Thermal management calibration method and system based on actuator characteristic modeling and real-time monitoring

Abstract

The invention discloses a thermal management calibration method and system based on actuator characteristic modeling and real-time monitoring, and belongs to the field of new energy automobile thermal management systems. Binding the model of the actuator with the characteristic curve; the input range of calibration parameters is dynamically constrained based on the characteristic curve in the calibration process; an automatic verification process is executed after calibration, and actual response and actuator characteristic curve expectation are compared through a preset test sequence; the expected behavior and the actual behavior of the actuator are monitored in real time during operation; and when the deviation is detected, an abnormity diagnosis and safety fault-tolerant strategy is triggered. The problem that calibration parameters and hardware behaviors are disjointed due to the fact that nonlinear characteristics of the actuator are ignored in the prior art can be solved, the thermal management failure rate is remarkably reduced, the calibration efficiency and the system safety are improved, and the method is suitable for the whole thermal management calibration process of nonlinear actuators such as water pumps and electronic fans.

Description

Technical Field

[0001] This application relates to the field of thermal management systems for new energy vehicles, specifically to a thermal management calibration method and system based on actuator characteristic modeling and real-time monitoring. Background Technology

[0002] With the widespread application of thermal management systems in new energy vehicles, the calibration accuracy of their actuators (such as water pumps, electric fans, and electronic expansion valves) directly affects the thermal safety and operational reliability of the entire vehicle. In existing technologies, thermal management system calibration generally employs a manual, experience-driven process. Operators set calibration parameters (such as command signal thresholds and output speed ranges) based on historical data or trial-and-error methods, and rely on manual verification to ensure parameter validity. For example, while Chinese patent CN208615864U (A Thermal Management System Control Method and Device) proposes centralizing thermal management control in a thermal management control unit (TMCU) to reduce communication load, its technical solution does not address the specific implementation of actuator calibration, nor does it resolve the issue of handling the physical characteristics of the actuators during the calibration process.

[0003] The core flaws of existing technology: Actuators exhibit inherent nonlinear characteristics during actual operation, including dead zone (no response when the command signal is below a threshold), saturation zone (constant output when the command signal reaches its upper limit), and stall zone (the actuator stops rotating when the command signal approaches its full value). In existing calibration procedures, operators typically focus only on parameter values ​​(e.g., 5% for the water pump command) without incorporating the actuator's physical characteristics (e.g., the dead zone range of 0%-10%) into the calibration logic. This leads to a significant disconnect between the calibration parameters and the actual hardware behavior. A typical scenario is that the water pump is mistakenly triggered to full rotation when the command is 5% (when it should actually be in the dead zone), potentially causing cooling failure.

[0004] Post-calibration verification often relies on manual testing (such as manually testing key points like 0%, 5%, and 100%), which is inefficient and prone to oversights. For example, failing to verify whether the stop zone command (98%) actually stops the vehicle can cause the parameters to become invalid during vehicle operation.

[0005] Existing systems lack the ability to monitor the real-time behavior of actuators, cannot identify deviations between calibration parameters and hardware responses (such as the actuator still rotating when the instruction is 98%), and cannot intervene in the early stages of a fault, which can easily lead to abnormal thermal management (such as battery overheating, fast charging cooling failure) or even thermal runaway and other safety accidents.

[0006] In summary, there is an urgent need for a calibration method that can systematically handle the nonlinear characteristics of actuators, in order to solve the problems of manual calibration ignoring hardware physical characteristics, insufficient verification, and lack of operational monitoring, and improve the safety boundary and engineering reliability of thermal management systems. Summary of the Invention

[0007] This application provides a thermal management calibration method and system based on actuator characteristic modeling and real-time monitoring, which can solve the technical problems in the prior art where the nonlinear characteristics of the actuator are ignored, leading to a disconnect between calibration parameters and hardware behavior, abnormal thermal management, and safety risks.

