High-temperature and high-pressure calibration method for automobile water temperature sensor

Abstract

The invention is applicable to the technical field of automobile water temperature sensors, and particularly relates to an automobile water temperature sensor high-temperature and high-pressure calibration method, which comprises the following steps: determining a plurality of calibration points and output response information of a water temperature sensor under each calibration point according to a target working range of the water temperature sensor; according to the target working range, determining a plurality of key working condition points in the calibration process, and pairing the plurality of key working condition points in pairs to obtain working condition point pairs; according to the working condition point pairs and the output response information of the water temperature sensor under each calibration point, a calibration compensation curve of the water temperature sensor under the high-temperature and high-pressure environment is determined, measurement errors caused by factors such as temperature and pressure fluctuation are greatly reduced, and the accuracy of temperature measurement is improved; according to the calibration compensation curve, the original output of the water temperature sensor is compensated and corrected, an accurate temperature measurement value is obtained, manual intervention and time cost are reduced, and calibration efficiency and accuracy are improved at the same time.

Description

Technical Field

[0001] This application belongs to the field of automotive water temperature sensor technology, and particularly relates to a high-temperature and high-pressure calibration method for automotive water temperature sensors. Background Technology

[0002] In the modern automotive industry, coolant temperature sensors play a crucial role, particularly in monitoring critical components such as engine management, emissions control, cooling systems, and air conditioning systems. As a core component of automotive electronic systems, coolant temperature sensors are widely used to monitor the temperature of the engine coolant, ensuring the engine operates within its optimal temperature range. Accurate temperature data is essential for controlling engine performance, reducing emissions, and extending engine life. However, the measurement accuracy of sensors is often affected by various factors, including ambient temperature, sensor aging, electronic noise, and mechanical vibration, leading to deviations between the sensor output signal and the actual temperature value.

[0003] Traditional calibration methods typically rely on manual or semi-automated equipment to obtain compensation data through manual adjustments. While effective, this method is cumbersome, time-consuming, and difficult to adapt to complex operating environments in actual production, especially under high temperature, high pressure, or extreme operating conditions. Traditional calibration methods cannot meet the more complex and higher accuracy requirements of calibration. Summary of the Invention

[0004] This application provides a high-temperature and high-pressure calibration method for automotive water temperature sensors, which can solve the problem that traditional calibration methods cannot meet the more complex and higher accuracy requirements under high temperature, high pressure or extreme operating conditions.

[0005] In a first aspect, embodiments of this application provide a high-temperature, high-pressure calibration method for an automotive coolant temperature sensor, comprising: Based on the target operating range of the water temperature sensor, multiple calibration points and the sensor's output response information at each calibration point are determined. Each calibration point corresponds to a set of temperature and pressure conditions. This allows for a comprehensive understanding of the sensor's performance under various operating conditions, providing fundamental data for the subsequent establishment of compensation curves. Based on the target working range, multiple key operating points are determined during the calibration process, and these key operating points are paired up to obtain operating point pairs; wherein, each operating point pair includes at least one pair of operating point pairs; this can effectively cover the complex operating conditions that the sensor may face.

[0006] Based on the operating point pairs and the output response information of the water temperature sensor at each calibration point, the calibration compensation curve of the water temperature sensor under high temperature and high pressure environment is determined; this greatly reduces the measurement error caused by factors such as temperature and pressure fluctuations and improves the accuracy of temperature measurement.

[0007] Based on the calibration compensation curve, the original output of the water temperature sensor is compensated and corrected to obtain an accurate temperature measurement value.

[0008] The technical solutions described in this application embodiment have at least the following technical effects: The high-temperature and high-pressure calibration method for automotive coolant temperature sensors provided in this application determines multiple calibration points and the sensor's output response information at each calibration point based on the sensor's target operating range. This provides a comprehensive understanding of the sensor's performance under various operating conditions and lays the foundation for establishing subsequent compensation curves. Based on the target operating range, multiple key operating points are identified during the calibration process, and these key points are paired to obtain operating point pairs, effectively covering the complex operating conditions the sensor may face. Based on the operating point pairs and the sensor's output response information at each calibration point, a calibration compensation curve for the coolant temperature sensor under high-temperature and high-pressure conditions is determined, significantly reducing measurement errors caused by temperature and pressure fluctuations and improving the accuracy of temperature measurements. Based on the calibration compensation curve, the original output of the coolant temperature sensor is compensated and corrected to obtain accurate temperature measurements, reducing manual intervention and time costs while improving calibration efficiency and accuracy.

[0009] Secondly, embodiments of this application provide a high-temperature and high-pressure calibration system for an automotive water temperature sensor, the system comprising: The acquisition unit determines multiple calibration points and the output response information of the water temperature sensor at each calibration point based on the target operating range of the water temperature sensor; wherein each calibration point corresponds to a set of temperature and pressure conditions. The working condition unit is used to determine multiple key working condition points in the calibration process based on the target working range, and to pair the multiple key working condition points in pairs to obtain working condition point pairs; wherein, the working condition point pairs include at least one pair of working condition point pairs. The curve unit is used to determine the calibration compensation curve of the water temperature sensor under high temperature and high pressure environment based on the working condition point pair and the output response information of the water temperature sensor at each calibration point. The calibration unit is used to compensate and correct the original output of the water temperature sensor according to the calibration compensation curve to obtain an accurate temperature measurement value.

[0010] Thirdly, embodiments of this application provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method as described in any of the foregoing aspects.

[0011] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer instructions that, when executed on a computer, cause the computer to perform the method described in any of the preceding aspects.

[0012] Fifthly, embodiments of this application provide a computer program product that, when run on an electronic device, causes the electronic device to perform the method described in any of the preceding aspects.

[0013] It is understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant descriptions in the above aspects, and will not be repeated here. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is a schematic flowchart of a high-temperature and high-pressure calibration method for an automotive water temperature sensor provided in an embodiment of this application; Figure 2 This is a partial schematic diagram of the principle of a high-temperature and high-pressure calibration method for an automotive water temperature sensor provided in one embodiment of this application; Figure 3 This is a schematic diagram of curve optimization for a high-temperature and high-pressure calibration method for an automotive water temperature sensor provided in an embodiment of this application; Figure 4 This is a temperature compensation schematic diagram of a high-temperature and high-pressure calibration method for an automotive water temperature sensor provided in an embodiment of this application; Figure 5 This is a schematic diagram of the structure of a high-temperature and high-pressure calibration system for an automotive water temperature sensor provided in one embodiment of this application; Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0016] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0017] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0018] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0019] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determination" or "if the described condition or event is detected" may be interpreted, depending on the context, as "once determination," "in response to determination," "once the described condition or event is detected," or "in response to the detection of the described condition or event."

