A flash memory rating test method, apparatus, device and medium

Abstract

This application discloses a flash memory level testing method, apparatus, device, and medium. The method includes: acquiring real-time test values ​​corresponding to the flash memory core parameters and test environment parameters of the flash memory device; wherein the flash memory core parameters include erase / write cycles, and the test environment parameters include temperature parameters; performing a normalization operation based on the real-time test values ​​to obtain normalized weight coefficients; dividing a preset value range to obtain multiple weighted sub-ranges; determining a target raw bit error rate (BER) grading threshold list based on the normalized weight coefficients and the multiple weighted sub-ranges; acquiring the real-time raw BER; and determining the target flash memory level of the flash memory device based on the real-time raw BER and the target raw BER grading threshold list. This technical solution integrates the dynamic influence of flash memory core parameters and test environment parameters to construct a real-time dynamic grading method, achieving accurate determination of the flash memory level of the flash memory device.

Description

Technical Field

[0001] This application belongs to the field of electronic digital value processing technology, specifically relating to a flash memory level testing method, apparatus, device, and medium. Background Technology

[0002] Flash memory, as a non-volatile storage medium, has been deeply integrated into core hardware devices in storage scenarios such as personal electronic devices, industrial embedded control equipment, and data center server equipment due to its advantages such as fast read and write speeds and strong shock resistance. These hardware devices and related modules that use flash memory as their core storage medium are collectively referred to as flash memory devices. Flash memory performance can serve as a key indicator for evaluating the smoothness, stability, and service efficiency of flash memory devices.

[0003] Currently, the performance evaluation of flash memory devices mostly adopts the traditional method based on fixed thresholds. This involves pre-setting static evaluation criteria for key parameters such as erase / write cycles and raw bit error rate, and then classifying them accordingly. However, this method has significant limitations in complex real-world application scenarios. It cannot fully consider the impact of dynamic changes in workload and usage environment on the performance of flash memory devices, making it difficult to achieve accurate performance classification. Summary of the Invention

[0004] This application provides a flash memory level testing method and system, aiming to construct a real-time dynamic grading method by comprehensively considering the dynamic influence of flash memory core parameters and test environment parameters, so as to achieve accurate determination of the flash memory level of flash memory devices.

[0005] Firstly, this application provides a flash memory level testing method, the method comprising:

[0006] The system acquires real-time test values ​​corresponding to the flash memory core parameters and test environment parameters of the flash memory device; wherein, the flash memory core parameters include the number of erase / write cycles, and the test environment parameters include temperature parameters.

[0007] The normalized weighting coefficients are determined based on the real-time test values;

[0008] The preset value range is divided into multiple weighted sub-ranges. Based on the normalized weight coefficients and the multiple weighted sub-ranges, a target original bit error rate classification threshold list is determined.

[0009] The real-time raw bit error rate is obtained, and the target flash memory level of the flash memory device is determined based on the real-time raw bit error rate and the target raw bit error rate grading threshold list.

[0010] Furthermore, the preset value range is divided to obtain multiple weighted sub-ranges, including:

[0011] The preset value range is divided into low loss level range, medium loss level range and high loss level range.

[0012] Based on the preset number of sub-intervals corresponding to the low-loss level interval, the medium-loss level interval, and the high-loss level interval, the low-loss level interval, the medium-loss level interval, and the high-loss level interval are divided into multiple weighted sub-intervals.

[0013] Furthermore, based on the preset number of sub-intervals corresponding to the low-loss level interval, the medium-loss level interval, and the high-loss level interval, the low-loss level interval, the medium-loss level interval, and the high-loss level interval are respectively divided to obtain multiple weighted sub-intervals, including:

[0014] Based on the logarithmic increasing function and the number of preset sub-intervals corresponding to the low-loss level interval, multiple weighted sub-intervals corresponding to the low-loss level interval are obtained.

[0015] Based on the linearly increasing function and the number of preset sub-intervals corresponding to the intermediate loss level interval, multiple weighted sub-intervals corresponding to the intermediate loss level interval are obtained.

[0016] Based on the exponentially increasing function and the preset number of sub-intervals corresponding to the high-loss level interval, multiple weighted sub-intervals corresponding to the high-loss level interval are obtained.

[0017] Furthermore, after obtaining the real-time test values ​​corresponding to the flash memory core parameters and test environment parameters of the flash memory device, the method further includes:

[0018] Obtain the global maximum test value and the maximum test value at the target ambient temperature of the flash memory core parameters; wherein, the target ambient temperature is equal to the real-time test value of the temperature parameter;

[0019] Accordingly, determining the normalized weight coefficients based on the real-time test values ​​includes:

[0020] Based on the real-time test value of the number of erase / write cycles and the maximum test value at the target ambient temperature, the environmental impact value of the number of erase / write cycles is calculated;

[0021] Based on the real-time test values ​​and the global maximum test values ​​of all flash memory core parameters, calculate the normalized values ​​of all flash memory core parameters;

[0022] Based on the environmental impact value of the number of erase / write cycles and the normalized values ​​of all flash memory core parameters, the normalization weight coefficient is determined.

[0023] Furthermore, the core parameters of the flash memory also include auxiliary parameters;

[0024] Accordingly, before determining the normalization weighting coefficients based on the environmental impact value of the erase / write cycles and the normalized values ​​of all flash memory core parameters, the method further includes:

[0025] Based on the real-time test values ​​of the auxiliary parameters and the maximum test values ​​at the target ambient temperature, the environmental impact value of the auxiliary parameters is calculated.

[0026] Accordingly, the determination of normalization weighting coefficients based on the environmental impact value of the erase / write cycles and the normalized values ​​of all flash memory core parameters includes:

[0027] Based on the environmental impact value of the erase / write count and the normalized value of all flash memory core parameters, calculate the comprehensive impact weight coefficient corresponding to the erase / write count; and based on the environmental impact value of the auxiliary parameter and the normalized value of all flash memory core parameters, calculate the comprehensive impact weight coefficient corresponding to the auxiliary parameter.

[0028] The normalized weight coefficients are obtained by weighted summation of the combined influence of the number of erase / write cycles and the auxiliary parameters.

[0029] Furthermore, after obtaining the real-time test values ​​corresponding to the flash memory core parameters and test environment parameters of the flash memory device, the method further includes:

[0030] Obtain the global maximum test values ​​of the flash memory core parameters and the test environment parameters;

[0031] Accordingly, determining the normalized weight coefficients based on the real-time test values ​​includes:

[0032] Based on the real-time test values ​​of the flash memory core parameters and the test environment parameters, as well as the global maximum test value, the normalized values ​​of the flash memory core parameters and the test environment parameters are calculated.

[0033] The normalized values ​​of the flash memory core parameters and the test environment parameters are weighted and summed to obtain the normalized weight coefficients.

[0034] Furthermore, before determining the target flash memory class of the flash memory device based on the real-time raw bit error rate and the target raw bit error rate classification threshold list, the method further includes:

[0035] Based on the normalized weight coefficients and the multiple weight sub-intervals, a target grading threshold list for the flash memory core parameters and the test environment parameters is determined.

[0036] Accordingly, determining the target flash memory class of the flash memory device based on the real-time raw bit error rate and the target raw bit error rate classification threshold list includes:

[0037] The component flash memory level corresponding to the original bit error rate is determined based on the real-time original bit error rate and the target original bit error rate classification threshold list. The component flash memory level corresponding to the flash memory core parameters and the test environment parameters is determined based on the real-time test values ​​of the flash memory core parameters and the test environment parameters and the target classification threshold list.