[0008] In a first aspect, embodiments of this application provide a thermal management calibration method based on actuator characteristic modeling and real-time monitoring, the method comprising: Build an actuator characteristic curve library; Bind the actuator model to the characteristic curve; During the calibration process, the input range of calibration parameters is dynamically constrained based on the characteristic curve; After calibration, an automated verification process is executed, comparing the actual response with the expected actuator characteristic curve using a preset test sequence. Monitor the expected and actual behavior of the actuator in real time during runtime; When a deviation is detected, anomaly diagnosis and safety fault tolerance strategies are triggered.

[0009] In conjunction with the first aspect, in one implementation, the construction of the actuator characteristic curve library includes: defining the dead zone range, linear range, saturation range, and stop range of the actuator; and storing the dead zone range, linear range, saturation range, and stop range in association with the actuator model.

[0010] In conjunction with the first aspect, in one implementation, the input range of the dynamic constraint calibration parameters includes: in the calibration interface, limiting the selectable range of the input box to within the nonlinear characteristic range of the characteristic curve; and displaying a visual alarm prompt when the user input exceeds the nonlinear characteristic range.

[0011] In conjunction with the first aspect, in one implementation, the automated verification process includes: executing a preset test sequence, the preset test sequence covering multiple key points of the nonlinear characteristic range; automatically comparing the actual response with the expected response of the characteristic curve; and generating a verification report.

[0012] In conjunction with the first aspect, in one implementation, the real-time monitoring of the actuator's expected behavior and actual behavior includes: estimating the actuator's actual behavior through sensorless soft measurement; and comparing the actual behavior with the expected behavior.

[0013] In conjunction with the first aspect, in one implementation, the abnormal diagnosis includes: when the expected behavior is within the dead zone range, the actual behavior is a non-zero speed, triggering a characteristic curve mismatch fault code; when the expected behavior is within the stop range, the actual behavior is a non-zero speed, triggering a characteristic curve mismatch fault code.

[0014] In conjunction with the first aspect, in one implementation, the safety fault-tolerance strategy includes: automatically switching to a conservative operating mode when a serious mismatch is detected; and activating a backup actuator under critical operating conditions.

[0015] In conjunction with the first aspect, in one implementation, the preset test sequence includes: execution of zero instruction test, low instruction test, linear instruction test, high instruction test, and stop instruction test.

[0016] In conjunction with the first aspect, in one implementation, the automated verification process is executed before the calibration data is fed into the control unit, and the calibration data is allowed to be fed in only if all test points pass.

[0017] Secondly, embodiments of this application provide a thermal management calibration system based on actuator characteristic modeling and real-time monitoring, the system comprising: Actuator characteristic curve library, used to store the characteristic curves of actuators, including dead zone, linear zone, saturation zone and stall zone; Binding unit, used to bind actuator model to characteristic curve; Constraint units are used to dynamically constrain the input range of calibration parameters based on characteristic curves during the calibration process; The verification unit is used to execute a preset test sequence and compare the actual response with the expected response of the characteristic curve. The real-time monitoring unit is used to monitor the expected and actual behavior of the actuator in real time. The diagnostic unit is used to trigger anomaly diagnosis and safety fault tolerance strategies when a deviation is detected.

[0018] The beneficial effects of the technical solutions provided in this application include: By constructing an actuator characteristic curve library (including dead zone, linear zone, saturation zone, and stall zone) and forcibly binding it to the actuator model, combined with dynamic parameter constraints during calibration, automated verification after calibration, and sensorless soft measurement closed-loop monitoring during operation, the problem of calibration parameters being out of sync with hardware behavior caused by the manual calibration ignoring of actuator nonlinear characteristics (such as dead zone and stall zone) in related technologies is solved. This significantly reduces the thermal management failure rate, shortens calibration time, reduces debugging cycle, and achieves a safe closed loop for the thermal management system (such as automatically triggering the backup pump in fast charging scenarios), effectively preventing the risk of thermal runaway caused by pump malfunction. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating an embodiment of the thermal management calibration method based on actuator characteristic modeling and real-time monitoring according to this application; Figure 2 This is a schematic diagram of the functional modules of an embodiment of the thermal management calibration system based on actuator characteristic modeling and real-time monitoring according to this application. Detailed Implementation

[0020] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0021] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0022] In a first aspect, embodiments of this application provide a thermal management calibration method based on actuator characteristic modeling and real-time monitoring.

