Method and system for testing electric quantity maintaining performance of hybrid electric vehicle in plateau environment

Abstract

The invention discloses a hybrid electric vehicle electric quantity retention performance test method and system in a plateau environment, and the method comprises the steps: obtaining environment information, the battery aging degree of a hybrid electric vehicle and the rated electric quantity of the hybrid electric vehicle, and calculating the equivalent available electric quantity of the vehicle in the plateau environment, the environment information comprises altitude and environment temperature; dividing the driving cycle of the hybrid electric vehicle into a plurality of time slices according to a certain time step, setting a battery charge state estimation model, and calculating the charge state of each time point according to the equivalent available electric quantity; setting a battery internal resistance estimation model, calculating the battery internal resistance at each time point according to the charge state, and calculating the maximum safe discharge power at each time point according to the battery internal resistance; and obtaining the real maximum discharge power at each time point, and comparing the real maximum discharge power with the corresponding maximum safe discharge power, thereby determining whether the corresponding time point and the real maximum discharge power are abnormal.

Description

Technical Field

[0001] This invention belongs to the field of hybrid electric vehicle battery retention performance testing technology, and more specifically, relates to a method and system for testing the battery retention performance of hybrid electric vehicles in high-altitude environments. Background Technology

[0002] In existing technologies, the battery capacity retention performance of hybrid electric vehicles is primarily tested in a plain environment with normal temperature and pressure. Whether it's bench testing or road cycle testing, most methods rely solely on preset power cycling curves to assess whether the battery can maintain a charge balance at a fixed initial state of charge (SOC). These methods generally assume that the battery's output power and charge / discharge efficiency are constant and independent of environmental factors (such as altitude, temperature, air pressure, and air density), failing to consider the significant impact of the unique low air pressure, low temperature, and thin air in high-altitude regions on the battery's thermal management system's heat dissipation capacity, cooling efficiency, and electrochemical reaction kinetics. Specifically, in high-altitude environments, air density is significantly reduced, making it difficult for battery heat to dissipate effectively, leading to a faster temperature rise. Current testing methods lack models that consider the constraints of heat accumulation on power decay. Simultaneously, low temperatures increase electrolyte viscosity, reduce lithium-ion diffusion rates, and intensify polarization, causing a sharp increase in battery internal resistance and a significant decrease in discharge power. However, existing testing systems typically use fixed rated internal resistance or room-temperature efficiency parameters, failing to reflect the true characteristics of SOC decay rate changes with temperature and altitude.

[0003] In summary, the existing technology lacks a unified mathematical modeling and testing method that can comprehensively consider the dual effects of altitude, temperature, and SOC on battery internal resistance and thermal power limit. This results in the test results being unable to accurately predict the vehicle's true SOC maintenance capability under complex high-altitude conditions, thus limiting the applicability and safety of hybrid power system control strategies in high-altitude areas. Summary of the Invention

[0004] To address the above technical problems, this invention proposes a method for testing the battery retention performance of hybrid vehicles in high-altitude environments, comprising: The system acquires environmental information, the battery aging rate of the hybrid electric vehicle, and the rated charge of the hybrid electric vehicle to calculate the equivalent usable charge of the vehicle in a high-altitude environment. The environmental information includes: altitude and ambient temperature. The driving cycle of a hybrid vehicle is divided into multiple time slices according to a certain time step. A battery charge state estimation model is set up, and the charge state at each time point is calculated based on the equivalent available power. Set up a battery internal resistance estimation model, and calculate the battery internal resistance at each time point based on the charge state. Then, calculate the maximum safe discharge power at each time point based on the battery internal resistance. The actual maximum discharge power at each time point is obtained and compared with the corresponding maximum safe discharge power to determine whether the corresponding time point and the actual maximum discharge power are abnormal.

[0005] Furthermore, the calculation of the vehicle's equivalent usable electricity in a high-altitude environment includes: , in, This refers to the equivalent usable electrical energy of the vehicle in a high-altitude environment. Rated power, Altitude is the primary weighting factor. Altitude For reference height, The first adjustment factor for altitude. Temperature is the first weighted factor. For ambient temperature, For reference temperature, As a weight for battery aging, The battery aging degree is calculated by dividing the number of battery charge cycles by the designed number of charge cycles. This is an adjustment factor for battery aging.

