A high and low temperature intelligent start-stop test method for a solid state disk

Abstract

The application relates to the technical field of data storage, and discloses a high-low temperature intelligent start-stop test method for a solid state disk, which comprises the following steps: obtaining a to-be-tested solid state disk, and pretreating the to-be-tested solid state disk; performing high-temperature start test on the pretreated to-be-tested solid state disk, and obtaining the high-temperature start performance of the to-be-tested solid state disk according to a test result; performing low-temperature start test on the pretreated to-be-tested solid state disk, and obtaining the low-temperature start performance of the to-be-tested solid state disk according to a test result; setting a temperature cycle curve in a temperature box based on the high-temperature start performance and the low-temperature start performance, performing high-low temperature cycle start-stop test on the pretreated to-be-tested solid state disk based on the temperature cycle curve, and monitoring and recording current change waveforms of each high-low temperature cycle start-stop test. The application comprehensively simulates actual use scenes of users in extreme environments, and improves the accuracy and reliability of test results.

Description

Technical Field

[0001] This invention relates to the field of data storage technology, and in particular to a high and low temperature intelligent start-stop test method for solid-state drives. Background Technology

[0002] With the rapid development of information technology and the explosive growth of data volume, solid-state drives (SSDs) have gained widespread attention as a mainstream enterprise-level data storage medium. SSDs offer advantages such as light weight, small size, high transfer speeds, and high capacity density, representing a significant improvement over traditional hard disk drives (HDDs). However, despite the abundance of SSDs available on the market, the corresponding debugging and testing methods remain relatively primitive and simplistic, primarily relying on manual operation. This not only leads to low testing efficiency, low reliability, and high security risks, but may also affect the accuracy of test results.

[0003] Currently, when conducting performance tests on solid-state drives (SSDs), performance is typically judged based on existing standard parameters or the results of similar products. While this method can determine performance to some extent, it cannot verify the reliability of SSD testing methods. Furthermore, existing SSD performance testing equipment is not suitable for performing performance tests on SSDs under various conditions, and it is difficult to detect and locate anomalies during the performance testing process. Summary of the Invention

[0004] This invention provides a high and low temperature intelligent start-stop test method for solid-state drives (SSDs), which can solve the technical problems of existing SSD performance testing devices, which are not convenient for performing performance tests on SSDs under various conditions and are difficult to detect and locate abnormal phenomena during the performance testing process.

[0005] To solve the above-mentioned technical problems, one technical solution adopted by the present invention is: to provide a high and low temperature intelligent start-stop test method for solid-state drives, the method comprising:

[0006] Acquire the solid-state drive to be tested and preprocess it.

[0007] The pre-processed solid-state drive under test was subjected to a high-temperature boot test, and the high-temperature boot performance of the solid-state drive under test was evaluated based on the test results.

[0008] The pre-processed solid-state drive under test was subjected to a low-temperature boot test, and the low-temperature boot performance of the solid-state drive under test was evaluated based on the test results.

[0009] Based on the high-temperature start-up performance and low-temperature start-up performance, a temperature cycle curve is set in the temperature chamber. Based on the temperature cycle curve, a high-low temperature cycle start-up and stop test is performed on the processed solid-state drive under test. The current change waveform of each high-low temperature cycle start-up and stop test is monitored and recorded.

[0010] It automatically records the test data generated in each test and generates a comprehensive report that includes test curves, pass / fail statistics, and trend analysis.

[0011] The beneficial effects of this invention are as follows: By introducing innovative elements such as multi-role simulation, temperature gradient and shock, dynamic load pressure, performance baseline comparison, and fault pre-diagnosis, it comprehensively simulates actual user scenarios under extreme environments, overcoming the inefficiency and low reliability caused by the reliance on manual operation in traditional testing methods, and improving the accuracy and reliability of test results; It adopts a temperature curve extension mechanism, including three stages: gradient temperature rise, thermal shock start-up, and extreme temperature start-up, which can comprehensively evaluate the performance of SSDs under different temperature environments, effectively solving the problem of difficulty in performing performance testing of solid-state drives under various conditions in existing technologies; Through the design of role A (system disk) and role B (data disk + load), combined with different... The occupancy rate test comprehensively evaluated the boot performance and reliability of SSDs under different usage scenarios, overcoming the shortcomings of existing technologies that lack role simulation and load stress assessment mechanisms for SSDs under different temperature environments. Based on performance recording and baseline comparison mechanisms, the test established a corresponding connection between performance index data and labels and models by accurately recording and analyzing BIOS / POST self-test time and operating system loading time, simplifying the testing steps and improving testing efficiency. Through the construction of an automated testing platform and data collection, intelligent analysis and early warning mechanisms, the test process was monitored in real time and anomalies were detected in real time, effectively solving the problem of lack of real-time monitoring and intelligent analysis capabilities for test data in existing technologies. Attached Figure Description

[0012] Figure 1 This is a flowchart illustrating the high and low temperature intelligent start-stop test method for solid-state drives according to the first embodiment of the present invention.

[0013] Figure 2 yes Figure 1 A flowchart illustrating step 2.

[0014] Figure 3 yes Figure 1 A flowchart illustrating step 3.

[0015] Figure 4 yes Figure 1 A flowchart illustrating step 4.

[0016] Figure 5 yes Figure 1A flowchart illustrating step 5. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0018] The terms "first," "second," and "third" used in this invention are for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified. All directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of this invention are only used to explain the relative positional relationships and movements between components in a specific orientation (as shown in the figures). If the specific orientation changes, the directional indications also change accordingly. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0019] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0020] Figure 1 This is a flowchart illustrating the high and low temperature intelligent start-stop test method for solid-state drives according to the first embodiment of the present invention. Figure 1 As shown, the system includes hardware and software components:

[0021] Step 1: Obtain the solid-state drive to be tested and preprocess it;

[0022] Step 2: Perform a high-temperature boot test on the pre-processed solid-state drive to be tested, and evaluate the high-temperature boot performance of the solid-state drive to be tested based on the test results;

[0023] Step 3: Perform a low-temperature boot test on the pre-processed solid-state drive to be tested, and evaluate the low-temperature boot performance of the solid-state drive to be tested based on the test results.

[0024] Step 4: Set the temperature cycle curve in the chamber based on the high temperature start-up performance and the low temperature start-up performance. Perform high and low temperature cycle start-up and stop tests on the processed solid-state drive under test based on the temperature cycle curve. Monitor and record the current change waveform of each high and low temperature cycle start-up and stop test.