[0023] In one embodiment, reference is made to Figure 1 , Figure 1 This is a flowchart illustrating an embodiment of the thermal management calibration method based on actuator characteristic modeling and real-time monitoring according to this application. Figure 1 As shown, the thermal management calibration method based on actuator characteristic modeling and real-time monitoring includes: Step S1: Construct an actuator characteristic curve library.

[0024] Step S2: Bind the actuator model to the characteristic curve.

[0025] Step S3: During the calibration process, dynamically constrain the input range of calibration parameters based on the characteristic curve.

[0026] Step S4: After calibration, execute the automated verification process and compare the actual response with the expected actuator characteristic curve using a preset test sequence.

[0027] Step S5: Monitor the expected behavior and actual behavior of the actuator in real time during runtime.

[0028] Step S6: When a deviation is detected, trigger the anomaly diagnosis and safety fault tolerance strategy.

[0029] In this embodiment, by constructing an actuator characteristic curve library (including dead zone, linear zone, saturation zone, and stall zone) and forcibly binding it to the actuator model, combined with dynamic parameter constraints during the calibration process, automated verification after calibration, and sensorless soft measurement closed-loop monitoring during operation, the problem of calibration parameters being out of sync with hardware behavior caused by the manual calibration ignoring of actuator nonlinear characteristics (such as dead zone and stall zone) in related technologies is solved. This significantly reduces the thermal management failure rate, shortens the calibration time, reduces the debugging cycle, and achieves a safe closed loop for the thermal management system (such as automatically triggering the backup pump in fast charging scenarios), effectively preventing the risk of thermal runaway caused by pump malfunction.

[0030] Furthermore, in one embodiment, the aforementioned construction of the actuator characteristic curve library includes: defining the actuator's dead zone range, linear range, saturation range, and stall range. The aforementioned dead zone range, linear range, saturation range, and stall range are then stored in association with the actuator model.

[0031] In this embodiment, the pump characteristic range is predefined in the enterprise-level calibration database: Dead zone range: 0%–10% (the actuator does not respond when the command signal is below 10%).

[0032] Linear region: 10%–90% (the command signal and the speed are linearly related).

[0033] Saturation zone: 90%–95% (speed increase slows down after the command signal reaches 90%).

[0034] Stop zone: 95%–100% (the actuator stops rotating when the command signal is ≥95%).

[0035] The above-mentioned ranges are associated with and stored with the water pump model (e.g., PN code: PUMP-2023A) to form a characteristic curve library. The physical characteristics of the hardware are digitized before calibration, avoiding the neglect of nonlinear characteristics during manual calibration.

[0036] By defining the dead zone, linear zone, saturation zone, and stall zone of the actuator, and associating these characteristic ranges with the actuator model for storage, the problem of calibration parameters being out of sync with hardware behavior caused by the neglect of the nonlinear characteristics of the actuator in related technologies is solved, which significantly reduces the thermal management failure rate and improves calibration efficiency.

[0037] In VCU software or calibration tools, when an engineer selects a specific water pump model, the system automatically associates and loads its predefined characteristic curves. Calibration cannot be performed without selecting a model or associating a curve. In the vehicle software configuration management system, the water pump model (such as PN code) is strongly bound to a unique identifier in the characteristic curve database. When the model is selected, its corresponding characteristic curve parameters are automatically downloaded to the non-volatile memory of the vehicle controller.

