Energy-saving-based power battery thermal management optimization test method and system

Abstract

The invention discloses an energy-saving-based power battery thermal management optimization test method and system, and relates to the field of vehicle battery thermal management, and the method comprises the steps: constructing a power battery thermal management strategy optimization integrated test system which comprises an upper computer, a controlled thermal management execution device, an environment simulation device and a battery test device; setting a quantifiable thermal performance target for the to-be-tested battery system according to the target thermal management working condition of the power battery; based on the thermal performance target, iterative optimization is carried out on the output power of the thermal management component in the integrated test system, and the optimal thermal management component power meeting the thermal performance requirement is determined; performing iterative optimization on the target temperature of the thermal management medium according to the optimal power of the thermal management component, and determining an optimal medium temperature set point meeting the thermal performance requirement; and the optimal heat management component power and the optimal medium temperature set point are matched to the corresponding power battery system and the heat management control strategy thereof, so that the energy-saving performance and the reliability of the heat management control strategy are improved.

Description

Technical Field

[0001] This invention relates to the field of vehicle battery thermal management, and in particular to an energy-saving power battery thermal management optimization test method, an energy-saving power battery thermal management optimization test system, electronic equipment, and storage medium. Background Technology

[0002] With the rapid development of new energy vehicles, the thermal management (BTMS) of power battery systems plays a decisive role in ensuring their performance, safety, and lifespan. In low-temperature environments, batteries require rapid heating to restore their discharge capacity; under high-rate conditions such as fast charging, effective cooling is necessary to prevent thermal runaway. Currently, the selection and operating parameter settings of thermal management systems (such as heat pumps, PTC heaters, and water chillers) mainly rely on theoretical calculations, simulations, or engineering experience.

[0003] Existing methods have significant shortcomings: First, component selection (such as heat pump power) is often based on worst-case scenario estimates with added safety margins, which can easily lead to over-design of power, resulting in increased equipment costs, energy consumption, and wasted space. Second, even if a component with a certain power is selected, its operating parameters (such as the target temperature of the cooling medium) are usually set empirically, failing to precisely match the thermal characteristics of the specific battery system, leading to low operating efficiency. All of this contradicts the design goals of energy conservation and lightweighting for electric vehicles.

[0004] Therefore, there is an urgent need for a method that can optimize the selection of thermal management components and operation control strategies for specific battery systems through systematic experiments, so as to achieve end-to-end energy efficiency improvement from hardware matching to software control. Summary of the Invention

[0005] In view of this, the purpose of this invention is to provide an energy-saving power battery thermal management optimization test method, system, electronic device and storage medium, which aims to address the problems of existing power battery thermal management system designs relying on experience and having suboptimal energy efficiency.

[0006] This invention provides the following solution:

[0007] According to one aspect of this application, a method for optimizing the thermal management of power batteries based on energy saving is provided, comprising the following steps:

[0008] An integrated testing system for optimizing thermal management strategies of power batteries is constructed. The system includes a host computer, and a constant power water chiller, a battery charging and discharging device, an environmental chamber, and a battery system under test, which are respectively connected to the host computer via CAN or Ethernet communication bus.

[0009] For the target thermal management conditions of the power battery, a quantifiable thermal performance target is set for the battery system under test;

[0010] The first stage of thermal management component power optimization is performed as follows: The battery system under test is placed in the environmental chamber until the core temperature is uniformly and stably stabilized to the preset initial temperature. The initial thermal management power and the initial target medium temperature are set. The host computer controls the constant power water chiller to run in constant power mode until the medium temperature reaches the target, and then switches to constant temperature mode. Multiple iterative tests are performed on the battery system under test to obtain multiple sets of thermal management power values ​​and their corresponding actual thermal performance data. Based on the quantifiable thermal performance target, the minimum thermal management power value that meets the target is selected as the optimal thermal management component power.

[0011] Based on the optimal thermal management component power, the second stage of operating medium temperature optimization is performed: the output power of the constant power water chiller is fixed, the medium target temperature is adjusted based on the initial medium target temperature, and the host computer controls the constant power water chiller to perform multiple iterative tests on the battery system under test in the same constant power to constant temperature mode, to obtain multiple sets of medium temperature values ​​and their corresponding actual thermal performance data under fixed power, and to calculate the optimal medium temperature setpoint that meets the target based on the quantifiable thermal performance target.

