Vehicle control method, electronic device, and vehicle

Abstract

The application provides a vehicle control method, an electronic device and a vehicle, and applies to the technical field of intelligent control of vehicles, and the method comprises the following steps: in response to determining that the power battery is in a charging and discharging state, acquiring current state data of the power battery, and predicting future state data of the power battery based on the current state data; determining target future state data of each single battery according to the future state data, and determining the health state of each single battery according to the target future state data to obtain a health state data set, and judging whether the power battery has a health risk according to the health state data set; in response to determining that the power battery has a health risk, determining target charging and discharging parameters of the power battery according to the target future state data, and charging and discharging the power battery based on the target charging and discharging parameters. The application ensures the use efficiency, safety and reliability of the power battery.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle intelligent control, and in particular to a vehicle control method, an electronic device and a vehicle. BACKGROUND

[0002] The main function of the power battery is to provide driving energy for the electric vehicle, and it is also the core of energy storage and management of the vehicle. The existing power battery technology is mainly lithium ion battery, which has the advantages of high energy density and long cycle life, but also has some inherent technical limitations, such as high difficulty in thermal management, which directly or indirectly affects the chemical reaction rate inside the battery, thereby affecting the energy utilization efficiency of the battery, resulting in problems such as shortening of battery life, low charging and discharging efficiency, and battery failure. SUMMARY

[0003] Therefore, the purpose of the present application is to provide a vehicle control method, an electronic device and a vehicle to prolong the battery life, improve the charging efficiency and avoid battery failure.

[0004] To achieve the above purpose, the present application provides a vehicle control method, comprising:

[0005] In response to determining that the power battery is in a charging and discharging state, obtaining current state data of the power battery, and predicting future state data of the power battery based on the current state data;

[0006] According to the future state data, determining the target future state data of each single battery, and determining the health state of each single battery according to the target future state data to obtain a health state data set, and determining whether the power battery has a health risk according to the health state data set;

[0007] In response to determining that the power battery has a health risk, determining the target charging and discharging parameter of the power battery according to the target future state data, and charging and discharging the power battery based on the target charging and discharging parameter.

[0008] Based on the same inventive concept, the present application also provides an electronic device, comprising a memory, a processor and a computer program stored in the memory and executable by the processor, wherein the processor implements the method as described above when executing the computer program.

[0009] Based on the same inventive concept, the present application also provides a vehicle, comprising the above-mentioned electronic device.

[0010] It can be seen from the above that the vehicle control method, electronic device and vehicle provided by the application, wherein the method comprises: in response to determining that the power battery is in a charging and discharging state, acquiring current state data of the power battery, and predicting future state data of the power battery based on the current state data; determining target future state data of each single battery according to the future state data, and determining a health state of each single battery according to the target future state data to obtain a health state data set, and judging whether the power battery has a health risk according to the health state data set; in response to determining that the power battery has a health risk, determining target charging and discharging parameters of the power battery according to the target future state data, and charging and discharging the power battery based on the target charging and discharging parameters. By predicting the future state data, and then determining the target future state data based on the future state data, and further evaluating the health state of each single battery to form the health state data set, it can be more accurately judged whether the power battery has a health risk. Compared with the traditional method of only monitoring the overall parameters of the power battery, the abnormal condition of the single battery can be accurately located, and the security risks such as performance deterioration of the entire power battery caused by the problem of the single battery not being discovered in time can be avoided. When it is determined that the power battery has a health risk, the target charging and discharging parameters of the power battery are determined according to the target future state data, and the power battery is charged and discharged according to the target charging and discharging parameters, which can effectively avoid the problems of overcharging, overdischarging and overheating that may be caused by using fixed charging and discharging parameters when the power battery is in an unhealthy state, thereby prolonging the service life of the power battery and improving the safety and reliability of the power battery. BRIEF DESCRIPTION OF DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the application or related art, the following will briefly introduce the drawings needed to be used in the embodiments or related art descriptions. Obviously, the drawings in the following description are only embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor.

[0012] Figure 1 Flowchart of the vehicle control method of the embodiment of the application;

[0013] Figure 2 Schematic diagram of the vehicle control method device of the embodiment of the application;

[0014] Figure 3 Schematic diagram of the hardware structure of the electronic device provided by the embodiment of the application. DETAILED DESCRIPTION

[0015] In order to make the purpose, technical solutions and advantages of the application more clear, the following will further describe the application in combination with specific embodiments and with reference to the drawings.

[0016] It should be noted that the technical terms or scientific terms used in the embodiments of the present application should be understood as the general meaning understood by those skilled in the art to which the embodiments of the present application belong, unless otherwise defined. The terms "first", "second" and similar terms used in the embodiments of the present application do not represent any order, quantity or importance, but are only used to distinguish different components. The terms "include" or "contain" and similar terms mean that the elements or objects before the terms cover the elements or objects listed after the terms and their equivalents, and do not exclude other elements or objects. The terms "connect" or "connected" and similar terms are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to represent relative positional relationships, and when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0017] With the increasing global energy crisis and environmental problems, electric vehicles have become one of the main directions to replace traditional fuel vehicles due to their zero emissions and low noise. However, the development of the core component of electric vehicles, power batteries, still faces many challenges, and its performance directly determines the vehicle's range, charging efficiency and service life. Therefore, how to optimize the battery management system (BMS) has become a key issue for the development of electric vehicles. The main function of the power battery is to provide driving energy for the electric vehicle, and it is also the core of energy storage and management of the vehicle. The existing power battery technology is mainly based on lithium-ion batteries, which have the advantages of high energy density and long cycle life, but also have some inherent technical limitations, such as difficulty in thermal management, and charging and discharging performance is significantly affected by the environment. The performance of the power battery is affected by many factors, including but not limited to temperature, voltage, charging and discharging frequency, driving mode, ambient temperature, etc. These factors will directly or indirectly affect the chemical reaction rate inside the battery, thereby having an important impact on the energy utilization efficiency, life and safety of the battery. For example, in a high-temperature environment, the chemical reaction inside the battery intensifies, which may cause overheating or even thermal runaway; while in a low-temperature environment, the energy output capacity of the battery will decrease significantly, resulting in a shortened range. In order to ensure the safety and reliability of electric vehicles, the power battery management system (BMS) needs to monitor the state of the battery in real time and dynamically adjust the charging and discharging strategy according to the operation of the battery. The functions of BMS include battery state monitoring (such as battery voltage, current, temperature, etc.), energy distribution optimization, charging and discharging control, fault detection and warning, etc. However, the temperature change of different battery units may affect the performance and life of the entire battery pack. Traditional systems can only monitor the overall temperature of the battery pack and cannot accurately locate the abnormalities of individual batteries. For example, when a single battery overheats, the system may not be able to detect it in time, causing the problem to worsen.