[0038] For example, when the VCU calibration tool is started, the operator selects the water pump model (e.g., PUMP-2023A), and the system automatically loads the preset characteristic curve. If no model is selected or the model is not associated with a curve, the calibration interface will prompt that no characteristic curve is bound, prohibit the calibration operation, and lock the parameter input box to avoid incorrect model selection or omission of characteristic parameters (e.g., misusing an old model curve, which would cause calibration failure), and ensure that the calibration starting point is consistent with the hardware characteristics.

[0039] Furthermore, in one embodiment, the input range of the aforementioned dynamic constraint calibration parameters includes: in the calibration interface, limiting the selectable range of the input box to within the nonlinear characteristic range of the characteristic curve. When the user input exceeds the aforementioned range, a visual alarm prompt is displayed.

[0040] In this embodiment, when inputting command parameters on the calibration interface, the input range is limited to 95%–100% for the stop command (e.g., if 90% is input, the system automatically corrects it to 95%). When the input value enters the dead zone (e.g., 5%) or the stop zone (e.g., 98%), a red warning is highlighted on the interface (such areas will cause a full-run warning for the water pump). The calibration parameters are strictly constrained within physical boundaries (e.g., avoiding setting the 5% command as a stop command), reducing human error and improving calibration efficiency by 30%.

[0041] The calibration tool's parameter editing interface displays an overlay of the current water pump's characteristic curves, highlighting the dead zone, saturation zone, and stop zone. A prominent warning pops up when the mouse hovers over or when attempting calibration in a danger zone (such areas may trigger a full-speed pump warning).

[0042] An error is triggered when the calibration request (such as duty cycle) is inconsistent with the preset logic (such as the pump stop flag). For example, the duty cycle is set to stop at 2%, but the characteristic curve shows that 2% actually corresponds to full rotation.

[0043] By limiting the selectable range of the input box in the calibration interface to the nonlinear characteristic range of the characteristic curve, and displaying a visual alarm prompt when the user input exceeds the above range, the problem of calibration parameter input exceeding the physical boundary (such as the stop command being incorrectly set to 5%) caused by the neglect of the nonlinear characteristics of the actuator in related technologies is solved, which significantly shortens the calibration time and reduces the human error rate.

[0044] Furthermore, in one embodiment, the automated verification process includes: executing a preset test sequence, the preset test sequence covering multiple key points of the nonlinear characteristic range; automatically comparing the actual response with the expected response of the characteristic curve; and generating a verification report.

[0045] The aforementioned automated verification process is executed before the calibration data is fed into the control unit, and the calibration data is only allowed to be fed into the control unit if all test points pass.

[0046] In this embodiment, after calibration is completed or before software flashing, the system automatically executes a preset test sequence: Send a 0% duty cycle command to verify if it is at full speed (if so, it meets the expected characteristics).

[0047] Send a 5% command to verify whether it is full speed or low speed (as expected).

[0048] Send a 10% command to verify whether rotation has started.

[0049] Send a 90% command to verify whether the calibrated maximum speed has been reached.

[0050] Send a 98% command to verify whether the rotation has stopped.

[0051] Automatically compare the actual response with the characteristic curve / calibration expectation and generate a test report.

[0052] Only after all test points pass can the calibration data be activated or flashed into the VCU. If any test fails, a report is generated indicating a mismatch in the characteristic curves. This comprehensive coverage of key characteristic curve points eliminates omissions from manual verification and shortens the debugging cycle.

[0053] Furthermore, in one embodiment, the above-mentioned real-time monitoring of the actuator's expected behavior and actual behavior includes: estimating the actuator's actual behavior through sensorless soft measurement; and comparing the actual behavior with the expected behavior.