[0025] Step 5: Automatically record the test data generated for each test, and generate a comprehensive report containing test curves, pass / fail statistics, and trend analysis.

[0026] Step 1 involves the following preprocessing steps for the SSD under test: Select the SSD and record its test number and model. For example, the test number is SSD001, and the model is SAMSUNG 860 EVO 1TB. Perform a secure erase on the SSD to ensure it is in the same initial state. Use the SSD's secure erase function to remove all data and encrypted information. Select a portion of the samples for aging preprocessing to simulate lightly used platters. Perform 30 cycles of testing on 10% of the samples, with each cycle involving writing 10GB of data and randomly reading 10GB of data. Immediately after performing a secure erase on all platters, test them at room temperature (25°C) to establish an "initial performance baseline." Then, age another 10% of the samples to simulate wear and tear. The test results of the aged samples can be compared with their own "initial performance baseline" before aging, or with the "initial performance baseline" of a new, unaged disk, to assess the impact of aging.

[0027] The impact of aging on SSD performance was assessed through secure erasure, pre-aging, and cyclic read / write tests, combined with baseline comparison. All SSDs underwent secure erasure to remove all data and encryption information, ensuring a consistent initial state. Immediately after secure erasure, they were tested at 25°C to establish an "initial performance baseline," which served as a benchmark for subsequent comparisons. A portion of the samples underwent pre-aging to simulate wear and tear after light use. 10% of the samples were then subjected to 30 cyclic tests, each cycle including 10GB of data write and 10GB of random read operations. The aged samples were compared to their pre-aging "initial performance baseline" to observe changes in single-disk performance.

[0028] Figure 2 yes Figure 1 The flowchart for step 2 is as follows: Figure 2As shown, step 2 includes: step 201, placing the pre-processed solid-state drive under test in a high-temperature test environment and performing a high-temperature curve extension test to obtain high-temperature curve extension test data; step 202, performing role simulation and load stress loading tests on the pre-processed solid-state drive under test to obtain role simulation test data and load stress loading test data; step 203, evaluating high-temperature startup performance based on the high-temperature curve extension test data, role simulation test data, and load stress loading test data and performing high-temperature baseline comparison; step 204, performing fault pre-diagnosis.

[0029] The pre-processed high-temperature performance testing and troubleshooting process for the SSD under test involves collecting data through multi-dimensional testing, and then evaluating and comparing the data to determine high-temperature performance and pre-diagnose potential faults. Step 201: High-Temperature Curve Expansion Testing. The pre-processed SSD is placed in a high-temperature testing environment, and a high-temperature curve expansion test is conducted. By acquiring curve expansion test data related to temperature changes under high-temperature conditions, the basic performance fluctuations that may occur with temperature changes in the SSD are captured. Step 202: Role Simulation and Load Stress Testing. Two key tests are simultaneously conducted on the pre-processed SSD: a role simulation test to simulate different roles the SSD might play in real-world applications (e.g., as a system drive, data storage drive); and a load stress test to simulate high-load operation by applying a certain workload. The relevant data for these two tests are then acquired to reflect the SSD's operating status under different application roles and loads. Step 203: High-Temperature Performance Assessment and Baseline Comparison. This step involves data processing and performance analysis. It integrates the high-temperature curve extension test data obtained in Step 201, as well as the role simulation test data and load stress test data acquired in Step 202. Based on this comprehensive data, the high-temperature startup performance of the SSD is evaluated. Simultaneously, these test results are compared with a preset high-temperature performance baseline to determine whether the SSD's high-temperature performance meets the standard and the degree of difference from the benchmark. Step 204: Fault Pre-diagnosis. Combining the various data and performance assessment results collected in the previous three steps, fault pre-diagnosis is performed on the SSD. The purpose is to identify potential faults that may exist in the SSD under high-temperature environments, different application roles, and load stresses, providing a basis for subsequent quality optimization or problem rectification.

[0030] Specifically, step 201 includes: Step 2011, execution phase one (gradient heating): placing the pre-treated solid-state drive under test in a temperature chamber, adjusting the temperature to slowly increase from room temperature (25℃) to a preset high temperature at a rate of 1℃ / minute, and holding at the temperature for a preset time; Step 2012, execution phase two (thermal shock start): performing a preset number of starts under the preset high temperature environment, and setting the dynamic change interval time for each start; Step 2013, execution phase three (extreme temperature start): raising the temperature to the maximum operating temperature specified in the datasheet of the pre-treated solid-state drive under test, and performing one start test.

[0031] Step 2011: Gradient Temperature Increase – Adapting the SSD to a High-Temperature Environment. The core of the initial testing phase is simulating a scenario of slowly increasing temperature. The pre-treated SSD is placed in a temperature chamber, and the chamber temperature is gradually increased from a room temperature of 25°C at a rate of 1°C per minute to a pre-set high temperature. Once the preset high temperature is reached, it is maintained for a predetermined period to allow the SSD to fully adapt to the high-temperature environment, preventing data distortion due to sudden temperature changes in subsequent tests and establishing a stable environmental foundation for subsequent high-temperature boot tests. Step 2012: Thermal Shock Boot – Testing Stability During Repeated Boots at High Temperatures. This phase focuses on the performance of the SSD during repeated boots under high-temperature conditions. The preset high-temperature environment achieved in Step 2011 is maintained throughout the test. The SSD is then subjected to a predetermined number of boot operations. Simultaneously, a dynamic interval (not a fixed interval) is set between each boot to simulate irregular boot scenarios that may occur in real-world use, thereby obtaining stability data of the SSD under sustained high temperatures during repeated boots. Step 2013: Extreme Temperature Startup, verifying high-temperature tolerance. The chamber temperature is further increased until it reaches the maximum operating temperature specified in the SSD's datasheet. In this extreme environment, approaching or reaching the product's upper operating temperature limit, only one startup test is performed. The core purpose of this test is to verify whether the SSD can successfully start under the maximum temperature limit allowed by its specifications, thereby confirming its critical tolerance for high-temperature startup.

[0032] Specifically, step 202 includes: step 2021, configuring role A (system disk) and installing the operating system on the pre-processed solid-state drive under test as the only hard drive and then performing a boot test; step 2022, using the pre-processed solid-state drive under test as a slave disk and pre-setting load files with different occupancy rates on it before performing a boot test; step 2023, running a lightweight continuous read script on the slave disk to verify whether it can immediately withstand I / O pressure after boot.

