A heat pump type integrated vehicle thermal management system for commercial vehicles

Abstract

The present invention provides a heat pump type integrated vehicle thermal management system for commercial vehicles, which relates to the technical field of data processing. The system includes: an environment acquisition module for obtaining ambient temperature data and a vehicle start signal; a heat source scheduling module for controlling the operation of a heat pump unit to generate a first heat energy flow; a battery pack heat exchange module for heating the battery pack through a heat exchange structure; a temperature feedback module for determining whether a preset start threshold is reached. If not, an adjustment signal is sent to the heat source scheduling module to adjust the first heat energy flow; a heat flow switching module for controlling the heat source scheduling module to switch the first heat energy flow to a cabin heating path to generate a second heat energy flow after the battery pack temperature reaches the preset start threshold; an energy distribution module for obtaining vehicle driving state data and dynamically distributing the second heat energy flow according to it, and sending it to the driver's cab and the electric drive cooling circuit respectively. The present invention improves the autonomy and accuracy of thermal management.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and particularly to an integrated heat management system for a commercial vehicle with a heat pump type for the whole vehicle. Background Art

[0002] In the prior art, commercial vehicles usually adopt a distributed heat management system to regulate the heat of the whole vehicle, independently controlling the temperatures of the battery pack, the electric drive system, and the cockpit respectively. A common practice is to heat the cockpit through an electric heater, cool the battery and the electric drive assembly through an independent cooling circuit, and some high-end models introduce a heat pump system to recover the heat of the condenser for air-conditioning heating to improve energy efficiency. However, these heat management modules are usually scattered in layout and have independent control strategies, lacking a sharing mechanism between heat sources, and it is difficult to achieve efficient heat transfer and reuse under different working conditions.

[0003] During the winter operation in cold regions, the existing distributed heat management system often has a slow response for preheating the battery pack due to its scattered structure and long response path. For example, before starting in a low-temperature environment, it is necessary to heat the power battery through an electric heater. If the initial temperature of the battery is lower than 0°C, the heating process will last for more than 15 minutes. During this period, the vehicle may not be able to start normally or the output is limited, seriously affecting the operation efficiency. Especially in working conditions such as cold chain transportation or the morning rush hour of urban buses, higher requirements are put forward for the rapid activation and stable performance of the vehicle, and the existing technology is difficult to achieve rapid overall heat regulation of the core components within a limited time. Summary of the Invention

[0004] The purpose of the present invention is to provide an integrated heat management system for a commercial vehicle with a heat pump type for the whole vehicle, aiming to solve the problems mentioned in the background art.

[0005] To solve the above technical problems, the technical solution of the present invention is as follows:

[0006] An integrated heat management system for a commercial vehicle with a heat pump type for the whole vehicle, the system includes:

[0007] An environment acquisition module, configured to obtain ambient temperature data and a vehicle start signal, and generate start condition data;

[0008] A temperature judgment module, configured to extract battery pack temperature data according to the start condition data, and judge whether the battery pack is in a low-temperature state. If so, generate first heat source request data;

[0009] A heat source scheduling module, configured to control the operation of the heat pump unit to generate a first heat energy flow according to the first heat source request data;

[0010] The battery pack heat exchange module is used to heat the battery pack through a heat exchange structure according to the first heat energy flow, and at the same time collect the temperature change data during the preheating process to generate battery pack preheating data;

[0011] The temperature feedback module is used to determine whether the preset start threshold is reached according to the battery pack preheating data. If not, it sends an adjustment signal to the heat source scheduling module to adjust the first heat energy flow and continue to heat the battery pack;

[0012] The heat flow switching module is used to control the heat source scheduling module to switch the first heat energy flow to the cabin heating path to generate the second heat energy flow after the battery pack temperature reaches the preset start threshold;

[0013] The energy distribution module is used to obtain the vehicle driving state data and dynamically distribute the second heat energy flow according to it, and send it to the cockpit and the electric drive cooling circuit respectively, and complete the heat energy distribution of the vehicle thermal management system by adjusting the proportional valve.

[0014] Preferably, the heat source scheduling module includes:

[0015] The heat control sub-module is used to extract the ambient temperature data and the battery pack temperature data according to the first heat source request data, determine the target operating frequency and the target exhaust temperature of the heat pump unit, and generate heat source adjustment parameters;

[0016] The operation instruction generation sub-module is used to send an operation control instruction to the heat pump unit according to the heat source adjustment parameters, so that the heat pump unit generates the first heat energy flow according to the target operating frequency;

[0017] The heat feedback sub-module is used to adjust the operation control instruction in real time according to the adjustment signal to generate the adjusted first heat energy flow.

[0018] Preferably, the battery pack heat exchange module includes:

[0019] The heat exchange path selection sub-module is used to determine the enabled flow channels in the heat exchange path according to the heat amount of the first heat energy flow and the temperature distribution data at different positions of the battery pack;

[0020] The bypass control sub-module is used to open the bypass channel to partially guide the first heat energy flow to bypass the battery pack area in case of excessive heat or local overheating, and generate an optimized heat exchange path;

[0021] The temperature monitoring sub-module is used to collect the temperature change data at different positions of the battery pack during the preheating process to generate battery pack preheating data.

[0022] Preferably, the temperature feedback module includes:

[0023] A temperature change rate calculation sub-module, which is used to calculate the change rate of the battery pack temperature according to the battery pack preheating data, and obtain the temperature rising trend data;

[0024] A threshold prediction sub-module, which is used to predict the remaining time required to reach the preset start threshold according to the temperature rising trend data, and generate a heat source adjustment advance signal;

[0025] A control instruction update sub-module, which is used to send the heat source adjustment advance signal to the heat source scheduling module to optimize the generation strategy of the first heat energy flow in advance.

[0026] Preferably, the energy distribution module includes:

[0027] A priority evaluation sub-module, which is used to calculate the corresponding heat energy demand value according to the vehicle driving state data, the current cockpit temperature data and the electric drive system temperature data, and generate heat distribution priority data;

[0028] A proportional decision sub-module, which is used to determine the distribution ratio of the second heat energy flow between the cockpit and the electric drive cooling circuit according to the heat distribution priority data, and generate a proportional control parameter;

[0029] An execution feedback sub-module, which is used to control the proportional valve to adjust the heat flow according to the proportional control parameter, and real-time monitor the heat flow distribution effect of the two circuits. If there is a deviation, an adjustment feedback signal is output to correct the proportional control parameter.

[0030] Preferably, the heat control sub-module includes:

[0031] An environment evaluation unit, which is used to determine whether the current environment belongs to the alpine region, the medium temperature region or the warm region according to the environment temperature data in the first heat source request data, and generate a corresponding temperature region label;

[0032] A load mapping unit, which is used to look up the table to determine the target operating frequency and the target exhaust temperature according to the temperature region label and the current temperature data of the battery pack, wherein the table look-up operation is based on a preset parameter mapping table;

[0033] An operating range selection unit, which is used to match the operating range of the heat pump unit according to the target exhaust temperature, and preferentially select the operating range with the optimal heat efficiency to generate a heat source adjustment parameter.

[0034] Preferably, the threshold prediction sub-module includes:

[0035] A heating trend modeling unit, which is used to construct a temperature change trend curve according to the multi-period temperature change data in the battery pack preheating data;

[0036] A threshold arrival time estimation unit, configured to predict the time required for the battery pack temperature to reach a preset start threshold according to the temperature change trend curve, and obtain the predicted remaining heating time;

[0037] An early warning judgment unit, configured to compare the predicted remaining heating time with the expected vehicle start time of the vehicle. If it is insufficient, an early heat source adjustment signal is generated.

[0038] Preferably, the priority evaluation sub-module includes:

[0039] A state recognition unit, configured to judge whether the vehicle is currently in the stage of passengers getting on and off, high-speed driving stage or idling and parking stage according to the vehicle driving state data, and generate corresponding operation state labels;

[0040] A heat energy demand calculation unit, configured to calculate the heat energy demand values of the cockpit and the electric drive cooling circuit respectively according to the operation state label, the current temperature data of the cockpit and the temperature data of the electric drive system;

[0041] A priority generation unit, configured to compare the heat energy demand values with the preset state threshold ranges respectively according to the heat energy demand values and the corresponding operation state labels, select the target with a higher demand value in the cockpit and the electric drive cooling circuit as the priority allocation object, and generate heat distribution priority data. If the difference between the two demand values is within the preset difference range, the priority order is determined and adjusted based on the preset weight factor.