[0054] In this embodiment, the system monitors the pump's requested duty cycle and actual feedback (such as speed and flow rate, if sensors are available) in real time. For pumps without direct speed / flow feedback, an observer can be constructed using indirect parameters (such as motor current, bus voltage, temperature rise rate, etc.) to estimate the actual speed / flow rate, thereby achieving closed-loop comparison.

[0055] Furthermore, in one embodiment, the above-mentioned abnormal diagnosis includes: when the expected behavior is within the dead zone range, the actual behavior is a non-zero speed, triggering a characteristic curve mismatch fault code. When the expected behavior is within the stop range, the actual behavior is a non-zero speed, triggering a characteristic curve mismatch fault code.

[0056] In this embodiment, if a request is made to enter the dead zone (e.g., 5%), but the feedback indicates full rotation, a characteristic curve mismatch fault code is triggered. If a request is made to enter the stop zone (e.g., 98%), but the feedback indicates that rotation is still occurring, a fault code is triggered. If a request is made to be in the linear zone, but the feedback deviates significantly from the expected range (considering tolerances), an actuator performance degradation / fault diagnosis is triggered.

[0057] Furthermore, in one embodiment, the aforementioned safety fault-tolerance strategy includes: automatically switching to a conservative operating mode when a severe mismatch is detected; and activating a backup actuator under critical operating conditions.

[0058] In this embodiment, once a severe mismatch in the characteristic curves is detected, the system can automatically switch to a safe mode (such as using the most conservative preset curve or limiting power output, and recording detailed diagnostic data for analysis). In critical operating conditions (such as fast-charging battery cooling), if the water pump is detected not working as expected, a backup plan can be activated (such as reducing charging power or activating a backup pump).

[0059] Furthermore, in one embodiment, the aforementioned preset test sequence includes: execution of zero instruction test, low instruction test, linear instruction test, high instruction test, and stop instruction test.

[0060] By executing a preset test sequence of zero instruction test, low instruction test, linear instruction test, high instruction test, and stop instruction test, the problem of parameter omission caused by manual testing after calibration in related technologies is solved (such as not verifying whether 98% of the instructions in the stop zone actually stop). This significantly reduces the debugging cycle and ensures that the calibration data matches the hardware characteristics 100%.

[0061] Secondly, embodiments of this application also provide a thermal management calibration device based on actuator characteristic modeling and real-time monitoring.

[0062] In one embodiment, reference is made to Figure 2 , Figure 2 This is a functional module diagram of an embodiment of the thermal management calibration device based on actuator characteristic modeling and real-time monitoring according to this application. Figure 2 As shown, the thermal management calibration device based on actuator characteristic modeling and real-time monitoring includes an actuator characteristic curve library 1, a binding unit 2, a constraint unit 3, a verification unit 4, a real-time monitoring unit 5, and a diagnostic unit 6.

[0063] The actuator characteristic curve library 1 is used to store the characteristic curves of actuators, including dead zone, linear zone, saturation zone and stall zone.

[0064] Binding unit 2 is used to bind the actuator model to the characteristic curve.

[0065] Constraint unit 3 is used to dynamically constrain the input range of calibration parameters based on the characteristic curve during the calibration process.

[0066] Verification unit 4 is used to execute a preset test sequence and compare the actual response with the expected response of the characteristic curve.

[0067] The real-time monitoring unit 5 is used to monitor the expected behavior and actual behavior of the actuator in real time.

[0068] Diagnostic unit 6 is used to trigger anomaly diagnosis and safety fault tolerance strategies when a deviation is detected.

[0069] In this embodiment, by constructing an actuator characteristic curve library (including dead zone, linear zone, saturation zone, and stall zone) and forcibly binding it to the actuator model, combined with dynamic parameter constraints during the calibration process, automated verification after calibration, and sensorless soft measurement closed-loop monitoring during operation, the problem of calibration parameters being out of sync with hardware behavior caused by the manual calibration ignoring of actuator nonlinear characteristics (such as dead zone and stall zone) in related technologies is solved. This significantly reduces the thermal management failure rate, shortens the calibration time, reduces the debugging cycle, and achieves a safe closed loop for the thermal management system (such as automatically triggering the backup pump in fast charging scenarios), effectively preventing the risk of thermal runaway caused by pump malfunction.

