Vehicle energy management method, storage medium, and vehicle

Abstract

A vehicle energy management method, a storage medium, and a vehicle, belonging to the technical field of vehicles. By means of comprehensively considering multiple battery parameters of a battery, current remaining power precision of the battery can be accurately identified, and then an appropriate target correction amount can be determined for the battery, on the basis of the current remaining power precision. On the basis of the target correction amount, an initial remaining power threshold is dynamically corrected, to obtain a target remaining power threshold. On the basis of the target remaining power threshold, finer energy management can be performed on the battery. In this way, battery energy can be used as much as possible while ensuring safe usage of the battery, thereby achieving full battery energy utilization, and effectively increasing vehicle range.

Description

A vehicle energy management method, storage medium, and vehicle

[0001] This disclosure claims priority to Chinese Patent Application No. 202411599689.4, filed on November 11, 2024, entitled "A Vehicle Energy Management Method, Storage Medium and Vehicle", the entire contents of which are incorporated herein by reference. Technical Field

[0002] This disclosure relates to the field of vehicle technology, and in particular to a vehicle energy management method, storage medium, and vehicle. Background Technology

[0003] Batteries are a crucial energy source for new energy vehicles. To protect batteries, extend their lifespan, and ensure vehicle safety, appropriate remaining charge thresholds are typically set for batteries to prevent over-discharge.

[0004] In related technologies, the remaining battery capacity threshold is typically set to a conservative, relatively large threshold. However, this approach can easily lead to inefficient use of battery energy and reduce the vehicle's driving range. Summary of the Invention

[0005] This disclosure provides a vehicle energy management method, storage medium, and vehicle to address the problem of low vehicle range caused by the inability to effectively utilize battery energy.

[0006] To address the aforementioned issues, the present disclosure adopts the following technical solution.

[0007] In a first aspect, embodiments of this disclosure provide a vehicle energy management method, the method comprising: determining the current remaining charge accuracy of the battery based on multiple battery parameters; determining a target correction amount based on the current remaining charge accuracy; wherein different remaining charge accuracies correspond to different correction amounts; and correcting an initial remaining charge threshold of the battery based on the target correction amount to obtain a target remaining charge threshold; wherein the target remaining charge threshold is used for energy management of the battery.

[0008] In one embodiment of this disclosure, determining the current remaining power accuracy of the battery based on multiple battery parameters of the battery includes: determining the current remaining power accuracy of the battery based on the multiple battery parameters and the parameter weights corresponding to each of the multiple battery parameters.

[0009] In one embodiment of this disclosure, determining the current remaining power accuracy of the battery based on multiple battery parameters of the battery includes: inputting the multiple battery parameters into an accuracy prediction model and outputting the current remaining power accuracy; wherein the accuracy prediction model is trained based on sample battery parameters of the battery.

[0010] In one embodiment of this disclosure, determining the current remaining battery power accuracy based on the plurality of battery parameters and the parameter weights corresponding to each of the plurality of battery parameters includes: determining the initial accuracy score corresponding to each of the plurality of battery parameters; determining the weighted accuracy score corresponding to each of the plurality of battery parameters based on the initial accuracy score and parameter weights corresponding to each of the plurality of battery parameters; and determining the current remaining battery power accuracy based on the weighted accuracy score corresponding to each of the plurality of battery parameters.

[0011] In one embodiment of this disclosure, determining the current remaining battery power accuracy based on the weighted accuracy scores corresponding to multiple battery parameters includes: determining a comprehensive accuracy score based on the weighted accuracy scores corresponding to multiple battery parameters; determining a target score interval to which the comprehensive accuracy score belongs among a preset number of score intervals; different score intervals correspond to different accuracy values; and determining the accuracy value corresponding to the target score interval as the current remaining battery power accuracy.

[0012] In one embodiment of this disclosure, the plurality of battery parameters include battery health status, battery operating temperature, charge / discharge rate, remaining capacity correction frequency, average remaining capacity correction magnitude, and cell difference parameters; the cell difference parameters include maximum cell temperature difference, maximum cell voltage difference, and / or maximum remaining capacity difference.

[0013] In one embodiment of this disclosure, determining a target correction amount based on the current remaining battery power accuracy includes: determining the target correction amount to be zero when the current remaining battery power accuracy is within a preset accuracy range; determining the target correction amount as a first correction amount when the current remaining battery power accuracy is greater than the upper limit of the preset accuracy range; the first correction amount is used to increase the initial remaining battery power threshold; and determining the target correction amount as a second correction amount when the current remaining battery power accuracy is less than the lower limit of the preset accuracy range; the second correction amount is used to decrease the initial remaining battery power threshold.

[0014] In one embodiment of this disclosure, the initial remaining battery power threshold includes an initial forced charging threshold and / or an initial balancing battery power threshold; adjusting the initial remaining battery power threshold based on the target adjustment amount to obtain a target remaining battery power threshold includes: adjusting the initial forced charging threshold based on the adjustment amount to obtain a target forced charging threshold; and / or, adjusting the initial balancing battery power threshold based on the adjustment amount to obtain a target balancing battery power threshold; wherein, the target forced charging threshold is used to indicate that when the current remaining battery power is lower than the target forced charging threshold, the vehicle's engine should be started to charge the battery; the target balancing battery power threshold is used to indicate that the engine should be controlled to charge the battery using the target balancing battery power threshold as the target remaining battery power.

