Intelligent control constant water temperature regulation method and system

Abstract

The application provides a kind of intelligent control constant water temperature regulation method and system, it is related to engine thermal management technical field, the method includes: real-time detection various parameters, including ambient temperature, cabin temperature, engine water temperature, main oil passage oil temperature, engine speed and engine torque;According to various parameters, the running condition of current engine including low-temperature cold start, normal temperature start and high-temperature start is judged, and the running condition judgment result is obtained;Based on the running condition judgment result, the opening and closing and opening degree of multifunctional valve are controlled in combination with preset water temperature threshold value;When water temperature is lower than preset first threshold value, close multifunctional valve to maintain small circulation mode;When water temperature is higher than preset second threshold value, gradually adjust the opening degree of multifunctional valve to transition to large circulation mode, and the state of function valve is monitored synchronously.The application can realize the precise constant control of engine water temperature, and improve engine operating efficiency and service life.

Description

Technical Field

[0001] This invention relates to the field of engine thermal management technology, and in particular to an intelligent control method and system for constant water temperature regulation. Background Technology

[0002] Stable control of engine coolant temperature is crucial for ensuring efficient engine operation and extending its service life. The quality of its control is directly related to engine power output, fuel economy, and operational reliability.

[0003] Most existing engine coolant temperature control systems suffer from the following technical defects: they primarily employ a single-component independent control mode. Specifically, after detecting the coolant temperature using a coolant temperature sensor, they individually drive components such as the thermostat, water pump, and fan. This lacks comprehensive analysis of multiple parameters, including ambient temperature, engine compartment temperature, main oil passage temperature, engine speed, and torque. Furthermore, a collaborative control mechanism for each control component has not been established, and the adjustment method is mainly based on passively responding to coolant temperature changes, failing to proactively predict and precisely coordinate based on operating conditions.

[0004] The aforementioned defects can lead to a series of problems, mainly in the following aspects: insufficient water temperature control precision, prone to large fluctuations, and difficult to maintain stable operation within the optimal range. This reduces engine combustion efficiency, increases fuel consumption, and exacerbates wear on internal parts, shortening engine lifespan. Under extreme conditions (such as cold starts at low temperatures and starts at high temperatures), it is impossible to balance the need for rapid engine warm-up with customer comfort. For example, in low-temperature environments, warm-up efficiency is low, and it is difficult to quickly meet the cabin insulation requirements. In high-temperature environments, the water temperature is prone to become too high due to insufficient heat dissipation. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide an intelligent control method for constant water temperature regulation, which can achieve precise and constant control of engine water temperature, improve engine operating efficiency and service life, and at the same time ensure the user experience of customers under different operating conditions.

[0006] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows:

[0007] A first aspect is a method for intelligent control of constant water temperature regulation, the method comprising:

[0008] Real-time monitoring of various parameters, including ambient temperature, cabin temperature, engine coolant temperature, main oil passage oil temperature, engine speed, and engine torque;

[0009] Based on various parameters, the current operating conditions of the engine, including low-temperature cold start, normal-temperature start and high-temperature start, are determined, and the operating condition determination result is obtained.

[0010] Based on the results of the operating condition judgment, the opening and closing of the multi-functional valve and the opening degree are controlled in combination with the preset water temperature threshold. When the water temperature is lower than the preset first threshold, the multi-functional valve is closed to maintain the small circulation mode. When the water temperature is higher than the preset second threshold, the opening degree of the multi-functional valve is gradually adjusted to transition to the large circulation mode, and the status of the multi-functional valve is monitored simultaneously.

[0011] Obtain the current engine load information and adjust the gear of the electronically controlled water pump according to the status of the multi-function valve to obtain the gear status of the electronically controlled water pump;

[0012] Based on the gear status of the electronically controlled water pump and the pre-acquired real-time engine speed, the speed of the electronic fan is dynamically controlled to form the current thermal management circuit status.

[0013] Based on the current thermal management loop status, the pre-stored historical operating data is continuously recorded and analyzed to adaptively optimize the control parameters of the multi-functional valve, the electric water pump, and the electric fan, thus forming optimized control parameters.

[0014] The current parameter change trend is analyzed based on the optimized control parameters to predict temperature fluctuations in advance, and the temperature fluctuation prediction results are obtained. Based on the temperature fluctuation prediction results, the coordinated operation of the multi-function valve, electronic water pump and electric fan is adjusted in a forward-looking manner to maintain the constant engine water temperature.

[0015] Furthermore, based on various parameters, the current engine operating conditions, including low-temperature cold start, normal-temperature start, and high-temperature start, are determined, and the operating condition determination results are obtained, including:

[0016] Acquire real-time ambient temperature data and cabin temperature data; compare the ambient temperature data with a preset first environmental threshold, and compare the cabin temperature data with a preset first cabin threshold.

[0017] When the ambient temperature is lower than or equal to the preset first ambient threshold, or the cabin temperature is lower than or equal to the preset first cabin threshold, the engine is determined to be in a low-temperature cold start condition, and the low-temperature cold start condition determination result is obtained.

[0018] If the ambient temperature is higher than the preset first ambient threshold, or the cabin temperature is higher than the preset first cabin threshold, then the ambient temperature is compared with the preset second ambient threshold, and the cabin temperature is compared with the preset second cabin threshold.

[0019] When the ambient temperature is higher than or equal to the preset second ambient threshold, or the cabin temperature is higher than or equal to the preset second cabin threshold, the engine is determined to be in a high-temperature start-up condition, and the high-temperature start-up condition determination result is obtained.

[0020] If the engine is determined to be neither a high-temperature start-up condition nor a low-temperature cold start-up condition, then the engine is determined to be a normal-temperature start-up condition, and the normal-temperature start-up condition determination result is obtained.

[0021] The results of low-temperature cold start condition judgment, high-temperature start condition judgment, and normal-temperature start condition judgment are integrated to form the operating condition judgment result.

[0022] Furthermore, based on the operational condition judgment results and combined with the preset water temperature threshold, the opening and closing of the multi-functional valve are controlled; when the water temperature is lower than the preset first threshold, the multi-functional valve is closed to maintain the small circulation mode; when the water temperature is higher than the preset second threshold, the opening of the multi-functional valve is gradually adjusted to transition to the large circulation mode, and the status of the multi-functional valve is monitored simultaneously, including:

[0023] The engine coolant temperature is obtained in real time. Based on the operating condition judgment, the real-time coolant temperature is compared with a preset first threshold. When the real-time coolant temperature is lower than the preset first threshold, the multi-function valve is controlled to be closed to maintain the engine small circulation mode.

[0024] When the engine coolant temperature is higher than the preset first threshold, the real-time coolant temperature is compared with the preset second threshold. The discrimination logic of two line segment intersection detection is used to make multiple condition judgments. That is, the current coolant temperature range and the set target coolant temperature range are regarded as two line segments. The adjustment strategy of the multi-function valve is determined by judging whether the two line segments or two ranges overlap.

[0025] Based on the adjustment strategy, when an overlap is detected between the current water temperature range and the set target water temperature range, the precise opening degree of the multi-functional valve is calculated according to the size of the overlap range and the judgment result of the operating conditions.

[0026] During the calculation of the precise opening degree, the engine coolant temperature change trend is continuously monitored, and the opening degree of the multi-function valve is dynamically adjusted to achieve a smooth transition from the small circulation mode to the large circulation mode; the current actual status of the multi-function valve is monitored simultaneously.

[0027] Furthermore, the current engine load information is obtained, and the speed of the electronically controlled water pump is adjusted according to the status of the multi-function valve to obtain the speed status of the electronically controlled water pump, including:

[0028] The current actual state of the multi-function valve and the real-time load information of the engine are obtained, and the engine load information is compared with the preset load threshold to obtain the comparison result.

[0029] Based on the comparison results, when the real-time engine load is lower than the preset load threshold and the multi-function valve is closed, the electronically controlled water pump is controlled to operate at a low flow rate.

[0030] When the engine load exceeds the preset load threshold or the multi-function valve is open, the electronically controlled water pump is switched to a high flow rate setting; during the switching process, the trend of engine load change is continuously monitored.

[0031] Based on the load change trend, the response speed of the electronically controlled water pump is dynamically adjusted to ensure that the flow regulation matches the engine operating conditions; while dynamically adjusting the electronically controlled water pump, the actual operating status of the electronically controlled water pump is acquired in real time.

[0032] The actual operating status is verified against the set target gear requirements to ensure that the electric water pump accurately executes the control commands and ultimately obtains the gear status of the electric water pump.

[0033] Furthermore, based on the gear status of the electronically controlled water pump and the pre-acquired real-time engine speed, the speed of the electronic fan is dynamically controlled to form the current thermal management circuit state, including:

[0034] Based on the gear status of the electronically controlled water pump, the corresponding basic heat dissipation requirements are determined; combined with the pre-acquired real-time engine speed, the basic heat dissipation requirements are corrected to generate the target heat dissipation intensity.

[0035] Calculate the target speed of the electric fan based on the target heat dissipation intensity; convert the target speed into a control signal for the electric fan to drive its operation.

[0036] During the operation of the electric fan, the actual speed of the electric fan is collected in real time. The actual speed is compared with the target speed to obtain the comparison result. Based on the comparison result, the control signal is adjusted to keep the actual speed stable within the target speed range, thus obtaining the final actual speed of the electric fan.

[0037] By combining the gear status of the integrated electronically controlled water pump, the real-time engine speed, and the final actual speed of the electric fan, a thermal management loop state characterizing the current heat dissipation capacity is generated, i.e., the current thermal management loop state.

[0038] Furthermore, based on the current thermal management loop status, pre-stored historical operating data is continuously recorded and analyzed to adaptively optimize the control parameters of the multi-functional valve, the electrically controlled water pump, and the electric fan, resulting in optimized control parameters, including:

[0039] Based on the current thermal management loop status, extract historical operating condition data similar to the current status from the pre-stored historical operating data; perform distribution density analysis on the historical operating condition data to identify high-frequency operating areas and abnormal operating points;

[0040] Based on the high-frequency operating range, a benchmark optimization model for control parameters is established; at the same time, the distribution characteristics of abnormal operating points are considered and analyzed to determine the safety boundary for parameter adjustment.

[0041] Based on the safety boundary of parameter adjustment, the baseline optimization model is constrained and corrected to obtain the corrected optimization model; based on the corrected optimization model, the optimization parameters for the opening degree of the multi-functional valve, the speed of the electric water pump, and the speed of the electric fan are generated respectively.

[0042] All optimized parameters are fused with the current control parameters to form a smooth transition parameter update strategy. The control effect of all optimized parameters in the current thermal management loop is verified in real time to complete the adaptive optimization of the control parameters, and finally the optimized control parameters are formed.