[0070] Furthermore, in one embodiment, in the VCU software or calibration tool, when an engineer selects a specific water pump model, the system automatically associates and loads its predefined characteristic curve. Calibration cannot be performed without selecting a model or associating a curve. In the vehicle software configuration management system, the water pump model (such as a PN code) is strongly bound to a unique identifier in the characteristic curve database. When the model is selected, its corresponding characteristic curve parameters are automatically downloaded to the non-volatile memory of the vehicle controller.

[0071] Furthermore, in one embodiment, the input range of the aforementioned dynamic constraint calibration parameters includes: in the calibration interface, limiting the selectable range of the input box to within the nonlinear characteristic range of the characteristic curve. When the user input exceeds the aforementioned range, a visual alarm prompt is displayed.

[0072] In this embodiment, by limiting the selectable range of the input box in the calibration interface to the nonlinear characteristic range of the characteristic curve, and displaying a visual alarm prompt when the user input exceeds the above range, the problem of the nonlinear characteristics of the actuator being ignored, causing the calibration parameter input to exceed the physical boundary (such as the stop command being incorrectly set to 5%), in the related technology is solved, which significantly shortens the calibration time and reduces the human error rate.

[0073] Furthermore, in one embodiment, the automated verification process includes: executing a preset test sequence, the preset test sequence covering multiple key points of the nonlinear characteristic range; automatically comparing the actual response with the expected response of the characteristic curve; and generating a verification report.

[0074] The aforementioned automated verification process is executed before the calibration data is fed into the control unit, and the calibration data is only allowed to be fed into the control unit if all test points pass.

[0075] In this embodiment, calibration data is only allowed to be activated or flashed into the VCU after all test points are passed. If any test fails, a report is generated indicating a mismatch in the characteristic curves. This comprehensive coverage of key points in the characteristic curves eliminates omissions in manual verification and shortens the debugging cycle.

[0076] Furthermore, in one embodiment, the above-mentioned real-time monitoring of the actuator's expected behavior and actual behavior includes: estimating the actuator's actual behavior through sensorless soft measurement; and comparing the actual behavior with the expected behavior.

[0077] In this embodiment, the system monitors the pump's requested duty cycle and actual feedback (such as speed and flow rate, if sensors are available) in real time. For pumps without direct speed / flow feedback, an observer can be constructed using indirect parameters (such as motor current, bus voltage, temperature rise rate, etc.) to estimate the actual speed / flow rate, thereby achieving closed-loop comparison.

[0078] Furthermore, in one embodiment, the above-mentioned abnormal diagnosis includes: when the expected behavior is within the dead zone range, the actual behavior is a non-zero speed, triggering a characteristic curve mismatch fault code. When the expected behavior is within the stop range, the actual behavior is a non-zero speed, triggering a characteristic curve mismatch fault code.

[0079] In this embodiment, if a request is made to enter the dead zone (e.g., 5%), but the feedback indicates full rotation, a characteristic curve mismatch fault code is triggered. If a request is made to enter the stop zone (e.g., 98%), but the feedback indicates that rotation is still occurring, a fault code is triggered. If a request is made to be in the linear zone, but the feedback deviates significantly from the expected range (considering tolerances), an actuator performance degradation / fault diagnosis is triggered.

[0080] Furthermore, in one embodiment, the aforementioned safety fault-tolerance strategy includes: automatically switching to a conservative operating mode when a severe mismatch is detected; and activating a backup actuator under critical operating conditions.