[0015] Secondly, based on the same inventive concept, embodiments of this disclosure provide a vehicle energy management device, the device comprising: an accuracy determination module, configured to determine the current remaining charge accuracy of the battery based on multiple battery parameters; a correction amount determination module, configured to determine a target correction amount based on the current remaining charge accuracy; wherein different remaining charge accuracies correspond to different correction amounts; and a threshold correction module, configured to correct an initial remaining charge threshold of the battery based on the target correction amount to obtain a target remaining charge threshold; wherein the target remaining charge threshold is used for energy management of the battery.

[0016] In one embodiment of this disclosure, the accuracy determination module includes: a first correction amount determination submodule, used to determine the current remaining power accuracy of the battery based on the plurality of battery parameters and the parameter weights corresponding to the plurality of battery parameters.

[0017] In one embodiment of this disclosure, the accuracy determination module includes: a second correction amount determination submodule, used to input the plurality of battery parameters into an accuracy prediction model and output the current remaining power accuracy; wherein, the accuracy prediction model is trained based on sample battery parameters of the battery.

[0018] In one embodiment of this disclosure, the first correction amount determination submodule includes: an initial accuracy score determination unit, configured to determine the initial accuracy score corresponding to each of the plurality of battery parameters; a weighted accuracy score determination unit, configured to determine the weighted accuracy score corresponding to each of the plurality of battery parameters based on the initial accuracy score and parameter weights corresponding to each of the plurality of battery parameters; and a remaining power accuracy determination unit, configured to determine the current remaining power accuracy based on the weighted accuracy score corresponding to each of the plurality of battery parameters.

[0019] In one embodiment of this disclosure, the remaining power accuracy determination unit includes: a comprehensive accuracy score determination subunit, used to determine a comprehensive accuracy score based on the weighted accuracy scores corresponding to multiple battery parameters; a score interval determination subunit, used to determine the target score interval to which the comprehensive accuracy score belongs among a plurality of preset score intervals; different score intervals correspond to different accuracy values; and a remaining power accuracy determination subunit, used to determine the accuracy value corresponding to the target score interval as the current remaining power accuracy.

[0020] In one embodiment of this disclosure, the plurality of battery parameters include battery health status, battery operating temperature, charge / discharge rate, remaining capacity correction frequency, average remaining capacity correction magnitude, and cell difference parameters; the cell difference parameters include maximum cell temperature difference, maximum cell voltage difference, and / or maximum remaining capacity difference.

[0021] In one embodiment of this disclosure, the correction amount determination module includes: a first correction amount determination submodule, configured to determine the target correction amount as zero when the current remaining power accuracy is within a preset accuracy range; a second correction amount determination submodule, configured to determine the target correction amount as a first correction amount when the current remaining power accuracy is greater than the upper limit of the preset accuracy range; the first correction amount is used to increase the initial remaining power threshold; and a third correction amount determination submodule, configured to determine the target correction amount as a second correction amount when the current remaining power accuracy is less than the lower limit of the preset accuracy range; the second correction amount is used to decrease the initial remaining power threshold.

[0022] In one embodiment of this disclosure, the initial remaining battery power threshold includes an initial forced charging threshold and / or an initial balancing battery power threshold; the threshold correction module includes: a first threshold correction submodule, configured to correct the initial forced charging threshold based on the correction amount to obtain a target forced charging threshold; and a second threshold correction submodule, configured to correct the initial balancing battery power threshold based on the correction amount to obtain a target balancing battery power threshold; wherein, the target forced charging threshold is used to indicate that when the current remaining battery power is lower than the target forced charging threshold, the vehicle's engine should be started to charge the battery; and the target balancing battery power threshold is used to indicate that the engine should be controlled to charge the battery using the target balancing battery power threshold as the target remaining battery power.

[0023] Thirdly, based on the same inventive concept, embodiments of this disclosure provide a computer-readable storage medium having an executable program stored thereon, which, when executed by a processor, implements the vehicle energy management method proposed in the first aspect of this disclosure.

[0024] Fourthly, based on the same inventive concept, embodiments of this disclosure provide a vehicle, including: a memory for storing an executable program; a processor; and when the executable program is executed by the processor, it implements the vehicle energy management method proposed in the first aspect of this disclosure.

[0025] Compared with existing technologies, this disclosure has the following advantages: The vehicle energy management method provided in this disclosure, by comprehensively considering multiple battery parameters, can accurately determine the current remaining battery charge. Based on this accuracy, a suitable target correction amount can be determined for the battery. Furthermore, based on this target correction amount, an initial remaining charge threshold is dynamically corrected to obtain a target remaining charge threshold. Based on this target remaining charge threshold, more refined energy management of the battery is possible. Thus, while ensuring battery safety, battery energy can be used as much as possible, thereby achieving full utilization of battery energy and effectively improving the vehicle's driving range. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 is a flowchart of the steps of a vehicle energy management method according to an embodiment of the present disclosure.

[0028] Figure 2 is a schematic diagram of the functional modules of a vehicle energy management device according to an embodiment of the present disclosure.

[0029] Figure 3 is a structural schematic diagram of a vehicle according to an embodiment of the present disclosure. Embodiments of the present invention

[0030] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. 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.

[0031] It's important to note that the battery's true SOC (State of Charge, also known as remaining charge) typically has system accuracy requirements. For example, if the system accuracy requirement is 5%, and the lower limit of SOC is set at 8%, then under the worst-case scenario, the true SOC could reach (8% - 5% =) 3%; if the lower limit of SOC is set at 6%, the true SOC risks dropping to (6% - 5% =) 1%. Furthermore, due to the battery's self-discharge characteristics, if the vehicle is parked for an extended period, a very low true SOC could prevent the vehicle from starting when restarted.