[0006] Furthermore, the battery charge state estimation model includes: , in, For the first The charge state at each point in time. For the first The charge state at each point in time. For the number of time slices, For the first Energy recovery efficiency at a given time point For the first Energy recovery power at each time point For the first Discharge power at each time point For the first Discharge efficiency at each time point For time step.

[0007] Furthermore, the battery internal resistance estimation model includes: , in, For the first Battery internal resistance at each time point For reference internal resistance, As the second weighting factor for altitude, The second adjustment factor for altitude. Temperature is the second weighting factor. For the first Battery temperature at various time points The temperature decay constant, The weights of the charge states, This is an adjustment factor for the charge state.

[0008] Furthermore, calculating the maximum safe discharge power at each time point includes: , in, For the first The maximum safe discharge power at each time point For the battery in the first No-load voltage under charge state at each time point This represents the maximum allowable drop in terminal voltage. This refers to the battery power safety limit.

[0009] Furthermore, determining whether the corresponding time point and the actual maximum discharge power are abnormal includes: if the actual maximum discharge power exceeds the maximum safe discharge power, then the corresponding time point is marked as an abnormal time point, and the corresponding actual maximum discharge power is marked as a discharge abnormality.

[0010] This invention also proposes a battery retention performance testing system for hybrid vehicles in high-altitude environments, comprising: The equivalent available power calculation module is used to obtain environmental information, the battery aging degree of the hybrid vehicle, and the rated power of the hybrid vehicle, and calculate the equivalent available power of the vehicle in a high-altitude environment. The environmental information includes: altitude and ambient temperature. The charge state calculation module is used to divide the driving cycle of the hybrid vehicle into multiple time slices according to a certain time step, set the battery charge state estimation model, and calculate the charge state at each time point based on the equivalent available power. The module for calculating the maximum safe discharge power is used to set up a battery internal resistance estimation model, calculate the battery internal resistance at each time point based on the charge state, and calculate the maximum safe discharge power at each time point based on the battery internal resistance. The anomaly detection module is used to obtain the actual maximum discharge power at each time point, compare it with the corresponding maximum safe discharge power, and thus determine whether the corresponding time point and the actual maximum discharge power are abnormal.

[0011] Furthermore, the calculation of the vehicle's equivalent usable electricity in a high-altitude environment includes: , in, This refers to the equivalent usable electrical energy of the vehicle in a high-altitude environment. Rated power, Altitude is the primary weighting factor. Altitude For reference height, The first adjustment factor for altitude. Temperature is the first weighted factor. For ambient temperature, For reference temperature, As a weight for battery aging, The battery aging degree is calculated by dividing the number of battery charge cycles by the designed number of charge cycles. This is an adjustment factor for battery aging.

[0012] Furthermore, the battery charge state estimation model includes: , in, For the first The charge state at each point in time. For the first The charge state at each point in time. For the number of time slices, For the first Energy recovery efficiency at a given time point For the first Energy recovery power at each time point For the first Discharge power at each time point For the first Discharge efficiency at each time point For time step.

[0013] Furthermore, including: , in, For the first Battery internal resistance at each time point For reference internal resistance, As the second weighting factor for altitude, The second adjustment factor for altitude. Temperature is the second weighting factor. For the first Battery temperature at various time points The temperature decay constant, The weights of the charge states, This is an adjustment factor for the charge state.

[0014] In summary, the technical solutions conceived by this invention have the following beneficial effects compared with the prior art: The technical solution of this invention enables accurate assessment of the upper limit of the actual output / recovery power of hybrid vehicle batteries under extreme environments. This allows for effective consideration of real-world operating conditions such as reduced cooling capacity due to high altitude and low air tightness, and a sharp increase in internal resistance under low temperature conditions during SOC retention performance testing. This significantly improves the authenticity and rigor of SOC retention performance testing, avoids distortion of test results due to neglecting environmental factors, and provides a scientific basis for power system calibration and control strategy optimization. Attached Figure Description

[0015] Figure 1 This is a flowchart of the method in Embodiment 1 of the present invention; Figure 2 This is a system structure diagram of Embodiment 2 of the present invention. Detailed Implementation

[0016] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0017] The method provided by this invention can be implemented in a terminal environment that may include one or more of the following components: a processor, a storage medium, and a display screen. The storage medium stores at least one instruction, which is loaded and executed by the processor to implement the method described in the following embodiments.