[0020] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0021] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0022] In the modern automotive industry, coolant temperature sensors play a crucial role, particularly in monitoring critical components such as engine management, emissions control, cooling systems, and air conditioning systems. As a core component of automotive electronic systems, coolant temperature sensors are widely used to monitor the temperature of the engine coolant, ensuring the engine operates within its optimal temperature range. Accurate temperature data is essential for controlling engine performance, reducing emissions, and extending engine life. However, the measurement accuracy of sensors is often affected by various factors, including ambient temperature, sensor aging, electronic noise, and mechanical vibration, leading to deviations between the sensor output signal and the actual temperature value.

[0023] Traditional calibration methods typically rely on manual or semi-automated equipment to obtain compensation data through manual adjustments. While effective, this method is cumbersome, time-consuming, and difficult to adapt to complex operating environments in actual production, especially under high temperature, high pressure, or extreme operating conditions. Traditional calibration methods cannot meet the more complex and higher accuracy requirements of calibration.

[0024] To address the aforementioned issues, this application provides a high-temperature and high-pressure calibration method for automotive coolant temperature sensors. This method determines multiple calibration points and the sensor's output response information at each calibration point based on the target operating range of the coolant temperature sensor. This comprehensively understands the sensor's performance under various operating conditions, providing fundamental data for establishing subsequent compensation curves. Based on the target operating range, multiple key operating point pairs are determined during the calibration process, effectively covering the complex operating conditions the sensor may face. Based on these pairs and the sensor's output response information at each calibration point, a calibration compensation curve for the coolant temperature sensor under high-temperature and high-pressure conditions is determined, significantly reducing measurement errors caused by temperature and pressure fluctuations and improving the accuracy of temperature measurements. Based on the calibration compensation curve, the original output of the coolant temperature sensor is compensated and corrected to obtain accurate temperature measurements, reducing manual intervention and time costs while improving calibration efficiency and accuracy.

[0025] The high-temperature and high-pressure calibration method for automotive water temperature sensors provided in this application can be applied to electronic devices. In this case, the electronic device is the executing entity of the high-temperature and high-pressure calibration method for automotive water temperature sensors provided in this application. This application does not impose any restrictions on the specific type of electronic device.

[0026] It is understandable that electronic devices can be various intelligent devices. For example, electronic devices can be terminal devices such as laptops, ultra-mobile personal computers (UMPCs), netbooks, personal digital assistants (PDAs), and desktop computers.

[0027] To better understand the high-temperature and high-pressure calibration method for automotive water temperature sensors provided in this application, the specific implementation process of the high-temperature and high-pressure calibration method for automotive water temperature sensors provided in this application will be described below by way of example.

[0028] Figure 1 This paper presents a schematic flowchart of a high-temperature and high-pressure calibration method for an automotive coolant temperature sensor provided in an embodiment of this application. Figure 2This illustration shows a partial schematic diagram of the high-temperature and high-pressure calibration method for an automotive coolant temperature sensor provided in an embodiment of this application. The high-temperature and high-pressure calibration method for an automotive coolant temperature sensor includes: S100 determines multiple calibration points and the output response information of the water temperature sensor at each calibration point based on the target operating range of the water temperature sensor; wherein, each calibration point corresponds to a set of temperature and pressure conditions.

[0029] Calibration points, as understood, refer to selecting multiple specific temperature and pressure conditions within a given operating range to analyze and calibrate the sensor's performance by analyzing its output response under these conditions. These calibration points should cover the sensor's operating range, ensuring sufficient data collection of its response under different environmental conditions. The selection of calibration points must consider both the actual variations in the operating environment and the theoretical operating range. For example, a water temperature sensor may need to be calibrated at different water temperatures (e.g., 0°C to 100°C) and different pressures (e.g., normal pressure and high pressure). Multiple measurements can be performed under different conditions to collect sufficient data for fitting a calibration compensation curve. By performing multiple measurements at each calibration point, the sensor's output response information under different conditions can be obtained, providing necessary reference for subsequent compensation curve fitting and calibration compensation.

[0030] S200, based on the target working range, determine multiple key working points in the calibration process, and pair these multiple key working points together to obtain working point pairs; wherein, each working point pair includes at least one pair of working point pairs.

[0031] Critical operating points (COPs) are specific operating conditions determined by temperature and pressure during sensor operation. Throughout the calibration process, COPs typically lie at the limits of the operating range or in areas where sensor performance may change significantly. These COPs represent the typical operating state of the sensor in practical applications. Determining COPs involves defining the sensor's target operating range; for example, the operating temperature range might be 10°C to 90°C, and the pressure range might be from atmospheric pressure to high pressure. Then, by analyzing the relationship between these COPs and the sensor's output response data, it's determined which COPs significantly impact sensor calibration and performance. To identify COPs, the deviation between the sensor's response data and theoretically expected values ​​can be evaluated; COPs with larger deviations are generally considered critical. Selecting these COPs ensures that the calibration process effectively corrects sensor errors and provides accurate temperature measurements in practical applications.

[0032] In one possible implementation, in step S200, several key operating points in the calibration process are determined based on the target operating range, including: S210, determine alternative operating points based on the deviation between the sensor's original output and the theoretical expected value within the target operating range.

[0033] Ideally, the output of a water temperature sensor should perfectly match the theoretically expected value. However, due to manufacturing errors, environmental changes, and material aging, the actual output often deviates from the theoretical value. Therefore, candidate operating points can be determined based on the deviation between the original output and the theoretical expected value of the water temperature sensor within the target operating range. By calculating the output deviation at each operating point, it's possible to identify which operating points might significantly impact the calibration results, thus determining the candidate operating points. Candidate operating points are those with large output deviations; they represent the sensor's performance under certain special conditions and require special compensation or correction. When selecting candidate operating points, a deviation threshold can be set. Only when the deviation of a certain operating point is greater than or equal to this threshold will it be considered a candidate operating point. If the deviation is small, it indicates that the operating point has little impact on the sensor's output and can be ignored in subsequent calibration. In this way, key operating points affecting sensor performance can be effectively screened out, providing necessary data support for subsequent calibration compensation.

