Battery control method, vehicle, and storage medium

Abstract

The application discloses a battery control method, a vehicle and a storage medium, relates to the technical field of vehicles, and the battery control method comprises the following steps: in response to voltage sampling abnormality of a battery, determining accumulated discharge capacity and an operating state parameter of the battery under the voltage sampling abnormality; inputting the operating state parameter into a preset correction coefficient estimation model to obtain a comprehensive correction coefficient; inputting the comprehensive correction coefficient and the operating state parameter into a preset capacity prediction model to obtain a current safety capacity of the battery; determining a current residual capacity of the battery according to the accumulated discharge capacity and the current safety capacity, and executing a battery control strategy corresponding to the current residual capacity. The application can avoid premature cut-off of power output in the case of false failure of battery voltage sampling, and maintain the normal driving capability of the vehicle under the premise of ensuring driving safety.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, and more particularly to a battery control method, a vehicle, and a storage medium. Background Technology

[0002] The power battery pack is the core energy storage component of an electric vehicle, typically composed of multiple strings of individual battery cells connected in series to meet the vehicle's power supply needs. To ensure the battery operates within a safe voltage range, the Battery Management System (BMS) needs to monitor the voltage of each individual cell in the string in real time. In current technical solutions, the BMS mainly relies on AFE (Analog Front End) chips, sampling harnesses, connectors, and daisy-chain communication to complete the real-time acquisition and reporting of the voltage of each individual battery cell in the string.

[0003] However, during actual vehicle operation, factors such as road vibration, oxidation of sampling terminals, loose connectors, electromagnetic communication interference, and micro-wear of wiring harnesses can easily lead to the loss of voltage signal acquisition for single or multiple strings of individual battery cells. Such faults may be pseudo-failures of the acquisition channel, meaning the cell itself is not damaged, the battery still has sufficient remaining charge, and the faults are often intermittent, usually recovering automatically within a short time. However, because the BMS lacks effective individual cell voltage input, it cannot determine whether the string is undervoltage using conventional voltage thresholds. Therefore, traditional control strategies, for safety, typically involve directly cutting off discharge and prohibiting power output, resulting in the vehicle being unable to operate normally despite having power, severely impacting the user experience. Summary of the Invention

[0004] The main objective of this application is to provide a battery control method, a vehicle, and a storage medium, which aims to solve the technical problem of how to avoid prematurely cutting off power output in the event of a false failure in battery voltage sampling, and to maintain the normal driving capability of the vehicle while ensuring driving safety.

[0005] To achieve the above objectives, this application proposes a battery control method, the battery control method comprising: In response to an abnormal voltage sampling of the battery, the cumulative discharge capacity and operating status parameters of the battery under the abnormal voltage sampling condition are determined; The operating status parameters are input into a preset correction coefficient prediction model to obtain a comprehensive correction coefficient. The comprehensive correction coefficient and the operating status parameters are input into a preset capacity prediction model to obtain the current safe capacity of the battery. Based on the cumulative discharge capacity and the current safe capacity, the current remaining capacity of the battery is determined, and the battery control strategy corresponding to the current remaining capacity is executed.

[0006] In one embodiment, the correction coefficient prediction model includes: a single-factor coefficient calculation module and a comprehensive correction coefficient calculation module; The step of inputting the operating status parameters into a preset correction coefficient prediction model to obtain the comprehensive correction coefficient includes: The single-factor coefficient calculation module processes the operating status parameters to obtain at least one of the following: temperature correction coefficient, health decay correction coefficient, mileage correction coefficient, and rate discharge correction coefficient. The comprehensive correction coefficient is obtained by processing at least one of the temperature correction coefficient, the health decay correction coefficient, the mileage correction coefficient, and the rate discharge correction coefficient through the comprehensive correction coefficient calculation module. The temperature correction coefficient is obtained based on the ambient temperature in the operating status parameters. The battery health degradation correction coefficient is obtained based on the battery health in the operating status parameters. The mileage correction factor is obtained based on the sampled abnormal pre-charge state in the operating status parameters; The discharge rate correction factor is obtained based on the discharge current rate in the operating status parameters.

[0007] In one embodiment, the single-factor coefficient calculation module includes: a mileage correction coefficient mapping unit, and the step of processing the operating status parameters through the single-factor coefficient calculation module includes: The remaining driving range of the battery is determined by the mileage correction coefficient mapping unit based on the sampled abnormal state of charge and the rated driving range of the battery, and the mileage correction coefficient is obtained by mapping based on the remaining driving range.

[0008] In one embodiment, the single-factor coefficient calculation module includes: a rate discharge correction coefficient mapping unit, and the step of processing the operating state parameters through the single-factor coefficient calculation module includes: The rate correction coefficient mapping unit determines the rate change rate of the battery based on the discharge current rate, determines the aggressive driving style level based on the rate change rate, and determines the rate correction coefficient based on the aggressive driving style level. The rate of change of the multiplier is negatively correlated with the degree of aggressiveness of the driving style represented by the aggressiveness level of the driving style.

[0009] In one embodiment, the step of executing the battery control strategy corresponding to the current remaining capacity includes: If the current remaining capacity is greater than a preset first capacity threshold, the first control strategy in the battery control strategy is executed; If the current remaining capacity is less than or equal to the first capacity threshold and greater than the preset second capacity threshold, the second control strategy in the battery control strategy is executed. If the current remaining capacity is less than or equal to the second capacity threshold and greater than the preset third capacity threshold, the third control strategy in the battery control strategy is executed. If the current remaining capacity is less than or equal to the third capacity threshold, the fourth control strategy in the battery control strategy is executed; Wherein, the first capacity threshold is greater than the second capacity threshold, and the second capacity threshold is greater than the third capacity threshold; The performance release rate of the first control strategy is greater than that of the second control strategy, the performance release rate of the second control strategy is greater than that of the third control strategy, and the performance release rate of the third control strategy is greater than that of the fourth control strategy.

[0010] In one embodiment, at least one of the first capacity threshold, the second capacity threshold, and the third capacity threshold is determined based on the battery's rated capacity and a state correction factor, wherein the state correction factor is determined based on the operating state parameters.

[0011] In one embodiment, the method further includes: Obtain the current open-circuit voltage of the battery corresponding to the current remaining capacity; Determine the static voltage drop of the battery based on the current open-circuit voltage; The current theoretical voltage of the battery is determined based on its current current, DC internal resistance, voltage before sampling anomaly, and static voltage drop. If the current theoretical voltage is less than the preset undervoltage threshold, the fifth control strategy in the battery control strategy is executed.

[0012] In one embodiment, the method further includes: In response to the recovery of the battery's voltage sampling, the current sampled voltage of the battery is obtained; If the difference between the current sampled voltage and the current theoretical voltage is greater than a preset deviation threshold, the step of determining the cumulative discharge capacity of the battery under the abnormal voltage sampling condition, and subsequent steps, are performed.

[0013] In one embodiment, after the step of obtaining the comprehensive correction coefficient, the method further includes: Determine whether the comprehensive correction coefficient is greater than or equal to a preset coefficient threshold; If the comprehensive correction coefficient is greater than or equal to the coefficient threshold, the step of inputting the comprehensive correction coefficient and the operating status parameters into a preset capacity prediction model, and subsequent steps, are performed. If the overall correction coefficient is less than the coefficient threshold, the sixth control strategy in the battery control strategy is executed.