[0033] Step 2021: Simulate the system disk role and test core boot performance. First, set the pre-processed SSD under test as the only hard drive in the device, and then install the operating system on this hard drive to complete the configuration of "Role A (system disk)". Then, conduct boot tests. The core purpose is to verify the boot-related performance of the SSD as a system disk, such as boot speed and the stability of data loading during boot—after all, the system disk is the core of device boot and operation, and its boot performance directly affects the overall user experience. Step 2022: Simulate the slave disk role and test boot performance under different loads. This step shifts to the scenario of the SSD being used as auxiliary storage. Configure the pre-processed SSD under test as a slave disk (not a system disk, only used for auxiliary data storage), and pre-load different load files with different occupancy rates (e.g., some disk space occupied by 30%, some by 70%, etc.). After completing these preparations, conduct boot tests, focusing on exploring the impact of different data occupancy on the slave disk's boot state, determining whether the slave disk can cooperate with the whole system to boot normally under different storage loads, and avoiding boot anomalies due to load differences. Step 2023: Test the slave disk's ability to withstand immediate I / O pressure after booting. This step is a supplementary test to the basic operational capabilities of the slave disk after booting. The test object is still the slave disk configured in step 2022. After booting, immediately run a lightweight continuous read script on the disk. In this way, we can verify whether the slave disk can immediately withstand input / output (I / O) pressure when it has just finished booting and has not yet entered a long-term stable operating state. This verifies the slave disk's immediate response capability after booting and ensures that it can quickly start data reading and other tasks after booting in actual use.

[0034] Specifically, step 203 includes: step 2031, recording the BIOS / POST self-test time and operating system loading time during each startup process in the high-temperature startup test; step 2032, comparing the high-temperature startup time under high temperature with the baseline startup time under room temperature (25℃); step 2033, establishing high-temperature performance index data based on a preset percentage of the high-temperature startup time delay not exceeding the baseline startup time.

[0035] Step 2031: Record core time data during high-temperature startup, focusing on key time nodes in the high-temperature startup test. During testing, two core data points must be accurately recorded for each SSD startup process: 1) BIOS / POST self-test time (this is the hardware-level self-test phase after the computer powers on, reflecting the initial startup state of SSD and hardware compatibility); 2) Operating system loading time (i.e., the time from the completion of the hardware self-test to the successful loading and readiness of the operating system, directly related to the user's perceived startup progress). These two data points together constitute the core foundational data for evaluating startup performance under high temperatures. Time acquisition methods: "Startup current data is collected using a high-precision current sensor connected to the SSD power supply circuit and uploaded to the control computer via a data acquisition card." "Precise timestamps from power-on to the appearance of the BIOS interface and then to the appearance of the operating system login interface are automatically captured and recorded by embedding a custom script in the host BIOS or using an external hardware timer." "Analysis software on the control computer (such as software developed based on Python or LabVIEW) extracts features (such as peak value, rise time, and integral area) from the collected current waveform and compares and analyzes them with baseline waveform features."

[0036] Step 2032: Baseline comparison of high-temperature and room-temperature boot times to identify differences. Compare the total boot time recorded in Step 2031 under high-temperature conditions (summarized from BIOS / POST self-test time and operating system loading time) with the baseline boot time established previously at 25°C room temperature. This comparison visually shows whether high temperatures slow down SSD booting and the initial differences in speed. Step 2033: Establish quantifiable high-temperature boot performance metrics, setting a core rule: if the SSD boot time latency under high-temperature conditions (compared to the room-temperature baseline boot time) does not exceed a preset percentage (e.g., preset latency not exceeding 10%), then establish corresponding high-temperature performance metric data based on this. This metric is the core standard for quantifying whether SSD high-temperature boot performance meets the requirements. It can be used to quickly determine whether the SSD's boot performance in high-temperature scenarios meets the requirements.

[0037] Step 204 includes: Step 2041, analyzing the trend changes of the starting current waveform and starting time; Step 2042, if a certain parameter (such as starting time) shows a significant linear deterioration trend, the system issues an early warning.

[0038] Step 2041: Analyze the trends of core startup-related parameters. During the test, focus on collecting and analyzing two key pieces of information: first, the startup current waveform, which reflects the changes in the power supply current during SSD startup. Abnormal current fluctuations are often related to abnormalities in the internal hardware circuitry and chip operation of the SSD; second, the trend of startup time, which can be related to the BIOS / POST self-test time and operating system loading time mentioned earlier. By continuously tracking the changes in these two types of data, rather than just looking at single data points, a basis for subsequent fault diagnosis is provided. Step 2042: Trigger warnings based on parameter deterioration trends. Clear warning trigger conditions are set. When the analysis reveals a significant linear deterioration trend in a certain type of key parameter (for example, startup time increases with each test, exhibiting a stable and continuously lengthening linear change), it means that the SSD may have potential fault hazards (such as accelerated aging of internal components, abnormal firmware operation, etc.). At this time, the test system will automatically issue a warning so that staff can intervene in time to investigate the problem and prevent the hidden danger from developing into an actual failure.

