Method, system and equipment for evaluating total dose effect of analog-to-digital converter and medium

Abstract

The invention provides an analog-to-digital converter total dose effect evaluation method, system and device and a medium, and relates to the technical field of space environment effects, and the method comprises the steps: obtaining a total dose effect parameter; generating a behavior level evaluation model of the analog-to-digital converter according to the total dose effect parameter in combination with an initial evaluation model of the analog-to-digital converter; carrying out analogue simulation on the behavior level evaluation model to obtain simulation data under the action of the total dose effect; and generating a total dose effect evaluation report of the analog-to-digital converter according to the simulation data. According to the invention, the evaluation efficiency and precision of the total dose effect of the analog-to-digital converter are improved.

Description

Technical Field

[0001] This invention relates to the field of space environment effects technology, and more specifically, to a method, system, device, and medium for assessing the total dose effect of an analog-to-digital converter. Background Technology

[0002] Analog-to-digital converters (ADCs) are core components in aerospace electronic equipment, especially successive approximation register (SAR-ADCs), which are widely used in data acquisition, sensor signal processing, and system control. Their performance directly determines the data reliability of aerospace missions. Since high-energy particle sources such as cosmic and solar radiation can affect ADCs in the form of total dose effects, it is necessary to accurately assess their performance changes under radiation environments during the ADC design phase.

[0003] In related technologies, traditional evaluation methods often rely on complex physical models. While physical-level modeling can characterize radiation damage mechanisms, its modeling process is complex and its simulation efficiency is extremely low. It relies on a large number of device physical parameters, making it difficult to adapt to the design requirements of rapid iteration of aerospace electronic equipment, and it cannot support the radiation performance evaluation of large-scale circuits. Summary of the Invention

[0004] The problem addressed by this invention is how to improve the efficiency and accuracy of evaluating the radiation performance of analog-to-digital converters.

[0005] To address the above problems, this invention provides a method, system, device, and medium for evaluating the total dose effect of an analog-to-digital converter.

[0006] In a first aspect, the present invention provides a method for assessing the total dose effect of an analog-to-digital converter, comprising: Obtain the total dose-effect parameters; Based on the total dose-effect parameters and the initial evaluation model of the analog-to-digital converter, a behavioral-level evaluation model of the analog-to-digital converter is generated. The behavioral-level assessment model was simulated to obtain simulation data under the total dose effect; Based on the simulation data, a total dose effect assessment report of the analog-to-digital converter is generated.

[0007] Optionally, obtaining the total dose-effect parameter includes: Based on the orbit type, on-orbit duration, and device shielding conditions of the space mission in which the analog-to-digital converter is located, the total cumulative dose is estimated. Based on the total dose cumulative estimate and the mechanism of the total dose effect on semiconductor devices, the total dose effect parameters are obtained. The total dose effect parameters include threshold voltage offset, gate-source voltage, initial threshold voltage, input-to-physical-size change, input-to-initial-physical-size change, load resistance change, and initial load resistance.

[0008] Optionally, the initial evaluation model includes a comparator for the analog-to-digital converter; generating a behavioral-level evaluation model for the analog-to-digital converter based on the total dose-effect parameters and the initial evaluation model includes: The comparator model behavior in the initial evaluation model is modified based on the total dose effect parameters to obtain the comparator offset voltage of the analog-to-digital converter; Based on the comparator offset voltage, a comparator bias reflecting the influence of radiation effects is added to the initial evaluation model to obtain the behavioral-level evaluation model.

[0009] Optionally, modifying the comparator model behavior in the initial evaluation model based on the total dose-effect parameters to obtain the comparator offset voltage of the analog-to-digital converter includes: The threshold voltage drift is determined based on the threshold voltage offset and the initial threshold voltage in the total dose-effect parameters; The relative size mismatch rate is determined based on the input-to-physical-size change and the input-to-initial-physical-size in the total dose-effect parameters. The relative resistance mismatch rate is calculated based on the load resistance change and the initial load resistance in the total dose effect parameters. The comparator offset voltage is obtained based on the threshold voltage drift, the gate-source voltage, the initial threshold voltage, the relative size mismatch rate, and the relative resistor mismatch rate.

[0010] Optionally, obtaining the comparator offset voltage based on the threshold voltage drift, the gate-source voltage, the initial threshold voltage, the relative size mismatch rate, and the relative resistor mismatch rate includes: Substituting the threshold voltage drift, the gate-source voltage, the initial threshold voltage, the relative size mismatch rate, and the relative resistor mismatch rate into the comparator offset calculation formula, the comparator offset voltage is obtained. The formula for calculating the comparator offset is: ; in, V os is the comparator offset voltage. V GSThe gate-source voltage, V TH For the initial threshold voltage, Δ V TH ΔS / S is the threshold voltage drift, ΔR / R is the relative size mismatch rate, ΔR is the relative resistance mismatch rate, ΔR is the load resistance change, R is the initial load resistance, ΔS is the input-to-physical-size change, and S is the input-to-initial-physical-size.