[0032] In related technologies, to avoid the battery from running too low, a corresponding remaining capacity threshold is usually set for the battery. However, due to the limitations of the accuracy of the remaining battery capacity measurement, the remaining capacity threshold is usually set to a conservative and relatively large threshold. This means that when the battery has the ability to output energy, its remaining energy cannot be effectively utilized, thereby reducing the vehicle's driving range.

[0033] To address the problem of limited vehicle range due to the ineffective utilization of battery energy, this disclosure aims to provide a vehicle energy management method. By comprehensively considering multiple battery parameters, it can accurately identify the current remaining battery charge. Based on this accuracy, a suitable target correction amount can be determined for the battery. Furthermore, based on this target correction amount, an initial remaining charge threshold is dynamically adjusted to obtain a target remaining charge threshold. Using this target remaining charge threshold, more refined energy management of the battery is possible. In this way, while ensuring battery safety, battery energy can be used as much as possible, thereby achieving full utilization of battery energy and effectively improving the vehicle's driving range.

[0034] Referring to FIG1, a vehicle energy management method of the present disclosure is shown, which may include the following steps.

[0035] S101: Determines the current remaining battery charge accuracy based on multiple battery parameters.

[0036] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, or an electronic device with the above functions, such as a vehicle computer, an on-board computer, or an ECU (Electronic Control Unit), HCU (Hybrid Control Unit), BMS (Battery Management System), etc. This embodiment does not impose specific limitations on the type of executing entity; the following description will use BMS as the executing entity.

[0037] In this embodiment, the BMS can acquire multiple battery parameters of the battery according to a preset data acquisition cycle, and then update the accuracy of the current remaining power based on the multiple battery parameters.

[0038] It's important to note that the accuracy of the remaining battery charge level indicates the precision of the measurement and estimation of the battery's current charge level. Higher remaining charge accuracy means the BMS can accurately reflect the battery's actual charge, thus effectively managing the charging and discharging process and ensuring battery safety and performance. As battery usage time increases, the remaining charge accuracy typically decreases due to factors such as battery aging and the operating environment.

[0039] In specific implementations, to achieve accurate identification of the current remaining power, multiple battery parameters may include SOH (State of Health), battery operating temperature, charge / discharge rate, remaining power correction frequency, average remaining power correction magnitude, and cell difference parameters; cell difference parameters include maximum cell temperature difference, maximum cell voltage difference, and / or maximum remaining power difference.

[0040] It should be noted that, considering the gradual capacity decay and increased internal impedance of a battery as its usage time increases, which affects the accurate measurement and prediction of State of Charge (SOC), the Battery Management System (BMS) calculates the Battery's State of Health (SOH) during battery use. SOH represents an indicator of the battery's overall health relative to its ideal performance during use, specifically including information such as the rate of capacity decay and resistance increase. The rate of capacity decay can be calculated by comparing the battery's current capacity with its rated capacity and expressed as a percentage.

[0041] It should be noted that temperature has a significant impact on battery performance. Both high and low temperatures can affect the battery's charge and discharge efficiency, thus affecting the accuracy of the State of Charge (SOC). Therefore, the Battery Management System (BMS) records the battery's operating temperature during use, specifically including the temperature range and duration. Based on the temperature range and duration, the BMS can calculate the ratio of the duration of the temperature range that significantly affects battery performance to the total duration.

[0042] It should be noted that when the battery operates at high charge / discharge rates, the battery's internal resistance may cause a large voltage drop, thus affecting the accuracy of SOC measurement. Therefore, the BMS records the battery's charge and discharge rates during the current driving cycle, and then calculates the battery's average charge / discharge rate over a preset period.

[0043] It should be noted that the remaining power correction frequency refers to the frequency at which SOC correction is triggered, and the average remaining power correction magnitude refers to the average correction amount for SOC. Specifically, the BMS can trigger SOC correction when the battery meets preset correction conditions, and record a correction event and calculate the corresponding SOC correction magnitude when the correction is detected to be complete. By statistically analyzing correction events within a preset time period, the BMS can calculate the battery's remaining power correction frequency and average remaining power correction magnitude. The preset correction conditions can be set as follows: the battery is in a fully charged or fully discharged state, or the battery is in an abnormal state (e.g., abnormal voltage or current), or SOC correction is performed at fixed time intervals.

[0044] It should be noted that chemical inhomogeneities between multiple battery cells can lead to differences in overall battery performance. Therefore, by obtaining cell difference parameters, it is possible to effectively analyze the differences between multiple cells within the battery. Specifically, the maximum cell temperature difference represents the temperature difference between the cell with the highest and lowest temperature; the maximum cell pressure difference represents the pressure difference between the cell with the highest and lowest pressure; and the maximum remaining capacity difference represents the remaining capacity difference between the cell with the highest and lowest remaining capacity.

[0045] It should be noted that deep discharge of a battery accelerates internal chemical reactions, damaging its physical and chemical structure and thus shortening its lifespan. Therefore, multiple battery parameters may also include the battery's deep discharge frequency, which represents the number of times the battery's remaining capacity is discharged to below a preset threshold within a preset time period.

[0046] It should be noted that different types of batteries differ in chemical properties, discharge curves, internal resistance, and self-discharge rates. These factors all affect the calculation and evaluation of remaining capacity. For example, the accuracy of remaining capacity calculations for lithium-ion batteries is generally higher than that for lead-acid batteries. Therefore, multiple battery parameters can also include battery type.

[0047] In this embodiment, by comprehensively considering multiple battery parameters that affect battery accuracy, the remaining power accuracy of the battery can be comprehensively evaluated from multiple dimensions, thereby achieving accurate identification of the current remaining power accuracy of the battery.

