Automobile air conditioner pre-adjusting energy-saving control method and system based on in-automobile environment prediction
By constructing a thermal hysteresis prediction model based on multi-source heterogeneous data, we have achieved accurate prediction and energy-saving control of the future in-vehicle thermal environment, solved the comfort and energy consumption problems in traditional air conditioning control methods, and improved the pre-adjustment capability and energy-saving effect of automotive air conditioning.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ZHUHAI WISDOM HI-TECH ELECTRIC TECH CO LTD
- Filing Date
- 2026-04-08
- Publication Date
- 2026-05-05
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
Existing automotive air conditioning control methods lack the ability to predict future in-vehicle thermal environment, resulting in poor comfort and increased energy consumption. They fail to fully consider the impact of driver physiological state, vehicle speed, and road weather changes on thermal hysteresis.
By collecting multi-source heterogeneous data to construct a thermal hysteresis prediction model, the perceived comfort index within a future preset time window is extrapolated, and energy-saving graded intervention strategies are implemented, including airflow organization adjustment, air volume regulation and cooling power regulation, to optimize the energy consumption of the air conditioning system step by step.
It improves the accuracy of predicting the future in-vehicle thermal environment, avoids the lag of traditional feedback control, reduces the energy consumption of the air conditioning system, and enhances in-vehicle comfort and energy-saving performance.
Smart Images
Figure CN121973598A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of automotive intelligent control technology, and in particular to an automotive air conditioning pre-adjustment energy-saving control method and system based on in-vehicle environment prediction. Background Technology
[0002] With the rapid development of intelligent and new energy vehicles, users are increasingly demanding higher levels of thermal comfort and energy efficiency in their vehicles. In the high temperatures of summer, when cars are exposed to solar radiation for extended periods, interior materials absorb and store a significant amount of heat, resulting in a substantial thermal hysteresis effect.
[0003] Traditional automotive air conditioning control methods typically rely solely on real-time data such as the current interior temperature and outside ambient temperature for feedback-based adjustments, lacking the ability to predict future interior thermal conditions. The compressor is only activated for forced cooling when a rise in interior temperature is detected or the user experiences discomfort. This delayed adjustment not only leads to a poor comfort experience but also results in unnecessary energy consumption due to frequent high-load compressor operation.
[0004] In addition, existing technologies have significant limitations in heat load identification: most solutions only focus on environmental heat loads such as solar radiation, failing to fully consider the direct impact of the driver's physiological state (such as skin sweating and metabolic heat generation) on physical comfort, resulting in a disconnect between air conditioning control strategies and the actual thermal sensation of the human body, making it difficult to achieve precise and differentiated energy-saving intervention.
[0005] Meanwhile, during vehicle operation, changes in vehicle speed significantly affect the convective cooling efficiency of the interior, thereby altering the intensity of the thermal hysteresis effect; and the micro-meteorological conditions of the road ahead (such as cloudy skies or intense sunlight) directly influence the future intensity of solar radiation. Existing air conditioning control methods generally fail to incorporate these dynamic factors into predictive models, resulting in insufficient accuracy in extrapolating the future thermal environment inside the vehicle, and significantly reducing the accuracy and energy-saving effect of pre-adjustment strategies.
[0006] Therefore, how to construct an accurate thermal hysteresis prediction model based on multi-source heterogeneous data, identify the perceived comfort index within a preset time window in advance, and implement energy-saving control accordingly has become a technical problem that urgently needs to be solved in the field of vehicle air conditioning control. Summary of the Invention
[0007] To address the aforementioned technical problems, the purpose of this application is to provide a method and system for pre-adjusting energy-saving control of automotive air conditioning based on in-vehicle environment prediction, aiming to solve at least one of the aforementioned technical problems.
[0008] In a first aspect, embodiments of this application provide a method for pre-adjusting and energy-saving control of automotive air conditioning based on in-vehicle environment prediction, the method comprising:
[0009] Real-time collection of multi-source heterogeneous data including the rate of change of solar radiation heat flux outside the vehicle, the rate of change of the resistance value of micro-perspiration on the driver's skin, the ambient temperature outside the vehicle, and the micro-meteorological type of the road section ahead.
[0010] Based on the multi-source heterogeneous data, a thermal hysteresis prediction model is constructed to predict the in-vehicle thermal environment state within a future preset time window and generate the body comfort index within the future preset time window.
[0011] The system compares the perceived comfort index within a future preset time window with a preset threshold. If the perceived comfort index within the future preset time window is greater than the preset threshold and the current measured comfort index is lower than the pre-adjustment trigger line, then it is determined to enter the pre-adjustment mode.