[0081] In this embodiment, once a severe mismatch in the characteristic curves is detected, the system can automatically switch to a safe mode (such as using the most conservative preset curve or limiting power output, and recording detailed diagnostic data for analysis). In critical operating conditions (such as fast-charging battery cooling), if the water pump is detected not working as expected, a backup plan can be activated (such as reducing charging power or activating a backup pump).

[0082] Furthermore, in one embodiment, the aforementioned preset test sequence includes: execution of zero instruction test, low instruction test, linear instruction test, high instruction test, and stop instruction test.

[0083] By executing a preset test sequence of zero instruction test, low instruction test, linear instruction test, high instruction test, and stop instruction test, the problem of parameter omission caused by manual testing after calibration in related technologies is solved (such as not verifying whether 98% of the instructions in the stop zone actually stop). This significantly reduces the debugging cycle and ensures that the calibration data matches the hardware characteristics 100%.

[0084] The functions of each module in the above-mentioned thermal management calibration device based on actuator characteristic modeling and real-time monitoring correspond to the steps in the above-mentioned thermal management calibration method embodiment based on actuator characteristic modeling and real-time monitoring. Their functions and implementation processes will not be described in detail here.

[0085] Thirdly, embodiments of this application provide a thermal management calibration device based on actuator characteristic modeling and real-time monitoring. The thermal management calibration device based on actuator characteristic modeling and real-time monitoring can be a personal computer (PC), laptop computer, server, or other device with data processing capabilities.

[0086] In this embodiment, the thermal management calibration device based on actuator characteristic modeling and real-time monitoring may include a processor, a memory, a communication interface, and a communication bus.

[0087] The communication bus can be of any type and is used to interconnect the processor, memory, and communication interface.

[0088] The communication interface includes input / output (I / O) interfaces, physical interfaces, and logical interfaces. These interfaces enable interconnection of devices within the thermal management calibration equipment, which uses actuator characteristic modeling and real-time monitoring. They also enable interconnection between the thermal management calibration equipment and other devices (such as other computing devices or user equipment). Physical interfaces can be Ethernet interfaces, fiber optic interfaces, ATM interfaces, etc. User equipment can be displays, keyboards, etc.

[0089] Memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0090] The processor can be a general-purpose processor, which can call a thermal management calibration program based on actuator characteristic modeling and real-time monitoring stored in memory, and execute the thermal management calibration method based on actuator characteristic modeling and real-time monitoring provided in the embodiments of this application. For example, the general-purpose processor can be a central processing unit (CPU). The method executed when the thermal management calibration program based on actuator characteristic modeling and real-time monitoring is called can refer to the various embodiments of the thermal management calibration method based on actuator characteristic modeling and real-time monitoring in this application, and will not be repeated here.

[0091] Fourthly, embodiments of this application also provide a computer-readable storage medium.

[0092] The computer-readable storage medium of this application stores a thermal management calibration program based on actuator characteristic modeling and real-time monitoring, wherein when the aforementioned thermal management calibration program based on actuator characteristic modeling and real-time monitoring is executed by a processor, it implements the steps of the thermal management calibration method based on actuator characteristic modeling and real-time monitoring as described above.

[0093] The method implemented when the thermal management calibration program based on actuator characteristic modeling and real-time monitoring is executed can be referred to in various embodiments of the thermal management calibration method based on actuator characteristic modeling and real-time monitoring in this application, and will not be repeated here.

[0094] It should be noted that the sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0095] The terms "comprising" and "having," and any variations thereof, in the specification, claims, and accompanying drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus. The terms "first," "second," and "third," etc., are used to distinguish different objects, etc., and do not indicate a sequence, nor do they limit "first," "second," and "third" to different types.

[0096] In the description of the embodiments of this application, terms such as "exemplary," "for example," or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "exemplary," "for example," or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary," "for example," or "for instance" is intended to present the relevant concepts in a concrete manner.

[0097] In the description of the embodiments of this application, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The "and / or" in the text is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of this application, "multiple" means two or more.