[0018] Based on the above issues, the applicant discovered that: in response to determining that the power battery is in a charging / discharging state, the current state data of the power battery is acquired, and the future state data of the power battery is predicted based on the current state data; the target future state data of each individual battery is determined based on the future state data, and the health status of each individual battery is determined based on the target future state data, resulting in a health status dataset; the power battery is then judged to have any health risks based on the health status dataset; in response to determining that the power battery has health risks, the target charging / discharging parameters of the power battery are determined based on the target future state data, and the power battery is charged and discharged based on the target charging / discharging parameters. By acquiring the current state data of the power battery and predicting the future state data, and then determining the target future state data of each individual battery based on the future state data, and further evaluating the health status of each individual battery to form a health status dataset, it is possible to more accurately determine whether the power battery has any health risks. Compared with traditional methods such as only monitoring the overall temperature of the battery pack, this method can accurately locate abnormal conditions of individual batteries, avoiding the deterioration of the entire battery pack performance or even safety hazards caused by the failure to detect individual battery problems in time. When a health risk is identified in a power battery, target charge and discharge parameters are determined based on future state data, and the battery is charged and discharged accordingly. Dynamically adjusting charge and discharge parameters based on the battery's future state and health condition effectively avoids overcharging, over-discharging, and overheating problems that may occur when using a fixed charge and discharge mode when the battery is in poor health. This extends battery life, improves battery safety and reliability, and ensures the overall performance and operational safety of the electric vehicle.

[0019] The embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0020] This application provides a vehicle control method, such as... Figure 1 As shown, in some embodiments, the method is executed by a vehicle controller or a data processor independently of the vehicle controller; subsequent embodiments will use the vehicle controller as an example for illustration. The vehicle includes a power battery, which comprises multiple individual battery cells; the method includes:

[0021] S101. In response to determining that the power battery is in a charging and discharging state, the current state data of the power battery is obtained, and the future state data of the power battery is predicted based on the current state data.

[0022] In a specific implementation, the battery management system of the vehicle detects whether the power battery is in a charging or discharging state. This can be achieved by monitoring the current direction of the battery. When the current flows into the power battery, it indicates that the power battery is in a charging state; when the current flows out of the power battery, it indicates that the power battery is in a discharging state. The power battery is composed of multiple single batteries, and the multiple single batteries form a battery pack through series or parallel connection to provide power for the vehicle. The current state data includes but is not limited to the voltage, current, hotspot temperature, average temperature, SOC (State of Charge) of each single battery in the power battery, etc. In order to ensure the real-time and accuracy of the data, the current state data is usually collected at a high frequency, for example, once per second or once per minute. These data are transmitted in real time to the control unit of the BMS for processing. The future state data of the power battery is predicted based on the current state data, and the prediction of the future state data is achieved by establishing a mathematical model or a machine learning algorithm. Specifically, the state data of each single battery in the power battery under different working conditions is collected, the data is preprocessed to remove noise and outliers in the data, for example, the erroneous data caused by sensor failure is removed, the data is normalized to the same dimension, such as normalizing the temperature, voltage, etc. to 0-1, so that the model can be better processed, a suitable machine learning algorithm is selected, common models include LSTM (Long Short-Term Memory), RNN (Recurrent Neural Network), etc. These models can process time series data and capture the change of battery state over time. The preprocessed data is input into the selected model for training, the parameters (such as weights and biases) of the model are adjusted to make the model better fit the training data, and the trained model is deployed to the vehicle. When the current state data of the power battery is obtained, the future state data can be output according to the current state data, and the future state data of several minutes to several hours can usually be predicted.

[0023] S102, determining target future state data of each single battery according to the future state data, and determining a health state of each single battery according to the target future state data to obtain a health state data set, and judging whether the power battery has a health risk according to the health state data set;

[0024] In a specific implementation, the future state data of the power battery is a data set, the power battery includes a plurality of single batteries, and therefore the data of each single battery is included in the future state data, i.e., the target future state data of each single battery. The target future state data of each single battery is extracted from the future state data, and the health state of each single battery is determined according to the target future state data and is divided into different health levels (such as a high-risk state, a low-risk state, and a safe state), to obtain a health state data set. The health state data set is composed of the health states of all single batteries, and can be further divided into the following subsets: a high-risk data subset including all single batteries with a high-risk health state; a low-risk data subset including all single batteries with a low-risk health state; and a safe data subset including all single batteries with a safe health state. Generally, if the high-risk data subset is not empty (i.e., there are high-risk single batteries), it indicates that the power battery has a health risk. If the high-risk data subset is empty but the low-risk data subset is not empty (i.e., there are no high-risk single batteries but there are low-risk single batteries), the number and distribution of the low-risk single batteries are further analyzed. If both the high-risk data subset and the low-risk data subset are empty (i.e., all single batteries are in a safe state), it indicates that the power battery has no health risk.

[0025] S103, in response to determining that the power battery has a health risk, determining a target charging and discharging parameter of the power battery according to the target future state data, to charge and discharge the power battery based on the target charging and discharging parameter.