[0042] Preferably, the operation interval selection unit includes:

[0043] An interval screening unit, configured to screen candidate intervals that meet the upper and lower limits of the target exhaust temperature from a plurality of preset operation intervals according to the target exhaust temperature;

[0044] An interval evaluation unit, configured to perform a weighted evaluation on the historical energy efficiency performance of each candidate interval, the current heat demand level of the battery and the ambient temperature of the vehicle where the vehicle is located, and calculate a comprehensive score;

[0045] A preferred output unit, configured to select the operation interval with the highest comprehensive score from the candidate intervals as the optimal operation interval, and extract the corresponding frequency and operation parameters to generate heat source adjustment parameters.

[0046] Preferably, the heating trend modeling unit includes:

[0047] A data integration unit, configured to extract temperature sampling values at multiple different times according to the battery pack preheating data, and construct a temperature sequence data set in chronological order;

[0048] A local trend analysis unit is used to divide the temperature series data set into several continuous time periods, and determine the local rising trend or platform trend according to the temperature change rate in each time period to form trend data;

[0049] The global trend construction unit is used to combine the local trends of each continuous time period according to the trend data to construct a temperature change trend curve.

[0050] The above solution of the present invention includes at least the following beneficial effects:

[0051] The commercial vehicle heat pump integrated thermal management system provided by the present invention centrally integrates thermal management strategies through a modular architecture, breaking through the decentralized problems of the structural layout and control strategies of the distributed thermal management system in the prior art, and realizing the unified scheduling and on-demand allocation of the heat source of the whole vehicle. In this system, the ambient temperature and vehicle start-up signal are obtained through the environmental acquisition module, which can identify the key working conditions in cold climates in real time and activate the subsequent thermal control process in advance, significantly improving the system's responsiveness in extreme environments.

[0052] The system uses the temperature judgment module to conduct a linkage analysis of the battery pack temperature and environmental conditions. It has the function of intelligently identifying "preheating requirements" and can actively generate the first heat source request data when the temperature is lower than the preset standard, avoiding the passive startup after waiting for the delayed response of the temperature sensor in traditional technology, thereby shortening the preheating startup time from the root.

[0053] Different from the existing solution of using electric heaters to independently heat up, this system controls the heat pump unit to output the first heat energy flow through the heat source scheduling module, introduces the high-efficiency heat pump system into the battery heating path, and enables the heat source to have dynamic adjustment capabilities and rapid response characteristics. At the initial start-up, the battery pack heat exchange module can quickly guide the first heat energy flow to the heat exchange structure, and build a closed-loop adjustment mechanism through the temperature feedback module to continuously monitor and feedback control the temperature changes during the preheating process, thereby avoiding overheating, underheating or energy waste in the traditional single-time heating mode.

[0054] When the battery pack is heated to the preset start threshold, the system quickly switches the heat energy path through the heat flow switching module, so that the heat source originally used for battery preheating is immediately transferred to the cockpit and electric drive cooling system, ensuring uninterrupted use of heat energy and improving the thermal management efficiency of the vehicle. On this basis, the energy distribution module dynamically controls the distribution ratio of heat energy between the cockpit and the electric drive cooling circuit according to the real-time vehicle driving status, so that the heat energy resources are allocated according to the current working conditions, further avoiding the problem of heat redundancy or insufficient local cooling.

[0055] Compared with the prior art, the present invention effectively solves the problems of long response path and low energy allocation efficiency caused by the dispersion of the thermal management module through the unified scheduling mechanism of the vehicle's thermal energy. Especially in the early start-up scenarios in cold regions, such as when urban buses are put into operation in the early morning or cold chain transportation vehicles are restarted in sub-zero low-temperature environments, the system can complete the preheating of the battery pack in a very short time and promptly transfer the thermal energy to other subsystems, improving the vehicle's rapid start-up ability and the thermal stability of the system operation. The entire heating and regulation process is constructed based on the data flow between modules, with a clear logical path, fast response speed, and significant advantages of high integration, high efficiency, and high adaptability. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 FIG. is an architecture diagram of an integrated vehicle thermal management system of a heat pump type for commercial vehicles provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0057] Hereinafter, exemplary embodiments of the present disclosure will be described in more detail with reference to the drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be fully communicated to those skilled in the art.

[0058] As Figure 1 shown, an embodiment of the present invention provides an integrated vehicle thermal management system of a heat pump type for commercial vehicles, and the system includes:

[0059] An environment acquisition module, configured to obtain ambient temperature data and a vehicle start signal, and generate start-up condition data;

[0060] A temperature judgment module, configured to extract battery pack temperature data according to the start-up condition data, and judge whether the battery pack is in a low-temperature state. If so, generate first heat source request data;

[0061] A heat source scheduling module, configured to control the operation of the heat pump unit to generate a first heat energy flow according to the first heat source request data;

[0062] A battery pack heat exchange module, configured to heat the battery pack through a heat exchange structure according to the first heat energy flow, and simultaneously collect temperature change data during the preheating process to generate battery pack preheating data;

[0063] A temperature feedback module, configured to judge whether a preset start threshold is reached according to the battery pack preheating data. If not, send an adjustment signal to the heat source scheduling module to adjust the first heat energy flow, and continue to heat the battery pack;

[0064] A heat flow switching module, configured to control a heat source scheduling module to switch a first heat energy flow to a cabin heating path to generate a second heat energy flow after the temperature of the battery pack reaches a preset start threshold;

[0065] An energy distribution module, configured to obtain vehicle driving state data and dynamically distribute the second heat energy flow according to the data, and send the second heat energy flow to the cockpit and the electric drive cooling circuit respectively, and complete the heat energy distribution of the vehicle integrated thermal management system by adjusting the proportional valve.

[0066] In an embodiment of the present invention, when a commercial vehicle is in a low-temperature environment and is ready to start, the vehicle integrated thermal management system can realize rapid heating of the battery pack and efficient scheduling of the vehicle's heat energy resources through the coordinated operation of multiple functional modules. The environment acquisition module first senses the external environmental temperature and the vehicle start signal, and generates start condition data, which serves as a trigger basis for subsequent judgment and control. The start condition data can significantly improve the response speed and adaptability of the entire system to vehicle start conditions, and avoid response delays caused by data lag.

[0067] After receiving the start condition data, the temperature judgment module extracts the temperature data of the current battery pack, and judges whether it is in a low-temperature range based on the combination of the current environmental temperature and the battery pack state. This judgment process can realize risk prediction in the early start stage. Especially when the environmental temperature is significantly lower than the freezing point, the system can generate first heat source request data through the low-temperature state judgment result, providing a clear trigger signal for the subsequent activation of the heat pump.

[0068] After receiving the first heat source request data, the heat source scheduling module immediately controls the heat pump unit to start and output a first heat energy flow. Since the response time of this module is short and the control link is direct, the first heat energy flow can be quickly generated at the initial stage of vehicle start, which helps to quickly establish effective heat exchange conditions. Subsequently, the battery pack heat exchange module guides the first heat energy flow to the battery heat exchange structure and heats the battery pack using the established heat exchange path. During the preheating process, this module can also continuously collect temperature change information and generate battery pack preheating data to realize real-time feedback control conditions.

[0069] The system further judges the collected battery pack preheating data through a temperature feedback module, and determines whether the current temperature of the battery pack has reached the preset start threshold. If not, this module will actively send an adjustment signal to the heat source scheduling module to drive it to optimize the heat pump operation strategy, and then adjust the output level of the first heat energy flow. This feedback process has the characteristics of closed-loop control, can correct the heating strategy in real time according to the actual temperature rise curve, and significantly improve the preheating efficiency and temperature stability.

[0070] Once the battery pack reaches the startup threshold, the system exports the first heat flow from the battery circuit through the heat flow switching module and switches to the cabin heating path, thereby generating the second heat flow. This heat flow switching action is uniformly controlled by the heat source scheduling module, with a simple switching logic and high execution efficiency, avoiding the risks of energy waste or thermal shock caused by disordered heat source distribution.

[0071] The energy distribution module starts to operate after the heat flow switching is completed. It dynamically adjusts the distribution path of the second heat flow according to the vehicle driving state data obtained in real time, and distributes it to the cockpit and the electric drive cooling circuit respectively. The actual distribution of the heat flow is completed by adjusting the proportional valve, enabling the thermal resources of the whole vehicle to be flexibly regulated according to the states and priorities of different working components, ensuring that the comfort of the cockpit and the thermal stability of the electric drive system are satisfied simultaneously. This module enhances the intelligent level of the whole vehicle thermal management and has strong adaptability to sudden working conditions.