[0043] Furthermore, based on the optimized control parameters, the changing trends of the current parameters are analyzed to predict temperature fluctuations in advance, resulting in a temperature fluctuation prediction result. Based on the temperature fluctuation prediction result, the coordinated operation of the multi-function valve, electronically controlled water pump, and electric fan is proactively adjusted to maintain a constant engine coolant temperature, including:

[0044] Based on the optimized control parameters, real-time variation curves of engine coolant temperature, engine oil temperature, and environmental parameters are established; key characteristic parameters are extracted by trend analysis of the real-time variation curves.

[0045] Based on key characteristic parameters, predict the temperature change trajectory over a future time period; based on the temperature change trajectory, identify potential overheating or overcooling risk points;

[0046] For overheating or overcooling risk points, calculate the corresponding preventive control quantities; the preventive control quantities include the pre-adjustment opening of the multi-functional valve, the pre-switching gear of the electric water pump, and the pre-set speed of the electric fan.

[0047] Convert preventive control quantities into specific execution instructions, and adjust the coordinated working status of multi-functional valves, electric water pumps and electric fans in advance according to the specific execution instructions;

[0048] During the adjustment of the coordinated operation of the multi-function valve, electronically controlled water pump, and electric fan, the actual changes in engine coolant temperature are continuously monitored. The actual changes in coolant temperature are compared with the predicted temperature change trajectory in real time to dynamically correct the control parameters and ultimately maintain the engine coolant temperature within the set range.

[0049] Secondly, an intelligent control system for constant water temperature regulation, wherein the system performs the method described, including:

[0050] The acquisition module is used to detect various parameters in real time, including ambient temperature, cabin temperature, engine coolant temperature, main oil passage oil temperature, engine speed, and engine torque.

[0051] The judgment module determines the current operating conditions of the engine, including low-temperature cold start, normal-temperature start and high-temperature start, based on various parameters, and obtains the operating condition judgment result.

[0052] The processing module, based on the results of the operating condition judgment and combined with the preset water temperature threshold, controls the opening and closing of the multi-functional valve and its opening degree. When the water temperature is lower than the preset first threshold, the multi-functional valve is closed to maintain the small circulation mode. When the water temperature is higher than the preset second threshold, the opening degree of the multi-functional valve is gradually adjusted to transition to the large circulation mode, and the status of the multi-functional valve is monitored simultaneously.

[0053] The adjustment module obtains the current engine load information and adjusts the gear of the electronically controlled water pump according to the status of the multi-function valve to obtain the gear status of the electronically controlled water pump.

[0054] The control module dynamically controls the speed of the electric fan based on the gear status of the electronically controlled water pump and the pre-acquired real-time engine speed, thus forming the current thermal management circuit state.

[0055] The optimization module continuously records and analyzes pre-stored historical operating data based on the current thermal management loop status, in order to adaptively optimize the control parameters of the multi-functional valve, the electric water pump, and the electric fan, thus forming optimized control parameters.

[0056] The execution module analyzes the changing trend of the current parameters based on the optimized control parameters to predict temperature fluctuations in advance and obtain temperature fluctuation prediction results. Based on the temperature fluctuation prediction results, it proactively adjusts the coordinated operation of the multi-function valve, the electronically controlled water pump, and the electric fan to maintain a constant engine water temperature.

[0057] Thirdly, a computing device including a memory and a processor;

[0058] The memory stores one or more computer programs, the one or more computer programs including instructions; when the instructions are executed by the processor, the computing device performs the method as described in the first aspect.

[0059] Fourthly, a computer-readable storage medium for storing a computer program for performing the method as described in the first aspect.

[0060] The above-described solution of the present invention has at least the following beneficial effects:

[0061] Because it employs real-time multi-parameter detection, precise judgment based on different operating conditions, coordinated regulation of multi-functional valves, electronically controlled water pumps, and electronic fans, self-learning optimization of control parameters, and forward-looking prediction of temperature fluctuations, while retaining the priority of manual intervention, it effectively overcomes the technical problems of existing technologies, such as independent control of a single component, lack of comprehensive multi-parameter analysis and coordination mechanisms, passive adjustment, insufficient water temperature control accuracy, and difficulty in balancing engine operating needs and customer comfort under extreme operating conditions. This achieves precise and constant control of engine water temperature, improves engine operating efficiency and service life, and ensures a better user experience for customers under different operating conditions, resulting in better adaptability to operating conditions and human-machine collaboration. Attached Figure Description

[0062] Figure 1 A schematic diagram of a method for intelligent control and constant water temperature regulation;

[0063] Figure 2 This is a schematic diagram of an intelligent control system for constant water temperature regulation.

[0064] Figure 3 This is a schematic diagram of a computing device. Detailed Implementation

[0065] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0066] An embodiment of the present invention proposes an intelligent control method for constant water temperature regulation, the method comprising:

[0067] Step 1: Real-time monitoring of various parameters, including ambient temperature, cabin temperature, engine coolant temperature, main oil passage oil temperature, engine speed, and engine torque;

[0068] Step 2: Based on various parameters, determine the current operating conditions of the engine, including low-temperature cold start, normal-temperature start and high-temperature start, and obtain the operating condition judgment result;

[0069] Step 3: Based on the operating condition judgment results, and combined with the preset water temperature threshold, control the opening and closing of the multi-functional valve and its opening degree; when the water temperature is lower than the preset first threshold, close the multi-functional valve to maintain the small circulation mode; when the water temperature is higher than the preset second threshold, gradually adjust the opening degree of the multi-functional valve to transition to the large circulation mode, and monitor the status of the multi-functional valve simultaneously.

[0070] Step 4: Obtain the current engine load information and adjust the gear of the electronic water pump according to the status of the multi-function valve to obtain the gear status of the electronic water pump.

[0071] Step 5: Based on the gear status of the electronically controlled water pump and the pre-acquired real-time engine speed, dynamically control the speed of the electronic fan to form the current thermal management circuit status.

[0072] Step 6: Based on the current thermal management loop status, continuously record and analyze the pre-stored historical operating data to adaptively optimize the control parameters of the multi-functional valve, the electric water pump, and the electric fan, thus forming optimized control parameters;

[0073] Step 7: Analyze the changing trend of the current parameters based on the optimized control parameters to predict temperature fluctuations in advance and obtain temperature fluctuation prediction results; based on the temperature fluctuation prediction results, proactively adjust the coordinated operation of the multi-function valve, electronic water pump and electric fan to maintain a constant engine water temperature.

[0074] In this embodiment of the invention, the engine operating status is accurately captured by real-time detection of multiple core parameters such as ambient temperature and cabin temperature. Combined with the operating condition judgment results, the multi-functional valve, electronically controlled water pump, and electric fan are coordinated and linked to avoid the lag of independent control of a single component. With the addition of self-learning parameter optimization and temperature fluctuation prediction, the risk of abnormal water temperature fluctuations can be avoided in advance, and the water temperature can be maintained at a constant level efficiently. This not only improves the engine combustion efficiency and operating stability, reduces part wear and extends service life, but also adapts to various scenarios such as low-temperature cold start and high-temperature operation. At the same time, it ensures the comfort needs of customers under different operating conditions, retains the priority of manual intervention, and takes into account the convenience of intelligent control and the autonomy of human operation, effectively improving the adaptability and user experience under different operating conditions.

[0075] In a preferred embodiment of the present invention, step 1 above may include:

[0076] Step 1.1: Acquire ambient temperature data and cabin temperature data; simultaneously collect engine coolant temperature data and main oil passage oil temperature data. Specifically, this includes: an ambient temperature sensor, using a thermistor type, installed in an unobstructed ventilated location outside the engine compartment to capture the surrounding ambient temperature in real time and convert it into an electrical signal; a cabin temperature sensor positioned in the middle of the cockpit near the area where the driver and passengers are active, to accurately collect cabin temperature change data; engine coolant temperature sensors installed at the cylinder head outlet, cylinder block water jacket, and key nodes in the circulation pipeline, simultaneously collecting coolant temperature data from different key parts of the engine to comprehensively reflect the coolant temperature distribution; and a main oil passage oil temperature sensor embedded in the side wall of the main oil passage, in direct contact with the oil, to collect real-time temperature data of the oil flowing through the main oil passage.

[0077] Step 1.2: Acquire real-time engine speed and torque data. Specifically, this includes: the engine electronic control unit (ECU), also known as the engine control unit, is the core control module of the engine, responsible for receiving and processing various sensor signals and calculating key operating parameters; through the crankshaft position sensor installed at the front of the crankshaft, it detects changes in the tooth tip and backlash of the crankshaft gear ring, generating periodic pulse signals, and then calculates the real-time engine speed data based on the period of the pulse signals; simultaneously receiving real-time operating parameters from the air flow sensor, throttle position sensor, and fuel injection unit, and combining them with engine design parameters and actual operating calibration data, directly calculating the real-time engine torque data; among them, the speed and torque data are synchronously collected at a frequency of 10 times per second and stored in real time in the ECU's temporary data buffer area.

[0078] Step 1.3 verifies the validity of ambient temperature data, cabin temperature data, real-time engine speed data, and engine torque data to obtain valid data. Specifically, this includes: pre-setting reasonable value ranges for each parameter based on engine design parameters and actual operating experience; the reasonable range for ambient temperature is -40℃ to 50℃, cabin temperature is -10℃ to 40℃, engine coolant temperature is 0℃ to 130℃, main oil passage oil temperature is 0℃ to 150℃, engine speed is 0r / min to 3000r / min, and engine torque is 0N·m to the engine's maximum rated torque; each collected data is compared with its corresponding value range one by one; if three consecutive data collections exceed the range, they are judged as abnormal data and removed; if data transmission is missing, the previous valid data is used as a temporary substitute and marked; duplicate data retains the first collected value; finally, valid data that meets the value range, is transmitted completely, and has no duplicates is selected.

[0079] Step 1.4 involves standardizing the verified data to form a unified real-time parameter dataset. This includes: adopting a unified 16-bit binary data format standard to convert all verified data into the same data type and standard unit, with temperature data uniformly expressed in degrees Celsius, speed data in revolutions per minute, and torque data in Newton-meters; normalizing the converted data using a linear transformation method to map each parameter value to the 0-1 range to eliminate dimensional differences between different parameters; and sequentially integrating all standardized data according to a fixed structure of acquisition timestamp, ambient temperature, cabin temperature, engine coolant temperature, main oil passage oil temperature, engine speed, and engine torque to form a unified, standardized, and directly usable real-time parameter dataset for subsequent operating condition determination.

