A method and apparatus for calculating Rdson in real time
By acquiring and processing voltage Vds and current Ids data in real time, forming a two-dimensional array and filtering it to eliminate unstable points, the problem of low Rdson calculation accuracy in existing technologies is solved, and real-time and accurate Rdson measurement is realized.
Patent Information
- Application Number
- CN202610681172.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-05-18
- Publication Date
- 2026-06-16
AI Technical Summary
Existing technologies cannot achieve high-speed dynamic data acquisition, resulting in low Rdson calculation accuracy, inability to identify stable segments, and inability to measure Rdson in real time.
By collecting voltage Vds and current Ids data in real time, forming a two-dimensional array, performing data processing and filtering, calculating the average value of the Rdson array, eliminating unstable points, and obtaining the final Rdson value.
It enables real-time calculation of Rdson, improves calculation accuracy, and provides reliability data support for semiconductor power devices.
Smart Images
Figure CN122218443A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to semiconductor testing technology, and more particularly to a method and apparatus for real-time calculation of Rdson. Background Technology
[0002] Rdson, or drain-source on-resistance, is the equivalent resistance between the drain and source of a power MOSFET (including SiC MOSFETs) in the on-state. Its value is typically between tens and hundreds of milliohms. It directly determines the device's conduction loss (P = I² × Rds(on)) and heat generation, and is a key indicator for measuring system efficiency and thermal design.
[0003] For SiC devices, the material advantages enable them to maintain extremely low Rds(on) even at high voltages, thereby significantly improving system efficiency and reducing heat generation.
[0004] Rdson has a significant positive temperature coefficient, meaning its resistance increases with increasing junction temperature. This characteristic not only enables automatic current sharing in parallel devices but also allows it to be used as a temperature-sensitive electrical parameter to indirectly estimate chip junction temperature. Furthermore, its long-term variation is an important health indicator for assessing device aging and predicting failure. Therefore, real-time measurement of Rdson has significant practical implications. Summary of the Invention
[0005] This invention addresses the problems of existing technologies, such as the inability to achieve high-speed dynamic data acquisition and the fact that existing methods calculate the average Rdson by dividing the voltage and current of a fixed segment, resulting in low accuracy and the inability to identify stable segments. The invention provides a method and apparatus for real-time calculation of Rdson.
[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: A method for real-time calculation of Rdson, comprising: The acquisition of voltage Vds data and current Ids data involves real-time acquisition of n rows of voltage Vds data and n rows of current Ids data, which together form a two-dimensional array A[n][2]. The processing of the two-dimensional array A[n][2] involves iterating through the first column Vds[i] data, comparing each Vds value with the first voltage threshold H. If the first column Vds[i] data is less than the first voltage threshold H, then the voltage Vds data of Vds[i] and the current Ids data of Ids[i] are retained, along with the array index T. After iterating through all the first column Vds[i] data, a two-dimensional array B[p][3] is formed, where the first column data is the voltage Vds data, the second column data is the current Ids data, and the third column data is the array index data; p is the number of rows of data, and p is less than n. The processing of array B[p][3] involves iterating through the third column of B[p][3]. If T[i] - T[i-1] is greater than the second threshold K, then T[i-1] is retained, and T[i-1] forms a one-dimensional array C[j], where j is the number of data. The interpolation process for array C[j] involves inserting 0 before the first element of array C[j] and inserting the value p after the last element of array C[j] to form a new array C1[j+2]. Starting from the second element of array C1[j+2], iterate through the array sequentially, subtract the previous element C1[i-1] from each element C1[i] to obtain the difference Δh, and given the interval range [x, y] of the index, process the element C1[i] of array C1[j+2] to obtain 2 new elements, and combine the 2 new elements to form a new array C2[j+2]. Take out C2[j+2] in groups of two to get a set of index intervals. Take out all the elements in the two-dimensional array B[p][3] according to this index interval. After filtering all Vds and Ids in this interval, we get the filtered voltage Vds' and filtered current Ids'. Based on the filtered voltage Vds' and filtered current Ids', we get the Rdson array. Calculate the average value of the Rdson array to get the Rdson average value. By analogy, we can get the corresponding Rdson value of all index intervals. Based on the corresponding Rdson value of all index intervals, we construct the corresponding Rdson array Rdson[m] of all index intervals. The Rdson array Rdson[m] is filtered by iterating through the data in the Rdson array Rdson[m]. The difference between Rdson[k] and Rdson[k-1] is compared with the third threshold L. If the difference is less than the third threshold L, the data corresponding to Rdson[k] is filtered. After the last element less than the threshold L is found, its index is incremented by 1, which is the number of unstable points to be removed from the Rdson array, thus generating the filtered Rdson array Rdson[z]. The average value of the filtered Rdson array Rdson[z] is calculated to obtain the final output Rdson. finish .