[0012] In the pre-adjustment mode, an energy-saving graded intervention strategy is implemented for the automotive air conditioning system.
[0013] Furthermore, the step of constructing a thermal hysteresis prediction model based on the multi-source heterogeneous data, extrapolating the in-vehicle thermal environment state within a future preset time window, and generating a perceived comfort index within the future preset time window includes:
[0014] Based on the rate of change of solar radiation heat flux outside the vehicle, combined with the vehicle speed and the thermal time constant of the interior materials, the cumulative heat absorption of the interior surface within the future time window is estimated and mapped into an equivalent temperature increment, which serves as the first input component of the thermal hysteresis prediction model.
[0015] The rate of change of the impedance value of the microperspiration on the driver's contact surface is trend-identified. When a continuous decrease in impedance value is detected, the cumulative index of future skin moisture is calculated based on the rate of change of the impedance value of the microperspiration on the driver's contact surface, and mapped to the future equivalent metabolic heat production power. The future equivalent metabolic heat production power within the future time window is integrated to obtain the mean value of the future equivalent metabolic heat production power, which is used as the second input component of the thermal hysteresis prediction model.
[0016] The basic weights are obtained based on the micro-weather type identifier of the road section ahead, and the basic weights are corrected by using the difference between the predicted future outside temperature and the set temperature inside the vehicle, so as to generate dynamic boundary correction coefficients within the future time window.
[0017] The current measured comfort index, the first input component, the second input component, and the dynamic boundary correction coefficient are weighted and fused to generate a future perceived comfort index within a preset time window.
[0018] Furthermore, the steps of implementing an energy-saving tiered intervention strategy for the automotive air conditioning system include:
[0019] The following intervention steps should be implemented step by step and evaluated in real time:
[0020] Level 1 intervention: Execute airflow organization adjustment, control the electric air outlet blades to form a dynamic air curtain that blocks the direct sunlight path, and keep the blower speed constant; if the human comfort index is lower than the preset threshold after the first preset time of the Level 1 intervention, the subsequent intervention is terminated; otherwise, Level 2 intervention is executed.
[0021] Level 2 intervention: If the outside temperature is lower than the current average inside temperature, the air volume and fresh air are adjusted, the fresh air damper opening is increased and the blower speed is increased; if the body comfort index is lower than the preset threshold after the second preset time of the Level 2 intervention, the subsequent intervention is terminated; otherwise, Level 3 intervention is performed.
[0022] Level 3 intervention: Execute cooling power adjustment and increase compressor operating frequency.
[0023] Secondly, embodiments of this application provide an automotive air conditioning pre-adjustment energy-saving control system based on in-vehicle environment prediction, the system comprising:
[0024] The data acquisition module is used to collect multi-source heterogeneous data in real time, including the rate of change of solar radiation heat flux outside the vehicle, the rate of change of the impedance value of microperspiration on the driver's skin, the ambient temperature outside the vehicle, and the micro-meteorological type of the road section ahead.
[0025] The body comfort index prediction module is used to construct a thermal hysteresis prediction model based on the multi-source heterogeneous data, to deduce the in-vehicle thermal environment state within a future preset time window, and to generate the body comfort index within the future preset time window.
[0026] The judgment module is used to compare the perceived comfort index within a future preset time window with a preset threshold. If the perceived comfort index within the future preset time window is greater than the preset threshold and the current measured comfort index is lower than the pre-adjustment trigger line, then it is determined to enter the pre-adjustment mode.
[0027] An execution module is used to implement an energy-saving graded intervention strategy for the automotive air conditioning system in the pre-adjustment mode.
[0028] Furthermore, the step of constructing a thermal hysteresis prediction model based on the multi-source heterogeneous data, extrapolating the in-vehicle thermal environment state within a future preset time window, and generating a perceived comfort index within the future preset time window includes:
[0029] Based on the rate of change of solar radiation heat flux outside the vehicle, combined with the vehicle speed and the thermal time constant of the interior materials, the cumulative heat absorption of the interior surface within the future time window is estimated and mapped into an equivalent temperature increment, which serves as the first input component of the thermal hysteresis prediction model.
[0030] The rate of change of the impedance value of the microperspiration on the driver's contact surface is trend-identified. When a continuous decrease in impedance value is detected, the cumulative index of future skin moisture is calculated based on the rate of change of the impedance value of the microperspiration on the driver's contact surface, and mapped to the future equivalent metabolic heat production power. The future equivalent metabolic heat production power within the future time window is integrated to obtain the mean value of the future equivalent metabolic heat production power, which is used as the second input component of the thermal hysteresis prediction model.
[0031] The basic weights are obtained based on the micro-weather type identifier of the road section ahead, and the basic weights are corrected by using the difference between the predicted future outside temperature and the set temperature inside the vehicle, so as to generate dynamic boundary correction coefficients within the future time window.