[0048] S102: Determine the target correction amount based on the current remaining battery power accuracy.

[0049] In this embodiment, different remaining battery power accuracies correspond to different correction amounts. This correction amount represents the magnitude and direction of the correction to the initial remaining battery power threshold. Specifically, the correction amount can be zero, negative, or positive. Zero indicates that no correction is needed for the initial remaining battery power threshold; when the target correction amount is positive, the initial remaining battery power threshold will be corrected upwards to increase it; when the target correction amount is negative, the initial remaining battery power threshold can be corrected downwards to decrease it.

[0050] In its implementation, the BMS pre-stores a mapping table that represents the relationship between the remaining power accuracy and the correction amount. After determining the current remaining power accuracy, the BMS can determine the corresponding target correction amount by looking up the table.

[0051] S103: Based on the target correction amount, correct the initial remaining battery power threshold to obtain the target remaining battery power threshold.

[0052] In this embodiment, the sum of the initial remaining power threshold and the correction amount can be determined as the target remaining power threshold.

[0053] In practical implementation, after calculating the target remaining battery power threshold, the BMS can directly send the target remaining battery power threshold to the HCU, so that the HCU can perform energy management of the vehicle based on the target remaining battery power threshold; or, after calculating the correction amount, the BMS can send the correction amount to the HCU, and the HCU can calculate the target remaining battery power threshold and then perform energy management of the vehicle.

[0054] It should be noted that the target remaining battery capacity threshold is used for battery energy management. In other words, if the battery's current remaining capacity is less than the initial remaining capacity threshold, an appropriate energy management strategy will be triggered to manage the battery's energy and prevent the remaining battery capacity from decreasing further.

[0055] In one example, the initial remaining battery power threshold is 9%, meaning the battery will be charged when its remaining power is less than 9%. Based on multiple battery parameters, the BMS determines a target correction of -3%, thus calculating the target remaining battery power threshold as (9% - 3% =) 6%. In other words, by correcting the initial remaining battery power threshold from 9% to 6%, the battery can output an additional 3% of its power, thereby providing the user with greater driving range.

[0056] In this embodiment, by comprehensively considering multiple battery parameters, a suitable target correction amount can be determined for the battery. Based on this target correction amount, the initial remaining power threshold is dynamically corrected to obtain a target remaining power threshold. Based on this target remaining power threshold, battery energy management can be performed more precisely. In this way, while ensuring battery safety, battery energy can be used as much as possible, thereby achieving full utilization of battery energy and effectively improving the vehicle's driving range.

[0057] In one feasible implementation, S101 may specifically include the following sub-steps:

[0058] S101-A: Determines the accuracy of the current remaining battery power based on multiple battery parameters and their respective weights.

[0059] In this embodiment, considering that different battery parameters have different sensitivities and importance to the SOC accuracy, a corresponding parameter weight will be assigned to each battery parameter, thereby improving the accuracy of remaining power identification.

[0060] In practice, the weights of each of the multiple battery parameters can be determined through expert experience, historical data analysis, or by using machine learning methods (such as regression analysis).

[0061] S101-B: Input multiple battery parameters into the accuracy prediction model and output the current remaining power accuracy.

[0062] In this embodiment, to fully explore the correlation between multiple battery parameters and the accuracy of remaining battery capacity, sample battery parameters can be used as training samples to train the neural network model to obtain an accuracy prediction model. A sample battery parameter includes multiple historical battery parameters.

[0063] In practical implementation, the accuracy prediction model can be trained as follows: Obtain sample battery parameters, which include the battery's accuracy label; train the initial neural network model using these sample battery parameters to obtain the accuracy prediction result output by the initial neural network model; then, calculate the loss function value based on the accuracy prediction result and the accuracy label, and iteratively update the network parameters of the initial neural network model based on the loss function value until the initial neural network model meets the training cutoff condition, thus obtaining the accuracy prediction model. After the model training is complete, it can also be validated using a test dataset to evaluate the accuracy and generalization ability of the accuracy prediction model.

[0064] In this embodiment, to improve the model recognition capability of the accuracy prediction model, the accuracy prediction model can also be trained using sample-weighted battery parameters. These sample-weighted battery parameters are determined based on multiple historical battery parameters and their respective weights. By weighting multiple historical battery parameters and inputting them into the neural network model for training, the neural network model can better capture key information, thereby improving the accuracy of the prediction.

[0065] In one feasible implementation, S101-A may specifically include the following sub-steps.

[0066] S101-A1: Determine the initial accuracy score for each of the multiple battery parameters;

[0067] In this embodiment, the BMS will determine the initial accuracy score corresponding to any given battery parameter. It should be noted that a higher initial accuracy score for a battery parameter indicates better battery performance from that parameter's perspective, and a higher accuracy in SOC estimation.

[0068] In its implementation, the BMS quantifies multiple battery parameters from multiple dimensions to obtain the initial accuracy scores for each of the multiple battery parameters.

[0069] Referring to Table 1, an example table of accuracy scores for battery health status among multiple battery parameters is shown.

[0070] Table 1

[0071]

[0072] Where X1 represents the battery health status, which is the ratio between the battery's current capacity and its rated capacity; Y1 represents the initial accuracy score corresponding to the battery health status.

[0073] Referring to Table 2, an example table of accuracy ratings for battery operating temperature among multiple battery parameters is shown.

[0074] Table 2

[0075]

[0076] Where X2 represents the battery operating temperature; Y2 represents the initial accuracy score corresponding to the battery operating temperature.