[0007] To address the aforementioned technical problems, the present invention also provides a method for real-time calculation of Rdson, the method comprising: The acquisition of voltage Vds data and current Ids data involves real-time acquisition of n rows of voltage Vds data and n rows of current Ids data, which together form a two-dimensional array A[n][2]. The processing of the two-dimensional array A[n][2] involves iterating through the second column Ids[i] data, comparing each Vds value with the first voltage threshold H. If the second column Ids[i] data is greater than the fourth current threshold I, then the voltage Vds data and the current Ids data of Vds[i] are retained, along with the array index T. After iterating through all the first column Vds[i] data, a two-dimensional array B[p][3] is formed, where the first column data is the voltage Vds data, the second column data is the current Ids data, and the third column data is the array index data; p is the number of rows of data, and p is less than n. The processing of array B[p][3] involves iterating through the third column of B[p][3]. If T[i] - T[i-1] is greater than the second threshold K, then T[i-1] is retained, and T[i-1] forms a one-dimensional array C[j], where j is the number of data. The interpolation process for array C[j] involves inserting 0 before the first element of array C[j] and inserting the value p after the last element of array C[j] to form a new array C1[j+2]. Starting from the second element of array C1[j+2], iterate through the array sequentially, subtract the previous element C1[i-1] from each element C1[i] to obtain the difference Δh, and given the interval range [x, y] of the index, process the element C1[i] of array C1[j+2] to obtain 2 new elements, and combine the 2 new elements to form a new array C2[j+2]. Take out C2[j+2] in groups of two to get a set of index intervals. Take out all the elements in the two-dimensional array B[p][3] according to this index interval. After filtering all Vds and Ids in this interval, we get the filtered voltage Vds' and filtered current Ids'. Based on the filtered voltage Vds' and filtered current Ids', we get the Rdson array. Calculate the average value of the Rdson array to get the Rdson average value. By analogy, we can get the corresponding Rdson value of all index intervals. Based on the corresponding Rdson value of all index intervals, we construct the corresponding Rdson array Rdson[m] of all index intervals. The Rdson array Rdson[m] is filtered by iterating through the data in the Rdson array Rdson[m]. The difference between Rdson[k] and Rdson[k-1] is compared with the third threshold L. If the difference is less than the third threshold L, the data corresponding to Rdson[k] is filtered. After the last element less than the threshold L is found, its index is incremented by 1, which is the number of unstable points to be removed from the Rdson array, thus generating the filtered Rdson array Rdson[z]. The average value of the filtered Rdson array Rdson[z] is calculated to obtain the final output Rdson. finish .
[0008] As a preferred approach, the element C1[i] of array C1[j+2] is processed to obtain two new elements: the first new element is △h*x+C1[i-1], which is rounded down; the second new element is △h*y+C1[i-1], which is rounded down. Thus, the first new element after rounding down and the second new element after rounding down are combined to form a new array C2[j+2]. To address the aforementioned technical problems, the present invention also provides an apparatus for real-time calculation of Rdson, which is used to implement a method for real-time calculation of Rdson.
[0009] This invention, by adopting the above technical solutions, has significant technical effects: This invention can collect data and calculate Rdson in real time. This invention improves the accuracy of Rdson calculation by determining the stable segment based on multiple waveforms of a single data acquisition.
[0010] This invention provides real-time Rdson variation trends for semiconductor power devices during DHTOL testing, providing data support for device reliability.