[0039] The specific analysis is achieved through a closed-loop process of data acquisition, trend modeling, and anomaly detection. The specific steps are as follows: Step 1: Thorough data acquisition and preprocessing are crucial for reliable analysis. This step involves three key tasks: data acquisition, sample accumulation, and invalid data removal. When acquiring the startup current waveform, an oscilloscope or dedicated power supply monitoring equipment should be connected to the SSD power supply circuit. The sampling rate should be set between 1MHz and 10MHz to accurately capture instantaneous fluctuations. Record the complete current change curve from SSD power-on to operating system loading, while simultaneously marking the time axis. When acquiring startup time data, record the BIOS / POST self-test time and operating system loading time for each startup according to previous standards and summarize them into a total startup time. Also, note the corresponding test environment, such as the specific stage and temperature value of the high-temperature test. Accumulate at least 10-30 sets of continuous test data, including the results of 30 cycle tests and multiple high-temperature startup tests mentioned earlier. Insufficient sample size makes it difficult to reflect the true trend and easily leads to misjudging occasional data fluctuations as anomalies. Preprocessing to remove invalid data: Verify the collected data against the corresponding test conditions. If there are data points that clearly indicate test errors, such as a sudden increase in startup time due to loose wiring or discontinuous current waveforms, these should be removed promptly to avoid interfering with subsequent trend analysis. Second step: In-depth analysis across dimensions: Deconstruct the startup current waveform and startup time trend. A detailed analysis of both the startup current waveform and startup time trend is necessary to pinpoint potential problems through characteristic changes in different dimensions. Startup current waveform analysis: First, observe the peak current and duration. Compare the magnitude of the peak current and the duration it lasts during each startup. If the peak current gradually increases, it may indicate aging of the SSD's internal power components, leading to a greater power load. If the peak duration continuously lengthens, it is highly likely that the chip's initialization efficiency has decreased. Second, observe the waveform smoothness. A normal current curve should have no abrupt spikes or large drops. Frequent spikes may indicate poor circuit contact or capacitor degradation. A sudden drop in current to near zero should raise suspicion of a power supply circuit failure, posing a risk of startup interruption. Third, analyze the current differences across startup stages. Divide the waveform into segments according to the startup process: power-on, BIOS self-test, and system loading. If a segment has an abnormally high and persistent current, it indicates a potential problem with hardware compatibility or firmware operation in that stage.Startup Time Trend Analysis: First, arrange the cumulative startup times in the order of testing, and label the environmental conditions corresponding to each test. Then, use tools such as Excel and MATLAB to perform linear regression analysis on these data to fit a curve showing the change in startup time with the number of tests or the degree of aging. Finally, judge the trend of the curve. If the slope of the fitted curve is positive and the absolute value is large, it indicates that the startup time is continuously increasing. For example, if the startup time gradually increases from 20 seconds to 35 seconds in 30 tests, and the increase is relatively uniform each time, it is a typical trend of continuous deterioration. If the slope is close to 0, it indicates that the startup time remains stable. Step 3: Define quantitative standards and accurately trigger fault warnings. Set clear quantitative rules to determine whether to trigger a warning. This can be done in three ways. Set trend judgment thresholds: Calculate the rate of change of startup time through linear regression and formulate clear standards, such as "in 10 consecutive tests, the startup time increases by ≥2% each time", or "the slope of the fitted line of startup time in 30 tests is ≥0.5 seconds / test". As long as these conditions are met, it can be judged that the startup time shows a clear linear deterioration trend. Secondary verification using parameter thresholds: In addition to trend standards, specific numerical thresholds can be used to assist in judgment. For example, if the high-temperature start-up delay is previously set to not exceed 15% of the room temperature baseline, and the linear deterioration trend of the start-up time has brought it close to or is about to exceed this threshold, an early warning can be triggered even if the preset number of tests has not been completed. Automatic system feedback warnings: When any of the above warning conditions are met, the testing system will issue a warning through pop-up prompts, alarm sounds, or special log markers, while simultaneously recording the number of tests triggered and specific parameter values, providing clear evidence for subsequent staff to trace the cause of the fault and troubleshoot the problem.

[0040] In this embodiment, step 201 involves placing the SSD in a high-temperature testing environment and performing temperature curve extension. The SSD is placed in a temperature-controlled high-temperature testing chamber, and the temperature curve is set as follows: room temperature (25°C) → temperature rises to 70°C at a rate of 1°C / minute → temperature is maintained at 70°C for 1 hour → temperature is rapidly reduced from 70°C to room temperature.

[0041] Step 202: Perform role simulation and load testing: Configure Role A (system disk) and install the operating system. Install the Windows 10 operating system on the SSD and configure it as the system disk. Configure Role B (data disk + load test). Before startup, pre-store a large number of small and large files into the SSD. Use a random file generator to generate 1 million random small files of 4KB each, occupying 30% of the space; generate 10 random large files of 1GB each, occupying 70% of the space; generate a random super-large file of 5GB each, occupying 95% of the space. In Role B, run a lightweight continuous read script. Write a script using Python to execute immediately after startup, simulating read operations: read all filenames from the root directory of the SSD, read the size of each file one by one, until the total read size reaches 10GB.

[0042] Step 203: Evaluate boot performance and perform baseline comparison: Record the BIOS / POST self-test time and operating system loading time during each boot process. Use a high-precision timer to record the timestamp of each boot. Compare the boot time under high temperature with the baseline boot time under room temperature (25℃). Use the boot time under room temperature as the baseline, requiring that the boot time delay under high temperature does not exceed 20% of the baseline time. Establish the correspondence between performance index data and labels and models. Store the performance index of each SSD in the database and establish the mapping relationship between SSD label, model and performance index.

[0043] Step 204: Perform fault pre-diagnosis: Analyze the trend changes of the startup current waveform and startup time. Use a current sensor to monitor the current consumption during startup in real time, and analyze the stability and peak value changes of the current waveform. If a parameter (such as startup time) shows a significant linear deterioration trend, the system issues an early warning. Abnormal trends are identified through data analysis algorithms, and early warning prompts are issued.

[0044] Figure 3 yes Figure 1 The flowchart for step 3 is as follows: Figure 3 As shown, step 3 includes: step 301, placing the pre-processed solid-state drive under test in a low-temperature test environment and performing a low-temperature curve extension test to obtain low-temperature curve extension test data; step 302, performing role simulation and load stress loading tests on the pre-processed solid-state drive under test to obtain role simulation test data and load stress loading test data; step 303, evaluating low-temperature startup performance based on the low-temperature curve extension test data, role simulation test data, and load stress loading test data and performing low-temperature baseline comparison; step 304, performing fault pre-diagnosis.

[0045] Specifically, step 301: Low-temperature curve expansion test. First, the pre-processed SSD under test is placed in a low-temperature test environment, followed by a low-temperature temperature curve expansion test. The core of this test is to capture data on how the SSD's performance changes with temperature in a low-temperature environment. After all, low temperatures easily affect the working state of the SSD's internal components and firmware; collecting this data provides initial evidence for subsequently judging the fundamental impact of low temperatures on the SSD. Step 302: Role simulation and load stress test. Also for the pre-processed SSD under test, two key tests are performed simultaneously. One is the role simulation test, simulating different roles it might play in actual use, such as a system disk running the system, or a slave disk only storing data; the other is the load stress test, simulating the SSD's high-load operation by applying corresponding workloads. Finally, data from these two tests are collected to understand the SSD's performance under different application scenarios and load intensities at low temperatures. Step 303: Low-Temperature Performance Assessment and Low-Temperature Baseline Comparison. This step combines the low-temperature temperature curve extension test data obtained in Step 301 with the role simulation and load stress test data from Step 302. Based on this comprehensive data, the low-temperature boot performance of the SSD is evaluated. Simultaneously, these test results are compared with a preset low-temperature performance baseline to clearly determine whether the SSD's low-temperature boot performance meets the standard and how much it differs from the benchmark. Step 304: Fault Pre-diagnosis in Low-Temperature Scenarios. Combining the various test data collected in the previous three steps with the low-temperature boot performance assessment results, fault pre-diagnosis is performed on the SSD. The purpose is to identify potential hidden faults in the SSD under low-temperature environments, different application roles, and load stresses, such as abnormal boot delays caused by low temperatures and stability issues during load operation, providing direction for subsequent targeted optimization of the product's low-temperature adaptability.