[0026] In a specific implementation, when it is determined that the power battery has a health risk, the target charging and discharging parameter is determined according to the target future state data of the single battery. For example, the target charging and discharging current of the single battery is determined according to the target future state data of the single battery, which includes but is not limited to the hotspot area temperature and the average temperature. If the hotspot area temperature of the single battery is too high, it may cause a thermal runaway risk. At this time, a target charging and discharging current lower than the current charging and discharging current is determined, and the single battery is charged and discharged based on the target charging and discharging current, to reduce the heat generation inside the single battery. If the average temperature of the single battery is too high, it may affect the service life and performance of the battery. At this time, a target charging and discharging current lower than the current charging and discharging current is determined, and the single battery is charged and discharged based on the target charging and discharging current. At the same time, a heat dissipation system (such as a fan or a liquid cooling system) can be started to reduce the average temperature of the single battery, to avoid the health risk of the power battery as a whole.

[0027] In the embodiment, the future state data of the power battery is predicted by the current state data of the power battery, the future state data includes target future state data of each single battery, the health state of each single battery is determined according to the target future state data, and whether the power battery has a health risk is judged, so that the actual safety state of the power battery can be more accurately reflected. Based on the prediction of the future state data, the possible health risk can be found in advance to realize active management. Through multi-level analysis of high-risk, low-risk and safe state, the accuracy and comprehensiveness of the judgment result are ensured, so as to effectively improve the safety and reliability of the power battery and prolong the service life of the battery.

[0028] In some embodiments, the target future state data includes a hotspot area temperature and an average temperature of the single battery; and the determining the health state of each single battery according to the target future state data comprises:

[0029] determining a first integral of the single battery according to the hotspot area temperature;

[0030] In specific implementation, the hotspot area temperature refers to the area with the highest temperature inside the single battery, which is usually the place with the greatest risk of thermal runaway. The hotspot area temperature reflects the state of the single battery under high load or uneven heat dissipation conditions. The average temperature refers to the average temperature level of the whole single battery, which reflects the overall thermal management effect and working environment of the single battery. According to the hotspot area temperature, a first integral of the single battery is determined. If the hotspot area temperature is lower than a certain safety threshold, the first integral is lower. If the hotspot area temperature is higher than a certain dangerous threshold, the first integral is higher.

[0031] determining a second integral of the single battery according to the average temperature;

[0032] In specific implementation, according to the average temperature, different integral levels are set to reflect the effect of overall thermal management of the single battery. That is, if the average temperature is lower than a certain safety threshold, the second integral is lower. If the average temperature is higher than a certain dangerous threshold, the second integral is higher. By calculating the first integral and the second integral, the temperature-related risk of the single battery can be quantified.

[0033] determining a state score as a sum of the first integral and the second integral;

[0034] In specific implementation, the state score is obtained by adding the first integral and the second integral, and is used for comprehensive evaluation of the health state of the single battery. State score = first integral + second integral. The score reflects the comprehensive risk of the single battery in the future state.

[0035] in response to determining that the state score is greater than a first preset score, determining that the single battery is in a high-risk state;

[0036] In implementation, the first preset score is used to distinguish the high-risk state, and is usually set as a higher threshold. If the state score is greater than the first preset score, it indicates that the single battery has serious temperature-related problems, which may cause thermal runaway or rapid aging, and the single battery is considered to be in a high-risk state.

[0037] In response to determining that the state score is less than or equal to the first preset score and greater than the second preset score, the single battery is determined to be in a low-risk state.

[0038] In implementation, the second preset score is used to distinguish the low-risk and safe states, and is usually set as a lower threshold. If the state score is less than or equal to the first preset score and greater than the second preset score, it indicates that the single battery has certain temperature-related problems, but the risk is relatively low, and the single battery is considered to be in a low-risk state.

[0039] In response to determining that the state score is less than or equal to the second preset score, the single battery is determined to be in a safe state, wherein the first preset score is greater than the second preset score.

[0040] In implementation, if the state score is less than or equal to the second preset score, it indicates that the temperature management of the single battery is good, the operation is stable, and there is no obvious risk, and the single battery is considered to be in a safe state. The first preset score is greater than the second preset score, which ensures that the identification of the high-risk state is more strict.

[0041] In this embodiment, by analyzing the hotspot area temperature and the average temperature of the single battery, the state score is calculated, the temperature-related risk of the single battery is accurately quantified, the health state of the single battery is divided into three levels of high-risk, low-risk and safe based on the preset score standard, and the health management level of the power battery is effectively improved, thereby providing strong support for the safety and performance of the electric vehicle.

[0042] In some embodiments, the health state data set includes a high-risk data subset, a low-risk data subset and a safe data subset; and the determining whether the power battery has a health risk according to the health state data set comprises:

[0043] In response to the high-risk data subset being a non-empty set, it is determined that the power battery has a health risk.

[0044] In implementation, the health state data set is a summary of the health states of all single batteries in the power battery, reflecting the overall health of the power battery. The health state of a single battery is evaluated by analyzing its target future state data and classified into a high-risk data subset, a low-risk data subset, and a safe data subset. The high-risk data subset contains all single batteries with a health state of "high risk". The high-risk state is usually caused by a single battery hotspot area temperature that is too high, which may trigger local thermal runaway, or a single battery SOC abnormal fluctuation, which may cause overcharging or overdischarging; the high-risk single battery poses a direct threat to the safety and performance of the power battery. The low-risk data subset contains all single batteries with a health state of "low risk". The low-risk state indicates that the single battery has certain performance or health problems, but the problem is not serious enough to threaten the entire power battery. For example: the single battery temperature is slightly higher than the normal range, but does not reach the danger threshold, and the single battery SOC fluctuation is large but still within the controllable range. The safe data subset contains all single batteries with a health state of "safe". The safe state indicates that the single battery is running normally and has no abnormal or health problems. For example, the single battery temperature and SOC are within the normal range, the single battery performance is stable, and there is no obvious sign of aging. Through classification, the health state data set can comprehensively reflect the health state of all single batteries in the power battery, providing a basis for subsequent health risk judgment. Therefore, if the high-risk data subset is not empty, it indicates that there is at least one single battery in the power battery that is in a high-risk state, and it is determined that the power battery has a health risk.

