calibration Mode Selection: The system automatically identifies the specifications of the device under test and the test conditions, and recommends the appropriate calibration mode. It supports three modes: automatic calibration, remote calibration, and manual calibration. For remote testing or unattended scenarios, remote calibration mode can be started through cloud standard source connection, eliminating the need for on-site operation by staff and greatly reducing maintenance costs.

[0070] 2.2 Full-Module Collaborative Calibration: The adaptive calibration module incorporates high-precision standard current and temperature sources, with the standard current source having an accuracy of ±0.05% and the standard temperature source an accuracy of ±0.05℃. It automatically identifies calibration requirements, adjusts calibration parameters, and simultaneously calibrates the signal acquisition module, magnetic field sensor, current generator, and data collection module, achieving a calibration accuracy of ±0.1%. Specifically, the probe sensitivity calibration of the magnetic field sensor is linked to the acquisition error calibration of the signal acquisition module, completing a real-time acquisition error calibration every 30 seconds. The magnetic field sensor sensitivity calibration is synchronized to ensure measurement accuracy for long-term use. During the calibration process, a calibration log is automatically recorded, detailing the calibration time, parameters, and results for easy traceability and to meet industry compliance requirements.

[0071] 2.3 Calibration Anomaly Handling: If the calibration result exceeds the threshold, the system will immediately trigger an audible and visual warning, and an anomaly pop-up window will appear on the touch screen, clearly displaying the calibration anomaly module and adjustment suggestions; if it is a minor calibration deviation, the system will automatically adjust the calibration parameters and re-complete the calibration; if it is a serious anomaly, the power supply to the corresponding module will be immediately cut off to avoid affecting the accuracy of subsequent tests, and the anomaly information will be recorded to facilitate troubleshooting by staff.

[0072] Example 3.

[0073] This embodiment 3 discloses a portable crimp-type power module current distribution testing system, wherein step 3 includes the following steps.

[0074] 3.1 Adaptive Switching of Operating Modes: The multi-condition adaptation module automatically identifies the actual operating conditions of the device under test (DUT) and, based on the input basic parameters, automatically switches to the appropriate test condition from three basic operating conditions: low frequency, medium-high frequency, and high-low temperature. To simulate complex scenarios in actual operation, the extreme condition simulation function can be manually activated, setting extreme parameters such as instantaneous overload, sudden temperature changes, and sudden electromagnetic interference changes to construct test scenarios that closely match real-world applications. Low frequency is ≤1kHz, medium-high frequency is 1kHz-10MHz, and high-low temperature is -40℃ to 150℃.

[0075] 3.2 Intelligent Optimization of Test Parameters: The controller, in conjunction with the current generator and signal acquisition module, automatically optimizes various test parameters based on the current test conditions. The current generator automatically matches the load parameters, eliminating the need for manual load replacement. Simultaneously, it optimizes the trigger parameters, defaulting to the trigger mode adapted to the current scenario, including fiber optic / wireless / manual, ensuring trigger latency ≤10ns and trigger accuracy ±0.5ns. The signal acquisition module automatically adjusts the sampling rate and filtering parameters, activating a dual filtering mechanism: hardware low-pass filtering and software adaptive noise reduction filtering, ensuring synchronization latency ≤10ns and acquisition accuracy maintained at ±0.2%.

[0076] 3.3 Electromagnetic Interference Adaptive Prevention and Control: The electromagnetic shielding module monitors the electromagnetic interference intensity in the test environment in real time. Through the built-in electromagnetic interference sensor, if the interference intensity exceeds the threshold in the 10MHz-1GHz frequency band, the enhanced shielding mode is automatically activated, and the internal shielding circuit parameters are adjusted to ensure that the shielding effectiveness is ≥80dB, avoiding electromagnetic interference that could cause test data distortion. At the same time, the touch screen displays the information to remind the staff to adjust the test position as needed, further ensuring test stability.

[0077] In this technical solution, the multi-condition adaptation module can automatically identify the actual working conditions of the device under test and automatically switch between three basic conditions: low frequency, medium and high frequency, and high and low temperature. At the same time, it supports manual simulation of extreme conditions to build test scenarios that fit actual applications and discover hidden faults in devices in advance.

[0078] Example 4.

[0079] This embodiment 4 discloses a portable crimp-type power module current distribution testing system, wherein step 4 includes the following steps.

[0080] 4.1 Trigger Start-up Test: First, confirm that the preset trigger mode has been adapted. Select manually or automatically according to the test scenario. The fiber optic trigger mode is suitable for long-distance testing scenarios, with a transmission distance ≤50m and stronger resistance to electromagnetic interference in industrial environments. The wireless trigger mode uses the Bluetooth 5.2 protocol, suitable for portable mobile testing scenarios, with a transmission distance ≤10m and supports wireless router relay extension. The manual trigger mode serves as an emergency backup, activated via the physical trigger button on the touchscreen display, suitable for simple scenarios without network or fiber optic deployment. Trigger commands are uniformly issued by the controller. After receiving the command, the current generator quickly responds and outputs an adapted dual-pulse signal. The pulse width can be automatically adjusted according to the rated current of the device under test. It is also compatible with mainstream valve drive control protocols such as IEC 61850 and Modbus, and can be linked with the on-site maintenance system. Maintenance personnel can remotely monitor the trigger status and dual-pulse signal waveform through the on-site maintenance terminal, and intervene in the testing process in real time, such as pausing or restarting the test, ensuring that the testing process is traceable and controllable. After being triggered, the system automatically enters the data acquisition preparation state. After a delay of ≤50μs, it starts multi-parameter synchronous acquisition to avoid data distortion caused by conflict between the trigger signal and the acquisition signal.