[0014] In addition, to achieve the above objectives, this application also proposes a vehicle comprising: a processor, a memory, and a battery control program stored in the memory and executable on the processor, wherein the battery control program, when executed, implements the steps of the battery control method as described above.

[0015] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the battery control method described above.

[0016] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the battery control method described above.

[0017] One or more technical solutions proposed in this application have at least the following technical effects: In this embodiment, when the battery voltage sampling is abnormal, the cumulative discharge capacity and operating state parameters of the battery are determined to provide a reliable data basis for matching the subsequent battery control strategy. Then, a comprehensive correction coefficient is estimated based on the operating state parameters using a preset correction coefficient prediction model. Then, the current safe capacity of the battery is predicted using a preset capacity prediction model, combined with the comprehensive correction coefficient and operating state parameters. Since the comprehensive correction coefficient can correct the output of the capacity prediction model, an accurate prediction of the current safe capacity of the battery is achieved. Then, the current remaining capacity of the battery is determined based on the cumulative discharge capacity and the current safe capacity to reflect the battery's safety margin. Based on this, the corresponding battery control strategy is executed to achieve a battery control method that matches the current remaining capacity of the battery. Thus, in the case of false voltage sampling failure and the battery cell still having power, it avoids the sudden vehicle stoppage caused by the traditional strategy of directly cutting off power, which affects the user experience, and avoids over-discharge damage to the battery cell through the battery control strategy, achieving a balance between safety and availability. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0019] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating the first embodiment of the battery control method of this application. Figure 1 ; Figure 2 This is a flowchart illustrating the first embodiment of the battery control method of this application. Figure 2 ; Figure 3 This is a flowchart illustrating the second embodiment of the battery control method of this application; Figure 4 This is a flowchart illustrating the third embodiment of the battery control method of this application; Figure 5 This is a schematic diagram of the device structure of the hardware operating environment involved in the battery control method of this application.

[0021] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0022] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0023] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0024] The power battery pack is the core energy storage component of an electric vehicle, typically composed of multiple strings of individual battery cells connected in series to meet the vehicle's power supply needs. To ensure the battery operates within a safe voltage range, the Battery Management System (BMS) needs to monitor the voltage of each individual cell in real time. In current technologies, the BMS primarily relies on AFE (Analog Front End) chips, sampling harnesses, connectors, and daisy-chain communication to collect and report the voltage of each individual battery cell in real time. However, during actual vehicle operation, factors such as road vibration, oxidation of sampling terminals, loose connectors, electromagnetic communication interference, and wear and tear on the wiring harness can easily lead to the loss of voltage signals from single or multiple strings of individual cells. However, such failures may be pseudo-failures of the acquisition channel, meaning the cell itself is not damaged, the battery still has sufficient remaining charge, and the failures are often intermittent and usually recover automatically within a short time. However, since the BMS lacks an effective individual cell voltage input, it cannot determine whether the string is undervoltage by using the conventional voltage threshold. Therefore, in order to ensure safety, the traditional control strategy usually directly takes protective measures such as cutting off discharge and prohibiting power output, which causes the vehicle to be unable to drive normally even though it has power, seriously affecting the user experience.

[0025] The main solution of this application embodiment is as follows: When the battery voltage sampling is abnormal, the cumulative discharge capacity and operating state parameters of the battery are determined to provide a reliable data basis for the matching of subsequent battery control strategies; then, a comprehensive correction coefficient is estimated based on the operating state parameters through a preset correction coefficient prediction model; then, the current safe capacity of the battery is predicted by a preset capacity prediction model in combination with the comprehensive correction coefficient and the operating state parameters; since the comprehensive correction coefficient can correct the output of the capacity prediction model accordingly, the accurate prediction of the current safe capacity of the battery is achieved; then, the current remaining capacity of the battery is determined based on the cumulative discharge capacity and the current safe capacity to reflect the safety margin of the battery, and the corresponding battery control strategy is executed accordingly to achieve a battery control method that matches the current remaining capacity of the battery. Thus, in the case of false voltage sampling failure and the battery cell still having power, it avoids the sudden vehicle stop caused by the traditional strategy of directly cutting off power, which affects the user experience, and avoids over-discharge damage to the battery cell through the battery control strategy, achieving a balance between safety and availability.

[0026] It should be noted that the executing entity in this embodiment may be a vehicle, a controller on the vehicle, or an electronic device associated with the vehicle.

[0027] Reference Figure 1 This is a flowchart illustrating the first embodiment of the battery control method of this application.

[0028] In this embodiment, the battery control method includes steps S10 to S30: Step S10: In response to the abnormal voltage sampling of the battery, determine the cumulative discharge capacity and operating status parameters of the battery under the abnormal voltage sampling condition.

[0029] In one feasible embodiment, to achieve safe management and precise control of the battery, AFE (Analog Front End) chips, sampling harnesses, connectors, and daisy-chain communication are typically used to collect and report the voltage of each individual battery cell in the vehicle in real time, thereby achieving real-time monitoring of the voltage of each individual battery cell in the string. However, during actual vehicle operation, factors such as road vibration, oxidation of sampling terminals, loose connectors, electromagnetic communication interference, and micro-motion wear of the harness can easily lead to the loss of voltage signal acquisition for one or more individual cells in the string. When voltage signal acquisition is lost, it can be identified as a voltage sampling anomaly, meaning that the battery management system cannot obtain a valid individual cell voltage value at the expected sampling time. However, this anomaly may be a false failure of the acquisition channel, meaning that the cell itself is not damaged and there is still usable power inside the battery. To avoid directly taking protective measures such as cutting off discharge or prohibiting power output, which would cause the vehicle to be unable to drive normally despite having power, affecting the user experience, this embodiment of the application determines the cumulative discharge capacity of the battery under the voltage sampling anomaly condition and obtains the battery's operating status parameters.

[0030] Optionally, the vehicle's AFE (Analog Front End) chip will have a built-in voltage diagnostic function. It will perform real-time self-testing on the voltage signals of each sampling channel and report the diagnostic results to the application layer of the battery management system. Therefore, the battery management system can determine whether the current voltage sampling is normal based on the diagnostic results.

[0031] Optionally, the cumulative discharge capacity refers to the total capacity that the battery has cumulatively released through discharge during the voltage sampling anomaly period, and its unit is ampere-hour (Ah), which is used to characterize the electrochemical capacity consumed by the battery during this period.

[0032] Optionally, the steps for determining the cumulative discharge capacity include: dynamically acquiring the battery's discharge current; and discretizing and integrating the discharge current over a preset sampling period to obtain the cumulative discharge capacity.

[0033] Optionally, the steps for determining the cumulative discharge capacity include: at the moment when the voltage sampling anomaly is triggered, resetting the integral counter used for the cumulative discharge capacity to zero, that is, taking this moment as the integration starting point, setting the initial cumulative value to zero, and acquiring the battery discharge current in real time, discretizing the discharge current with a preset sampling period, and using the product of the current value collected in the current sampling period and the sampling period as the discharge capacity increment in the current sampling period; after each sampling period is completed, the discharge capacity increment is added to the cumulative value at the end of the previous sampling period to obtain the cumulative discharge capacity at the current moment, thereby realizing continuous tracking and updating of the cumulative discharge capacity during the voltage sampling anomaly period.