[0038] The target flash memory level of the flash memory device is obtained by weighted summation of the original bit error rate, the flash memory core parameters, and the component flash memory levels corresponding to the test environment parameters.

[0039] Secondly, this application provides a flash memory level testing apparatus, the apparatus comprising:

[0040] The parameter acquisition module is used to acquire real-time test values ​​corresponding to the flash memory core parameters and test environment parameters of the flash memory device; wherein, the flash memory core parameters include the number of erase / write cycles, and the test environment parameters include temperature parameters;

[0041] The weight determination module is used to determine the normalized weight coefficients based on the real-time test values;

[0042] The threshold determination module is used to divide the preset value range to obtain multiple weighted sub-ranges, and determine the target original bit error rate classification threshold list based on the normalized weight coefficient and the multiple weighted sub-ranges.

[0043] The level determination module is used to obtain the real-time raw bit error rate and determine the target flash memory level of the flash memory device based on the real-time raw bit error rate and the target raw bit error rate classification threshold list.

[0044] Furthermore, the threshold determination module is specifically used for:

[0045] The preset value range is divided into low loss level range, medium loss level range and high loss level range.

[0046] Based on the preset number of sub-intervals corresponding to the low-loss level interval, the medium-loss level interval, and the high-loss level interval, the low-loss level interval, the medium-loss level interval, and the high-loss level interval are divided into multiple weighted sub-intervals.

[0047] Furthermore, the threshold determination module is specifically used for:

[0048] Based on the logarithmic increasing function and the number of preset sub-intervals corresponding to the low-loss level interval, multiple weighted sub-intervals corresponding to the low-loss level interval are obtained.

[0049] Based on the linearly increasing function and the number of preset sub-intervals corresponding to the intermediate loss level interval, multiple weighted sub-intervals corresponding to the intermediate loss level interval are obtained.

[0050] Based on the exponentially increasing function and the preset number of sub-intervals corresponding to the high-loss level interval, multiple weighted sub-intervals corresponding to the high-loss level interval are obtained.

[0051] Furthermore, the device is also used for:

[0052] Obtain the global maximum test value and the maximum test value at the target ambient temperature of the flash memory core parameters; wherein, the target ambient temperature is equal to the real-time test value of the temperature parameter;

[0053] Accordingly, the weight determination module is specifically used for:

[0054] Based on the real-time test value of the number of erase / write cycles and the maximum test value at the target ambient temperature, the environmental impact value of the number of erase / write cycles is calculated;

[0055] Based on the real-time test values ​​and the global maximum test values ​​of all flash memory core parameters, calculate the normalized values ​​of all flash memory core parameters;

[0056] Based on the environmental impact value of the number of erase / write cycles and the normalized values ​​of all flash memory core parameters, the normalization weight coefficient is determined.

[0057] Furthermore, the core parameters of the flash memory also include auxiliary parameters;

[0058] Accordingly, the device is also used for:

[0059] Based on the real-time test values ​​of the auxiliary parameters and the maximum test values ​​at the target ambient temperature, the environmental impact value of the auxiliary parameters is calculated.

[0060] Accordingly, the weight determination module is specifically used for:

[0061] Based on the environmental impact value of the erase / write count and the normalized value of all flash memory core parameters, calculate the comprehensive impact weight coefficient corresponding to the erase / write count; and based on the environmental impact value of the auxiliary parameter and the normalized value of all flash memory core parameters, calculate the comprehensive impact weight coefficient corresponding to the auxiliary parameter.

[0062] The normalized weight coefficients are obtained by weighted summation of the combined influence of the number of erase / write cycles and the auxiliary parameters.

[0063] Furthermore, the device is also used for:

[0064] Obtain the global maximum test values ​​of the flash memory core parameters and the test environment parameters;

[0065] Accordingly, the weight determination module is specifically used for:

[0066] Based on the real-time test values ​​of the flash memory core parameters and the test environment parameters, as well as the global maximum test value, the normalized values ​​of the flash memory core parameters and the test environment parameters are calculated.

[0067] The normalized values ​​of the flash memory core parameters and the test environment parameters are weighted and summed to obtain the normalized weight coefficients.

[0068] Furthermore, the device is also used for:

[0069] Based on the normalized weight coefficients and the multiple weight sub-intervals, a target grading threshold list for the flash memory core parameters and the test environment parameters is determined.

[0070] Accordingly, the level determination module is specifically used for:

[0071] The component flash memory level corresponding to the original bit error rate is determined based on the real-time original bit error rate and the target original bit error rate classification threshold list. The component flash memory level corresponding to the flash memory core parameters and the test environment parameters is determined based on the real-time test values ​​of the flash memory core parameters and the test environment parameters and the target classification threshold list.

[0072] The target flash memory level of the flash memory device is obtained by weighted summation of the original bit error rate, the flash memory core parameters, and the component flash memory levels corresponding to the test environment parameters.

[0073] Thirdly, this application provides an electronic device including a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the method described in the first aspect.

[0074] Fourthly, this application provides a readable storage medium on which a program or instructions are stored, which, when executed by a processor, implement the method described in the first aspect.

[0075] In this application, real-time test values ​​corresponding to the flash memory core parameters and test environment parameters of the flash memory device are obtained. The flash memory core parameters include the number of erase / write cycles, and the test environment parameters include temperature parameters. A normalized weighting coefficient is determined based on the real-time test values. A preset value range is divided into multiple weighted sub-ranges, and a target raw bit error rate (BER) grading threshold list is determined based on the normalized weighting coefficients and the multiple weighted sub-ranges. The real-time raw BER is obtained, and the target flash memory level of the flash memory device is determined based on the real-time raw BER and the target raw BER grading threshold list. This flash memory level testing method comprehensively considers the dynamic influence of flash memory core parameters and test environment parameters to construct a real-time dynamic grading method, achieving accurate determination of the flash memory level of the flash memory device. Attached Figure Description

[0076] Figure 1 This is a flowchart illustrating a flash memory level testing method provided in an embodiment of this application;

[0077] Figure 2 This is a flowchart illustrating another flash memory level testing method provided in an embodiment of this application;

[0078] Figure 3 This is a flowchart illustrating another flash memory level testing method provided in an embodiment of this application;

[0079] Figure 4 This is a flowchart illustrating another flash memory level testing method provided in an embodiment of this application;

[0080] Figure 5 This is a schematic diagram of the structure of a flash memory level testing device provided in an embodiment of this application;

[0081] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0082] To make the objectives, technical solutions, and advantages of this application clearer, specific embodiments of this application will be described in further detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely for explaining this application and not for limiting it. It should also be noted that, for ease of description, only the parts relevant to this application are shown in the drawings, not all of them. Before discussing exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe operations (or steps) as sequential processes, many of these operations can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but may also have additional steps not included in the drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0083] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0084] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such values ​​can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0085] The flash memory level testing method and system provided in this application will be described in detail below with reference to the accompanying drawings and through specific embodiments and application scenarios.