[0080] In this embodiment of the invention, multi-dimensional core data such as ambient temperature, cabin temperature, and engine coolant temperature are collected simultaneously to comprehensively capture the engine's operating status and surrounding environmental characteristics. Abnormal and invalid data are eliminated through validity verification to ensure the authenticity and reliability of the data. Furthermore, standardized processing is used to form a unified format of real-time parameter dataset, providing a high-quality data foundation for accurate determination of operating conditions and coordinated action of various control components. This not only reduces control decision errors caused by data deviations and improves the response accuracy of the entire control method, but also lays a solid data foundation for self-learning optimization and temperature forecasting, further ensuring the engine's operational stability.

[0081] In a preferred embodiment of the present invention, step 2 above may include:

[0082] Step 2.1: Acquire real-time ambient temperature data and cabin temperature data; compare the ambient temperature data with a preset first environmental threshold, and simultaneously compare the cabin temperature data with a preset first cabin threshold. Specifically, this includes: based on a time synchronization signal, extracting the latest ambient temperature data and cabin temperature data from the standardized real-time parameter dataset at a fixed frequency of 5 times per second; the preset first environmental threshold is 0℃ and the first cabin threshold is 10℃. First, convert the extracted raw temperature data into a standard format retaining one decimal place, and then simultaneously conduct two numerical comparisons through a preset comparison mechanism: one is the comparison between the ambient temperature and the first environmental threshold, and the other is the comparison between the cabin temperature and the first cabin threshold; during the comparison process, verify the consistency of the data format in real time to ensure that there is no format deviation. Record the two sets of comparison results in a structured form according to parameter name, comparison value, threshold, and result, clearly marking each set of results as meeting or not meeting the threshold conditions, providing a clear basis for subsequent steps.

[0083] Step 2.2: When the ambient temperature is lower than or equal to a preset first environmental threshold, or the cabin temperature is lower than or equal to a preset first cabin threshold, the engine is determined to be in a low-temperature cold start condition, i.e., a low-temperature cold start condition determination result is obtained. Specifically, this includes: first reading the identification information of two sets of comparison results, verifying whether the ambient temperature is lower than or equal to 0℃ and the cabin temperature is lower than or equal to 10℃ respectively, and then performing an OR operation according to preset logical operation rules; if the operation result is true, it is determined that the current condition is a low-temperature cold start condition, and a unique and non-repeatable condition determination code is generated; the specific values ​​of the ambient temperature and cabin temperature at the time of determination, the acquisition identifier of the corresponding sensor, and the data acquisition timestamp accurate to milliseconds are recorded simultaneously; at the same time, the standby state of the control channel associated with this condition is activated, and the preparatory control process is started to ensure that subsequent control actions can respond quickly.

[0084] Step 2.3: If the ambient temperature is higher than the preset first environmental threshold, or the cabin temperature is higher than the preset first cabin threshold, then the ambient temperature is compared with the preset second environmental threshold, and the cabin temperature is compared with the preset second cabin threshold. Specifically, if both sets of comparison results are not satisfied, i.e., the ambient temperature is higher than 0℃ and the cabin temperature is higher than 10℃, the data secondary verification process is initiated first; the temperature data collected from the three consecutive times is extracted, and the fluctuation range of each data and the average value is calculated. If the fluctuation does not exceed ±0.5℃, it is confirmed that the current data is not affected by instantaneous interference and has reliability; if the fluctuation exceeds the limit, the latest data is extracted again to replace the abnormal value and then verified again; after the verification is passed, the preset second environmental threshold is 35℃ and the second cabin threshold is 26℃. The comparison process is triggered by the synchronous clock to ensure that the comparison of the ambient temperature with the second environmental threshold and the comparison of the cabin temperature with the second cabin threshold are started synchronously without time difference; after the comparison is completed, the two sets of results are stored in the designated address of the temporary cache area, and the result status is updated in real time.

[0085] Step 2.4: When the ambient temperature is higher than or equal to the preset second ambient threshold, or the cabin temperature is higher than or equal to the preset second cabin threshold, the engine is determined to be in a high-temperature start-up condition, i.e., a high-temperature start-up condition determination result is obtained. Specifically, this includes: reading two sets of new comparison results from the temporary buffer area, starting the preset logic determination process, first verifying whether the ambient temperature is higher than or equal to 35℃ and whether the cabin temperature is higher than or equal to 26℃ respectively, and then integrating the verification results through OR logic rules. As long as any one of them meets the threshold condition, the condition confirmation step is entered; three consecutive temperature data are collected for consistency verification. If all of them meet the threshold requirements, the current condition is determined to be a high-temperature start-up condition, and a unique condition determination code is generated; the ambient temperature, cabin temperature, sensor working status identifier, and start-up duration at the time of determination are recorded synchronously, accurate to the second, and initial control parameters are preset based on the high-temperature heat dissipation requirements: the initial opening of the multi-function valve is set to 50% to open part of the large circulation, the electronic water pump is switched to a high position to ensure coolant flow, and the electric fan starts at a medium-high speed to form a basic heat dissipation combination, providing an initial benchmark for dynamic optimization and control in subsequent steps.

[0086] Step 2.5: If the engine is determined to be neither in a high-temperature start-up condition nor a low-temperature cold start-up condition, then the engine is determined to be in a normal-temperature start-up condition, i.e., a normal-temperature start-up condition determination result is obtained. Specifically, this includes: if the two sets of temperature data do not meet the conditions for both low-temperature cold start-up and high-temperature start-up, then the start-up interval stability verification process is performed; real-time temperature data is extracted three times consecutively, and the difference between the maximum and minimum values ​​of the ambient temperature and the cabin temperature is calculated each time. If both differences do not exceed 1℃, then the temperature is confirmed to be in a stable range; combined with the preset range standard, when the ambient temperature is stable between 0℃ and 35℃ and the cabin temperature is stable between 10℃ and 26℃, it is determined that the current condition is normal-temperature start-up, and a corresponding condition determination code is generated; then, the data is updated to the data traceability storage area in the format of timestamp, condition code, and temperature range, and the last five condition determination records are retained for future query and verification.

[0087] Step 2.6 integrates the results of the low-temperature cold start condition judgment, the high-temperature start condition judgment, and the normal-temperature start condition judgment to form the operating condition judgment result. Specifically, this includes: organizing and collecting the judgment codes corresponding to the three operating conditions, the specific temperature values ​​on which the judgment is based, the data acquisition timestamps, the sensor status identifiers, and the data validity verification results according to classification rules; generating a complete operating condition judgment result by following a fixed structured format of operating condition type code, judgment temperature parameter group, judgment timestamp, and data verification report; first storing the result in chronological order in a non-volatile storage area, retaining the most recent 100 records to prevent data loss; then pushing the result to the receiving end of the subsequent control process in a fixed frame format through a preset transmission protocol; after pushing, waiting for the receiving end to provide a successful reception signal; if no feedback is received within 500 milliseconds, automatically re-pushing once to ensure that the result is transmitted accurately and in a timely manner, ensuring the continuity of the control process.

[0088] In this embodiment of the invention, by acquiring real-time ambient temperature and cabin temperature data, and comparing them one by one with preset first and second environmental and cabin thresholds, three operating conditions—low-temperature cold start, high-temperature start, and normal-temperature start—are clearly distinguished, and then integrated to form a unified operating condition judgment result. This design overcomes the problems of vague and unspecific operating condition judgment in existing technologies, and provides a precise basis for the coordinated control of components such as multi-functional valves and electronically controlled water pumps. It ensures that the control actions are accurately matched with the engine starting conditions, which not only ensures the smooth start and operation of the engine under different temperature environments, but also better adapts to the comfort needs of customers under different operating conditions, and improves the accuracy of the operating condition adaptation of the entire control system.

[0089] In a preferred embodiment of the present invention, step 3 above may include:

[0090] Step 3.1: Obtain the real-time engine coolant temperature. Based on the operating condition judgment result, compare the real-time coolant temperature with a preset first threshold. When the real-time coolant temperature is lower than the preset first threshold, control the multi-function valve to be closed to maintain the engine's small circulation mode. Specifically, this includes: extracting real-time engine coolant temperature data from the standardized real-time parameter dataset at a frequency of 8 times per second, and simultaneously retrieving the complete operating condition judgment result for correlation matching; the preset first coolant temperature threshold is 60℃. After extracting the coolant temperature data, perform a double validity check: collect data twice consecutively; if the difference between the two data points does not exceed 0.3℃, the data is considered reliable; otherwise, ... The latest data is retrieved again; after verification, the real-time water temperature is compared with the 60℃ threshold with one decimal place precision; if the real-time water temperature is lower than or equal to 60℃, a closing control command is immediately sent to the multi-function valve in a fixed frame format, specifying the position parameters and execution time limit for the valve disc to be fully closed; after waiting for 50 milliseconds, the position signal fed back by the valve is received to confirm that the valve disc is in contact with the sealing surface, there is no leakage, and it is in a locked state; at the same time, the coolant flow sensor is used to assist in verification to confirm that the coolant only circulates in the engine block, cylinder head, water pump, and internal pipelines, and does not flow through the external radiator, locking the small circulation mode to quickly increase the water temperature in the core area.

[0091] Step 3.2: When the real-time engine coolant temperature is higher than the preset first threshold, the real-time coolant temperature is compared with the preset second threshold. A two-segment intersection detection logic is used for multi-condition judgment. That is, the current coolant temperature range and the set target coolant temperature range are considered as two line segments. The adjustment strategy of the multi-function valve is determined by judging whether the two line segments or two ranges overlap. Specifically, when the real-time coolant temperature is higher than 60℃, the preset second coolant temperature threshold is 96℃, and a precise comparison between the real-time coolant temperature and this threshold is completed simultaneously. The two-segment intersection detection logic is activated, and real-time coolant temperature data is continuously collected three times at 0.2-second intervals, with the first collection value as the starting point and the third as the ending point. If the starting point is greater than the ending point, the positions are swapped. Current water temperature range; set the target water temperature range to 90℃ to 100℃. After standardizing the order of the endpoints of the range, determine whether there is overlap by using the logic that the starting point of the current range is less than or equal to the ending point of the target range, and the ending point of the current range is greater than or equal to the starting point of the target range. Then start calculating the overlap ratio, that is, divide the length of the overlapping part by the total length of the target range (the total length of the target range is 10℃). If the overlap ratio exceeds 80%, maintain the current adjustment rhythm; between 30% and 80%, use gradual adjustment, with each opening change not exceeding 5%; if there is no overlap and the current water temperature is lower than the target range, then slowly accelerate the adjustment at a rate of 3% per second; if it is higher than the target range, then quickly adjust at a rate of 8% per second to ensure that it approaches the target range as soon as possible.