[0034] Optionally, the mathematical expression corresponding to the process of determining the cumulative discharge capacity Ah is: Ah = ∫I(t)dt; Where I(t) is the discharge current at time t, and dt is the sampling period.

[0035] Optionally, the direction of the discharge current is positive with the discharge direction as the positive direction, and the charging current does not participate in the accumulation of the cumulative discharge capacity, or the charging current is included as a negative value when accumulating. The specific setting depends on the actual application scenario, and this application embodiment does not impose specific restrictions on this.

[0036] Optionally, since the current sampling channel and the voltage sampling channel are hardware-independent, an accurate current value can still be obtained based on the current sampling channel during the period when the voltage sampling signal is lost, so as to perform ampere-hour integration and provide a reliable data basis for subsequent safety judgment and control strategies.

[0037] Optionally, the operating status parameter refers to a multi-dimensional set of information that can characterize the battery's current working environment, its own health status, and / or usage conditions. It is used to predict the upper limit of the battery's capacity that can be safely released at the current moment and under the current operating conditions, i.e., the current safe capacity.

[0038] Optionally, the operating status parameters include at least one of the following: ambient temperature of the battery, battery health, state of charge before sampling anomalies, and discharge current rate.

[0039] Optionally, the ambient temperature of the battery directly affects the ionic conductivity of the electrolyte and the electrochemical reaction rate. For example, at low temperatures, the ion mobility decreases and the internal resistance increases, causing the terminal voltage to reach the cutoff voltage earlier during discharge, thereby narrowing the safe usable capacity window of the battery. Therefore, ambient temperature is one of the key parameters for correcting capacity prediction results.

[0040] Optionally, battery health (SOH) reflects the degree of capacity decay caused by the loss of active materials, lithium ion loss and / or increase in internal resistance during long-term use. Under the same state of charge, the discharge capacity of an aged battery is lower than that of a new battery. Therefore, battery health can be introduced when predicting the current safe capacity.

[0041] Optionally, the state of charge before the sampling anomaly (i.e., the initial state of charge of the fault) serves as the initial remaining charge reference of the battery when the voltage sampling anomaly is triggered. It determines the starting boundary of the current safe capacity prediction, that is, the total capacity that can be theoretically released from this state of charge to the discharge cutoff voltage.

[0042] Optionally, the discharge current rate characterizes the current discharge rate of the battery. When the discharge rate is high, the voltage drop caused by the battery polarization internal resistance increases, and the terminal voltage is pulled down rapidly, causing the battery to reach the undervoltage protection point earlier, thereby narrowing the actual safe discharge capacity window. Therefore, the discharge current rate determines the dynamic range of safe capacity.

[0043] Optionally, the operating status parameters can assess the upper limit of the battery's safe capacity under the current state from different dimensions, thereby achieving an accurate prediction of the battery's current safe capacity and providing a reliable basis for subsequent remaining capacity judgment and hierarchical control strategies.

[0044] Step S20: Input the operating status parameters into the preset correction coefficient prediction model to obtain the comprehensive correction coefficient.

[0045] In one feasible embodiment, in order to improve the accuracy of the prediction of the current safety capacity, the operating status parameters can be first input into a preset correction coefficient prediction model to obtain a comprehensive correction coefficient, wherein the comprehensive correction coefficient is used to comprehensively correct the safety capacity.

[0046] Optionally, the comprehensive correction coefficient can be a quantified product of the combined impact of various factors on the battery's usable capacity under the current operating conditions, i.e.: k = k1 × k2 × k3 × ... × kn; Where k is the comprehensive correction coefficient, and k1 to kn represent correction coefficients for a single dimension. The obtained comprehensive correction coefficient is used to characterize the comprehensive reduction of battery safety capacity under the combined effect of multiple factors.

[0047] Optionally, the correction coefficient for a single dimension can reflect the independent impact of a single-dimensional factor (e.g., ambient temperature, battery health, state of charge before sampling anomalies, discharge current rate, etc.) on the safe capacity. The correction coefficient for a single dimension can be determined based on the operating state parameters through a correction coefficient prediction model.

[0048] Optionally, the correction coefficient prediction model can be a machine learning model trained on a big data platform. For example, the correction coefficient prediction model can be trained by a cloud-based big data platform by aggregating operational data from the entire lifecycle of tens of millions of power batteries of the same model. The data collection dimensions include, but are not limited to: cell model, cycle count, battery health, ambient temperature, discharge current rate, sampled abnormal state of charge, historical charge and discharge conditions, and the maximum discharge capacity corresponding to the cutoff voltage. Through training with the above multi-dimensional data, the correction coefficient prediction model can learn the mapping relationship between different operating state parameters and the comprehensive correction coefficient, thereby outputting the corresponding comprehensive correction coefficient after inputting the current operating state parameters.

[0049] Optionally, the correction coefficient prediction model can be deployed on a cloud server, where the cloud performs the calculation and then sends the comprehensive correction coefficient to the vehicle. Alternatively, it can be deployed directly in the vehicle's local battery management system, where the vehicle performs the calculation offline. This application embodiment does not impose any specific limitations on this.

[0050] Step S30: Input the comprehensive correction coefficient and operating status parameters into the preset capacity prediction model to obtain the current safe capacity of the battery.

[0051] In one feasible embodiment, in order to obtain the current safe capacity of the battery, a comprehensive correction coefficient and operating status parameters are input into a preset capacity prediction model, and the current safe capacity (A_safe) of the battery is obtained based on the output of the capacity prediction model.

[0052] Optionally, the capacity prediction model is used to predict the initial safe capacity based on the operating status parameters, and to correct the initial safe capacity using a comprehensive correction coefficient, ultimately outputting the current safe capacity.

[0053] Optionally, the capacity prediction model includes: an initial capacity estimation module and a correction module; the initial capacity estimation module determines the theoretical capacity that the battery can release from the current state of charge to the discharge cutoff voltage under the current state based on the operating state parameters, as the initial safe capacity; the correction module multiplies the initial safe capacity by a comprehensive correction coefficient to obtain the corrected current safe capacity and outputs it.

[0054] Optionally, the initial capacity estimation module can adopt a hybrid modeling strategy that combines a mechanistic model and a data-driven model. When the sampled abnormal state of charge is within a preset battery plateau region, capacity estimation is performed primarily by the equivalent circuit mechanistic unit; when the sampled abnormal state of charge is outside the battery plateau region, capacity estimation is performed primarily by the data-driven unit; the outputs of the two units are fused according to preset weights to obtain the initial safe capacity.

[0055] Optionally, the capacity prediction model and the correction coefficient prediction model can be two functional sub-modules in the same large model, or they can be two independent models. This application does not limit this.

[0056] Optionally, when the capacity prediction model and the correction factor prediction model are two functional sub-modules in the same large model, the input of the large model is the operating status parameters, and the two functional branches of correction factor prediction and capacity prediction are executed sequentially inside, and the output is the current safe capacity.

[0057] Optionally, when the capacity prediction model and the correction factor prediction model are two independent models, the correction factor prediction model and the capacity prediction model can be deployed in the same or different locations. For example, the correction factor prediction model can be deployed in the cloud, and the capacity prediction model can be deployed locally on the vehicle. The two can exchange data through a data interface.