[0011] Optionally, the step of simulating the behavioral-level evaluation model to obtain simulation data under the total dose effect includes: Configure the system operating voltage, analog-to-digital converter bit width, and clock frequency according to the application scenario requirements of the behavioral evaluation model to obtain the simulation parameters of the behavioral evaluation model; The behavioral evaluation model is simulated according to the simulation parameters to obtain the output signal of the analog-to-digital converter under the total dose effect. Based on the output signal, the key performance parameters of the analog-to-digital converter under the total dose effect are obtained. The key performance parameters include signal-to-noise ratio, effective number of bits, integral nonlinearity error, and differential nonlinearity error. The signal-to-noise ratio, the effective number of bits, the integral nonlinearity error, and the differential nonlinearity error are used as the simulation data.

[0012] Optionally, generating a total dose effect assessment report for the analog-to-digital converter based on the simulation data includes: Based on the initial evaluation model, a comparative simulation was performed under equivalent simulation conditions without total dose effect to obtain baseline performance parameters. The type of the baseline performance parameters is consistent with the type of the key performance parameters. Based on the signal-to-noise ratio, the effective number of bits, the integral nonlinearity error, and the differential nonlinearity error, and in conjunction with the benchmark performance parameters, determine the relative degradation rates corresponding to the signal-to-noise ratio, the effective number of bits, the integral nonlinearity error, and the differential nonlinearity error, respectively. The performance margin of the analog-to-digital converter is determined based on the relative degradation rate; Based on the performance margin, a total dose effect assessment report for the analog-to-digital converter is generated.

[0013] In a second aspect, the present invention provides a total dose effect assessment system for an analog-to-digital converter, comprising: The parameter acquisition unit is used to acquire the total dose-effect parameters; The model building unit is used to generate a behavioral-level evaluation model of the analog-to-digital converter based on the total dose-effect parameters and the initial evaluation model of the analog-to-digital converter. The simulation unit is used to simulate the behavioral-level evaluation model to obtain simulation data under the total dose effect. An analysis unit is used to generate a total dose effect assessment report of the analog-to-digital converter based on the simulation data.

[0014] Thirdly, an electronic device according to the present invention includes: a processor and a memory, the memory being used to store a computer program; When the computer program is loaded by the processor, it causes the processor to execute the total dose effect assessment method for analog-to-digital converters as described above.

[0015] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the analog-to-digital converter total dose effect assessment method as described above.

[0016] The present invention discloses a method, system, device, and medium for evaluating the total dose effect of analog-to-digital converters (ADCs). First, it acquires parameters related to the total dose effect without relying on complex device physical parameters required by complex physical models, avoiding the cumbersome process of physical-level modeling and significantly shortening the evaluation preparation cycle. Second, it generates a behavioral-level evaluation model based on the acquired parameters and the initial evaluation model of the ADC. This simplifies modeling complexity and accelerates model construction without sacrificing the characterization of the core radiation impact mechanism. Simultaneously, through the direct correlation between parameters and the model, it accurately maps the path of the total dose effect on the ADC, reducing the accuracy loss caused by model simplification. Third, it simulates the behavioral-level evaluation model. Compared to the inefficient simulation of physical-level modeling, the simulation process of the behavioral-level model is faster, quickly acquiring simulation data under the influence of the total dose effect and improving evaluation efficiency. Finally, it directly generates an evaluation report based on the simulation data, eliminating the need for additional complex data processing or verification steps. This ensures that the evaluation results accurately reflect the performance changes of the ADC under radiation conditions, and through process simplification and model optimization, achieves a dual improvement in evaluation efficiency and accuracy. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating the total dose effect assessment method for analog-to-digital converters according to an embodiment of the present invention. Figure 2 This is a schematic diagram of the structure of the behavioral-level evaluation model according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the simulation results without total dose effect in an embodiment of the present invention; Figure 4 This is a schematic diagram of the simulation results under radiation effects in an embodiment of the present invention; Figure 5This is a schematic diagram of the total dose effect assessment system for analog-to-digital converters according to an embodiment of the present invention. Detailed Implementation

[0018] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Although some embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the present invention. It should be understood that the accompanying drawings and embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of protection of the present invention.

[0019] It should be understood that the various steps described in the method embodiments of the present invention may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0020] The term "comprising" and its variations as used herein are open-ended, meaning "including but not limited to"; the term "based on" means "at least partially based on"; the term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments"; and the term "optionally" means "optional embodiments". Definitions of other terms will be given in the following description. It should be noted that the concepts of "first," "second," etc., mentioned in this invention are used only to distinguish different devices, modules, or units, and are not intended to limit the order of functions performed by these devices, modules, or units or their interdependencies.

[0021] It should be noted that the terms "one" and "more" used in this invention are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0022] Combination Figure 1 As shown in the figure, an embodiment of the present invention provides a method for evaluating the total dose effect of an analog-to-digital converter, comprising: Obtain the total dose-effect parameters.