[0012] Output the optimal thermal management strategy for the battery system under test: match the rated power thermal management component to the battery system under test, and set the target medium temperature under the target thermal management condition as the optimal medium temperature setpoint in the battery management system of the battery system under test.

[0013] Furthermore, the target thermal management conditions include the low-temperature heating condition of the power battery and the fast-charging cooling condition. When it is the fast-charging cooling condition, the thermal management power is replaced with the cooling power, the target medium temperature is replaced with the target cooling medium temperature, and steps S3-S5 are repeated to complete the optimization of the thermal management strategy for the fast-charging cooling condition.

[0014] Furthermore, the thermal management power adjustment methods for multiple iterations of testing include:

[0015] By comparing the actual thermal performance data of a single test with the quantifiable thermal performance target, if the actual thermal performance data is lower than the target, the thermal management power is increased for the next test; if the actual thermal performance data meets or exceeds the target, the thermal management power is decreased for the next test.

[0016] Based on the existing product model series of thermal management components, discretized thermal management power selection and iterative testing are performed.

[0017] Furthermore, the discretized selection and iterative testing of thermal management power includes: the optimal thermal management component power is the minimum rated power value among existing product models that meets the quantifiable thermal performance target.

[0018] Furthermore, the adjustment method for the target medium temperature is as follows: starting from the initial target medium temperature, the target medium temperature is set to decrease sequentially according to a preset fixed temperature step size, and iterative tests are carried out.

[0019] Furthermore, the method for calculating and determining the optimal medium temperature setpoint is as follows:

[0020] When the actual thermal performance data at a certain medium temperature is lower than the quantifiable thermal performance target, the iterative test is stopped. The theoretical medium temperature value that meets the target is calculated by linear interpolation between the medium temperature and the previous test medium temperature. The theoretical medium temperature value is corrected by combining the control accuracy and performance margin of the power battery thermal management system to obtain the final optimal medium temperature setpoint.

[0021] Furthermore, it includes: a single test procedure in which the constant power mode is operated until the medium temperature reaches the standard, and then the constant temperature mode is switched, specifically as follows:

[0022] A1. The host computer controls the constant power water chiller to operate at a constant power at the currently set thermal management power to heat or cool the coolant and the battery system under test.

[0023] A2. When the coolant outlet temperature reaches the currently set target temperature of the medium, the constant power water chiller automatically switches to a constant temperature mode with the target temperature of the medium as the set value and continues to operate.

[0024] A3. Monitor the core temperature of the battery system under test in real time. Stop the test when the core temperature reaches the preset target temperature and record the total test time.

[0025] A4. Calculate the actual thermal performance data of this test based on the total test duration.

[0026] Furthermore, including

[0027] During the iterative testing process, the host computer synchronously collects test data from the entire system, including: power and temperature data of the constant power water chiller, voltage and temperature data of the battery management system of the battery system under test, and current and voltage data of the battery charging and discharging equipment; the host computer calculates the actual thermal performance data based on the aforementioned test data.

[0028] Furthermore, including:

[0029] The iterative test is an automated iterative test: the host computer has a built-in iterative control module. This module automatically adjusts the thermal management power or the target temperature of the medium for the next test based on the comparison between the actual thermal performance data of a single test and the quantifiable thermal performance target, and automatically starts the next iterative test.

[0030] According to two aspects of this application, an energy-saving power battery thermal management optimization test system is provided, comprising:

[0031] The system includes a host computer, a controlled thermal management execution module, an environmental simulation module, a battery system under test, and a battery testing module.

[0032] The controlled thermal management execution module has cooling and heating functions, and can operate at constant power according to a set power value or at constant temperature according to a set medium temperature value, and is used to provide thermal management services for heating or cooling of the battery system under test.

[0033] The battery testing module is used to apply a charge and discharge load to the battery system under test to simulate the actual driving and fast charging conditions of the power battery.