[0058] Optionally, whenever a vehicle experiences a voltage sampling anomaly, the entire lifecycle data of the fault can be automatically packaged and uploaded to the cloud. The cloud will then import the new fault samples into the training dataset, revise the coefficient prediction model and / or capacity prediction model, and distribute the updated lightweight model to the vehicle.

[0059] Step S40: Determine the current remaining capacity of the battery based on the cumulative discharge capacity and the current safe capacity, and execute the battery control strategy corresponding to the current remaining capacity.

[0060] In one feasible embodiment, the difference between the cumulative discharge capacity (Ah) and the current safe capacity (A_safe) is calculated as the current remaining capacity (A_remain) of the battery, and the battery control strategy corresponding to the current remaining capacity is obtained. The battery control strategy is then executed to realize a battery control method that matches the current remaining capacity of the battery.

[0061] In one feasible embodiment, the battery control method further includes: in response to the duration of abnormal voltage sampling reaching a preset calibration threshold, controlling the vehicle's battery to power down and / or prohibiting discharge.

[0062] In one feasible embodiment, to avoid safety hazards caused by continuous discharge due to permanent hardware damage, a preset calibration threshold can be set (e.g., the calibration threshold is determined based on the duration of two discharge cycles). If the duration of abnormal voltage sampling reaches the preset calibration threshold, it indicates that the abnormality is likely caused by irreversible permanent hardware damage such as wiring harness open circuit or AFE channel burnout, which is difficult to recover on its own. To prevent the battery from over-discharging, damaging the cells, or causing safety accidents due to continuous discharge without effective voltage monitoring, the vehicle's battery high voltage is controlled to be reduced and / or discharge is prohibited, thus providing a safety protection logic fallback. If the duration of abnormal voltage sampling does not reach the preset calibration threshold, since it is likely due to a momentary acquisition failure caused by recoverable factors such as vehicle driving vibration, terminal oxidation, loose connectors, or electromagnetic communication interference, step S10 and subsequent steps are executed. In this way, by distinguishing voltage sampling anomalies into two categories, permanent hardware failures and recoverable false failures, and adopting two differentiated handling strategies, namely, fallback power-down and fault-tolerant discharge, safety can be ensured when there is real hardware failure, while maintaining the vehicle's ability to continue driving in the event of a false failure. This avoids the problems of false power-down protection and user experience degradation caused by uniformly implementing power-down protection, thus achieving a balance between safety and availability.

[0063] For example, refer to Figure 2 The battery control method includes: Step A101, determining the voltage sampling status through the AFE chip; if the voltage sampling is abnormal, proceed to Step A102. Step A102, determining whether the duration of the abnormal voltage sampling is less than a calibrated threshold; if so, proceed to Step A103; otherwise, proceed to Step B103. Step A103, determining the battery's cumulative discharge capacity and operating status parameters under abnormal voltage sampling conditions. Step A104, inputting the operating status parameters into a preset correction coefficient prediction model to obtain a comprehensive correction coefficient; inputting the comprehensive correction coefficient and operating status parameters into a preset capacity prediction model to obtain the battery's current safe capacity. Step A105, determining the battery's current remaining capacity based on the cumulative discharge capacity and current safe capacity. Step A106, executing the battery control strategy corresponding to the current remaining capacity. Step B103, controlling the vehicle's battery to power down at high voltage and / or prohibiting discharge.

[0064] In this embodiment, when the battery voltage sampling is abnormal, the cumulative discharge capacity and operating state parameters of the battery are determined, providing a reliable data foundation for matching the subsequent battery control strategy. Then, a comprehensive correction coefficient is estimated based on the operating state parameters using a preset correction coefficient prediction model. Subsequently, the current safe capacity of the battery is predicted using a preset capacity prediction model, combined with the comprehensive correction coefficient and operating state parameters. Since the comprehensive correction coefficient can correct the output of the capacity prediction model, an accurate prediction of the current safe capacity of the battery is achieved. Then, the current remaining capacity of the battery is determined based on the cumulative discharge capacity and the current safe capacity to reflect the battery's safety margin. Based on this, a corresponding battery control strategy is executed to achieve a battery control method that matches the current remaining capacity of the battery. Thus, in the case of a false voltage sampling failure and the battery cell still having charge, it avoids the sudden vehicle stoppage caused by the traditional strategy of directly cutting off power, which affects the user experience, and avoids over-discharge damage to the battery cell through the battery control strategy, achieving a balance between safety and availability.

[0065] Based on the first embodiment described above, a second embodiment of the positioning method of this application is proposed. In this embodiment, referring to... Figure 3 The correction coefficient prediction model includes: a single-factor coefficient calculation module and a comprehensive correction coefficient calculation module; step S20, inputting the running status parameters into the preset correction coefficient prediction model to obtain the comprehensive correction coefficient includes steps S21~S22: Step S21: The single-factor coefficient calculation module processes the operating status parameters to obtain at least one of the following: temperature correction coefficient, health attenuation correction coefficient, mileage correction coefficient, and rate discharge correction coefficient.

[0066] Among them, the temperature correction coefficient is obtained from the ambient temperature in the operating status parameters; the health degradation correction coefficient is obtained from the battery health in the operating status parameters; the mileage correction coefficient is obtained from the sampled abnormal pre-charge state in the operating status parameters; and the rate discharge correction coefficient is obtained from the discharge current rate in the operating status parameters.

[0067] In one feasible embodiment, the correction coefficient prediction model includes: a single-factor coefficient calculation module and a comprehensive correction coefficient calculation module. The single-factor coefficient calculation module is used to process the operating status parameters to obtain single-factor coefficients of at least one dimension. The single-factor coefficients include at least one of the following: temperature correction coefficient, health decay correction coefficient, mileage correction coefficient, and rate discharge correction coefficient.

[0068] Optionally, the single-factor coefficient calculation module may further include multiple-dimensional mapping units, each of which is used to process the running state parameters of different dimensions and independently map to obtain the corresponding single-factor coefficients.

[0069] Optionally, the single-factor coefficient calculation module includes a temperature correction coefficient mapping unit, which is used to map the corresponding temperature correction coefficient according to the ambient temperature in the operating status parameters through a preset temperature-coefficient mapping relationship.

[0070] Optionally, the temperature-coefficient mapping relationship can be referred to Table 1 below. In low-temperature environments, the viscosity of the electrolyte inside the cell increases, the ionic conductivity decreases, the electrochemical reaction rate slows down, and the internal resistance of the battery increases significantly. This causes the terminal voltage to reach the cutoff voltage earlier during discharge, and the usable capacity can be reduced accordingly. Therefore, as the ambient temperature decreases, the temperature correction coefficient decreases accordingly to reflect the reduction effect of low temperature on the safe usable capacity.

[0071] Table 1

[0072] Optionally, to more accurately capture this dynamic temperature rise effect, the temperature correction coefficient mapping unit can also be dynamically adjusted in conjunction with the current driving scenario. For example, it can determine the remaining driving range of the battery and estimate the temperature rise trend of the battery during continuous discharge based on the current ambient temperature and the remaining driving range. The temperature correction coefficient is then adjusted according to the temperature rise trend. That is, if the current ambient temperature is low but the remaining driving range is long, and the battery temperature is expected to gradually rise to a higher range during discharge, the temperature correction coefficient is appropriately increased to predict the usable capacity recovery space after the temperature rise. Conversely, if the current temperature is low and the remaining driving range is short, and the expected temperature rise during discharge is limited, the low temperature reduction is maintained. In this way, by introducing the prediction of the temperature rise trend and combining it with the judgment of driving distance, the safe capacity can be adaptively adjusted in the early stage of a fault.