[0081] 4.2 Multi-dimensional synchronous data acquisition: Achieve non-invasive, high-precision, and multi-parameter collaborative acquisition. Through the linkage between the magnetic field sensor and various modules of the test system, complete the comprehensive acquisition of relevant data inside and outside the device under test. Specifically, the magnetic field sensor probe synchronously acquires the magnetic field signal and surface temperature signal of the device under test. The magnetic field signal measurement range is 0-500mT, with a sensitivity ≥10mV / mT. The sampling interval can be automatically adjusted according to the test conditions: 10μs for low-frequency conditions and 1μs for medium- and high-frequency conditions. The acquired magnetic field signal is transmitted to the signal acquisition module through a double-shielded cable. The signal conversion unit built into the module indirectly converts the magnetic field signal into real-time current data of each parallel chip inside the press-fit power module. The conversion formula is based on previous calibration data and AI algorithm optimization, with a conversion error ≤±0.3%, completely solving the blind spot of existing methods being unable to obtain chip-level current distribution. The temperature signal measurement range is -40℃~150℃, with an accuracy of ±0.2℃. The sampling frequency is synchronized with the magnetic field signal, which can accurately capture local temperature changes on the surface of the device under test, providing basic data for subsequent calculation of local thermal stress coefficient. Simultaneously, the signal acquisition module activates eight independent acquisition channels, each working independently without interference, synchronously acquiring the total current signal, terminal voltage signal, and ambient temperature signal of the device under test. This enables multi-parameter collaborative monitoring of the internal parallel chip current distribution, surface temperature, total current, terminal voltage, and ambient temperature. In addition, the data collection module synchronously acquires the operating parameters of each hardware module of the test system, including the power supply voltage of the power management module, the operating temperature of each module, and power consumption data. Standby power consumption is ≤5W, and the power consumption is dynamically adjusted from 20W to 50W during testing. This data is used for subsequent system operation status self-checks and data anomaly troubleshooting. The synchronization delay of all acquired data is strictly controlled to ≤10ns to ensure the time consistency of multi-parameter data and provide a guarantee for subsequent correlation analysis.

[0082] 4.3 Real-time Data Preprocessing: After the signal acquisition module completes data acquisition, it immediately starts the built-in preprocessing algorithm to quickly optimize and filter the data, reducing the data processing pressure on the controller and ensuring the efficiency and accuracy of subsequent analysis. The specific preprocessing process is as follows.

[0083] The first step is data normalization, which transforms the collected data from different dimensions such as current, temperature, and magnetic field into a standardized range of 0-1 to eliminate analysis errors caused by differences in the magnitude of different parameters.

[0084] The second step is peak extraction, which automatically identifies peak current distribution, temperature, and magnetic field signal, and marks the time and location of peak occurrence, providing direct evidence for identifying abnormal phenomena such as local current congestion and local overheating.

[0085] The third step is invalid data screening. The data collection module simultaneously starts the data anomaly pre-identification function, presets the normal threshold range of each parameter, such as the current signal threshold of 0-1000A and the temperature signal threshold of -40℃~150℃. By comparing the thresholds, invalid data that exceeds the normal range and abnormal data with excessive fluctuations are quickly screened out. Fluctuations ≥5% are considered abnormal and invalid data types are automatically marked, such as acquisition interference and poor sensor contact, to reduce redundant storage.

[0086] The fourth step is to initially label the data. Based on information such as the model of the device under test, test conditions, and environmental parameters, standardized tags are added to the valid data. The tags include device number, test time, operating condition type, and acquisition channel number, which facilitates subsequent data query, classification, and analysis.

[0087] The fifth step is data verification. After preprocessing, the system automatically compares the consistency of data from different acquisition channels with the same parameter. The consistency deviation is ≤ ±0.1%. If the deviation exceeds the threshold, the corresponding acquisition channel is automatically restarted and data is reacquired to ensure that the accuracy of the preprocessed data meets the test requirements. The preprocessed data is temporarily stored in the system cache, waiting for transmission and subsequent analysis.

[0088] Example 5.

[0089] This embodiment discloses a portable crimp-type power module current distribution testing system, wherein step 5 includes the following steps.

[0090] 5.1 Data Encryption Transmission and Storage: This step focuses on achieving end-to-end data security, multi-channel transmission, and dual backup to ensure that test data is not leaked, tampered with, and is traceable, while also adapting to the data storage and sharing needs of different scenarios.