[0046] Step 301 includes: Step 3011, Execution Phase 1 (Deep Freezing): The pre-treated solid-state drive under test is stored in a preset low-temperature environment for a preset time to ensure that the chip is completely cooled; Step 3012, Execution Phase 2 (Low-Temperature Startup): The cooled solid-state drive under test is quickly transferred to a 0°C environment and immediately executed a preset number of startups; Step 3013, Execution Phase 3 (Startup with Temperature Rise): After startup at 0°C, the solid-state drive under test is kept powered on, and the operational stability of the solid-state drive under test is monitored as the internal temperature of the solid-state drive under test naturally rises to room temperature.

[0047] Step 3011: Deep Freezing, ensuring the SSD is fully adapted to low-temperature conditions, simulating the scenario of the SSD being in a low-temperature environment for an extended period. The pre-treated SSD under test is placed in an environment with a preset low temperature and stored at this temperature for a predetermined duration. This is to ensure the SSD, especially its internal core chips, is completely cooled and stabilized at this low temperature, preventing data distortion due to chip temperatures not reaching the target low temperature in subsequent tests, thus laying a solid environmental foundation for subsequent low-temperature boot tests. Step 3012: Low-Temperature Boot, testing boot reliability under sudden temperature changes. The deep-frozen SSD is quickly transferred to a 0°C environment and immediately subjected to a preset number of boot operations. This test simulates the scenario in real-world use where an SSD urgently needs to boot after suddenly moving from a cold environment to a relatively mild near-freezing environment. The core purpose is to verify whether the SSD can successfully complete multiple boots under the impact of sudden temperature changes, avoiding boot failures and boot stutters caused by low temperatures. Step 3013: Booting with Temperature Rise, monitoring operational stability during temperature recovery. After booting in the 0°C environment, the SSD is kept continuously powered on. Afterward, no further adjustment of the ambient temperature was made. Instead, the stability of the SSD's operation was monitored throughout the process of its internal temperature naturally rising to room temperature. The core purpose of this test was to verify whether the SSD's performance would fluctuate and whether data transmission would be normal as the temperature gradually increased, thereby identifying potential operational anomalies during the transition from low temperature to room temperature.

[0048] Step 302 includes: Step 3021, after the low-temperature start-up test, acquiring visual images of the interface and PCB board of the solid-state drive under test, and checking whether there are signs of condensation or corrosion on the interface and PCB board of the solid-state drive under test based on the visual images, and recording the visual image inspection results; Step 3022, recording the time required from low-temperature start-up to performance recovery to the room temperature reference level.

[0049] Step 3021: Visually inspect the interface and PCB board to identify potential hardware appearance issues caused by low temperature. After completing the low-temperature boot test, first acquire visual images of the SSD interface (the port used to connect the device) and the PCB board (the core circuit board carrying the internal electronic components). Then, compare these images and focus on checking two key potential issues: first, whether there are signs of condensation, because when the SSD is in a low-temperature state and comes into contact with a relatively high-temperature environment, moisture in the air can easily condense on the hardware surface, which may cause a short circuit; second, whether there are signs of corrosion, because if condensation remains for a long time, it may cause slight corrosion of the hardware, affecting the normal conduction of the circuit. Finally, record the results of this visual inspection in detail, such as whether there are any potential issues and the specific location of the issues, to provide a basis for hardware reliability assessment. Step 3022: Record the time taken for performance to recover to the room temperature baseline to assess the performance rebound capability after low temperature. During the test, a key duration needs to be accurately recorded—the time taken from the time the SSD completes the low-temperature boot until its various performance indicators (such as read and write speeds, boot response speeds, etc.) recover to the preset performance baseline level at room temperature (25℃). This data can intuitively reflect the performance rebound ability of SSDs after being affected by low temperature. If the recovery time is too long, it means that in actual use, after switching from a low temperature environment to a normal temperature environment, users may need to wait for a long time before they can use the SSD normally. Conversely, it indicates that its adaptability after low temperature is better.

[0050] Figure 4 yes Figure 1 The flowchart for step 4 is as follows: Figure 4 As shown, step 4 includes: step 401, setting the temperature cycle curve in the chamber based on the high temperature start-up performance and the low temperature start-up performance, and cyclically testing the solid-state drive under test within the temperature cycle curve range; step 402, determining the highest and lowest temperatures for each cycle, and performing one start-up test at each of the highest and lowest temperatures; step 403, monitoring and recording the current change waveform of each high and low temperature cycle start-up and stop test, and observing whether there are abnormal current peaks in the current change waveform.

[0051] Step 401: Develop a temperature cycling curve and conduct cycle tests. First, integrate the results of previous high-temperature and low-temperature startup performance tests to set the temperature cycling curve within the chamber. This curve will clearly show the pattern of temperature alternation, such as the heating rate, cooling rate, and duration of high and low temperature changes. Then, place the SSD under test in the chamber and conduct continuous cycle tests within the temperature range corresponding to the set temperature cycling curve to simulate the SSD's repeated exposure to high and low temperatures in real-world usage. Step 402: Fix the extreme temperature of the cycle and perform start-stop tests. During each complete temperature cycle, first identify the highest and lowest extreme temperatures of the cycle. Then, perform one startup test on each SSD at each of these extreme temperatures. The core purpose of this operation is to accurately verify whether the SSD can start successfully when the temperature reaches the upper and lower limits of the cycle, avoiding startup failures due to excessively high or low temperatures. Step 403: Monitor and record the current waveform to identify potential current anomalies. During each high and low temperature cycle start-up and shutdown test, continuously monitor and record the current changes during SSD startup and shutdown. Then, focus on observing the recorded waveforms to determine if any abnormal current peaks are present. Abnormal current peaks are often related to SSD internal circuit failures, component aging, power supply mismatch issues, etc. This monitoring can proactively identify these hardware-level problems, providing crucial data support for subsequent fault analysis.