[0077] Specifically, the operating temperature range of the battery can be set, such as [-30℃, 55℃], and then the initial accuracy score corresponding to the battery operating temperature can be determined based on this operating temperature range and the suitable operating temperature of the battery.

[0078] Referring to Table 3, an example table of accuracy ratings for charge / discharge rates among multiple battery parameters is shown.

[0079] Table 3

[0080]

[0081] Where X3 represents the charge / discharge rate; Y3 represents the initial accuracy score corresponding to the charge / discharge rate.

[0082] Specifically, taking the charging rate as an example, the charging rate range of the battery can be set, such as [0.1C, 5C]. Then, based on this charging rate range and the appropriate charging rate of the battery, the initial accuracy score corresponding to the charging rate can be determined.

[0083] Referring to Table 4, an example table of accuracy scores for the remaining charge correction frequency among multiple battery parameters is shown.

[0084] Table 4

[0085]

[0086] Where X4 represents the remaining battery power correction frequency within a preset time period. When the preset time period is 7 days, its unit can be set to: times / 7 days; Y4 represents the initial accuracy score corresponding to the remaining battery power correction frequency.

[0087] Referring to Table 5, an example table of accuracy scores for the maximum cell temperature difference among multiple battery parameters is shown.

[0088] Table 5

[0089]

[0090] Where X5 represents the maximum cell temperature difference; Y5 represents the initial accuracy score corresponding to the maximum cell temperature difference.

[0091] Specifically, the temperature difference range of the battery can be set, for example [1℃, 6℃]. Then, based on the temperature difference range and the allowable cell temperature difference of the battery, the initial accuracy score corresponding to the maximum cell temperature difference can be determined.

[0092] In this embodiment, by quantifying and standardizing multiple battery parameters, the impact of different battery parameters on the accuracy of remaining power can be compared fairly, thereby improving the accuracy of the accuracy assessment.

[0093] S101-A2: Based on the initial accuracy scores and parameter weights corresponding to each of the multiple battery parameters, determine the weighted accuracy scores corresponding to each of the multiple battery parameters.

[0094] In this embodiment, for any battery parameter, the initial accuracy score is multiplied by the parameter weight corresponding to that battery parameter to obtain the weighted accuracy score. It should be noted that the sum of the parameter weights for multiple battery parameters is 1.

[0095] For example, referring to Table 6, a sample table of weighted accuracy scores for multiple battery parameters is shown.

[0096] Table 6

[0097]

[0098] S101-A3: Determine the accuracy of the current remaining battery power based on the weighted accuracy scores corresponding to multiple battery parameters.

[0099] In this embodiment, the comprehensive accuracy score can be determined first by summing the weighted accuracy scores corresponding to each of the multiple battery parameters, and then the current remaining power accuracy can be calculated based on the comprehensive accuracy score.

[0100] In practice, the current remaining battery power accuracy can be calculated using the following formula.

[0101] SOC 精度 =(1-S 评分 %) / 10(1);

[0102] Among them, SOC 精度 Indicates the precision of the current remaining battery power, S 评分 This indicates the overall accuracy score.

[0103] It should be noted that, based on Formula 1, the remaining battery power accuracy range is [0%, 10%], where 0% represents the highest remaining battery power accuracy and 10% represents the lowest remaining battery power accuracy.

[0104] For example, based on Formula 1, we can obtain an example table of remaining battery power accuracy as shown in Table 7.

[0105] Table 7

[0106]

[0107] In this embodiment, taking the data shown in Table 6 as an example, the comprehensive accuracy score can be calculated as (19+14.25+19+14.25+14.25+14.25=)95. Using Formula 1, the current remaining power accuracy can be calculated as 1% (take 1% if it is less than 1%).

[0108] In this embodiment, since the different effects of various battery parameters on the accuracy of remaining power are taken into account, a weighted summation method is used to integrate the various factors, thereby enabling accurate identification of the current remaining power accuracy.

[0109] In a specific implementation, S101-A3 may also include the following sub-steps.

[0110] S101-A3-1: Determine the comprehensive accuracy score based on the weighted accuracy scores corresponding to multiple battery parameters.

[0111] In this embodiment, the overall accuracy score of the battery can be calculated based on the weighted accuracy scores corresponding to each of the multiple battery parameters.

[0112] S101-A3-2: Among multiple preset scoring intervals, determine the target scoring interval to which the comprehensive accuracy score belongs.

[0113] In this embodiment, to simplify calculations, the BMS presets multiple scoring intervals; different scoring intervals correspond to different accuracy values. Thus, by determining the target scoring interval to which the comprehensive accuracy score belongs, the BMS can quickly determine the corresponding current remaining battery level accuracy.

[0114] S101-A3-3: Determine the accuracy value corresponding to the target scoring interval as the current remaining battery power accuracy.

[0115] In this embodiment, the number of scoring intervals can be set according to actual needs. For example, by reducing the data coverage of each scoring interval and setting more scoring intervals, the accuracy of remaining battery power identification can be improved.

[0116] In one feasible implementation, S102 may specifically include the following sub-steps.

[0117] S102-1: If the current remaining battery power accuracy is within the preset accuracy range, determine the target correction amount to be zero.

[0118] In this embodiment, the preset accuracy range can be set to [3%, 5%], that is, when 3% ≤ SOC 精度 If the remaining battery capacity is ≤5%, it is considered that the accuracy of the remaining battery capacity is within the normal range, and there is no need to correct the initial remaining battery capacity threshold.

[0119] S102-2: If the current remaining power accuracy is greater than the upper limit of the preset accuracy range, determine the target correction amount as the first correction amount.