[0018] A processor may include one or more processing cores. The processor uses various interfaces and lines to connect various parts of the terminal, and performs various functions and processes data by running or executing instructions, programs, code sets or instruction sets stored in the storage medium, and by calling data stored in the storage medium.

[0019] Storage media can include random access memory (RAM) or read-only memory (ROM). Storage media can be used to store instructions, programs, code, code sets, or instructions.

[0020] The display screen is used to show the user interface of each application.

[0021] In addition, those skilled in the art will understand that the structure of the terminal described above does not constitute a limitation on the terminal. The terminal may include more or fewer components, or combine certain components, or have different component arrangements. For example, the terminal may also include radio frequency circuits, input units, sensors, audio circuits, power supplies, and other components, which will not be described in detail here.

[0022] Example 1 like Figure 1 As shown in the figure, this embodiment proposes a method for testing the battery retention performance of hybrid vehicles in high-altitude environments, including: Step 101: Obtain environmental information, battery aging of the hybrid vehicle, and rated power of the hybrid vehicle; calculate the equivalent usable power of the vehicle in a high-altitude environment. The environmental information includes: altitude and ambient temperature. Specifically, calculating the equivalent usable electricity of a vehicle in a high-altitude environment includes: , in, This refers to the equivalent usable electrical energy of the vehicle in a high-altitude environment. Rated power, Altitude is the primary weighting factor. Altitude For reference height, The first adjustment factor for altitude. Temperature is the first weighted factor. For ambient temperature, For reference temperature, As a weight for battery aging, The battery aging degree is calculated by dividing the number of battery charge cycles by the designed number of charge cycles. As an adjustment factor for battery aging, Perform normalization, for example, divide by .

[0023] Preferably, the formula for calculating the equivalent available power of a vehicle in a high-altitude environment is fitted using the least squares method or ant colony algorithm based on the observed value of the equivalent available power, thereby obtaining the weights and adjustment factors in the formula.

[0024] Step 102: Divide the driving cycle of the hybrid vehicle into multiple time slices according to a certain time step, set up a battery charge state estimation model, and calculate the charge state at each time point based on the equivalent available power. Specifically, the battery charge state estimation model includes: , in, For the first The charge state at each point in time. For the first The charge state at each point in time. For the number of time slices, For the first Energy recovery efficiency at a given time point For the first Energy recovery power at each time point For the first Discharge power at each time point For the first Discharge efficiency at each time point For time step.

[0025] Step 103: Set up a battery internal resistance estimation model, calculate the battery internal resistance at each time point based on the charge state, and calculate the maximum safe discharge power at each time point based on the battery internal resistance. Specifically, the battery internal resistance estimation model includes: , in, For the first Battery internal resistance at each time point For reference internal resistance, As the second weighting factor for altitude, The second adjustment factor for altitude. Temperature is the second weighting factor. For the first Battery temperature at various time points The temperature decay constant, The weights of the charge states, This is an adjustment factor for the charge state.

[0026] Preferably, the formula for calculating the battery internal resistance is fitted based on the observed values ​​of the battery internal resistance using the least squares method or ant colony algorithm, thereby obtaining the weights and adjustment factors in the formula.

[0027] Preferably, in this embodiment, the temperature decay constant is obtained in the following manner. : Under constant SOC and constant altitude, select several groups of different temperatures The internal resistance was measured using a small current pulse at each temperature. Calculate the relative internal resistance gain: , Fit to exponential form: , The result fitted by least squares method Substituting into it, the calculation is as follows .

[0028] Specifically, calculating the maximum safe discharge power at each time point includes: , in, For the first The maximum safe discharge power at each time point For the battery in the first No-load voltage under charge state at each time point This represents the maximum allowable drop in terminal voltage. This refers to the battery power safety limit.

[0029] Step 104: Obtain the actual maximum discharge power at each time point and compare it with the corresponding maximum safe discharge power to determine whether the corresponding time point and the actual maximum discharge power are abnormal.

[0030] Specifically, determining whether the corresponding time point and the actual maximum discharge power are abnormal includes: if the actual maximum discharge power exceeds the maximum safe discharge power, then the corresponding time point is marked as an abnormal time point, and the corresponding actual maximum discharge power is marked as a discharge abnormality.