[0023] Specifically, the total dose effect parameter is key data reflecting the impact of radiation on the core components of an analog-to-digital converter (ADC). It is obtained based on the actual radiation environment characteristics faced by the ADC in aerospace missions, focusing on parameters related to the performance degradation of semiconductor devices caused by radiation. These parameters are directly related to physical mechanisms such as charge accumulation and crystal structure defects caused by radiation, providing accurate microscopic data support for the subsequent evaluation model construction, and ensuring that the evaluation can closely match the actual radiation environment's effect on the ADC.

[0024] Based on the total dose-effect parameters and the initial evaluation model of the analog-to-digital converter, a behavioral evaluation model of the analog-to-digital converter is generated.

[0025] Specifically, the initial evaluation model is a basic abstraction of the ADC workflow, which can reflect the collaborative logic of its core functional modules. By incorporating the total dose effect parameter into this model, the essence is to introduce the influence mechanism of radiation on the key components of the ADC into the basic model, realizing the transformation from the ideal working state model to the working state model under radiation environment. This behavioral evaluation model does not rely on complex physical details, but can accurately map the path of the total dose effect on the macroscopic performance of the ADC, laying the foundation for efficient simulation.

[0026] The behavioral-level evaluation model was simulated to obtain simulation data under the total dose effect.

[0027] Specifically, the simulation process is based on a behavioral-level evaluation model. It uses professional simulation tools to reproduce the complete workflow of the ADC in a radiation environment, thereby quickly capturing the changes in the ADC output data under the total dose effect. Compared with traditional physical-level modeling and simulation, it eliminates the need for tedious physical parameter debugging and complex calculations, significantly shortening the simulation cycle. At the same time, it can accurately collect the core output data that reflects the ADC performance, providing a direct basis for subsequent performance analysis.

[0028] Based on the simulation data, a total dose effect assessment report of the analog-to-digital converter is generated.

[0029] Specifically, by analyzing simulation data, the impact of total dose effect on the key performance of ADC can be presented intuitively, and the specific manifestations of ADC performance degradation under radiation environment can be clarified. Based on these quantitative data, the evaluation report clearly defines the working state and performance boundary of ADC under target radiation environment, providing direct and effective decision-making reference for radiation hardening design, performance optimization and reliability assurance of ADC in aerospace electronic equipment.

[0030] The total dose effect assessment method for analog-to-digital converters (ADCs) of this invention firstly acquires relevant parameters of the total dose effect without relying on complex device physical parameters required by complex physical models, avoiding the cumbersome process of physical-level modeling and significantly shortening the assessment preparation cycle. Secondly, based on the acquired parameters and the initial assessment model of the ADC, a behavioral-level assessment model is generated. This simplifies modeling complexity and accelerates model construction without sacrificing the characterization of the core radiation impact mechanism. Simultaneously, through the direct correlation between parameters and the model, the path of the total dose effect on the ADC is accurately mapped, reducing the accuracy loss caused by model simplification. Thirdly, the behavioral-level assessment model is simulated. Compared to the inefficient simulation of physical-level modeling, the simulation process of the behavioral-level model is faster, quickly acquiring simulation data under the influence of the total dose effect and improving assessment efficiency. Finally, an assessment report is directly generated based on the simulation data, without the need for additional complex data processing or verification steps. This ensures that the assessment results accurately reflect the performance changes of the ADC under radiation conditions, and through process simplification and model optimization, achieves a dual improvement in assessment efficiency and accuracy.

[0031] Optionally, obtaining the total dose-effect parameter includes: Based on the orbit type, on-orbit duration, and device shielding conditions of the space mission in which the analog-to-digital converter is located, the total cumulative dose is estimated. Based on the total dose cumulative estimate and the mechanism of the total dose effect on semiconductor devices, the total dose effect parameters are obtained. The total dose effect parameters include threshold voltage offset, gate-source voltage, initial threshold voltage, input-to-physical-size change, input-to-initial-physical-size change, load resistance change, and initial load resistance.

[0032] Specifically, firstly, considering the orbital type (e.g., low Earth orbit, deep space orbit), on-orbit duration, and device shielding conditions (e.g., shielding material thickness, structural design) of the aerospace mission in which the analog-to-digital converter is located, the contribution of different environmental factors to radiation dose is quantified to obtain the total cumulative dose estimate. Secondly, based on the influence mechanism of the total dose effect on semiconductor devices (oxide layer charge accumulation caused by radiation ionization and crystal structure defect evolution), the correlation between the total cumulative dose estimate and microscopic transistor parameters is established, and the quantitative mapping relationship between radiation dose and parameters such as threshold voltage offset, physical size change, and load resistance change is clarified. Finally, the total dose effect parameters, including threshold voltage offset, gate-source voltage, initial threshold voltage, input to physical size change, input to initial physical size, load resistance change, and initial load resistance, are obtained. In a preferred embodiment of the present invention, taking an 8-bit analog-to-digital converter as an example, the converter is located in a lunar probe orbit with an on-orbit duration of 6 months. The device uses an aluminum shielding structure with a thickness of 2 mm. By querying the space radiation environment database, the estimated total dose accumulation is 50 krad (Si). Combining the mechanism of charge accumulation and defect evolution of semiconductor devices under the total dose effect, through device radiation test data calibration and theoretical model derivation, the threshold voltage offset corresponding to the total dose accumulation is determined to be 0.5V, the gate-source voltage is 1.0V, the initial threshold voltage is 0.5V, the input to physical size change is 1, the input to initial physical size is 1, the load resistance change is 1, and the initial load resistance is 1kΩ, thus completing the acquisition of the total dose effect parameters.