[0086] First, this application applies to scenarios where the flash memory level of a flash memory device needs to be determined in order to dynamically adjust read / write strategies, provide bad block warnings, or perform hierarchical management of the flash memory device based on the determined flash memory level. Based on the above usage scenarios, it is understood that the implementing entity of this application can be a smart terminal device, such as a desktop computer, laptop computer, mobile phone, tablet computer, or interactive multimedia device, etc., without further limitations here.

[0087] Flash memory devices can refer to various hardware devices and related modules that use flash memory chips as the core storage medium and rely on flash memory technology to realize data storage and reading / writing. They are the carriers for the practical application of flash memory technology. Flash memory grade can be a classification identifier that divides the flash memory storage performance of flash memory devices into different levels.

[0088] Figure 1 This is a flowchart illustrating a flash memory level testing method provided in an embodiment of this application. Figure 1 As shown, the specific steps include the following:

[0089] S101, Obtain the real-time test values ​​corresponding to the flash memory core parameters and test environment parameters of the flash memory device; wherein, the flash memory core parameters include the number of erase / write cycles, and the test environment parameters include temperature parameters.

[0090] Among these, the core parameters of flash memory can be inherent technical parameters that reflect the storage performance of flash memory devices, and can include the number of erase / write cycles. Specifically, the number of erase / write cycles refers to the cumulative number of times a storage block of a flash memory device completes an erase and write cycle.

[0091] The test environment parameters refer to the characteristic parameters of the external environment in which the flash memory device operates. Changes in these parameters directly affect the electrical characteristics and data storage stability of the flash memory. Test environment parameters can include temperature parameters. Specifically, the temperature parameter refers to the ambient temperature of the external environment in which the flash memory device operates.

[0092] Among them, the real-time test value can be the specific value of the flash memory core parameters and test environment parameters obtained at the current moment.

[0093] In one embodiment, the real-time test values ​​corresponding to the flash memory core parameters and test environment parameters of the flash memory device can be obtained by reading parameter acquisition data stored in the built-in registers of the flash memory device's main control chip to obtain the real-time test values ​​of the flash memory core parameters, and by acquiring the real-time test values ​​of the test environment parameters through dedicated sensors corresponding to the test environment parameters. Specifically, the real-time test value of the erase / write cycles can be counted by the flash memory controller according to the cycle period and written to the register, and the real-time test value of the temperature parameter can be acquired in real time by a temperature sensor and transmitted to the register.

[0094] S102, determine the normalized weight coefficients based on the real-time test values.

[0095] The normalized weight coefficient can be a dimensionless coefficient obtained by mapping the real-time test values ​​of flash memory core parameters and test environment parameters with different dimensions and numerical ranges to the same numerical range through a normalization algorithm. It is used to characterize the influence weight of each parameter on the original bit error rate of the flash memory device.

[0096] In one embodiment, the method of determining the normalized weight coefficient based on real-time test values ​​can be achieved by determining the normalized value corresponding to each real-time test value based on the range of values ​​of each real-time test value, and calculating the average value of each normalized value as the normalized weight coefficient.

[0097] S103, the preset value range is divided to obtain multiple weighted sub-ranges, and the target original bit error rate classification threshold list is determined based on the normalized weight coefficients and the multiple weighted sub-ranges.

[0098] The preset value range can be a pre-defined range of normalized weight coefficients, such as [0,1]; the weight sub-interval can be a sub-interval obtained by dividing the preset value range, and each sub-interval corresponds to a set of original bit error rate classification thresholds.

[0099] In one embodiment, dividing a preset value range into multiple weighted sub-ranges can be achieved by dividing the preset value range into a preset number of weighted sub-ranges on an average basis. For example, if the preset value range is [0,1] and the preset number is 5, then the corresponding weighted sub-ranges are [0,0.2), [0.2,0.4), [0.4,0.6), [0.6,0.8), and [0.8,1].

[0100] The raw bit error rate can be the ratio of the number of bit errors that occur when reading stored data to the total number of bits read, without any error correction coding, bad block management or other fault tolerance processing. The raw bit error rate classification threshold list can be a set of raw bit error rate thresholds preset for different flash memory levels of flash memory devices.

[0101] Specifically, a weighted sub-interval corresponds to a list of original bit error rate (BER) grading thresholds. For example, the list of original BER grading thresholds corresponding to the weighted sub-interval [0, 0.2) is [1, 4, 8, 12, 16, 20, 24, 28, 32, 36].

[0102] Correspondingly, the target raw bit error rate classification threshold list is the raw bit error rate classification threshold list that is adapted to the current normalized weight coefficients.

[0103] In one embodiment, the method of determining the target original bit error rate (BER) classification threshold list based on normalized weight coefficients and multiple weight sub-intervals can be achieved by comparing the normalized weight coefficients with each weight sub-interval to determine the target weight sub-interval corresponding to the normalized weight coefficients, and then determining the preset original BER classification threshold list corresponding to the target weight sub-interval as the target original BER classification threshold list.

[0104] S104, obtain the real-time raw bit error rate, and determine the target flash memory level of the flash memory device based on the real-time raw bit error rate and the target raw bit error rate classification threshold list.

[0105] The real-time raw bit error rate can be the raw bit error rate calculated at the current moment after performing data read and write tests on a specified storage block of the flash memory device.

[0106] In one embodiment, the real-time raw bit error rate can be obtained by writing preset test data to a specified storage block through a flash memory controller, then reading data from the storage block, comparing the read data with the original test data bit by bit, counting the number of error bits, and dividing the number of error bits by the total number of bits in the test data to obtain the real-time raw bit error rate.

[0107] The target flash memory level can be the flash memory level of the flash memory device determined at the current moment.

[0108] In one embodiment, determining the target flash memory class of a flash memory device based on the real-time raw bit error rate (BER) and a target BER grading threshold list can be achieved by sequentially comparing the real-time raw BER with each BER threshold in the target BER grading threshold list, and matching the corresponding target flash memory class according to the BER threshold range in which the real-time raw BER falls. Where the number of BER thresholds in the target BER grading threshold list is N, N+1 flash memory classes are obtained. For example, if the real-time raw BER is 3 (parts per million), and the target BER grading threshold list is [1,4,8,12,16,20,24,28,32,36], then the corresponding target flash memory class is 2.

[0109] In one embodiment, before determining the target flash memory level of the flash memory device based on the real-time raw bit error rate and the target raw bit error rate grading threshold list, the method further includes: determining the target grading threshold list of the flash memory core parameters and the test environment parameters based on the normalized weight coefficients and the plurality of weighted sub-intervals; correspondingly, determining the target flash memory level of the flash memory device based on the real-time raw bit error rate and the target raw bit error rate grading threshold list includes: determining the component flash memory level corresponding to the raw bit error rate based on the real-time raw bit error rate and the target raw bit error rate grading threshold list, and determining the component flash memory level corresponding to the flash memory core parameters and the test environment parameters based on the real-time test values ​​of the flash memory core parameters and the test environment parameters and the target grading threshold list; and performing a weighted summation calculation on the raw bit error rate, the flash memory core parameters, and the component flash memory levels corresponding to the test environment parameters to obtain the target flash memory level of the flash memory device.

[0110] The target tiered threshold list for flash core parameters and test environment parameters can be a set of multi-level parameter thresholds configured separately for each parameter (including each flash core parameter and each test environment parameter) based on normalized weight coefficient matching.