[0072] In summary, through this integrated thermal management system, it is possible to achieve high-responsive rapid heating of the battery pack under extremely cold conditions, while dynamically switching the heat energy utilization path, ensuring the stable operation of the battery, electric drive and cabin temperature control systems under different working conditions, thus effectively solving problems such as slow startup response and rigid heat energy distribution, and improving the operation efficiency and system reliability of the whole vehicle.

[0073] Among them, the environment acquisition module is mainly used to timely sense the temperature change of the current external environment and synchronously receive the signal information of whether the vehicle is ready to start when the vehicle is in a stationary or about-to-start state. This module is usually composed of two main functional units: the ambient temperature sensing unit and the start signal receiving unit.

[0074] The ambient temperature sensing unit is set on the vehicle shell or in an area where the atmospheric temperature is easily accessible, preferably at the front of the vehicle or outside the battery compartment. Its core is a digital or thermosensitive temperature sensor, which is used to detect the external temperature of the environment where the vehicle is currently located. This temperature information serves as the basic judgment parameter for the whole vehicle thermal management strategy. In terms of structural layout, the sensor should avoid interference from the residual heat source of the engine to ensure the representativeness and accuracy of the collected temperature data.

[0075] The start signal receiving unit is connected to the vehicle's power management system and can monitor various signal sources such as the vehicle key switch state, remote start command, and output of the battery ignition controller, so as to judge whether the vehicle is in the start preparation stage. The logic circuit of this signal reception can be set to the edge trigger mode. When the signal state changes from "not started" to "ready to start", the state is immediately reported to the control unit to trigger the activation of the subsequent module.

[0076] After the two units operate in combination, the environmental acquisition module will simultaneously output the external environmental temperature data and the vehicle start signal, integrate and generate the "start operating condition data", which serves as the basic input for subsequent temperature judgment and heat source scheduling, and plays a key role as a trigger source in the entire thermal management control process. In the system design, it is recommended to set the sampling period within 1 second to ensure the timeliness of response to temperature mutations or sudden start operations.

[0077] Among them, the temperature judgment module is used to judge whether the current battery pack is in a state that needs to be heated, and generate the first heat source request data when necessary. The core function of this module is to logically compare the start operating condition data with the battery pack temperature data, and set a set of judgment conditions to make a heating decision.

[0078] This module usually includes three key processing steps: battery pack temperature extraction, low-temperature state identification, and request generation.

[0079] First, the system extracts the current battery pack temperature data from the temperature acquisition point in the battery pack thermal management loop. This data can be obtained through multiple temperature sensors arranged on the outer shell or inside the housing of the battery pack, and the representative temperature is extracted through the temperature averaging or minimum temperature algorithm to avoid misjudging the overall state due to local temperature rise.

[0080] Secondly, the module compares the extracted battery pack temperature with a set of preset low-temperature determination thresholds. For example, in areas where the environmental temperature is lower than 5°C, if the battery pack temperature is lower than 0°C or lower than the system-defined safe operating lower limit (such as 5°C), it is determined to be in the "low-temperature state". This judgment process can be adjusted according to specific vehicle types, battery types, and operating regions.

[0081] When the low-temperature state is confirmed, the module will immediately generate the "first heat source request data" and output it to the heat source scheduling module. This request data includes information such as the current temperature state of the battery, the required heat energy level, and the external environmental temperature level. The control strategy can judge based on this whether the heat pump needs to be immediately enabled, at what power level to output heat, and other specific contents.

[0082] The temperature judgment module has the characteristics of high judgment accuracy, fast response speed, and dynamic configurability, and is applicable to various commercial vehicle battery system structures, especially suitable for the application environment of power battery packs with distributed temperature control and complex heat capacity.

[0083] In a preferred embodiment of the present invention, the heat source scheduling module includes:

[0084] The heat control sub-module is used to extract the environmental temperature data and the battery pack temperature data according to the first heat source request data, determine the target operating frequency and target exhaust temperature of the heat pump unit, and generate heat source adjustment parameters;

[0085] An operation instruction generation sub-module, configured to issue an operation control instruction to the heat pump unit according to the heat source adjustment parameter, so that the heat pump unit generates a first heat energy flow at a target operation frequency;

[0086] A heat feedback sub-module, configured to adjust the operation control instruction in real time according to the adjustment signal to generate an adjusted first heat energy flow.

[0087] In an embodiment of the present invention, in the vehicle integrated thermal management system, the heat source scheduling module is further refined into three sub-modules, each responsible for parameter determination, control signal generation, and output adjustment functions of the heat pump unit. Through the internal division of labor and cooperation within the module, the system can achieve precise heat source control under different working conditions and improve the heating response efficiency.

[0088] The heat control sub-module first extracts the current ambient temperature data and battery pack temperature data according to the first heat source request data, and uses these as inputs to determine the target operation frequency and target exhaust temperature of the heat pump unit. Compared with the traditional scheme with fixed operation parameters, this method realizes the dynamic adaptation of the operation strategy by integrating external and internal thermal environment information. Especially when the ambient temperature changes rapidly or the battery has strong thermal inertia, the adaptive setting of the target frequency and exhaust temperature can significantly improve the heat pump energy efficiency and reduce the ineffective operation time.

[0089] The operation instruction generation sub-module constructs a specific control instruction based on the heat source adjustment parameter and issues it to the heat pump unit. This control link has high timeliness in response time, can quickly trigger the change of the heat pump heating state, and enable the first heat energy flow to be accurately output according to the expected parameters. At the same time, this instruction generation mechanism also has a certain fault tolerance design, and can perform fault detection according to the response state of the control instruction, enhancing the stability and safety of the system.

[0090] The heat feedback sub-module is used to adjust the original operation control instruction in real time according to the subsequent adjustment signal from the temperature feedback module. When it is detected that the heating effect is insufficient or the target temperature is not reached for a long time, the system can quickly reconstruct the heat pump operation strategy, increase the heat output or extend the heating time, and realize the continuous optimization of the heat pump working state.

[0091] This structured heat source scheduling module makes the heat pump unit no longer a fixed device driven by a single logic, but an intelligent heating component that can be dynamically scheduled and real-time controlled. Compared with the traditional heat pump control system, this method can greatly improve the adaptability of the system to complex thermal environments without increasing additional hardware costs, and is especially suitable for the rapid start-up requirements of the vehicle in cold environments.

[0092] In a preferred embodiment of the present invention, the battery pack heat exchange module includes:

[0093] The heat exchange path selection sub-module is used to determine the enabled flow channels in the heat exchange path according to the heat amount of the first heat energy flow and the temperature distribution data at different positions of the battery pack;

[0094] The bypass control sub-module is used to open the bypass channel to partially guide the first heat energy flow around the battery pack area in case of excessive heat or local overheating, so as to generate an optimized heat exchange path;

[0095] The temperature monitoring sub-module is used to collect the temperature change data at different positions of the battery pack during the preheating process and generate the battery pack preheating data.

[0096] In the embodiments of the present invention, in order to achieve more efficient heat conduction of the first heat energy flow to the battery pack, the battery pack heat exchange module in the system is further divided into three sub-modules, which are respectively responsible for three functions: heat exchange path selection, heat guidance and temperature monitoring. The core design of this module lies in improving the uniformity and stability of heat distribution, reducing the risk of local thermal shock or overheating, and enhancing the safety and efficiency performance of the battery system during the heating process.

[0097] The heat exchange path selection sub-module dynamically selects the currently enabled flow channels according to the heat amount of the first heat energy flow and the temperature distribution data at different positions inside the battery pack. This path selection basis can preferentially guide the heat to the area with lower temperature, accelerating the consistency of the overall temperature rise of the battery. In addition, this channel selection mechanism has a hierarchical priority structure and can automatically complete the optimal path combination according to the target temperature gradient and path impedance, thereby reducing heat transfer loss.

[0098] The bypass control sub-module is activated when it detects excessive heat or abnormal temperature rise in a local area of the battery. By opening the bypass channel, this module diverts part of the heat energy flow from the main heating path, bypasses the high-temperature area and enters the bypass heat exchange loop, thus realizing the dynamic dispersion of the heat flow. This operation not only avoids the performance degradation of local battery cells caused by overheating, but also enhances the thermal stability of the entire heating process.