[0031] Example 2 like Figure 2 As shown, this embodiment proposes a hybrid electric vehicle battery retention performance testing system for high-altitude environments, including: The equivalent available power calculation module is used to obtain environmental information, the battery aging degree of the hybrid vehicle, and the rated power of the hybrid vehicle, and calculate the equivalent available power of the vehicle in a high-altitude environment. The environmental information includes: altitude and ambient temperature. Specifically, calculating the equivalent usable electricity of a vehicle in a high-altitude environment includes: , in, This refers to the equivalent usable electrical energy of the vehicle in a high-altitude environment. Rated power, Altitude is the primary weighting factor. Altitude For reference height, The first adjustment factor for altitude. Temperature is the first weighted factor. For ambient temperature, For reference temperature, As a weight for battery aging, The battery aging degree is calculated by dividing the number of battery charge cycles by the designed number of charge cycles. As an adjustment factor for battery aging, Perform normalization, for example, divide by .

[0032] Preferably, the formula for calculating the equivalent available power of a vehicle in a high-altitude environment is fitted using the least squares method or ant colony algorithm based on the observed value of the equivalent available power, thereby obtaining the weights and adjustment factors in the formula.

[0033] The charge state calculation module is used to divide the driving cycle of the hybrid vehicle into multiple time slices according to a certain time step, set the battery charge state estimation model, and calculate the charge state at each time point based on the equivalent available power. Specifically, the battery charge state estimation model includes: , in, For the first The charge state at each point in time. For the first The charge state at each point in time. For the number of time slices, For the first Energy recovery efficiency at a given time point For the first Energy recovery power at each time point For the first Discharge power at each time point For the first Discharge efficiency at each time point For time step.

[0034] The module for calculating the maximum safe discharge power is used to set up a battery internal resistance estimation model, calculate the battery internal resistance at each time point based on the charge state, and calculate the maximum safe discharge power at each time point based on the battery internal resistance. Specifically, the battery internal resistance estimation model includes: , in, For the first Battery internal resistance at each time point For reference internal resistance, As the second weighting factor for altitude, The second adjustment factor for altitude. Temperature is the second weighting factor. For the first Battery temperature at various time points The temperature decay constant, The weights of the charge states, This is an adjustment factor for the charge state.

[0035] Preferably, the formula for calculating the battery internal resistance is fitted based on the observed values ​​of the battery internal resistance using the least squares method or ant colony algorithm, thereby obtaining the weights and adjustment factors in the formula.

[0036] Preferably, in this embodiment, the temperature decay constant is obtained in the following manner. : Under constant SOC and constant altitude, select several groups of different temperatures The internal resistance was measured using a small current pulse at each temperature. Calculate the relative internal resistance gain: , Fit to exponential form: , The result fitted by least squares method Substituting into it, the calculation is as follows .

[0037] Specifically, calculating the maximum safe discharge power at each time point includes: , in, For the first The maximum safe discharge power at each time point For the battery in the first No-load voltage under charge state at each time point This represents the maximum allowable drop in terminal voltage. This refers to the battery power safety limit.

[0038] The anomaly detection module is used to obtain the actual maximum discharge power at each time point, compare it with the corresponding maximum safe discharge power, and thus determine whether the corresponding time point and the actual maximum discharge power are abnormal.

[0039] Specifically, determining whether the corresponding time point and the actual maximum discharge power are abnormal includes: if the actual maximum discharge power exceeds the maximum safe discharge power, then the corresponding time point is marked as an abnormal time point, and the corresponding actual maximum discharge power is marked as a discharge abnormality.

[0040] Example 3 This invention also proposes a storage medium storing multiple instructions for implementing the aforementioned method for testing the battery retention performance of hybrid vehicles in high-altitude environments.

[0041] Optionally, in this embodiment, the storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals.

[0042] Optionally, in this embodiment, the storage medium is configured to store program code for performing the following method steps: Step 101, obtaining environmental information, the battery aging degree of the hybrid vehicle and the rated power of the hybrid vehicle, and calculating the equivalent available power of the vehicle in a high-altitude environment, wherein the environmental information includes: altitude and ambient temperature. Specifically, calculating the equivalent usable electricity of a vehicle in a high-altitude environment includes: , in, This refers to the equivalent usable electrical energy of the vehicle in a high-altitude environment. Rated power, Altitude is the primary weighting factor. Altitude For reference height, The first adjustment factor for altitude. Temperature is the first weighted factor. For ambient temperature, For reference temperature, As a weight for battery aging, The battery aging degree is calculated by dividing the number of battery charge cycles by the designed number of charge cycles. As an adjustment factor for battery aging, Perform normalization, for example, divide by .