[0034] S220. If the deviation at the candidate operating point is not less than the deviation threshold, then it is determined as a critical operating point.

[0035] Understandingly, the deviation threshold is a pre-set standard for judging whether operating points significantly affect sensor performance, and its setting directly impacts the efficiency and accuracy of the calibration process. The magnitude of the deviation threshold typically depends on the sensor's accuracy requirements, the range of variations in the operating environment, and the objectives of the calibration process. A smaller deviation threshold leads to more operating points being considered critical, increasing the complexity of the calibration process; while a larger deviation threshold may ignore some potentially influential operating points. Therefore, setting a reasonable deviation threshold is crucial. After identifying critical operating points, these points will play a key role in the subsequent compensation curve fitting process, and their output data will be used to optimize the sensor's calibration compensation curve. By ensuring that critical operating points effectively represent the sensor's response under different operating conditions, the accuracy and reliability of the calibration results can be improved.

[0036] S230, if the deviation at the candidate operating point is less than the deviation threshold, then the candidate operating point is ignored.

[0037] It is understandable that when the deviation of the candidate operating points is less than the set deviation threshold, these operating points will be ignored. In actual calibration, the sensor's output response may approach the theoretical expected value under certain conditions, and the error under these conditions has a small impact on the sensor's performance, thus requiring no additional compensation or correction. By ignoring these operating points with small deviations, the computational load and time cost of the calibration process are reduced. Ignoring operating points with small deviations not only improves calibration efficiency but also avoids the curve overfitting problem caused by overcompensation. This screening strategy makes the calibration process more efficient, allowing focus on processing operating points that significantly affect the sensor output, thereby ensuring the quality of the calibration compensation curve. In practice, the ignored operating points are usually within the sensor's operating range, and their output errors are within acceptable limits, therefore not affecting the overall calibration results.

[0038] In one possible implementation, in step S200, multiple key operating points are paired up to obtain operating point pairs, including: S240 determines the position of each key operating point in the parameter space based on the temperature and pressure values ​​corresponding to each key operating point; wherein, the parameter space consists of a temperature dimension and a pressure dimension.

[0039] The parameter space can be understood as a two-dimensional space composed of temperature and pressure dimensions. The position of each operating point in the parameter space is determined by its temperature and pressure values. Therefore, the distribution of operating points in the parameter space reflects the sensor's response characteristics under different temperature and pressure conditions. Key operating points of the sensor are mapped to this two-dimensional space for subsequent operating point pairing and compensation curve fitting. Determining the position of key operating points in the parameter space is crucial for subsequent operating point pairing, as the relative positions between operating points determine whether they can be paired and affect the fitting quality of the compensation curve. In this way, it can be ensured that each operating point in the calibration process can be reasonably located in the parameter space, thus providing effective data support for the optimization of the compensation curve.

[0040] S250: Pair each key operating point with other key operating points in the parameter space that are more than a preset threshold apart to obtain operating point pairs.

[0041] It can be understood that in parameter space, distance refers to the Euclidean distance between operating points in two dimensions: temperature and pressure. It is typically calculated using the distance formula between two points. Where L is the Euclidean distance between the operating points in the parameter space, ΔT is the temperature difference between the two operating points, and ΔP is the pressure difference. By calculating the distance between key operating points, it can be determined whether they have sufficient differences for pairing. Only when the distance between two operating points in the parameter space is greater than a preset threshold are they considered valid pairs. The purpose of this pairing method is to ensure that the selected pairs of operating points have significant environmental differences, so that the fitted compensation curve can cover a wider operating range, thereby improving the comprehensiveness and accuracy of the calibration. Through this pairing strategy, it can be ensured that the temperature and pressure changes between each pair of operating points are large enough to reflect the sensor's response characteristics under different environmental conditions. In the actual calibration process, this pairing method helps to avoid selecting overly similar operating points, which can effectively improve the applicability of the calibration compensation curve, ensuring that the compensation curve can not only adapt to common operating conditions, but also effectively handle the sensor response under extreme operating conditions.

[0042] S300 determines the calibration compensation curve of the water temperature sensor under high temperature and high pressure environment based on the working condition points and the output response information of the water temperature sensor at each calibration point.

[0043] The purpose of calibration compensation curves is to mathematically model the sensor output data and correct the sensor's errors under different operating conditions to achieve accurate temperature measurement. In this process, a defined pair of operating points can be used, combined with the actual output response information of the water temperature sensor, to comprehensively compensate for the sensor's performance. The fitting process of calibration compensation curves typically employs methods such as regression analysis and least squares. Based on the differences between the operating point pairs, a series of preliminary fitting operations are performed to obtain one or more candidate compensation curves. Then, the optimal compensation curve is selected through evaluation of the candidate curves. Evaluation criteria include fitting error, compensation effect, and curve smoothness. The ultimate goal is to obtain a curve that effectively compensates for the response error of the water temperature sensor under different temperature and pressure conditions, thereby improving measurement accuracy.

[0044] In one possible implementation, S300 determines the calibration compensation curve of the water temperature sensor under high temperature and high pressure environment based on the operating point pair and the output response information of the water temperature sensor at each calibration point, including: S310, based on at least one pair of operating point pairs, fits at least one candidate compensation curve according to the output response information of the water temperature sensor at each calibration point.

[0045] It is understandable that candidate compensation curves can be fitted using at least one pair of operating point data points combined with the output response information of the water temperature sensor at each calibration point. The selection of operating point pairs directly affects the fitting effect of the compensation curve. Typically, operating point pairs are selected based on the sensor's operating range and environmental variations; they represent the sensor's performance under extreme operating conditions.

[0046] The goal of the fitting process is to find a mathematical model that accurately describes the relationship between the sensor output and the actual temperature. Fitting methods can include linear regression, nonlinear regression, spline interpolation, etc. The choice of fitting method depends on the characteristics of the operating point pair. For example, if the temperature and pressure differences between the operating point pairs are large, a more complex nonlinear regression method may be needed, while if the differences are small, a linear regression model can be used. During the fitting process, a candidate compensation curve can be obtained by minimizing the fitting error (e.g., using the least squares method). The candidate compensation curve is a preliminary compensation model that can be used to correct the sensor output, but it may still have some errors. Therefore, the candidate compensation curve can be further optimized and evaluated to ensure its effectiveness under actual operating conditions. Optionally, S310, based on at least one pair of operating point pairs, fits at least one candidate compensation curve according to the output response information of the water temperature sensor at each calibration point, including: S311, determine the current working point pair; wherein, the current working point pair includes a first working point and a second working point, the first working point is the point with the largest output deviation among all current key working points, and the second working point is the point with the largest output deviation among the points paired with the first working point.