[0111] In one embodiment, the method of determining the target grading threshold list for flash memory core parameters and test environment parameters based on normalized weight coefficients and multiple weight sub-intervals can be achieved by pre-configuring grading threshold lists for each flash memory core parameter and each test environment parameter for each weight sub-interval, comparing the normalized weight coefficients with each weight sub-interval to determine the target weight sub-interval corresponding to the normalized weight coefficients, and determining the grading threshold list corresponding to each flash memory core parameter and each test environment parameter for each target weight sub-interval as the target grading threshold list.

[0112] Among them, component flash memory level can be a flash memory level used to quantify the performance of individual parameters (including raw bit error rate, each flash memory core parameter and each test environment parameter).

[0113] In one embodiment, the method of determining the component flash memory level corresponding to the original bit error rate based on the real-time original bit error rate and the target original bit error rate classification threshold list can be achieved by sequentially comparing the real-time original bit error rate with each original bit error rate threshold in the target original bit error rate classification threshold list, and matching the component flash memory level corresponding to the original bit error rate according to the original bit error rate threshold range in which the real-time original bit error rate is located.

[0114] In one embodiment, the method of determining the component flash level corresponding to the flash core parameters and test environment parameters based on the real-time test values ​​of the flash core parameters and test environment parameters and the target grading threshold list can be achieved by sequentially comparing the real-time test value of each parameter (including each flash core parameter and each test environment parameter) with the threshold values ​​of each parameter in the target grading threshold list corresponding to that parameter, and matching to obtain the component flash level corresponding to that parameter.

[0115] In one embodiment, the target flash memory level of the flash memory device is obtained by weighted summation of the component flash memory levels corresponding to the original bit error rate, flash memory core parameters, and test environment parameters. This can be achieved by configuring a component weight coefficient for each parameter (including the original bit error rate, each flash memory core parameter, and each test environment parameter), multiplying the component flash memory level of each parameter by the corresponding component weight coefficient, summing all the product results, and rounding the sum up to obtain the target flash memory level.

[0116] The advantage of this approach is that it enables a multi-dimensional and comprehensive evaluation of flash memory device performance, completely overcoming the limitations of traditional single-indicator or local parameter judgments.

[0117] In this embodiment, real-time test values ​​corresponding to the flash memory core parameters and test environment parameters of the flash memory device are obtained. The flash memory core parameters include the number of erase / write cycles, and the test environment parameters include temperature parameters. A normalized weighting coefficient is determined based on the real-time test values. A preset value range is divided into multiple weighted sub-ranges, and a target raw bit error rate (BER) grading threshold list is determined based on the normalized weighting coefficients and the multiple weighted sub-ranges. The real-time raw BER is obtained, and the target flash memory level of the flash memory device is determined based on the real-time raw BER and the target raw BER grading threshold list. This flash memory level testing method comprehensively considers the dynamic influence of flash memory core parameters and test environment parameters to construct a real-time dynamic grading method, achieving accurate determination of the flash memory level of the flash memory device.

[0118] Figure 2 This is a flowchart illustrating another flash memory level testing method provided in an embodiment of this application. Figure 2 As shown, the specific steps include the following:

[0119] S201, Obtain the real-time test values ​​corresponding to the flash memory core parameters and test environment parameters of the flash memory device; wherein, the flash memory core parameters include the number of erase / write cycles, and the test environment parameters include temperature parameters.

[0120] S202, determine the normalized weight coefficients based on the real-time test values.

[0121] S203 divides the preset value range into a low-loss level range, a medium-loss level range, and a high-loss level range.

[0122] The low-loss level range can be a range of low values ​​within a preset range, corresponding to a low overall loss level of the flash memory device. The medium-loss level range can be a range of medium values ​​within a preset range, corresponding to a medium overall loss level of the flash memory device. The high-loss level range can be a range of high values ​​within a preset range, corresponding to a high overall loss level of the flash memory device.

[0123] In one embodiment, dividing the preset value range into low-loss, medium-loss, and high-loss intervals can be achieved by taking the first 30% of the preset value range as the low-loss interval, the 30%-70% of the preset value range as the medium-loss interval, and the last 30% of the preset value range as the high-loss interval. For example, if the preset value range is [0,1], then the corresponding low-loss interval is [0,0.3], the medium-loss interval is [0.3,0.7], and the high-loss interval is [0.7,1].

[0124] S204, based on the preset number of sub-intervals corresponding to the low-loss level interval, the medium-loss level interval, and the high-loss level interval, the low-loss level interval, the medium-loss level interval, and the high-loss level interval are divided to obtain multiple weighted sub-intervals.

[0125] The preset number of sub-intervals can be the number of sub-intervals corresponding to the division of low-loss, medium-loss, and high-loss level intervals.

[0126] In one embodiment, based on the preset number of sub-intervals for low-loss, medium-loss, and high-loss levels, the low-loss, medium-loss, and high-loss levels are divided into multiple weighted sub-intervals. Alternatively, the low-loss, medium-loss, and high-loss levels can be divided equally into the corresponding preset number of weighted sub-intervals.

[0127] In one embodiment, the step of dividing the low-loss level interval, the medium-loss level interval, and the high-loss level interval into multiple weighted sub-intervals based on the preset number of sub-intervals corresponding to the low-loss level interval, the medium-loss level interval, and the high-loss level interval respectively, includes: dividing based on a logarithmic increasing function and the preset number of sub-intervals corresponding to the low-loss level interval to obtain multiple weighted sub-intervals corresponding to the low-loss level interval; dividing based on a linear increasing function and the preset number of sub-intervals corresponding to the medium-loss level interval to obtain multiple weighted sub-intervals corresponding to the medium-loss level interval; and dividing based on an exponential increasing function and the preset number of sub-intervals corresponding to the high-loss level interval to obtain multiple weighted sub-intervals corresponding to the high-loss level interval.

[0128] The logarithmic increasing function can be a function that takes the normalized weight coefficient candidate values ​​within the low-loss level interval as the independent variable and the right boundary value of the weight sub-interval as the dependent variable, satisfying that the dependent variable increases logarithmically with the increase of the independent variable. Its mathematical expression can be: ; where the values ​​of x and y are both within the low-loss level range.

[0129] In one embodiment, the method of dividing the low-loss level interval based on a logarithmic increasing function and a preset number of sub-intervals corresponding to the low-loss level interval to obtain multiple weighted sub-intervals can be achieved by dividing the low-loss level interval into an initial number of sub-intervals corresponding to the low-loss level interval, taking the right boundary value of each initial sub-interval as the independent variable of the logarithmic increasing function to calculate its corresponding dependent variable, and using each dependent variable as the right boundary value of the weighted sub-intervals to divide the low-loss level interval, thus obtaining the weighted sub-intervals corresponding to the low-loss level interval. For example, if the low-loss level interval is [0, 0.3), and the preset number of sub-intervals corresponding to the low-loss level interval is 3, then the mathematical expression of the logarithmic increasing function can be set as follows: x takes values ​​of 0.1, 0.2, and 0.3 respectively, and their corresponding (rounded) y values ​​are 0.109, 0.208, and 0.300 respectively. The multiple weighted sub-intervals corresponding to the low-loss level interval are [0, 0.109), [0.109, 0.208), and [0.208, 0.300].

[0130] The linearly increasing function can be a function that takes the normalized weight coefficient candidate values ​​within the intermediate loss level interval as the independent variable and the right boundary value of the weight sub-interval as the dependent variable, satisfying that the dependent variable increases linearly and uniformly with the increase of the independent variable. Its mathematical expression can be: ; where the values ​​of x and y are both within the range of the medium loss level.