[0052] Figure 5 yes Figure 1 The flowchart for step 5 is as follows: Figure 5 As shown, step 5 includes: step 501, using the Python / TestStand language tool to write an automated running script for the high and low temperature cycle start-stop test, and running the high and low temperature cycle start-stop test according to the automated running script; step 502, automatically recording the test data generated by each high and low temperature cycle start-stop test, wherein the test data includes at least temperature, start-up time, start-up current, success status, and performance data; step 503, generating a comprehensive report from the test data that includes test curves, pass / fail statistics, and trend analysis.

[0053] Step 501: Write an automated script to drive the automatic testing. Staff need to use languages ​​and tools like Python or TestStand, adapted to the testing scenario, to write an automated script for the high and low temperature cycle start-up and shutdown test. The script will pre-set the core logic of the test, such as the parameters of the temperature cycle of the incubator, the frequency of SSD startup tests, and the sequence of test procedures. After writing the script, the high and low temperature cycle start-up and shutdown test will be started according to this script, eliminating the need for repeated manual intervention. This reduces human error and significantly improves testing efficiency and consistency. Step 502: Automatically collect and record multi-dimensional test data. During the script-driven test execution, the system will automatically and synchronously record various key data generated by each high and low temperature cycle start-up and shutdown test, clearly defining the coverage of core data. This includes environmental and hardware-related temperatures, startup current; startup time and startup success status reflecting the startup status; and performance data reflecting operational capabilities. This automatically recorded data is comprehensive and accurate, providing complete and reliable raw data for subsequent test analysis. Generate a multi-dimensional comprehensive test report. The system will integrate and process all collected test data and generate a comprehensive report. This report goes beyond simply listing data; it includes three core components: test curves that visually represent data changes, pass / fail statistics that clearly indicate test results, and trend analysis that reveals patterns in data changes. This report allows staff to quickly grasp the overall performance of SSDs in high and low temperature cycle start-stop tests, providing an intuitive and comprehensive reference for evaluating SSD performance and troubleshooting potential problems.

[0054] Based on the first embodiment, a second embodiment is proposed. In the second embodiment, a consumer-grade SSD test example is provided. The test object is labeled SSD001 and model number SAMSUNG 860 EVO 1TB SATA SSD.

[0055] 1. Preprocessing and Performance Baseline Establishment: The SSD under test (SSD001) is installed in a dedicated test fixture and connected to the automated test host via a SATA interface. The system automatically records its unique identifier, model, firmware version, and production batch information. An automated security erase is performed. The test host ensures the SSD is restored to its factory initial state by sending an ATA Security Erase Unit command, making all physical blocks writable. Initial performance testing is conducted under baseline environmental conditions (25°C ± 1°C, normal pressure, relative humidity 45%-55%) to establish the SSD's performance baseline.

[0056] The test host control program simulated three cold starts (complete power off and then power on) and automatically recorded the following data:

[0057] Boot time: Captured using a high-precision hardware timer integrated on the motherboard, from the moment the power-on signal (PWR_ON) is applied to the motherboard until the operating system login screen is fully loaded (T_total_base). This time can be further broken down into BIOS / POST self-test time (T_bios_base) and operating system loading time (T_os_base).

[0058] Startup current waveform: The current data of the entire startup process is collected by using a Keysight PXIe-4082 high-precision digital multimeter (sampling rate 1MSa / s) connected in series in the SSD power supply circuit, and its characteristic values, such as peak current (I_peak_base), average current (I_avg_base) and current rise slope, are calculated.

[0059] All baseline data (T_total_base, T_bios_base, T_os_base, I_peak_base, I_avg_base) are bound to the SSD's label and model number and stored in the central test database.

[0060] 2. High-temperature start-up test. First, in the temperature profile extension:

[0061] Phase 1 (Gradual Temperature Increase): The test fixture with the SSD installed is moved into the ESPEC PH-201 temperature chamber. The temperature chamber is controlled by the LabVIEW program on the test host, increasing the temperature from 25°C to 70°C at a rate of 1°C / minute, and holding at 70°C for 60 minutes to ensure uniform and stable temperature of the internal chips of the SSD.

[0062] Phase Two (Thermal Shock Start-up): After the thermal insulation period ends, the test host immediately controls the Chroma 63213A DC power supply to cycle power to the host motherboard and SSD: 3 minutes of complete power off -> power on -> data recording -> 5 minutes of complete power off -> power on -> data recording -> 10 minutes of complete power off -> power on -> data recording.

[0063] The startup was executed a total of 3 times.

[0064] Phase 3 (Extreme Temperature Start-up): Raise the chamber temperature to the maximum operating temperature (85°C) specified in the SSD datasheet, maintain the temperature for 30 minutes, and then perform one startup test.

[0065] Secondly, in role simulation and load stress loading:

[0066] Scenario A (System Disk): Before the test began, a clean Windows 10 operating system had been installed on the SSD and configured as the system boot disk.

[0067] Scenario B (Data Disk + Load): Before each high-temperature boot test, the test host automatically runs a Python script. This script calls the FIO (Flexible I / O Tester) tool to generate a load with a specific utilization rate on the SSD:

[0068] 30% utilization: Generate 1 million random small files, each 4KB in size.

[0069] 70% utilization: Generates 10 additional random large files, each 1GB in size.

[0070] 95% utilization: Generate an additional random large file of 5GB.

[0071] After booting into the system, another Python script starts automatically and performs continuous random read operations (4KB blocks, queue depth 32) for 60 seconds to simulate the I / O pressure that the system experiences immediately after booting.

[0072] Evaluate startup performance and compare it to a baseline:

[0073] The automated testing platform records data such as T_total_high, T_bios_high, T_os_high, and I_peak_high for each high-temperature startup.

[0074] Comparison Algorithm: The system automatically retrieves the SSD's performance baseline data from the database, performs calculations, and makes judgments.

[0075] If (T_total_high>1.2×T_total_base) OR (I_peak_high>1.5×I_peak_base):

[0076] Then, the startup test is deemed a failure, and the exception is logged.