[0091] First, the data encryption transmission module uses the AES-256 military-grade encryption algorithm to encrypt the valid data after preprocessing in step 4 throughout the entire process. The encryption process consists of three stages: encryption at the acquisition end, encryption at the transmission end, and encryption at the storage end, completely eliminating the risk of data leakage and tampering during acquisition, transmission, and storage. During transmission, data is encrypted into data packets with a checksum added. Data is encrypted again before storage, and keys are dynamically generated, with each batch of test data corresponding to a unique key. The transmission method adopts multi-channel adaptive switching. The system has a built-in network status monitoring unit that detects the current network environment in real time. When the network is stable, wireless transmission mode is prioritized, and test data is simultaneously uploaded to the host computer, the on-site operation and maintenance system, and the cloud database. When the network is unstable, it automatically switches to wired transmission mode to ensure the stability and integrity of data transmission. If there is no network environment, the data is temporarily stored in the local storage unit, with a default local storage capacity of 16GB, which can be expanded to 64GB via SD card. Meanwhile, the system features built-in local and cloud dual backup capabilities. Local data is automatically backed up every 30 minutes, while cloud data is backed up in real time. If local data is lost, it can be quickly restored through the cloud backup. It also has a data anomaly tracing function. When data leakage, tampering, or transmission failure is detected, the system automatically records the transmission node, operation time, and operator information, generating a tracing report to facilitate rapid problem investigation. Furthermore, it supports hierarchical data access control, divided into three levels: administrator, maintenance personnel, and test personnel. Different levels of personnel have different data viewing, editing, and export permissions, further ensuring data security. In addition, during data transmission, the system displays the transmission progress, transmission rate, and transmission status in real time. If a transmission interruption occurs, it automatically resumes transmission after network recovery, without needing to retransmit all data.

[0092] 5.2 Multi-dimensional Data Analysis: Based on pre-processed encrypted valid data, combined with AI intelligent algorithms and a multi-dimensional database, chip-level current distribution analysis and device aging assessment are achieved, providing data support for subsequent health status assessment. The specific analysis process is as follows.

[0093] The first step is data decryption and retrieval. The controller calls the decryption algorithm to decrypt the encrypted data transmitted to the local machine or the cloud. At the same time, it retrieves historical test data and industry benchmark data of the same model and operating conditions as the device under test from the multi-dimensional database built by the data collection module as reference samples for analysis and comparison.

[0094] The second step is algorithm startup and parameter configuration. The controller calls the LSTM neural network and CNN convolutional neural network fusion algorithm of the health status prediction module. This algorithm has been trained and optimized with massive historical test data, with ≥10,000 training samples and a prediction error ≤5%. The algorithm automatically configures the corresponding analysis parameters, such as the current distribution deviation threshold and the temperature change rate threshold, according to the specifications of the device under test and the test conditions.

[0095] The third step is to calculate the core indicators. The decrypted test data is analyzed from multiple dimensions using a fusion algorithm. The focus is on calculating six core evaluation indicators: maximum deviation rate, current dispersion, local thermal stress coefficient, current drift rate, device aging degree, and insulation performance degradation coefficient.

[0096] The maximum deviation rate assesses the uniformity of current distribution among parallel chips, with a threshold of ≤5%; exceeding this threshold is considered an abnormal current distribution. Current dispersion assesses the degree of current difference among parallel chips; the greater the dispersion, the lower the device reliability. The local thermal stress coefficient is calculated by combining local temperature changes and current distribution data; a coefficient ≥1.2 is considered an over-limit thermal stress. The current drift rate assesses the current stability of the device after long-term operation; a drift rate ≥0.5% / 100h is considered abnormal. The device aging degree is divided into three levels: mild aging, moderate aging, and severe aging, based on the current drift rate and local thermal stress coefficient. The insulation performance attenuation coefficient is assessed by combining temperature data and current signal fluctuations; an attenuation coefficient ≥0.1 is considered a decrease in insulation performance.

[0097] The fourth step is comparative analysis and anomaly identification. The calculated core indicators are compared with historical test data and industry benchmark data to identify the differences between the current test data and the reference sample, accurately locate anomalies such as local current congestion and thermal stress exceeding limits, and analyze the preliminary causes of the anomalies, such as chip aging, poor contact and electromagnetic interference.

[0098] The fifth step is to cache and feed back the analysis results. The core indicators and anomaly identification results obtained from the multi-dimensional analysis are cached in the local and cloud databases and fed back to the controller to provide data support for subsequent health status assessment and early warning.

[0099] The calculation model for the maximum deviation rate is as follows.

[0100] ; .

[0101] In the formula, The maximum real-time current value of each parallel chip, in A; is the average real-time current of each parallel chip; n is the number of parallel chips. The real-time current value of the i-th chip is calculated from the magnetic field signal; This is a correction term for the accuracy of magnetic field acquisition. =0.001~0.003, obtained from the real-time calibration accuracy of the magnetic field sensor, reflects the unique adaptability of non-invasive acquisition, which is different from the deviation calculation of traditional direct flow measurement.

[0102] The current dispersion model is as follows.

[0103] .

[0104] in: For multi-condition adaptation factors, low-frequency conditions =1.0, medium and high frequency operating conditions =1.05~1.1, high and low temperature operating conditions =1.1~1.15, adaptable to different test conditions for dispersion evaluation, unlike traditional fixed-coefficient dispersion calculation; dispersion threshold σ≤0.8A× It adaptively adjusts according to the rated current of the device under test and the type of operating condition.

[0105] The local thermal stress coefficient model is as follows.

[0106] .

[0107] Where: k is the thermal stress correction factor, k=1.05~1.15, which is adapted according to the material of the device; The local temperature of the region corresponding to the i-th chip; The ambient temperature of the device; Let be the magnetic field signal value of the i-th chip region. The maximum range of the magnetic field signal is 500 mT; This is a magnetic field-coordinated correction term that reflects the linkage of three parameters: magnetic field, temperature, and current. It corrects the influence of magnetic field strength on local thermal stress, which is different from the traditional thermal stress calculation that only considers current and temperature.

[0108] The current drift rate model is as follows.

[0109] .

