New energy vehicle thermal management control method and system adaptive to altitude

Abstract

The invention discloses a new energy automobile thermal management control method and system capable of self-adapting to the altitude. Environment, battery, electric drive and air conditioner parameters are acquired through a multi-dimensional parameter acquisition module, the altitude and road condition change of a driving route is predicted in combination with comprehensive road condition data, the heat production load of the battery is pre-judged, and a predicted working condition is generated. A PID + fuzzy control fusion algorithm is adopted, thermal management compensation parameters are calculated according to the altitude, wind speed correction is combined, and PID parameters are dynamically adjusted to adjust target cold and hot power of a battery, an electric drive and an air conditioning system. Meanwhile, real-time fault diagnosis and mode setting are carried out based on a preset fault strategy. According to the method, by constructing an altitude-air pressure-thermal management parameter dynamic mapping model, multi-system cooperative adaptive control is achieved, the cruising ability, the battery life and the comfort of the new energy vehicle in a full-altitude area are effectively improved, and the method has good practicability and reliability.

Description

Technical Field

[0001] This invention relates to the field of thermal management technology for new energy vehicles, and more specifically, to a thermal management control method and system for new energy vehicles that adapts to altitude. Background Technology

[0002] The performance of the thermal management system of new energy vehicles (including battery thermal management, electric drive system heat dissipation, and air conditioning / heat pump heating) directly determines the vehicle's driving range, battery life, and the reliability of the electric drive system. Altitude has a more significant impact on the thermal management of new energy vehicles than on traditional gasoline vehicles. This is mainly due to two aspects: First, high altitude and low air pressure exacerbate heat dissipation problems: for every 1000 meters increase in altitude, atmospheric pressure decreases by 12-15 kPa, and air density decreases by about 10%, leading to a 15%-20% decrease in heat exchange capacity of the air conditioning condenser and electric drive system radiator, a 5-8°C decrease in refrigerant condensation temperature, and a reduction in air conditioning cooling capacity. Second, the battery's natural heat dissipation efficiency decreases, especially during high-altitude, high-load driving (such as climbing hills), where the battery's heat generation rate increases by more than 30%, increasing the risk of temperature runaway. Additionally, in low-pressure environments, the heat exchanger of the electric drive system (motor + electronic control) becomes less efficient, easily triggering overheat protection and limiting power output.

[0003] Traditional new energy vehicle thermal management systems mostly use fixed parameter control (such as preset coolant pump speed, radiator fan power, compressor speed, electronic expansion valve opening, etc. through thermal management calibration). They rely solely on environmental variables such as ambient temperature, water temperature, and sunlight to adjust control parameters, without taking altitude as a core control dimension. In high-altitude environments, "insufficient heat dissipation" or "energy waste" are likely to occur.

[0004] Some existing thermal management control optimization solutions for high altitudes simply increase water pump speed and fan power without dynamically adjusting to changes in air pressure and wind speed at different altitudes. This results in limited improvement in heat dissipation efficiency and excessive energy consumption in high-altitude, low-wind-speed scenarios. Furthermore, low air pressure at high altitudes can cause a more than 40% reduction in the heating efficiency of heat pump air conditioners. Existing systems do not optimize heat pump operation for altitude, leading to poor in-vehicle comfort and increased range loss during winter travel at high altitudes. Therefore, there is an urgent need for a new energy vehicle thermal management control system that adapts to altitude. Summary of the Invention

[0005] This invention overcomes the shortcomings of existing technologies and proposes an adaptive altitude-based thermal management control method and system for new energy vehicles. It involves a thermal management control strategy for new energy vehicles based on dynamic altitude adjustment, and is particularly suitable for the coordinated control of battery thermal management system, electric drive cooling system and vehicle air conditioning system. It is especially applicable to complex driving scenarios where high and low altitudes frequently switch (such as commuting in plateau mountainous areas and long-distance travel across altitudes).

[0006] The first aspect of this invention provides a thermal management control method for new energy vehicles that adapts to altitude, comprising: S1: Collect multi-dimensional environmental parameters, battery temperature parameters, electric drive temperature parameters, air conditioning management parameters, and comprehensive road condition data through the multi-dimensional thermal management parameter acquisition module in the target vehicle; S2: By comprehensively analyzing road condition data, analyze the altitude change and road condition change trend of the future preset driving distance, and predict the battery heat load to obtain the predicted operating conditions; S3: It adopts a "PID + fuzzy control" fusion algorithm to calculate the compensation parameters of the battery, electric drive and air conditioning based on the altitude, and correct the compensation parameters in combination with the wind speed. At the same time, it calculates the fuzzy logic range in combination with the predicted working conditions and dynamically adjusts the PID parameters. The target cooling and heating power parameters of the battery thermal management system, electric drive cooling system and air conditioning thermal management system are adjusted by PID. S4: Based on the preset fault strategy, the parameters collected by S1 are used to determine the fault threshold in real time, and the fault mode is set for the battery, electric drive and air conditioner.