[0045] In response to the high-risk data subset being an empty set and the low-risk data subset not being an empty set, the number of elements in the low-risk data subset is determined, and it is determined whether the power battery has a health risk according to the number of elements.

[0046] In implementation, if the high-risk data subset is empty, it indicates that there is no high-risk single battery in the power battery. However, if the low-risk data subset is not empty, it indicates that there is a certain number of single batteries in the power battery that are in a low-risk state. Although the low-risk single battery does not immediately threaten the safety of the power battery, if the number is large or the distribution is abnormal, it may have an adverse effect on the long-term performance and life of the power battery, so it is determined whether the power battery has a health risk according to the number of elements.

[0047] In this embodiment, according to the judgment result of the health risk of the single battery in the power battery, it can be accurately determined whether the power battery has a health risk, so as to adjust the charging and discharging strategy in real time and ensure the efficient and safe operation of the power battery. Through quantity and distribution analysis, the potential impact of low-risk single batteries on the power battery is comprehensively evaluated, which can significantly improve the health management level of the power battery and provide strong protection for the safety and reliability of electric vehicles.

[0048] In some embodiments, the determining whether the power battery has a health risk according to the element quantity comprises:

[0049] In response to determining that the element quantity is greater than the preset quantity, determining a single battery corresponding to the low-risk data subset as a target single battery, determining position data of the target single battery, and determining whether the target single battery meets a preset distribution condition based on the position data;

[0050] In specific implementation, if the number of low-risk single batteries exceeds the preset quantity (for example, the preset quantity can be set to 30% of the total number of single batteries in the power battery), it indicates that a certain number of single batteries have an overheating condition, the single battery corresponding to the low-risk data subset is determined as a target single battery, and the distribution of the target single battery is analyzed. If the target single battery is relatively dispersed, even if there is a certain overheating condition, it will not cause thermal runaway, but if the target single battery is compact, the accumulation of heat will cause thermal runaway of the entire power battery, affecting the health of the battery. Therefore, the position data of the target single battery needs to be determined, and whether the target single battery meets a preset distribution condition is determined based on the position data. If the preset distribution condition is met, it indicates that the target single battery is compact, and the power battery has a risk of thermal runaway. If the preset distribution condition is not met, it indicates that the target single battery is relatively dispersed, and the power battery does not have a risk of thermal runaway.

[0051] In response to determining that the target single battery meets the preset distribution condition, it is determined that the power battery has a health risk;

[0052] In specific implementation, the spatial distribution of the target single battery is analyzed through the position data of the target single battery, and potential problems in the power battery can be identified. If the target single battery is compact, it indicates that the thermal management or energy management of the target single battery in a certain region of the power battery has a problem. If the target single battery meets the preset distribution condition, the power battery is considered to have a health risk.

[0053] In response to determining that the target single battery does not meet the preset distribution condition, it is determined that the power battery does not have a health risk;

[0054] In specific implementation, the spatial distribution of the target single battery is analyzed through the position data of the target single battery, and potential problems in the power battery can be identified. If the target single battery is relatively dispersed, it indicates that although the number of target single batteries in a low-risk state is large, the distribution is loose, and the overall performance of the power battery is less affected. If the target single battery does not meet the preset distribution condition, the power battery is considered to have no health risk.

[0055] In response to determining that the number of elements is less than or equal to the preset number, it is determined that the power battery does not have a health risk.

[0056] In specific implementation, if the number of low-risk single batteries is less than or equal to the preset number, the power battery is considered to have no health risk, because a small number of low-risk single batteries has limited impact on the overall performance of the power battery and generally does not cause serious problems.

[0057] In the embodiment, by analyzing the number and spatial distribution of single batteries in the low-risk state, the comprehensiveness of the judgment is ensured. When the number of single batteries in the low-risk state is large and the distribution is relatively compact, it is determined that the power battery has a health risk, which ensures more accurate judgment of the overall health risk of the power battery, avoids misjudgment, and improves the flexibility of the system. By presetting the distribution condition, the potential health problems of the power battery are accurately identified to ensure the safety and reliability of the battery.

[0058] In some embodiments, the determining whether the target single battery meets the preset distribution condition based on the position data comprises:

[0059] determining an average distance between the target single batteries based on the position data;

[0060] In specific implementation, in the power battery, each single battery has its fixed position. These positions can be determined by the physical layout of the power battery, for example, the power battery can be a two-dimensional or three-dimensional array, and the position data of each single battery can be represented by coordinates (such as row and column). If the power battery is a two-dimensional layout, the position data of each single battery can be represented by two-dimensional coordinates (x, y), and if the power battery is a three-dimensional layout, the position data of each single battery can be represented by three-dimensional coordinates (x, y, z). These position data can be pre-stored by a battery management system (BMS) or detected in real time by a sensor. Therefore, the coordinates of each target single battery are determined first, and based on the coordinates of each target single battery, the distance between each two adjacent target single batteries can be determined, and the average distance between all target single batteries is obtained by averaging a plurality of distances.

[0061] In response to determining that the average distance is greater than or equal to a preset average distance, it is determined that the target single battery does not meet the preset distribution condition.

[0062] In specific implementation, when the average distance between the target single batteries is greater than or equal to the preset average distance (for example, the preset average distance can be set to 20 cm), it indicates that the distribution of the target single batteries is relatively dispersed, and it is determined that the target single battery does not meet the preset distribution condition.

[0063] In response to determining that the average distance is less than a preset average distance, it is determined that the target single battery satisfies a preset distribution condition.

[0064] In particular implementation, when the average distance between the target single batteries is less than the preset average distance, it indicates that the distribution of the target single batteries is relatively concentrated, and it is determined that the target single batteries satisfy the preset distribution condition.

[0065] In the embodiment, by evaluating the distribution of the target single battery based on the position data, the health risk of the power battery can be accurately identified, so as to timely optimize the charging and discharging strategy, improve the adaptability and flexibility of the battery management system, prolong the service life of the power battery, enhance the safety of the power battery, reduce the maintenance cost, and improve the user experience.