[0077] Fault Pre-diagnosis:

[0078] The system performs linear regression analysis on the startup time data from several consecutive tests. If the slope is positive and passes the significance test (e.g., p-value < 0.05), it indicates a "performance degradation trend," and the test platform will automatically issue a warning and suggest checking the SSD.

[0079] 3. Low-temperature start-up test

[0080] Step 301 (Temperature profile extension):

[0081] Phase 1 (Deep Freezing): The SSD was moved into a Thermotron T2C2 incubator and stored at -20°C for 12 hours.

[0082] Phase 2 (Low Temperature Start-up): Quickly raise the temperature of the incubator to 0°C (heating rate ~10°C / minute), and immediately perform 3 start-up tests at this temperature (with 5-minute intervals).

[0083] Phase 3 (Startup with Temperature Rise): After the final boot at 0°C, the SSD is kept powered on, and the host machine runs under idle load, allowing the chamber temperature to rise naturally to 25°C. During this period, the test host records the Reported Uncorrectable Errors and Temperature values ​​in the SSD's SMART attribute every 5 minutes to monitor its stability.

[0084] Condensation inspection and performance restoration:

[0085] After the test, manually observe the SSD interface and PCB for signs of condensation through the glass window of the chamber, and take photos for record-keeping (this step is an auxiliary manual inspection).

[0086] The system automatically records the time required from low-temperature boot to when the SSD's read / write performance (determined by a standard CrystalDiskMark quick test script) recovers to 95% of the baseline level. This time is recorded as "performance recovery time" and stored in the database.

[0087] 4. High and Low Temperature Cyclic Start-up and Shutdown Test: Set the temperature chamber cycling curve: -10°C (hold for 60 minutes) <-> 70°C (hold for 60 minutes), for a total of 5 cycles. Set the temperature chamber switching rate to the maximum rate. At the end of each cycle when the lowest temperature (-10°C) and highest temperature (70°C) holding phases are reached, perform one start-up test each time. During each start-up, a high-precision digital multimeter continuously monitors the current waveform. The analysis software compares each current waveform with the baseline waveform and calculates their correlation coefficient. If the correlation coefficient of the current waveform during a start-up is lower than a preset threshold (e.g., 0.85), the waveform is marked as abnormal, which may indicate a fault in the capacitor or chip due to thermal stress.

[0088] 5. Data Acquisition, Analysis, and Report Generation: The entire testing process is scheduled and controlled by NI TestStand test sequence software, integrating Python scripts to control the temperature chamber, power supply, data acquisition card, and test host, achieving 24 / 7 unattended automated testing. All data (temperature, time, current, pass / fail results, SMART data) are automatically stored in the database.

[0089] After the test, the system calls the JMP statistics software to automatically generate a comprehensive report. The report includes: a test parameter table, temperature-time curves overlaid with startup event markers, a startup time trend graph, a current waveform comparison graph, a pass / fail statistics table, and a reliability pre-diagnosis conclusion based on data analysis (e.g., "SSD001 performed stably in the high-temperature extreme startup test, but an abnormal startup current waveform was observed in the low-temperature cycle test, and disassembly analysis is recommended").

[0090] Based on the first embodiment, a third embodiment is proposed. In the third embodiment, an enterprise-grade NVMe SSD test example is provided. The test object is labeled SSD002, model: Intel SSD DC P4510 2TB NVMe SSD.

[0091] The difference between this embodiment and Embodiment 1 is that:

[0092] Interfaces and Protocols: The PCIe interface and NVMe protocol are used, with corresponding changes to the test host and fixture. Load Stress: Higher loads are applied to simulate enterprise-level scenarios. More complex load profiles are configured using FIO, such as additionally applying continuous background write pressure (simulating database log writes) at 95% utilization. The post-boot I / O stress script uses FIO to simulate mixed read / write operations (70% read, 30% write) across multiple queues (Queue Depth=128). Performance Baseline Parameters: In addition to boot time, latency and IOPS are added as part of the performance baseline and compared after stress testing. Fault Pre-diagnosis: Greater emphasis is placed on the automatic reading and analysis of NVMe Log Pages (such as the SMART Health Information Log and Error Log). The system automatically reads these logs after each boot, and any increase in error counts directly triggers an alert. Temperature Range: Based on the enterprise-level SSD specifications, the high-temperature limit test temperature may be set higher (e.g., 95°C).

[0093] This embodiment comprehensively simulates real-world user scenarios under extreme environments by introducing innovative elements such as multi-role simulation, temperature gradient and shock, dynamic load stress, performance baseline comparison, and fault pre-diagnosis. This overcomes the inefficiencies and low reliability caused by traditional testing methods relying on manual operation, improving the accuracy and reliability of test results. Employing a temperature curve extension mechanism, including three stages—gradient heating, thermal shock startup, and extreme temperature startup—it can comprehensively evaluate SSD performance under different temperature environments, effectively solving the problem of difficulty in performing performance testing of solid-state drives under various conditions in existing technologies. Through the design of Role A (system disk) and Role B (data disk + load), combined with different occupancy rates... The tests comprehensively evaluated the boot performance and reliability of SSDs under different usage scenarios, overcoming the shortcomings of existing technologies that lack role simulation and load stress assessment mechanisms for SSDs under different temperature environments. Based on performance recording and baseline comparison mechanisms, the system established a correspondence between performance index data and labels and models by accurately recording and analyzing BIOS / POST self-test time and operating system loading time, simplifying the testing steps and improving testing efficiency. Through the construction of an automated testing platform and data collection, intelligent analysis and early warning mechanisms, the system achieved real-time monitoring of the testing process and real-time anomaly detection, effectively solving the problem of lack of real-time monitoring and intelligent analysis capabilities for test data in existing technologies.

[0094] In the embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, indirect coupling or communication connection between apparatuses or units, and may be electrical, mechanical, or other forms.