[0033] In this embodiment of the invention, the total dose effect parameters are obtained by combining the actual environmental parameters of the aerospace mission with the radiation damage mechanism of semiconductor devices. This avoids the deviation caused by parameter estimation that is out of touch with the actual application scenario. Furthermore, through theoretical calculation and mechanism modeling, the parameters are ensured to accurately reflect the impact of the total dose effect on the core components of the analog-to-digital converter. This provides microscopic data support that fits the real radiation environment for the construction of subsequent behavioral evaluation models. At the same time, key parameters can be obtained efficiently without relying on complex physical-level experiments, thus balancing the accuracy and efficiency of parameter acquisition.

[0034] Optionally, the initial evaluation model includes a comparator for the analog-to-digital converter; generating a behavioral-level evaluation model for the analog-to-digital converter based on the total dose-effect parameters and the initial evaluation model includes: The comparator model behavior in the initial evaluation model is modified based on the total dose effect parameters to obtain the comparator offset voltage of the analog-to-digital converter; Based on the comparator offset voltage, a comparator bias reflecting the influence of radiation effects is added to the initial evaluation model to obtain the behavioral-level evaluation model.

[0035] Specifically, the initial evaluation model is a basic behavioral-level model built for successive approximation analog-to-digital converters (ADCs). Its components correspond one-to-one with the core functional modules of the ADC, including a comparator, a digital-to-analog converter (DAC), a control unit, and a result register. These modules work together to achieve the complete workflow of starting the conversion, bit-by-bit approximation comparison, and outputting the result. Specifically, after starting the conversion, the control unit controls the comparator to compare the input analog signal with the feedback signal from the DAC from the most significant bit to the least significant bit. Each clock cycle completes the comparison and determination of one bit of signal. An N-bit ADC requires N clock cycles to complete one complete conversion. Finally, the corresponding binary digital signal is stored in the comparison register and output. This model is constructed using a hardware description language (Verilog) to write the model files. By abstracting the working logic and timing relationships of the core modules, a high-level abstract model is formed that does not rely on complex physical details. It does not require involvement of the internal microscopic physical structure parameters of the device, focusing only on the functional cooperation and signal transmission between modules. This ensures that the model has the characteristics of rapid construction and convenient debugging, while accurately reproducing the normal working state of the ADC under ideal conditions. After the conversion is initiated, the comparator compares the input signal with the DAC feedback, starting from the most significant bit. One comparison is completed in one clock cycle, allowing the DAC's output voltage to successively approximate the input signal. An N-bit ADC requires N clock cycles for one conversion. After conversion, a binary number is output. Figure 2 As shown, taking a 3-bit SAR ADC as an example, the result register ADC[2:0] has 3 bits, and the reference voltage is 5V. An analog signal of 0-5V will be converted into a digital signal of 000-111 by the ADC, with a resolution of 0.625V, and the conversion requires 3 cycles. Incorrectly introducing the total dose effect will affect the comparison results, and thus affect the output of the digital-to-analog converter.

[0036] Therefore, for the comparator in the initial evaluation model, using the total dose effect parameters (threshold voltage shift, gate-source voltage, initial threshold voltage, input-to-physical-size change, input-to-initial-physical-size change, load resistance change, and initial load resistance), a radiation damage quantification mapping technique is employed. By constructing the correlation calculation logic between each parameter and the comparator offset voltage, the radiation-induced microscopic parameter changes are transformed into macroscopic performance deviations of the comparator. Specifically, this process relies on the influence mechanism of the total dose effect on semiconductor devices (charge accumulation and crystal structure defects caused by radiation ionization), and uses quantification formulas to integrate parameters such as threshold voltage drift, input-to-physical-size mismatch, and load resistance mismatch. The calculations are performed to obtain the comparator offset voltage, which characterizes the degree of radiation impact. Secondly, a hardware description language timing logic modification technique is used to add a deviation response mechanism based on the comparator offset voltage to the timing logic block of the initial evaluation model. This mechanism dynamically adjusts the output voltage of the digital-to-analog converter (DAC) module according to the least significant bit of the offset voltage (for example, when the least significant bit is logic 1, the output voltage of the DAC module increases by a minimum unit; when it is logic 0, it remains unchanged). This realistically simulates the comparator decision deviation caused by the total dose effect in the model, enabling the modified model to accurately reproduce the working state of the DAC under radiation conditions, ultimately generating a behavioral-level evaluation model.

[0037] In this embodiment of the invention, the influence of total dose effect on the core components of the analog-to-digital converter is captured by specifically modifying the model behavior of the comparator in the initial evaluation model. The acquisition of the comparator offset voltage is based on the quantitative calculation of specific parameters, which ensures the accuracy of the radiation effect characterization. The addition of comparator bias enables the model to realistically reproduce the working state under radiation environment. Compared with traditional modeling methods, it does not rely on complex physical details, which simplifies the modeling process, improves modeling efficiency, and ensures the accuracy of the model in simulating radiation effects.