[0066] In some embodiments, the first integral of the single battery according to the hotspot area temperature comprises:

[0067] In response to determining that the hotspot area temperature is less than a first area temperature threshold, a first preset value is determined as the first integral;

[0068] In particular implementation, the hotspot area temperature refers to the area with the highest internal temperature of the single battery, which is usually the place with the highest risk of thermal runaway. The first area temperature threshold is a lower temperature threshold, which is used to distinguish between normal temperature and slight overheating. For example, it can be set as the upper limit of the safe working temperature of the single battery. When the hotspot area temperature is less than the first area temperature threshold, it indicates that the temperature of the single battery is within the safe range, and the risk of thermal runaway is low, and a lower first preset value (for example, the first preset value can be set to 1) is determined as the first integral.

[0069] In response to determining that the hotspot area temperature is greater than or equal to the first area temperature threshold and less than a second area temperature threshold, a second preset value is determined as the first integral;

[0070] In particular implementation, the second area temperature threshold is a higher temperature threshold, which is used to distinguish between slight overheating and severe overheating, for example, it can be set as the upper limit of the dangerous temperature of the single battery. By the first area temperature threshold and the second area temperature threshold, the hotspot area temperature can be divided into three levels: normal temperature, slight overheating and severe overheating. When the hotspot area temperature is greater than or equal to the first area temperature threshold and less than the second area temperature threshold, it indicates that the temperature of the single battery is in a state of slight overheating, and the risk of thermal runaway increases, and a higher second preset value (for example, the second preset value can be set to 2) is determined as the first integral.

[0071] determining a third preset value as the first integral in response to determining that the hotspot area temperature is greater than or equal to a second area temperature threshold; wherein the first preset value is less than a second preset value, the second preset value is less than the third preset value, and the second area temperature threshold is greater than a first area temperature threshold.

[0072] In particular implementation, when the hotspot area temperature is greater than or equal to the second area temperature threshold, it indicates that the temperature of the single battery is in a serious overheating state, and the risk of thermal runaway is significantly increased. The highest third preset value (for example, the third preset value can be set to 3) is determined as the first integral. The first preset value is less than the second preset value, and the second preset value is less than the third preset value, which ensures that the higher the temperature is, the greater the integral value is, and the higher the reflected risk is. For example, assuming that the first area temperature threshold is 60°C, and the second area temperature threshold is 80°C. If the hotspot area temperature is less than 60°C, the first integral is determined to be 1 (the first preset value). If the hotspot area temperature is between 60°C and 80°C, the first integral is determined to be 2 (the second preset value). If the hotspot area temperature is greater than or equal to 80°C, the first integral is determined to be 3 (the third preset value).

[0073] In the embodiment, through the hierarchical evaluation of the hotspot area temperature of the single battery and the determination of the integral value, the refinement of the evaluation is ensured. According to the temperature level, the integral value is determined, the risk of thermal runaway of the single battery is quantified, the comprehensive evaluation is facilitated, and the health management level of the power battery is effectively improved.

[0074] In some embodiments, the second integral of the single battery is determined according to the average temperature, including:

[0075] determining a fourth value as the second integral in response to determining that the average temperature is less than a first average temperature threshold;

[0076] In implementation, the average temperature is the temperature level of the whole battery cell, which is usually calculated by averaging the data of multiple temperature sensors inside the battery. Unlike the hotspot area temperature, the average temperature reflects the overall thermal state of the battery cell. The average temperature can reflect the heat dissipation capacity and thermal management effect of the battery cell. If the average temperature is too high, it may indicate that the battery's heat dissipation efficiency is insufficient. The battery cell that is in a high temperature for a long time will have its chemical reaction rate accelerated, leading to accelerated capacity attenuation and affecting the battery life. Although the average temperature does not directly reflect the local hotspot problem, when the average temperature is too high, the risk of thermal runaway of the whole battery pack will also increase. The first average temperature threshold is a lower temperature threshold for distinguishing between normal temperature and slight overheating. For example, it can be set to the upper limit of the optimal working temperature of the battery cell (such as 40°C). When the average temperature is less than the first average temperature threshold, it indicates that the overall temperature of the battery cell is within a safe range, the thermal management effect is good, and the risk is low, and a lower fourth value (for example, the fourth preset value can be set to 1) is determined for the second integral.

[0077] In response to determining that the average temperature is greater than or equal to the first average temperature threshold and less than a second average temperature threshold, a fifth value is determined for the second integral.

[0078] In implementation, the second average temperature threshold is a higher temperature threshold for distinguishing between slight overheating and severe overheating. For example, it can be set to the upper limit of the safe working temperature of the battery cell (such as 60°C). When the average temperature is greater than or equal to the first average temperature threshold and less than the second average temperature threshold, it indicates that the overall temperature of the battery cell is slightly higher than the safe range, but has not yet reached a dangerous level, and there is a certain risk, and a higher fifth value (for example, the fifth preset value can be set to 2) is determined for the second integral.

[0079] In response to determining that the average temperature is greater than or equal to the second average temperature threshold, a sixth value is determined for the second integral; wherein the fourth value is less than the fifth value, the fifth value is less than the sixth value, and the second average temperature threshold is greater than the first average temperature threshold.

[0080] In specific implementation, when the average temperature is greater than or equal to the second average temperature threshold, it indicates that the overall temperature of the single battery is in a dangerous range, the heat dissipation is insufficient, and there is a high risk of thermal runaway, and the highest sixth value (for example, the sixth preset value can be set to 3) is determined as the second integral. The fourth value is less than the fifth value, and the fifth value is less than the sixth value, which ensures that the higher the average temperature, the greater the integral value, and the higher the risk reflected. For example, assuming that the first average temperature threshold is 40°C and the second average temperature threshold is 60°C. If the average temperature is less than 40°C, the second integral is determined to be 1 (the fourth value). If the average temperature is between 40°C and 60°C, the second integral is determined to be 2 (the fifth value). If the average temperature is greater than or equal to 60°C, the second integral is determined to be 3 (the sixth value). By setting the first average temperature threshold and the second average temperature threshold, the average temperature can be divided into three intervals, corresponding to low risk, medium risk and high risk respectively.