[0095] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0096] The above are merely embodiments of the present invention and do not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for intelligent start-stop testing of solid-state drives at high and low temperatures, characterized in that, The method includes: Acquire the solid-state drive to be tested and preprocess it. The pre-processed solid-state drive under test was subjected to a high-temperature boot test, and the high-temperature boot performance of the solid-state drive under test was evaluated based on the test results. The pre-processed solid-state drive under test was subjected to a low-temperature boot test, and the low-temperature boot performance of the solid-state drive under test was evaluated based on the test results. Based on the high-temperature start-up performance and low-temperature start-up performance, a temperature cycle curve is set in the temperature chamber. Based on the temperature cycle curve, a high-low temperature cycle start-up and stop test is performed on the processed solid-state drive under test. The current change waveform of each high-low temperature cycle start-up and stop test is monitored and recorded. Automatically records test data generated from each test and generates a comprehensive report containing test curves, pass / fail statistics, and trend analysis. The step of performing a high-temperature boot test on the pre-processed solid-state drive under test and evaluating the high-temperature boot performance of the solid-state drive under test based on the test results includes: The pre-processed solid-state drive under test was placed in a high-temperature test environment and a high-temperature curve extension test was performed to obtain the high-temperature curve extension test data. The pre-processed solid-state drive under test was subjected to role simulation and load stress test to obtain role simulation test data and load stress test data. The high-temperature start-up performance was evaluated based on high-temperature curve extended test data, role simulation test data, and load pressure loading test data, and a high-temperature baseline comparison was performed.

2. The high and low temperature intelligent start-stop test method for solid-state drives according to claim 1, characterized in that, The step of placing the pre-processed solid-state drive under test in a high-temperature test environment and performing a high-temperature curve extension test to obtain high-temperature curve extension test data includes: Phase 1: Place the pre-treated solid-state drive to be tested in a temperature chamber, adjust the temperature to slowly increase from room temperature to the preset high temperature at a rate of 1℃ / minute, and keep it at the preset temperature for a preset time; Phase Two: Under a preset high-temperature environment, perform a preset number of starts, and set the dynamic change interval time for each start; Phase 3: Raise the temperature to the maximum operating temperature specified in the datasheet of the pre-processed solid-state drive under test, and perform one boot test; The execution phase one is gradient heating, the execution phase two is thermal shock start-up, the execution phase three is extreme temperature start-up, and the room temperature is 25°C.

3. The high and low temperature intelligent start-stop test method for solid-state drives according to claim 2, characterized in that, The step of performing role simulation and load stress loading tests on the pre-processed solid-state drive under test, and obtaining role simulation test data and load stress loading test data, includes: After installing the operating system on the pre-processed solid-state drive under test as the sole hard drive, a boot test is performed, configuring role A and installing the operating system; wherein, role A is the system disk; The pre-processed solid-state drive under test was used as a slave drive, and load files with different occupancy rates were pre-loaded into it before the boot test was performed. Run a lightweight continuous read script from the disk to test whether it can immediately withstand I / O pressure after startup.

4. The high and low temperature intelligent start-stop test method for solid-state drives according to claim 3, characterized in that, The steps for evaluating high-temperature startup performance and comparing it against a high-temperature baseline based on high-temperature curve extended test data, role simulation test data, and load pressure loading test data include: Record the BIOS / POST self-test time and operating system loading time during each boot process in the high-temperature boot test; The high-temperature start-up time at high temperature is compared with the baseline start-up time at room temperature; High-temperature performance index data are established based on a preset percentage of the high-temperature start-up time delay not exceeding the baseline start-up time.

5. The high and low temperature intelligent start-stop test method for solid-state drives according to claim 1, characterized in that, The steps of performing a low-temperature boot test on the pre-processed solid-state drive under test and evaluating the low-temperature boot performance of the solid-state drive under test based on the test results include: The pre-processed solid-state drive under test was placed in a low-temperature test environment and a low-temperature curve extension test was performed to obtain the low-temperature curve extension test data. The pre-processed solid-state drive under test was subjected to role simulation and load stress test to obtain role simulation test data and load stress test data. The low-temperature start-up performance was evaluated based on the extended test data of the low-temperature temperature curve, the role simulation test data, and the load pressure test data, and a low-temperature baseline comparison was performed.

6. The high and low temperature intelligent start-stop test method for solid-state drives according to claim 5, characterized in that, The step of placing the pre-processed solid-state drive under test in a low-temperature test environment and performing a low-temperature curve extension test to obtain low-temperature curve extension test data includes: Phase 1: The pre-processed solid-state drive under test is stored in a preset low-temperature environment for a preset time to ensure that the chip is completely cooled. Phase Two: Quickly transfer the cooled solid-state drive under test to a 0°C environment and immediately execute the preset number of startup cycles; Phase 3: After starting at 0℃, keep the SSD under test powered on and monitor its operational stability as the internal temperature of the SSD naturally rises to room temperature. Specifically, the first execution stage is deep freezing, the second execution stage is low-temperature start-up, and the third execution stage is start-up with temperature rise.

7. The high and low temperature intelligent start-stop test method for solid-state drives according to claim 6, characterized in that, The step of performing role simulation and load stress loading tests on the pre-processed solid-state drive under test, and obtaining role simulation test data and load stress loading test data, includes: After the low-temperature startup test, visual images of the interface and PCB board of the solid-state drive under test are obtained. Based on the visual images, the interface and PCB board of the solid-state drive under test are checked for signs of condensation or corrosion, and the visual image inspection results are recorded. Record the time required for performance to recover from low-temperature startup to room temperature baseline levels.

8. The high and low temperature intelligent start-stop test method for solid-state drives according to claim 1, characterized in that, The steps of setting a temperature cycling curve in the chamber based on high-temperature and low-temperature startup performance, performing high- and low-temperature cycle start-up and shutdown tests on the processed solid-state drive under test based on the temperature cycling curve, and monitoring and recording the current change waveform of each high- and low-temperature cycle start-up and shutdown test include: Based on high-temperature startup performance and low-temperature startup performance, a temperature cycling curve was set in the chamber, and the solid-state drive under test was cyclically tested within the range of the temperature cycling curve. Determine the highest and lowest temperatures for each cycle, and perform a startup test once at each of the highest and lowest temperatures; Monitor and record the current change waveform during each high and low temperature cycle start-up and shutdown test, and observe whether there are any abnormal current peaks in the current change waveform.

9. The high and low temperature intelligent start-stop test method for solid-state drives according to claim 1, characterized in that, The steps of automatically recording the test data generated in each test and generating a comprehensive report containing test curves, pass / fail statistics, and trend analysis include: Use the Python / TestStand language tool to write an automated script for the high and low temperature cycle start-up and shutdown test, and run the high and low temperature cycle start-up and shutdown test according to the automated script; Automatically record the test data generated by each high and low temperature cycle start-up and shutdown test, wherein the test data includes at least temperature, start-up time, start-up current, success status, and performance data; Generate a comprehensive report from the test data, including test curves, pass / fail statistics, and trend analysis.

Images