[0032] The current measured comfort index, the first input component, the second input component, and the dynamic boundary correction coefficient are weighted and fused to generate a future perceived comfort index within a preset time window.
[0033] Furthermore, the energy-saving tiered intervention strategy for the automotive air conditioning system includes:
[0034] The following intervention steps should be implemented step by step and evaluated in real time:
[0035] Level 1 intervention: Execute airflow organization adjustment, control the electric air outlet blades to form a dynamic air curtain that blocks the direct sunlight path, and keep the blower speed constant; if the human comfort index is lower than the preset threshold after the first preset time of the Level 1 intervention, the subsequent intervention is terminated; otherwise, Level 2 intervention is executed.
[0036] Level 2 intervention: If the outside temperature is lower than the current average inside temperature, the air volume and fresh air are adjusted, the fresh air damper opening is increased and the blower speed is increased; if the body comfort index is lower than the preset threshold after the second preset time of the Level 2 intervention, the subsequent intervention is terminated; otherwise, Level 3 intervention is performed.
[0037] Level 3 intervention: Execute cooling power adjustment and increase compressor operating frequency.
[0038] This application embodiment constructs a predictive model considering thermal hysteresis by integrating multi-source heterogeneous data such as the rate of change of solar radiation heat flux outside the vehicle, the rate of change of driver's skin micro-perspiration impedance, the ambient temperature outside the vehicle, and the micro-meteorological type of the road ahead. This improves the accuracy of predicting the perceived comfort index within a future preset time window. By using the dual judgment of "the future perceived comfort index being greater than a preset threshold and the current measured comfort index being lower than the pre-adjustment trigger line", the pre-adjustment mode is precisely triggered, avoiding the hysteresis of traditional feedback control. On this basis, an energy-saving graded intervention strategy is implemented for the automotive air conditioning system to reduce the energy consumption of the air conditioning system. Attached Figure Description
[0039] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.
[0040] Figure 1 This is a schematic flowchart of the automotive air conditioning pre-adjustment energy-saving control method based on in-vehicle environment prediction provided in the embodiments of this application;
[0041] Figure 2 This is a schematic diagram of the structure of the automotive air conditioning pre-adjustment energy-saving control system based on in-vehicle environment prediction provided in the embodiments of this application. Detailed Implementation
[0042] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.
[0043] Those skilled in the art will understand that, unless explicitly stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in the specification of this application means the presence of features, integers, steps, operations, elements, modules, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, modules, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or wireless coupling. The term “and / or” as used herein includes all or any modules and all combinations of one or more associated listed items.
[0044] Those skilled in the art will understand that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined as herein.
[0045] Please see Figure 1 This application provides a method for pre-adjusting and energy-saving control of automotive air conditioning based on in-vehicle environment prediction. The method includes:
[0046] S1. Real-time collection of multi-source heterogeneous data including the rate of change of solar radiation heat flux outside the vehicle, the rate of change of the resistance value of micro-perspiration on the driver's skin, the ambient temperature outside the vehicle, and the micro-meteorological type of the road ahead.
[0047] S2. Based on the multi-source heterogeneous data, construct a thermal hysteresis prediction model, deduce the in-vehicle thermal environment state within a future preset time window, and generate the body comfort index within the future preset time window.
[0048] S3. Compare the body comfort index within the future preset time window with the preset threshold. If the body comfort index within the future preset time window is greater than the preset threshold and the current measured comfort index is lower than the pre-adjustment trigger line, then determine to enter the pre-adjustment mode.
[0049] S4. In the pre-adjustment mode, an energy-saving graded intervention strategy is implemented for the automotive air conditioning system.
[0050] This application embodiment is based on an in-vehicle hardware system, which includes at least: a solar radiation sensor for collecting the rate of change of solar radiation heat flux outside the vehicle (e.g., installed on the outside of the vehicle to avoid obstruction by the vehicle body and ensure the collection of unobstructed solar radiation data); a skin impedance sensor for collecting the rate of change of the micro-perspiration impedance value of the driver's skin (embedded in the contact surface between the driver's seat cushion and backrest, or the steering wheel grip area, conforming to the driver's skin contact scenario to achieve real-time collection of physiological data); an outside temperature sensor for collecting the outside ambient temperature (e.g., installed on the inside of the front bumper of the vehicle in a well-ventilated location without direct sunlight to avoid environmental interference and ensure accurate temperature collection); an in-vehicle navigation module / vehicle networking module for obtaining the micro-weather type identifier of the road section ahead (integrated into the in-vehicle central control system, obtaining real-time road section weather data through the vehicle networking, or associating with the weather information of the road section ahead through the navigation map); and an in-vehicle controller (ECU) for executing the method, constructing a thermal hysteresis prediction model, and controlling the air conditioning system (installed inside the vehicle dashboard, and connected to various sensors, the air conditioning system, and the navigation / The vehicle networking module establishes a communication connection and serves as the core execution unit of the entire control method. The method described in this application can be applied to new energy vehicles.
