Power battery service life optimization method, device, vehicle and storage medium

Abstract

The present application relates to the field of automobile technology, and in particular to a method, device, vehicle and storage medium for optimizing the service life of a power battery, wherein the method comprises: obtaining the current parameters of the power battery when detecting that the vehicle is in the service life mode; identifying the current control intention of the user, and matching the target control parameters of the power battery corresponding to the current control intention; optimizing the target control parameters of the power battery according to the current parameters, obtaining the current optimal control parameters of the power battery, and controlling the power battery to perform charging and / or discharging actions based on the current optimal control parameters, so that the power battery is in the best service life. Thus, the problems in the related art that the service life of the power battery of the vehicle cannot be guaranteed to be the best, the service life is short, resulting in a decrease in the optimal use performance of the battery, and the cost performance of the vehicle is low are solved.

Description

Technical Field

[0001] The present application relates to the field of automobile technology, and in particular to a method, device, vehicle and storage medium for optimizing the service life of a power battery. Background Art

[0002] For vehicles equipped with power batteries, such as electric vehicles, the driving modes usually follow the driving modes of fuel vehicles, such as economy mode, standard mode, sports mode, etc. Different modes correspond to different power and comfort.

[0003] However, the related art usually controls the power battery from the perspective of the power and comfort of the electric vehicle, ignoring the impact of battery life on the power battery. Therefore, the control method of the power battery in the related art cannot guarantee the optimal service life, which greatly shortens the service life of the power battery, reduces the cost performance of the electric vehicle and the optimal performance of the power battery. Summary of the invention

[0004] The present application provides a method, device, vehicle and storage medium for optimizing the service life of a power battery to solve the problems in the related art that the service life of the vehicle's power battery cannot be guaranteed to be optimal, the service life is short, resulting in a decrease in the optimal performance of the battery, and the vehicle has a low cost-performance ratio.

[0005] The first aspect of the present application provides a method for optimizing the service life of a power battery, comprising the following steps: when it is detected that a vehicle is in a life mode, obtaining current parameters of the power battery; identifying a user's current control intention, and matching target control parameters of the power battery corresponding to the current control intention; optimizing the target control parameters of the power battery according to the current parameters to obtain current optimal control parameters of the power battery, and controlling the power battery to perform charging and / or discharging actions based on the current optimal control parameters, so that the power battery is in an optimal service life.

[0006] Furthermore, optimizing the target control parameters of the power battery according to the current parameters to obtain the current optimal control parameters of the power battery includes: matching the optimal service life model of the power battery based on the current parameters; inputting the target control parameters into the optimal service life model to generate the current optimal control parameters.

[0007] Furthermore, the step of inputting the target control parameter into the optimal service life model to generate the current optimal control parameter includes: inputting the target control parameter into the optimal service life model to generate at least one reference control parameter; identifying the user's selection intention, and using the reference control parameter corresponding to the selection intention as the current optimal control parameter.

[0008] Optionally, matching the optimal service life model of the power battery based on the current parameters includes: collecting current environmental information of the vehicle; and matching the optimal service life model based on the current parameters and the current environmental information.

[0009] Optionally, matching the optimal service life model of the power battery based on the current parameters further includes: identifying the identity information of the user, and matching the driving habits of the user according to the identity information; matching the optimal service life model based on the current parameters, the current environmental information and the driving habits.

[0010] The second aspect of the present application provides a device for optimizing the service life of a power battery, including: an acquisition module, used to acquire the current parameters of the power battery when it is detected that the vehicle is in a life mode; a matching module, used to identify the user's current control intention and match the target control parameters of the power battery corresponding to the current control intention; an optimization module, used to optimize the target control parameters of the power battery according to the current parameters, obtain the current optimal control parameters of the power battery, and control the power battery to perform charging and / or discharging actions based on the current optimal control parameters, so that the power battery is in an optimal service life.