[0034] The environmental simulation module is used to provide and precisely control the initial ambient temperature required for testing, so that the core temperature of the battery system under test is uniformly and stably stabilized to the preset initial temperature.

[0035] The battery system under test includes a battery module or battery pack, and its internally integrated thermal management channels.

[0036] The host computer is connected to the constant power water chiller, battery charging and discharging equipment, environmental chamber and battery system under test via CAN or Ethernet communication bus, respectively. It serves as the system control center and is used to set test parameters, control the start and stop of the test process, synchronously collect test data of the whole system, calculate actual thermal performance data and perform two-stage iterative optimization.

[0037] Furthermore, the host computer has a built-in data processing module and an iterative control module; the data processing module is used to calculate the actual thermal performance data based on the collected full system test data and compare and analyze it with the preset quantifiable thermal performance target; the iterative control module is used to automatically adjust the thermal management power or medium target temperature for the next test based on the comparison and analysis results, so as to realize automated iterative testing.

[0038] According to three aspects of this application, an electronic device is provided, comprising: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0039] The memory stores a computer program, which, when executed by the processor, causes the processor to perform steps of an energy-saving power battery thermal management optimization test method.

[0040] According to four aspects of this application, a computer-readable storage medium is provided that stores a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of an energy-saving power battery thermal management optimization test method.

[0041] Compared with the prior art, the present invention has the following advantages:

[0042] This application determines the power of the most economical thermal management component that meets the performance requirements through experiments (first stage: power optimization), and then further optimizes the optimal medium temperature setpoint for the component during operation (second stage: temperature optimization), thereby outputting a complete thermal management hardware selection and control strategy scheme that takes into account both performance and energy efficiency.

[0043] This application integrates equipment for all aspects of thermal management, battery condition simulation, environmental control, and data acquisition, providing a dedicated and standardized hardware foundation for optimization testing. This changes the current situation where existing technology equipment is fragmented and cannot work in tandem, ensuring the standardization of the testing process.

[0044] This application uses a host computer as the control center to synchronously collect power / temperature data of the water chiller, voltage / temperature data of the battery management system, and current / voltage data of the charging and discharging equipment, avoiding time deviation and data error caused by manual collection, and providing accurate data support for optimization results;

[0045] This application addresses the over-design problem from the hardware selection stage through power optimization and taps into energy-saving potential from the software operation and control level through temperature optimization. The two stages are carried out sequentially and rely on each other, realizing full-link energy efficiency optimization of the thermal management system from hardware to software, which is different from the single-dimensional adjustment of existing technologies.

[0046] This application adopts a constant power water chiller operating mode that first maintains constant power and then constant temperature, which is highly consistent with the actual working conditions of the power battery thermal management system (in actual applications, the rated power is used to quickly heat / cool first, and then the medium temperature is maintained at a constant temperature). This allows the test process to truly reflect the actual thermal characteristics of the battery system, avoids the disconnect between theoretical testing and actual application, and ensures the effectiveness of the optimization strategy in the actual operation of the vehicle.

[0047] This application utilizes a two-stage experimental framework of power optimization and temperature optimization to explore energy-saving potential from two dimensions: the source of hardware selection and the operational control strategy, thereby achieving system-level energy efficiency optimization. Attached Figure Description

[0048] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0049] Figure 1 This is a flowchart of an energy-saving power battery thermal management optimization test method provided by one or more embodiments of the present invention.

[0050] Figure 2 This is a framework diagram of an energy-saving power battery thermal management optimization test system provided by one or more embodiments of the present invention.

[0051] Figure 3 This is a schematic diagram of the optimization test system provided in a specific embodiment of the present invention.

[0052] Figure 4 This is a schematic diagram of the iterative process of an optimization test system provided in a specific embodiment of the present invention.

[0053] Figure 5 This is an example diagram showing the results of the iterative process of the optimization test system provided in a specific embodiment of the present invention.

[0054] Figure 6 This is a schematic diagram of the iterative process for optimizing the upper limit temperature of the cooling medium according to a specific embodiment of the present invention.

[0055] Figure 7 This is an example diagram showing the result of the iterative process for optimizing the upper limit temperature of the cooling medium, provided in a specific embodiment of the present invention.