[0099] The temperature monitoring sub-module continuously collects the temperature change data at different positions of the battery pack during the entire preheating process and generates the battery pack preheating data, providing basic information for the subsequent judgment of the temperature feedback module. This sub-module has the capabilities of high-frequency sampling and multi-point monitoring, can quickly sense the change trend of the thermal field, and identify potential abnormal areas, thereby improving the preheating control accuracy.

[0100] With the above structure, the battery pack heat exchange module not only has the traditional function of heat flow access, but also has multiple capabilities such as heat distribution control, heat risk avoidance and information collection and feedback. It is especially suitable for use in the application scenarios of large commercial vehicles with large initial temperature differences and complex battery structures, and can effectively improve the intelligent level of vehicle thermal management and the reliability of the battery system.

[0101] Among them, the heat exchange path selection sub-module, as the core functional unit in the battery pack heat exchange module, is mainly used to dynamically select a suitable heat exchange path according to the current heat source output situation and the temperature distribution characteristics inside the battery pack, so as to achieve efficient heat transfer and balanced distribution of heat inside the battery pack.

[0102] This sub-module includes the following implementation logic steps: judgment of heat energy flow intensity, perception of temperature distribution, and path switching control.

[0103] First of all, the system obtains the output parameters of the first heat energy flow, including indicators such as heat flow rate, fluid temperature, and flow velocity. This information can be obtained in real time through the temperature sensor and flow sensor at the outlet of the heat pump unit. Combining this information, the system evaluates whether the current heat energy flow has sufficient heating capacity, and judges whether it can enter the normal heat exchange process or needs to be bypassed (the bypass control function is completed by subsequent sub-modules).

[0104] Next, the system establishes a battery pack temperature distribution model through temperature sensors arranged at multiple positions in the battery pack, and identifies which areas are still at a low temperature and which areas have approached the target temperature. This distribution information serves as the core reference data for path selection. Combining the heat transfer efficiency and path impedance, the heat exchange branch or sub-circuit that should be preferentially guided by the heat energy flow at present is selected.

[0105] The path switching control mechanism then performs the heat flow path switching operation according to the above judgment results through electromagnetic valves, commutators or controllable flow guiding mechanisms inside the heat exchange unit. The specific path configuration can be parallel, series or ring structure, and flow resistance control devices can be set between each path to accurately control the heat energy distribution ratio of each path.

[0106] Through path selection control, this sub-module can achieve effects such as local temperature difference compensation, avoiding overheating of hot spots, and improving overall heating uniformity. It is particularly effective in complex multi-module battery structures, which helps to extend the battery life and improve the system heating efficiency.

[0107] Among them, the bypass control sub-module is set in the battery pack heat exchange module and is used to shunt the heat energy flow when the heat energy flow intensity is too high or there is a local overheating trend inside the battery pack, so as to avoid a certain sub-region of the battery from being subjected to concentrated thermal shock and ensure the balance and safety of the overall heating of the battery pack.

[0108] Structurally, the bypass control sub-module includes a heat flow diversion judgment unit, a bypass valve control unit, and a guiding path switching unit. The heat flow diversion judgment unit receives in real time the current heat energy flow information from the heat exchange path selection sub-module, including data such as flow rate, temperature, and fluid pressure, and simultaneously monitors the local temperature information of the battery pack from the temperature monitoring sub-module. If it is found that the heat flow intensity exceeds the set threshold, or the temperature in some battery areas continues to rise and approaches the upper limit, this unit will generate a bypass trigger signal.

[0109] The bypass valve control unit responds to this trigger signal and controls the switching operation of the bypass solenoid valve, proportional valve, or switching valve device provided on the main heat flow path to divert part of the heat energy flow into the bypass pipeline or the auxiliary heat exchange path. Usually, these paths are arranged in parallel or cross with the main heating circuit, and can guide the heat flow around the high-temperature area and flow to the heat exchange branch with a relatively lower temperature, playing a buffering role.

[0110] The guiding path switching unit is used to perform the path stabilization operation after the heat energy is redistributed, such as delaying the closing of the bypass, slowly opening and closing the valve, ensuring that the heat flow pressure does not fluctuate violently during the switching process, and avoiding pulse shock in the heat system. At the same time, in combination with the feedback mechanism of the main controller, the maximum opening time can be set to prevent continuous operation of the bypass.

[0111] Overall, the bypass control sub-module effectively improves the thermal safety during the battery heating process by introducing an "active avoidance" mechanism in heat regulation. Especially in a system environment with high power output or uneven temperature control sensing, it has strong practical value and control flexibility.

[0112] Among them, the core role of the temperature monitoring sub-module is to provide high-resolution temperature status data for the entire heat exchange control process and support dynamic acquisition and real-time upload functions, which is the basis for constructing a temperature feedback mechanism and preheating trend judgment.

[0113] Its structure usually includes a sensor layout unit, a data acquisition unit, and a data reporting interface unit. The sensor layout unit needs to combine the internal structure characteristics of the battery pack and arrange multiple temperature sensors at key thermosensitive parts, such as the middle of the battery cell, the end of the module, and the position of the battery pack shell near the heat exchange interface. These sensors should preferably use high-sensitivity digital temperature sensors or thermocouple arrays, and are required to have a small temperature response lag time and a high sampling frequency.

[0114] The data acquisition unit is responsible for periodically polling or batch synchronously reading the temperature data of each measurement point, and performing preliminary outlier screening and filtering to remove pseudo-signals such as instantaneous pulse interference. The sampling period is recommended to be set within 1 second so that the system can timely obtain the change trend of the thermal field during the heating process.

[0115] The data reporting interface unit uniformly formats the sorted temperature data and transmits it to the system main control unit or the temperature feedback module through the bus or serial port protocol. The reported data should include information such as the current value of each measuring point, the sampling timestamp, and the change rate, facilitating subsequent trend analysis and control response of the system.

[0116] The temperature monitoring sub-module not only provides a single temperature value but also supports the system to achieve the thermal state recognition ability of "spatial distribution + time variation" through time series changes, providing basic data support for multiple functions such as bypass control, trend modeling, and startup judgment.

[0117] In a preferred embodiment of the present invention, the temperature feedback module includes:

[0118] A temperature change rate calculation sub-module, which is used to calculate the change rate of the battery pack temperature based on the battery pack preheating data to obtain temperature rise trend data;

[0119] A threshold prediction sub-module, which is used to predict the remaining time required to reach the preset startup threshold based on the temperature rise trend data and generate a heat source adjustment advance signal;

[0120] A control instruction update sub-module, which is used to send the heat source adjustment advance signal to the heat source scheduling module to optimize the generation strategy of the first heat energy flow in advance.

[0121] In the embodiment of the present invention, during the preheating process, in order to avoid the heat pump system being in a low-efficiency state of blind constant power output or fixed heating cycle, a temperature feedback module is introduced and further refined into three sub-modules with clear functions to achieve dynamic prediction and closed-loop regulation control, enhancing the system's response ability to the battery heating state.

[0122] After receiving the battery pack preheating data, the temperature change rate calculation sub-module first calculates the time change rate of the battery temperature. This rate value is calculated based on the temperature difference change within a continuous time period and can accurately reflect the actual response speed of the current heating system. Through this parameter, the system can determine whether the current heat output reaches the expected efficiency and provide a quantitative basis for the subsequent prediction module.

[0123] Based on the temperature change rate, the threshold prediction sub-module further estimates the remaining time required to reach the preset startup threshold to obtain the predicted remaining heating time. This prediction behavior upgrades the traditional "whether the target temperature is reached" determination method to a feedforward control method of "when it is expected to reach the target". The prediction mechanism enables the system to identify in advance whether the heating progress lags behind before the temperature reaches, effectively avoiding the problem of slow startup. For example, when the heating curve shows a plateau trend and the temperature rise speed slows down, this module can quickly sense and issue a warning signal.

[0124] Once it is found that the predicted remaining heating time is too long, the early warning judgment sub-module will immediately generate a heat source adjustment early signal, which is fed back to the heat source scheduling module to trigger an increase in heating power or an adjustment of the operating frequency, and intervene in the output strategy of the heat pump system in advance. This strategy can not only shorten the total preheating duration, but also avoid the risk of vehicle start failure or delay caused by insufficient heating.

[0125] The temperature feedback module constructs a dynamic prediction mechanism based on the current state, which essentially breaks the single-dependence mode of the traditional feedback mechanism on the real-time temperature threshold, improves the intelligent adjustment ability of the temperature control system, has strong adaptability and foresight, and is especially suitable for the rapid startup scenarios of commercial vehicles under different ambient temperatures and different battery states.