[0011] Furthermore, the optimization module is used to: match the optimal service life model of the power battery based on the current parameters; input the target control parameters into the optimal service life model to generate the current optimal control parameters.

[0012] Furthermore, the optimization module is further used to input the target control parameter into the optimal service life model to generate at least one reference control parameter; identify the user's selection intention, and use the reference control parameter corresponding to the selection intention as the current optimal control parameter.

[0013] A third aspect of the present application provides a vehicle, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for optimizing the service life of a power battery as described in the above embodiment.

[0014] The fourth aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to implement the method for optimizing the service life of a power battery as described in the above embodiment.

[0015] Therefore, this application has at least the following beneficial effects:

[0016] The power battery life mode has been added, which can control the power battery operation based on the optimal service life, ensure the optimal service life of the power battery, effectively extend the service life of the power battery, improve the cost performance of the vehicle, and improve the optimal performance of the battery. This solves the technical problems in the related technology that the optimal service life of the power battery of the vehicle cannot be guaranteed, the service life is short, resulting in a decrease in the optimal performance of the battery, and the cost performance of the vehicle is low.

[0017] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0019] Figure 1 This is an example diagram of the effect of charging cut-off voltage on battery life in the related art;

[0020] Figure 2 This is an example diagram of the impact of different discharge depths on battery life in the related art;

[0021] Figure 3 This is an example diagram of the effect of temperature on cycle life in the related art;

[0022] Figure 4 An example diagram of the effect of temperature on storage capacity in the related art;

[0023] Figure 5 A schematic diagram of a flow chart of a method for optimizing the service life of a power battery provided in an embodiment of the present application;

[0024] Figure 6 A block diagram of a system for optimizing the service life of a power battery provided according to an embodiment of the present application;

[0025] Figure 7 A schematic diagram of a flow chart of a method for optimizing the service life of a power battery provided according to an embodiment of the present application;

[0026] Figure 8 A block diagram of a device for optimizing the service life of a power battery provided according to an embodiment of the present application;

[0027] Fig. 9 It is a schematic diagram of the structure of a vehicle provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0028] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0029] For vehicles equipped with power batteries, such as electric vehicles, the driving mode usually follows the driving mode of fuel vehicles, which generally includes economic mode, standard mode, sports mode, etc. Different modes correspond to different power and comfort. For example, the power output in the economic mode is relatively gentle and continuous; after switching to the standard mode, the most obvious change is that the acceleration becomes stronger; the sports mode is suitable for driving on highways, and the output power is increased. The power is transmitted and the acceleration is very fast when the accelerator is lightly pressed. In addition, the power saving, comfort and sports modes correspond to the three-speed energy recovery settings of strong, medium and light, that is, the difference in the intervention time and intervention intensity of the energy recovery system. The earlier the energy recovery system intervenes, the more power it saves, but the cost of saving power is the lack of power and kinetic energy recovery affecting part of the driving experience. The greater the intensity of energy recovery intervention, the more driving experience is sacrificed, but it saves more power.

[0030] However, no matter which driving mode is adopted in the related technology, only the power output and whether it is power-saving are considered, and the key indicator of battery life is ignored, which affects the service life of electric vehicles, as follows:

[0031] Although rechargeable batteries have a much longer lifespan than primary batteries, their lifespan is not infinite. Rechargeable lithium-ion batteries can typically be charged 1,000 to 20,000 times or more. In addition to the electrochemical type, the number of cycles depends on a variety of other factors, including: 1) the charge rate, such as slow charge versus fast charge; 2) the charge level, such as 75% full, full or overcharged; 3) the level of discharge before charging; 4) the temperature of the battery when it is not in use and when it is in use.