[0056] Figure 8 This is a block diagram of an electronic device structure provided by one or more embodiments of the present invention, which is a method for optimizing the thermal management of power batteries based on energy saving. Detailed Implementation

[0057] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0058] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to limit the application. The singular forms “a,” “said,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms, and “multiple” generally includes at least two unless the context clearly indicates otherwise.

[0059] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0060] It should be understood that although the terms first, second, third, etc., may be used in the embodiments of this application, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, first may also be referred to as second without departing from the scope of the embodiments of this application, and similarly, second may also be referred to as first.

[0061] Depending on the context, the words “if” or “suppose” as used here can be interpreted as “when” or “in response to determination” or “in response to detection.” Similarly, depending on the context, the phrases “if determination” or “if detection (of the stated condition or event)” can be interpreted as “when determination” or “in response to determination” or “when detection (of the stated condition or event)” or “in response to detection (of the stated condition or event).”

[0062] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that an article or device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such an article or device. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the article or device that includes said element.

[0063] It should be noted that any symbols and / or numbers present in the specification that are not marked in the accompanying drawings are not reference numerals.

[0064] Figure 1 This is a flowchart of an energy-saving power battery thermal management optimization test method provided by one or more embodiments of the present invention.

[0065] like Figure 1 As shown, it includes the following steps:

[0066] Step S1: Construct an integrated test system for optimizing thermal management strategies of power batteries. The system includes a host computer, and a constant power water chiller, a battery charging and discharging device, an environmental chamber, and a battery system under test, which are respectively connected to the host computer via CAN or Ethernet communication bus.

[0067] Step S2: Set quantifiable thermal performance targets for the battery system under test based on the target thermal management conditions of the power battery.

[0068] Step S3, perform the first stage of thermal management component power optimization: place the battery system under test in the environmental chamber until the core temperature is uniformly and stably stabilized to the preset initial temperature, set the initial thermal management power and the initial medium target temperature, and control the constant power water chiller to run in constant power mode until the medium temperature reaches the target, and then switch to constant temperature mode to perform multiple iterative tests on the battery system under test, obtain multiple sets of thermal management power values ​​and their corresponding actual thermal performance data, and select the minimum thermal management power value that meets the target as the optimal thermal management component power based on the quantifiable thermal performance target;

[0069] Step S4: Based on the optimal thermal management component power, perform the second stage of operating medium temperature optimization: fix the output power of the constant power water chiller, adjust the medium target temperature based on the initial medium target temperature, and control the constant power water chiller to perform multiple iterative tests on the battery system under test in the same constant power to constant temperature mode through the host computer, obtain multiple sets of medium temperature values ​​and their corresponding actual thermal performance data under fixed power, and calculate the optimal medium temperature set point that meets the target based on the quantifiable thermal performance target.

[0070] Step S5: Output the optimal thermal management strategy for the battery system under test: match the rated power thermal management component to the battery system under test, and set the target medium temperature under the target thermal management condition to the optimal medium temperature setpoint in the battery management system of the battery system under test.

[0071] Furthermore, the target thermal management conditions include the low-temperature heating condition of the power battery and the fast-charging cooling condition. When it is the fast-charging cooling condition, the thermal management power is replaced with the cooling power, the target medium temperature is replaced with the target cooling medium temperature, and steps S3-S5 are repeated to complete the optimization of the thermal management strategy for the fast-charging cooling condition.

[0072] Furthermore, the thermal management power adjustment methods for multiple iterations of testing include:

[0073] By comparing the actual thermal performance data of a single test with the quantifiable thermal performance target, if the actual thermal performance data is lower than the target, the thermal management power is increased for the next test; if the actual thermal performance data meets or exceeds the target, the thermal management power is decreased for the next test.

[0074] Based on the existing product model series of thermal management components, discretized thermal management power selection and iterative testing are performed.

[0075] Furthermore, the discretized selection and iterative testing of thermal management power includes: the optimal thermal management component power is the minimum rated power value among existing product models that meets the quantifiable thermal performance target.