[0043] Preferably, the formula for calculating the equivalent available power of a vehicle in a high-altitude environment is fitted using the least squares method or ant colony algorithm based on the observed value of the equivalent available power, thereby obtaining the weights and adjustment factors in the formula.

[0044] Step 102: Divide the driving cycle of the hybrid vehicle into multiple time slices according to a certain time step, set up a battery charge state estimation model, and calculate the charge state at each time point based on the equivalent available power. Specifically, the battery charge state estimation model includes: , in, For the first The charge state at each point in time. For the first The charge state at each point in time. For the number of time slices, For the first Energy recovery efficiency at a given time point For the first Energy recovery power at each time point For the first Discharge power at each time point For the first Discharge efficiency at each time point For time step.

[0045] Step 103: Set up a battery internal resistance estimation model, calculate the battery internal resistance at each time point based on the charge state, and calculate the maximum safe discharge power at each time point based on the battery internal resistance. Specifically, the battery internal resistance estimation model includes: , in, For the first Battery internal resistance at each time point For reference internal resistance, As the second weighting factor for altitude, The second adjustment factor for altitude. Temperature is the second weighting factor. For the first Battery temperature at various time points The temperature decay constant, The weights of the charge states, This is an adjustment factor for the charge state.

[0046] Preferably, the formula for calculating the battery internal resistance is fitted based on the observed values ​​of the battery internal resistance using the least squares method or ant colony algorithm, thereby obtaining the weights and adjustment factors in the formula.

[0047] Preferably, in this embodiment, the temperature decay constant is obtained in the following manner. : Under constant SOC and constant altitude, select several groups of different temperatures The internal resistance was measured using a small current pulse at each temperature. Calculate the relative internal resistance gain: , Fit to exponential form: , The result fitted by least squares method Substituting into it, the calculation is as follows .

[0048] Specifically, calculating the maximum safe discharge power at each time point includes: , in, For the first The maximum safe discharge power at each time point For the battery in the first No-load voltage under charge state at each time point This represents the maximum allowable drop in terminal voltage. This refers to the battery power safety limit.

[0049] Step 104: Obtain the actual maximum discharge power at each time point and compare it with the corresponding maximum safe discharge power to determine whether the corresponding time point and the actual maximum discharge power are abnormal.

[0050] Specifically, determining whether the corresponding time point and the actual maximum discharge power are abnormal includes: if the actual maximum discharge power exceeds the maximum safe discharge power, then the corresponding time point is marked as an abnormal time point, and the corresponding actual maximum discharge power is marked as a discharge abnormality.

[0051] Example 4 This invention also proposes an electronic device, including a processor and a storage medium connected to the processor. The storage medium stores multiple instructions, which can be loaded and executed by the processor to enable the processor to execute the aforementioned method for testing the battery retention performance of a hybrid vehicle in a high-altitude environment.

[0052] Specifically, the electronic device in this embodiment can be a computer terminal, which may include one or more processors and a storage medium.

[0053] The storage medium can be used to store software programs and modules, such as the battery retention performance testing method for hybrid vehicles in a high-altitude environment according to an embodiment of the present invention. The corresponding program instructions / modules allow the processor to execute various functional applications and data processing by running the software programs and modules stored in the storage medium, thus realizing the aforementioned battery retention performance testing method for hybrid vehicles in a high-altitude environment. The storage medium may include high-speed random access storage media, and may also include non-volatile storage media, such as one or more magnetic storage systems, flash memory, or other non-volatile solid-state storage media. In some instances, the storage medium may further include storage media remotely configured relative to the processor, which can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0054] The processor can call the information and application stored in the storage medium through the transmission system to execute the following method steps: Step 101, obtain environmental information, battery aging degree of the hybrid vehicle and rated power of the hybrid vehicle, and calculate the equivalent available power of the vehicle in the high-altitude environment, wherein the environmental information includes: altitude and ambient temperature. Specifically, calculating the equivalent usable electricity of a vehicle in a high-altitude environment includes: , in, This refers to the equivalent usable electrical energy of the vehicle in a high-altitude environment. Rated power, Altitude is the primary weighting factor. Altitude For reference height, The first adjustment factor for altitude. Temperature is the first weighted factor. For ambient temperature, For reference temperature, As a weight for battery aging, The battery aging degree is calculated by dividing the number of battery charge cycles by the designed number of charge cycles. As an adjustment factor for battery aging, Perform normalization, for example, divide by .