[0007] In this scheme, the environmental parameters in S1 include altitude, atmospheric pressure, ambient temperature, and wind speed.

[0008] In this scheme, the battery temperature parameters in S1 include the average temperature of the battery pack, the highest temperature of the battery pack, the lowest temperature of the battery pack, the temperature difference between individual cells in the battery pack, the battery SOC, the battery charging and discharging power, the battery coolant inlet temperature, the battery coolant outlet temperature, the battery coolant flow rate, and the radiator fan speed.

[0009] In this scheme, the electric drive temperature parameters in S1 include motor winding temperature, electronic control module temperature, electric drive coolant flow rate, electric drive coolant inlet temperature, and electric drive coolant outlet temperature.

[0010] In this scheme, the air conditioning management parameters in S1 include condenser temperature, evaporator temperature, refrigerant pressure, and air conditioning duct temperature.

[0011] In this solution, S2 specifically refers to: Comprehensive road condition data includes the target vehicle's GPS location and map elevation data; Based on comprehensive road condition data, the altitude change trend and road condition trend of the target vehicle's future 5km driving route are determined, and the changes in battery heat load and the demand of the liquid cooling system are predicted. The analyzed trends and predictions are summarized to obtain the predicted operating conditions.

[0012] In this solution, S3 specifically refers to: Based on the target vehicle's current altitude and altitude range-benchmark parameter mapping table, compensation parameter analysis is performed. Linear interpolation is introduced to calculate the compensation parameters for the battery, electric drive, and air conditioning, and the compensation parameters are corrected in combination with wind speed. A fuzzy PID rule table is established based on the predicted operating conditions, and the PID parameters are dynamically adjusted through fuzzy logic intervals. The target cooling and heating power parameters of the battery thermal management system, electric drive cooling system, and air conditioning thermal management system are adjusted through PID.

[0013] In this solution, S4 includes: If the altitude data is abnormal, the altitude range is deduced by using atmospheric pressure P, and redundant judgment is made by linking the average battery temperature with the target temperature difference of the coolant. When the average battery temperature is >45℃ or the target temperature difference of the coolant is >10℃, it is judged as a liquid cooling failure warning, triggering the power reduction protection mode, reducing the battery charging and discharging power by 30%, and simultaneously starting the battery water pump and radiator fan to run at full load. If the battery coolant flow rate is detected to be <5L / min at low altitudes or <10L / min at high altitudes, the battery charging and discharging power will decrease by 50%. When the refrigerant pressure is abnormal in a high-altitude environment, the air conditioner will automatically switch to PTC heating mode and the battery will be set to cooling mode. Based on the above fault diagnosis, the warning information will be sent to the vehicle display terminal.

[0014] A second aspect of the present invention also provides an adaptive altitude thermal management control system for new energy vehicles, the system comprising: an environmental parameter acquisition unit responsible for acquiring and storing environmental parameters; Battery temperature acquisition unit: responsible for acquiring and storing battery temperature parameters; Electric drive temperature acquisition unit: responsible for acquiring and storing electric drive temperature parameters; Air conditioning system data acquisition unit: responsible for collecting and storing air conditioning management parameters; Predictive processing unit: responsible for real-time analysis of comprehensive traffic data and setting predicted traffic conditions; Intelligent decision control unit: responsible for comprehensively analyzing multi-dimensional thermal management parameters, and setting corresponding control and compensation parameters for the battery thermal management system, electric drive cooling system, and air conditioning thermal management system, and controlling the battery, electric drive, and air conditioning thermal management systems in real time; The adaptive altitude new energy vehicle thermal management control system also includes an adaptive altitude new energy vehicle thermal management control program, which implements the above steps S1-S4 when running in the system.

[0015] A third aspect of the present invention also provides a computer-readable storage medium comprising an adaptive altitude thermal management control program for new energy vehicles, wherein when the adaptive altitude thermal management control program is executed by a processor, it implements the steps of the adaptive altitude thermal management control method for new energy vehicles as described in any of the preceding claims.