[0126] In a preferred embodiment of the present invention, the energy distribution module includes:

[0127] A priority evaluation sub-module, which is used to calculate the corresponding heat energy demand value according to the vehicle driving state data, the current temperature data of the cockpit, and the temperature data of the electric drive system, and generate heat distribution priority data;

[0128] A proportional decision sub-module, which is used to determine the distribution ratio of the second heat energy flow between the cockpit and the electric drive cooling circuit according to the heat distribution priority data, and generate a proportional control parameter;

[0129] An execution feedback sub-module, which is used to control the proportional valve to adjust the heat flow according to the proportional control parameter, and monitor the heat flow distribution effect of the two circuits in real time. If there is a deviation, an adjustment feedback signal is output to correct the proportional control parameter.

[0130] In the embodiment of the present invention, after the battery pack reaches the startable state and the heat energy switches to the cabin heating path, the focus of the vehicle's heat energy regulation turns to the coordination between the comfort of the cockpit and the cooling demand of the electric drive. The energy distribution module has carried out a systematic design for this, and is divided into three functional sub-modules, from demand recognition, proportional decision-making to adjustment feedback, to build a complete dynamic distribution logic.

[0131] The priority evaluation sub-module calculates the heat energy demand values of the two circuits by obtaining the vehicle driving state data, the current temperature data of the cockpit, and the temperature data of the electric drive system, and generates heat distribution priority data accordingly. Compared with the static weight or fixed-ratio distribution mechanism, this module can dynamically judge the distribution focus by combining real-time data. For example, when the vehicle is started for the first time in the morning and the cockpit is still in a low-temperature state, the system preferentially guides the heat energy to the cockpit; after a long time of operation, when the temperature of the electric drive system rises to the safety boundary, this priority can be automatically switched to the electric drive cooling.

[0132] The proportional decision sub-module calculates the distribution ratio of the second heat energy flow between two targets based on the priority data, generates a proportional control parameter, and passes this parameter as an input to the execution unit. This proportional parameter supports high-precision continuous adjustment and can achieve stepless switching of different ratios (such as 70%–30%, 50%–50%, etc.) to adapt to changes in actual working conditions.

[0133] The execution feedback sub-module serves as the closed-loop control node for the entire heat energy distribution process, continuously monitoring the actual distribution effect. When phenomena such as valve control deviation, uneven heat energy distribution, or slow loop response occur, the module can immediately generate an adjustment feedback signal and correct the current proportional control parameter to ensure that the heat regulation conforms to the desired strategy and avoid problems such as uneven heating and cooling, overheating, or insufficient cooling.

[0134] Through the above division of labor and cooperation, the energy distribution module can not only achieve dual-channel allocation of the heat energy flow, but also continuously optimize the distribution strategy under various driving and working conditions, effectively enhancing the adaptive ability and comfort guarantee ability of the vehicle's thermal management system.

[0135] Among them, the proportional decision sub-module is used to dynamically determine the distribution ratio of heat energy between the cockpit heating circuit and the electric drive cooling circuit according to the heat distribution priority data under the condition that the second heat energy flow has been generated, and output the corresponding proportional control parameter.

[0136] The working process of this module includes three steps: a priority interpretation unit, a ratio calculation unit, and a ratio parameter generation unit. The priority interpretation unit first receives and reads the heat distribution priority data output by the priority evaluation sub-module to determine whether the current heat demand of the cockpit is the main one or the cooling load of the electric drive system is higher. This priority information may be expressed in ways such as fixed values, weight factors, scoring intervals, etc., and the system can make a judgment by comparing high and low values or referring to weight factors.

[0137] The ratio calculation unit then divides the second heat energy flow into different ratios according to the identified priority. It is recommended that the ratio be set in a continuously adjustable manner, such as any value between 0% and 100%, rather than only supporting fixed gears (such as 70 / 30, 50 / 50). This calculation process can be determined by considering multiple factors comprehensively, such as the magnitude of the heat load difference, the trend of heat demand, vehicle speed, or driving state and other parameters, to further improve the rationality of heat energy resource allocation.

[0138] The ratio parameter generation unit generates a proportional control parameter in a standard data format based on the calculated distribution ratio and outputs it to the execution feedback sub-module. This parameter can correspond to the control signal of the electric proportional valve in the physical execution component or be used to control the opening and closing time of the reversing valve, thereby actually completing the adjustment of the heat flow direction and flow distribution.

[0139] The proportional decision-making sub-module realizes the precise distribution of thermal energy, enabling the vehicle to dynamically respond to different thermal demands of the cabin and the electric drive during driving, with high thermal adaptability, and improving the thermal balance control performance of the vehicle's thermal management system in complex operating scenarios.

[0140] Among them, the execution feedback sub-module is responsible for implementing the control parameters of the proportional decision-making sub-module into the physical heat flow path, and performing real-time monitoring and dynamic correction of the execution effect. It is an important part of building a complete closed-loop control structure.

[0141] The module structure includes three parts: an execution control unit, a feedback acquisition unit, and an adjustment output unit. The execution control unit is responsible for receiving proportional control parameters and converting them into specific control instructions to be sent to proportional valves, electric commutators, or other execution devices. The form of the control instructions can be PWM pulse width modulation signals, current drive signals, or digital adjustment commands, depending on the execution device.

[0142] The feedback acquisition unit, through devices such as flow sensors, temperature sensors, or pressure difference sensors set in the thermal energy circulation path, real-time collects the actual flow direction, flow rate, and temperature change of the current heat flow in the corresponding area. By comparing these feedback information with the preset expected state, it can judge whether there is a control deviation.

[0143] When it is detected that there is a significant deviation between the heat flow distribution and the expected ratio (such as the error exceeds the allowable range), the adjustment output unit will generate an adjustment feedback signal based on the error magnitude and change trend, and re-correct the control parameters to make the valve control action tend to the target ratio value, realizing fast closed-loop adjustment.

[0144] This module ensures that the proportional control instructions can not only be issued, but also form real-time response and effective verification at the execution end, forming a complete loop of "decision - execution - feedback - correction" in the control chain, effectively solving the problem of heat flow control distortion caused by factors such as valve response lag and unstable execution accuracy.

[0145] In a preferred embodiment of the present invention, the heat control sub-module includes:

[0146] An environment assessment unit, used to determine whether the current environment belongs to a high-cold interval, a medium-temperature interval, or a warm interval according to the environmental temperature data in the first heat source request data, and generate a corresponding temperature interval label;

[0147] A load mapping unit, used to look up the table to determine the target operating frequency and the target exhaust temperature according to the temperature interval label and the current temperature data of the battery pack, wherein the table lookup operation is based on a preset parameter mapping table;

[0148] An operating range selection unit is used to match the operating range of the heat pump unit according to the target exhaust temperature, preferentially select the operating range with the optimal thermal efficiency, and generate heat source adjustment parameters.

[0149] In the embodiment of the present invention, in the heat source scheduling module, in order to make the heat pump operation closer to the actual working conditions and improve the energy efficiency, the system further designs the internal structure of the heat quantity control sub-module, and completes the whole process of environment judgment, parameter look-up table and operating range selection through three sub-units.

[0150] The environment assessment unit is used to analyze the ambient temperature data in the first heat source request data, judge the current external temperature environment, and divide it into an alpine region, a medium temperature region or a warm region. This classification operation provides a basic condition for the subsequent switching of control strategies. For example, in the alpine region, the heat pump system usually requires a higher initial frequency to quickly output heat energy, while in the medium temperature or warm region, more attention is paid to the balance between efficiency and energy consumption.

[0151] The load mapping unit combines the temperature range label and the current temperature data of the battery pack, looks up the table to determine the target operating frequency and target exhaust temperature of the heat pump system, and the mapping table used is preset by the system and constructed according to experience and test data. This table look-up process has the characteristic of fast response and can complete the matching of operating parameters within milliseconds, avoiding the response delay caused by the long operation time of traditional algorithms.

[0152] The operating range selection unit then matches within multiple operating ranges of the heat pump system according to the determined target exhaust temperature, preferentially selects the operating range with the optimal thermal efficiency as the current activation target, and outputs the frequency and exhaust temperature corresponding to this range as heat source adjustment parameters. This selection process is not only based on the principle of energy efficiency priority, but also can be comprehensively judged by combining safety factors such as the current and voltage of the system, further improving the operation stability.