[0032] like Figure 1 and Figure 2 As shown, full charging and full discharging are not conducive to extending the service life of the battery. Figure 1 As shown in the figure, the impact of the charging cut-off voltage on the battery life is: after 200 cycles, the battery capacity has obvious attenuation (the attenuation degree varies from manufacturer to manufacturer), the solid line is 4.15V and the dotted line is 4.10V; Figure 2 As shown, the influence of different discharge depths on the battery life is as follows: if the discharge depth exceeds 70-80% frequently, the discharge capacity of the battery will be significantly attenuated, reducing the cycle life of the battery (the attenuation degree varies for batteries from different manufacturers).

[0033] In addition, temperature also has a certain impact on the life of the battery, such as Figure 3 As shown in Figure 1, the effect of temperature on cycle life is as follows: as the cycle life increases, lowering the temperature can make the battery contain a higher capacity; Figure 4 As shown, the effect of temperature on storage capacity is: as the storage temperature increases, the capacity decreases sharply.

[0034] Therefore, there are many engineering challenges for both electric and hybrid vehicles, mainly because such vehicles require power batteries to meet consumer expectations for performance, range, reliability, life and cost. In order to solve the above problems, the present application embodiment adds a battery optimal life mode for the entire vehicle, which can be configured to select operating parameters and charging parameters to emphasize battery health and battery life in terms of mileage and life.

[0035] The following will describe the service life optimization method, device, vehicle and storage medium of the power battery of the embodiment of the present application with reference to the accompanying drawings. In view of the problems mentioned in the above background technology that the related art cannot guarantee the optimal service life of the power battery of the vehicle, the service life is short, resulting in a decrease in the optimal use performance of the battery, and the cost performance of the vehicle is low, the present application provides a method for optimizing the service life of a power battery, in which a power battery life mode is added, and the power battery operation can be controlled based on the optimal service life to ensure the optimal service life of the power battery, which can effectively extend the service life of the power battery, improve the cost performance of the vehicle, and improve the optimal use performance of the battery. As a result, the technical problems such as the inability to guarantee the optimal service life of the power battery of the vehicle, the short service life, resulting in a decrease in the optimal use performance of the battery, and the low cost performance of the vehicle in the related art are solved.

[0036] Specifically, Figure 5 A schematic flow chart of a method for optimizing the service life of a power battery provided in an embodiment of the present application. It should be noted that the method in the embodiment of the present application can be applied to vehicles equipped with power batteries, such as pure electric vehicles or hybrid electric vehicles, etc., without specific limitation.

[0037] like Figure 5 As shown, the method for optimizing the service life of a power battery comprises the following steps:

[0038] In step S101 , when it is detected that the vehicle is in the life mode, the current parameters of the power battery are obtained.

[0039] Among them, the life mode refers to a mode that can maximize the battery life, and the embodiments of the present application can control the vehicle to enter the life mode in a variety of ways, for example, the vehicle can be controlled to enter the life mode by button triggering or voice triggering, etc., and there is no specific limitation on this.

[0040] It can be understood that when the vehicle enters the life mode, the optimization method of controlling the vehicle to execute steps S101 to S103 first obtains the current parameters of the power battery, where the current parameters may include operating condition information, mileage, power battery usage and other information, as well as temperature, current, voltage and other parameters.

[0041] In step S102, the current control intention of the user is identified, and the target control parameters of the power battery corresponding to the current control intention are matched.

[0042] Among them, the current control intention refers to the user's intention to control the discharge or charging of the power battery, that is, it can include charging control intention and discharging control intention. For example, when the accelerator pedal is detected to be triggered, the user's current control intention can be identified as the discharging control intention; when the charging gun is detected to be connected, the user's current control intention can be identified as the charging intention.

[0043] It is understandable that the embodiments of the present application can match control parameters corresponding to the control intent, such as discharge parameters or charging parameters, when detecting the user's specific control intent.

[0044] In step S103, the target control parameters of the power battery are optimized according to the current parameters to obtain the current optimal control parameters of the power battery, and the power battery is controlled to perform charging and / or discharging actions based on the current optimal control parameters so that the power battery is in the best service life.

[0045] The current optimal control parameters refer to the optimal control parameters that can make the power battery have the best service life.