[0047] It can be understood that a working point pair consists of two working points. The first working point is the one with the largest output deviation among all key working points, while the second working point is the one with the largest output deviation among the points paired with the first working point. The core objective of this selection strategy is to maximize the difference between the working point pairs, thereby covering more operating conditions and environmental variations during the calibration process. Selecting the working point with the largest deviation as the first choice for pairing ensures that the compensation curve can effectively compensate for the sensor's errors under extreme operating conditions. By selecting a working point with a larger output deviation, the fitting accuracy of the compensation curve can be improved, ensuring that the sensor's output can be effectively compensated even under the most complex operating conditions. Furthermore, when selecting the second working point, it should be a point with a significant difference from the first working point, which helps ensure that the compensation curve can effectively handle different operating conditions. Through this strategy, a wider range of operating conditions can be achieved, ensuring that the compensation curve can adapt to the actual operating conditions of the sensor, and improving the reliability and accuracy of the calibration process.

[0048] S312, connect the first working point and the second working point, and select at least one intermediate calibration point on the connecting line to obtain the initial compensation curve.

[0049] It's understandable that a line is drawn connecting the first and second operating points, with at least one intermediate calibration point selected along this line. This connection method allows for understanding the response differences between the two points, and interpolation methods are used to estimate the compensation curve. The purpose of selecting intermediate calibration points is to fill the gaps between the two points, making the compensation curve smoother and ensuring it accurately describes the sensor's response under different operating conditions. Selecting intermediate calibration points along the line enhances the fitting effect of the compensation curve, especially when there are significant temperature or pressure differences between the two operating points. Intermediate calibration points not only provide more accurate compensation data but also reduce curve fitting errors, improving the accuracy of compensation.

[0050] S313, optimize the initial compensation curve based on the output response information to obtain the current compensation curve.

[0051] It's understandable that the initial compensation curve was obtained through connecting lines and interpolation, but it may still have some fitting error, thus requiring further optimization. The goal of optimization is to reduce the deviation between the compensation curve and the actual response. Please refer to [link to relevant documentation]. Figure 3 This allows the compensation curve to more accurately describe the sensor's behavior. Optimization can be achieved by adjusting the compensation value corresponding to intermediate calibration points. Optimization methods may include gradient descent, least squares, etc. By continuously adjusting the compensation curve, the fitting error is gradually reduced until a satisfactory fitting effect is achieved. The key to the optimization process lies in how to adjust the shape of the compensation curve based on the output response information. For example, when a certain part of the curve exhibits a large error, the optimization process will focus on adjusting the compensation value of that part to narrow the gap with the actual output. In addition, the overall smoothness of the curve needs to be ensured during the optimization process to avoid overfitting. Overfitting can cause the compensation curve to perform well under certain specific operating conditions but lose accuracy under other conditions. Therefore, the fitting error must be strictly controlled during the optimization process to ensure that the compensation curve can effectively compensate for the sensor's response throughout the entire operating range. Finally, the optimized current compensation curve will be used as one of the candidate compensation curves for further evaluation and selection in subsequent steps.

[0052] Optionally, S313, the initial compensation curve is optimized based on the output response information to obtain the current compensation curve, including: S3131, adjust the compensation value corresponding to the intermediate calibration point according to the output response information to obtain the process compensation curve, so that the overall fitting error of the process compensation curve is not greater than the overall fitting error before adjustment.

[0053] It can be understood that the overall fitting error refers to the sum of errors at all operating points during the fitting process of the compensation curve, which can be represented by calculating the mean square error (MSE). Therefore, the compensation value corresponding to the intermediate calibration point can be adjusted according to the output response information to obtain the process compensation curve, ensuring that the overall fitting error of the optimized compensation curve is not greater than the fitting error before adjustment. By adjusting the compensation value of the intermediate calibration point, the compensation curve can be gradually optimized, reducing the deviation between the curve and the actual output. This optimization process can be achieved iteratively, that is, adjusting the compensation value according to the performance of the compensation curve until the fitting error is reduced to a satisfactory level. During the adjustment process, the goal is to make the compensation curve maintain smoothness and adaptability while reducing the error. If the adjusted compensation curve does not significantly improve the fitting error compared to the previous one, or if the error is greater than the previous one, the optimization process should stop and revert to the previous round of optimization.

[0054] S3132, if the overall fitting error of the process compensation curve is equal to the overall fitting error before adjustment, or if the overall fitting error of the process compensation curve is not greater than the first error threshold, then stop the optimization and use the process compensation curve as the current compensation curve.

[0055] It is understandable that if the overall fitting error of the process compensation curve is equal to the overall fitting error before adjustment, or if the optimized fitting error fails to reach the preset first error threshold, then the optimization stops, and the process compensation curve is used as the current compensation curve. The purpose of this step is to evaluate whether the optimization process has reached convergence. If the optimization process fails to bring about a significant reduction in error, or if the fitting error is still greater than the set threshold, then the optimization process will be considered invalid, and it needs to be stopped and the current compensation curve selected as the final result.

[0056] This process essentially involves convergence assessment to ensure the compensation curve has achieved optimal optimization. If continued optimization does not significantly improve the fitting quality of the compensation curve, the optimization process can be stopped to avoid the risk of overfitting due to excessive adjustments. In this case, while the current compensation curve may not be perfect, it has met the calibration requirements and can provide sufficiently accurate compensation under most operating conditions.

[0057] S3133, if the overall fitting error of the process compensation curve is less than the overall fitting error before adjustment, and the number of optimizations is less than the iteration threshold, then return to execute the adjustment of the compensation value corresponding to the intermediate calibration point based on the output response information.