[0051] In this embodiment, the perceived comfort index is a comprehensive evaluation index constructed by integrating the in-vehicle thermal environment, the heat retention lag effect of the interior, the driver's skin physiological state, and the external road weather conditions. It is used to quantitatively characterize the degree of hot or cold felt by the driver and passengers. The higher the perceived comfort index, the hotter the driver and passengers feel, and the lower the comfort level; the lower the index value, the cooler the driver and passengers feel, and the higher the comfort level.
[0052] This application embodiment constructs a predictive model considering thermal hysteresis by integrating multi-source heterogeneous data such as the rate of change of solar radiation heat flux outside the vehicle, the rate of change of driver's skin micro-perspiration impedance, the ambient temperature outside the vehicle, and the micro-meteorological type of the road ahead. This improves the accuracy of predicting the perceived comfort index within a future preset time window. By using the dual judgment of "the future perceived comfort index being greater than a preset threshold and the current measured comfort index being lower than the pre-adjustment trigger line", the pre-adjustment mode is precisely triggered, avoiding the hysteresis of traditional feedback control. On this basis, an energy-saving graded intervention strategy is implemented for the automotive air conditioning system to reduce the energy consumption of the air conditioning system.
[0053] In one embodiment, the step of constructing a thermal hysteresis prediction model based on the multi-source heterogeneous data, extrapolating the in-vehicle thermal environment state within a future preset time window, and generating a perceived comfort index within the future preset time window includes:
[0054] Based on the rate of change of solar radiation heat flux outside the vehicle, combined with the vehicle speed and the thermal time constant of the interior materials, the cumulative heat absorption of the interior surface within the future time window is estimated and mapped into an equivalent temperature increment, which serves as the first input component of the thermal hysteresis prediction model.
[0055] The rate of change of the impedance value of the microperspiration on the driver's contact surface is trend-identified. When a continuous decrease in impedance value is detected, the cumulative index of future skin moisture is calculated based on the rate of change of the impedance value of the microperspiration on the driver's contact surface, and mapped to the future equivalent metabolic heat production power. The future equivalent metabolic heat production power within the future time window is integrated to obtain the mean value of the future equivalent metabolic heat production power, which is used as the second input component of the thermal hysteresis prediction model.
[0056] The basic weights are obtained based on the micro-weather type identifier of the road section ahead, and the basic weights are corrected by using the difference between the predicted future outside temperature and the set temperature inside the vehicle, so as to generate dynamic boundary correction coefficients within the future time window.
[0057] The current measured comfort index, the first input component, the second input component, and the dynamic boundary correction coefficient are weighted and fused to generate a future perceived comfort index within a preset time window.
[0058] In this embodiment of the application, specifically, the solar radiation heat flux outside the vehicle is collected in real time. And calculate the rate of change of solar radiation heat flux. ;in, Indicates time, Indicates a time interval. Driver's skin perspiration impedance value. And calculate the rate of change of impedance. , Ambient temperature outside the vehicle Car interior temperature setting And the micro-weather type indicator for the road section ahead. The micro-weather type indicator for the road section ahead includes sunny, cloudy, overcast, tunnel, shaded, etc. The step of estimating the cumulative heat absorption of the interior surface within a future time window based on the rate of change of solar radiation heat flux outside the vehicle, combined with the vehicle speed and the thermal time constant of the interior materials, and mapping it to an equivalent temperature increment includes:
[0059] Estimate the cumulative heat absorption of the interior surface within a future time window using the following formula. :
[0060] ;
[0061] in, The heat absorption coefficient of the interior materials; The effective area of the vehicle interior exposed to solar radiation. For prediction time windows; It is the integral variable, representing the time from the current time t to... At any time between, Indicates future time The solar radiation heat flux outside the vehicle at any given time; It is the hysteresis decay factor. To follow vehicle speed The thermal time constant of varying interior materials; Where C represents the heat capacity of the interior material; To follow vehicle speed The varying convective heat transfer coefficient. The calculation method for the effective area of the vehicle interior receiving solar radiation is as follows: The effective lighting area A1 of the vehicle's windshield and the effective lighting area A2 of the driver's side window are pre-calibrated. Based on the time and location information obtained from the vehicle navigation / vehicle networking module, or through solar radiation sensors and attitude sensors, the solar altitude angle β and solar azimuth angle θ are determined. Combined with the vehicle's driving direction, the projection coefficient η of direct sunlight inside the vehicle (range 0-1) is calculated; the effective area A of the vehicle interior receiving solar radiation is obtained by the following formula: .