[0011] The method designed in this invention can perform real-time dynamic calculation of Rdson on the collected raw data, with high accuracy and speed. Attached Figure Description
[0012] Figure 1 This is a data graph collected in Embodiment 4 of the present invention.
[0013] Figure 2 This is a data graph showing the processed data obtained in this invention.
[0014] Figure 3 This is a flowchart of the present invention. Detailed Implementation
[0015] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments.
[0016] Example 1
[0017] A method for real-time calculation of Rdson, comprising: The acquisition of voltage Vds data and current Ids data involves real-time acquisition of n rows of voltage Vds data and n rows of current Ids data, which together form a two-dimensional array A[n][2]. The processing of the two-dimensional array A[n][2] involves iterating through the first column Vds[i] data, comparing each Vds value with the first voltage threshold H. If the first column Vds[i] data is less than the first voltage threshold H, then the voltage Vds data of Vds[i] and the current Ids data of Ids[i] are retained, along with the array index T. After iterating through all the first column Vds[i] data, a two-dimensional array B[p][3] is formed, where the first column data is the voltage Vds data, the second column data is the current Ids data, and the third column data is the array index data; p is the number of rows of data, and p is less than n. The processing of array B[p][3] involves iterating through the third column of B[p][3]. If T[i] - T[i-1] is greater than the second threshold K, then T[i-1] is retained, and T[i-1] forms a one-dimensional array C[j], where j is the number of data. The interpolation process for array C[j] involves inserting 0 before the first element of array C[j] and inserting the value p after the last element of array C[j] to form a new array C1[j+2]. Starting from the second element of array C1[j+2], iterate through the array sequentially, subtract the previous element C1[i-1] from each element C1[i] to obtain the difference Δh, and given the interval range [x, y] of the index, process the element C1[i] of array C1[j+2] to obtain 2 new elements, and combine the 2 new elements to form a new array C2[j+2]. Take out C2[j+2] in groups of two to get a set of index intervals. Take out all the elements in the two-dimensional array B[p][3] according to this index interval. After filtering all Vds and Ids in this interval, we get the filtered voltage Vds' and filtered current Ids'. Based on the filtered voltage Vds' and filtered current Ids', we get the Rdson array. Calculate the average value of the Rdson array to get the Rdson average value. By analogy, we can get the corresponding Rdson value of all index intervals. Based on the corresponding Rdson value of all index intervals, we construct the corresponding Rdson array Rdson[m] of all index intervals. The Rdson array Rdson[m] is filtered by iterating through the data in the Rdson array Rdson[m]. The difference between Rdson[k] and Rdson[k-1] is compared with the third threshold L. If the difference is less than the third threshold L, the data corresponding to Rdson[k] is filtered. After the last element less than the threshold L is found, its index is incremented by 1, which is the number of unstable points to be removed from the Rdson array, thus generating the filtered Rdson array Rdson[z]. The average value of the filtered Rdson array Rdson[z] is calculated to obtain the final output Rdson. finish .
[0018] Process the element C1[i] of array C1[j+2] to obtain two new elements: the first new element is △h*x+C1[i-1], which is rounded down; the second new element is △h*y+C1[i-1], which is rounded down. The first new element after rounding down and the second new element after rounding down are combined to form a new array C2[j+2].