[0092] Step 3.3: Based on the adjustment strategy, when an overlap is detected between the current water temperature range and the set target water temperature range, the precise opening degree of the multi-functional valve is calculated according to the size of the overlap range and the operating condition judgment result. Specifically, this includes: Based on the determined adjustment strategy, first accurately calculating the overlap length between the current water temperature range and the target water temperature range: sorting the endpoints of the two ranges from smallest to largest, taking the difference between the maximum and minimum values ​​of the overlapping part as the overlap length, and then dividing it by 10℃ of the total length of the target range to obtain the overlap ratio; setting the adjustment coefficient in combination with the operating condition judgment result: for high-temperature start-up conditions where heat dissipation is urgent... The adjustment coefficient is set to 1.2; for normal temperature start-up conditions, the basic adjustment rhythm is maintained, with a coefficient of 1.0; for low temperature cold start conditions, warm-up needs to be taken into account, with a coefficient of 0.9; the initial opening value is calculated as precise opening degree = overlap ratio × 100% × adjustment coefficient, and a second verification is performed after calculation to ensure that the opening degree is within the safe range of 1% to 100%. If it exceeds the safe range, it is automatically corrected to the critical value; the final precise opening degree is bound to the operating condition code and timestamp, and then stored in the designated address of the control parameter cache area, while marking the calculation basis, including the overlap ratio and adjustment coefficient, for subsequent traceability and optimization.

[0093] Step 3.4: During the calculation of the precise opening degree, continuously monitor the trend of engine coolant temperature changes. Dynamically adjust the opening degree of the multi-function valve to achieve a smooth transition from the small circulation mode to the large circulation mode. Simultaneously monitor the current actual state of the multi-function valve, specifically: when adjusting the multi-function valve opening degree, advance at a fixed interval of once every 0.5 seconds, while continuously collecting real-time engine coolant temperature data at a frequency of 10 times per second; calculate the difference in coolant temperature between two adjacent measurements to determine the trend: a temperature increase exceeding 0.5℃ per second indicates a rapid rise, 0.2℃ to 0.5℃ indicates a slow rise, and below 0.2℃ indicates stabilization; if the coolant temperature rises rapidly, increase the opening degree by 5% each time based on the original adjustment rhythm; if the rise is slow, maintain the original rhythm, increasing the opening degree by 5% each time. The adjustment range is controlled within 3%. If the temperature stabilizes, the adjustment is paused, and after 3 seconds of observation, if the water temperature is still at the edge of the target range, fine-tuning continues. At the same time, the actual opening degree of the multi-functional valve, the valve disc running speed, and the current feedback signal are monitored in real time by the built-in position sensor. The actual opening degree is compared with the commanded opening degree in real time, and a correction command is sent immediately if the error exceeds 2%. If the feedback shows a deviation of more than 5% for 3 consecutive times, it is judged as stuck, and the backup adjustment channel is switched immediately, and the emergency adjustment program is started to try to unlock by gradually increasing the drive current. Throughout the process, the water temperature fluctuation is always aimed at not exceeding ±0.5℃ to ensure a smooth transition from small circulation mode to large circulation mode. All adjustment parameters and water temperature change data during the transition process are recorded simultaneously.

[0094] In this embodiment of the invention, by combining the results of the operating condition judgment with the real-time engine water temperature, the state of the multi-functional valve is adjusted in layers according to a preset threshold. The adjustment strategy is accurately determined by the discrimination logic of the intersection detection of two line segments. Then, the precise opening degree of the multi-functional valve is calculated according to the overlap range and operating conditions. At the same time, the opening degree is dynamically adjusted to achieve a smooth transition of the circulation mode and to monitor the actual state of the valve simultaneously. This design effectively overcomes the problems of insufficient valve adjustment precision, abrupt switching of circulation mode, and loss of valve state control in traditional water temperature control. It ensures that the action of the multi-functional valve is precisely matched with water temperature changes and operating conditions, which not only maintains the stability of water temperature under different operating conditions, but also ensures a smooth transition from small circulation to large circulation. This lays a reliable foundation for the coordinated control of the electronically controlled water pump and electronic fan, and further improves the stability and response accuracy of the intelligent control constant water temperature control system.

[0095] In a preferred embodiment of the present invention, step 4 above may include:

[0096] Step 4.1: Obtain the current actual status of the multi-function valve and the real-time engine load information. Compare the engine load information with a preset load threshold to obtain the comparison result. Specifically, this includes: acquiring the valve disc real-time position signal 10 times per second using the high-precision position sensor built into the multi-function valve, converting it into a precise opening value after second-order low-pass filtering; combining the valve's operating current feedback signal to determine whether there are any abnormalities such as jamming or leakage, and comprehensively generating current actual status data including opening degree and operating status; extracting real-time engine speed and torque data from the standardized real-time parameter dataset, and weighting them according to a ratio of 0.4 for speed and 0.6 for torque. For example, weighted calculations are performed to obtain real-time load information expressed as a percentage of the engine's rated load. The preset load threshold is 75% of the engine's rated load. The calculated real-time load data is processed using a three-fold moving average method. Three consecutive real-time load data points are extracted, and the arithmetic mean of the three is calculated. This average is used to replace the original value of the intermediate data point. All data are processed sequentially to effectively eliminate instantaneous fluctuation interference. The smoothed real-time load is compared with the 75% threshold with a precision of one decimal place. Results that are lower than, equal to, or higher than the threshold are clearly recorded. The data collection timestamp and validity identifier are marked and stored in a temporary cache for later retrieval.

[0097] Step 4.2: Based on the comparison results, when the real-time engine load is lower than the preset load threshold and the multi-function valve is closed, the electronically controlled water pump is controlled to operate at a low flow rate. Specifically, this includes: based on the comparison results, synchronously verifying the status feedback signal of the multi-function valve to confirm that the valve disc is fully closed, well-sealed, and without any jamming abnormalities; when the real-time engine load is lower than 75% of the preset threshold and the multi-function valve is fully closed, sending a low flow rate control command to the electronically controlled water pump in a fixed frame format, the command including a PWM duty cycle range of 40% to 50%, the target speed, and an execution time limit of 500 milliseconds; after sending the command, waiting 30 milliseconds, collecting the real-time output flow rate through the water pump flow sensor, and performing dual verification by combining the water pump speed feedback from the speed sensor, requiring that the flow rate fluctuation does not exceed ±2% and the speed deviation does not exceed ±3%; after successful verification, locking the low flow rate, continuously monitoring the engine load and multi-function valve status at a frequency of 2 times per second, and immediately triggering the gear re-evaluation process when the load change exceeds 10% or the valve status changes.

[0098] Step 4.3: When the engine load exceeds the preset load threshold or the multi-function valve is open, control the electronically controlled water pump to switch to the high flow rate setting. During the setting switch, continuously monitor the engine load trend, specifically including: when the real-time engine load exceeds 75% of the preset threshold, or the multi-function valve is open regardless of its opening degree, immediately initiate the electronically controlled water pump setting switch process; first, send a preheating signal to the water pump to activate the motor drive module for 10 milliseconds of preheating, stabilizing the motor operation to reduce current surges during switching; then, send a high flow rate setting control command, explicitly requiring the water pump to output the current rotation speed. The system rapidly reduces the maximum coolant flow rate to 100%, using a linear increase method to control the flow rate, increasing it by 20% per second until the target value is reached. During the switching process, real-time engine load data is collected at a frequency of 5 times per second, and the difference between two adjacent data points is calculated to determine whether the load is continuously increasing, remaining stable, or gradually decreasing. The system simultaneously records the switching time, which is controlled to be within 0.3 seconds, and the flow rate change curve. If the switching timeout exceeds 0.5 seconds, the switching command is resent, with a maximum of 3 retries. If the flow rate fluctuation exceeds ±10%, the flow rate increase rate is reduced to 10% per second to ensure a smooth and shock-free switching process.

[0099] Step 4.4: Dynamically adjust the response speed of the electronically controlled water pump according to the load change trend to ensure that the flow regulation matches the engine operating conditions. While dynamically adjusting the electronically controlled water pump, acquire its actual operating status in real time. Specifically, this includes: dynamically adjusting the response speed parameters of the electronically controlled water pump based on the monitored load change trend; if the load continues to rise and the difference is positive for three consecutive times with an absolute value greater than 5%, shorten the flow regulation time constant to 0.2 seconds to accelerate the rate at which the flow reaches the target value; if the load gradually decreases and the difference is negative for three consecutive times with an absolute value greater than 5%, extend the time constant to 0.5 seconds. Avoid excessive flow rate adjustment; if the load remains stable, maintain a reference time constant of 0.3 seconds; while adjusting the response speed, collect data 8 times per second from the pump's speed, current, and flow rate sensors, and use a weighted average with a flow rate weight of 0.5, a speed weight of 0.3, and a current weight of 0.2 to generate actual operating status data; compare the fused data with the preset standard value of the corresponding gear in real time, and if the deviation exceeds 3%, fine-tune the PWM duty cycle in a gradient of 1% to 3% to correct the drive signal, while monitoring the motor temperature. If the temperature is higher than 80℃, slow down the adjustment pace to ensure stable operation.

[0100] Step 4.5 verifies the actual operating status against the set target gear requirements to ensure the electric water pump accurately executes control commands and ultimately obtains the gear status of the electric water pump. Specifically, this includes multi-dimensional verification of the actual operating status data of the electric water pump in the order of flow rate, speed, current, noise, and temperature. The verification standards are: flow rate deviation not exceeding ±5%, speed deviation not exceeding ±3%, operating current within the rated range of 5 amps to 8 amps, operating noise below 65 decibels, and motor temperature not exceeding 85℃. If any indicator deviates beyond the allowable range, a correction command is sent in 5% increments to adjust the operating parameters. After waiting 20 milliseconds, data is re-collected for verification until all indicators meet the requirements. If the data collected five times consecutively meets the verification standard, the verification is deemed successful, confirming the current speed status of the electric water pump as low or high flow. The verified speed status, key operating data, verification results, and timestamps are bound and stored in a non-volatile storage area according to the timestamp speed parameter verification result format, retaining the most recent 100 records. The speed status is pushed to the subsequent thermal management loop control module through a preset transmission channel, waiting for the receiving end to provide a successful reception signal. If no feedback is received within 300 milliseconds, the data is re-pushed to ensure accurate data transmission.