[0153] Through the coordinated cooperation of the three units, the heat quantity control sub-module can dynamically construct the optimal operating parameters in the face of complex and changeable environmental temperatures and battery states, achieving the dual goals of fast response and efficient heating. This mechanism avoids the operation deviation caused by fixed parameters of the heat pump system in different scenarios, and has remarkable working condition adaptability and control flexibility.

[0154] In a preferred embodiment of the present invention, the threshold prediction sub-module includes:

[0155] A heating trend modeling unit is used to construct a temperature change trend curve according to the multi-period temperature change data in the battery pack preheating data;

[0156] A threshold arrival time estimation unit is used to predict the time required for the battery pack temperature to reach the preset start threshold according to the temperature change trend curve, and obtain the predicted remaining heating time;

[0157] An early warning judgment unit is configured to compare the predicted remaining heating time with the expected vehicle start time of the vehicle. If it is insufficient, an early heat source adjustment signal is generated.

[0158] In an embodiment of the present invention, during the process of the system executing battery pack preheating control, relying solely on real-time temperature for judgment often has problems of lag or insufficient judgment accuracy. Especially when the battery temperature changes slowly or there is a phenomenon of thermal inertia, it is difficult for traditional control strategies to accurately predict the arrival time of the target threshold. Therefore, the system refines the threshold prediction sub-module into three sub-units to improve the time prediction ability and control response efficiency of the thermal management system.

[0159] The heating trend modeling unit receives the battery pack preheating data from the temperature monitoring sub-module and extracts the temperature change conditions at multiple time nodes. By establishing a time series and analyzing multiple consecutive sampling points, this unit can construct a battery temperature change trend curve to form a basic model for reflecting the current temperature rise trajectory. Compared with simple linear estimation methods, this trend curve has the capabilities of smoothing fluctuations, platform judgment, and variable rate tracking, and is applicable to non-linear temperature rise scenarios.

[0160] Based on this trend curve, the threshold arrival time estimation unit further calculates the remaining time required for the battery temperature to reach the preset start threshold. The estimation process comprehensively judges by combining elements such as the current temperature rise rate, the slope of the trend curve, and the target temperature difference distance, so as to give a more engineering-feasible remaining time value. This time estimate not only has a certain accuracy but also can be periodically corrected during the long-term heating process to improve the stability and reliability of the prediction.

[0161] The early warning judgment unit compares the estimated remaining heating time with the expected vehicle start time of the vehicle. If it is found that the remaining time is greater than the system's expected response time limit, an early heat source adjustment signal is immediately generated to activate the heat source scheduling module to execute the operation of increasing the heating intensity or the operation frequency adjustment strategy. This early trigger control logic has obvious feed-forward control characteristics and can drive the execution of actions without relying on the state of reaching the target value, which is an innovative expansion of the traditional closed-loop logic.

[0162] Through the above structural design, the battery heating control process is upgraded from "judgment based on real-time state" to "intervention based on trend prediction", which can effectively improve the heating response efficiency of the system, especially applicable to the operating scenarios of commercial vehicles where the battery temperature changes slowly or the environmental temperature difference fluctuates violently.

[0163] In a preferred embodiment of the present invention, the priority evaluation sub-module includes:

[0164] A state recognition unit, configured to determine whether the vehicle is currently in the stage of passengers getting on or off, high-speed driving, or idling and parking according to the vehicle driving state data, and generate corresponding operation state labels;

[0165] A thermal energy demand calculation unit, configured to calculate the thermal energy demand values of the cockpit and the electric drive cooling circuit respectively according to the operation state labels, the current temperature data of the cockpit, and the temperature data of the electric drive system; where

[0166] ,

[0167] is the thermal energy demand value, representing the current heat compensation demand value of the corresponding module (cockpit or electric drive), is the set target temperature, the working temperature that the cockpit or the electric drive expects to reach, is the current temperature, the current temperature of the cockpit or the electric drive collected in real time, is the change rate of the current temperature with time, representing the response speed of the system for heating or cooling, is the current heat load factor, representing the load intensity of the system's response to heat flow in the current state, , , are the weight coefficients, corresponding to the influences of the temperature difference, the response rate, and the load factor on the thermal energy demand value respectively, satisfying ;

[0168] A priority generation unit, configured to compare the thermal energy demand value with the preset state threshold range respectively according to the thermal energy demand value and the corresponding operation state label, select the target with a higher demand value in the cockpit and the electric drive cooling circuit as the priority allocation object, and generate heat allocation priority data. If the difference between the two demand values is within the preset difference range, the priority order is determined and adjusted based on the preset weight factor.

[0169] In the embodiments of the present invention, to achieve precise heat distribution between the cockpit and the electric drive system, the system refines the structure of the priority evaluation sub-module and constructs a priority generation strategy based on state perception and demand judgment to achieve more flexible and intelligent thermal energy scheduling control.

[0170] The state recognition unit first reads the vehicle driving state data to determine whether the current vehicle is in the stages of passengers getting on or off, high-speed driving, idling and parking, etc., and generates operation state labels according to the judgment results. This recognition result, as an input condition, not only reflects the system's understanding ability of the operation context but also provides different processing paths for the heat distribution strategy. For example, in the high-speed driving stage, more emphasis is placed on electric drive cooling, while in the getting on or off or idling state, more attention is paid to the comfort of the cockpit.

[0171] Based on the status label, the heat energy demand calculation unit further combines the current cockpit temperature data and the electric drive system temperature data to calculate the heat energy demand values of the two systems respectively. This demand value is not only based on the temperature difference, but can also be calculated in combination with factors such as the temperature rise rate and the load level, constructing a comprehensive index reflecting the real-time heat load, ensuring the accuracy and dynamics of the demand assessment.

[0172] The priority generation unit then compares the two heat energy demand values and makes a judgment in combination with the preset threshold range under the current status label, so as to determine which subsystem has a higher allocation priority at the current moment. When the two demand values are close and the difference falls within the preset threshold range, this unit will call the built-in weight factor for judgment and dynamically adjust the allocation order to ensure the fairness and stability of resource allocation. This mechanism avoids the oscillation phenomenon of frequently switching the allocation priority due to small numerical differences, and at the same time improves the allocation flexibility of the system.

[0173] Generally speaking, the design logic of this module has three control dimensions: working condition identification - demand quantification - priority adjustment, which not only improves the rationality of heat distribution, but also enhances the execution stability of the control strategy, and is especially suitable for variable and dynamic driving scenarios.

[0174] Among them, the status identification unit is used to identify the driving condition of the current vehicle and generate the corresponding operation status label, providing a decision-making basis for the subsequent heat energy demand calculation and priority judgment. The unit constructs an intelligent identification mechanism based on "vehicle condition perception", and the core task is to judge whether the vehicle is in the starting stage, high-speed driving stage, low-speed cruising stage, idle waiting state, or in the short-term parking stage before and after passengers get on and off.

[0175] The inputs of this unit mainly include vehicle speed data, acceleration data, transmission gear information, parking state signal, door control switch state, driving mileage change, etc. The above data can be collected through the existing vehicle CAN bus system, or can be connected to the body control module (BCM) and the vehicle control unit (VCU) for linkage.

[0176] The judgment logic is generally processed based on a set of status determination rules. For example, when the vehicle speed is 0 km / h and the transmission is in the P gear, and the door is in the open state for more than the set time, it can be judged as the passenger getting on and off stage; when the vehicle speed is continuously and stably higher than 60 km / h and the acceleration remains within a low fluctuation range, it can be determined as the high-speed driving state; while being stationary for a long time but not turning off the engine and the air conditioner is in operation, it is identified as the idle waiting state.

[0177] Once the recognition result is generated, the status recognition unit will output a set of discrete state tags (such as "start", "high speed", "stop", etc.), which will be used as the basis for adjusting the weight factor in the subsequent heat energy distribution strategy. This operating condition determination mechanism can significantly improve the environmental adaptability of heat energy scheduling, enabling the dynamic synchronization of heat energy resource allocation with the vehicle's operating intention.

[0178] Among them, the priority generation unit is the core decision-making unit in the entire heat energy distribution logic. Its main task is to determine the heat energy distribution priority based on the current operating state on the basis of obtaining the heat energy demand values of the cockpit and the electric drive system respectively, so as to guide the proportional decision-making module to complete the reasonable allocation of heat flow resources.

[0179] In terms of functional structure, this unit first compares the two heat energy demand values. If the demand value of one party is significantly higher than the other party (such as exceeding the set difference threshold), then directly mark this party as the high-priority target; if the demand difference between the two is small and within the preset "critical interval", a set of preset weight factor rules will be referenced according to the operating state label for further judgment. For example, in the "idle stop" state, the system may preset that the cockpit takes priority; in the "high-speed driving" state, the electric drive system has a higher priority.