[0019] Example 2
[0020] Unlike Example 1, this embodiment provides a method for real-time calculation of Rdson, which includes: The acquisition of voltage Vds data and current Ids data involves real-time acquisition of n rows of voltage Vds data and n rows of current Ids data, which together form a two-dimensional array A[n][2]. The processing of the two-dimensional array A[n][2] involves iterating through the second column Ids[i] data, comparing each Vds value with the first voltage threshold H. If the second column Ids[i] data is greater than the fourth current threshold I, then the voltage Vds data and the current Ids data of Vds[i] are retained, along with the array index T. After iterating through all the first column Vds[i] data, a two-dimensional array B[p][3] is formed, where the first column data is the voltage Vds data, the second column data is the current Ids data, and the third column data is the array index data; p is the number of rows of data, and p is less than n. The processing of array B[p][3] involves iterating through the third column of B[p][3]. If T[i] - T[i-1] is greater than the second threshold K, then T[i-1] is retained, and T[i-1] forms a one-dimensional array C[j], where j is the number of data. The interpolation process for array C[j] involves inserting 0 before the first element of array C[j] and inserting the value p after the last element of array C[j] to form a new array C1[j+2]. Starting from the second element of array C1[j+2], iterate through the array sequentially, subtract the previous element C1[i-1] from each element C1[i] to obtain the difference Δh, and given the interval range [x, y] of the index, process the element C1[i] of array C1[j+2] to obtain 2 new elements, and combine the 2 new elements to form a new array C2[j+2]. Take out C2[j+2] in groups of two to get a set of index intervals. Take out all the elements in the two-dimensional array B[p][3] according to this index interval. After filtering all Vds and Ids in this interval, get the filtered voltage Vds' and filtered current Ids'. Get the Rdson array based on the filtered voltage Vds' and filtered current Ids'. Get the corresponding Rdson array Rdson[m] for all index intervals based on the Rdson array. The Rdson array Rdson[m] is filtered by comparing the difference between the data Rdson[k] and Rdson[k-1] in the Rdson array Rdson[m] with the third threshold L. If the difference is less than the third threshold L, the data corresponding to Rdson[k] is filtered to generate the filtered Rdson array Rdson[z]. The average value of the filtered Rdson array Rdson[z] is calculated to obtain the final output Rdson. finish .
[0021] Process the element C1[i] of array C1[j+2] to obtain two new elements: the first new element is △h*x+C1[i-1], which is rounded down; the second new element is △h*y+C1[i-1], which is rounded down. The first new element after rounding down and the second new element after rounding down are combined to form a new array C2[j+2].
[0022] Example 3
[0023] This embodiment is a device for real-time calculation of Rdson, which is used to implement a method for real-time calculation of Rdson.
[0024] Example 4
[0025] Based on the above embodiments, this embodiment applies a 100kHz excitation signal to the GS terminal of the device under test (DUT) to drive the DS terminal to turn on and off. A high-speed oscilloscope is used to acquire the Vds and Ids signals of the DS terminal within a 160µs sampling time at a sampling rate of 12.5M / s. Since Vds is clamped to about 2.4V when the device is off and drops to about 0.3V when it is on, the curve shows that the current rises when the device is on and stabilizes after several on-off cycles.
[0026] By performing real-time Rdson calculation on the curve data, it is necessary to calculate the average Rdson within a given calculation interval after the current stabilizes. For example, after stabilizing for 3 cycles, it is necessary to calculate the average Rdson in each segment [20%, 80%]. The average of several Rdson values is then used as the real-time Rdson of the current data acquisition.
[0027] Figure 1 As shown, the original data collected this time is A
[2000] [2], which has 2 columns and 2000 data points in each column, namely Vds
[2000] and Ids
[2000] ; Process array A
[2000] [2], taking the first voltage threshold H as 2V, compare the index data of column Vds[i] in array A
[2000] [2] with the first voltage threshold H2V, retain Vds[i] and the corresponding Ids[i] below 2V, and also retain the index i in the array where the current Vds[i] is located. After all Vds[i] are traversed, a new array B
[968] [3] is formed. Array B has 968 rows and 3 columns of data, namely Vds, Ids and index i; plot the values as follows. Figure 2 As shown, the x-axis represents the sequence number i.