[0120] In this embodiment, when SOC 精度If the remaining battery level is greater than 5%, the battery's remaining power accuracy is considered low. In this case, the initial remaining power threshold will be adjusted according to a preset first adjustment amount, which increases the initial remaining power threshold. For example, the first adjustment amount can be set to 3%. When the initial remaining power threshold is s, the adjusted target remaining power threshold is s+3%.

[0121] In this embodiment, by increasing the initial remaining charge threshold when the battery's remaining charge accuracy is low, the risk of the battery's true SOC dropping to a dangerous value during use can be effectively avoided.

[0122] S102-3: If the current remaining power accuracy is less than the lower limit of the preset accuracy range, determine the target correction amount as the second correction amount.

[0123] In this embodiment, when SOC 精度 If the remaining battery capacity is less than 3%, it is considered to have a high accuracy. In this case, the initial remaining battery capacity threshold will be corrected according to a preset second correction amount. This first correction amount is used to reduce the initial remaining battery capacity threshold. For example, the second correction amount can be set to -3%. When the initial remaining battery capacity threshold is s, the corrected target remaining battery capacity threshold is s-3%.

[0124] In this embodiment, by reducing the initial remaining power threshold when the battery's remaining power accuracy is high, the battery can output more power, thereby avoiding the excess power from being underutilized.

[0125] In this embodiment, by comparing the current remaining power accuracy with the preset accuracy range, it is possible to quickly determine whether the initial remaining power threshold needs to be corrected, as well as the corresponding correction direction and correction magnitude, thereby achieving dynamic management of battery energy.

[0126] In one feasible implementation, the initial remaining power threshold includes an initial forced charging threshold and / or an initial balancing power threshold; S103 may specifically include the following sub-steps.

[0127] S103-1: Based on the correction amount, the initial forced charging threshold is corrected to obtain the target forced charging threshold.

[0128] It should be noted that the initial forced charging threshold represents the default forced charging threshold set for the battery without considering the accuracy of the battery's remaining charge; the target forced charging threshold is the actual forced charging threshold obtained by correcting the initial forced charging threshold based on the accuracy of the battery's current remaining charge.

[0129] Specifically, the target forced charging threshold is used to indicate when the vehicle's engine will be started to charge the battery if the current remaining battery charge is lower than the target forced charging threshold. In other words, when the vehicle is in pure electric mode, i.e., driven solely by the battery, the remaining battery charge is allowed to drop to the target forced charging threshold at most.

[0130] It should be noted that when the vehicle's intelligent idle charging function is activated, if the BMS detects that the vehicle is parked and the battery's current remaining charge is below the target forced charging threshold, it will also start the engine to charge the battery. This effectively avoids the problem of the vehicle being unable to start due to insufficient battery charge caused by the self-discharge characteristics of the battery after prolonged parking. Users can enable or disable the vehicle's intelligent idle charging function via a mobile device or the in-vehicle terminal.

[0131] In one example, the preset accuracy range is set to [3%, 5%], the initial forced charge threshold can be set to 9%, the first correction is 3%, and the second correction is -3%. When SOC... 精度 If the value is greater than 5%, then the initial forced charging threshold of 9% is corrected according to the first correction amount of 3%, resulting in a target forced charging threshold of 12%; if 3% ≤ SOC 精度 If the SOC is ≤5%, the initial forced charging threshold remains unchanged; when the SOC is ≤5%, the initial forced charging threshold remains unchanged. 精度 If the value is less than 3%, then the initial forced charging threshold of 9% is corrected by the second correction amount of -3%, resulting in a target forced charging threshold of 6%.

[0132] S103-2: Based on the correction amount, the initial balanced power threshold is corrected to obtain the target balanced power threshold.

[0133] It should be noted that the initial balance charge threshold represents the default balance charge threshold set for the battery without considering the accuracy of the battery's remaining charge; the target balance charge threshold is the actual balance charge threshold obtained by correcting the initial balance charge threshold based on the accuracy of the battery's current remaining charge.

[0134] Specifically, the target balance charge threshold is used to indicate the target remaining battery charge level and control the engine to charge the battery accordingly. In other words, the engine will continuously charge the battery until the current remaining battery charge falls below the target balance charge threshold; once the current remaining battery charge reaches the target balance charge threshold, the engine will stop charging.

[0135] In one example, the preset accuracy range is set to [3%, 5%], the initial balanced charge threshold can be set to 20%, the first correction is 3%, and the second correction is -3%. When SOC... 精度If the value is greater than 5%, then the initial balanced charge threshold of 20% is corrected according to the first correction amount of 3%, resulting in a target balanced charge threshold of 23%; if 3% ≤ SOC 精度 If the SOC is ≤5%, the initial equilibrium charge threshold remains unchanged; when the SOC is ≤5%, the initial equilibrium charge threshold remains unchanged. 精度 If the value is less than 3%, then the initial balanced power threshold of 20% is corrected by the second correction amount of -3%, resulting in a target balanced power threshold of 17%.

[0136] In this embodiment, compared to the prior art which sets a single and conservative large threshold for the remaining battery charge, by comprehensively considering various battery parameters that affect the accuracy of the remaining battery charge, accurate identification of the remaining battery charge accuracy can be achieved. Then, based on the actual state of the battery, a suitable target remaining battery charge threshold can be dynamically set. This improves the accuracy of the remaining battery charge to within 3% and lowers the battery's SOC window to 6%. While preventing over-discharge, it allows the battery to output more power, achieving full utilization of battery energy and effectively improving the vehicle's driving range in pure electric mode.