[0062] The cumulative heat absorption of the interior surface within the future time window is mapped to an equivalent temperature increment using the following formula. :
[0063]
[0064] Where C represents the heat capacity of the interior materials.
[0065] To ensure dimensional consistency, it is normalized: ;in, To preset the maximum equivalent temperature rise threshold, after normalization The value is in the range [0,1].
[0066] The cumulative skin moisture index for: ;in, The reference impedance is given when the skin is dry, and k represents the sampling number. This represents the impedance value of the microperspiration on the skin at the contact surface measured during the k-th sampling, and N represents the total number of samples.
[0067] It should be understood that, since the impedance of skin microperspiration decreases with increasing perspiration, the reference impedance under dry skin conditions should be used. Subtract the impedance measured at the kth sampling time This allows the decrease in impedance to be directly mapped to the degree of skin moisture. The higher the value, the more the skin sweats and the higher the skin moisture level. The cumulative skin moisture index is then mapped to equivalent metabolic heat production power. As shown in the formula below:
[0068] ;
[0069] in, This is the body's basal metabolic rate. This is the impedance-heat generation mapping coefficient.
[0070] Normalize the metabolic heat production power: in, This represents the normalized metabolic heat production power. The value is in the range [0,1]. This is the preset maximum equivalent metabolic heat production power.
[0071] The basic weights are obtained based on the micro-weather type identifier of the road section ahead, and the basic weights are corrected using the difference between the outside ambient temperature and the set temperature inside the vehicle to generate dynamic boundary correction coefficients. ;in, This is the temperature difference correction factor. , Based on the weights, The outside temperature of the vehicle. Set the temperature inside the car. This is the difference between the outside temperature and the set temperature inside the vehicle.
[0072] The current measured comfort index, the first input component, the second input component, and the dynamic boundary correction coefficient are weighted and fused to generate a future perceived comfort index within a preset time window. Specifically, this is done according to the following formula: ;
[0073] in, , , , For the weighting coefficients, satisfying It is determined through actual vehicle calibration. This represents the current measured comfort index.
[0074] This application combines the rate of change of solar radiation heat flux outside the vehicle with the vehicle's speed and the thermal time constant of the interior materials. This allows for accurate estimation of the accumulated heat absorption on the interior surface and its conversion into an equivalent temperature increment. It fully considers the thermal hysteresis characteristics of the in-vehicle thermal environment, improving the accuracy of thermal environment prediction. By identifying and continuously monitoring the rate of change of the driver's skin's microperspiration impedance, it reflects the driver's sweating trend and metabolic heat changes in real time, quantifying physiological signals into equivalent metabolic heat production power. This upgrades comfort prediction from a simple judgment of environmental parameters to a precise human-vehicle-environment coupling prediction, more closely reflecting the actual driving experience. Based on the micro-meteorological type markings of the road ahead and the dynamic correction boundary conditions of the temperature difference between the inside and outside of the vehicle, a dynamic boundary correction coefficient is introduced. This allows for the early perception of the impact of meteorological changes along the driving path on the in-vehicle thermal environment, achieving road-level, forward-looking thermal environment prediction and avoiding the lag and energy waste caused by traditional air conditioning that only adjusts based on the current state. By weighting and fusing environmental heat components, human physiological components, dynamic boundary coefficients, and the current comfort index, a multi-dimensional and robust thermal hysteresis prediction model is formed. This model provides a reliable and accurate decision-making basis for subsequent air conditioning pre-adjustment and graded energy-saving control. Under the premise of ensuring driving and riding comfort, it significantly reduces unnecessary energy consumption output of the air conditioning system and achieves synergistic optimization of comfort and energy saving.
[0075] It should be understood that the current measured comfort index method and the calculation method for the perceived comfort index within a future preset time window are logically the same, but the current measured comfort index uses current data rather than data from the past or future. This will not be elaborated further in the embodiments of this application.
[0076] In one embodiment, the step of implementing an energy-saving tiered intervention strategy for the automotive air conditioning system includes:
[0077] The following intervention steps should be implemented step by step and evaluated in real time:
[0078] Level 1 intervention: Execute airflow organization adjustment, control the electric air outlet blades to form a dynamic air curtain that blocks the direct sunlight path, and keep the blower speed constant; if the human comfort index is lower than the preset threshold after the first preset time of the Level 1 intervention, the subsequent intervention is terminated; otherwise, Level 2 intervention is executed.