[0081] In this embodiment, by grading evaluation and integral value determination of the average temperature of the single battery, the overall thermal state of the single battery is evaluated, and the deficiency that the hotspot area temperature cannot reflect the overall situation is made up. The risk corresponding to the average temperature is quantified as an integral value, providing data support for subsequent health state evaluation. By real-time monitoring and predicting the average temperature, the charging and discharging strategy is dynamically adjusted to ensure the safety and reliability of the single battery.

[0082] In some embodiments, the target charging and discharging parameter includes a target charging and discharging current; and determining the target charging and discharging parameter of the power battery according to the target future state data, to charge and discharge the power battery based on the target charging and discharging parameter, includes:

[0083] In response to determining that a single battery in the power battery is in a high-risk state or a low-risk state, determining a current adjustment coefficient based on the hotspot area temperature and the average temperature of the single battery, determining a target charging and discharging current as a product of the current adjustment coefficient and the current charging and discharging current of the single battery, and charging and discharging the single battery based on the target charging and discharging current.

[0084] In specific implementation, when it is determined that a single battery in the power battery is in a high-risk state or a low-risk state, a current adjustment coefficient is determined according to the hotspot area temperature and the average temperature. The current adjustment coefficient is a value between 0 and 1, which is used to adjust the current charging and discharging current. The larger the hotspot area temperature, the smaller the current adjustment coefficient, so as to reduce the charging and discharging current and reduce heat generation. The larger the average temperature, the smaller the current adjustment coefficient, so as to reduce the charging and discharging current and avoid overheating. For example, the current adjustment coefficient can be calculated according to the following formula Wherein T represents a current adjustment coefficient, A represents a hotspot area temperature, A1 represents a first area temperature threshold, B represents an average temperature, B1 represents a first average temperature threshold, and e represents a natural constant. The product of the current adjustment coefficient and the current charge-discharge current of the single battery is determined as a target charge-discharge current, i.e., target charge-discharge current = current adjustment coefficient * current charge-discharge current, and the single battery is charged and discharged based on the target charge-discharge current.

[0085] In this embodiment, by dynamically adjusting the charge-discharge current, the safety risk of the battery caused by overheating and other problems is avoided, and the safety of the power battery is significantly improved. By adjusting the charge-discharge current, the uneven aging of the battery is reduced, and the overall life of the battery pack is further prolonged. Dynamically adjusting the charge-discharge current can ensure that the battery operates in the best working state, improve the energy utilization efficiency of the battery, and improve the performance of the vehicle.

[0086] It should be noted that the method of the embodiments of the present application can be executed by a single device, such as a computer or a server, etc. The method of the embodiments of the present application can also be applied to a distributed scenario, and be completed by multiple devices cooperating with each other. In this distributed scenario, one of the multiple devices can only execute one or more steps in the method of the embodiments of the present application, and the multiple devices can interact with each other to complete the method.

[0087] It should be noted that some embodiments of the present application have been described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in a different order than the order described above and still achieve desirable results. In addition, the processes depicted in the figures do not necessarily require the particular order shown or sequential order to achieve the desired results. In certain implementations, multitasking and parallel processing can be advantageous.

[0088] Based on the same inventive concept, the present application also provides a vehicle control device corresponding to any of the above-mentioned embodiment methods.

[0089] Reference Figure 2 The vehicle control device comprises:

[0090] The acquisition module 701 is configured to, in response to determining that the power battery is in a charge-discharge state, acquire current state data of the power battery, and predict future state data of the power battery based on the current state data;

[0091] a determining module 702, configured to determine target future state data of each single battery according to the future state data, and determine a health state of each single battery according to the target future state data, to obtain a health state data set, and determine whether the power battery has a health risk according to the health state data set;

[0092] a control module 703, configured to, in response to determining that the power battery has a health risk, determine target charging and discharging parameters of the power battery according to the target future state data, and charge and discharge the power battery based on the target charging and discharging parameters.

[0093] Further, the determining module 702 is specifically further configured to:

[0094] determine a first integral of the single battery according to the hotspot area temperature;

[0095] determine a second integral of the single battery according to the average temperature;

[0096] determine a sum value of the first integral and the second integral as a state score;

[0097] in response to determining that the state score is greater than a first preset score, determine that the single battery is in a high-risk state;

[0098] in response to determining that the state score is less than or equal to the first preset score and greater than a second preset score, determine that the single battery is in a low-risk state;

[0099] in response to determining that the state score is less than or equal to the second preset score, determine that the single battery is in a safe state, wherein the first preset score is greater than the second preset score.

[0100] Further, the determining module 702 is specifically further configured to:

[0101] in response to the high-risk data subset being a non-empty set, determine that the power battery has a health risk;

[0102] in response to the high-risk data subset being an empty set and the low-risk data subset being a non-empty set, determine a number of elements of the low-risk data subset, and determine whether the power battery has a health risk according to the number of elements.

[0103] Further, the determining module 702 is specifically further configured to:

[0104] in response to determining that the number of elements is greater than a preset number, determine a target single battery corresponding to the low-risk data subset, determine position data of the target single battery, and determine whether the target single battery satisfies a preset distribution condition based on the position data;

[0105] in response to determining that the target monomer battery meets the preset distribution condition, determining that the power battery has a health risk;

[0106] in response to determining that the target monomer battery does not meet the preset distribution condition, determining that the power battery does not have a health risk;

[0107] in response to determining that the number of elements is less than or equal to the preset number, determining that the power battery does not have a health risk.

[0108] Further, the judgment module 702 is specifically used for:

[0109] determining an average distance between target monomer batteries based on the position data;

[0110] in response to determining that the average distance is greater than or equal to a preset average distance, determining that the target monomer battery does not meet the preset distribution condition;

[0111] in response to determining that the average distance is less than the preset average distance, determining that the target monomer battery meets the preset distribution condition.