[0137] Secondly, based on the same inventive concept and referring to FIG2, an embodiment of this disclosure provides a vehicle energy management device. The vehicle energy management device 200 includes: an accuracy determination module 201 for determining the current remaining charge accuracy of the battery based on multiple battery parameters; a correction amount determination module 202 for determining a target correction amount based on the current remaining charge accuracy; wherein different remaining charge accuracies correspond to different correction amounts; and a threshold correction module 203 for correcting the initial remaining charge threshold of the battery based on the target correction amount to obtain a target remaining charge threshold; wherein the target remaining charge threshold is used for energy management of the battery.

[0138] In one embodiment of this disclosure, the accuracy determination module 201 includes a first correction amount determination submodule, which is used to determine the accuracy of the current remaining battery power based on multiple battery parameters and the parameter weights corresponding to each of the multiple battery parameters.

[0139] In one embodiment of this disclosure, the accuracy determination module 201 includes a second correction amount determination submodule, which is used to input multiple battery parameters into the accuracy prediction model and output the current remaining power accuracy; wherein, the accuracy prediction model is trained based on sample battery parameters of the battery.

[0140] In one embodiment of this disclosure, the first correction amount determination submodule includes: an initial accuracy score determination unit, used to determine the initial accuracy score corresponding to each of the multiple battery parameters; a weighted accuracy score determination unit, used to determine the weighted accuracy score corresponding to each of the multiple battery parameters based on the initial accuracy score and parameter weight; and a remaining power accuracy determination unit, used to determine the current remaining power accuracy based on the weighted accuracy score corresponding to each of the multiple battery parameters.

[0141] In one embodiment of this disclosure, the remaining power accuracy determination unit includes: a comprehensive accuracy score determination subunit, used to determine a comprehensive accuracy score based on the weighted accuracy scores corresponding to multiple battery parameters; a score interval determination subunit, used to determine the target score interval to which the comprehensive accuracy score belongs among multiple preset score intervals; different score intervals correspond to different accuracy values; and a remaining power accuracy determination subunit, used to determine the accuracy value corresponding to the target score interval as the current remaining power accuracy.

[0142] In one embodiment of this disclosure, multiple battery parameters include battery health status, battery operating temperature, charge / discharge rate, remaining capacity correction frequency, average remaining capacity correction magnitude, and cell difference parameters; the cell difference parameters include maximum cell temperature difference, maximum cell voltage difference, and / or maximum remaining capacity difference.

[0143] In one embodiment of this disclosure, the correction amount determination module 202 includes: a first correction amount determination submodule, configured to determine a target correction amount of zero when the current remaining power accuracy is within a preset accuracy range; a second correction amount determination submodule, configured to determine a target correction amount as a first correction amount when the current remaining power accuracy is greater than the upper limit of the preset accuracy range; the first correction amount is used to increase the initial remaining power threshold; and a third correction amount determination submodule, configured to determine a target correction amount as a second correction amount when the current remaining power accuracy is less than the lower limit of the preset accuracy range; the second correction amount is used to decrease the initial remaining power threshold.

[0144] In one embodiment of this disclosure, the initial remaining power threshold includes an initial forced charging threshold and / or an initial balancing power threshold; the threshold correction module 203 includes: a first threshold correction submodule, used to correct the initial forced charging threshold based on a correction amount to obtain a target forced charging threshold; and a second threshold correction submodule, used to correct the initial balancing power threshold based on a correction amount to obtain a target balancing power threshold; wherein, the target forced charging threshold is used to indicate that when the current remaining power of the battery is lower than the target forced charging threshold, the vehicle's engine should be started to charge the battery; and the target balancing power threshold is used to indicate that the engine should be controlled to charge the battery using the target balancing power threshold as the target remaining power of the battery.

[0145] It should be noted that the specific implementation of the vehicle energy management device 200 in this disclosure embodiment refers to the specific implementation of the vehicle energy management method proposed in the first aspect of the present disclosure embodiment, and will not be repeated here.

[0146] Thirdly, based on the same inventive concept, embodiments of this disclosure provide a computer-readable storage medium having an executable program stored thereon, which, when executed by a processor, implements the vehicle energy management method proposed in the first aspect of this disclosure.

[0147] It should be noted that the specific implementation of the computer-readable storage medium in the embodiments of this disclosure refers to the specific implementation of the vehicle energy management method proposed in the first aspect of the embodiments of this disclosure, and will not be repeated here.

[0148] Fourthly, referring to FIG3, based on the same inventive concept, the present disclosure provides a vehicle 300, including: a memory 301 for storing an executable program; a processor 302; when the executable program is executed by the processor 302, the vehicle energy management method proposed in the first aspect of the present disclosure is implemented.

[0149] It should be noted that the specific implementation of the vehicle 300 in this disclosure embodiment refers to the specific implementation of the vehicle energy management method proposed in the first aspect of the present disclosure embodiment, and will not be repeated here.

[0150] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, apparatus, or computer program products. Therefore, embodiments of the present invention can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of the present invention can take the form of computer program products implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0151] Embodiments of the present invention are described with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, create means for implementing the functions specified in one or more blocks of the flowchart illustrations and / or one or more blocks of the block diagrams.

[0152] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means that implement the functions specified in one or more flowcharts and / or one or more block diagrams.

[0153] These computer program instructions may also be loaded onto a computer or other programmable data processing terminal equipment to cause a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, such that the instructions, which execute on the computer or other programmable terminal equipment, provide steps for implementing the functions specified in one or more flowcharts and / or one or more block diagrams.

[0154] Although preferred embodiments of the present invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the present invention.