[0055] Preferably, the formula for calculating the equivalent available power of a vehicle in a high-altitude environment is fitted using the least squares method or ant colony algorithm based on the observed value of the equivalent available power, thereby obtaining the weights and adjustment factors in the formula.

[0056] Step 102: Divide the driving cycle of the hybrid vehicle into multiple time slices according to a certain time step, set up a battery charge state estimation model, and calculate the charge state at each time point based on the equivalent available power. Specifically, the battery charge state estimation model includes: , in, For the first The charge state at each point in time. For the first The charge state at each point in time. For the number of time slices, For the first Energy recovery efficiency at a given time point For the first Energy recovery power at each time point For the first Discharge power at each time point For the first Discharge efficiency at each time point For time step.

[0057] Step 103: Set up a battery internal resistance estimation model, calculate the battery internal resistance at each time point based on the charge state, and calculate the maximum safe discharge power at each time point based on the battery internal resistance. Specifically, the battery internal resistance estimation model includes: , in, For the first Battery internal resistance at each time point For reference internal resistance, As the second weighting factor for altitude, The second adjustment factor for altitude. Temperature is the second weighting factor. For the first Battery temperature at various time points The temperature decay constant, The weights of the charge states, This is an adjustment factor for the charge state.

[0058] Preferably, the formula for calculating the battery internal resistance is fitted based on the observed values ​​of the battery internal resistance using the least squares method or ant colony algorithm, thereby obtaining the weights and adjustment factors in the formula.

[0059] Preferably, in this embodiment, the temperature decay constant is obtained in the following manner. : Under constant SOC and constant altitude, select several groups of different temperatures The internal resistance was measured using a small current pulse at each temperature. Calculate the relative internal resistance gain: , Fit to exponential form: , The result fitted by least squares method Substituting into it, the calculation is as follows .

[0060] Specifically, calculating the maximum safe discharge power at each time point includes: , in, For the first The maximum safe discharge power at each time point For the battery in the first No-load voltage under charge state at each time point This represents the maximum allowable drop in terminal voltage. This refers to the battery power safety limit.

[0061] Step 104: Obtain the actual maximum discharge power at each time point and compare it with the corresponding maximum safe discharge power to determine whether the corresponding time point and the actual maximum discharge power are abnormal.

[0062] Specifically, determining whether the corresponding time point and the actual maximum discharge power are abnormal includes: if the actual maximum discharge power exceeds the maximum safe discharge power, then the corresponding time point is marked as an abnormal time point, and the corresponding actual maximum discharge power is marked as a discharge abnormality.

[0063] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0064] In the several embodiments provided by this invention, it should be understood that the disclosed technical content can be implemented in other ways. The system embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, indirect coupling or communication connection between units or modules, and may be electrical or other forms.

[0065] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0066] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0067] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes: USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, optical disks, and other media capable of storing program code.

[0068] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A method for testing the battery retention performance of a hybrid electric vehicle in a high-altitude environment, characterized in that, include: The system acquires environmental information, the battery aging rate of the hybrid electric vehicle, and the rated charge of the hybrid electric vehicle to calculate the equivalent usable charge of the vehicle in a high-altitude environment. The environmental information includes: altitude and ambient temperature. The driving cycle of a hybrid vehicle is divided into multiple time slices according to a certain time step. A battery charge state estimation model is set up, and the charge state at each time point is calculated based on the equivalent available power. Set up a battery internal resistance estimation model, and calculate the battery internal resistance at each time point based on the charge state. Then, calculate the maximum safe discharge power at each time point based on the battery internal resistance. The actual maximum discharge power at each time point is obtained and compared with the corresponding maximum safe discharge power to determine whether the corresponding time point and the actual maximum discharge power are abnormal.