[0058] It is understandable that if the overall fitting error of the process compensation curve is less than the fitting error before adjustment, and the number of optimizations is less than the preset iteration threshold, then the process returns to adjust the compensation value corresponding to the intermediate calibration point based on the output response information. The goal of this process is to ensure that the optimization process can continue until the fitting error reaches a satisfactory level. By continuing optimization, the accuracy of the compensation curve can be further improved, ensuring that the final compensation curve can cover a wider working range and effectively compensate for the sensor's output error. The iteration threshold is usually set according to the sensor's accuracy requirements and the needs of the calibration process. In the actual optimization process, when the error of the compensation curve continues to decrease, the number of iterations can be increased until the error is reduced to the set target range. If the number of optimizations reaches the iteration threshold, and the error still does not reach a satisfactory level, the optimization process will stop and switch to using the current compensation curve.

[0059] S3134, if the overall fitting error of the process compensation curve is less than the overall fitting error before adjustment, and the number of optimizations is equal to the iteration threshold, then confirm whether the overall fitting error of the process compensation curve is not greater than the second error threshold, and determine the current compensation curve according to the second error threshold; wherein, the second error threshold is not less than the first error threshold.

[0060] It is understandable that when the number of optimization iterations reaches the threshold, the overall fitting error of the process compensation curve needs to be evaluated to determine whether to stop optimization. Specifically, it can be confirmed whether the overall fitting error of the optimized process compensation curve is less than the fitting error before adjustment, and whether this error is less than the second error threshold. The second error threshold is usually set as a strict standard to ensure that the fitting quality of the compensation curve achieves higher accuracy, especially in practical applications where high precision is required, the setting of the second error threshold is particularly important.

[0061] If the optimized fitting error is less than the second error threshold and the overall fitting effect meets expectations, then the process compensation curve can be considered to have met the calibration requirements and can be used as the final compensation curve. At this point, the compensation curve can effectively compensate for the sensor's response error under different operating conditions, ensuring that its output temperature value is accurate and stable.

[0062] If the optimized fitting error still exceeds the second error threshold, it indicates that the compensation curve still fails to meet the calibration requirements. In this case, the current optimization process should be abandoned, and the previous step should be returned to reselect the operating point pair or readjust the fitting method of the compensation curve. This process ensures the accuracy and reliability of the optimization results, preventing the adoption of compensation curves with excessively large errors, which could affect the final sensor measurement accuracy.

[0063] For example, in step S3134, confirming whether the overall fitting error of the process compensation curve is not greater than a second error threshold, and determining the current compensation curve based on the second error threshold, includes: S31341, If ​​the overall fitting error of the process compensation curve is not greater than the second error threshold, then the process compensation curve is used as the current compensation curve.

[0064] It is understandable that if the overall fitting error of the optimized process compensation curve is no greater than the second error threshold, the process compensation curve can be determined as the current compensation curve. This means that after multiple iterations of optimization, the compensation curve has reached the ideal accuracy, effectively compensating for the sensor's output error and meeting the accuracy requirements. At this point, the compensation curve is ready for use in practical applications. In this step, the process compensation curve, as the current compensation curve, not only accurately reflects the sensor's response under different temperature and pressure conditions but also provides stable and accurate temperature measurements under various operating conditions. The final determination of the compensation curve marks the completion of the calibration process; the sensor's output will no longer be affected by deviations and will provide high-precision measurement data.

[0065] S31342, If the overall fitting error of the process compensation curve is greater than the second error threshold, then abandon the current optimization process and return to the execution to determine the current working condition point pair.

[0066] Understandably, if the overall fitting error of the compensation curve after multiple optimizations still exceeds the second error threshold, it indicates that the current compensation curve has failed to effectively correct the sensor output and still contains a significant error. In this case, the current optimization process should be abandoned, and the determination of operating point pairs should begin anew for new optimization. This decision signifies that the compensation curve has not yet reached the expected accuracy, and the optimization process needs to be readjusted to seek a more suitable solution.

[0067] There could be several reasons to abandon the current optimization process, such as the compensation curve being too complex to achieve the desired effect within a limited number of iterations, or the differences between the selected working point pairs not being sufficient to cover the entire working range. In such cases, it is necessary to reselect the working points, or consider different fitting methods and optimization algorithms to refit a more accurate compensation curve.

[0068] Re-establishing the operating point pair typically involves selecting more operating points and adjusting the fitting algorithm to obtain a better compensation curve, reduce errors, and improve calibration accuracy. This process ensures that the final selected compensation curve provides stable and accurate compensation throughout the entire operating range.

[0069] S314 If the current compensation curve can compensate the output deviation of other key operating points besides the current operating point pair to an acceptable range, then the current compensation curve is determined as a candidate compensation curve and the final calibration compensation curve is determined based on the candidate compensation curve.

[0070] It is understandable that if the current compensation curve can compensate for the output deviation of other key operating points besides the current operating point pair to an acceptable range, then the current compensation curve is determined as a candidate compensation curve. The effectiveness of the current compensation curve is verified to ensure that it can effectively compensate for multiple operating points within the calibration range. The effectiveness evaluation of the compensation curve is usually based on the following criteria: Compensation effect: Can the current compensation curve effectively reduce the sensor's output deviation at other key operating points, keeping the difference from the theoretical expected value within an acceptable range? Generally, the acceptable range is determined by the sensor's accuracy requirements and the standards of the calibration process.

[0071] Coverage: Does the current compensation curve cover all key operating conditions, including response under extreme conditions? If the compensation curve can only effectively compensate for a few operating conditions, further optimization may be needed to increase the curve's adaptability.

[0072] Fit quality: The quality is evaluated by calculating the fitting error (such as mean square error) of the compensation curve. If the error is too large, the optimization process needs to be returned for further adjustments.

[0073] If the current compensation curve meets these conditions, it can be used as a candidate compensation curve for further verification and selection. If it does not meet these conditions, further optimization is required.

[0074] S315, if the current compensation curve fails to compensate the output deviation of other key operating points outside the current operating point pair to an acceptable range, then ignore the second operating point in the current operating point pair and return to execute to determine the current operating point pair.

[0075] It is understandable that if the current compensation curve fails to compensate the output deviation of other key operating points outside the current operating point pair to an acceptable range, then the second operating point in the current operating point pair needs to be ignored, and the process should return to the step of determining the current operating point pair.

[0076] During the operating point pairing process, the first operating point is typically the one with the largest output deviation, and the second operating point is the other operating point paired with the first. If the current compensation curve fails to effectively compensate for the output deviation of other key operating points, it means that the second operating point is not suitable as a pairing point, and therefore needs to be ignored, with other operating points being selected for pairing. The essence of this process is to optimize the operating point pairing, ensuring that the compensation curve can effectively correct the sensor's output error throughout the entire operating range. By ignoring the second operating point and reselecting pairing points, the adaptability and accuracy of the compensation curve can be improved, resulting in a more stable compensation curve suitable for different operating conditions.