[0076] Furthermore, the adjustment method for the target medium temperature is as follows: starting from the initial target medium temperature, the target medium temperature is set to decrease sequentially according to a preset fixed temperature step size, and iterative tests are carried out.

[0077] Furthermore, the method for calculating and determining the optimal medium temperature setpoint is as follows:

[0078] When the actual thermal performance data at a certain medium temperature is lower than the quantifiable thermal performance target, the iterative test is stopped. The theoretical medium temperature value that meets the target is calculated by linear interpolation between the medium temperature and the previous test medium temperature. The theoretical medium temperature value is corrected by combining the control accuracy and performance margin of the power battery thermal management system to obtain the final optimal medium temperature setpoint.

[0079] Furthermore, it includes: a single test procedure in which the constant power mode is operated until the medium temperature reaches the standard, and then the constant temperature mode is switched, specifically as follows:

[0080] A1. The host computer controls the constant power water chiller to operate at a constant power at the currently set thermal management power to heat or cool the coolant and the battery system under test.

[0081] A2. When the coolant outlet temperature reaches the currently set target temperature of the medium, the constant power water chiller automatically switches to a constant temperature mode with the target temperature of the medium as the set value and continues to operate.

[0082] A3. Monitor the core temperature of the battery system under test in real time. Stop the test when the core temperature reaches the preset target temperature and record the total test time.

[0083] A4. Calculate the actual thermal performance data of this test based on the total test duration.

[0084] Furthermore, including

[0085] During the iterative testing process, the host computer synchronously collects test data from the entire system, including: power and temperature data of the constant power water chiller, voltage and temperature data of the battery management system of the battery system under test, and current and voltage data of the battery charging and discharging equipment; the host computer calculates the actual thermal performance data based on the aforementioned test data.

[0086] Furthermore, including:

[0087] The iterative test is an automated iterative test: the host computer has a built-in iterative control module. This module automatically adjusts the thermal management power or the target temperature of the medium for the next test based on the comparison between the actual thermal performance data of a single test and the quantifiable thermal performance target, and automatically starts the next iterative test.

[0088] Specifically, by using a host computer to uniformly control the constant power water chiller, battery charging and discharging equipment, environmental chamber, and battery system under test, multi-device collaboration, bus communication, and unified data acquisition are achieved, which greatly improves the consistency, reproducibility, and testing efficiency of thermal management strategy optimization tests and avoids errors caused by manual operation of multiple devices.

[0089] Quantifiable and comparable thermal performance targets are set for target operating conditions such as low-temperature heating and fast-charging cooling, so that the optimization process does not rely on subjective experience, and the test results are objective, uniform and quantifiable, which facilitates horizontal comparison between different operating conditions and different battery systems.

[0090] Phase 1: First, determine the minimum power of the thermal management components that meet the thermal performance targets, so as to achieve energy saving and consumption reduction, optimal component cost, and precise power matching;

[0091] The second stage involves fixing the optimal power and then optimizing the target temperature of the medium to avoid power and temperature coupling interference, which makes the optimization process converge faster, the results more stable, and the computational load smaller.

[0092] Through a two-stage experimental framework of power optimization and temperature optimization, energy-saving potential was explored from two dimensions: the source of hardware selection and the operational control strategy, achieving system-level energy efficiency optimization. End-to-end engineering support: the output of the first stage directly guides the selection of components such as heat pumps and water chillers; the output of the second stage can be directly used as core parameters for battery thermal management control software, providing accurate data support for control strategy development, thus realizing a closed loop from design to control.

[0093] Precise matching avoids waste: Through experiments, optimization is directly targeted at specific battery systems. The resulting strategy is highly matched with the thermal characteristics of the system, fundamentally avoiding power excess and energy waste caused by relying on general experience or conservative estimates, and reducing system cost and space occupation.

[0094] The method is versatile and highly automated: It is applicable to various thermal management scenarios such as heating and cooling, and through integrated control by a host computer, the testing process is automated and the data synchronization is accurate, which improves the optimization efficiency and the reliability and repeatability of the results.

[0095] Figure 2 This is a framework diagram of an energy-saving power battery thermal management optimization test system provided by one or more embodiments of the present invention.