[0110] in: This represents the average current of each chip during the current test cycle. The current value of each chip in the device's brand-new state during the initial test cycle is t; t is the current test time; t0 is the initial test time. This is a calibration accuracy correction term, derived from the calibration accuracy of the adaptive calibration module. =0.002~0.005; The time decay factor, =0.001~0.003 / h, which reflects the drift decay characteristics of the device during long-term operation, and is different from the traditional drift rate calculation that ignores calibration accuracy and time decay. This represents the current drift rate.

[0111] The insulation performance attenuation coefficient model is as follows.

[0112] .

[0113] in: Insulation performance attenuation coefficient This represents the maximum voltage fluctuation at the terminals, in volts (V). This is the rated terminal voltage of the device; For local temperature, Standard reference temperature; This represents the local magnetic field signal value, in mT. This is a temperature-magnetic field coupling correction term, which reflects the coupling effect of magnetic field and temperature on insulation performance in non-invasive testing, unlike the traditional insulation attenuation calculation that only considers temperature.

[0114] The device aging model is as follows.

[0115] .

[0116] Where D∈[0,1], D<0.3 indicates mild aging, 0.3≤D<0.7 indicates moderate aging, and D≥0.7 indicates severe aging; As an aging acceleration factor, =0.1~0.2, calculated by linking the local thermal stress coefficient S and the insulation performance attenuation coefficient λ, reflecting the characteristics of multi-factor synergistic acceleration of aging, which is different from the traditional aging assessment that only considers current drift and thermal stress.

[0117] 5.3 Health Status Assessment and Early Warning: Based on the multi-dimensional analysis results in step 5.2, a full-chain health management system for the device under test (DUT) is constructed, encompassing detection, assessment, early warning, and prediction, achieving a leap from single detection to intelligent control. The specific implementation process is as follows.

[0118] The first step is health level assessment. Based on the six core assessment indicators calculated in step 5.2 and combined with the preset health level classification standards, the controller comprehensively assesses the health status of the tested press-fit power module submodule, which is divided into four health levels.

[0119] Health: All core indicators are within the normal threshold range, with no abnormalities.

[0120] Mild degradation: One or two core indicators are close to the threshold, with no obvious abnormalities, and do not affect normal operation. Regular monitoring is required.

[0121] Moderate degradation: One or two core indicators exceed the threshold, indicating localized current congestion or slight thermal stress exceeding limits, requiring timely maintenance.

[0122] Severe degradation: Three or more core indicators exceed the threshold, indicating serious abnormal current distribution and excessive thermal stress, posing a risk of failure. It is necessary to stop using it immediately and replace it.

[0123] The second step is to visualize the health status. The controller transmits the health level assessment results, core indicator data, and anomaly identification results to the touch screen, which is displayed intuitively in the form of curves, charts, and heat maps. The current distribution is presented in the form of a heat map, which can clearly show the current distribution of each parallel chip. Local areas with excessive thermal stress are marked in red, which makes it easy for staff to quickly locate the potential hazards.

[0124] The third step is to trigger tiered warnings. Based on the health level assessment results, the system will automatically trigger the corresponding tiered warnings.

[0125] Mild degradation triggers a Level 1 warning, indicated by a green indicator light and a notification message popping up on the touchscreen. No immediate action is required; only periodic monitoring is necessary.

[0126] Moderate degradation triggers a Level 2 warning: a yellow indicator light plus an audible and visual warning, and a pop-up with troubleshooting suggestions, reminding staff to complete maintenance within 24 hours.

[0127] Severe degradation triggers a Level 3 warning: a red indicator light plus continuous audible and visual alarms, automatically cutting off the test circuit of the device under test, prohibiting further testing, and displaying an emergency handling plan to remind staff to replace the device immediately.

[0128] The fourth step is lifespan prediction and maintenance recommendations. Combining the full lifespan data of the device under test, including current test data, historical test data, and maintenance records, a fusion algorithm is used to predict the remaining lifespan of the device. At the same time, based on the anomaly identification results, targeted maintenance recommendations are automatically generated, such as local chip maintenance, probe re-attaching, and module calibration.

[0129] The fifth step involves transmitting early warning information and maintenance recommendations. The health level assessment results, graded early warning information, remaining service life prediction, and maintenance recommendations are simultaneously transmitted to the on-site operation and maintenance system, cloud management platform, and staff mobile devices. This ensures that operation and maintenance personnel can obtain early warning information in a timely manner, quickly carry out maintenance work, achieve predictive maintenance, avoid the positive feedback accumulation of local current congestion → local high temperature → further parameter drift → further current congestion, and prevent the early failure of a single chip / few sub-units from expanding into a chain reaction of damage to multiple sub-units.

[0130] The health status assessment and early warning model is as follows.

[0131] .

[0132] Where H is the overall health score, 0≤H≤100; - These are the weighting coefficients for each core indicator. =0.25, =0.15, =0.2, =0.15, =0.15, =0.1, with a weighted sum of 1.0, which can be adaptively adjusted according to the application scenario of the device; For multi-condition adaptation factors, For health assessment fit coefficient, =0.95~1.05, adjusted in conjunction with the device's service life and test conditions, for older devices and under extreme conditions. Appropriately lower the threshold to improve the relevance of health assessments; classify health into four levels based on H-values.

[0133] Health: H≥85, all core indicators are within the normal threshold range, with no abnormalities.

[0134] Mild degradation: 70≤H<85, 1-2 core indicators are close to the threshold, no obvious abnormalities, does not affect normal operation, but requires regular monitoring.

[0135] Moderate degradation: 50≤H<70, 1-2 core indicators exceed the threshold, there is local current congestion or slight thermal stress exceeding the limit, timely maintenance is required.