[0180] This judgment mechanism is based on a simple interval decision and conditional matching logic. It does not rely on complex calculation models in engineering implementation, is easy to deploy in embedded systems, and has high real-time performance. The output of the priority generation unit is usually a set of priority tags or numerical levels (such as "electric drive priority: high, cockpit priority: low"), and serves as the direct input for heat distribution ratio decision-making.

[0181] By introducing this unit, the vehicle's thermal management system has achieved a complete closed-loop from "real-time perception" to "demand calculation" and then to "strategy decision-making", effectively improving the utilization efficiency of heat flow resources. Especially in scenarios where the vehicle's operating state frequently changes and the heat demand rapidly varies, it has significant practical value.

[0182] In a preferred embodiment of the present invention, the operating range selection unit includes:

[0183] Range screening unit, which is used to screen candidate ranges that meet the upper and lower limits of the target exhaust temperature from a plurality of preset operating ranges according to the target exhaust temperature;

[0184] Range evaluation unit, which is used to perform a weighted evaluation on the historical energy efficiency performance of each candidate range, the current heat demand level of the battery, and the ambient temperature of the vehicle, and calculate a comprehensive score; where

[0185] ,

[0186] is the candidate operating range The comprehensive score is used to optimize the working range that is most suitable for the current thermal management strategy. is the candidate operating range The historical average thermal efficiency reflects its energy-saving effect during historical operation. and are the thermal energy demand values of the cockpit and the electric drive system respectively. is the candidate operating range The maximum available thermal power represents the upper limit of its heating capacity. is the current external environmental temperature. is the candidate operating range The most suitable working environmental temperature. is the allowable environmental temperature difference tolerance, representing the tolerance range for temperature deviation. , , are the weight coefficients, corresponding to thermal efficiency, demand matching degree, and environmental adaptability respectively, satisfying ;

[0187] The optimal selection output unit is used to select the operating range with the highest comprehensive score from the candidate ranges as the optimal operating range, and extract the corresponding frequency and operating parameters to generate the heat source adjustment parameters.

[0188] In the embodiment of the present invention, after the heat source scheduling module completes the preliminary determination of the target exhaust temperature and frequency, the operating range selection unit screens and evaluates the optional operating ranges according to multi-dimensional evaluation factors to ensure that the system operates in the range with the optimal efficiency and the highest matching degree, thereby maximizing the overall energy efficiency performance of the heat pump unit.

[0189] Based on the target exhaust temperature, the range screening unit first screens out all candidate ranges whose upper and lower limits contain this target value from multiple operating ranges preset in the system. This operation not only reduces the subsequent calculation scale but also provides boundary conditions for centralized evaluation, improving the system response speed. The formation of the candidate ranges is based on the heat pump structure, the refrigeration curve of the compressor, and historical operation data, and has stable physical boundary properties.

[0190] After the candidate ranges are determined, the range evaluation unit performs weighted scoring on each range according to multiple evaluation dimensions and calculates the comprehensive score of each range. Among them, the evaluation factors include three core parameters: the average thermal efficiency of this range during historical operation, the current heat demand level of the battery, and the current environmental temperature. The thermal efficiency reflects the heat that can be output per unit input power in this range, the demand level reflects whether the heat source output capacity matches the current load, and the environmental temperature adaptability reflects the energy efficiency stability of this range under the current external conditions. The multi-factor comprehensive scoring mechanism effectively avoids the system judging the range solely based on a single thermal efficiency and improves the adaptability of actual operation.

[0191] Preferably, the output unit finally selects the operating range with the highest comprehensive score from the scoring results as the optimal operating range, and extracts the corresponding frequency and operating parameters as the heat source adjustment parameters and outputs them to the control logic layer. Through this selection mechanism, the heat pump unit can always operate in a state that takes into account both responsiveness and efficiency, significantly reducing the high-energy consumption operation time and improving the overall control quality of the system.

[0192] In a preferred embodiment of the present invention, the heating trend modeling unit includes:

[0193] A data integration unit, configured to extract temperature sampling values at multiple different times according to the battery pack preheating data, and construct a temperature sequence data set in chronological order;

[0194] A local trend analysis unit, configured to divide the temperature sequence data set into several continuous time periods, and determine a local upward trend or a platform trend according to the temperature change rate within each time period, forming trend data;

[0195] A global trend construction unit, configured to combine the local trends of each continuous time period according to the trend data to construct a temperature change trend curve.

[0196] In the embodiment of the present invention, in order to enhance the analysis ability of the battery temperature change trend, the heating trend modeling unit realizes the construction of the heat rise trajectory through a multi-stage data processing process, so as to provide data support for heating prediction and energy scheduling.

[0197] The data integration unit first extracts temperature sampling values at multiple different times according to the battery pack preheating data, and constructs a temperature sequence data set in chronological order. This sequence not only reflects the heat rise speed, but also can capture minute changes such as temperature anomalies and fluctuation inflection points, and is the basic data source for trend modeling.

[0198] Subsequently, the local trend analysis unit divides the sequence into multiple continuous time periods, and calculates the temperature change rate within each time period to determine whether it shows an upward trend, a platform trend or a downward trend. This stage not only realizes the quantitative analysis of the heat rate, but also improves the adaptability of the model to complex curves through the division of trend labels, avoiding error accumulation or overfitting in the overall modeling.

[0199] The global trend construction unit then combines the local trends of each time period to form a complete temperature change trend curve. This trend curve is output as a dynamic feature, which can be updated in real time, adapt to the change of the temperature sampling interval, and become an important basic information for predicting the remaining heating time and the system dynamic control strategy.

[0200] Through the above multi-stage analysis process of data acquisition, local recognition, and overall integration, the heating trend modeling unit provides the system with a complete, accurate, and continuously updated expression of temperature changes, with good scalability and system compatibility, and can significantly improve the prediction accuracy and regulation response effect during actual operation.

[0201] Among them, the data integration unit, as the basic component of heating trend modeling, its main responsibility is to summarize, organize, and structure the original temperature data from the battery pack temperature monitoring system, providing an available time series data set for subsequent trend analysis.

[0202] Specifically, this unit receives the temperature sampling values from the temperature monitoring sub-module and arranges them in chronological order. The sampling data usually includes the temperature readings of multiple monitoring points at specific timestamps. To meet the needs of trend analysis, the data integration unit will select one or more representative sampling points as the basis for trend reference, such as selecting the location with the lowest temperature inside the battery pack, the location with the most significant temperature change, or calculating the representative temperature value through a weighted method.

[0203] In actual engineering implementation, this unit can be designed as a circular buffer or queue structure to store the continuous temperature values and corresponding timestamps within a recent period of time. The system can set a fixed time window (such as the most recent 5 minutes or 30 sets of sampling values) and continuously update the data content to ensure that the analysis is based on the latest thermal state.

[0204] In addition, the data integration unit can have a preliminary data quality screening function, such as removing error readings, filling in missing values, smoothing extreme fluctuations, etc., to improve the accuracy and stability of subsequent trend analysis. The output result is a set of ordered, continuous, and non-missing temperature-time pair data sets.

[0205] Among them, the local trend analysis unit is responsible for segmenting the temperature time series provided by the data integration unit to identify the phased change characteristics during the heating process. Its goal is to capture the local change trend of the battery pack temperature during the preheating process, such as continuous temperature rise, plateau, or brief decline, etc., and convert it into structured trend information.

[0206] This unit usually segments the temperature-time series by time or quantity (for example, every 5 sets of data as an analysis segment), and analyzes the temperature change direction and rate within each segment. If the temperature continuously rises and fluctuates little within a certain segment, it is marked as an "upward trend segment"; if the temperature fluctuates little and remains stable overall, it is marked as a "plateau trend segment"; if the temperature drops, it is marked as a "downward trend segment" or an "abnormal segment".

[0207] This analysis process does not rely on complex algorithm models, but makes judgments based on simple trend recognition rules, which is convenient for implementation in an embedded controller. The rising and falling rates can be judged by setting thresholds to ensure that the recognized trends have practical engineering significance.

[0208] After the recognition is completed, the system encapsulates the trend result of each segment into trend label data, including trend type, duration, temperature change range, etc., for the global trend construction unit to conduct summary analysis. The design of this module improves the response ability of the entire system to non-linear heating behavior, avoids misjudging the temperature change process, and is especially suitable for complex heating scenarios with battery thermal inertia or external disturbance effects.