[0096] like Figure 2 As shown, it includes:

[0097] A constant power water chiller has cooling and heating functions. It can operate at a constant power value or at a constant temperature value according to a set medium temperature value. It is used to provide thermal management services for heating or cooling of the battery system under test.

[0098] A battery charging and discharging device is used to apply a charging and discharging load to the battery system under test to simulate the actual driving and fast charging electrical conditions of the power battery.

[0099] An environmental chamber is used to provide and precisely control the initial ambient temperature required for testing, so that the core temperature of the battery system under test is uniformly and stably stabilized to the preset initial temperature.

[0100] The battery system under test includes a battery module or battery pack, and its internally integrated thermal management channels;

[0101] The host computer is connected to the constant power water chiller, battery charging and discharging equipment, environmental chamber and battery system under test via CAN or Ethernet communication bus, respectively. It serves as the system control center and is used to set test parameters, control the start and stop of the test process, synchronously collect test data of the whole system, calculate actual thermal performance data and perform two-stage iterative optimization.

[0102] Furthermore, the host computer has a built-in data processing module and an iterative control module; the data processing module is used to calculate the actual thermal performance data based on the collected full system test data and compare and analyze it with the preset quantifiable thermal performance target; the iterative control module is used to automatically adjust the thermal management power or medium target temperature for the next test based on the comparison and analysis results, so as to realize automated iterative testing.

[0103] Figure 3 This is a schematic diagram of the optimization test system provided in a specific embodiment of the present invention.

[0104] like Figure 3 As shown, unified coordination, control, and data acquisition are performed through a host computer:

[0105] Constant power water chiller: It has cooling and heating functions and can output constant power precisely according to the set power (kW) or operate at a constant temperature according to the set medium temperature (°C).

[0106] Battery charging and discharging equipment: used to apply charging and discharging loads to the battery system under test, simulating actual driving, fast charging and other electrical operating conditions.

[0107] Environmental chamber: Used to provide and control the initial ambient temperature required for testing, ensuring that the battery system starts testing from a stable and uniform temperature field.

[0108] Battery system under test: includes battery modules or packs, as well as their internal thermal management channels (liquid cooling plates, pipes, etc.).

[0109] Host computer: As the control center, it connects to all the above devices via a communication bus (such as CAN or Ethernet). Its responsibilities include: setting test parameters, controlling the test process (such as starting and stopping the water chiller and charging / discharging equipment), and synchronously collecting power and temperature data from the water chiller, voltage / temperature data from the battery management system, and current / voltage data from the charging / discharging equipment.

[0110] Figure 4 This is a schematic diagram of the iterative process of an optimization test system provided in a specific embodiment of the present invention.

[0111] like Figure 4 , 5 As shown, initialization: The battery system is placed in an environmental chamber to allow its core temperature to stabilize uniformly to the initial temperature. (e.g., -20℃). Set clear performance targets, for example: from Heat to target temperature Average heating rate (e.g., 0°C) Not less than 1 ℃ / min. Provide an initial estimate of heating power. and upper limit of medium temperature . and The values ​​can be derived from previous simulation inputs.

[0112] Single test:

[0113] a. The host computer controls the constant power water chiller, first at constant power. It operates, heating the coolant and battery system.

[0114] b. When the coolant outlet temperature reaches At that time, the water chiller automatically switches to a water-cooled mode. The target is a constant temperature mode.

[0115] c. Monitor the battery system temperature in real time, and when it reaches... Stop heating when the time is right and record the total heating time. .

[0116] d. Calculate the actual average heating rate of this test. .

[0117] Iteration and optimization:

[0118] contrast and .

[0119] like < This indicates insufficient power, and the power needs to be increased for the next test (e.g., setting...). =1.1* ).

[0120] like ≥ This indicates that the current power may be sufficient or even excessive. To improve efficiency, consider reducing the power for the next test (e.g., setting...). =0.9* This was to verify whether lower power could still meet the requirements.

[0121] Engineering implementation: Power adjustment can be discretized based on the existing product model series (such as testing 2.5kW, 4.5kW, and 6.5kW heat pumps in sequence), and the results can more directly serve the selection.