[0098] In some processes described in the embodiments of this application, multiple operations or steps are included in a specific order. However, it should be understood that these operations or steps may not be executed in the order they appear in the embodiments of this application, or they may be executed in parallel. The sequence number of the operation is only used to distinguish different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed sequentially or in parallel, and these operations or steps may be combined.

[0099] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device to execute the methods described in the various embodiments of this application.

[0100] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A thermal management calibration method based on actuator characteristic modeling and real-time monitoring, characterized in that, The method comprises: building an actuator characteristic curve library; binding the actuator model with the characteristic curve; dynamically constraining the input range of the calibration parameters based on the characteristic curve during calibration; performing an automatic verification process after calibration, comparing the actual response with the expected response of the actuator characteristic curve through a preset test sequence; monitoring the expected behavior and actual behavior of the actuator in real time during runtime; triggering abnormal diagnosis and safety fault-tolerant strategy when deviation is detected.

2. The actuator property modeling and real-time monitoring based thermal management calibration method of claim 1, wherein, The building of the actuator characteristic curve library comprises: defining the dead zone range, linear range, saturation range and stall range of the actuator; and storing the dead zone range, linear range, saturation range and stall range in association with the actuator model.

3. The actuator property modeling and real-time monitoring based thermal management calibration method of claim 1, wherein, The dynamic constraint of the input range of the calibration parameters comprises: limiting the selectable range of the input box within the nonlinear characteristic interval of the characteristic curve in the calibration interface; and displaying a visual warning prompt when the user input exceeds the nonlinear characteristic interval.

4. The actuator property modeling and real-time monitoring based thermal management calibration method of claim 1, wherein, The automatic verification process comprises: performing a preset test sequence covering multiple key points of the nonlinear characteristic interval; automatically comparing the actual response with the expected response of the characteristic curve; and generating a verification report.

5. The actuator property modeling and real-time monitoring based thermal management calibration method of claim 1, wherein, The real-time monitoring of the expected behavior and actual behavior of the actuator comprises: estimating the actual behavior of the actuator through sensorless soft measurement; and comparing the actual behavior with the expected behavior.

6. The actuator property modeling and real-time monitoring based thermal management calibration method of claim 1, wherein, The abnormal diagnosis comprises: triggering a characteristic curve mismatch fault code when the expected behavior is in the dead zone range and the actual behavior is a non-zero speed; and triggering a characteristic curve mismatch fault code when the expected behavior is in the stall range and the actual behavior is a non-zero speed.

7. The actuator property modeling and real-time monitoring based thermal management calibration method of claim 1, wherein, The safety fault-tolerant strategy comprises: automatically switching to a conservative operation mode when a serious mismatch is detected; and enabling a backup actuator under critical working conditions.

8. The actuator property modeling and real-time monitoring based thermal management calibration method of claim 1, wherein, The preset test sequence comprises: zero instruction test, low instruction test, linear instruction test, high instruction test and stall instruction test.

9. The actuator property modeling and real-time monitoring based thermal management calibration method of claim 1, wherein, The automatic verification process is performed before the calibration data is brushed into the control unit, and only when all test points pass, the calibration data is allowed to be brushed in.

10. A thermal management calibration system based on actuator property modeling and real-time monitoring, characterized in that, The system comprises: an actuator characteristic curve library for storing the characteristic curve of the actuator, the characteristic curve comprising a dead zone range, a linear range, a saturation range and a stall range; a binding unit for binding the actuator model with the characteristic curve; a constraint unit for dynamically constraining the input range of the calibration parameters based on the characteristic curve during calibration; a verification unit for performing a preset test sequence and comparing the actual response with the expected response of the characteristic curve; a real-time monitoring unit for monitoring the expected behavior and actual behavior of the actuator in real time; a diagnosis unit for triggering abnormal diagnosis and safety fault-tolerant strategy when deviation is detected.

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