[0209] Among them, the role of the global trend construction unit is to integrate multiple local trend segments into a complete temperature change trend curve that can describe the heating process of the entire battery pack, so as to provide reliable trend reference information for the prediction model and control strategy.

[0210] This unit receives multiple trend label data from the local trend analysis unit and splices and fuses them in chronological order. During the fusion process, the system can judge the continuity of adjacent trend segments. If a short-term platform trend is sandwiched between two rising trends, the system can fuse it to form a more representative overall rising trend segment. Similarly, if there is an abnormal trend segment (such as a short-term temperature drop), the system can mark it as an area that needs attention to judge whether there is an abnormal heat flow distribution or sensor error.

[0211] The constructed global trend curve is not a function in the mathematical sense, but a structured data chain composed of several trend segments, which can clearly describe the trend direction, temperature rise amplitude, duration, and fluctuation state in the current heating process. This data chain can be referenced by the temperature feedback module and the heat source scheduling module as an important basis for predicting whether the preset temperature threshold can be reached within the expected time.

[0212] In addition, the global trend construction unit can also set a trend update mechanism, that is, whenever new sampling data enters the integration unit and the local trend recognition is completed, the system automatically refreshes the global trend curve to make it have the ability of dynamic update, ensuring that the system control logic always makes judgments and decisions based on the latest thermal state.

[0213] The above is the preferred implementation manner of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle described in the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. An integrated vehicle thermal management system for commercial vehicles with a heat pump type, characterized in that, The system includes: An environment acquisition module, configured to obtain ambient temperature data and a vehicle start signal, and generate start condition data; A temperature judgment module, configured to extract battery pack temperature data according to the start condition data, and judge whether the battery pack is in a low temperature state. If so, generate first heat source request data; A heat source scheduling module, configured to control the operation of a heat pump unit to generate a first heat energy flow according to the first heat source request data; A battery pack heat exchange module, configured to heat the battery pack through a heat exchange structure according to the first heat energy flow, and simultaneously collect temperature change data during the preheating process to generate battery pack preheating data; A temperature feedback module, configured to judge whether a preset start threshold is reached according to the battery pack preheating data. If not, send an adjustment signal to the heat source scheduling module to adjust the first heat energy flow and continue to heat the battery pack; A heat flow switching module, configured to control the heat source scheduling module to switch the first heat energy flow to a cabin heating path to generate a second heat energy flow after the battery pack temperature reaches the preset start threshold; An energy distribution module, configured to obtain vehicle driving state data, and dynamically distribute the second heat energy flow according to the vehicle driving state data, and send it to the cockpit and the electric drive cooling circuit respectively, and complete the heat energy distribution of the vehicle thermal management system by adjusting the proportional valve; The heat source scheduling module includes: A heat quantity control sub-module, configured to extract ambient temperature data and battery pack temperature data according to the first heat source request data, determine the target operating frequency and target exhaust temperature of the heat pump unit, and generate heat source adjustment parameters; An operation instruction generation sub-module, configured to send an operation control instruction to the heat pump unit according to the heat source adjustment parameters, so that the heat pump unit generates a first heat energy flow according to the target operating frequency; A heat quantity feedback sub-module, configured to adjust the operation control instruction in real time according to the adjustment signal to generate an adjusted first heat energy flow; The heat quantity control sub-module includes: An environment evaluation unit, configured to determine whether the current environment belongs to an alpine region, a medium temperature region or a warm region according to the ambient temperature data in the first heat source request data, and generate a corresponding temperature region label; A load mapping unit, configured to look up a table to determine the target operating frequency and target exhaust temperature according to the temperature region label and the current temperature data of the battery pack, wherein the table lookup operation is based on a preset parameter mapping table; An operation region selection unit, configured to match the operation region of the heat pump unit according to the target exhaust temperature, and preferentially select the operation region with the optimal thermal efficiency to generate heat source adjustment parameters; The operation region selection unit includes: A region screening unit, configured to screen candidate regions that meet the upper and lower limits of the target exhaust temperature from a plurality of preset operation regions according to the target exhaust temperature; A region evaluation unit, configured to perform a weighted evaluation on the historical energy efficiency performance of each candidate region, the current heat demand level of the battery, and the ambient temperature of the vehicle where the vehicle is located, and calculate a comprehensive score; An optimal selection output unit, configured to select the operation region with the highest comprehensive score from the candidate regions as the optimal operation region, and extract the corresponding frequency and operation parameters to generate heat source adjustment parameters.

2. The integrated vehicle thermal management system with heat pump for commercial vehicle according to claim 1, characterized in that, The battery pack heat exchange module includes: A heat exchange path selection sub-module, which is used to determine the enabled flow channels in the heat exchange path according to the heat amount of the first heat energy flow and the temperature distribution data at different positions of the battery pack; A bypass control sub-module, which is used to open the bypass channel to partially guide the first heat energy flow around the battery pack area in case of heat surplus or local overheating, so as to generate an optimized heat exchange path; A temperature monitoring sub-module, which is used to collect the temperature change data at different positions of the battery pack during the preheating process and generate the battery pack preheating data.

3. The integrated vehicle thermal management system with heat pump for commercial vehicle according to claim 2, wherein, The temperature feedback module includes: A temperature change rate calculation sub-module, which is used to calculate the temperature change rate of the battery pack according to the battery pack preheating data to obtain the temperature rising trend data; A threshold prediction sub-module, which is used to predict the remaining time required to reach the preset start threshold according to the temperature rising trend data and generate a heat source adjustment advance signal; A control instruction update sub-module, which is used to send the heat source adjustment advance signal to the heat source scheduling module to optimize the generation strategy of the first heat energy flow in advance.

4. The integrated vehicle thermal management system with heat pump for commercial vehicle according to claim 3, characterized in that, The energy distribution module includes: A priority evaluation sub-module, which is used to calculate the corresponding heat energy demand value according to the vehicle driving state data, the current temperature data of the cockpit and the temperature data of the electric drive system, and generate the heat distribution priority data; A proportion decision sub-module, which is used to determine the distribution proportion of the second heat energy flow between the cockpit and the electric drive cooling circuit according to the heat distribution priority data and generate a proportion control parameter; An execution feedback sub-module, which is used to control the proportional valve to adjust the heat flow according to the proportion control parameter, and monitor the heat flow distribution effect of the two circuits in real time. If there is a deviation, an adjustment feedback signal is output to correct the proportion control parameter.

5. The integrated vehicle thermal management system with heat pump for commercial vehicle according to claim 3, wherein, The threshold prediction sub-module includes: A heating trend modeling unit, which is used to construct a temperature change trend curve according to the multi-period temperature change data in the battery pack preheating data; A threshold arrival time estimation unit, which is used to predict the time required for the battery pack temperature to reach the preset start threshold according to the temperature change trend curve to obtain the predicted remaining heating time; An early warning judgment unit, which is used to compare the predicted remaining heating time with the expected vehicle start time of the vehicle. If it is insufficient, a heat source adjustment advance signal is generated.

6. The integrated vehicle thermal management system with heat pump for commercial vehicles according to claim 4, characterized in that, The priority evaluation sub-module includes: A state recognition unit, which is used to judge whether the vehicle is currently in the stage of passengers getting on and off, high-speed driving stage or idling and parking stage according to the vehicle driving state data, and generate the corresponding operation state label; A heat energy demand calculation unit, which is used to calculate the heat energy demand values of the cockpit and the electric drive cooling circuit respectively according to the operation state label, the current temperature data of the cockpit and the temperature data of the electric drive system; A priority generation unit, which is used to compare the heat energy demand value with the preset state threshold range respectively according to the heat energy demand value and the corresponding operation state label, select the target with a higher demand value in the cockpit and the electric drive cooling circuit as the priority distribution object, and generate the heat distribution priority data. If the difference between the two demand values is within the preset difference range, the priority order is determined and adjusted based on the preset weight factor.

7. The integrated vehicle thermal management system with heat pump for commercial vehicle according to claim 5, characterized in that The heating trend modeling unit includes: A data integration unit, configured to extract temperature sampling values at multiple different moments according to the battery pack preheating data, and construct a temperature sequence data set in chronological order; A local trend analysis unit, configured to divide the temperature sequence data set into several continuous time periods, and determine a local upward trend or a platform trend according to the temperature change rate in each time period, so as to form trend data; A global trend construction unit, configured to combine the local trends of the continuous time periods according to the trend data, and construct a temperature change trend curve.

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