[0073] Optionally, the single-factor coefficient calculation module includes a health coefficient mapping unit, which is used to map the battery health status in the operating status parameters to obtain the health degradation correction coefficient through a preset health-coefficient mapping relationship.

[0074] Optionally, the health status-coefficient mapping relationship can be referenced in Table 2 below. As the number of charge-discharge cycles increases, the active materials inside the cell gradually deteriorate, lithium-ion loss intensifies, and internal resistance continuously increases, leading to a gradual decline in battery health. Under the same state of charge, the actual usable capacity of an aged battery is lower than that of a new battery. Therefore, the health status coefficient mapping unit determines the capacity decay correction amount based on the current battery health. The lower the battery health, the smaller the health status decay correction coefficient, thereby reasonably adjusting the safe usable capacity of older batteries.

[0075] Table 2

[0076] Step S22: The comprehensive correction coefficient is obtained by processing at least one of the temperature correction coefficient, health attenuation correction coefficient, mileage correction coefficient and rate discharge correction coefficient through the comprehensive correction coefficient calculation module.

[0077] In one feasible embodiment, the comprehensive correction coefficient calculation module is connected to each unit in the single factor coefficient calculation module. The comprehensive correction coefficient calculation module multiplies at least one of the temperature correction coefficient, health decay correction coefficient, mileage correction coefficient and rate discharge correction coefficient to calculate the comprehensive correction coefficient.

[0078] Optionally, the comprehensive correction coefficient can be obtained by calculating the product of the temperature correction coefficient, health decay correction coefficient, mileage correction coefficient and rate discharge correction coefficient through the comprehensive correction coefficient calculation module.

[0079] Optionally, the overall correction factor K satisfies the following formula: K=K_Temp K_Dist K_SOP K_SOH; Wherein, K_Temp is the temperature correction coefficient, K_SOH is the health decay correction coefficient, K_Dist is the mileage correction coefficient, and K_SOP is the rate discharge correction coefficient.

[0080] In this embodiment, the correction coefficient prediction model maps multi-dimensional operating state parameters such as ambient temperature, battery health, estimated driving distance, and discharge current rate to corresponding correction coefficients through a single-factor coefficient calculation module. Then, the comprehensive correction coefficient calculation module integrates the single-factor coefficients into a unified comprehensive correction coefficient. Each single-factor coefficient independently reflects the independent impact of a single-dimensional factor on the safe available capacity. After multiplication, a multi-factor coupled reduction result is formed. Compared with a single fixed correction or empirical lookup table method, it can more comprehensively and accurately characterize the actual reduction degree of battery safe capacity under the combined effect of current multi-dimensional operating conditions, and improve the accuracy of current safe capacity prediction.

[0081] In one feasible implementation, the single-factor coefficient calculation module includes: a mileage correction coefficient mapping unit; step S21, the step of processing the operating status parameters through the single-factor coefficient calculation module includes step S211: Step S211: The remaining driving range of the battery is determined by the mileage correction coefficient mapping unit based on the sampled abnormal state of charge and the rated driving range of the battery, and the mileage correction coefficient is mapped based on the remaining driving range.

[0082] In one feasible embodiment, the single-factor coefficient calculation module includes: a mileage correction coefficient mapping unit, which calculates the product of the sampled abnormal state of charge and the rated driving range of the battery, and the result is used as the remaining driving range of the battery. Through a preset mileage-coefficient mapping relationship, the mileage correction coefficient corresponding to the remaining driving range is mapped to obtain the mileage correction coefficient.

[0083] Optionally, the state of charge before the sampling anomaly refers to the last reliable state of charge value latched by the battery management system at the moment the voltage sampling anomaly is triggered, i.e., the remaining percentage of battery charge at the instant the fault occurs.

[0084] Optionally, the rated driving range of the battery refers to the nominal distance that the vehicle can travel under standard test conditions when it is fully charged.

[0085] Optionally, the mileage-coefficient mapping relationship can be found in Table 3 below.

[0086] Table 3

[0087] In this embodiment, by introducing the remaining driving range as a dynamic factor, the mileage correction coefficient can intuitively reflect the distance that the vehicle can still drive, thereby adaptively adjusting the correction range of the safe available capacity in subsequent capacity prediction.

[0088] In one feasible implementation, step S21, the single-factor coefficient calculation module includes: a rate discharge correction coefficient mapping unit. The step of processing the operating state parameters through the single-factor coefficient calculation module includes step S212: Step S212: Through the rate discharge correction coefficient mapping unit, determine the rate change rate of the battery based on the discharge current rate, determine the aggressive driving style level based on the rate change rate, and determine the rate discharge correction coefficient based on the aggressive driving style level.

[0089] Among them, the rate of change of the multiplier is negatively correlated with the degree of aggressiveness of the driving style represented by the aggressiveness level of the driving style.

[0090] In one feasible embodiment, the single-factor coefficient calculation module includes: a rate discharge correction coefficient mapping unit, which calculates the rate change rate of the battery based on the discharge current rate, determines the aggressiveness level of the driver's driving style based on the rate change rate of the battery, and maps the rate discharge correction coefficient through a preset driving style-coefficient mapping relationship.

[0091] Optionally, the rate of change refers to the rate of change of the battery discharge current rate per unit time. When the driver depresses the accelerator pedal deeply, the discharge current increases rapidly, and the rate of change is positive and relatively large. When the driver releases the accelerator pedal or brakes suddenly, the discharge current decreases rapidly, and the rate of change is negative and relatively large in absolute value. When the driver is driving at a constant speed, the discharge current remains stable, and the rate of change approaches zero. Therefore, the magnitude and direction of the rate of change directly reflect the intensity of the driver's operation of the accelerator pedal. The larger the absolute value of the rate of change, the more rapid and frequent the driver's operation, corresponding to a more aggressive driving style; the smaller the absolute value of the rate of change, the smoother and more stable the driver's operation, corresponding to a more relaxed driving style.

[0092] Optionally, under an aggressive driving style, the driver frequently performs rapid acceleration and deceleration, causing significant fluctuations in the discharge current. This results in a persistently high voltage drop due to the battery's polarization resistance, frequently pulling down the terminal voltage and compressing the safe available capacity window. Conversely, under a gentle driving style, the current output is smooth and stable, the polarization level is low and consistently stable, and the safe capacity window is relatively wide. Therefore, the aggressiveness level of the driving style can be identified by the rate change rate, and the rate discharge correction coefficient can be dynamically adjusted accordingly. The higher the aggressiveness level, the smaller the rate discharge correction coefficient, thus appropriately reducing the safe available capacity in subsequent capacity predictions. Conversely, the lower the aggressiveness level (i.e., a gentle driving style), the larger the rate discharge correction coefficient, achieving a dynamic balance between safety and driving experience.

[0093] Optionally, the driving style-coefficient mapping relationship can be referred to Table 4 below, where the smaller the value of the aggressive driving style level, the higher the degree of aggressiveness of the driving style it represents.