[0136] Severe degradation: H<50, 3 or more core indicators exceed the threshold, there is serious abnormal current distribution and thermal stress exceeding the limit, there is a risk of failure, and it is necessary to stop using it immediately and replace it.

[0137] Example 6.

[0138] This embodiment discloses a portable crimp-type power module current distribution testing system, wherein step 6 includes the following steps.

[0139] 6.1 Full Lifecycle File Establishment: The full lifecycle management module establishes a dedicated full lifecycle file for the device under test, recording detailed information such as device model, specifications, test data, health assessment results, calibration records, etc. It supports quick queries by device model, test time, health level, and other conditions, and can automatically generate PDF test reports containing test parameters, data curves, health assessments, early warning suggestions, etc., facilitating test acceptance and maintenance reporting.

[0140] 6.2 Batch Management and Data Linkage: If multiple devices from the same batch are tested, the full lifecycle management module will activate the batch management function to centrally manage the test data of the same batch of devices, compare and analyze the performance differences between batches, and provide a basis for device procurement and quality control. At the same time, the test data will be linked with the cloud database and equipment operation and maintenance system to realize predictive maintenance of the devices under test and automatically issue maintenance suggestions and maintenance time.

[0141] 6.3 Test Completion: After the test is completed, the controller issues a command, and each module stops working in sequence. The power management module automatically switches to standby mode to reduce energy consumption. If there is no operation for a long time, the touch screen will automatically turn off for protection. The staff can remove the magnetic field sensor probe without disassembling the device under test or tidying up the test equipment. They can view the test report and export the data through the touch screen to complete the test completion. If subsequent tests are needed, the test parameters can be directly called up without repeated initialization.

[0142] Example 7.

[0143] This embodiment discloses a portable crimp-type power module current distribution testing system, wherein the testing device includes a housing 1, a cover 2, and a pull rod 9. The overall structure adopts a rectangular portable design, balancing structural strength and ease of movement, and is suitable for both fixed laboratory testing and mobile on-site maintenance needs.

[0144] A lid 2 is rotatably mounted on the enclosure 1; a latch is installed between the enclosure 1 and the lid 2. The connection between the enclosure 1 and the lid 2 is a hinge made of high-strength stainless steel, which can open and close freely from 0-180°, facilitating operators to open the lid for wiring, debugging, and maintenance. The latch between the enclosure 1 and the lid 2 has a waterproof and anti-theft structure, ensuring a tight fit between the lid 2 and the enclosure 1 when closed, preventing the lid from loosening during transportation or movement, while also improving the waterproof and dustproof performance of the device, achieving an IP54 protection rating in conjunction with the enclosure shell.

[0145] The housing 1 is equipped with a pull rod 9. The pull rod 9 is installed at the top center of the housing 1. It is a telescopic structure made of high-strength aluminum alloy, which is lightweight and has a strong load-bearing capacity. The telescopic stroke is 0-80cm, and the telescopic length can be flexibly adjusted according to the height of the operator and the handling needs. The bottom of the housing 1 is equipped with multiple casters 8 that can rotate. They are made of silent and non-slip rubber wheels, which can easily drag and move the device, greatly reducing the difficulty of on-site handling.

[0146] The enclosure 1 houses a touch screen display 3, measurement terminals 4, a USB network port 5, connection terminals 6, and fiber optic drive terminals 7. All are integrated into the front panel inside the enclosure 1, resulting in a rational layout and convenient operation.

[0147] Connection terminal 6 is a power terminal with two channels, with a maximum current carrying capacity of 50A and voltage of 1000V. It adopts a high-temperature resistant ceramic interface and is used to connect the device under test. The fiber optic drive terminal 7 has two channels and is an SC interface, which is compatible with mainstream valve drive control protocols.

[0148] Intelligent cooling fans 10 are fixedly installed on both sides of the housing 1.

[0149] The front panel of the testing device features an integrated touchscreen design for easy operation, and is equipped with six measurement terminals, a USB network port, power terminals, fiber optic driver terminals, and a display. It features a 10.1-inch high-definition industrial-grade touchscreen display with a resolution of 1920×1200 and a viewing angle of 178°. It supports multi-touch and offline operation modes, allowing for testing, data viewing, and local storage even without a network connection. Once connected to the network, data is automatically synchronized to the cloud. The display interface uses a modular design, displaying test parameters, collected data, health status, power supply status, electromagnetic interference intensity, and other information in real time. Data curves are updated in real time, providing a clear view of the testing process. It also features an anomaly pop-up alert function; when equipment malfunctions, test anomalies, or calibration failures occur, a pop-up window immediately appears, clearly displaying the fault point and troubleshooting suggestions for quick problem identification. It is also waterproof and dustproof, with an IP65 protection rating, suitable for complex testing environments such as industrial sites and outdoor environments. Below the display are three status indicator lights: a green power indicator (always on in standby, flashing during operation); a red fault indicator (flashing and accompanied by a buzzer when abnormal); and a blue communication indicator (always on when communication is normal). The display screen uses a graphical interface. The device is equipped with a host computer system that stores corresponding calibration data for different components and collects test data. The graphical interface displays evaluation result cloud maps and evaluation indicators, such as... Figure 2 and Figure 3 As shown.

[0150] The measurement terminal area is equipped with six measurement terminals for connecting sensor probes, which support hot-swapping and are compatible with self-developed dual-sensor probes and general magnetic field probes. Each terminal is labeled with a number and equipped with an independent signal shielding cap to prevent interference when not in use. The terminals adopt an anti-misinsertion design, and the interface shape of different probe specifications is different to avoid damage to the probe or device caused by incorrect insertion.