[0131] In one embodiment, the method of dividing the intermediate loss level interval based on a linearly increasing function and the number of preset sub-intervals corresponding to the intermediate loss level interval to obtain multiple weighted sub-intervals can be achieved by dividing the intermediate loss level interval into an initial sub-interval of the preset number of sub-intervals corresponding to the intermediate loss level interval. The right boundary value of each initial sub-interval is then used as the independent variable of the linearly increasing function to calculate its corresponding dependent variable. Each dependent variable is then used as the right boundary value of the weighted sub-intervals to divide the intermediate loss level interval, thus obtaining the weighted sub-intervals corresponding to the intermediate loss level interval. For example, if the intermediate loss level interval is [0.3, 0.7), the number of preset sub-intervals corresponding to the intermediate loss level interval is 4, and x takes values ​​of 0.4, 0.5, 0.6, and 0.7, the corresponding y values ​​are 0.4, 0.5, 0.6, and 0.7, respectively. The multiple weighted sub-intervals corresponding to the intermediate loss level interval are then [0.3, 0.4), [0.4, 0.5), [0.5, 0.6), and [0.6, 0.7).

[0132] The exponentially increasing function can be a function that takes the normalized weight coefficient candidate values ​​within the high-loss level interval as the independent variable and the right boundary value of the weighted sub-interval as the dependent variable, satisfying that the dependent variable grows rapidly in an exponential form as the independent variable increases. Its mathematical expression can be: ; where x and y both take values ​​within the high-loss level range, and a is the left boundary value of the high-loss level range.

[0133] In one embodiment, the method of dividing the high-loss level interval based on the exponentially increasing function and the preset number of sub-intervals corresponding to the high-loss level interval to obtain multiple weighted sub-intervals can be achieved by dividing the high-loss level interval into an initial number of sub-intervals corresponding to the high-loss level interval on an average basis. The right boundary value of each initial sub-interval is then taken as the independent variable of the linearly increasing function to calculate its corresponding dependent variable. Each dependent variable is then used as the right boundary value of the weighted sub-intervals to divide the high-loss level interval, thus obtaining the weighted sub-intervals corresponding to the high-loss level interval. For example, if the high-loss level interval is [0.7, 1] and the preset number of sub-intervals corresponding to the high-loss level interval is 3, then the mathematical expression of the logarithmic increasing function can be set as follows: x takes values ​​of 0.8, 0.9 and 1.0 respectively, and their corresponding (rounded) y values ​​are 0.805, 0.921 and 1.000 respectively. The multiple weighted sub-intervals corresponding to the high loss level interval are [0.7, 0.805), [0.805, 0.921) and [0.921, 1.000].

[0134] The advantage of this scheme is that it can fit the changing characteristics of losses in different levels and achieve refined and differentiated weighted sub-interval division.

[0135] S205, determine the target original bit error rate classification threshold list based on the normalized weight coefficients and the multiple weight sub-intervals.

[0136] S206, obtain the real-time raw bit error rate, and determine the target flash memory level of the flash memory device based on the real-time raw bit error rate and the target raw bit error rate classification threshold list.

[0137] The advantage of this scheme is that by using a two-level division method of first classifying the layers and then dividing them into sub-intervals, the logic of dividing the weighted intervals is clearer, and the matching of the subsequent target original bit error rate classification threshold list is more accurate, thereby improving the accuracy and rationality of flash memory level determination for flash memory devices.

[0138] Figure 3 This is a flowchart illustrating another flash memory level testing method provided in an embodiment of this application. Figure 3 As shown, the specific steps include the following:

[0139] S301, Obtain the real-time test values ​​corresponding to the flash memory core parameters and test environment parameters of the flash memory device; wherein, the flash memory core parameters include the number of erase / write cycles, and the test environment parameters include temperature parameters.

[0140] S302, obtain the global maximum test value of the flash memory core parameter and the maximum test value at the target ambient temperature; wherein, the target ambient temperature is equal to the real-time test value of the temperature parameter.

[0141] The core parameters of flash memory can also include read data speed and write data speed. Specifically, read data speed is the actual transfer rate at which the flash memory device reads data from the storage medium; write data speed is the actual transfer rate at which the flash memory device writes data to the storage medium.

[0142] The global maximum test value of the flash memory core parameters can be the theoretical maximum threshold that the flash memory core parameters can reach, which is the limit value calibrated at the factory of the flash memory device. This value is not affected by the operating environment of the flash memory device. The maximum test value of the flash memory core parameters at the target ambient temperature can be the actual maximum threshold that the flash memory core parameters can reach under the operating environment of the target ambient temperature. This value is dynamically adjusted with changes in ambient temperature. The target ambient temperature is equal to the real-time test value of the temperature parameter. For example, if the real-time test value of the temperature parameter is 25 degrees Celsius, then the maximum test value of the flash memory core parameters at 25 degrees Celsius is obtained.

[0143] In one embodiment, the method for obtaining the global maximum test value of the flash memory core parameters and the maximum test value at the target ambient temperature can be as follows: retrieve the global maximum test value of the flash memory core parameters from the factory configuration parameter library of the flash memory device, and retrieve the maximum test value of the corresponding flash memory core parameters from the environment-parameter threshold mapping table of the flash memory device according to the value of the target ambient temperature.

[0144] S303, based on the real-time test value of the number of erase / write cycles and the maximum test value at the target ambient temperature, calculate the environmental impact value of the number of erase / write cycles.

[0145] Among them, the environmental impact value of the number of erase / write cycles can be a dimensionless parameter used to quantify the degree of influence of the current ambient temperature on the number of erase / write cycles of the flash memory device, with a value range of 0 to 1.

[0146] In one embodiment, the environmental impact value of the number of erase / write cycles can be calculated based on the real-time test value of the number of erase / write cycles and the maximum test value at the target ambient temperature. This can be achieved by subtracting the real-time test value of the number of erase / write cycles from the maximum test value at the target ambient temperature, and then dividing the result of this subtraction by the maximum test value at the target ambient temperature to obtain the environmental impact value of the number of erase / write cycles.

[0147] S304 calculates the normalized values ​​of all flash memory core parameters based on real-time test values ​​and global maximum test values.

[0148] Among them, the normalized value of the flash memory core parameter can be a dimensionless value obtained by mapping the real-time test values ​​of flash memory core parameters with different dimensions and different numerical ranges to the [0,1] interval.

[0149] In one embodiment, the normalized value of all flash memory core parameters can be calculated based on the real-time test value and the global maximum test value of all flash memory core parameters by dividing the real-time test value of each flash memory core parameter by the corresponding global maximum test value.

[0150] S305, Based on the environmental impact value of the erase / write cycles and the normalized values ​​of all flash memory core parameters, determine the normalization weight coefficient.

[0151] In one embodiment, the normalization weighting coefficient is determined based on the environmental impact value of the erase / write cycles and the normalized values ​​of all flash memory core parameters. This can be achieved by subtracting the environmental impact value of the erase / write cycles from 1 to obtain the erase / write cycle loss correction coefficient. Then, the normalized value of each flash memory core parameter is multiplied by the erase / write cycle loss correction coefficient, and the results of each multiplication are weighted and summed to obtain the normalization weighting coefficient. For example, the formula for calculating the normalization weighting coefficient is: ;in, These are the normalized weighting coefficients. , as well as These are the weighting coefficients for the number of erase / write cycles, read speed, and write speed, respectively. ), , as well as These are the normalized values ​​corresponding to the number of erase / write cycles, read speed, and write speed, respectively. This represents the environmental impact value.