[0016] The following technical effects can be achieved through this invention: Thermal management system with all-altitude environment self-adaptation: The thermal management system achieves adaptive control across the entire altitude range, with high control precision, avoiding insufficient air conditioning cooling performance in high-altitude environments, and also avoiding the risk of battery thermal runaway caused by insufficient battery liquid cooling; Energy consumption optimization of thermal management system: Compared with the traditional fixed parameter strategy, the energy consumption of thermal management system at high altitude (altitude > 3000 meters) is reduced, while the heat dissipation efficiency is improved; Improved reliability: The overheat protection trigger rate is reduced when climbing at high altitudes, ensuring stable power output; Wide compatibility: It is compatible with the thermal management system architecture of pure electric vehicles and plug-in / range-extended hybrid vehicles. It can be achieved by adding an altitude sensor and upgrading the software, without modifying the core thermal management hardware (such as radiators, thermal management integrated modules, compressors, etc.), and the modification cost is low. Attached Figure Description

[0017] Figure 1 The diagram illustrates the architecture of an adaptive altitude thermal management control system for new energy vehicles according to the present invention. Figure 2 The flowchart of the thermal management control software layer of the present invention is shown; Figure 3 A simplified schematic diagram of an adaptive altitude thermal management control system for new energy vehicles according to the present invention is shown. Detailed Implementation

[0018] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It is understood that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0019] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0020] Figure 1 The diagram shows the architecture of a new energy vehicle thermal management control system that adapts to altitude according to the present invention.

[0021] The first aspect of this invention provides a thermal management control method for new energy vehicles that adapts to altitude, comprising: S1: Collect multi-dimensional environmental parameters, battery temperature parameters, electric drive temperature parameters, air conditioning management parameters, and comprehensive road condition data through the multi-dimensional thermal management parameter acquisition module in the target vehicle; S2: By comprehensively analyzing road condition data, analyze the altitude change and road condition change trend of the future preset driving distance, and predict the battery heat load to obtain the predicted operating conditions; S3: It adopts a "PID + fuzzy control" fusion algorithm to calculate the compensation parameters of the battery, electric drive and air conditioning based on the altitude, and correct the compensation parameters in combination with the wind speed. At the same time, it calculates the fuzzy logic range in combination with the predicted working conditions and dynamically adjusts the PID parameters. The target cooling and heating power parameters of the battery thermal management system, electric drive cooling system and air conditioning thermal management system are adjusted by PID. S4: Based on the preset fault strategy, the parameters collected by S1 are used to determine the fault threshold in real time, and the fault mode is set for the battery, electric drive and air conditioner.

[0022] It is understood that the multi-dimensional thermal management parameter acquisition module is a single module, which includes an environmental parameter acquisition unit, a battery temperature acquisition unit, an electric drive temperature acquisition unit, and an air conditioning system acquisition unit. Figure 1 This is a schematic diagram of the thermal management control system architecture of the present invention, including a simplified schematic flow of the method of the present invention.

[0023] According to an embodiment of the present invention, in step S1, the environmental parameters include altitude, atmospheric pressure, ambient temperature, and wind speed.

[0024] It is understood that the environmental parameters are collected specifically as follows: altitude sensor (measurement range -1000 meters to 8000 meters, accuracy ±3 meters), atmospheric pressure sensor (30 kPa - 110 kPa, accuracy ±0.3 kPa), ambient temperature sensor (-40℃ - 85℃, accuracy ±0.5℃), and wind speed sensor (measurement range 0-30 m / s, accuracy ±0.5 m / s). The environmental parameter acquisition unit includes all of the above-mentioned environmental sensors.

[0025] According to an embodiment of the present invention, in step S1, the battery temperature parameters include the average temperature of the battery pack, the highest temperature of the battery pack, the lowest temperature of the battery pack, the temperature difference between individual cells in the battery pack, the battery SOC, the battery charging and discharging power, the battery coolant inlet temperature, the battery coolant outlet temperature, the battery coolant flow rate, and the radiator fan speed.

[0026] Understandably, the battery temperature parameters are expressed as follows: average battery pack temperature T_bat (accuracy ±0.5℃), maximum battery pack temperature T_Max, minimum battery pack temperature T_Min, individual battery pack temperature difference ΔT_bat, battery SOC (state of charge), battery charge / discharge power P_bat, battery coolant inlet temperature T_cool_in, battery coolant outlet temperature T_cool_out, battery coolant flow rate Q_cool (accuracy ±0.5L / min), and radiator fan speed N_rad.

[0027] According to an embodiment of the present invention, in step S1, the electric drive temperature parameters include the motor winding temperature, the electronic control module temperature, the electric drive coolant flow rate, the electric drive coolant inlet temperature, and the electric drive coolant outlet temperature.