[0101] In this embodiment of the invention, by associating the current actual state of the multi-functional valve with the real-time load information of the engine, and combining preset load thresholds to control the electronically controlled water pump speed according to different scenarios, the load change trend is continuously monitored during speed switching, the water pump response speed is dynamically adjusted, and the accurate execution of commands is ensured through verification of the actual operating state and the target speed. This design effectively overcomes the problems of fixed water pump speed, disconnect between flow regulation and engine operating conditions, and abrupt switching process in traditional systems. It achieves precise adaptation of the electronically controlled water pump flow rate with the state of the multi-functional valve and the engine load, making flow regulation more in line with real-time operating conditions. This improves the collaborative regulation efficiency of the intelligent control constant water temperature regulation system, indirectly ensuring stable control of engine water temperature, and further optimizing the reliability and economy of engine operation.

[0102] In a preferred embodiment of the present invention, step 5 above may include:

[0103] Step 5.1: Based on the gear status of the electronically controlled water pump, determine the corresponding basic heat dissipation requirements; combine this with the pre-acquired real-time engine speed to correct the basic heat dissipation requirements and generate the target heat dissipation intensity. Specifically, this includes: retrieving the stored current gear status of the electronically controlled water pump to determine whether it is in a low-flow or high-flow gear; determining the basic heat dissipation requirement level based on the coolant circulation flow characteristics corresponding to different gears, with low-flow gears corresponding to lower basic heat dissipation requirements and high-flow gears corresponding to higher basic heat dissipation requirements; extracting real-time engine speed data from a standardized real-time parameter dataset at a fixed frequency, continuously collecting three speed data points and calculating the average value to eliminate the impact of instantaneous speed fluctuations; setting correction coefficients for different speed ranges based on the correlation between engine speed and heat generation and dissipation, with higher speeds generating more heat and correspondingly increasing correction coefficients; multiplying the determined basic heat dissipation requirements by the correction coefficients for the corresponding speed range to accurately correct the basic heat dissipation requirements, ultimately generating the target heat dissipation intensity adapted to the current operating conditions, and recording the speed data and coefficient information used for correction.

[0104] Step 5.2: Calculate the target speed of the electric fan based on the target heat dissipation intensity; convert the target speed into a control signal for the electric fan to drive its operation. Specifically, this includes: establishing a correspondence between the target heat dissipation intensity and the target speed of the electric fan based on extensive prior heat dissipation test data to ensure that different heat dissipation intensities can be matched with efficient fan speeds; accurately matching the corresponding target speed of the electric fan within the preset correspondence based on the target heat dissipation intensity; converting the matched target speed into a drive control signal recognizable by the electric fan; using PWM modulation to determine a suitable duty cycle based on the linear adaptation law of speed and duty cycle; stably sending the modulated control signal to the electric fan receiver via a preset transmission path; upon receiving the signal, the receiver initiates the drive operation, controlling the electric fan to start operating at the target speed; after sending the control signal, waiting for a fixed duration to receive feedback confirmation information to confirm that the fan has successfully started without any abnormalities.

[0105] Step 5.3: During the operation of the electric fan, the actual speed of the electric fan is collected in real time. The actual speed is compared with the target speed to obtain the comparison result. Based on the comparison result, the control signal is adjusted to stabilize the actual speed within the target speed range, thus obtaining the final actual speed of the electric fan. Specifically, this includes: collecting the actual speed data of the fan in real time at high frequency to ensure timely capture of speed changes; comparing each collected actual speed with the preset target speed to accurately calculate the deviation between the two; formulating an adjustment strategy based on the magnitude and direction of the deviation; if the deviation is within the allowable range, keeping the current control signal unchanged; if the actual speed is lower than the target speed, appropriately increasing the PWM duty cycle to increase the speed; if the actual speed is higher than the target speed, appropriately decreasing the PWM duty cycle to decrease the speed; strictly controlling the change in duty cycle for each adjustment to avoid drastic fluctuations in speed; continuously repeating the closed-loop process of collection, comparison, and adjustment until the actual speed stabilizes within a reasonable range of the target speed and no longer fluctuates significantly. At this point, the stable speed is recorded as the final actual speed of the electric fan.

[0106] Step 5.4: Based on the combined status of the electronically controlled water pump, the real-time engine speed, and the final actual speed of the electric fan, a thermal management loop status representing the current heat dissipation capacity is generated, i.e., the current thermal management loop status. Specifically, this includes: sorting and collecting the current status of the electronically controlled water pump, the average data of the real-time engine speed, and the final actual speed of the electric fan; classifying and integrating these core data according to a fixed structure of water pump status, average engine speed, and final electric fan speed; combining the target heat dissipation intensity information to comprehensively evaluate the heat dissipation capacity of the current intelligent control constant water temperature regulation system, generating a thermal management loop status that includes heat dissipation level, operating parameters of each core component, and operating condition adaptability identifiers; storing the generated thermal management loop status in a non-volatile storage area, retaining a certain number of historical records in chronological order for subsequent operating condition traceability and system optimization; and simultaneously pushing this status to the engine control terminal through the data transmission path.

[0107] In this embodiment of the invention, the basic heat dissipation requirements are determined based on the electronically controlled water pump's gear position. This is then precisely corrected by combining the engine's real-time speed to generate the target heat dissipation intensity. Based on this, the target speed of the electronic fan is calculated and converted into a control signal to drive its operation. Simultaneously, by comparing the actual speed with the target speed in real time and adjusting the control signal through feedback, the fan speed is ensured to remain stable within the target range. Finally, a thermal management loop state is generated by integrating multiple dimensions of parameters. This design achieves deep coordination between the electronic fan speed, water pump gear position, and engine operating conditions, overcoming the shortcomings of traditional fixed or lagging fan speed adjustments. It allows the heat dissipation intensity to precisely match real-time heat dissipation requirements. The closed-loop feedback adjustment mechanism ensures the stability of the fan speed, preventing fluctuations in heat dissipation efficiency due to speed fluctuations. The generated thermal management loop state provides a basis for optimizing the intelligent control constant water temperature regulation system, further improving the response accuracy and operational stability of the system, helping the engine maintain its optimal operating temperature, and balancing operational reliability and fuel economy.

[0108] In a preferred embodiment of the present invention, step 6 above may include:

[0109] Step 6.1: Based on the current thermal management loop status, extract historical operating condition data similar to the current status from the pre-stored historical operating data; perform distribution density analysis on the historical operating condition data to identify high-frequency operating areas and abnormal operating points. Specifically, this includes: first, sorting out the core parameters of the current thermal management loop status, including water pump gear, engine average speed, electric fan final speed, target heat dissipation intensity, and real-time water temperature; using these core parameters as a reference, comparing each parameter of the pre-stored historical operating data item by item, setting reasonable deviation ranges for each parameter, and filtering out historical operating condition data where all parameter deviations are within the range; performing distribution density analysis on the filtered historical operating condition data, using a grid-based point set density estimation algorithm, the core principle of which is to... The multi-dimensional parameter space, consisting of water pump speed, average engine speed, final electric fan speed, target heat dissipation intensity, and real-time water temperature, is uniformly divided into non-overlapping grid cells with a fixed step size. Each cell precisely corresponds to a fixed range of parameter values, achieving full coverage of the parameter space without overlapping areas. After division, the number of historical data points contained in each grid cell is counted first. Then, the density calculation is optimized through a neighborhood expansion mechanism. That is, taking the current cell as the center, the eight adjacent grid cells are associated to form a complete neighborhood range. The number of points in the current cell and the neighboring cells is summed and then divided by the total parameter space size of the neighborhood range to obtain the local point set density value of the region. This avoids density misjudgment caused by parameter dispersion in a single cell and makes the density estimation more consistent with the actual distribution pattern.

[0110] After calculating the density of each grid cell individually, a density threshold is set based on the statistical average density of all cells. Clusters of grid cells with local density values ​​higher than the threshold and continuously adjacent to each other are designated as high-frequency operating areas. These areas represent the concentrated range of stable operating conditions and optimal parameter combinations in historical operation. For data points with local density values ​​much lower than the threshold and whose grid cell is more than the distance from all high-frequency area clusters, the parameters of normal operation are combined to determine whether they have caused problems such as water temperature fluctuations or component abnormalities. Data points that are confirmed to affect operational stability are marked as abnormal operating points, and the deviation direction and degree of each parameter are recorded in detail.

[0111] Step 6.2: Based on the high-frequency operating area, establish a benchmark optimization model for control parameters. Simultaneously, analyze the distribution characteristics of abnormal operating points to determine the safety boundary for parameter adjustment. Specifically, this includes: for each set of operating condition data within the identified high-frequency operating area, correlate the corresponding control parameter combination with the actual operating effect; compare key indicators such as water temperature stabilization time, component operating load, and energy consumption level under different control parameters, and select the control parameters with the best overall performance under each operating condition as sample data; combine the changing logic of operating conditions within the high-frequency area, such as the parameter adjustment pattern when engine speed increases or cooling demand increases, and fit and integrate these optimal sample data according to the changing trend of operating conditions to construct a benchmark optimization model for control parameters, ensuring that the model fits the actual operating requirements of normal operating conditions; simultaneously, classify abnormal operating points according to their abnormal manifestations, such as excessive water temperature, component stagnation, and abnormal energy consumption, trace the parameter combinations corresponding to each type of abnormality, analyze the direct causes of the abnormality, and clarify which parameters exceeding the normal range will cause operational abnormalities; combine the safety operation technical requirements of each component, refer to the critical values ​​of key parameters in the abnormal points, and delineate the maximum allowable fluctuation range for each control parameter adjustment, forming a safety boundary for parameter adjustment.

[0112] The specific construction and training process of the benchmark optimization model is as follows:

[0113] Based on the operation records of the intelligent control constant water temperature regulation system, complete operational data under historical operating conditions is collected, covering core control parameters such as multi-function valve opening, electronically controlled water pump gear, and electronic fan speed, as well as operating condition characterization parameters such as real-time engine speed, real-time water temperature, oil temperature, target heat dissipation intensity, ambient temperature, and ambient humidity. The collected raw data is preprocessed to remove abnormal data caused by sensor malfunctions or signal transmission interruptions, and to filter invalid data whose parameters exceed the safe operating range of components, retaining only valid datasets with stable operating conditions and complete parameters. Based on the operational performance of the intelligent control constant water temperature regulation system, the valid dataset is labeled, and judged from three dimensions: water temperature control accuracy, component operational coordination, and energy consumption level. The labeled dataset is then divided into training, validation, and test sets according to a preset ratio for model parameter iteration, fitting effect verification, and final performance evaluation, respectively.