[0038] Optionally, modifying the comparator model behavior in the initial evaluation model based on the total dose-effect parameters to obtain the comparator offset voltage of the analog-to-digital converter includes: The threshold voltage drift is determined based on the threshold voltage offset and the initial threshold voltage in the total dose-effect parameters; The relative size mismatch rate is determined based on the input-to-physical-size change and the input-to-initial-physical-size in the total dose-effect parameters. The relative resistance mismatch rate is calculated based on the load resistance change and the initial load resistance in the total dose effect parameters. The comparator offset voltage is obtained based on the threshold voltage drift, the gate-source voltage, the initial threshold voltage, the relative size mismatch rate, and the relative resistor mismatch rate.

[0039] Specifically, firstly, using the difference calculation technique, the threshold voltage offset in the total dose effect parameters is calculated by subtracting the initial threshold voltage, resulting in the threshold voltage drift, which reflects the degree of change in the threshold voltage caused by radiation. Secondly, using the proportional calculation technique, the ratios of the input pair physical size change to the initial physical size and the load resistance change to the initial load resistance are calculated, respectively, to obtain the relative size mismatch rate characterizing the physical structure deviation and the relative resistance mismatch rate characterizing the circuit parameter deviation. Finally, based on the quantitative mechanism of the total dose effect's influence on comparator performance, using the multi-parameter coupling calculation technique, the obtained threshold voltage drift, the gate-source voltage and the initial threshold voltage in the total dose effect parameters, and the two relative mismatch rates mentioned above are substituted into the preset comparator offset calculation logic. By integrating the influence weights of each parameter on the comparator's operating state, the comparator offset voltage, which comprehensively reflects the radiation effect, is finally obtained, realizing the step-by-step transformation from the original parameters to the target parameters.

[0040] In this embodiment of the invention, by converting the complex total dose effect parameters into offset voltages that can directly characterize the radiation damage to the comparator, the acquisition of each new parameter relies on a clear calculation process, ensuring the accuracy and traceability of the parameter conversion. This avoids the problem of poor model adaptability caused by directly using the original parameters, and comprehensively captures the combined effect of radiation on the comparator through the coupled calculation of multi-dimensional parameters. This provides a reliable quantitative basis for the accurate introduction of radiation bias into the model in the future. At the same time, the calculation process is simple and efficient, without relying on complex physical experiments or simulation tools, thus balancing evaluation efficiency and accuracy.

[0041] Optionally, obtaining the comparator offset voltage based on the threshold voltage drift, the gate-source voltage, the initial threshold voltage, the relative size mismatch rate, and the relative resistor mismatch rate includes: Substituting the threshold voltage drift, the gate-source voltage, the initial threshold voltage, the relative size mismatch rate, and the relative resistor mismatch rate into the comparator offset calculation formula, the comparator offset voltage is obtained. The formula for calculating the comparator offset is: ; in, V os is the comparator offset voltage. V GS The gate-source voltage, V TH For the initial threshold voltage, Δ V THΔS / S is the threshold voltage drift, ΔR / R is the relative size mismatch rate, ΔR is the relative resistance mismatch rate, ΔR is the load resistance change, R is the initial load resistance, ΔS is the input-to-physical-size change, and S is the input-to-initial-physical-size.

[0042] Specifically, firstly, based on the total dose-effect parameter, the threshold voltage shift is calculated by subtracting the initial threshold voltage from the threshold voltage using a difference calculation technique, thus obtaining the threshold voltage drift (Δ). V TH The proportional calculation technique is used to compare the change in physical size of the input with the initial physical size of the input, and the change in load resistance with the initial load resistance, to obtain the relative size mismatch rate (ΔS / S) and the relative resistance mismatch rate (ΔR / R). Subsequently, the formula quantization calculation technique is used to calculate the threshold voltage drift and the gate-source voltage in the total dose effect parameters. V GS ) and initial threshold voltage ( V TH ), and the two relative mismatch rates mentioned above, are substituted into the preset comparator offset calculation formula. By integrating the influence weights of each parameter on the comparator performance (the direct influence of threshold voltage drift, the coupling influence of size and resistance mismatch), the comparator offset voltage that can comprehensively characterize the radiation effect is finally obtained. V Based on the comparator offset calculation formula, the accurate conversion from the original parameters to the target parameters is achieved. In a preferred embodiment of the present invention, if the threshold voltage offset is 0.3V, the initial threshold voltage is 0.5V, the input-to-physical-size change is 0.2, the initial input-to-physical-size is 2, the load resistance change is 50Ω, the initial load resistance is 1000Ω, and the gate-source voltage is 1.2V, the threshold voltage drift Δ is first calculated by the difference. V TH =0.3V. By proportional calculation, the relative size mismatch rate ΔS / S=0.2 / 2=0.1 and the relative resistance mismatch rate ΔR / R=50 / 1000=0.05. Substituting these parameters into the formula, the comparator offset voltage Vos=0.3+(1.2-0.5) / 2×(0.1+0.05)=0.3+0.35×0.15=0.3525V.