[0028] It is understandable that the electric drive temperature parameters include: motor winding temperature T_motor (accuracy ±1℃), IGBT temperature of the electronic control module T_igbt (accuracy ±1℃), electric drive coolant flow rate Q_drive, electric drive coolant inlet temperature T_rad_d_in, and electric drive coolant outlet temperature T_rad_d_out.

[0029] According to an embodiment of the present invention, in step S1, the air conditioning management parameters include condenser temperature, evaporator temperature, refrigerant pressure, and air conditioning duct temperature.

[0030] It is understandable that the air conditioning management parameters are expressed as follows: condenser temperature T_heat_cond, evaporator temperature T_evap, refrigerant pressure P_ref (high pressure side / low pressure side), and air conditioning duct temperature T_air.

[0031] According to an embodiment of the present invention, step S2 specifically includes: Comprehensive road condition data includes the target vehicle's GPS location and map elevation data; Based on comprehensive road condition data, the altitude change trend and road condition trend of the target vehicle's future 5km driving route are determined, and the changes in battery heat load and the demand of the liquid cooling system are predicted. The analyzed trends and predictions are summarized to obtain the predicted operating conditions.

[0032] It is understood that the map elevation data includes data such as altitude and terrain. The predicted operating conditions include elevation change trends, road condition trends, changes in battery heat load, and the demand for the liquid cooling system. Here, S2 is specifically implemented through a prediction processing unit, which, based on the vehicle's GPS positioning and map elevation data, extracts the elevation change trend (climb rate R_h ≥ 50 m / km or descent rate ≤ -50 m / km) and road condition information (such as the percentage of uphill / downhill sections) for the next 5km driving route, and predicts the changes in the demand for the liquid cooling system due to the battery heat load (such as the increase in P_bat during uphill driving).

[0033] According to an embodiment of the present invention, step S3 specifically includes: Based on the target vehicle's current altitude and altitude range-benchmark parameter mapping table, compensation parameter analysis is performed. Linear interpolation is introduced to calculate the compensation parameters for the battery, electric drive, and air conditioning, and the compensation parameters are corrected in combination with wind speed. A fuzzy PID rule table is established based on the predicted operating conditions, and the PID parameters are dynamically adjusted through fuzzy logic intervals. The target cooling and heating power parameters of the battery thermal management system, electric drive cooling system, and air conditioning thermal management system are adjusted through PID.

[0034] The altitude range-benchmark parameter mapping table is as follows:

[0035] It should be noted that S3 employs a fusion algorithm of "PID + fuzzy control". Compensation parameters are calculated based on altitude, and wind speed is used for secondary correction. Simultaneously, fuzzy logic intervals are calculated based on predicted operating conditions to dynamically adjust PID parameters. This PID control adjusts the target cooling and heating power parameters of the battery thermal management system, electric drive cooling system, and air conditioning thermal management system, specifically including: Battery thermal management system: The average battery pack temperature T_bat and the target temperature difference of the coolant ΔT_cool are used as dual targets for dynamic adjustment control. When the battery is at high altitude and the charging and discharging power P_bat is greater than 80% of the rated power (such as fast charging or climbing), the coolant pump speed is increased to 90% 5 minutes in advance to predictively improve the liquid cooling capacity and avoid a sudden rise in battery temperature.

[0036] Electric drive cooling system: With T_motor≤85℃ and T_igbt≤105℃ as the target (parameters can be calibrated and adjusted), when T_motor>80℃, the electric drive fan speed is increased and the coolant pump flow is adjusted through fuzzy PID control; under high altitude climbing conditions, the rising trend of T_motor is predicted and the cooling power is increased by 20% 1 minute in advance.

[0037] This invention also includes a predictive adjustment process: When GPS information predicts that you will enter a high-altitude uphill section within the next 3km, perform the following steps 2 minutes in advance: Battery liquid cooling system: coolant pump speed increased to 90%, radiator fan power increased to 90%; Electric drive cooling system: Fans and coolant pumps enter high-load mode in advance; Air conditioning thermal management system: If cooling is turned on, the compressor speed is increased to 80% in advance to prepare for liquid cooling and heat exchange.

[0038] Meanwhile, in the thermal management system of the present invention, the execution unit includes: radiator fan, electronic coolant pump, electronically adjustable multi-way water valve, electric compressor, high-pressure PTC, electronic expansion valve, air conditioning blower and damper motor, etc. Core actuator parameter requirements: electronic coolant pump (maximum flow rate 20L / min, adjustment accuracy ±100rpm (or flow rate ±0.5L / min)), brushless radiator fan (maximum speed 4500rpm, adjustment accuracy ±100rpm); PTC power 6kW, adjustment accuracy ±500W; compressor power 4kW, adjustment accuracy ±50rpm; the control actuator is controlled by static PID parameters, and the PID parameters need to be calibrated by bench testing.