[0079] Level 2 intervention: If the outside temperature is lower than the current average inside temperature, the air volume and fresh air are adjusted, the fresh air damper opening is increased and the blower speed is increased; if the body comfort index is lower than the preset threshold after the second preset time of the Level 2 intervention, the subsequent intervention is terminated; otherwise, Level 3 intervention is performed.
[0080] Level 3 intervention: Execute cooling power adjustment and increase compressor operating frequency.
[0081] In this embodiment, a tiered energy-saving control logic is constructed for radiation-dominated heat loads: "passive shading first, natural cooling source second, and mechanical refrigeration as a backup." First, a dynamic air curtain physically blocks the direct path of solar radiation, reducing the maximum heat load input at the source with extremely low energy consumption. Second, fresh air is introduced only when there is a natural cooling source outside the vehicle (the outside temperature is lower than the inside temperature), enhancing convection heat transfer and avoiding the ineffective work of introducing additional heat loads in high-temperature environments. Finally, the high-energy-consuming compressor is activated only when the two low-energy-consumption methods fail to bring the predicted human comfort level back to the threshold range. This step-by-step upgrade strategy based on predictive feedback maximizes the use of physical shading and natural environmental cooling sources, reduces the high-frequency operation time and start-stop frequency of the compressor, and minimizes the energy consumption of the entire vehicle air conditioning system while ensuring in-vehicle comfort.
[0082] This application embodiment also provides an automotive air conditioning pre-adjustment energy-saving control system based on in-vehicle environment prediction, the system comprising:
[0083] Data acquisition module 1 is used to collect multi-source heterogeneous data in real time, including the rate of change of solar radiation heat flux outside the vehicle, the rate of change of the resistance value of microperspiration on the driver's skin, the ambient temperature outside the vehicle, and the micro-meteorological type of the road section ahead.
[0084] The body comfort index prediction module 2 is used to construct a thermal hysteresis prediction model based on the multi-source heterogeneous data, to deduce the in-vehicle thermal environment state within a future preset time window, and to generate the body comfort index within the future preset time window.
[0085] The judgment module 3 is used to compare the body comfort index within a future preset time window with a preset threshold. If the body comfort index within the future preset time window is greater than the preset threshold and the current measured comfort index is lower than the pre-adjustment trigger line, then it is determined to enter the pre-adjustment mode.
[0086] Execution module 4 is used to implement an energy-saving graded intervention strategy for the automotive air conditioning system in the pre-adjustment mode.
[0087] In one embodiment, the step of constructing a thermal hysteresis prediction model based on the multi-source heterogeneous data, extrapolating the in-vehicle thermal environment state within a future preset time window, and generating a perceived comfort index within the future preset time window includes:
[0088] Based on the rate of change of solar radiation heat flux outside the vehicle, combined with the vehicle speed and the thermal time constant of the interior materials, the cumulative heat absorption of the interior surface within the future time window is estimated and mapped into an equivalent temperature increment, which serves as the first input component of the thermal hysteresis prediction model.
[0089] The rate of change of the impedance value of the microperspiration on the driver's contact surface is trend-identified. When a continuous decrease in impedance value is detected, the cumulative index of future skin moisture is calculated based on the rate of change of the impedance value of the microperspiration on the driver's contact surface, and mapped to the future equivalent metabolic heat production power. The future equivalent metabolic heat production power within the future time window is integrated to obtain the mean value of the future equivalent metabolic heat production power, which is used as the second input component of the thermal hysteresis prediction model.
[0090] The basic weights are obtained based on the micro-weather type identifier of the road section ahead, and the basic weights are corrected by using the difference between the predicted future outside temperature and the set temperature inside the vehicle, so as to generate dynamic boundary correction coefficients within the future time window.
[0091] The current measured comfort index, the first input component, the second input component, and the dynamic boundary correction coefficient are weighted and fused to generate a future perceived comfort index within a preset time window.
[0092] In one embodiment, the implementation of an energy-saving tiered intervention strategy for the automotive air conditioning system includes:
[0093] The following intervention steps should be implemented step by step and evaluated in real time:
[0094] Level 1 intervention: Execute airflow organization adjustment, control the electric air outlet blades to form a dynamic air curtain that blocks the direct sunlight path, and keep the blower speed constant; if the human comfort index is lower than the preset threshold after the first preset time of the Level 1 intervention, the subsequent intervention is terminated; otherwise, Level 2 intervention is executed.
[0095] Level 2 intervention: If the outside temperature is lower than the current average inside temperature, the air volume and fresh air are adjusted, the fresh air damper opening is increased and the blower speed is increased; if the body comfort index is lower than the preset threshold after the second preset time of the Level 2 intervention, the subsequent intervention is terminated; otherwise, Level 3 intervention is performed.