[0155] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes the element.

[0156] The present invention has provided a detailed description of a vehicle energy management method, storage medium, and vehicle. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, those skilled in the art will recognize that there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A vehicle energy management method, wherein, The method includes: The current remaining battery power is determined with accuracy based on multiple battery parameters. Based on the current remaining battery power accuracy, a target correction amount is determined; wherein, different remaining battery power accuracies correspond to different correction amounts; Based on the target correction amount, the initial remaining power threshold of the battery is corrected to obtain the target remaining power threshold; wherein, the target remaining power threshold is used for energy management of the battery.

2. The vehicle energy management method according to claim 1, wherein, Based on multiple battery parameters of the battery, the current remaining charge accuracy of the battery is determined, including: The accuracy of the current remaining battery power is determined based on the multiple battery parameters and their respective weights.

3. The vehicle energy management method according to claim 1, wherein, Based on multiple battery parameters of the battery, the current remaining charge accuracy of the battery is determined, including: The multiple battery parameters are input into the accuracy prediction model, and the current remaining power accuracy is output; wherein, the accuracy prediction model is trained based on the sample battery parameters of the battery.

4. The vehicle energy management method according to claim 2, wherein, Based on the multiple battery parameters and their respective weights, the accuracy of determining the current remaining battery capacity is as follows: Determine the initial accuracy score corresponding to each of the multiple battery parameters; Based on the initial accuracy score and parameter weight corresponding to each of the multiple battery parameters, the weighted accuracy score corresponding to each of the multiple battery parameters is determined. The accuracy of the current remaining battery power is determined based on the weighted accuracy scores corresponding to multiple battery parameters.

5. The vehicle energy management method according to claim 4, wherein, Determining the current remaining battery power accuracy based on the weighted accuracy scores corresponding to multiple battery parameters includes: determining a comprehensive accuracy score based on the sum of the weighted accuracy scores corresponding to the multiple battery parameters, and then calculating the current remaining battery power accuracy based on the comprehensive accuracy score. The accuracy of the current remaining battery power is calculated using the following formula: SOC 精度 =(1-S 评分 %) / 10(1); Among them, SOC 精度 Indicates the precision of the current remaining battery power, S 评分 This indicates the overall accuracy score.

6. The vehicle energy management method according to claim 4, wherein, The accuracy of the current remaining battery capacity is determined based on a weighted accuracy score corresponding to multiple battery parameters, including: A comprehensive accuracy score is determined based on the weighted accuracy scores corresponding to multiple battery parameters. Among multiple preset scoring intervals, the target scoring interval to which the comprehensive accuracy score belongs is determined; different scoring intervals correspond to different accuracy values. The accuracy value corresponding to the target scoring interval is determined as the accuracy of the current remaining battery power.

7. The vehicle energy management method according to claim 3, wherein, The accuracy prediction model is trained as follows: Sample battery parameters of the battery are obtained, the sample battery parameters including the battery's accuracy label; an initial neural network model is trained using the sample battery parameters to obtain the accuracy prediction result output by the initial neural network model; then, based on the accuracy prediction result and the accuracy label, a loss function value is calculated, and the network parameters of the initial neural network model are iteratively updated based on the loss function value until the initial neural network model meets the training cutoff condition, thus obtaining the accuracy prediction model.

8. The vehicle energy management method according to claim 7, wherein, The sample battery parameters are sample weighted battery parameters, which are determined based on multiple historical battery parameters and their respective parameter weights.

9. The vehicle energy management method according to any one of claims 1-8, wherein, The multiple battery parameters include battery health status, battery operating temperature, charge / discharge rate, remaining capacity correction frequency, average remaining capacity correction magnitude, and cell difference parameters; the cell difference parameters include maximum cell temperature difference, maximum cell voltage difference, and / or maximum remaining capacity difference.

10. The vehicle energy management method according to claim 9, wherein, The battery parameters also include deep discharge frequency and / or battery type.

11. The vehicle energy management method according to claim 1, wherein, Based on the current remaining battery power accuracy, determine the target correction amount, including: If the current remaining battery power accuracy is within a preset accuracy range, the target correction amount is determined to be zero; If the current remaining battery power accuracy is greater than the upper limit of the preset accuracy range, the target correction amount is determined as the first correction amount; the first correction amount is used to increase the initial remaining battery power threshold. If the current remaining battery power accuracy is less than the lower limit of the preset accuracy range, the target correction amount is determined as the second correction amount; the second correction amount is used to reduce the initial remaining battery power threshold.

12. The vehicle energy management method according to claim 1, wherein, The initial remaining power threshold includes an initial forced charging threshold and / or an initial balancing power threshold; Based on the target correction amount, the initial remaining battery capacity threshold is corrected to obtain the target remaining battery capacity threshold, including: Based on the correction amount, the initial forced charging threshold is corrected to obtain the target forced charging threshold; and / or, Based on the correction amount, the initial balanced power threshold is corrected to obtain the target balanced power threshold; Wherein, the target forced charging threshold is used to indicate that when the current remaining charge of the battery is lower than the target forced charging threshold, the vehicle's engine should be started to charge the battery; the target balanced charge threshold is used to indicate that the engine should be controlled to charge the battery with the target balanced charge threshold as the target remaining charge of the battery.

13. A computer-readable storage medium having an executable program stored thereon, wherein, When the executable program is executed by the processor, it implements the vehicle energy management method as described in any one of claims 1-12.

14. A vehicle, wherein, include: Memory, used to store executable programs; processor; When the executable program is executed by the processor, the vehicle energy management method as described in any one of claims 1-12 is implemented.

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