[0114] A network structure for the baseline optimization model is constructed. The input layer uses real-time engine speed, target heat dissipation intensity, real-time water temperature, ambient temperature, and ambient humidity as input variables, which are normalized according to their actual physical meaning to eliminate the influence of dimensional differences. The output layer is set to provide optimal opening degree of the multi-function valve, optimal gear of the electronically controlled water pump, and optimal speed of the electric fan, directly outputting control parameter suggestions. The hidden layers adopt a multi-layer fully connected structure. Multiple hidden layers are set based on the nonlinear correlation characteristics of the operating condition data. The number of nodes in each hidden layer decreases progressively from the input layer to the output layer, enhancing the model's ability to fit complex operating condition mapping relationships and ensuring accurate capture of the optimal adaptation rules of control parameters under different operating conditions.

[0115] Next, the model training process is initiated, inputting the training set data into the initial model and using the gradient descent algorithm to iteratively update the model parameters. In each iteration, the model's predicted output is compared with the optimal parameters labeled on the dataset, the degree of deviation is calculated, and the weights and biases of each hidden layer are adjusted through backpropagation to gradually reduce the deviation. An early stopping mechanism is introduced during training, using the change in the deviation of the validation set as the monitoring basis. Training is stopped when the deviation of the validation set no longer decreases for several consecutive rounds to avoid overfitting, while saving the current optimal model parameters. Afterwards, the validation set data is input into the initially trained model to evaluate the prediction accuracy and error range. If the error exceeds a preset threshold, historical data from the working condition range in the error set is added, the dataset is re-divided, and a second iteration of training is performed. At the same time, hyperparameters such as the number of hidden layer nodes are adjusted to optimize the topology until the prediction effect on the validation set meets the target.

[0116] After model tuning, test set data is input into the model to conduct full-condition performance testing, verifying the model's adaptability to new operating conditions not previously trained. Once the tests are passed, the model parameters are fixed, and a mapping between the model parameters and the high-frequency operating region is established, ensuring that the model's output control parameters conform to the operating patterns of high-frequency conditions. Through this series of processes, a benchmark optimized model that can be directly applied to thermal management loop control is ultimately formed, ensuring that the model can accurately output optimal control parameters based on actual operating conditions.

[0117] Step 6.3: Based on the safety boundaries of parameter adjustment, the baseline optimization model is constrained and corrected to obtain the corrected optimization model. Based on the corrected optimization model, optimization parameters for the multi-function valve opening, the electric water pump speed, and the electric fan speed are generated. Specifically, this includes: first, clarifying the safety boundaries corresponding to each core control parameter; the multi-function valve opening has minimum closing and maximum opening limits; the electric water pump speed is only allowed to switch between low and high flow rates; and the electric fan speed has a minimum starting speed and a maximum safe speed range. These specific limitations are transformed into targeted constraints for the baseline optimization model. Each control parameter corresponds to an independent constraint rule to ensure that the constraints accurately cover all types of parameters. The baseline optimization model is then started for preliminary parameter calculations. Based on the optimal parameter patterns in the high-frequency operating region and combined with the core data of the current thermal management loop, the model generates preliminary calculation results for the multi-function valve opening, the electric water pump speed, and the electric fan speed. These preliminary results are then checked for safety boundaries by component type. First, it is checked whether the multi-function valve opening is within the allowable range, and then the electric water pump speed is checked for compliance and whether the electric fan speed exceeds the safe range.

[0118] If the preliminary calculation result of a certain parameter exceeds the corresponding safety boundary, targeted corrections are made based on the characteristics of that parameter; when the opening degree of the multi-function valve exceeds the limit, it is directly adjusted to the nearest safety critical value; when the gear of the electronically controlled water pump is in violation of regulations, the closest compliant gear is automatically matched; when the speed of the electronic fan exceeds the limit, it is corrected to the optimal speed value within the safe range; through such parameter-by-parameter verification and correction, the constraint adjustment of the benchmark optimization model is completed, forming the corrected optimization model; then, the core data of the current thermal management loop, including the current gear of the water pump, the average speed of the engine, the current speed of the electronic fan, the target heat dissipation intensity, and the real-time water temperature, are respectively input into the corrected optimization model; for the multi-function valve, the optimal opening degree is calculated within the safety boundary by combining the current circulation mode requirements and the opening degree adjustment law of the high-frequency area; for the electronically controlled water pump, the optimal gear is determined by referring to the current flow demand and the load correlation logic; for the electronic fan, the adaptation relationship between the target heat dissipation intensity and the speed is matched to calculate the efficient and safe optimized speed; the optimization parameter calculation of each component takes into account both the adaptability to normal working conditions and the operational safety.

[0119] Step 6.4: Integrate all optimized parameters with the current control parameters to form a smooth transition parameter update strategy. Verify the control effect of all optimized parameters in the current thermal management loop in real time to achieve adaptive optimization of the control parameters, ultimately forming optimized control parameters. Specifically, this includes: extracting the currently executing control parameters and matching the optimized parameters with the currently executing parameters according to the component types of the multi-functional valve, electric water pump, and electric fan; the parameter update strategy adopts a phased gradient transition method, initially setting an update ratio of 10% each time, i.e., replacing the corresponding current parameters with 10% of the optimized parameters during the first push, while the remaining 90% retains the original parameters; a fixed adaptation period is reserved after each update to allow the intelligent control constant water temperature regulation system to gradually adapt to the new parameter combination; during the adaptation period, the operating status of the intelligent control constant water temperature regulation system is monitored in real time. The system focuses on key indicators such as water temperature fluctuations, current stability of various components, noise levels, and energy consumption. If all indicators are within the normal range and operation is stable, the update ratio will be increased to 20% in the next update. If some indicators show slight fluctuations but do not exceed the safety threshold, the current update ratio will be maintained. If excessive water temperature fluctuations or abnormal component currents occur, the update ratio will be immediately reduced to 5%, and the increase will be paused until the intelligent control constant water temperature regulation system returns to stability. Following this dynamic adjustment logic, the replacement ratio of optimized parameters will be gradually increased, with each adjustment not exceeding 10% to avoid shocks caused by rapid parameter changes. The closed-loop process of parameter push, status monitoring, and ratio fine-tuning will be continuously repeated until the replacement ratio of optimized parameters reaches 100%, and the water temperature remains stable within the target range, all components operate in coordination, and energy consumption reaches the optimal level for several consecutive adaptation cycles. At this point, the adaptive optimization of the control parameters is completed, and the optimized control parameters are finally determined and stored.

[0120] In this embodiment of the invention, similar historical operating condition data is mined based on the current thermal management loop state. High-frequency operating areas and abnormal operating points are accurately identified through distribution density analysis. A baseline optimization model for control parameters is established based on the high-frequency areas, while the distribution characteristics of abnormal points clarify the safety boundaries for parameter adjustment. After constraint correction, an adaptive model is obtained, generating targeted optimization parameters for the multi-functional valve, electronically controlled water pump, and electric fan. Finally, a smooth transition strategy is formed by integrating the current parameters, and the control effect is verified in real time, completing the parameter adaptive optimization. This design effectively overcomes the shortcomings of traditional fixed and rigid control parameters, lack of dynamic optimization capabilities, and insufficient response to abnormal operating conditions. It ensures that control parameter optimization is both reasonable based on actual operating laws and reliable under safety boundary constraints. The smooth transition strategy avoids the impact of parameter mutations on the system, and the adaptive optimization mechanism enables the intelligent control constant water temperature regulation system to continuously adapt to changes in operating conditions, further improving the accuracy and stability of water temperature control, extending component lifespan, and optimizing engine operating efficiency and fuel economy.

[0121] In a preferred embodiment of the present invention, step 7 above may include:

[0122] Step 7.1: Based on the optimized control parameters, establish real-time variation curves for engine coolant temperature, oil temperature, and environmental parameters. Perform trend analysis on these real-time curves to extract key characteristic parameters. Specifically, this includes: retrieving the optimized control parameters and continuously collecting engine coolant temperature, oil temperature, and environmental parameter data at fixed short time intervals; environmental parameters mainly include ambient temperature and humidity, ensuring data continuity and accuracy during collection, and eliminating data with obvious collection errors to guarantee the reliability of the basic data; using the collection time as the horizontal axis and the values ​​of engine coolant temperature, oil temperature, ambient temperature, and ambient humidity as the vertical axes, first establish a basic data coordinate framework; then, use a polynomial curve fitting calculation method to construct the curve. The core implementation process is as follows: first, sort the continuously collected multiple sets of time-series data in chronological order, then select an appropriate fitting order, and determine the coefficients of the fitting curve by minimizing the sum of squared deviations between the data points and the fitted curve; for the time-series data of each parameter, complete the curve fitting segment by segment, so that the fitted curve accurately matches the actual change trend of the data, while smoothing out the small random fluctuations generated during the collection process.

[0123] After fitting, four independent real-time change curves are obtained. Then, a segmented trend analysis is performed on each curve. First, the curve is divided into rising, falling, and stable segments based on the slope change. The rising segment focuses on extracting the slope change amplitude and rising duration, the falling segment extracts the slope change amplitude and falling duration, and the stable segment extracts the stable value range and duration. At the same time, the occurrence time of the inflection point between each segment and the parameter value at the inflection point are recorded. These extracted information are integrated into key feature parameters.

[0124] Step 7.2: Based on key feature parameters, predict the temperature change trajectory over a future time period; based on the temperature change trajectory, identify potential overheating or overcooling risk points, specifically including: classifying and organizing all key feature parameters, dividing data into groups according to engine coolant temperature, engine oil temperature, and environmental parameters, serving as the core input for temperature prediction; combining the temperature change patterns under similar operating conditions in the historical database, selecting historical cases with high matching degree with the current feature parameters, and extracting their temperature change correlation logic; based on these logics, constructing a temperature change prediction logic that fits the actual operating scenario, and using a trend extrapolation method to carry out prediction, that is, first judging the trend of the current curve, and then based on the key feature parameters... Information such as slope and inflection points in key feature parameters is used to predict the trajectory of engine coolant and oil temperature changes in future time periods in stages, specifying the exact temperature prediction value corresponding to each time node, and providing the fluctuation range of the value to reflect the rationality of the prediction. The optimal operating temperature range of the engine is set in advance, and the predicted temperature change trajectory is compared with this range point by point. If the predicted temperature at a certain time node exceeds the upper limit of the optimal range and the subsequent trend is still upward, it is marked as a potential overheating risk point. If the predicted temperature is lower than the lower limit of the optimal range and the subsequent trend is continuously downward, it is marked as a potential undercooling risk point. The expected time of occurrence, the degree of temperature deviation, and the risk development trend of each risk point are recorded in detail.