[0096] Level 3 intervention: Execute cooling power adjustment and increase compressor operating frequency.
[0097] In one embodiment, estimating the cumulative heat absorption of the interior surface within a future time window based on the rate of change of solar radiation heat flux outside the vehicle, combined with the vehicle's driving speed and the thermal time constant of the interior materials, and mapping it to an equivalent temperature increment includes:
[0098] Estimate the cumulative heat absorption of the interior surface within a future time window using the following formula. :
[0099] ;
[0100] in, The heat absorption coefficient of the interior materials; The effective area of the vehicle interior exposed to solar radiation. For prediction time windows; It is the integral variable, representing the time from the current time t to... At any time between, Indicates future time The solar radiation heat flux outside the vehicle at any given time; It is the hysteresis decay factor. To follow vehicle speed The thermal time constant of varying interior materials;
[0101] The cumulative heat absorption of the interior surface within the future time window is mapped to an equivalent temperature increment using the following formula. :
[0102]
[0103] Where C represents the heat capacity of the interior materials.
[0104] In one embodiment, calculating the cumulative skin moisture index and mapping it to equivalent metabolic heat production power includes:
[0105] The cumulative skin moisture index is calculated using the following formula. :
[0106] ;
[0107] in, The reference impedance is given when the skin is dry, and k represents the sampling number. This represents the impedance value of the microperspiration on the skin at the contact surface measured during the k-th sampling, and N represents the total number of samples.
[0108] Mapping the skin moisture accumulation index to equivalent metabolic heat production power As shown in the formula below:
[0109] ;
[0110] in, This is the body's basal metabolic rate. This is the impedance-heat generation mapping coefficient.
[0111] It should be noted that the technical solutions in the embodiments of this specification, if involving the processing of personal information, will all be processed under the premise of having a legal basis (such as obtaining the consent of the personal information subject), and will only be processed within the scope stipulated or agreed. The collection, storage, use, processing, transmission, provision, and presentation of related information all comply with the provisions of relevant laws and regulations, do not infringe on the privacy of others, and do not violate public order and good morals.
[0112] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in this application and in the embodiments can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual-speed SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
[0113] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, apparatus, article, or method. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, apparatus, article, or method that includes that element.
[0114] The above description is only a preferred embodiment of this application and does not limit the patent scope of this application. Any equivalent structural or procedural changes made based on the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.
Claims
1. A method for pre-regulating and energy-saving control of automotive air conditioning based on in-vehicle environment prediction, characterized in that, The method includes: Real-time collection of multi-source heterogeneous data including the rate of change of solar radiation heat flux outside the vehicle, the rate of change of the resistance value of micro-perspiration on the driver's skin, the ambient temperature outside the vehicle, and the micro-meteorological type of the road section ahead. Based on the multi-source heterogeneous data, a thermal hysteresis prediction model is constructed to predict the in-vehicle thermal environment state within a future preset time window and generate the body comfort index within the future preset time window. The system compares the perceived comfort index within a future preset time window with a preset threshold. If the perceived comfort index within the future preset time window is greater than the preset threshold and the current measured comfort index is lower than the pre-adjustment trigger line, then it is determined to enter the pre-adjustment mode. In the pre-adjustment mode, an energy-saving graded intervention strategy is implemented for the automotive air conditioning system.
2. The automotive air conditioning pre-adjustment energy-saving control method based on in-vehicle environment prediction according to claim 1, characterized in that, The steps of constructing a thermal hysteresis prediction model based on the multi-source heterogeneous data, extrapolating the in-vehicle thermal environment state within a future preset time window, and generating a perceived comfort index within the future preset time window include: Based on the rate of change of solar radiation heat flux outside the vehicle, combined with the vehicle speed and the thermal time constant of the interior materials, the cumulative heat absorption of the interior surface within the future time window is estimated and mapped into an equivalent temperature increment, which serves as the first input component of the thermal hysteresis prediction model. The rate of change of the impedance value of the microperspiration on the driver's contact surface is trend-identified. When a continuous decrease in impedance value is detected, the cumulative index of future skin moisture is calculated based on the rate of change of the impedance value of the microperspiration on the driver's contact surface, and it is mapped to the future equivalent metabolic heat production power. The future equivalent metabolic heat production power within the future time window is integrated to obtain the mean value of the future equivalent metabolic heat production power, which is used as the second input component of the thermal hysteresis prediction model. The basic weights are obtained based on the micro-weather type identifier of the road section ahead, and the basic weights are corrected by using the difference between the predicted future outside temperature and the set temperature inside the vehicle, so as to generate dynamic boundary correction coefficients within the future time window. The current measured comfort index, the first input component, the second input component, and the dynamic boundary correction coefficient are weighted and fused to generate a future perceived comfort index within a preset time window.