[0122] Output: Through multiple iterations, a mapping data table (Map-I) is obtained for the relationship between "heating power (a) - actual heating rate (X)". Based on the actual situation, select data from the table that satisfies x ≥ The minimum power value under the conditions is used as the recommended rated power of the heat pump. This stage solves the problem of "choosing the right amount of power hardware," preventing over-design from the outset.

[0123] Figure 6 This is a schematic diagram of the iterative process for optimizing the upper limit temperature of the cooling medium according to a specific embodiment of the present invention.

[0124] like Figure 6 , 7 As shown, it includes: Objective: At a selected power of Based on the heat pump, we seek the optimal medium temperature setpoint that achieves energy savings during operation while meeting the same heating performance requirements. .

[0125] Premise: It is known that in terms of power and initial test temperature Below, the heating rate meets the standard ( ≥ ).

[0126] Fixed Power: In all subsequent tests, the output power of the water chiller remained fixed at the level determined in the first phase. .

[0127] Iterative testing:

[0128] a. with Starting from this point, we attempt to reduce the target temperature of the medium in fixed step sizes (e.g., ΔT = 5°C). = .

[0129] b. Perform the test: Control the water chiller to operate at constant power first. During operation, the medium temperature reaches Then switch to constant temperature mode, until the battery temperature reaches Record duration and calculate. .

[0130] c. Energy efficiency assessment:

[0131] like ≥ : This indicates the power Below, use a lower medium temperature. It still meets the heating requirements. This means the system can operate under milder conditions with lower energy consumption. Keep trying. = .

[0132] like < : Indicate temperature If the value is too low, performance will not meet the requirements. Therefore, iteration will stop. and The performance boundary can be obtained by interpolation between them.

[0133] Output result: Results obtained at a fixed power... The following is a data table showing the relationship between "medium temperature (b) - actual heating rate (X)" (Map-II).

[0134] Optimal strategy determination: Analyze Map-II and calculate the optimal heating rate through interpolation. The optimal medium temperature setpoint .

[0135] Final solution: Match this battery system with a rated power of The heat pump, and in its battery management system control strategy, sets the target coolant temperature in heating mode to [value missing]. This combined solution achieves optimal balance between hardware cost and operating energy consumption while ensuring heating performance.

[0136] (The same method applies to fast charging cooling conditions: the first stage is to find the optimal cooling power.) The second stage is at a fixed power. Below, the optimal medium temperature is sought. 。

[0137] Figure 8 This is a block diagram of an electronic device structure provided by one or more embodiments of the present invention, which is a method for optimizing the thermal management of power batteries based on energy saving.

[0138] like Figure 8 As shown, this application provides an electronic device, including: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0139] The memory stores a computer program, which, when executed by the processor, causes the processor to perform steps of an energy-saving power battery thermal management optimization test method.

[0140] This application also provides a computer-readable storage medium storing a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of an energy-saving power battery thermal management optimization test method.

[0141] For the sake of simplicity, the method embodiments are described as a series of actions. However, those skilled in the art should understand that the embodiments of the present invention are not limited to the described order of actions, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions involved are not necessarily essential to the embodiments of the present invention.

[0142] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of this application.

[0143] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for optimizing the thermal management of power batteries based on energy conservation, characterized in that, Includes the following steps: Step S1: Construct an integrated testing system for optimizing thermal management strategies for power batteries. The system includes a host computer, a controlled thermal management execution device, an environmental simulation device, and a battery testing device. Step S2: Set thermal performance targets for the battery system under test based on the target thermal management conditions of the power battery. Step S3: Based on the thermal performance target, the output power of the thermal management component is iteratively optimized in the integrated test system to determine the optimal thermal management component power that meets the thermal performance requirements. Step S4: Based on the power of the optimal thermal management component, iteratively optimize the target temperature of the thermal management medium to determine the optimal medium temperature setpoint that meets the thermal performance requirements. Step S5: Match the power of the optimal thermal management component with the optimal medium temperature setpoint to the corresponding power battery system and its thermal management control strategy.