[0094] Table 4

[0095] In this embodiment, the discharge current ratio can reflect the intensity of the driver's operation of the accelerator pedal, i.e., the aggressiveness of their driving style. Based on this, the discharge ratio correction coefficient is determined. This allows the correction range of the safety capacity to match the actual intensity of driving during periods of voltage sampling anomalies. This avoids premature power limiting due to an excessively small safety window during aggressive driving, and also avoids undervoltage risks due to an excessively large window during gentle driving, thus achieving a dynamic balance between safety and driving experience.

[0096] In one feasible implementation, after obtaining the comprehensive correction coefficient in step S20, the method further includes steps S31 to S33: Step S31: Determine whether the comprehensive correction coefficient is greater than or equal to the preset coefficient threshold. Step S32: If the comprehensive correction coefficient is greater than or equal to the coefficient threshold, perform the step of inputting the comprehensive correction coefficient and the operating status parameters into the preset capacity prediction model, and subsequent steps. Step S33: If the comprehensive correction coefficient is less than the coefficient threshold, execute the sixth control strategy in the battery control strategy.

[0097] In one feasible embodiment, a coefficient threshold (e.g., 0.6, 0.65, 0.7, etc.) is also set for the comprehensive correction coefficient. After determining the comprehensive correction coefficient, it is determined whether the comprehensive correction coefficient is greater than or equal to the preset coefficient threshold. If the comprehensive correction coefficient is less than the coefficient threshold, it indicates that the current battery state is in a sub-healthy state range with multiple adverse factors superimposed, and the coupling of multiple factors causes the current comprehensive correction coefficient to be low; or it indicates that the estimation result of the correction coefficient prediction model under the current extreme operating conditions has a large error, and there is a risk of over-correction. To avoid erroneous correction under the above extreme conditions, the sixth control strategy in the battery control strategy is directly executed. If the comprehensive correction coefficient is greater than or equal to the coefficient threshold, step S30, which inputs the comprehensive correction coefficient and operating state parameters into the preset capacity prediction model, and subsequent steps are executed.

[0098] Optionally, the sixth control strategy includes: deep current limiting, allowing only a portion (e.g., 30%, 20%, etc.) of the performance release to creep at low speed, significantly reducing the discharge rate, while the vehicle dashboard pop-up reminds the user to go to the station for maintenance.

[0099] Optionally, the sixth control strategy in the battery control strategy may be the same as or different from the third control strategy.

[0100] In this embodiment, by setting a coefficient threshold, erroneous correction of battery safety capacity is avoided under extreme conditions, thus ensuring driving safety under extreme operating conditions.

[0101] Based on any of the above embodiments, a third embodiment of the positioning method of this application is proposed. In this embodiment, step S40, which involves executing the battery control strategy corresponding to the current remaining capacity, includes steps S41 to S44: Step S41: If the current remaining capacity is greater than the preset first capacity threshold, execute the first control strategy in the battery control strategy. Step S42: If the current remaining capacity is less than or equal to the first capacity threshold and greater than the preset second capacity threshold, execute the second control strategy in the battery control strategy. Step S44: If the current remaining capacity is less than or equal to the second capacity threshold and greater than the preset third capacity threshold, execute the third control strategy in the battery control strategy. Step S44: If the current remaining capacity is less than or equal to the third capacity threshold, execute the fourth control strategy in the battery control strategy. Among them, the first capacity threshold is greater than the second capacity threshold, and the second capacity threshold is greater than the third capacity threshold; The performance release rate of the first control strategy is greater than that of the second control strategy, the performance release rate of the second control strategy is greater than that of the third control strategy, and the performance release rate of the third control strategy is greater than that of the fourth control strategy.

[0102] In one feasible embodiment, a tiered battery control strategy is executed based on the comparison results between the battery's current remaining capacity and preset capacity thresholds. If the current remaining capacity is greater than a preset first capacity threshold, it indicates that the remaining usable capacity is sufficient and the battery cell has a large safety margin, allowing for power output with little or no constraint. In this case, a first control strategy is executed, such as no power limitation, allowing the vehicle controller to execute full-power output to fully ensure the vehicle's normal driving experience and power performance. If the current remaining capacity is less than or equal to the first capacity threshold but greater than a preset second capacity threshold, it indicates that although the remaining usable capacity has decreased, it still has a certain safety window. In this case, a second control strategy is executed, such as moderate current limiting, limiting the battery's peak discharge power to 70%~80% of the rated power, appropriately extending the fault-tolerant driving range while ensuring that the undervoltage boundary is not reached, and avoiding premature power outages that could affect the user's arrival at their destination. If the current remaining capacity is less than or equal to the second capacity threshold and greater than the preset third capacity threshold, it indicates that the remaining usable capacity is approaching the cell's undervoltage critical value, and the safety margin is extremely limited. At this time, the third control strategy, namely deep current limiting, is implemented, limiting the battery's peak discharge power to 30% of the rated power for low-speed creep, significantly reducing the discharge rate. At the same time, the vehicle's dashboard can also display a pop-up window to remind the user that the current battery status is abnormal and recommend that the battery be taken to a service station for maintenance as soon as possible. If the current remaining capacity is less than or equal to the third capacity threshold, it indicates that the remaining usable capacity has been basically exhausted, and the cell faces a real risk of over-discharge. At this time, the fourth control strategy is implemented, for example, immediately cutting off the discharge circuit and forcibly stopping the discharge to prevent irreversible permanent damage to the cell due to over-discharge and ensure the safety of the battery itself.

[0103] Optionally, the values ​​of the first capacity threshold, the second capacity threshold, and the third capacity threshold decrease sequentially, and the specific values ​​of each threshold are pre-calibrated according to the battery type, cell chemistry system, and safety design requirements, and are not specifically limited here.

[0104] Optionally, the first, second, third, and fourth control strategies described above result in a progressively decreasing degree of vehicle performance release. The limitation on peak discharge power is merely an example. The regulation of vehicle performance release can also be achieved by limiting the upper limit of available discharge power requested by the battery management system from the vehicle controller, limiting the upper limit of peak torque output of the motor controller, limiting the upper limit of the vehicle's maximum operating speed, etc., without specific limitations here.

[0105] Optionally, to prevent frequent switching between control strategies at threshold boundaries from causing vehicle power output oscillations and affecting driving smoothness, the tiered battery control strategy also includes hysteresis control logic. Each capacity threshold has a corresponding first hysteresis value and a second hysteresis value. When the current remaining capacity drops from above a certain threshold to below that threshold, triggering the execution of the next-level strategy corresponding to that threshold, if the current remaining capacity recovers, it must recover to a level greater than the sum of the threshold and the corresponding hysteresis value before reverting to the previous-level strategy. For example, when the second control strategy is triggered, if the current remaining capacity recovers, it must recover to a level greater than the sum of the first capacity threshold and the preset first hysteresis value before resuming the execution of the first control strategy; when the third strategy is triggered, if the current remaining capacity recovers, it must recover to a level greater than the sum of the second capacity threshold and the preset second hysteresis value before resuming the execution of the second control strategy; when the fourth strategy is triggered, if the current remaining capacity recovers, it must recover to a level greater than the sum of the third capacity threshold and the preset third hysteresis value before resuming the execution of the third control strategy. In this way, by setting a hysteresis range at the threshold, the current control strategy remains unchanged when the current remaining capacity fluctuates around the threshold, avoiding frequent changes in power limitation state due to small fluctuations in capacity estimation, thereby effectively improving driving smoothness and system stability.