[0112] Further, the judgment module 702 is specifically used for:

[0113] in response to determining that the hotspot area temperature is less than a first area temperature threshold, determining a first preset value as the first integral;

[0114] in response to determining that the hotspot area temperature is greater than or equal to the first area temperature threshold and less than a second area temperature threshold, determining a second preset value as the first integral;

[0115] in response to determining that the hotspot area temperature is greater than or equal to the second area temperature threshold, determining a third preset value as the first integral;

[0116] wherein the first preset value is less than the second preset value, the second preset value is less than the third preset value, and the second area temperature threshold is greater than the first area temperature threshold.

[0117] Further, the judgment module 702 is specifically used for:

[0118] in response to determining that the average temperature is less than a first average temperature threshold, determining a fourth value as the second integral;

[0119] in response to determining that the average temperature is greater than or equal to the first average temperature threshold and less than a second average temperature threshold, determining a fifth value as the second integral;

[0120] determining a sixth numerical value in response to determining that the average temperature is greater than or equal to a second average temperature threshold;

[0121] wherein the fourth numerical value is less than a fifth numerical value, the fifth numerical value is less than the sixth numerical value, and the second average temperature threshold is greater than the first average temperature threshold.

[0122] Further, the control module 703 is specifically configured to:

[0123] In response to determining that a single battery cell in the power battery is in a high-risk state or a low-risk state, determining a current adjustment coefficient based on a hotspot area temperature and an average temperature of the single battery cell, determining a target charge-discharge current as a product of the current adjustment coefficient and a current charge-discharge current of the single battery cell, and performing charge-discharge on the single battery cell based on the target charge-discharge current.

[0124] For the ease of description, the above apparatus is described in various modules in terms of functions. Of course, in the implementation of the present application, the functions of the modules can be implemented in one or more software and / or hardware.

[0125] The apparatus of the above embodiments is used to implement the corresponding vehicle control method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiments, which are not described herein again.

[0126] Based on the same inventive concept, the present application also provides an electronic device corresponding to any of the above method embodiments, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the vehicle control method of any of the above embodiments when executing the program.

[0127] Figure 3 A more specific hardware structure of an electronic device is shown in the embodiment, which can include a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040 are connected to each other through the bus 1050 for communication within the device.

[0128] The processor 1010 can be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits, etc., for executing related programs to implement the technical solutions provided by the embodiments of the present application.

[0129] The memory 1020 can be implemented in the form of a ROM (Read Only Memory), a RAM (Random Access Memory), a static storage device, a dynamic storage device, etc. The memory 1020 can store an operating system and other application programs, and when the technical solutions provided by the embodiments of the present specification are implemented by software or firmware, the related program codes are stored in the memory 1020 and are called and executed by the processor 1010.

[0130] The input / output interface 1030 is configured to connect an input / output module to realize information input and output. The input / output module can be configured as a component in the device (not shown in the figure) or can be externally connected to the device to provide corresponding functions. The input device can include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device can include a display, a speaker, a vibrator, an indicator light, etc.

[0131] The communication interface 1040 is configured to connect a communication module (not shown in the figure) to realize communication interaction between the device and other devices. The communication module can realize communication through a wired manner (such as a USB, a network cable, etc.) or through a wireless manner (such as a mobile network, WIFI, Bluetooth, etc.).

[0132] The bus 1050 includes a channel for transmitting information between various components (such as the processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040) of the device.

[0133] It should be noted that although the above device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040, and the bus 1050, in the specific implementation process, the device can also include other components necessary for normal operation. In addition, those skilled in the art can understand that the above device can also only include components necessary for implementing the embodiments of the present specification, and does not have to include all the components shown in the figure.

[0134] The electronic device of the above embodiments is used to implement the corresponding vehicle control method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiments, which are not described here again.

[0135] Based on the same inventive concept, corresponding to any of the above method embodiments, the present application also provides a non-transitory computer readable storage medium storing computer instructions for causing the computer to execute the vehicle control method according to any of the above embodiments.

[0136] The computer readable medium of the embodiments includes permanent and non-permanent, removable and non-removable media, which can realize information storage by any method or technology. The information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device.

[0137] The storage medium of the above embodiments stores computer instructions for causing the computer to execute the vehicle control method as described in any of the above embodiments, and has the beneficial effects of the corresponding method embodiments, which are not repeated here.

[0138] Based on the same concept, the present application also provides a computer program product corresponding to the method of any of the above embodiments, comprising computer program instructions, which, when executed on a computer, cause the computer to execute the method as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which are not repeated here.

[0139] It can be understood that before using the technical solutions of the various embodiments in the present disclosure, the type of personal information involved, the scope of use, the use scenario, etc. will be informed to the user in a proper manner, and the authorization of the user will be obtained.

[0140] For example, in response to receiving the user's active request, prompt information is sent to the user to explicitly prompt the user that the operation requested to be performed will require obtaining and using the user's personal information. Thus, the user can voluntarily choose whether to provide personal information to the software or hardware such as electronic device, application program, server or storage medium that performs the technical solutions of the present disclosure according to the prompt information.

[0141] As an optional but not limited implementation manner, in response to accepting the user's active request, the way of sending prompt information to the user may, for example, be a pop-up window manner, and the prompt information can be presented in the form of text in the pop-up window. In addition, the pop-up window can also carry selection controls for the user to select "agree" or "disagree" to provide personal information to the electronic device.

[0142] It can be understood that the above notification and obtaining user authorization process is only illustrative, and does not limit the implementation of the present disclosure, and other ways meeting relevant laws and regulations can also be applied to the implementation of the present disclosure.

[0143] Those skilled in the art will understand that the above discussion of any embodiment is merely exemplary in nature and is not intended to imply that the present application is limited to these examples; the above embodiments or technical features among different embodiments can also be combined, steps can be implemented in any order, and there are many other changes of different aspects of the embodiments of the present application as described above, which are not provided in details for the sake of brevity.