[0043] In this embodiment of the invention, by substituting the multi-dimensional total dose effect parameters into the comparator offset calculation formula, the accurate calculation of the comparator offset voltage is achieved. This not only avoids subjective errors in the parameter integration process, but also comprehensively captures the direct and coupled effects of radiation on the comparator through the weight allocation of each parameter in the formula.

[0044] Optionally, the step of simulating the behavioral-level evaluation model to obtain simulation data under the total dose effect includes: Configure the system operating voltage, analog-to-digital converter bit width, and clock frequency according to the application scenario requirements of the behavioral evaluation model to obtain the simulation parameters of the behavioral evaluation model; The behavioral evaluation model is simulated according to the simulation parameters to obtain the output signal of the analog-to-digital converter under the total dose effect. Based on the output signal, the key performance parameters of the analog-to-digital converter under the total dose effect are obtained. The key performance parameters include signal-to-noise ratio, effective number of bits, integral nonlinearity error, and differential nonlinearity error. The signal-to-noise ratio, the effective number of bits, the integral nonlinearity error, and the differential nonlinearity error are used as the simulation data.

[0045] Specifically, firstly, based on the aerospace application scenarios (such as low Earth orbit and deep space exploration) corresponding to the behavioral-level evaluation model, the system operating voltage (power supply requirements of adapters), the number of bits of the analog-to-digital converter (to match data accuracy requirements), and the clock frequency (to conform to system timing specifications) are clearly defined to directly obtain targeted simulation parameters. Secondly, using behavioral-level model simulation technology, the configured simulation parameters are imported into professional simulation tools such as Verilog-AMS to drive the behavioral-level evaluation model to run, simulating the complete workflow of the analog-to-digital converter under the total dose effect, and collecting information such as the converted digital signal and output voltage to obtain the output signal. Finally, using performance parameter quantization extraction technology, based on the output signal, the signal-to-noise ratio, effective number of bits, integral nonlinearity error, and differential nonlinearity error are obtained sequentially through the signal-to-noise ratio calculation formula (the ratio of signal power to noise power), the effective number of bits derivation formula (converted from the signal-to-noise ratio), the integral nonlinearity error calculation method (the maximum deviation between the actual transmission characteristics and the ideal straight line), and the differential nonlinearity error calculation method (the deviation between the actual step size and the ideal step size of adjacent quantization intervals). Finally, these parameters are integrated into simulation data. For example, taking a 12-bit analog-to-digital converter (ADC) for a near-Earth orbit space mission as an example, simulation parameters are configured according to the application scenario requirements. These parameters include a system operating voltage of 3.3V, an ADC bit depth of 12 bits, and a clock frequency of 1MHz. These parameters are imported into a simulation tool to simulate a behavioral-level evaluation model, obtaining the output signal under the total dose effect (including a series of converted digital code values ​​and corresponding output voltages). Based on the output signal, the signal-to-noise ratio is calculated to be 65dB. The effective bit depth is derived to be 10.5 bits. By comparing the actual transmission characteristics with the ideal straight line, the integral nonlinearity error is found to be ±0.8LSB. By checking the step size deviation between adjacent quantization intervals, the differential nonlinearity error is found to be ±0.5LSB. These four parameters are used as the final simulation data.

[0046] In this embodiment of the invention, the objectivity and accuracy of simulation data are ensured through standardized parameter configuration, simulation, and performance extraction. Scenario-adaptive parameter configuration makes the simulation more closely resemble the actual application environment. Behavioral-level model simulation significantly improves simulation efficiency compared to physical-level simulation. The extraction of four key performance parameters comprehensively covers core indicators such as the accuracy and linearity of the analog-to-digital converter, comprehensively reflecting the impact of the total dose effect. Simultaneously, the entire process does not rely on complex physical experiments, reducing evaluation costs and rapidly outputting quantified simulation data, providing support for the subsequent generation of accurate total dose effect assessment reports.

[0047] Optionally, generating a total dose effect assessment report for the analog-to-digital converter based on the simulation data includes: Based on the initial evaluation model, a comparative simulation was performed under equivalent simulation conditions without total dose effect to obtain baseline performance parameters. The type of the baseline performance parameters is consistent with the type of the key performance parameters. Based on the signal-to-noise ratio, the effective number of bits, the integral nonlinearity error, and the differential nonlinearity error, and in conjunction with the benchmark performance parameters, determine the relative degradation rates corresponding to the signal-to-noise ratio, the effective number of bits, the integral nonlinearity error, and the differential nonlinearity error, respectively. The performance margin of the analog-to-digital converter is determined based on the relative degradation rate; Based on the performance margin, a total dose effect assessment report for the analog-to-digital converter is generated.