[0151] The front panel is equipped with a gigabit Ethernet port, two USB 3.0 interfaces, and a Type-C interface. The Type-C interface supports bidirectional power supply and can be used as a backup power interface. At the same time, it supports data transmission and is suitable for on-site debugging of portable computers. Two power terminals are reserved, with a maximum carrying current of 50 A and a voltage of 1000 V. High-temperature-resistant ceramic interfaces are used to connect the measured crimp-type power module or sub-module. Fuse tubes are equipped beside the terminals to prevent damage to the device caused by overcurrent. Two optical fiber drive terminals 7 and two BNC interface drive signal terminals are reserved, which are compatible with the valve drive central control protocols of different manufacturers and can realize the linkage trigger test with the on-site operation and maintenance system. At the same time, a wireless trigger interface is set, which supports Bluetooth 5.2 and WiFi 6, with a transmission distance ≤ 100 m, supports remote wireless trigger, and is suitable for test scenarios in high-altitude and dangerous areas.

[0152] The front panel is also equipped with a test start / stop button, a parameter setting button, an emergency power-off button, and a test mode switching button. The test mode switching button supports three-level switching, including single discharge, single double pulse, and continuous trigger test, which can be quickly switched without entering the system menu, improving the test efficiency.

[0153] Furthermore, the device adopts a modular partition design inside, which is divided into five independent areas: a power supply area, a control area, a collection area, a power area, and a calibration area. An independent electromagnetic shielding cover is set in each area, made of copper foil material, with a shielding effectiveness ≥ 80 dB, effectively reducing the electromagnetic interference between modules and solving the test accuracy problem under medium and high-frequency working conditions. The internal wiring uses shielded cables and is routed by area to avoid signal interference. The specific structures and functions of each area are as follows.

[0154] Power supply area: Deploy a power management module, which is powered by external AC 220 V, with an input voltage range of 180 - 240 V and a frequency of 50 / 60 Hz. It includes a transformer, a rectifier filter circuit, a voltage regulator circuit, and an overcurrent / overvoltage / overheat protection circuit. A backup lithium battery module is set, which can work continuously for ≥ eight hours in case of power failure, ensuring the uninterrupted on-site test. The power module supports adaptive voltage regulation and can automatically match the supply voltage according to the specifications of the measured device, avoiding the cumbersome and error-prone manual adjustment.

[0155] Power Zone: Deploys a current generator, including a basic inductor, capacitor, diode, and charging module, and features an adaptive load adjustment unit. The current generator uses a classic dual-pulse topology: IGBT + load inductor + diode + DC-link capacitor. The IGBT is a high-performance power device, model: IGBT4 series, rated current 100A, rated voltage 1200V. The load inductor specification is 10-100μH, which is adaptively adjustable. The DC-link capacitor has a capacitance of 1000μF and a withstand voltage of 1500V. It uses metallized polypropylene capacitors for high stability. The charging module adopts a constant current and constant voltage charging mode, with an adjustable charging current of 0-5A and an adjustable charging voltage of 0-1000V, and a charging efficiency ≥90%. The adaptive load adjustment unit can automatically adjust the load inductance and capacitance parameters according to the power and model of the device under test, without the need for manual load replacement. It adapts to the testing requirements of different specifications of press-fit power modules, breaking through the limitation of existing devices that can only adapt to a single model of device.

[0156] Furthermore, the adaptive load adjustment unit adopts a modular integrated structure, which is seamlessly linked with the power area dual-pulse topology and the control area controller. The core consists of seven functional components, and the model, parameters and working mechanism of each component are as follows. The overall size is adapted to the internal space of the portable device. It is encapsulated with a copper foil electromagnetic shielding cover with a shielding effectiveness of ≥80dB to avoid electromagnetic interference with other modules.

[0157] Core control components: The STM32H743VIT6 dual-core microcontroller with a main frequency of 480MHz is used as the unit control core. It is linked with the system main controller through the SPI communication interface, receives the parameters of the device under test and adjustment commands issued by the main controller, and synchronously feeds back the current adjustment status and operating parameters of the load inductance and capacitance. The response delay is ≤5μs to ensure real-time adjustment. The built-in adjustment algorithm firmware is adapted to the AI-assisted optimization algorithm of this system. It can automatically parse the parameters of the device under test, calculate the optimal target values ​​of load inductance and capacitance, and drive the various execution components to work together.

[0158] Programmable inductor adjustment component: Employs a programmable inductor array and precision relay switching structure. The core includes six sets of high-frequency power inductors of different specifications, four high-speed electromagnetic relays, and inductor sampling resistors. The relays are driven by the core control component and automatically switch the series / parallel combination of the inductor array according to the target inductance value, achieving continuous adjustment within the range of 10-100μH with an adjustment accuracy of ±0.5μH. The inductor sampling resistors collect the inductor current signal in real time and feed it back to the core control component, forming a closed loop for inductor adjustment and avoiding adjustment deviations. The system includes six sets of high-frequency power inductors of different specifications: CDRH127-10μH, CDRH127-20μH, CDRH127-40μH, CDRH127-60μH, CDRH127-80μH, and CDRH127-100μH; four high-speed electromagnetic relays: model G6K-2P-Y, rated current 20A, withstand voltage 1500V, switching time ≤100ns; and inductor sampling resistors: model RX27-1W-0.01Ω, accuracy ±0.1%.