2. The method for testing the battery retention performance of a hybrid vehicle in a high-altitude environment as described in claim 2, characterized in that, The calculation of the vehicle's equivalent usable electricity in a high-altitude environment includes: ， in, This refers to the equivalent usable electrical energy of the vehicle in a high-altitude environment. Rated power, Altitude is the primary weighting factor. Altitude For reference height, The first adjustment factor for altitude. Temperature is the first weighted factor. For ambient temperature, For reference temperature, As a weight for battery aging, The battery aging degree is calculated by dividing the number of battery charge cycles by the designed number of charge cycles. This is an adjustment factor for battery aging.

3. The method for testing the battery retention performance of a hybrid vehicle in a high-altitude environment as described in claim 2, characterized in that, The battery charge state estimation model includes: ， in, For the first The charge state at each point in time. For the first The charge state at each point in time. For the number of time slices, For the first Energy recovery efficiency at a given time point For the first Energy recovery power at each time point For the first Discharge power at each time point For the first Discharge efficiency at each time point For time step.

4. The method for testing the battery retention performance of a hybrid electric vehicle in a high-altitude environment as described in claim 3, characterized in that, The battery internal resistance estimation model includes: ， in, For the first Battery internal resistance at each time point For reference internal resistance, As the second weighting factor for altitude, The second adjustment factor for altitude. Temperature is the second weighting factor. For the first Battery temperature at various time points The temperature decay constant, The weights of the charge states, This is an adjustment factor for the charge state.

5. The method for testing the battery retention performance of a hybrid electric vehicle in a high-altitude environment as described in claim 4, characterized in that, The calculation of the maximum safe discharge power at each time point includes: ， in, For the first The maximum safe discharge power at each time point For the battery in the first No-load voltage under charge state at each time point This represents the maximum allowable drop in terminal voltage. This refers to the battery power safety limit.

6. The method for testing the battery retention performance of a hybrid vehicle in a high-altitude environment as described in claim 1, characterized in that, Determining whether the corresponding time point and the actual maximum discharge power are abnormal includes: if the actual maximum discharge power exceeds the maximum safe discharge power, then the corresponding time point is marked as an abnormal time point, and the corresponding actual maximum discharge power is marked as a discharge abnormality.

7. A system for testing the battery retention performance of hybrid vehicles in high-altitude environments, characterized in that, include: The equivalent available power calculation module is used to obtain environmental information, the battery aging degree of the hybrid vehicle, and the rated power of the hybrid vehicle, and calculate the equivalent available power of the vehicle in a high-altitude environment. The environmental information includes: altitude and ambient temperature. The charge state calculation module is used to divide the driving cycle of the hybrid vehicle into multiple time slices according to a certain time step, set the battery charge state estimation model, and calculate the charge state at each time point based on the equivalent available power. The module for calculating the maximum safe discharge power is used to set up a battery internal resistance estimation model, calculate the battery internal resistance at each time point based on the charge state, and calculate the maximum safe discharge power at each time point based on the battery internal resistance. The anomaly detection module is used to obtain the actual maximum discharge power at each time point, compare it with the corresponding maximum safe discharge power, and thus determine whether the corresponding time point and the actual maximum discharge power are abnormal.

8. The hybrid electric vehicle battery retention performance testing system as described in claim 7, characterized in that, The calculation of the vehicle's equivalent usable electricity in a high-altitude environment includes: ， in, This refers to the equivalent usable electrical energy of the vehicle in a high-altitude environment. Rated power, Altitude is the primary weighting factor. Altitude For reference height, The first adjustment factor for altitude. Temperature is the first weighted factor. For ambient temperature, For reference temperature, As a weight for battery aging, The battery aging degree is calculated by dividing the number of battery charge cycles by the designed number of charge cycles. This is an adjustment factor for battery aging.

9. The hybrid electric vehicle battery retention performance testing system as described in claim 8, characterized in that, The battery charge state estimation model includes: ， in, For the first The charge state at each point in time. For the first The charge state at each point in time. For the number of time slices, For the first Energy recovery efficiency at a given time point For the first Energy recovery power at each time point For the first Discharge power at each time point For the first Discharge efficiency at each time point For time step.

10. The hybrid electric vehicle battery retention performance testing system as described in claim 9, characterized in that, Battery internal resistance estimation models include: ， in, For the first Battery internal resistance at each time point For reference internal resistance, As the second weighting factor for altitude, The second adjustment factor for altitude. Temperature is the second weighting factor. For the first Battery temperature at various time points The temperature decay constant, The weights of the charge states, This is an adjustment factor for the charge state.

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