[0028] The array B
[968] [3] is processed. The index i of the third column of the array B
[968] [3] is traversed. The current index is subtracted from the previous index. The second threshold K is taken. The threshold K=5. The difference is compared with the threshold K. If it is greater than the threshold 5, the previous numerical index is retained. After the traversal is completed, a one-dimensional array C1[7] is formed, which has 7 data. The array C contains the following elements: {125,250,375,501,627,754,879}. The array C is interpolated. 0 is inserted before the first element and the value p=968 in step two is inserted after the last element to form a new array C2[9], which contains the following elements: {0,125,250,375,501,627,754,879,968}. To process array C1[7], starting from the second element of array C1[7], iterate through the array sequentially. Subtract the previous element C1[i-1] from each element C1[i] to obtain the difference △h. For example, starting from the second element, subtract the previous element to obtain the difference △h=125, with a range of [20%, 80%]. Process the current C1 array element C1[2] to obtain two new elements. The calculation method is as follows: the new element 1 is 125*20%+the previous element C1[1]=0. After the nearest integer is rounded down to 25, the new element 2 is 125*80%+the previous element C1[1]=0. After the nearest integer is rounded down to 100, the new elements obtained after the above processing of all elements of array C1 are combined into a new array C2
[16] , which has 16 elements. The elements are as follows: {25,100,150,225,275,350,400,476,526,602,652,729,779,854,897,950}; The arrays C2[9] and B
[968] [3] are processed. The array C2[9] is extracted in pairs to form an index range. For example, the index range [25,100] is formed after the first two elements are extracted. The array B
[968] [3] is extracted according to this index range. All the elements in the range are extracted. After filtering all the Vds and Ids in this range, new Vds' and Ids' are obtained respectively. Each Vds' and its corresponding Ids' are processed. Dividing Ids' by the Rdson array, and then calculating the average of the Rdson arrays within that segment, gives the Rdson value for that segment. After calculation, Rdson = 1.38391Ω. By analogy, the corresponding Rdson values for all index intervals can be obtained, which are {1.38391, 0.750803, 0.634748, 0.598454, 0.574114, 0.55824, 0.551345, 0.550339}. Multiple Rdson values are obtained. Depending on the needs, the average of these Rdson values can be calculated, or the average of the remaining values after filtering the first n values can be calculated. If the average of all elements is calculated, the final Rdson value is 0.70. Since the device current is not actually stable in the waveforms of the first few cycles, it is normal to discard the first few waveforms and then calculate the average of the remaining Rdson values. This makes the data more stable. Stability analysis is performed using the discrete differential method, as follows: Subtract the previous value from each subsequent Rdson value to obtain a difference array, with elements { Given the array -0.633107, -0.116055, -0.036294, -0.02434, -0.015874, -0.006895, a threshold is applied to each element of the difference. The threshold L is -0.06. Elements less than the threshold L are considered unstable. The last element less than the threshold L is -0.116055, and its array index is 2. Adding 1 to its index gives the number of unstable points that need to be removed from the Rdson array, which is 3. In other words, the first 3 Rdson values are unstable points that need to be removed.
[0029] After removing the first three unstable points from the Rdson array, the average value of the remaining data is calculated to obtain Rdson=0.57, which is the real-time Rdson value for that time. Repeating the above steps can realize the calculation of each data collection and achieve the function of real-time Rdson calculation.
Claims
1. A method for real-time calculation of Rdson, characterized in that the method... include: The acquisition of voltage Vds data and current Ids data involves real-time acquisition of n rows of voltage Vds data and n rows of current Ids data, which together form a two-dimensional array A[n][2]. The processing of the two-dimensional array A[n][2] involves iterating through the first column Vds[i] data, comparing each Vds value with the first voltage threshold H. If the first column Vds[i] data is less than the first voltage threshold H, then the voltage Vds data of Vds[i] and the current Ids data of Ids[i] are retained, along with the array index T. After iterating through all the first column Vds[i] data, a two-dimensional array B[p][3] is formed, where the first column data is the voltage Vds data, the second column data is the current Ids data, and the third column data is the array index data; p is the number of rows of data, and p is less than n. The processing of array B[p][3] involves iterating through the third column of B[p][3]. If T[i] - T[i-1] is greater than the second threshold K, then T[i-1] is retained, and T[i-1] forms a one-dimensional array C[j], where j is the number of data. The interpolation process for array C[j] involves inserting 0 before the first element of array C[j] and inserting the value p after the last element of array C[j] to form a new array C1[j+2]. Starting from the second element of array C1[j+2], iterate through the array sequentially, subtract the previous element C1[i-1] from each element C1[i] to obtain the difference Δh, and given the interval range [x, y] of the index, process the element C1[i] of array C1[j+2] to obtain 2 new elements, and combine the 2 new elements to form a new array C2[j+2]. Take out C2[j+2] in groups of two to get a set of index intervals. Take out all the elements in the two-dimensional array B[p][3] according to this index interval. After filtering all Vds and Ids in this interval, we get the filtered voltage Vds' and filtered current Ids'. Based on the filtered voltage Vds' and filtered current Ids', we get the Rdson array. Calculate the average value of the Rdson array to get the Rdson average value. By analogy, we can get the corresponding Rdson value for all index intervals. Based on the corresponding Rdson value for all index intervals, we construct the corresponding Rdson array Rdson[m] for all index intervals. The Rdson array Rdson[m] is filtered by iterating through the data in the Rdson array Rdson[m]. The difference between Rdson[k] and Rdson[k-1] is compared with the third threshold L. If the difference is less than the third threshold L, the data corresponding to Rdson[k] is filtered. When the last element less than the threshold L is found, its index is incremented by 1, which is the number of unstable points that need to be removed from the Rdson array, thus generating the filtered Rdson array Rdson[z]. The average value of the filtered Rdson array Rdson[z] is calculated to obtain the final output Rdson. finish .