[0039] According to an embodiment of the present invention, step S4 includes: If the altitude data is abnormal, the altitude range is deduced by using atmospheric pressure P, and redundant judgment is made by linking the average battery temperature with the target temperature difference of the coolant. When the average battery temperature is >45℃ or the target temperature difference of the coolant is >10℃, it is judged as a liquid cooling failure warning, triggering the power reduction protection mode, reducing the battery charging and discharging power by 30%, and simultaneously starting the battery water pump and radiator fan to run at full load. If the battery coolant flow rate is detected to be <5L / min at low altitudes or <10L / min at high altitudes, the battery charging and discharging power will decrease by 50%. When the refrigerant pressure is abnormal in a high-altitude environment, the air conditioner will automatically switch to PTC heating mode and the battery will be set to cooling mode. Based on the above fault diagnosis, the warning information will be sent to the vehicle display terminal.

[0040] In cases where altitude data is abnormal, it may be due to a malfunction of the altitude sensor. In this case, the altitude range can be deduced by using atmospheric pressure P (e.g., P=60kPa corresponds to H≈3500 meters). At the same time, the redundancy of battery T_bat and coolant ΔT_cool can be checked (ΔT_cool tends to increase at high altitudes). For the battery thermal management system, when T_bat > 45℃ or ΔT_cool > 10℃ (liquid cooling failure warning), the power reduction protection is triggered (P_bat is reduced by 30%), and the battery water pump and radiator fan are started to run at full load, and the driver is notified through the vehicle display screen. The present invention also includes coolant pump failure protection. If the coolant flow rate is detected to be <5L / min (low altitude) or <10L / min (high altitude), the battery power is immediately reduced (P_bat is reduced by 50%) to avoid battery overheating in the absence of liquid cooling. For heat pump systems, when the heat pump pressure (refrigerant pressure) is abnormal (high pressure side > 3.0MPa) in high-altitude environments, the air conditioner will automatically switch to PTC heating mode and set the battery cooling mode to prioritize the heat exchange needs of the battery liquid cooling system.

[0041] In a preferred embodiment of the present invention, the specific thermal management control is implemented as follows: System Initialization: After the vehicle is powered on, the thermal management control system performs self-diagnosis of sensor faults, actuator faults, communication faults, and other system faults, and classifies the detected faults into levels. When the system detects an unrecoverable fault that affects the basic functions of the vehicle's thermal management, it should immediately stop system operation, report fault information to the driver, and record fault codes. This corresponds to step S4, and fault detection can be performed at any time.

[0042] Real-time acquisition of sensor and system parameters: Environmental parameters (ambient temperature T_env, altitude, atmospheric pressure, wind speed), battery pack temperature parameters (average battery pack temperature T_bat, maximum battery pack temperature T_Max, minimum battery pack temperature T_Min, individual battery pack temperature difference ΔT_bat, battery SOC, battery charging and discharging power P_bat, battery coolant inlet temperature T_cool_in, battery coolant outlet temperature T_cool_out, battery coolant flow rate Q_cool, radiator fan speed N_rad), electric drive temperature parameters (motor winding temperature T_motor, IGBT temperature T_igbt, electric drive coolant flow rate Q_drive, electric drive coolant inlet temperature T_rad_d_in, electric drive coolant outlet temperature T_rad_d_out), and air conditioning system temperature parameters (condenser temperature T_heat_cond, evaporator temperature T_evap, refrigerant pressure P_ref (high pressure side / low pressure side), air conditioning duct temperature T_air, etc.) are acquired at a frequency of 10Hz; GPS altitude trend is updated at 1Hz.

[0043] Altitude range determination and reference retrieval: Determine the altitude range based on altitude and atmospheric pressure, and retrieve the corresponding reference parameters for battery thermal management, electric drive cooling, and air conditioning systems.

[0044] Thermal management basic power requirement calculation: Battery thermal management system: Calculates the battery thermal management system mode (cooling / heating / temperature equalization) based on the target water temperature of the battery and the current temperature parameters of the battery pack, and also calculates the cooling / heating power requirements and coolant flow requirements; Electric drive cooling system: The cooling power requirement and coolant flow rate requirement are calculated based on the target temperature of the electric drive cooling circuit, the target temperature of the motor, the target temperature of the IGBT, and the current temperature parameters of the electric drive system. Air conditioning thermal management system: Calculates the system mode (cooling / heating / ventilation / defrosting) and target air outlet temperature based on parameters such as the air conditioner's set temperature, air volume, and blowing mode, and also calculates the cooling / heating power requirements of the air conditioning system.