[0125] Step 7.3: For overheating or overcooling risk points, calculate the corresponding preventive control quantities. These preventive control quantities include the pre-adjustment opening of the multi-functional valve, the pre-switching gear of the electric water pump, and the pre-set speed of the electric fan. Specifically, for each identified potential risk point, first assess its risk level, which is determined comprehensively based on the degree of temperature deviation and the duration of the risk. Then, combining the risk level, the expected occurrence time, and the current operating status of the thermal management loop, formulate a targeted control strategy and calculate the preventive control quantities. For overheating risk points, the core idea is to improve the heat dissipation capacity of the intelligent control constant water temperature regulation system. The pre-adjustment opening of the multi-functional valve is determined according to the risk level; the higher the risk, the larger the opening adjustment range. Simultaneously, ensure that the opening adjustment conforms to the flow logic of the coolant circulation path to guarantee rapid coolant flow. For the heat dissipation area: The pre-switching setting of the electronically controlled water pump is set to high flow rate. Increasing the pump speed increases the coolant circulation rate and accelerates heat transfer. The preset speed of the electronic fan is set according to heat dissipation requirements, matching the corresponding speed range based on the risk level. Higher risk levels result in higher speed settings to ensure rapid removal of excess heat. For overcooling risk points, the core approach is to reduce the heat dissipation capacity of the intelligent control constant water temperature regulation system. The pre-adjustment opening of the multi-function valve is adjusted according to the risk level, reducing the opening amplitude to decrease the amount of coolant involved in the heat dissipation circuit and thus reducing heat dissipation efficiency. The pre-switching setting of the electronically controlled water pump is set to low flow rate to reduce coolant circulation efficiency and minimize heat loss. Depending on the degree of temperature drop, the preset speed of the electronic fan is set to an even lower range, or a stop command is issued directly to avoid unnecessary heat loss.

[0126] Step 7.4: Convert preventative control quantities into specific execution instructions. Based on these instructions, adjust the coordinated operation of the multi-functional valve, electric water pump, and electric fan in advance. This includes: classifying the calculated preventative control quantities according to the component types of the multi-functional valve, electric water pump, and electric fan to ensure a clear correspondence between the control quantities for each component; for each component, converting the corresponding control quantity into specific and executable instructions, such as a clear opening angle instruction for the pre-adjustment degree of the multi-functional valve, a clear gear switching signal for the pre-switching position of the electric water pump, and a precise speed control instruction for the pre-set speed of the electric fan; and adjusting the operation in advance based on the expected occurrence time of the risk point. Sufficient adjustment response time should be reserved, and the response time needs to be determined based on the action delay characteristics of each component. Before a risk occurs, the command sending process should be initiated, and the commands should be sent sequentially to the control terminals of the corresponding components through a stable data transmission path. After the sending is completed, the command reception confirmation operation should be performed, and the components should be asked to send back a successful reception signal. If no feedback is received, the command should be resent to ensure that the command is transmitted correctly. After all components have sent back a successful reception signal, the multi-functional valve, the electric water pump, and the electric fan should be ensured to start the adjustment action synchronously according to the preset command. The multi-functional valve should be gradually adjusted to the pre-adjusted opening, the electric water pump should complete the gear switching, and the electric fan should be adjusted to the preset speed, forming a coordinated and linked preventive control mechanism.

[0127] Step 7.5: During the adjustment of the coordinated operation of the multi-functional valve, electronically controlled water pump, and electric fan, continuously monitor the actual changes in engine coolant temperature; compare the actual changes in coolant temperature with the predicted temperature change trajectory in real time to dynamically correct control parameters, ultimately maintaining a constant engine coolant temperature within the set range. Specifically, this includes: continuously collecting actual engine coolant temperature change data at a high frequency throughout the entire process of adjusting the coordinated operation of each component according to instructions. The collection frequency must be higher than the predicted time interval to ensure real-time capture of dynamic coolant temperature changes; organizing the collected actual coolant temperature data in chronological order to form an actual coolant temperature change sequence; accurately comparing the actual coolant temperature change sequence with the predicted temperature change trajectory in Step 7.2 at each time node, and calculating the actual value at each node compared with the predicted value. The magnitude and direction of the estimated deviation are analyzed. If the deviation is within the preset allowable range, the current preventive control command is effective, and the existing control parameters remain unchanged. If the deviation exceeds the allowable range, the cause is quickly analyzed based on the direction and magnitude of the deviation to determine whether the deviation is caused by insufficient or excessive control. The corresponding control parameters are dynamically adjusted according to different causes. If the actual water temperature is higher than the estimated temperature and there is a tendency to overheat, the electric fan speed or the opening of the multi-function valve is further increased to enhance the heat dissipation effect. If the actual water temperature is lower than the estimated temperature and there is a tendency to overcool, the opening of the multi-function valve is appropriately reduced or the electric fan speed is reduced to weaken the heat dissipation effect. The closed-loop process of water temperature acquisition, trajectory comparison, and parameter correction is continuously repeated until the engine water temperature stabilizes within the set optimal range, ultimately achieving constant water temperature control.

[0128] In this embodiment of the invention, based on optimized control parameters, real-time change curves of engine coolant temperature, oil temperature, and environmental parameters are established, and key feature parameters are extracted. Based on this, future temperature change trajectories are predicted, potential overheating or overcooling risks are identified, and preventative control quantities such as the pre-adjustment opening of the multi-function valve, the pre-switching gear of the electronically controlled water pump, and the pre-set speed of the electronic fan are calculated and converted into execution commands to preemptively adjust the collaborative working state of each component. Simultaneously, the actual coolant temperature changes are continuously monitored and compared with the predicted trajectory in real time, and control parameters are dynamically corrected. This design breaks through the limitations of traditional reactive coolant temperature control. Through a closed-loop logic of preventative prediction, pre-coordinated adjustment, and dynamic correction, coolant temperature control is upgraded from passive adaptation to proactive prediction, effectively avoiding the impact of abnormal temperature fluctuations on the engine and improving the foresight and accuracy of coolant temperature control. The coordinated pre-adjustment of each component ensures consistent control actions, and the dynamic correction mechanism further consolidates the stability of coolant temperature control, ultimately achieving precise and constant engine coolant temperature within the set range, creating an optimal operating temperature environment for the engine.

[0129] A smart control system for constant water temperature regulation includes:

[0130] The acquisition module is used to detect various parameters in real time, including ambient temperature, cabin temperature, engine coolant temperature, main oil passage oil temperature, engine speed, and engine torque.

[0131] The judgment module determines the current operating conditions of the engine, including low-temperature cold start, normal-temperature start and high-temperature start, based on various parameters, and obtains the operating condition judgment result.

[0132] The processing module, based on the results of the operating condition judgment and combined with the preset water temperature threshold, controls the opening and closing of the multi-functional valve and its opening degree. When the water temperature is lower than the preset first threshold, the multi-functional valve is closed to maintain the small circulation mode. When the water temperature is higher than the preset second threshold, the opening degree of the multi-functional valve is gradually adjusted to transition to the large circulation mode, and the status of the multi-functional valve is monitored simultaneously.

[0133] The adjustment module obtains the current engine load information and adjusts the gear of the electronically controlled water pump according to the status of the multi-function valve to obtain the gear status of the electronically controlled water pump.

[0134] The control module dynamically controls the speed of the electric fan based on the gear status of the electronically controlled water pump and the pre-acquired real-time engine speed, thus forming the current thermal management circuit state.

[0135] The optimization module continuously records and analyzes pre-stored historical operating data based on the current thermal management loop status, in order to adaptively optimize the control parameters of the multi-functional valve, the electric water pump, and the electric fan, thus forming optimized control parameters.

[0136] The execution module analyzes the changing trend of the current parameters based on the optimized control parameters to predict temperature fluctuations in advance and obtain temperature fluctuation prediction results. Based on the temperature fluctuation prediction results, it proactively adjusts the coordinated operation of the multi-function valve, the electronically controlled water pump, and the electric fan to maintain a constant engine water temperature.

[0137] The control system according to embodiments of the present invention can correspond to the execution of the method described in the embodiments of the present invention, and the above and other operations and / or functions of each module of the control system are respectively for implementing Figure 1 The corresponding process of the method in the illustrated embodiment will not be described in detail here for the sake of brevity.

[0138] This application also provides a computing device. This computing device can utilize a server.

[0139] like Figure 3 As shown in the figure, this is a schematic diagram of a computing device provided in an embodiment of this application. The computing device 700 includes a bus 701, a processor 702, a communication interface 703, and a memory 704. The processor 702, the memory 704, and the communication interface 703 communicate with each other via the bus 701.

[0140] The 701 bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 3 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0141] The processor 702 can be any one or more of the following processors: central processing unit (CPU), graphics processing unit (GPU), microprocessor (MP), or digital signal processor (DSP).

[0142] Communication interface 703 is used for external communication. Memory 704 may include volatile memory, such as random access memory (RAM). Memory 704 may also include non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid-state drive (SSD). Memory 704 stores executable code, which processor 702 executes to perform the aforementioned intelligent control constant water temperature regulation method.

[0143] Specifically, in implementing the embodiment of the intelligent control constant water temperature regulation system described above, and where each module or unit of the intelligent control constant water temperature regulation system described above is implemented by software, the software or program code required to execute the functions of each module / unit in the intelligent control constant water temperature regulation system described above can be partially or entirely stored in the memory 704. The processor 702 executes the program code corresponding to each unit stored in the memory 704 to execute the aforementioned intelligent control constant water temperature regulation method.

[0144] This application also provides a computer-readable storage medium. The computer-readable storage medium can be any available medium that a computing device can store, or a data storage device such as a data center containing one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state drive). The computer-readable storage medium includes instructions that instruct the computing device to execute the aforementioned intelligent control constant water temperature regulation method.

[0145] This application also provides a computer program product comprising one or more computer instructions. When the computer instructions are loaded and executed on a computing device, all or part of the processes or functions described in this application are generated.

[0146] The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, or data center to another website, computer, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means.

[0147] When the computer program product is executed by a computer, the computer executes any of the aforementioned intelligent control constant water temperature regulation methods. The computer program product can be a software installation package; when any of the aforementioned intelligent control constant water temperature regulation methods is required, the computer program product can be downloaded and executed on the computer.