[0159] Programmable capacitor regulation component: It adopts a modular capacitor array and MOSFET driving structure. The core consists of four sets of metallized polypropylene capacitors, four high-voltage MOSFETs, and a capacitor voltage sampling module. The MOSFETs are driven by the core control component through the driving module. According to the target capacitance value, it automatically controls the connection / disconnection of capacitors of different specifications to achieve adaptive adjustment in the range of 400-1000μF. It is compatible with DC-link capacitor supplementary adjustment and works in conjunction with the basic capacitor in the power area. The adjustment accuracy is ±10μF. The capacitor voltage sampling module collects the voltage across the capacitor in real time and feeds it back to the core control component to avoid capacitor overvoltage damage and ensure adjustment stability. The four sets of metallized polypropylene capacitors are model numbers: CBB21-1000μF / 1500V, CBB21-800μF / 1500V, CBB21-600μF / 1500V, and CBB21-400μF / 1500V; the four high-voltage MOSFETs are model number: IRF640N, rated current 18A, withstand voltage 200V, and on-resistance ≤0.18Ω.

[0160] The drive execution component consists of two high-voltage drive chips and drive amplifier circuits, corresponding to the relay drive of the programmable inductor adjustment component and the MOSFET drive of the programmable capacitor adjustment component, respectively. The weak drive signal output from the core control component is amplified by the drive chips to reliably drive the relay and MOSFET. A built-in drive protection circuit prevents damage to the execution component due to abnormal drive signals, making it suitable for high-voltage, high-current testing scenarios. The high-voltage drive chip is model IR2110, with an output current of 2A and a withstand voltage of 500V.

[0161] The detection feedback component consists of two high-precision acquisition modules, which respectively realize the real-time detection and feedback of inductance and capacitance parameters, forming a dual closed-loop regulation with the core control component: ① Inductance detection module: using a current transformer, model: TA100-100A / 5mA, accuracy ±0.1%, it acquires the inductor circuit current, combines it with the inductor sampling resistor signal, calculates the current inductance value, detection range 10-100μH, detection frequency 1kHz-10MHz, suitable for medium and high frequency test conditions; ② Capacitance detection module: using a capacitance tester chip, model: AD7746, 24-bit resolution, it acquires the voltage across the capacitor and the charging and discharging current, calculates the current capacitance value and capacitance loss angle, detection range 400-1000μF, detection accuracy ±0.2%; the detection data is updated every 1μs and synchronously fed back to the core control component for adjustment and deviation correction.

[0162] Power supply components: A DC-DC step-down module, model: LM2596S-5.0, is used. The input voltage is 12V and the output voltage is 5V / 3A. It is powered by the power area power module with an input voltage of 12V and a ripple of ≤50mV, providing stable power to all components of the unit. It has built-in overcurrent protection, overvoltage protection and undervoltage protection circuits. When the power supply is abnormal, it will automatically cut off the power supply and feed back the abnormal signal to the core control component to avoid damage to the unit.

[0163] Linkage Interface Components: Integrating three types of interfaces to achieve seamless linkage with other modules in the system: ① SPI communication interface, for linkage with the main controller; ② Power interface, for connection with dual-pulse topology IGBTs, load inductors, and DC-link capacitors, using high-temperature resistant ceramic interfaces with a rated current of 50A and a withstand voltage of 1500V; ③ Feedback interface, for linkage with the touch screen display in the control area, transmitting load adjustment parameters in real time for easy viewing by staff; the interfaces adopt an anti-misinsertion design, matching the shape of the corresponding module interface to avoid connection errors.

[0164] Its workflow is simple and efficient, requiring no manual intervention from staff: after the main controller sends the parameters of the device under test, the core control component quickly analyzes and calculates the optimal load parameters, drives the execution component to switch the inductor / capacitor array, and the detection feedback component collects parameters in real time and forms a closed-loop correction. The entire adjustment process is ≤50μs, which can quickly adapt to the testing requirements of different specifications of press-fit power modules.

[0165] Control Area: Deploys controllers, health status prediction modules, and multi-condition adaptation modules. It is responsible for coordinating the operation of various modules of the device, signal processing, and command issuance, and realizes functions such as AI-assisted optimization, condition adaptation, health assessment, and early warning.

[0166] Acquisition Area: Deploys signal acquisition modules that work in conjunction with the front panel measurement terminals and magnetic field sensors to handle synchronous acquisition and real-time preprocessing of multiple parameters, ensuring the accuracy and consistency of the acquired data.

[0167] Calibration area: Deploys an adaptive calibration module with built-in high-precision standard current source and standard temperature source, responsible for synchronous calibration of all modules, ensuring the accuracy and traceability of test data.

[0168] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A portable method for testing the current distribution of a crimp-type power module, characterized in that, include: Perform synchronous calibration on the signal acquisition module, magnetic field sensor, current generator and data collection module, and handle calibration anomalies caused by synchronous calibration; Based on the specifications and operating conditions of the device under test, characteristic parameters of the operating conditions are extracted. These characteristic parameters include at least one of voltage level, current level, switching frequency, load rate, and case temperature / junction temperature range. Based on these characteristic parameters, multi-condition adaptive matching is performed to automatically switch simulated test conditions and optimize test parameters, while also controlling electromagnetic interference. Using a triggering mode adapted to the test conditions, current distribution and temperature data are synchronously collected through a magnetic field sensor. After preprocessing to remove invalid data, valid data is obtained. Based on the valid data, the health level assessment, graded early warning, and remaining service life prediction of the device under test are completed.