[0045] PID dynamic correction: Based on the real-time updated altitude, linear interpolation is used to calculate the compensation adjustment parameters within the altitude range, and the compensation parameters are further corrected by taking into account the wind speed. A fuzzy PID rule table is established based on the predicted driving conditions, and the dynamic PID parameters are calculated by looking up the table. The thermal management requirements calculated above are dynamically corrected by PID adjustment (including the target cooling and heating power parameters of the battery thermal management system, electric drive cooling system, and air conditioning thermal management system).

[0046] If a high-altitude climb is anticipated, the thermal management system should be activated in advance for pre-emptive adjustments (such as increasing pump speed, fan power, and cooling capacity). Collaborative control: The overall target cooling power is calculated by comprehensively considering the cooling needs of the battery and the air conditioning, and the priority of arbitration is determined according to the different power needs of the battery and the air conditioning. The cooling capacity allocation needs of the refrigerant system are also calculated. The overall target heating power is calculated by comprehensively considering the heating needs of the battery and the air conditioning, and the power allocation of the PTC is combined with the altitude reference to convert to heat pump mode. The flow requirements of the water pumps are allocated by comprehensively considering the cooling flow requirements of the battery and the cooling flow requirements of the electric drive.

[0047] Execution control and feedback adjustment: The system adjusts the actuator's action through PID control. After the actuator moves, it provides real-time feedback on changes in battery temperature (T_bat), coolant temperature (ΔT_cool), evaporator temperature (T_evap), etc., and adjusts the control command according to the deviation to form a closed-loop control. Fault degradation allowance and protection strategy: Determine whether to stop system operation or degrade operation based on the preset fault level handling logic.

[0048] According to an embodiment of the present invention, it further includes: Within one driving monitoring cycle of the target vehicle, multiple data collection time points are set. For each time point, the rate of change of altitude and ambient temperature, P1 and P2, are calculated. If the change is greater than the preset standard, the time point is marked to obtain the control time point. Then, P1 and P2 are weighted and averaged to obtain the environmental change value. The coolant temperature difference between the battery thermal management system and the electric drive cooling system at the corresponding control time point is obtained, and a first temperature difference sequence and a second temperature difference sequence are generated based on the time dimension. An environmental change sequence is generated based on the environmental change values ​​at each control time point; Based on the grey relational analysis method, the correlation degree G1 between the environmental change sequence and the first temperature difference sequence is calculated, and the correlation degree G2 between the environmental change sequence and the second temperature difference sequence is calculated. The effectiveness and sustainability of thermal management for batteries and electric drives are evaluated by assessing the size of G1 and G2. During the driving monitoring cycle, the environmental and coolant temperature difference data corresponding to non-control time points are serialized and analyzed to calculate the corresponding environmental-temperature difference correlation degree, and obtain Gx and Gy; Using Gx and Gy as benchmarks, we analyze the changes in the correlation between G1 and G2. Here, the preset standards can be set to an altitude range of 30 meters and a temperature range of 3°C. If both the altitude and temperature changes exceed the preset standards, time points can be marked and change rates calculated. The weighted average is determined based on the actual predicted operating conditions. If the altitude change is significant, the altitude change is used as the core factor, with a larger weight assigned for analysis. Gx and Gy correspond to the correlation between the environment and the battery and electric drive dimensions at non-control time points. If G1 is greater than Gx and G2 is greater than Gy, it indicates a better thermal management effect, and the magnitude of the numerical difference reflects the sustainability and reliability of the corresponding thermal management decisions within the monitoring period. Change rates P1 and P2 can be calculated based on data from the current time point and the previous time point.

[0049] The temperature difference sequence includes a first temperature difference sequence, corresponding to battery thermal management, specifically the difference between the coolant inlet temperature T_cool_in and the battery coolant outlet temperature T_cool_out; and a second temperature difference sequence, corresponding to electric drive heat dissipation, specifically the difference between the electric drive coolant inlet temperature T_rad_d_in and the electric drive coolant outlet temperature T_rad_d_out. This invention uses these two temperature differences to reflect the correlation between environmental changes and regulatory changes after the thermal management system intervenes. If the correlation between environmental changes and the corresponding temperature difference sequence is high during regulation, it indicates a better thermal management regulation decision. Furthermore, the correlation degree corresponding to periods of non-preset environmental changes (i.e., periods when the thermal management system intervenes less frequently) is introduced as a benchmark reference. Analyzing the changes in the correlation degree allows for accurate evaluation of the effectiveness of the thermal management system's decision-making and control. It also enables further screening of abnormal periods for secondary analysis and regulation of control parameters, improving safety. Compared to the traditional thermal management system evaluation process that relies on a single dimension (such as real-time battery temperature changes or electric drive temperature changes), this invention can analyze and evaluate the relevance of decisions and the sustainability of thermal management effects from multiple dimensions of parameter matching, more accurately assess the efficiency and effectiveness of adaptive altitude thermal management, and simultaneously achieve anomaly control judgment in multiple time periods.