[0048] Specifically, firstly, based on the initial evaluation model, a comparative simulation is performed while removing the total dose effect parameter and maintaining other simulation conditions (system operating voltage, ADC bit depth, clock frequency, etc.) consistent with the simulation with radiation effects. Signal-to-noise ratio, effective bit depth, integral nonlinearity error, and differential nonlinearity error are collected under a radiation-free environment to obtain baseline performance parameters consistent with the key performance parameter types. In a preferred embodiment of the invention, for an 8-bit SAR ADC, the system voltage is 3.3V, and a 2.5V reference voltage is measured. Combined with... Figure 3 As stated above, without total dose effect, the iterative curve of the DAC feedback voltage is smooth and converges quickly, eventually stabilizing at 2.4976V, with minimal deviation from the target input voltage of 2.5V. Figure 4 As mentioned above, due to the radiation effect, the iterative curve of the DAC feedback voltage exhibits fluctuating or non-smooth convergence characteristics, eventually stabilizing at 1.65647V, which deviates significantly from the target input voltage of 2.5V. Figure 3 and Figure 4 The horizontal axis represents the number of clock cycles for bit-by-bit approximation, and the vertical axis represents the reference voltage value fed back by the DAC.

[0049] Therefore, it is necessary to evaluate the relative degradation rates corresponding to signal-to-noise ratio, effective bits, integral nonlinearity error, and differential nonlinearity error, respectively. Specifically, using each benchmark performance parameter as a reference, the relative degradation rate corresponding to each key performance parameter under the total dose effect is calculated through the quantization logic of (benchmark parameter value - simulation parameter value) / benchmark parameter value × 100%. Among them, signal-to-noise ratio and effective bits represent the performance degradation rate, while integral nonlinearity error and differential nonlinearity error represent the error growth rate. Then, using performance margin assessment technology, combined with the performance index requirement threshold of the aerospace mission for the ADC, the performance margin is calculated through (simulation parameter value - requirement threshold) / requirement threshold × 100%, clarifying the performance redundancy of the ADC in the radiation environment. Finally, all the above quantification results are integrated to form a total dose effect assessment report that includes the performance degradation law under the radiation environment, the degree of degradation of each parameter, performance margin, and usage recommendations.

[0050] In this embodiment of the invention, by comparing benchmark simulation and radiation environment simulation, and combining the quantified relative degradation rate and performance margin calculation, the influence of total dose effect on the core performance of analog-to-digital converter is comprehensively and accurately presented. The acquisition of benchmark performance parameters ensures the rationality of the degradation assessment, the calculation of the relative degradation rate realizes the quantitative characterization of performance changes, and the determination of performance margin clarifies the usage boundary of the device in the radiation environment. This invention relies on standardized calculation logic and simulation technology to avoid the bias of subjective assessment. Compared with the traditional assessment method that relies on physical experiments, the generated assessment report significantly improves the efficiency and cost advantage of report generation.

[0051] Combination Figure 5 As shown, another embodiment of the present invention provides a total dose effect assessment system for analog-to-digital converters, comprising: The parameter acquisition unit is used to acquire the total dose-effect parameters; The model building unit is used to generate a behavioral-level evaluation model of the analog-to-digital converter based on the total dose-effect parameters and the initial evaluation model of the analog-to-digital converter. The simulation unit is used to simulate the behavioral-level evaluation model to obtain simulation data under the total dose effect. An analysis unit is used to generate a total dose effect assessment report of the analog-to-digital converter based on the simulation data.

[0052] The total dose effect assessment system for analog-to-digital converters of the present invention has the same advantages over the prior art as the aforementioned total dose effect assessment method for analog-to-digital converters, and will not be repeated here.

[0053] Another embodiment of the present invention provides an electronic device, including: a processor and a memory, wherein the memory is used to store a computer program; When the computer program is loaded by the processor, it causes the processor to execute the total dose effect assessment method for analog-to-digital converters as described above.

[0054] The electronic device of the present invention has the same advantages over the prior art as the above-mentioned method for evaluating the total dose effect of analog-to-digital converters, and will not be repeated here.

[0055] This invention also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the analog-to-digital converter total dose effect assessment method as described above.

[0056] The advantages of the computer-readable storage medium of the present invention compared to the prior art are the same as the advantages of the above-described analog-to-digital converter total dose effect assessment method compared to the prior art, and will not be repeated here.

[0057] While the present invention has been disclosed above, its scope of protection is not limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention, and all such changes and modifications will fall within the scope of protection of the present invention.

Claims

1. A method of total dose effect evaluation of an analog-to-digital converter, characterized by, The method comprises the following steps: obtaining a total dose effect parameter; generating a behavior level evaluation model of the analog-to-digital converter according to the total dose effect parameter and an initial evaluation model of the analog-to-digital converter; performing simulation on the behavior level evaluation model to obtain simulation data under the action of the total dose effect; generating a total dose effect evaluation report of the analog-to-digital converter according to the simulation data.

2. The analog-to-digital converter total dose effect evaluation method of claim 1, wherein, The step of obtaining the total dose effect parameter comprises the following steps: obtaining a total dose accumulation estimation according to the orbit type, on-orbit time length and device shielding condition of a space task in which the analog-to-digital converter is located; obtaining the total dose effect parameter according to the total dose accumulation estimation and the influence mechanism of the total dose effect on the semiconductor device. The total dose effect parameter comprises a threshold voltage offset, a gate-source voltage, an initial threshold voltage, an input-to-physical size change amount, an input-to-initial physical size, a load resistance change amount and an initial load resistance.