2. The portable crimp-type power module current distribution testing method according to claim 1, characterized in that... Synchronous calibration includes the following steps: Calibration mode selection: The system identifies the specifications of the device under test and the test conditions and recommends an appropriate mode; it supports automatic, remote and manual calibration. Full-module collaborative calibration: Through the built-in standard current source and temperature source, the signal acquisition module, magnetic field sensor, current generator and data collection module are calibrated simultaneously; Calibration anomaly handling: Calibration exceeding the threshold triggers an alert and provides suggestions.

3. The portable crimp-type power module current distribution testing method according to claim 1, characterized in that... Multi-condition adaptive matching includes the following steps: Automatically identify and switch to the appropriate basic test conditions, which include low-frequency conditions, medium-high frequency conditions, and high-low temperature conditions; Supports manual setting of extreme operating condition parameters; The controller automatically optimizes test parameters based on operating conditions and monitors electromagnetic interference intensity in real time. When interference exceeds the threshold, it automatically activates enhanced shielding.

4. The portable crimp-type power module current distribution testing method according to claim 1, characterized in that... The process of collecting current distribution and temperature data includes the following steps: The controller issues a trigger command, and the current generator outputs a matching dual-pulse signal; The magnetic field signal and temperature signal are collected synchronously by a magnetic field sensor, and the magnetic field signal is converted into chip-level current distribution data. The collected data is normalized, peak values ​​are extracted, invalid data is filtered out, and labels are applied.

5. The portable crimp-type power module current distribution testing method according to claim 1, characterized in that... Health level assessment, graded early warning, and remaining useful life prediction include the following steps: Encrypted data transmission and storage; Multi-dimensional data analysis: Chip-level analysis and aging assessment based on encrypted and valid data combined with intelligent algorithms and multi-dimensional databases; Health status assessment and early warning: Based on multi-dimensional analysis results, a full-chain health management system is constructed to carry out intelligent control of detection, assessment, early warning and prediction.

6. The portable crimp-type power module current distribution testing method according to claim 5, characterized in that... Multidimensional data analysis includes the following: Decrypt the encrypted data and call the reference sample; Start the fusion algorithm and configure the parameters; Calculate the core evaluation indicators, including maximum deviation rate, current dispersion, local thermal stress coefficient, current drift rate, device aging degree, and insulation performance degradation coefficient. Comparative analysis locates anomalies; Cache and feed back the analysis results.

7. The portable crimp-type power module current distribution testing method according to claim 6, characterized in that... The local thermal stress coefficient model is as follows: ； Where: k is the thermal stress correction factor; The local temperature of the region corresponding to the i-th chip; The ambient temperature of the device; Let be the magnetic field signal value of the i-th chip region. This represents the maximum range of the magnetic field signal. The current drift rate model is as follows: ； in: This represents the average current of each chip during the current test cycle. The current value of each chip in the device's brand-new state during the initial test cycle is t; t is the current test time; t0 is the initial test time. This is a calibration accuracy correction term. This is the time decay factor; This represents the current drift rate.

8. The portable crimp-type power module current distribution testing method according to claim 5, characterized in that... Health status assessment and early warning include the following: Health level assessment is a comprehensive evaluation of the health status of the device under test. Visual display of health status; Based on the health level assessment results, the system automatically triggers the corresponding level-based warning; By combining the full lifecycle data of the device under test, the remaining service life of the device is predicted through a fusion algorithm, and targeted maintenance suggestions are generated based on the anomaly identification results. Transmission of early warning information and maintenance recommendations.

9. The portable crimp-type power module current distribution testing method according to claim 1, characterized in that... The steps involved in attaching the magnetic field sensor probe to the device under test and reliably connecting it are as follows: Select a suitable flexible probe that fits seamlessly to the device surface and reliably docks; The system starts up and adaptively switches power supply modes; Input the basic parameters of the device and complete the system parameter initialization.

10. A power module current distribution testing system employing the portable crimp-type power module current distribution testing method according to any one of claims 1-9, comprising: The device comprises a detection unit, a data collection module, a power management module, a current generator, a signal acquisition module, a data encryption transmission module, a magnetic field sensor, an adaptive calibration module, a lifecycle management module, an electromagnetic shielding module, a health status prediction module, a controller, and a multi-condition adaptation module, characterized in that: Testing device: adopts a portable and modular design; Data collection module: Enables full-dimensional data collection and traceability; Power management module: Ensures stable power supply to the foundation; Current generator: integrates intelligent load regulation unit and topology reconfiguration module, automatically matching load parameters according to the rated current, rated voltage and package specifications of the pressure-connected power module under test; Signal acquisition module: configured with multiple independent acquisition channels; Adaptive calibration module: Built-in standard current source and standard temperature source, automatically identify calibration requirements and adjust calibration parameters according to the specifications of the device under test and the test conditions; Multi-condition adaptation module: Based on the actual working conditions of the device under test, it automatically identifies the device specifications and test requirements, switches test modes, and adaptively adjusts the acquisition parameters, trigger parameters, and load parameters. Health status prediction module: Construct a full-link health management system of detection-assessment-early warning-prediction, integrate multi-dimensional indicators and intelligent algorithms to achieve full life cycle health management of the device under test; Lifecycle Management Module: Constructs a full lifecycle data management system for the device under test (DUT) and creates a unique full lifecycle profile for each DUT.

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