2. A method for real-time calculation of Rdson, characterized in that the method... include: The acquisition of voltage Vds data and current Ids data involves real-time acquisition of n rows of voltage Vds data and n rows of current Ids data, which together form a two-dimensional array A[n][2]. The processing of the two-dimensional array A[n][2] involves iterating through the second column Ids[i] data, comparing each Vds value with the first voltage threshold H. If the second column Ids[i] data is greater than the fourth current threshold I, then the voltage Vds data and the current Ids data of Vds[i] are retained, along with the array index T. After iterating through all the first column Vds[i] data, a two-dimensional array B[p][3] is formed, where the first column data is the voltage Vds data, the second column data is the current Ids data, and the third column data is the array index data; p is the number of rows of data, and p is less than n. The processing of array B[p][3] involves iterating through the third column of B[p][3]. If T[i] - T[i-1] is greater than the second threshold K, then T[i-1] is retained, and T[i-1] forms a one-dimensional array C[j], where j is the number of data. The interpolation process for array C[j] involves inserting 0 before the first element of array C[j] and inserting the value p after the last element of array C[j] to form a new array C1[j+2]. Starting from the second element of array C1[j+2], iterate through the array sequentially, subtract the previous element C1[i-1] from each element C1[i] to obtain the difference Δh, and given the interval range [x, y] of the index, process the element C1[i] of array C1[j+2] to obtain 2 new elements, and combine the 2 new elements to form a new array C2[j+2]. Take out C2[j+2] in groups of two to get a set of index intervals. Take out all the elements in the two-dimensional array B[p][3] according to this index interval. After filtering all Vds and Ids in this interval, we get the filtered voltage Vds' and filtered current Ids'. Based on the filtered voltage Vds' and filtered current Ids', we get the Rdson array. Calculate the average value of the Rdson array to get the Rdson average value. By analogy, we can get the corresponding Rdson value of all index intervals. Based on the corresponding Rdson value of all index intervals, we construct the corresponding Rdson array Rdson[m] of all index intervals. The Rdson array Rdson[m] is filtered by iterating through the data in the Rdson array Rdson[m]. The difference between Rdson[k] and Rdson[k-1] is compared with the third threshold L. If the difference is less than the third threshold L, the data corresponding to Rdson[k] is filtered. After the last element less than the threshold L is found, its index is incremented by 1, which is the number of unstable points to be removed from the Rdson array, thus generating the filtered Rdson array Rdson[z]. The average value of the filtered Rdson array Rdson[z] is calculated to obtain the final output Rdson. finish .
3. A method for real-time calculation of Rdson according to claim 1 or 2, characterized in that, Process the element C1[i] of array C1[j+2] to obtain two new elements: the first new element is △h*x+C1[i-1], which is rounded down; the second new element is △h*y+C1[i-1], which is rounded down. The first new element after rounding down and the second new element after rounding down are combined to form a new array C2[j+2].
4. A device for real-time calculation of Rdson, characterized in that, Apparatus for implementing a method for real-time calculation of Rdson as described in any one of claims 1-3.