[0144] In addition, in order to simplify the description and discussion, and so as not to make the embodiments of the present application difficult to understand, the well-known power / ground connections of integrated circuit (IC) chips and other components can or can not be shown in the provided drawings. In addition, the apparatus can be shown in the form of a block diagram in order to avoid making the embodiments of the present application difficult to understand, and this also takes into account the fact that the details of the implementation of these block diagram apparatus are highly dependent on the platform to be implemented to implement the embodiments of the present application (i.e., these details should be fully within the understanding of those skilled in the art). Where specific details (e.g., circuitry) are set forth in order to describe an illustrative embodiment of the present application, it will be apparent to those skilled in the art that the present application can be practiced without these specific details or with an implementation varying from these specific details. Therefore, these descriptions should be considered as illustrative rather than limiting.

[0145] Although the present application has been described in conjunction with the specific embodiments thereof, it is evident that many alternatives, modifications and variations will be apparent to those skilled in the art in light of the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) can use the embodiments discussed.

[0146] The embodiments of the present application are intended to cover all such alternatives, modifications and variations as falling within the broad scope of the application claimed. Accordingly, any omission, modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present application should be included in the protection scope of the present application.

Claims

1. A vehicle control method, characterized in that, The vehicle includes a power battery, and the power battery includes multiple individual cells; the method includes: In response to determining that the power battery is in a charging / discharging state, the current state data of the power battery is acquired, and the future state data of the power battery is predicted based on the current state data; Based on the future state data, the target future state data of each individual battery is determined, and the health state of each individual battery is determined based on the target future state data, resulting in a health state dataset. Based on the health state dataset, it is determined whether the power battery has any health risks. In response to the determination that there is a health risk in the power battery, the target charge and discharge parameters of the power battery are determined based on the target future state data, so as to charge and discharge the power battery based on the target charge and discharge parameters; The target future state data includes the hot spot temperature and average temperature of a single battery cell; determining the health status of each single battery cell based on the target future state data includes: The first integral of a single battery cell is determined based on the temperature of the hot spot region. The second integral of a single cell is determined based on the average temperature. The sum of the first integral and the second integral is determined as the state score; In response to determining that the status score is greater than the first preset score, the individual battery cell is determined to be in a high-risk state; In response to determining that the status score is less than or equal to a first preset score and greater than a second preset score, the individual battery cell is determined to be in a low-risk state. In response to determining that the state score is less than or equal to the second preset score, the single battery cell is determined to be in a safe state, wherein the first preset score is greater than the second preset score.

2. The vehicle control method according to claim 1, characterized in that, The health status dataset includes a high-risk subset, a low-risk subset, and a safe subset; The step of determining whether the power battery has a health risk based on the health status dataset includes: In response to the fact that the high-risk data subset is not an empty set, it is determined that the power battery has a health risk. In response to the fact that the high-risk data subset is empty and the low-risk data subset is not empty, the number of elements in the low-risk data subset is determined, and the presence of health risks in the power battery is judged based on the number of elements.

3. The vehicle control method according to claim 2, characterized in that, The step of determining whether the power battery poses a health risk based on the quantity of the elements includes: In response to determining that the number of elements is greater than a preset number, the individual battery corresponding to the low-risk data subset is identified as the target individual battery, the location data of the target individual battery is determined, and based on the location data, it is determined whether the target individual battery meets the preset distribution conditions. In response to determining that the target single battery cell meets the preset distribution conditions, it is determined that the power battery has a health risk; In response to determining that the target single cell does not meet the preset distribution conditions, it is determined that the power battery does not pose a health risk; In response to determining that the number of the elements is less than or equal to a preset number, it is determined that the power battery does not pose a health risk.

4. The vehicle control method according to claim 3, characterized in that, The step of determining whether the target single cell meets the preset distribution conditions based on the location data includes: The average distance between the target individual cells is determined based on the location data; In response to determining that the average distance is greater than or equal to a preset average distance, it is determined that the target single cell does not meet the preset distribution conditions; In response to determining that the average distance is less than a preset average distance, it is determined that the target single cell meets the preset distribution conditions.

5. The vehicle control method according to claim 1, characterized in that, The determination of the first integral of a single cell based on the temperature of the hot spot region includes: In response to determining that the temperature of the hot spot area is less than the temperature threshold of the first area, the first preset value is determined as the first integral; In response to determining that the temperature of the hot spot area is greater than or equal to the temperature threshold of the first area and less than the temperature threshold of the second area, the second preset value is determined as the first integral. In response to determining that the temperature of the hot spot area is greater than or equal to the temperature threshold of the second area, the third preset value is determined as the first integral; Wherein, the first preset value is less than the second preset value, the second preset value is less than the third preset value, and the temperature threshold of the second region is greater than the temperature threshold of the first region.

6. The vehicle control method according to claim 1, characterized in that, The determination of the second integral of a single cell based on the average temperature includes: In response to determining that the average temperature is less than the first average temperature threshold, the fourth value is determined as the second integral; In response to determining that the average temperature is greater than or equal to a first average temperature threshold and less than a second average temperature threshold, the fifth value is determined as the second integral; In response to determining that the average temperature is greater than or equal to the second average temperature threshold, the sixth value is determined as the second integral; Wherein, the fourth value is less than the fifth value, the fifth value is less than the sixth value, and the second average temperature threshold is greater than the first average temperature threshold.

7. The vehicle control method according to claim 1, characterized in that, The target charge / discharge parameters include the target charge / discharge current; determining the target charge / discharge parameters of the power battery based on the target future state data, and charging / discharging the power battery based on the target charge / discharge parameters, includes: In response to determining that a single cell in the power battery is in a high-risk or low-risk state, a current adjustment coefficient is determined based on the hot spot temperature and average temperature of the single cell. The product of the current adjustment coefficient and the current charge / discharge current of the single cell is determined as the target charge / discharge current, and the single cell is charged and discharged based on the target charge / discharge current.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the program, it implements the method as described in any one of claims 1 to 7.

9. A vehicle, characterized in that, The vehicle includes the electronic equipment as described in claim 8.

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