[0152] In one embodiment, the flash memory core parameters further include auxiliary parameters; correspondingly, before determining the normalized weight coefficient based on the environmental impact value of the erase / write cycles and the normalized values ​​of all flash memory core parameters, the method further includes: calculating the environmental impact value of the auxiliary parameter based on the real-time test value of the auxiliary parameter and the maximum test value at the target ambient temperature; correspondingly, determining the normalized weight coefficient based on the environmental impact value of the erase / write cycles and the normalized values ​​of all flash memory core parameters includes: calculating the comprehensive impact weight coefficient corresponding to the erase / write cycles based on the environmental impact value of the erase / write cycles and the normalized values ​​of all flash memory core parameters, and calculating the comprehensive impact weight coefficient corresponding to the auxiliary parameter based on the environmental impact value of the auxiliary parameter and the normalized values ​​of all flash memory core parameters; and performing a weighted summation calculation on the erase / write cycles and the comprehensive impact weight coefficient of the auxiliary parameter to obtain the normalized weight coefficient.

[0153] Among them, auxiliary parameters can be other inherent technical parameters that reflect the storage performance of flash memory devices, other than the number of erase / write cycles. Auxiliary parameters can include read data speed and write data speed.

[0154] In one embodiment, the environmental impact value of an auxiliary parameter can be calculated based on its real-time test value and its maximum test value at the target ambient temperature by subtracting the real-time test value of the auxiliary parameter from its maximum test value at the target ambient temperature, and then dividing the result of the subtraction by the maximum test value of the auxiliary parameter at the target ambient temperature.

[0155] Among them, the comprehensive impact weighting coefficient can be a dimensionless coefficient that can characterize the contribution of the core parameter to the overall loss of the flash memory device by weighted summation after the normalized values ​​of all flash memory core parameters are corrected for loss based on the environmental impact value of a single core parameter (erasure and write times or a certain auxiliary parameter), and the value range is [0,1].

[0156] In one embodiment, the method for calculating the comprehensive impact weight coefficient corresponding to the number of erase / write cycles based on the environmental impact value of the number of erase / write cycles and the normalized values ​​of all flash memory core parameters can be achieved by subtracting the environmental impact value of the number of erase / write cycles from 1 to obtain the erase / write cycle loss correction coefficient, multiplying the normalized values ​​of each flash memory core parameter by the erase / write cycle loss correction coefficient, and then performing a weighted summation of the multiplication results to obtain the comprehensive impact weight coefficient corresponding to the number of erase / write cycles.

[0157] In one embodiment, the method for calculating the comprehensive impact weight coefficient of the auxiliary parameter based on the environmental impact value of the auxiliary parameter and the normalized value of all flash memory core parameters can be as follows: subtract the environmental impact value of the auxiliary parameter from 1 to obtain the loss correction coefficient of the auxiliary parameter; multiply the normalized value of each flash memory core parameter by the loss correction coefficient of the auxiliary parameter; and perform a weighted summation of the multiplication results to obtain the comprehensive impact weight coefficient of the auxiliary parameter.

[0158] In one embodiment, the normalized weight coefficient is obtained by weighted summation of the combined influence weight coefficients of the number of erase / write cycles and auxiliary parameters. This can be achieved by configuring corresponding contribution weight coefficients for the number of erase / write cycles and each auxiliary parameter, multiplying the number of erase / write cycles and each auxiliary parameter by their corresponding contribution weight coefficients, and then summing all the product results to obtain the normalized weight coefficient.

[0159] The advantage of this approach is that it calculates the environmental impact value for each flash memory core parameter separately, enabling precise quantification of environmental losses for different flash memory core parameters and avoiding the problem that a single environmental impact value cannot fully cover the loss status of multiple parameters.

[0160] S306, the preset value range is divided to obtain multiple weighted sub-ranges, and the target original bit error rate classification threshold list is determined based on the normalized weight coefficients and the multiple weighted sub-ranges.

[0161] S307, obtain the real-time raw bit error rate, and determine the target flash memory level of the flash memory device based on the real-time raw bit error rate and the target raw bit error rate classification threshold list.

[0162] The advantage of this solution is that it quantifies the impact of ambient temperature on flash memory core parameters into an environmental impact value, breaking through the limitations of traditional methods that calculate wear based solely on the numerical values ​​of flash memory core parameters. It accurately reflects the actual usable state of the number of erase / write cycles under the current ambient temperature, making the wear characterization of flash memory core parameters more consistent with the actual operating scenarios of the device and improving the accuracy of parameter characterization.

[0163] Figure 4 This is a flowchart illustrating another flash memory level testing method provided in an embodiment of this application. Figure 4 As shown, the specific steps include the following:

[0164] S401, Obtain the real-time test values ​​corresponding to the flash memory core parameters and test environment parameters of the flash memory device; wherein, the flash memory core parameters include the number of erase / write cycles, and the test environment parameters include temperature parameters.

[0165] S402, obtain the global maximum test value of the flash memory core parameters and the test environment parameters.

[0166] The environmental parameters for testing may also include humidity and air pressure.

[0167] Among them, the global maximum test value of the test environment parameters can be the limit threshold that the flash memory device can withstand for each test environment parameter, which is the upper limit of environmental tolerance calibrated through reliability testing before leaving the factory.

[0168] In one embodiment, the global maximum test value of the test environment parameters can be obtained by retrieving the global maximum test value of the test environment parameters from the manufacturer's technical specifications of the flash memory device or the built-in environment parameter configuration library.

[0169] S403, based on the real-time test values ​​of the flash memory core parameters and the test environment parameters, as well as the global maximum test value, calculate the normalized values ​​of the flash memory core parameters and the test environment parameters.

[0170] In one embodiment, the normalized values ​​of flash memory core parameters and test environment parameters are calculated based on the real-time test values ​​and the global maximum test values ​​of the flash memory core parameters and test environment parameters. This can be achieved by dividing the real-time test value of each flash memory core parameter by the corresponding global maximum test value to obtain the normalized value of each flash memory core parameter, and by dividing the real-time test value of each test environment parameter by the corresponding global maximum test value to obtain the normalized value of each test environment parameter.

[0171] S404, perform a weighted summation of the normalized values ​​of the flash memory core parameters and the test environment parameters to obtain the normalized weight coefficient.

[0172] In one embodiment, the normalized weight coefficient is obtained by weighted summation of the normalized values ​​of the flash memory core parameters and the test environment parameters. This can be achieved by configuring corresponding influence weight coefficients for each flash memory core parameter and each test environment parameter, multiplying each flash memory core parameter and each test environment parameter by their respective influence weight coefficients, and then summing all the product results to obtain the normalized weight coefficient.

[0173] S405, the preset value range is divided to obtain multiple weighted sub-ranges, and the target original bit error rate classification threshold list is determined based on the normalized weight coefficients and the multiple weighted sub-ranges.

[0174] S406, obtain the real-time raw bit error rate, and determine the target flash memory level of the flash memory device based on the real-time raw bit error rate and the target raw bit error rate classification threshold list.