[0050] In the correlation coefficient test, a value greater than 0.3 (or greater than the baseline correlation coefficient) indicates a certain degree of correlation, suggesting that thermal management control has a positive effect. For driving monitoring cycles with significant environmental changes, the baseline correlation coefficient can be used for analysis and judgment to reduce errors in thermal management assessment.

[0051] Figure 2 A flowchart of the thermal management control software layer of the present invention is shown. Specifically, it is a schematic diagram of the thermal management control system of the present invention, used to illustrate the overall thermal management operation, calculation, decision-making, and control process.

[0052] Figure 3 A simplified schematic diagram of an adaptive altitude thermal management control system for new energy vehicles according to the present invention is shown.

[0053] A second aspect of the present invention also provides an adaptive altitude thermal management control system for new energy vehicles, the system comprising: an environmental parameter acquisition unit responsible for acquiring and storing environmental parameters; Battery temperature acquisition unit: responsible for acquiring and storing battery temperature parameters; Electric drive temperature acquisition unit: responsible for acquiring and storing electric drive temperature parameters; Air conditioning system data acquisition unit: responsible for collecting and storing air conditioning management parameters; Predictive processing unit: responsible for real-time analysis of comprehensive traffic data and setting predicted traffic conditions; Intelligent decision control unit: responsible for comprehensively analyzing multi-dimensional thermal management parameters, and setting corresponding control and compensation parameters for the battery thermal management system, electric drive cooling system, and air conditioning thermal management system, and controlling the battery, electric drive, and air conditioning thermal management systems in real time; The adaptive altitude new energy vehicle thermal management control system also includes an adaptive altitude new energy vehicle thermal management control program, which implements steps S1-S4 of the above embodiments when running in the system.

[0054] A third aspect of the present invention also provides a computer-readable storage medium comprising an adaptive altitude thermal management control program for new energy vehicles, wherein when the adaptive altitude thermal management control program is executed by a processor, it implements the steps of the adaptive altitude thermal management control method for new energy vehicles as described in any of the preceding claims.

[0055] This invention discloses an adaptive altitude-based thermal management control method and system for new energy vehicles. It acquires environmental, battery, electric drive, and air conditioning parameters through a multi-dimensional parameter acquisition module, and combines this with comprehensive road condition data to predict altitude and road condition changes along the driving route, thereby forecasting battery heat load and generating predicted operating conditions. A fusion algorithm of "PID + fuzzy control" is employed to calculate thermal management compensation parameters based on altitude, incorporate wind speed correction, and dynamically adjust PID parameters to regulate the target cooling and heating power of the battery, electric drive, and air conditioning systems. Simultaneously, real-time fault diagnosis and mode setting are performed based on preset fault strategies. This invention constructs a dynamic mapping model of "altitude-air pressure-thermal management parameters" to achieve multi-system collaborative adaptive control, effectively improving the range, battery life, and comfort of new energy vehicles across all altitude regions, demonstrating good practicality and reliability.

[0056] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0057] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0058] In addition, in the various embodiments of the present invention, each functional unit can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0059] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0060] Alternatively, if the integrated units of this invention are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

[0061] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A thermal management control method for new energy vehicles that adapts to altitude, characterized in that, include: S1: Collect multi-dimensional environmental parameters, battery temperature parameters, electric drive temperature parameters, air conditioning management parameters, and comprehensive road condition data through the multi-dimensional thermal management parameter acquisition module in the target vehicle; S2: By comprehensively analyzing road condition data, analyze the altitude change and road condition change trend of the future preset driving distance, and predict the battery heat load to obtain the predicted operating conditions; S3: It adopts a "PID + fuzzy control" fusion algorithm to calculate the compensation parameters of the battery, electric drive and air conditioning based on the altitude, and correct the compensation parameters in combination with the wind speed. At the same time, it calculates the fuzzy logic range in combination with the predicted working conditions and dynamically adjusts the PID parameters. The target cooling and heating power parameters of the battery thermal management system, electric drive cooling system and air conditioning thermal management system are adjusted by PID. S4: Based on the preset fault strategy, the parameters collected by S1 are used to determine the fault threshold in real time, and the fault mode is set for the battery, electric drive and air conditioner.