[0077] S320 determines the final calibration compensation curve based on the candidate compensation curves.

[0078] It's understandable that candidate compensation curves are obtained through a fitting process, but they may not be optimal and may contain some biases or errors. Therefore, it's essential to evaluate and optimize candidate compensation curves to ensure they accurately reflect the sensor's performance. Evaluation criteria for candidate compensation curves typically include fitting error, curve smoothness, and compensation effect. First, the fitting error (e.g., mean square error) of the candidate compensation curve can be calculated to determine if it meets the requirements. If the error of the candidate compensation curve is large, refitting or using other fitting methods may be necessary. If the error of the candidate compensation curve is within an acceptable range and the compensation effect is good (i.e., it effectively reduces the sensor's output deviation), it can be determined as the final calibration compensation curve. The final calibration compensation curve not only compensates for the sensor's nonlinearity error but also provides accurate temperature measurement throughout the sensor's entire operating range, as the final compensation curve directly affects the sensor's performance in practical applications.

[0079] For example, the candidate compensation curve is obtained through different operating point pairs, fitting methods, and optimization processes, and it represents the most likely compensation curve for the sensor during calibration. The final calibration compensation curve will serve as the standard compensation model for temperature calibration in practical applications.

[0080] Optionally, S320, based on the candidate compensation curves, determines the final calibration compensation curve, including: S321, if the number of candidate compensation curves is equal to 1, then the candidate compensation curve is determined as the final calibration compensation curve.

[0081] It's understandable that if the number of candidate compensation curves equals one, it can be directly determined as the final calibration compensation curve. This situation typically occurs during the calibration process, where only one compensation curve meets all the criteria and can effectively compensate for the sensor's output deviation. Candidate compensation curves are obtained through fitting multiple optimization steps and pairs of operating points; they represent the final compensation model of the sensor within the target operating range.

[0082] In this case, since there is only one compensation curve, it can be directly used as the final compensation curve for confirmation. This compensation curve will be used for sensor calibration in practical applications to ensure that the sensor output accurately reflects the actual temperature. Final confirmation also means the completion of the calibration process, and the water temperature sensor will operate according to this compensation curve.

[0083] S322, if the number of candidate compensation curves is greater than 1, the final calibration compensation curve is determined based on the fitting quality of the candidate compensation curves.

[0084] Understandably, if the number of candidate compensation curves is greater than one, the final calibration compensation curve needs to be determined based on the fitting quality of the candidate curves. This typically occurs when multiple candidate compensation curves are generated during the calibration process, which may come from different pairs of operating points, fitting algorithms, or optimization steps. To select the optimal compensation curve, the fitting quality of each candidate curve can be considered to ensure that the final compensation curve provides the most accurate temperature measurement. The fitting quality evaluation of candidate compensation curves can include the following aspects: Overall fit error: measures the difference between the candidate compensation curve and the actual output data. The compensation curve with a smaller error is usually more accurate.

[0085] Local error: Evaluate the compensation effect of candidate compensation curves within a specific temperature or pressure range to ensure that they can effectively compensate the sensor output under all operating conditions.

[0086] Stability and robustness: Examine whether the candidate compensation curves can remain stable under different environmental changes or long-term use.

[0087] After evaluating the fitting quality of the candidate compensation curves, the compensation curve with the smallest fitting error or the compensation curve with the best overall performance is selected as the final calibration compensation curve. This calibration compensation curve will be used for the final sensor calibration, ensuring that the sensor provides accurate temperature measurements under different operating environments.

[0088] In step S322, the final calibration compensation curve is determined based on the fitting quality of the candidate compensation curves, including: S3221, the candidate compensation curves whose overall fitting error is less than or equal to the error threshold are determined as the final calibration compensation curves.

[0089] It is understandable that if the overall fitting error of a candidate compensation curve is less than or equal to a preset error threshold, then that candidate compensation curve can be determined as the final calibration compensation curve. The error threshold is an important parameter set based on the sensor's accuracy requirements, calibration standards, and application scenarios, and can be determined based on experimental data or historical experience. It represents the maximum acceptable error of the compensation curve across the entire operating range, ensuring that the sensor can provide sufficiently accurate temperature measurements under different operating conditions.

[0090] If the fitting error of the candidate compensation curve meets the error threshold requirement, it will be directly selected as the final compensation curve. This means the compensation curve has sufficient accuracy to effectively compensate the output of the water temperature sensor in practical applications, making it closer to the true temperature value. After determining the final calibration compensation curve, the water temperature sensor can be formally calibrated to provide accurate temperature measurement data within the target operating range.

[0091] If multiple candidate compensation curves meet the error threshold requirements, the final compensation curve can be selected based on other evaluation criteria, such as fit quality, stability, and applicability, to further determine the optimal compensation curve.

[0092] In step S322, the final calibration compensation curve is determined based on the fitting quality of the candidate compensation curves, including: S3222, the candidate compensation curve with the smallest overall fitting error is determined as the final calibration compensation curve.

[0093] It is understandable that if multiple candidate compensation curves can meet the preset error threshold requirements, the final calibration compensation curve needs to be selected based on the overall fitting error of the candidate curves. Specifically, the candidate compensation curve with the smallest overall fitting error is determined as the final calibration compensation curve. The purpose of selecting the compensation curve with the smallest overall fitting error is to ensure that the sensor output has the smallest error at all operating points, thereby obtaining more accurate temperature measurement results. The overall fitting error is usually evaluated by calculating the sum of errors at all operating points; these errors can be the difference between the sensor output and the theoretical expected value. The smaller the fitting error, the more accurate the compensation curve is within the calibration range, and the smaller the difference between the sensor output and the actual temperature. Through this selection criterion, it can be ensured that the final compensation curve performs optimally under different operating conditions, providing higher calibration accuracy. If the fitting errors between the candidate compensation curves differ significantly, selecting the compensation curve with the smallest error will significantly improve the sensor calibration effect, thereby better meeting the temperature measurement requirements in practical applications.