2. The energy-saving power battery thermal management optimization test method according to claim 1, characterized in that, The target thermal management conditions include: low-temperature heating condition of power battery and fast charging cooling condition; When in fast charging cooling mode, the thermal management power is replaced with the cooling power, and the target medium temperature is replaced with the target cooling medium temperature. Steps S3-S5 are repeated to complete the optimization of the thermal management strategy for fast charging cooling mode.

3. The energy-saving power battery thermal management optimization test method according to claim 1, characterized in that, The thermal management power adjustment methods for the multiple iteration tests include: Compare the actual thermal performance data of a single test with the quantifiable thermal performance target. If the actual thermal performance data is lower than the target, increase the thermal management power for the next test. If the actual thermal performance data meets or exceeds the target, the thermal management power is reduced for the next test. Based on the existing product model series of thermal management components, discretized thermal management power selection and iterative testing are performed.

4. The energy-saving power battery thermal management optimization test method according to claim 1, characterized in that, include: The adjustment method for the target temperature of the medium is as follows: starting from the initial target temperature of the medium, the target temperature of the medium is set to decrease sequentially according to a preset fixed temperature step size, and iterative testing is carried out.

5. The energy-saving power battery thermal management optimization test method according to claim 1, characterized in that, include: The method for calculating and determining the optimal medium temperature setpoint is as follows: When the actual thermal performance data at a certain medium temperature is lower than the thermal performance target, the iterative test is stopped, and the theoretical medium temperature value that meets the target is calculated by linear interpolation between the medium temperature and the previous test medium temperature. By combining the control accuracy and performance margin of the power battery thermal management system, the theoretical medium temperature value is corrected to obtain the final optimal medium temperature setpoint.

6. The energy-saving power battery thermal management optimization test method according to claim 1, characterized in that, include: The single test procedure for switching to constant temperature mode after the constant power mode has reached the specified temperature is as follows: A1. The host computer controls the constant power water chiller to operate at a constant power at the currently set thermal management power to heat or cool the coolant and the battery system under test. A2. When the coolant outlet temperature reaches the currently set target temperature of the medium, the constant power water chiller automatically switches to a constant temperature mode with the target temperature of the medium as the set value and continues to operate. A3. Monitor the core temperature of the battery system under test in real time. Stop the test when the core temperature reaches the preset target temperature and record the total test time. A4. Calculate the actual thermal performance data of this test based on the total test duration.

7. The energy-saving power battery thermal management optimization test method according to claim 1, characterized in that, include: The iterative test is an automated iterative test: the host computer has a built-in iterative control module, which automatically adjusts the thermal management power or the target temperature of the medium for the next test based on the comparison between the actual thermal performance data of a single test and the thermal performance target, and automatically starts the next iterative test.

8. A power battery thermal management strategy optimization test system for implementing the method of any one of claims 1-7, characterized in that, include: The system includes a host computer, a controlled thermal management execution module, an environmental simulation module, a battery system under test, and a battery testing module. The controlled thermal management execution module has cooling and heating functions, and can operate at constant power according to a set power value or at constant temperature according to a set medium temperature value, and is used to provide thermal management services for heating or cooling of the battery system under test. The battery testing module is used to apply a charge and discharge load to the battery system under test to simulate the actual driving and fast charging conditions of the power battery. The environmental simulation module is used to provide and precisely control the initial ambient temperature required for testing, so that the core temperature of the battery system under test is uniformly and stably stabilized to the preset initial temperature. The battery system under test includes a battery module or battery pack, and its internally integrated thermal management channels. The host computer is connected to the constant power water chiller, battery charging and discharging equipment, environmental chamber and battery system under test via CAN or Ethernet communication bus, respectively. It serves as the system control center and is used to set test parameters, control the start and stop of the test process, synchronously collect test data of the whole system, calculate actual thermal performance data and perform two-stage iterative optimization.

9. An electronic device, characterized in that, include: The processor, communication interface, memory, and communication bus are connected, with the processor, communication interface, and memory communicating with each other via the communication bus. The memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of the energy-saving power battery thermal management optimization test method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, It stores a computer program that can be executed by an electronic device. When the computer program is run on the electronic device, it causes the electronic device to perform the steps of the energy-saving power battery thermal management optimization test method as described in any one of claims 1-7.

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