3. The method of total dose effect evaluation of an analog-to-digital converter according to claim 2, characterized in that, The initial evaluation model comprises a comparator of the analog-to-digital converter; the step of generating the behavior level evaluation model of the analog-to-digital converter according to the total dose effect parameter and the initial evaluation model of the analog-to-digital converter comprises the following steps: modifying the model behavior of the comparator in the initial evaluation model according to the total dose effect parameter to obtain a comparator offset voltage of the analog-to-digital converter; adding a comparator deviation reflecting the influence of the radiation effect in the initial evaluation model according to the comparator offset voltage to obtain the behavior level evaluation model.

4. The method of total dose effect evaluation of an analog-to-digital converter according to claim 3, characterized in that, The step of modifying the model behavior of the comparator in the initial evaluation model according to the total dose effect parameter to obtain the comparator offset voltage of the analog-to-digital converter comprises the following steps: determining a threshold voltage drift according to the threshold voltage offset and the initial threshold voltage in the total dose effect parameter; determining a size relative mismatch rate according to the input-to-physical size change amount and the input-to-initial physical size in the total dose effect parameter; calculating a resistance relative mismatch rate according to the load resistance change amount and the initial load resistance in the total dose effect parameter; obtaining the comparator offset voltage according to the threshold voltage drift, the gate-source voltage, the initial threshold voltage, the size relative mismatch rate and the resistance relative mismatch rate.

5. The method of total dose effect evaluation of an analog-to-digital converter according to claim 4, characterized in that, The step of obtaining the comparator offset voltage according to the threshold voltage drift, the gate-source voltage, the initial threshold voltage, the size relative mismatch rate and the resistance relative mismatch rate comprises the following steps: substituting the threshold voltage drift, the gate-source voltage, the initial threshold voltage, the size relative mismatch rate and the resistance relative mismatch rate into a comparator offset calculation formula to obtain the comparator offset voltage. The comparator offset calculation formula is as follows: ； wherein, V os is a comparator offset voltage, V GS is the gate-source voltage, V TH is the initial threshold voltage, Δ V TH is the threshold voltage shift, ΔS / S is the relative mismatch of the input pair physical dimensions, ΔR / R is the relative mismatch of the resistors, ΔR is the load resistor variation, R is the initial load resistor, ΔS is the input pair physical dimensions variation, and S is the initial input pair physical dimensions.

6. The analog-to-digital converter total dose effect evaluation method of claim 1, wherein, The step of performing simulation on the behavior level evaluation model to obtain simulation data under the action of the total dose effect comprises the following steps: configuring system working voltage, analog-to-digital converter bit number and clock frequency according to the application scene requirement of the behavior level evaluation model to obtain simulation parameters of the behavior level evaluation model. simulate the behavior level evaluation model according to the simulation parameters, to obtain an output signal of the analog-to-digital converter under the total dose effect; obtain a key performance parameter of the analog-to-digital converter under the total dose effect according to the output signal, the key performance parameter including a signal-to-noise ratio, a number of effective bits, an integral nonlinearity error, and a differential nonlinearity error; take the signal-to-noise ratio, the number of effective bits, the integral nonlinearity error, and the differential nonlinearity error as the simulation data.

7. The method of total dose effect evaluation of an analog-to-digital converter according to claim 6, characterized in that, The generating the total dose effect evaluation report of the analog-to-digital converter according to the simulation data includes: perform comparative simulation under an equivalent simulation condition without the total dose effect based on the initial evaluation model, to obtain a benchmark performance parameter, the type of the benchmark performance parameter being consistent with the type of the key performance parameter; determine a relative degradation rate corresponding to the signal-to-noise ratio, the number of effective bits, the integral nonlinearity error, and the differential nonlinearity error respectively according to the signal-to-noise ratio, the number of effective bits, the integral nonlinearity error, and the differential nonlinearity error in combination with the benchmark performance parameter; determine a performance margin of the analog-to-digital converter according to the relative degradation rate; generate the total dose effect evaluation report of the analog-to-digital converter according to the performance margin.

8. An analog-to-digital converter total dose effect evaluation system, comprising: includes: a parameter acquisition unit configured to acquire a total dose effect parameter; a model construction unit configured to generate a behavior level evaluation model of an analog-to-digital converter according to the total dose effect parameter in combination with an initial evaluation model of the analog-to-digital converter; a simulation unit configured to simulate the behavior level evaluation model to obtain simulation data under a total dose effect; an analysis unit configured to generate a total dose effect evaluation report of the analog-to-digital converter according to the simulation data.

9. An electronic device, comprising: includes: a processor and a memory, the memory being configured to store a computer program; the computer program, when loaded by the processor, causes the processor to execute the analog-to-digital converter total dose effect evaluation method according to any one of claims 1-7.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program, when executed by the processor, implements the analog-to-digital converter total dose effect evaluation method according to any one of claims 1-7.

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