[0094] In step S322, the final calibration compensation curve is determined based on the fitting quality of the candidate compensation curves, including: S32223, sort the candidate compensation curves from smallest to largest according to the overall fitting error, and fuse the top K candidate compensation curves to obtain the final calibration compensation curve, where K is a parameter determined according to the sensor characteristics.

[0095] It is understandable that when there are many candidate compensation curves and their fitting errors are not significantly different, a fusion-based strategy can be used to determine the final calibration compensation curve. The overall fitting errors of the candidate compensation curves are sorted in ascending order, and then the top K candidate compensation curves with the smallest fitting errors are selected and fused to obtain the final calibration compensation curve. The value of K is set based on the characteristics of the sensor and can be determined through experimentation or historical experience.

[0096] Fusion methods can use weighted averaging, least squares weighting, or other mathematical methods to synthesize data from the top K selected candidate compensation curves. Fusion methods can eliminate potential errors in a single compensation curve, thereby improving the stability and adaptability of the final compensation curve. The fused compensation curve combines the advantages of multiple candidate curves, resulting in a more superior overall fitting quality, especially suitable for situations where candidate compensation curves have some differences but all exhibit good fitting effects. This fusion strategy is particularly suitable for sensor calibration under complex operating conditions because it maximizes the use of information from multiple candidate compensation curves, thereby improving the accuracy and reliability of the compensation curve. The fusion process can also handle special operating conditions where a single compensation curve cannot provide a complete fit.

[0097] The S400 compensates and corrects the original output of the water temperature sensor according to the calibration compensation curve to obtain an accurate temperature measurement value.

[0098] It is understandable that the raw output of a water temperature sensor is typically an electrical signal; please refer to [link / reference]. Figure 4 Sensor outputs, such as voltage or current, are affected by temperature, pressure, and the inherent characteristics of the sensor itself, and therefore cannot directly reflect the true temperature. A compensation curve, obtained through the calibration process, describes the relationship between the sensor output and the actual temperature. By combining the original output signal with the compensation curve, the sensor's original signal can be converted into an accurate temperature value. Specifically, the compensation curve, as a mathematical model, outputs a compensated temperature value based on the original signal. This compensated temperature measurement will be used in practical applications, such as temperature control systems and monitoring systems, to ensure temperature control accuracy and stable equipment operation. After compensation and correction, the sensor's output is no longer affected by changes in operating conditions, providing stable and highly accurate temperature data, thus completing the entire calibration process, reducing manual intervention and time costs, and improving calibration efficiency and accuracy.

[0099] For example, during the calibration process, a compensation curve has been determined through a series of steps. This curve reflects the response characteristics of the water temperature sensor under different operating conditions (such as different temperatures and pressures). The purpose of the compensation curve is to convert the sensor's raw output (which may be affected by factors such as nonlinearity and temperature drift) into an accurate temperature value.

[0100] The raw output of a water temperature sensor is typically an electrical signal (such as voltage or current), which has a certain mapping relationship with the actual temperature. However, in actual measurements, due to the influence of factors such as temperature, pressure, and the characteristics of the sensor itself, the raw output often does not accurately reflect the actual temperature. Therefore, compensation correction is needed to correct this deviation. The compensation curve is a mathematical model derived from the operating point data during the calibration process. This curve describes the relationship between the sensor output and the actual temperature. The compensation curve is applied to the raw output of the water temperature sensor. Specifically, through the compensation curve, the sensor's raw output can be converted into a precise temperature value.

[0101] Assuming the sensor output signal is S, the compensation curve can be a function F(S), which can be linear or nonlinear, depending on the design of the compensation curve. By applying the compensation curve, the compensated temperature measurement value T is obtained, i.e., T = F(S). The compensated temperature value T is the actual temperature output of the sensor under the current operating conditions.

[0102] Corresponding to the high-temperature and high-pressure calibration method for automotive water temperature sensors in the above embodiments, this application also provides a high-temperature and high-pressure calibration system for automotive water temperature sensors. Each unit of this system can implement each step of the high-temperature and high-pressure calibration method for automotive water temperature sensors. Figure 5 The diagram shows a structural block diagram of a high-temperature and high-pressure calibration system for an automotive water temperature sensor provided in an embodiment of this application. For ease of explanation, only the parts related to the embodiments of this application are shown.

[0103] Reference Figure 5 The high-temperature and high-pressure calibration system for the automotive water temperature sensor includes: The acquisition unit determines multiple calibration points and the output response information of the water temperature sensor at each calibration point based on the target operating range of the water temperature sensor; wherein each calibration point corresponds to a set of temperature and pressure conditions. The working condition unit is used to determine multiple key working condition points in the calibration process based on the target working range, and to pair the multiple key working condition points in pairs to obtain working condition point pairs; wherein, the working condition point pairs include at least one pair of working condition point pairs. The curve unit is used to determine the calibration compensation curve of the water temperature sensor under high temperature and high pressure environment based on the working condition point pair and the output response information of the water temperature sensor at each calibration point. The calibration unit is used to compensate and correct the original output of the water temperature sensor according to the calibration compensation curve to obtain an accurate temperature measurement value.

[0104] It should be noted that the information interaction and execution process between the above systems / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0105] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit module can exist physically separately, or two or more unit modules can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0106] This application also provides an electronic device. Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 6 As shown, the electronic device 6 of this embodiment includes: at least one processor 60 ( Figure 6 Only one is shown in the image), at least one memory 61 ( Figure 6 (Only one is shown in the image) and a computer program 62 stored in the at least one memory 61 and executable on the at least one processor 60. When the processor 60 executes the computer program 62, it causes the electronic device 6 to perform the steps in any of the above embodiments of the high temperature and high pressure calibration method for automotive water temperature sensors, or causes the electronic device 6 to perform the functions of each unit in the above system embodiments.

[0107] For example, the computer program 62 may be divided into one or more units, which are stored in the memory 61 and executed by the processor 60 to complete this application. The one or more units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program 62 in the electronic device 6.

[0108] Electronic device 6 can be a computing device or terminal device such as a mobile phone, tablet computer, desktop computer, laptop, handheld computer, and cloud server. This electronic device may include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art will understand that... Figure 6 This is merely an example of electronic device 6 and does not constitute a limitation on electronic device 6. It may include more or fewer components than shown, or combine certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0109] The processor 60 can be a Central Processing Unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0110] In some embodiments, the memory 61 may be an internal storage unit of the electronic device 6, such as a hard disk or memory of the electronic device 6. In other embodiments, the memory 61 may be an external storage device of the electronic device 6, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the electronic device 6. Furthermore, the memory 61 may include both internal and external storage units of the electronic device 6. The memory 61 is used to store the operating system, applications, bootloader, data, and other programs, such as the program code of the computer program. The memory 61 can also be used to temporarily store data that has been output or will be output.