[0175] The advantage of this scheme is that the normalized weighting coefficients comprehensively consider the dual impact of core parameter loss and environmental parameter deviation, making the subsequent matching target original bit error rate classification threshold list more closely match the actual operating status of the device, and significantly improving the accuracy and reliability of flash memory level determination.

[0176] Figure 5 This is a schematic diagram of the structure of a flash memory level testing device provided in an embodiment of this application. Figure 5 As shown, the device includes:

[0177] The parameter acquisition module 510 is used to acquire real-time test values ​​corresponding to the flash memory core parameters and test environment parameters of the flash memory device, respectively; wherein, the flash memory core parameters include the number of erase / write cycles, and the test environment parameters include temperature parameters;

[0178] The weight determination module 520 is used to determine the normalized weight coefficients based on the real-time test values;

[0179] The threshold determination module 530 is used to divide the preset value range to obtain multiple weighted sub-ranges, and determine the target original bit error rate classification threshold list based on the normalized weight coefficient and the multiple weighted sub-ranges.

[0180] The grade determination module 540 is used to obtain the real-time raw bit error rate and determine the target flash memory grade of the flash memory device based on the real-time raw bit error rate and the target raw bit error rate grading threshold list.

[0181] Furthermore, the threshold determination module 530 is specifically used for:

[0182] The preset value range is divided into low loss level range, medium loss level range and high loss level range.

[0183] Based on the preset number of sub-intervals corresponding to the low-loss level interval, the medium-loss level interval, and the high-loss level interval, the low-loss level interval, the medium-loss level interval, and the high-loss level interval are divided into multiple weighted sub-intervals.

[0184] Furthermore, the threshold determination module 530 is specifically used for:

[0185] Based on the logarithmic increasing function and the number of preset sub-intervals corresponding to the low-loss level interval, multiple weighted sub-intervals corresponding to the low-loss level interval are obtained.

[0186] Based on the linearly increasing function and the number of preset sub-intervals corresponding to the intermediate loss level interval, multiple weighted sub-intervals corresponding to the intermediate loss level interval are obtained.

[0187] Based on the exponentially increasing function and the preset number of sub-intervals corresponding to the high-loss level interval, multiple weighted sub-intervals corresponding to the high-loss level interval are obtained.

[0188] Furthermore, the device is also used for:

[0189] Obtain the global maximum test value and the maximum test value at the target ambient temperature of the flash memory core parameters; wherein, the target ambient temperature is equal to the real-time test value of the temperature parameter;

[0190] Accordingly, the weight determination module 520 is specifically used for:

[0191] Based on the real-time test value of the number of erase / write cycles and the maximum test value at the target ambient temperature, the environmental impact value of the number of erase / write cycles is calculated;

[0192] Based on the real-time test values ​​and the global maximum test values ​​of all flash memory core parameters, calculate the normalized values ​​of all flash memory core parameters;

[0193] Based on the environmental impact value of the number of erase / write cycles and the normalized values ​​of all flash memory core parameters, the normalization weight coefficient is determined.

[0194] Furthermore, the core parameters of the flash memory also include auxiliary parameters;

[0195] Accordingly, the device is also used for:

[0196] Based on the real-time test values ​​of the auxiliary parameters and the maximum test values ​​at the target ambient temperature, the environmental impact value of the auxiliary parameters is calculated.

[0197] Accordingly, the weight determination module 520 is specifically used for:

[0198] Based on the environmental impact value of the erase / write count and the normalized value of all flash memory core parameters, calculate the comprehensive impact weight coefficient corresponding to the erase / write count; and based on the environmental impact value of the auxiliary parameter and the normalized value of all flash memory core parameters, calculate the comprehensive impact weight coefficient corresponding to the auxiliary parameter.

[0199] The normalized weight coefficients are obtained by weighted summation of the combined influence of the number of erase / write cycles and the auxiliary parameters.

[0200] Furthermore, the device is also used for:

[0201] Obtain the global maximum test values ​​of the flash memory core parameters and the test environment parameters;

[0202] Accordingly, the weight determination module 520 is specifically used for:

[0203] Based on the real-time test values ​​of the flash memory core parameters and the test environment parameters, as well as the global maximum test value, the normalized values ​​of the flash memory core parameters and the test environment parameters are calculated.

[0204] The normalized values ​​of the flash memory core parameters and the test environment parameters are weighted and summed to obtain the normalized weight coefficients.

[0205] Furthermore, the device is also used for:

[0206] Based on the normalized weight coefficients and the multiple weight sub-intervals, a target grading threshold list for the flash memory core parameters and the test environment parameters is determined.

[0207] Accordingly, the level determination module 540 is specifically used for:

[0208] The component flash memory level corresponding to the original bit error rate is determined based on the real-time original bit error rate and the target original bit error rate classification threshold list. The component flash memory level corresponding to the flash memory core parameters and the test environment parameters is determined based on the real-time test values ​​of the flash memory core parameters and the test environment parameters and the target classification threshold list.

[0209] The target flash memory level of the flash memory device is obtained by weighted summation of the original bit error rate, the flash memory core parameters, and the component flash memory levels corresponding to the test environment parameters.

[0210] In this embodiment, a parameter acquisition module is used to acquire real-time test values ​​corresponding to the flash memory core parameters and test environment parameters of the flash memory device, respectively; wherein, the flash memory core parameters include the number of erase / write cycles, and the test environment parameters include temperature parameters; a weight determination module is used to determine a normalized weight coefficient based on the real-time test values; a threshold determination module is used to divide a preset value range to obtain multiple weighted sub-ranges, and determine a target raw bit error rate (BER) grading threshold list based on the normalized weight coefficients and the multiple weighted sub-ranges; a grade determination module is used to acquire the real-time raw BER and determine the target flash memory grade of the flash memory device based on the real-time raw BER and the target raw BER grading threshold list. The above-mentioned flash memory grade testing device comprehensively considers the dynamic influence of flash memory core parameters and test environment parameters to construct a real-time dynamic grading method, achieving accurate determination of the flash memory grade of the flash memory device.

[0211] The flash memory level testing device in this application embodiment can be a device, or a component, integrated circuit, or chip in a terminal. The device can be a mobile electronic device or a non-mobile electronic device. For example, mobile electronic devices can be mobile phones, tablets, laptops, PDAs, in-vehicle electronic devices, wearable devices, ultra-mobile personal computers (UMPCs), netbooks, or personal digital assistants (PDAs), etc., while non-mobile electronic devices can be servers, network-attached storage (NAS), personal computers (PCs), televisions (TVs), ATMs, or self-service machines, etc. This application embodiment does not impose specific limitations.

[0212] The flash memory level testing device in this application embodiment can be a device with an operating system. This operating system can be Android, iOS, or other possible operating systems; this application embodiment does not specifically limit it.

[0213] The flash memory level testing device provided in this application embodiment can realize the various processes implemented in the above embodiments. To avoid repetition, it will not be described again here.

[0214] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. For example... Figure 6 As shown, this application embodiment also provides an electronic device 600, including a processor 601, a memory 602, and a program or instructions stored in the memory 602 and executable on the processor 601. When the program or instructions are executed by the processor 601, they implement the various processes of the above-described flash memory level testing method embodiment and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0215] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0216] This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the above-described flash memory level testing method embodiments and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0217] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0218] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0219] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0220] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

[0221] The above description is merely a preferred embodiment and the technical principles employed in this application. This application is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions that can be made by those skilled in the art will not depart from the scope of protection of this application. Therefore, although this application has been described in detail through the above embodiments, this application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of this application, the scope of which is determined by the scope of the claims.