[0148] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for intelligent control of constant water temperature regulation, characterized in that, The method includes: Step 1: Real-time monitoring of various parameters, including ambient temperature, cabin temperature, engine coolant temperature, main oil passage oil temperature, engine speed, and engine torque; Step 2: Based on various parameters, determine the current operating conditions of the engine, including low-temperature cold start, normal-temperature start and high-temperature start, and obtain the operating condition judgment result; Step 3: Based on the operating condition judgment results, and combined with the preset water temperature threshold, control the opening and closing of the multi-functional valve and its opening degree; when the water temperature is lower than the preset first threshold, close the multi-functional valve to maintain the small circulation mode; when the water temperature is higher than the preset second threshold, gradually adjust the opening degree of the multi-functional valve to transition to the large circulation mode, and monitor the status of the multi-functional valve simultaneously. Step 4: Obtain the current engine load information and adjust the gear of the electronic water pump according to the status of the multi-function valve to obtain the gear status of the electronic water pump. Step 5: Based on the gear status of the electronically controlled water pump and the pre-acquired real-time engine speed, dynamically control the speed of the electronic fan to form the current thermal management circuit status. Step 6: Based on the current thermal management loop status, continuously record and analyze the pre-stored historical operating data to adaptively optimize the control parameters of the multi-functional valve, the electric water pump, and the electric fan, thus forming optimized control parameters; Step 7: Analyze the changing trend of the current parameters based on the optimized control parameters to predict temperature fluctuations in advance and obtain temperature fluctuation prediction results; based on the temperature fluctuation prediction results, proactively adjust the coordinated operation of the multi-function valve, electronic water pump and electric fan to maintain a constant engine water temperature.

2. The intelligent control method for constant water temperature regulation according to claim 1, characterized in that, Based on various parameters, the current operating conditions of the engine, including low-temperature cold start, normal-temperature start, and high-temperature start, are determined, and the operating condition determination results are obtained, including: Acquire real-time ambient temperature data and cabin temperature data; compare the ambient temperature data with a preset first environmental threshold, and compare the cabin temperature data with a preset first cabin threshold. When the ambient temperature is lower than or equal to the preset first ambient threshold, or the cabin temperature is lower than or equal to the preset first cabin threshold, the engine is determined to be in a low-temperature cold start condition, and the low-temperature cold start condition determination result is obtained. If the ambient temperature is higher than the preset first ambient threshold, or the cabin temperature is higher than the preset first cabin threshold, then the ambient temperature is compared with the preset second ambient threshold, and the cabin temperature is compared with the preset second cabin threshold. When the ambient temperature is higher than or equal to the preset second ambient threshold, or the cabin temperature is higher than or equal to the preset second cabin threshold, the engine is determined to be in a high-temperature start-up condition, and the high-temperature start-up condition determination result is obtained. If the engine is determined to be neither a high-temperature start-up condition nor a low-temperature cold start-up condition, then the engine is determined to be a normal-temperature start-up condition, and the normal-temperature start-up condition determination result is obtained. The results of low-temperature cold start condition judgment, high-temperature start condition judgment, and normal-temperature start condition judgment are integrated to form the operating condition judgment result.

3. The intelligent control method for constant water temperature regulation according to claim 2, characterized in that, Based on the results of the operating condition judgment, the opening and closing of the multi-functional valve and the opening degree are controlled in combination with the preset water temperature threshold; when the water temperature is lower than the preset first threshold, the multi-functional valve is closed to maintain the small circulation mode. When the water temperature exceeds the preset second threshold, the opening of the multi-functional valve is gradually adjusted to transition to the large circulation mode, while simultaneously monitoring the status of the multi-functional valve, including: The engine coolant temperature is obtained in real time. Based on the operating condition judgment, the real-time coolant temperature is compared with a preset first threshold. When the real-time coolant temperature is lower than the preset first threshold, the multi-function valve is controlled to be closed to maintain the engine small circulation mode. When the engine coolant temperature is higher than the preset first threshold, the real-time coolant temperature is compared with the preset second threshold. The discrimination logic of two line segment intersection detection is used to make multiple condition judgments. That is, the current coolant temperature range and the set target coolant temperature range are regarded as two line segments. The adjustment strategy of the multi-function valve is determined by judging whether the two line segments or two ranges overlap. Based on the adjustment strategy, when an overlap is detected between the current water temperature range and the set target water temperature range, the precise opening degree of the multi-functional valve is calculated according to the size of the overlap range and the judgment result of the operating conditions. During the calculation of the precise opening degree, the engine coolant temperature change trend is continuously monitored, and the opening degree of the multi-function valve is dynamically adjusted to achieve a smooth transition from the small circulation mode to the large circulation mode; the current actual status of the multi-function valve is monitored simultaneously.

4. The intelligent control method for constant water temperature regulation according to claim 3, characterized in that, Obtain current engine load information and adjust the electronic water pump's speed according to the status of the multi-function valve to obtain the electronic water pump's speed status, including: The current actual state of the multi-function valve and the real-time load information of the engine are obtained, and the engine load information is compared with the preset load threshold to obtain the comparison result. Based on the comparison results, when the real-time engine load is lower than the preset load threshold and the multi-function valve is closed, the electronically controlled water pump is controlled to operate at a low flow rate. When the engine load exceeds the preset load threshold or the multi-function valve is open, the electronically controlled water pump is switched to a high flow rate setting; during the switching process, the trend of engine load change is continuously monitored. Based on the load change trend, the response speed of the electronically controlled water pump is dynamically adjusted to ensure that the flow regulation matches the engine operating conditions; while dynamically adjusting the electronically controlled water pump, the actual operating status of the electronically controlled water pump is acquired in real time. The actual operating status is verified against the set target gear requirements to ensure that the electric water pump accurately executes the control commands and ultimately obtains the gear status of the electric water pump.

5. The intelligent control method for constant water temperature regulation according to claim 4, characterized in that, Based on the gear status of the electronically controlled water pump and the pre-acquired real-time engine speed, the speed of the electronic fan is dynamically controlled to form the current thermal management circuit state, including: Based on the gear status of the electronically controlled water pump, the corresponding basic heat dissipation requirements are determined; combined with the pre-acquired real-time engine speed, the basic heat dissipation requirements are corrected to generate the target heat dissipation intensity. Calculate the target speed of the electric fan based on the target heat dissipation intensity; convert the target speed into a control signal for the electric fan to drive its operation. During the operation of the electric fan, the actual speed of the electric fan is collected in real time. The actual speed is compared with the target speed to obtain the comparison result. Based on the comparison result, the control signal is adjusted to keep the actual speed stable within the target speed range, thus obtaining the final actual speed of the electric fan. By combining the gear status of the integrated electronically controlled water pump, the real-time engine speed, and the final actual speed of the electric fan, a thermal management loop state characterizing the current heat dissipation capacity is generated, i.e., the current thermal management loop state.

6. The intelligent control method for constant water temperature regulation according to claim 5, characterized in that, Based on the current thermal management loop status, pre-stored historical operating data is continuously recorded and analyzed to adaptively optimize the control parameters of the multi-functional valve, the electrically controlled water pump, and the electric fan, resulting in optimized control parameters, including: Based on the current thermal management loop status, extract historical operating condition data similar to the current status from the pre-stored historical operating data; perform distribution density analysis on the historical operating condition data to identify high-frequency operating areas and abnormal operating points; Based on the high-frequency operating range, a benchmark optimization model for control parameters is established; at the same time, the distribution characteristics of abnormal operating points are considered and analyzed to determine the safety boundary for parameter adjustment. Based on the safety boundary of parameter adjustment, the baseline optimization model is constrained and corrected to obtain the corrected optimization model; based on the corrected optimization model, the optimization parameters for the opening degree of the multi-functional valve, the speed of the electric water pump, and the speed of the electric fan are generated respectively. All optimized parameters are fused with the current control parameters to form a smooth transition parameter update strategy. The control effect of all optimized parameters in the current thermal management loop is verified in real time to complete the adaptive optimization of the control parameters, and finally the optimized control parameters are formed.

7. The intelligent control method for constant water temperature regulation according to claim 6, characterized in that, Based on the optimized control parameters, the changing trend of the current parameters is analyzed to predict temperature fluctuations in advance and obtain temperature fluctuation prediction results. Based on temperature fluctuation predictions, the coordinated operation of the multi-function valve, electronically controlled water pump, and electric fan is proactively adjusted to maintain a constant engine coolant temperature, including: Based on the optimized control parameters, real-time variation curves of engine coolant temperature, engine oil temperature, and environmental parameters are established; key characteristic parameters are extracted by trend analysis of the real-time variation curves. Based on key characteristic parameters, predict the temperature change trajectory over a future time period; based on the temperature change trajectory, identify potential overheating or overcooling risk points; For overheating or overcooling risk points, calculate the corresponding preventive control quantities; the preventive control quantities include the pre-adjustment opening of the multi-functional valve, the pre-switching gear of the electric water pump, and the pre-set speed of the electric fan. Convert preventive control quantities into specific execution instructions, and adjust the coordinated working status of multi-functional valves, electric water pumps and electric fans in advance according to the specific execution instructions; During the adjustment of the coordinated operation of the multi-function valve, electronically controlled water pump, and electric fan, the actual changes in engine coolant temperature are continuously monitored. The actual changes in coolant temperature are compared with the predicted temperature change trajectory in real time to dynamically correct the control parameters and ultimately maintain the engine coolant temperature within the set range.

8. A smart control system for constant water temperature regulation, characterized in that, The system performs the method as described in any one of claims 1 to 7, comprising: The acquisition module is used to detect various parameters in real time, including ambient temperature, cabin temperature, engine coolant temperature, main oil passage oil temperature, engine speed, and engine torque. The judgment module determines the current operating conditions of the engine, including low-temperature cold start, normal-temperature start and high-temperature start, based on various parameters, and obtains the operating condition judgment result. The processing module, based on the results of the operating condition judgment and combined with the preset water temperature threshold, controls the opening and closing of the multi-functional valve and its opening degree. When the water temperature is lower than the preset first threshold, the multi-functional valve is closed to maintain the small circulation mode. When the water temperature is higher than the preset second threshold, the opening degree of the multi-functional valve is gradually adjusted to transition to the large circulation mode, and the status of the multi-functional valve is monitored simultaneously. The adjustment module obtains the current engine load information and adjusts the gear of the electronically controlled water pump according to the status of the multi-function valve to obtain the gear status of the electronically controlled water pump. The control module dynamically controls the speed of the electric fan based on the gear status of the electronically controlled water pump and the pre-acquired real-time engine speed, thus forming the current thermal management circuit state. The optimization module continuously records and analyzes pre-stored historical operating data based on the current thermal management loop status, in order to adaptively optimize the control parameters of the multi-functional valve, the electric water pump, and the electric fan, thus forming optimized control parameters. The execution module analyzes the changing trend of the current parameters based on the optimized control parameters to predict temperature fluctuations in advance and obtain temperature fluctuation prediction results. Based on the temperature fluctuation prediction results, it proactively adjusts the coordinated operation of the multi-function valve, the electronically controlled water pump, and the electric fan to maintain a constant engine water temperature.

9. A computing device, characterized in that, Including memory and processor; The memory stores one or more computer programs, the one or more computer programs including instructions; when the instructions are executed by the processor, the computing device performs the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store a computer program for performing the method as described in any one of claims 1 to 7.

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