2. The adaptive altitude thermal management control method for new energy vehicles according to claim 1, characterized in that, In S1, the environmental parameters include altitude, atmospheric pressure, ambient temperature, and wind speed.

3. The adaptive altitude thermal management control method for new energy vehicles according to claim 2, characterized in that, In S1, the battery temperature parameters include the average temperature of the battery pack, the highest temperature of the battery pack, the lowest temperature of the battery pack, the temperature difference between individual cells in the battery pack, the battery SOC, the battery charging and discharging power, the battery coolant inlet temperature, the battery coolant outlet temperature, the battery coolant flow rate, and the radiator fan speed.

4. The adaptive altitude thermal management control method for new energy vehicles according to claim 3, characterized in that, In S1, the electric drive temperature parameters include motor winding temperature, electronic control module temperature, electric drive coolant flow rate, electric drive coolant inlet temperature, and electric drive coolant outlet temperature.

5. The adaptive altitude thermal management control method for new energy vehicles according to claim 4, characterized in that, In S1, the air conditioning management parameters include condenser temperature, evaporator temperature, refrigerant pressure, and air conditioning duct temperature.

6. The adaptive altitude thermal management control method for new energy vehicles according to claim 5, characterized in that, Specifically, S2 is: Comprehensive road condition data includes the target vehicle's GPS location and map elevation data; Based on comprehensive road condition data, the altitude change trend and road condition trend of the target vehicle's future 5km driving route are determined, and the changes in battery heat load and the demand of the liquid cooling system are predicted. The analyzed trends and predictions are summarized to obtain the predicted operating conditions.

7. The adaptive altitude thermal management control method for new energy vehicles according to claim 6, characterized in that, Specifically, S3 is: Based on the target vehicle's current altitude and altitude range-benchmark parameter mapping table, compensation parameter analysis is performed. Linear interpolation is introduced to calculate the compensation parameters for the battery, electric drive, and air conditioning, and the compensation parameters are corrected in combination with wind speed. A fuzzy PID rule table is established based on the predicted operating conditions, and the PID parameters are dynamically adjusted through fuzzy logic intervals. The target cooling and heating power parameters of the battery thermal management system, electric drive cooling system, and air conditioning thermal management system are adjusted through PID.

8. The adaptive altitude thermal management control method for new energy vehicles according to claim 7, characterized in that, The S4 includes: If the altitude data is abnormal, the altitude range is deduced by using atmospheric pressure P, and redundant judgment is made by linking the average battery temperature with the target temperature difference of the coolant. When the average battery temperature is >45℃ or the target temperature difference of the coolant is >10℃, it is judged as a liquid cooling failure warning, triggering the power reduction protection mode, reducing the battery charging and discharging power by 30%, and simultaneously starting the battery water pump and radiator fan to run at full load. If the battery coolant flow rate is detected to be <5L / min at low altitudes or <10L / min at high altitudes, the battery charging and discharging power will decrease by 50%. When the refrigerant pressure is abnormal in a high-altitude environment, the air conditioner will automatically switch to PTC heating mode and the battery will be set to cooling mode. Based on the above fault diagnosis, the warning information will be sent to the vehicle display terminal.

9. A new energy vehicle thermal management control system that adapts to altitude, characterized in that, The system includes: Environmental parameter acquisition unit: responsible for collecting and storing environmental parameters; Battery temperature acquisition unit: responsible for acquiring and storing battery temperature parameters; Electric drive temperature acquisition unit: responsible for acquiring and storing electric drive temperature parameters; Air conditioning system data acquisition unit: responsible for collecting and storing air conditioning management parameters; Predictive processing unit: responsible for real-time analysis of comprehensive traffic data and setting predicted traffic conditions; Intelligent decision control unit: responsible for comprehensively analyzing multi-dimensional thermal management parameters, and setting corresponding control and compensation parameters for the battery thermal management system, electric drive cooling system, and air conditioning thermal management system, and controlling the battery, electric drive, and air conditioning thermal management systems in real time; The adaptive altitude new energy vehicle thermal management control system includes an adaptive altitude new energy vehicle thermal management control program, which, when running in the system, implements the steps of the adaptive altitude new energy vehicle thermal management control method as described in claim 1.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes an adaptive altitude thermal management control program for new energy vehicles. When the adaptive altitude thermal management control program is executed by a processor, it implements the steps of the adaptive altitude thermal management control method for new energy vehicles as described in any one of claims 1 to 8.

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