[0106] Optionally, if the battery voltage sampling is recovered and the actual voltage (i.e., the current sampling voltage) is obtained, in order to prevent power oscillation, the full power is not directly restored, but is gradually restored to the current actual usable power according to a preset value (e.g., 10A / S).

[0107] In this embodiment, a graded battery control strategy is executed by comparing the current remaining capacity of the battery with the preset capacity thresholds. This achieves battery control that matches the current remaining capacity of the battery. In the event of a false failure in voltage sampling and the battery cell still having charge, this avoids the sudden vehicle stoppage caused by the traditional strategy of directly cutting off power, which would affect the user experience. At the same time, the battery control strategy avoids over-discharge that could damage the battery cell, thus achieving a balance between safety and availability.

[0108] In one feasible implementation, at least one of the first capacity threshold, the second capacity threshold, and the third capacity threshold is determined based on the battery's rated capacity and a state correction factor, wherein the state correction factor is determined based on operating state parameters.

[0109] In one feasible embodiment, at least one of the above capacity thresholds is determined based on the battery's rated capacity and a state correction factor. The state correction factor is an adjustment factor determined based on at least one dimension of the operating state parameters, used to dynamically correct the base threshold set based on the rated capacity.

[0110] Optionally, a mapping table can be set up, which includes at least two dimensions: battery health (SOH) and ambient temperature (T). The corresponding state correction coefficient (M) is obtained by looking up the table (for example, refer to Table 5). The state correction coefficient reflects the combined impact of the current battery aging level and temperature environment on the capacity threshold. When the battery health decreases or the ambient temperature is too low, the usable capacity of the cell shrinks, and the state correction coefficient needs to be adjusted down accordingly to narrow the capacity thresholds proportionally.

[0111] Table 5

[0112] Alternatively, each capacity threshold can be determined in the following way: First capacity threshold = rated capacity × 20% × M; Second capacity threshold = rated capacity × 5% × M; Third capacity threshold = rated capacity × 2% × M; Fourth capacity threshold = 0; Where M is the state correction coefficient.

[0113] In this embodiment, the state correction coefficient makes each capacity threshold no longer a fixed calibration value, but adaptively adjusts according to the battery aging state and temperature environment, realizing the matching of the threshold setting with the actual usable capacity of the battery, and further improving the adaptability of the control strategy to changes in battery state.

[0114] In one feasible embodiment, the battery control method further includes steps A10 to A40: Step A10: Obtain the current open-circuit voltage of the battery with its current remaining capacity.

[0115] In one feasible embodiment, in order to further improve the safety during voltage sampling anomalies, the current open-circuit voltage corresponding to the current remaining capacity can be obtained by querying a preset capacity-open-circuit voltage (OCV) mapping table through the current remaining capacity.

[0116] Optionally, the capacity-OCV mapping table can be a table showing the relationship between the open-circuit voltage of the battery under different states of charge when it is in a resting state. This table is obtained in advance through experimental calibration and stored in the battery management system. It represents the baseline change trajectory of the open-circuit voltage during the capacity consumption process.

[0117] Step A20: Determine the static voltage drop of the battery based on the current open-circuit voltage; Step A30: Determine the current theoretical voltage of the battery based on the battery's current current, DC internal resistance, voltage before sampling anomaly, and static voltage drop.

[0118] In one feasible embodiment, based on the current open-circuit voltage, the static voltage drop of the battery is calculated, and combined with the voltage before the sampling anomaly, the current current, and the DC internal resistance latched at the time of the voltage sampling anomaly trigger, the current theoretical voltage is estimated. The estimation formula is as follows: V_ est= V_last - ∫ΔV_max- I Rint; Where V_est is the current theoretical voltage, V_last is the voltage before the sampling anomaly, ΔV_max is the static voltage drop, Rint is the battery DC internal resistance, and I is the current current.

[0119] Step A40: If the current theoretical voltage is less than the preset undervoltage threshold, execute the fifth control strategy in the battery control strategy.

[0120] In one feasible embodiment, the above formula can be used to estimate the theoretical voltage during voltage sampling anomalies, thereby determining the relationship between the current theoretical voltage and the preset undervoltage threshold. If the current theoretical voltage is greater than or equal to the preset undervoltage threshold, it indicates that the current theoretical voltage is still within a safe range, and step S10 and subsequent steps are continued. If the current theoretical voltage is less than the preset undervoltage threshold, it indicates that the theoretical voltage has approached or reached the undervoltage boundary, at which point a forced switch to the fifth control strategy is initiated.

[0121] Optionally, the undervoltage threshold can be determined based on the battery undervoltage fault threshold given by the battery manufacturer. For example, the undervoltage threshold is V, which is the battery undervoltage fault threshold given by the battery manufacturer + 20mV.

[0122] Optionally, the fifth control strategy may be at least partially the same as or different from the fourth control strategy.

[0123] Optionally, the fifth control strategy includes controlling the vehicle's battery to power down at high voltage and / or preventing discharge.

[0124] In this embodiment, by adding an independent voltage verification channel based on theoretical voltage estimation, dual redundancy safety monitoring of capacity and voltage is formed, thereby significantly improving the safety redundancy and reliability of discharge control during voltage sampling anomalies.

[0125] In one feasible implementation, refer to Figure 4 The battery control method also includes steps A50 to A60: Step A50: In response to the recovery of battery voltage sampling, obtain the current sampled voltage of the battery; Step A60: If the difference between the current sampled voltage and the current theoretical voltage is greater than a preset deviation threshold, perform the step of determining the cumulative discharge capacity of the battery under abnormal voltage sampling conditions, and subsequent steps.

[0126] In one feasible embodiment, to ensure that the identified voltage data is accurate and reliable after voltage sampling recovery, and to avoid abnormal power output caused by erroneous switching of control strategies due to momentary false recovery, the current sampled voltage of the battery is obtained after voltage sampling recovery; the difference between the current sampled voltage and the estimated current theoretical voltage is calculated, and it is determined whether the difference is greater than a preset deviation threshold. If the difference is greater than the preset deviation threshold, it indicates that the deviation between the current sampled voltage and the theoretical estimated value is too large, and the actual sampled data is still erroneous or unstable. At this time, step S10 and subsequent steps are continued to maintain the existing control method; if the difference is less than or equal to the preset deviation threshold, it indicates that the current sampled voltage and the theoretical estimated value are basically consistent, the sampled signal has been accurately recovered and the data is reliable. At this time, the system switches to conventional control based on the current sampled voltage.

[0127] In this embodiment, after voltage sampling recovery, the theoretical voltage can be used as a reference to verify the reliability of the recovered sampling voltage. Battery control is only performed based on the current sampling voltage when the deviation between the recovered sampling voltage and the theoretical voltage is within the allowable range. Otherwise, the original battery control method is maintained, which avoids the system frequently switching between fault-tolerant mode and normal mode due to instantaneous jitter or false recovery of the sampling signal, thereby improving the stability and safety of battery control.

[0128] The following is for reference. Figure 5 It shows a structural schematic diagram suitable for implementing electronic devices in vehicles according to embodiments of this application. Figure 5 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0129] like Figure 5As shown, the electronic devices in the vehicle may include a processing unit 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the electronic devices. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, magnetic tape, hard disk, etc.; and communication devices 1009. Communication device 1009 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although electronic devices with various systems are shown in the figures, it should be understood that implementation or possession of all the systems shown is not required. More or fewer systems may be implemented alternatively.