Claims

1. A flash memory level testing method, characterized in that, The method includes: The system acquires real-time test values ​​corresponding to the flash memory core parameters and test environment parameters of the flash memory device; wherein, the flash memory core parameters include the number of erase / write cycles, and the test environment parameters include temperature parameters. Obtain the global maximum test values ​​of the flash memory core parameters and the test environment parameters; The normalized weighting coefficients are determined based on the real-time test values; The step of determining the normalized weight coefficient based on the real-time test value includes: calculating the normalized value of the flash core parameter and the test environment parameter based on the real-time test value of the flash core parameter and the test environment parameter and the global maximum test value; and performing a weighted summation of the normalized value of the flash core parameter and the test environment parameter to obtain the normalized weight coefficient. The preset value range is divided into multiple weighted sub-ranges. Based on the normalized weight coefficients and the multiple weighted sub-ranges, a target original bit error rate classification threshold list is determined. Based on the normalized weight coefficients and the multiple weight sub-intervals, a target grading threshold list for the flash memory core parameters and the test environment parameters is determined. The real-time raw bit error rate is obtained, and the target flash memory level of the flash memory device is determined based on the real-time raw bit error rate and the target raw bit error rate classification threshold list; The step of determining the target flash memory level of the flash memory device based on the real-time raw bit error rate and the target raw bit error rate classification threshold list includes: determining the component flash memory level corresponding to the raw bit error rate based on the real-time raw bit error rate and the target raw bit error rate classification threshold list; and determining the component flash memory level corresponding to the flash memory core parameters and the test environment parameters based on the real-time test values ​​of the flash memory core parameters and the test environment parameters and the target classification threshold list; and performing a weighted summation calculation on the raw bit error rate, the flash memory core parameters, and the component flash memory levels corresponding to the test environment parameters to obtain the target flash memory level of the flash memory device.

2. The flash memory level testing method according to claim 1, characterized in that, The process of dividing the preset value range into multiple weighted sub-ranges includes: The preset value range is divided into low loss level range, medium loss level range and high loss level range. Based on the preset number of sub-intervals corresponding to the low-loss level interval, the medium-loss level interval, and the high-loss level interval, the low-loss level interval, the medium-loss level interval, and the high-loss level interval are divided into multiple weighted sub-intervals.

3. The flash memory level testing method according to claim 2, characterized in that, Based on the preset number of sub-intervals corresponding to the low-loss level interval, the medium-loss level interval, and the high-loss level interval, the low-loss level interval, the medium-loss level interval, and the high-loss level interval are respectively divided to obtain multiple weighted sub-intervals, including: Based on the logarithmic increasing function and the number of preset sub-intervals corresponding to the low-loss level interval, multiple weighted sub-intervals corresponding to the low-loss level interval are obtained. Based on the linearly increasing function and the number of preset sub-intervals corresponding to the intermediate loss level interval, multiple weighted sub-intervals corresponding to the intermediate loss level interval are obtained. Based on the exponentially increasing function and the preset number of sub-intervals corresponding to the high-loss level interval, multiple weighted sub-intervals corresponding to the high-loss level interval are obtained.

4. The flash memory level testing method according to claim 1, characterized in that, After obtaining the real-time test values ​​corresponding to the flash memory core parameters and test environment parameters of the flash memory device, the method further includes: Obtain the global maximum test value and the maximum test value at the target ambient temperature of the flash memory core parameters; wherein, the target ambient temperature is equal to the real-time test value of the temperature parameter; Accordingly, determining the normalized weight coefficients based on the real-time test values ​​includes: Based on the real-time test value of the number of erase / write cycles and the maximum test value at the target ambient temperature, the environmental impact value of the number of erase / write cycles is calculated; Based on the real-time test values ​​and the global maximum test values ​​of all flash memory core parameters, calculate the normalized values ​​of all flash memory core parameters; Based on the environmental impact value of the number of erase / write cycles and the normalized values ​​of all flash memory core parameters, the normalization weight coefficient is determined.

5. The flash memory level testing method according to claim 4, characterized in that, The core parameters of the flash memory also include auxiliary parameters; Accordingly, before determining the normalization weighting coefficients based on the environmental impact value of the erase / write cycles and the normalized values ​​of all flash memory core parameters, the method further includes: Based on the real-time test values ​​of the auxiliary parameters and the maximum test values ​​at the target ambient temperature, the environmental impact value of the auxiliary parameters is calculated. Accordingly, the determination of normalization weighting coefficients based on the environmental impact value of the erase / write cycles and the normalized values ​​of all flash memory core parameters includes: Based on the environmental impact value of the erase / write count and the normalized value of all flash memory core parameters, calculate the comprehensive impact weight coefficient corresponding to the erase / write count; and based on the environmental impact value of the auxiliary parameter and the normalized value of all flash memory core parameters, calculate the comprehensive impact weight coefficient corresponding to the auxiliary parameter. The normalized weight coefficients are obtained by weighted summation of the combined influence of the number of erase / write cycles and the auxiliary parameters.

6. A flash memory level testing device, characterized in that, The device includes: The parameter acquisition module is used to acquire real-time test values ​​corresponding to the flash memory core parameters and test environment parameters of the flash memory device; wherein, the flash memory core parameters include the number of erase / write cycles, and the test environment parameters include temperature parameters; The weight determination module is used to determine the normalized weight coefficients based on the real-time test values; The threshold determination module is used to divide the preset value range to obtain multiple weighted sub-ranges, and determine the target original bit error rate classification threshold list based on the normalized weight coefficient and the multiple weighted sub-ranges. The level determination module is used to obtain the real-time raw bit error rate and determine the target flash memory level of the flash memory device based on the real-time raw bit error rate and the target raw bit error rate classification threshold list; The device is also used to: obtain the global maximum test value of the flash memory core parameters and the test environment parameters; The weight determination module is specifically used for: calculating the normalized values ​​of the flash memory core parameters and the test environment parameters based on the real-time test values ​​of the flash memory core parameters and the test environment parameters, as well as the global maximum test value; and performing a weighted summation calculation on the normalized values ​​of the flash memory core parameters and the test environment parameters to obtain the normalized weight coefficients. The device is also used to: determine a target grading threshold list for the flash memory core parameters and the test environment parameters based on the normalized weight coefficients and the plurality of weight sub-intervals; The level determination module is specifically used for: determining the component flash memory level corresponding to the original bit error rate based on the real-time original bit error rate and the target original bit error rate classification threshold list; and determining the component flash memory level corresponding to the flash memory core parameters and the test environment parameters based on the real-time test values ​​of the flash memory core parameters and the test environment parameters and the target classification threshold list; and performing a weighted summation calculation on the original bit error rate, the flash memory core parameters, and the component flash memory levels corresponding to the test environment parameters to obtain the target flash memory level of the flash memory device.

7. An electronic device, characterized in that, It includes a processor, a memory, and a program or instructions stored on the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the flash memory level testing method as described in any one of claims 1-5.

8. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions that, when executed by a processor, implement the flash memory level testing method as described in any one of claims 1-5.

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