[0111] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0112] This application provides a computer program product that, when run on an electronic device, causes the electronic device to perform the steps in any of the above method embodiments.

[0113] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to an electronic device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0114] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0115] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0116] In the embodiments provided in this application, it should be understood that the disclosed automotive coolant temperature sensor high-temperature and high-pressure calibration system / electronic device and method can be implemented in other ways. For example, the embodiments of the automotive coolant temperature sensor high-temperature and high-pressure calibration system / electronic device described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0117] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0118] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A high-temperature and high-pressure calibration method for an automotive water temperature sensor, characterized in that, The method includes: Based on the target operating range of the water temperature sensor, multiple calibration points and the output response information of the water temperature sensor at each calibration point are determined; wherein, each calibration point corresponds to a set of temperature and pressure conditions; Based on the target working range, multiple key working points are determined in the calibration process, and these multiple key working points are paired up to obtain working point pairs; wherein, each working point pair includes at least one pair of working point pairs. Based on the working condition points and the output response information of the water temperature sensor at each calibration point, the calibration compensation curve of the water temperature sensor under high temperature and high pressure environment is determined. Based on the calibration compensation curve, the original output of the water temperature sensor is compensated and corrected to obtain an accurate temperature measurement value.

2. The method as described in claim 1, characterized in that, Based on the target working range, several key operating points are determined during the calibration process, including: Based on the deviation between the sensor's original output and the theoretical expected value within the target operating range, alternative operating points are determined; If the deviation at the candidate operating point is not less than the deviation threshold, then it is determined as the critical operating point. If the deviation at the candidate operating point is less than the deviation threshold, then the candidate operating point is ignored.

3. The method as described in claim 1, characterized in that, The multiple key operating points are paired up to obtain operating point pairs, including: Based on the temperature and pressure values ​​corresponding to each key operating point, the position of each key operating point in the parameter space is determined; wherein, the parameter space consists of a temperature dimension and a pressure dimension. Each key operating point is paired with other key operating points in the parameter space whose distance exceeds a preset threshold to obtain operating point pairs.

4. The method as described in claim 3, characterized in that, The step of determining the calibration compensation curve of the water temperature sensor under the high temperature and high pressure environment based on the working condition point pair and the output response information of the water temperature sensor at each calibration point includes: Based on at least one pair of operating point pairs, at least one candidate compensation curve is fitted according to the output response information of the water temperature sensor at each calibration point. Based on the candidate compensation curves, the final calibration compensation curve is determined.

5. The method as described in claim 4, characterized in that, The process of fitting at least one candidate compensation curve based on at least one pair of operating point pairs and the output response information of the water temperature sensor at each calibration point includes: Determine the current working condition point pair; wherein, the current working condition point pair includes a first working condition point and a second working condition point, the first working condition point is the point with the largest output deviation among all current key working condition points, and the second working condition point is the point with the largest output deviation among the points paired with the first working condition point; Connect the first operating point and the second operating point with a line, and select at least one intermediate calibration point on the line to obtain the initial compensation curve. The initial compensation curve is optimized based on the output response information to obtain the current compensation curve; If the current compensation curve can compensate the output deviation of other key operating points besides the current operating point pair to an acceptable range, then the current compensation curve is determined as a candidate compensation curve and the final calibration compensation curve is determined based on the candidate compensation curve. If the current compensation curve fails to compensate the output deviation of other key operating points besides the current operating point pair to an acceptable range, then the second operating point in the current operating point pair is ignored and the process returns to determining the current operating point pair.

6. The method as described in claim 5, characterized in that, The initial compensation curve is optimized based on the output response information to obtain the current compensation curve, including: Adjust the compensation value corresponding to the intermediate calibration point according to the output response information to obtain the process compensation curve, so that the overall fitting error of the process compensation curve is not greater than the overall fitting error before adjustment. If the overall fitting error of the process compensation curve is equal to the overall fitting error before adjustment, or if the overall fitting error of the process compensation curve is not greater than the first error threshold, then optimization is stopped, and the process compensation curve is used as the current compensation curve. If the overall fitting error of the process compensation curve is less than the overall fitting error before adjustment, and the number of optimizations is less than the iteration threshold, then return to execute the step of adjusting the compensation value corresponding to the intermediate calibration point based on the output response information. If the overall fitting error of the process compensation curve is less than the overall fitting error before adjustment, and the number of optimizations is equal to the iteration threshold, then it is confirmed whether the overall fitting error of the process compensation curve is not greater than the second error threshold, and the current compensation curve is determined according to the second error threshold; wherein, the second error threshold is not less than the first error threshold.

7. The method as described in claim 6, characterized in that, Confirming whether the overall fitting error of the process compensation curve is not greater than a second error threshold, and determining the current compensation curve based on the second error threshold, including: If the overall fitting error of the process compensation curve is not greater than the second error threshold, then the process compensation curve is used as the current compensation curve. If the overall fitting error of the process compensation curve is greater than the second error threshold, then abandon the current optimization process and return to the process of determining the current working point pair.

8. The method as described in claim 4, characterized in that, The step of determining the final calibration compensation curve based on the candidate compensation curves includes: If the number of candidate compensation curves is equal to 1, then the candidate compensation curve is determined as the final calibration compensation curve; If the number of candidate compensation curves is greater than 1, the final calibration compensation curve is determined based on the fitting quality of the candidate compensation curves.

9. The method as described in claim 8, characterized in that, Determining the final calibration compensation curve based on the fitting quality of the candidate compensation curves includes: The candidate compensation curve whose overall fitting error is less than or equal to the error threshold is determined as the final calibration compensation curve. And / or, the candidate compensation curve with the smallest overall fitting error is determined as the final calibration compensation curve.

10. The method as described in claim 8, characterized in that, Determining the final calibration compensation curve based on the fitting quality of the candidate compensation curves includes: The candidate compensation curves are sorted from smallest to largest based on their overall fitting error. The top K candidate compensation curves are then fused to obtain the final calibration compensation curve, where K is a parameter determined based on the sensor characteristics.

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