[0130] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0131] The electronic device in the vehicle provided in this application, employing the battery control method described in the above embodiments, can solve the technical problem of how to avoid prematurely cutting off power output in the event of a false failure in battery voltage sampling, thereby maintaining the vehicle's normal driving capability while ensuring driving safety. Compared with the prior art, the beneficial effects of the vehicle provided in this application are the same as those of the battery control method provided in the above embodiments, and other technical features of the electronic device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0132] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0133] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0134] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the battery control method in the above embodiments.

[0135] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0136] The aforementioned computer-readable storage medium may be included in the vehicle or may exist independently and not installed in the vehicle.

[0137] The aforementioned computer-readable storage medium carries one or more programs. When the aforementioned one or more programs are executed by an electronic device, the electronic device causes the electronic device to: respond to a voltage sampling anomaly of the battery, determine the cumulative discharge capacity and operating state parameters of the battery under the voltage sampling anomaly condition; input the operating state parameters into a preset correction coefficient prediction model to obtain a comprehensive correction coefficient; input the comprehensive correction coefficient and the operating state parameters into a preset capacity prediction model to obtain the current safe capacity of the battery; and determine the current remaining capacity of the battery based on the cumulative discharge capacity and the current safe capacity, and execute the battery control strategy corresponding to the current remaining capacity.

[0138] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0139] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0140] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0141] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described battery control method. This solves the technical problem of how to avoid prematurely cutting off power output in the event of a false failure in battery voltage sampling, thereby maintaining the vehicle's normal driving capability while ensuring driving safety. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the battery control method provided in the above embodiments, and will not be repeated here.

[0142] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the battery control method described above.

[0143] The computer program product provided in this application solves the technical problem of how to avoid prematurely cutting off power output when a false failure occurs in battery voltage sampling, thereby maintaining the vehicle's normal driving capability while ensuring driving safety. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the battery control method provided in the above embodiments, and will not be repeated here.

[0144] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A battery control method, characterized in that, The battery control method includes: In response to an abnormal voltage sampling of the battery, the cumulative discharge capacity and operating status parameters of the battery under the abnormal voltage sampling condition are determined; The operating status parameters are input into a preset correction coefficient prediction model to obtain a comprehensive correction coefficient. The comprehensive correction coefficient and the operating status parameters are input into a preset capacity prediction model to obtain the current safe capacity of the battery. Based on the cumulative discharge capacity and the current safe capacity, the current remaining capacity of the battery is determined, and the battery control strategy corresponding to the current remaining capacity is executed.

2. The method as described in claim 1, characterized in that, The correction coefficient prediction model includes: a single-factor coefficient calculation module and a comprehensive correction coefficient calculation module; The step of inputting the operating status parameters into a preset correction coefficient prediction model to obtain the comprehensive correction coefficient includes: The single-factor coefficient calculation module processes the operating status parameters to obtain at least one of the following: temperature correction coefficient, health decay correction coefficient, mileage correction coefficient, and rate discharge correction coefficient. The comprehensive correction coefficient is obtained by processing at least one of the temperature correction coefficient, the health decay correction coefficient, the mileage correction coefficient, and the rate discharge correction coefficient through the comprehensive correction coefficient calculation module. The temperature correction coefficient is obtained based on the ambient temperature in the operating status parameters. The battery health degradation correction coefficient is obtained based on the battery health in the operating status parameters. The mileage correction factor is obtained based on the sampled abnormal pre-charge state in the operating status parameters; The discharge rate correction factor is obtained based on the discharge current rate in the operating status parameters.

3. The method as described in claim 2, characterized in that, The single-factor coefficient calculation module includes a mileage correction coefficient mapping unit. The step of processing the operating status parameters through the single-factor coefficient calculation module includes: The remaining driving range of the battery is determined by the mileage correction coefficient mapping unit based on the sampled abnormal state of charge and the rated driving range of the battery, and the mileage correction coefficient is obtained by mapping based on the remaining driving range.

4. The method as described in claim 2, characterized in that, The single-factor coefficient calculation module includes: a rate discharge correction coefficient mapping unit. The step of processing the operating status parameters through the single-factor coefficient calculation module includes: The rate correction coefficient mapping unit determines the rate change rate of the battery based on the discharge current rate, determines the aggressive driving style level based on the rate change rate, and determines the rate correction coefficient based on the aggressive driving style level. The rate of change of the multiplier is negatively correlated with the degree of aggressiveness of the driving style represented by the aggressiveness level of the driving style.

5. The method as described in claim 1, characterized in that, The steps of executing the battery control strategy corresponding to the current remaining capacity include: If the current remaining capacity is greater than a preset first capacity threshold, the first control strategy in the battery control strategy is executed; If the current remaining capacity is less than or equal to the first capacity threshold and greater than the preset second capacity threshold, the second control strategy in the battery control strategy is executed. If the current remaining capacity is less than or equal to the second capacity threshold and greater than the preset third capacity threshold, the third control strategy in the battery control strategy is executed. If the current remaining capacity is less than or equal to the third capacity threshold, the fourth control strategy in the battery control strategy is executed; Wherein, the first capacity threshold is greater than the second capacity threshold, and the second capacity threshold is greater than the third capacity threshold; The performance release rate of the first control strategy is greater than that of the second control strategy, the performance release rate of the second control strategy is greater than that of the third control strategy, and the performance release rate of the third control strategy is greater than that of the fourth control strategy.

6. The method as described in claim 5, characterized in that, At least one of the first capacity threshold, the second capacity threshold, and the third capacity threshold is determined based on the rated capacity of the battery and a state correction factor, wherein the state correction factor is determined based on the operating state parameters.

7. The method as described in claim 1, characterized in that, The method further includes: Obtain the current open-circuit voltage of the battery corresponding to the current remaining capacity; Determine the static voltage drop of the battery based on the current open-circuit voltage; The current theoretical voltage of the battery is determined based on its current current, DC internal resistance, voltage before sampling anomaly, and static voltage drop. If the current theoretical voltage is less than the preset undervoltage threshold, the fifth control strategy in the battery control strategy is executed.

8. The method as described in claim 7, characterized in that, The method further includes: In response to the recovery of the battery's voltage sampling, the current sampled voltage of the battery is obtained; If the difference between the current sampled voltage and the current theoretical voltage is greater than a preset deviation threshold, the step of determining the cumulative discharge capacity of the battery under the abnormal voltage sampling condition, and subsequent steps, are performed.

9. The method as described in claim 1, characterized in that, Following the step of obtaining the comprehensive correction coefficient, the method further includes: Determine whether the comprehensive correction coefficient is greater than or equal to a preset coefficient threshold; If the comprehensive correction coefficient is greater than or equal to the coefficient threshold, the step of inputting the comprehensive correction coefficient and the operating status parameters into a preset capacity prediction model, and subsequent steps, are performed. If the overall correction coefficient is less than the coefficient threshold, the sixth control strategy in the battery control strategy is executed.

10. A vehicle, characterized in that, The vehicle includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the battery control method as described in any one of claims 1 to 9.

11. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the battery control method as described in any one of claims 1 to 9.

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