3. The automotive air conditioning pre-adjustment energy-saving control method based on in-vehicle environment prediction according to claim 1, characterized in that, The steps for implementing an energy-saving tiered intervention strategy for automotive air conditioning systems include: The following intervention steps should be implemented step by step and evaluated in real time: Level 1 intervention: Execute airflow organization adjustment, control the electric air outlet blades to form a dynamic air curtain that blocks the direct sunlight path, and keep the blower speed constant; if the human comfort index is lower than the preset threshold after the first preset time of the Level 1 intervention, the subsequent intervention is terminated; otherwise, Level 2 intervention is executed. Level 2 intervention: If the outside temperature is lower than the current average inside temperature, the air volume and fresh air are adjusted, the fresh air damper opening is increased and the blower speed is increased; if the body comfort index is lower than the preset threshold after the second preset time of the Level 2 intervention, the subsequent intervention is terminated; otherwise, Level 3 intervention is performed. Level 3 intervention: Execute cooling power adjustment and increase compressor operating frequency.
4. A vehicle air conditioning pre-adjustment energy-saving control system based on in-vehicle environment prediction, characterized in that, The system includes: The data acquisition module is used to collect multi-source heterogeneous data in real time, including the rate of change of solar radiation heat flux outside the vehicle, the rate of change of the impedance value of microperspiration on the driver's skin, the ambient temperature outside the vehicle, and the micro-meteorological type of the road section ahead. The body comfort index prediction module is used to construct a thermal hysteresis prediction model based on the multi-source heterogeneous data, to deduce the in-vehicle thermal environment state within a future preset time window, and to generate the body comfort index within the future preset time window. The judgment module is used to compare the perceived comfort index within a future preset time window with a preset threshold. If the perceived comfort index within the future preset time window is greater than the preset threshold and the current measured comfort index is lower than the pre-adjustment trigger line, then it is determined to enter the pre-adjustment mode. An execution module is used to implement an energy-saving graded intervention strategy for the automotive air conditioning system in the pre-adjustment mode.
5. The automotive air conditioning pre-adjustment energy-saving control system for predicting the in-vehicle environment according to claim 4, characterized in that, The step of constructing a thermal hysteresis prediction model based on the multi-source heterogeneous data, extrapolating the in-vehicle thermal environment state within a future preset time window, and generating a perceived comfort index within the future preset time window includes: Based on the rate of change of solar radiation heat flux outside the vehicle, combined with the vehicle speed and the thermal time constant of the interior materials, the cumulative heat absorption of the interior surface within the future time window is estimated and mapped into an equivalent temperature increment, which serves as the first input component of the thermal hysteresis prediction model. The rate of change of the impedance value of the microperspiration on the driver's contact surface is trend-identified. When a continuous decrease in impedance value is detected, the cumulative index of future skin moisture is calculated based on the rate of change of the impedance value of the microperspiration on the driver's contact surface, and mapped to the future equivalent metabolic heat production power. The future equivalent metabolic heat production power within the future time window is integrated to obtain the mean value of the future equivalent metabolic heat production power, which is used as the second input component of the thermal hysteresis prediction model. The basic weights are obtained based on the micro-weather type identifier of the road section ahead, and the basic weights are corrected by using the difference between the predicted future outside temperature and the set temperature inside the vehicle, so as to generate dynamic boundary correction coefficients within the future time window. The current measured comfort index, the first input component, the second input component, and the dynamic boundary correction coefficient are weighted and fused to generate a future perceived comfort index within a preset time window.
6. The automotive air conditioning pre-adjustment energy-saving control system based on in-vehicle environment prediction according to claim 4, characterized in that, The energy-saving tiered intervention strategy for automotive air conditioning systems includes: The following intervention steps should be implemented step by step and evaluated in real time: Level 1 intervention: Execute airflow organization adjustment, control the electric air outlet blades to form a dynamic air curtain that blocks the direct sunlight path, and keep the blower speed constant; if the human comfort index is lower than the preset threshold after the first preset time of the Level 1 intervention, the subsequent intervention is terminated; otherwise, Level 2 intervention is executed. Level 2 intervention: If the outside temperature is lower than the current average inside temperature, the air volume and fresh air are adjusted, the fresh air damper opening is increased and the blower speed is increased; if the body comfort index is lower than the preset threshold after the second preset time of the Level 2 intervention, the subsequent intervention is terminated; otherwise, Level 3 intervention is performed. Level 3 intervention: Execute cooling power adjustment and increase compressor operating frequency.