[0046] It can be understood that the embodiments of the present application can control the operation of the power battery based on the optimal service life to ensure the optimal service life of the power battery. Thus, by adding the optimal battery life mode, the purpose of extending the battery service life is achieved, which improves the cost performance of the vehicle while also improving the optimal use performance of the battery. It can also protect the battery more reasonably and effectively, prevent battery abuse, and improve safety.

[0047] In an embodiment of the present application, the target control parameters of the power battery are optimized according to the current parameters to obtain the current optimal control parameters of the power battery, including: matching the optimal service life model of the power battery based on the current parameters; inputting the target control parameters into the optimal service life model to generate the current optimal control parameters.

[0048] It can be understood that the embodiments of the present application can estimate the vehicle usage model based on the current parameters, optimize the key parameters of various vehicle batteries according to the specific information provided by the user's vehicle usage model, and customize the optimal battery life model suitable for the vehicle user to meet the user's usage needs, comfort, reliability and long battery life requirements.

[0049] It should be noted that the embodiments of the present application can not only match the optimal service life model based on the current parameters, but also match it in many other ways, which is not specifically limited. Among them, the embodiments of the present application can match the optimal service life model in many other ways, including the following implementations:

[0050] As a possible implementation method, matching the optimal service life model of the power battery based on current parameters includes: collecting current environmental information of the vehicle; and matching the optimal service life model based on current parameters and current environmental information.

[0051] Among them, the current environmental information may include geographic location and temperature information, etc. In some embodiments, the embodiments of the present application may use GPS (Global Positioning System) positioning and big data analysis to understand the user's driving environment such as geographic location and temperature information throughout the year.

[0052] It can be understood that the embodiments of the present application can take into account the vehicle's environment when determining the optimal usage model, and jointly determine the optimal service life model through current parameters and current environmental information to improve the accuracy of matching the optimal service life model, enhance the vehicle's adaptability to the environment, and enhance the optimization effect of the power battery's service life.

[0053] Specifically, the embodiments of the present application can obtain the user's location information through GPS data and some relevant information of battery parameters through big data, obtain the user's vehicle usage model, optimize the key parameters of batteries used in various vehicles based on the specific information provided by the user's vehicle usage model, and customize the optimal battery life model suitable for the vehicle user to meet the user's needs while achieving the purpose of extending the battery life.

[0054] As another possible implementation method, matching the optimal service life model of the power battery based on current parameters also includes: identifying the user's identity information and matching the user's driving habits based on the identity information; matching the optimal service life model based on current parameters, current environmental information and driving habits.

[0055] The identity information may include the user's fingerprint information, face information, etc., to identify the user's specific identity.

[0056] It can be understood that the embodiments of the present application can take the user's driving habits into consideration when determining the optimal usage model, and jointly determine the optimal service life model through current parameters, current environmental information and driving habits, thereby improving the accuracy of model matching and enhancing the vehicle's ability to adapt to the environment. At the same time, the optimal usage model can effectively meet the user's usage needs and enhance the user's usage experience.

[0057] Specifically, the embodiments of the present application can combine GPS and big data information to more clearly understand the user's usage environment, driving habits and other information, and more accurately obtain the vehicle's usage model, so as to continuously optimize the optimal life mode and other related parameters through the usage model, so that the optimal life mode is more suitable for each user, so that the user's usage environment, driving habits and other information can be more clearly understood through GPS and big data information, making the optimal life mode more customized, intelligent and personalized. Even if the driver is changed, the vehicle's usage model can be continuously updated through information such as GPS and big data information, and the key parameters of these optimal life modes can be continuously optimized and corrected.

[0058] After obtaining the optimal service life model according to any of the above embodiments, the embodiments of the present application can not only output the current optimal control parameters based on the optimal service life model, but also obtain the current optimal control parameters according to the user's selection. In some embodiments, the target control parameters are input into the optimal service life model to generate the current optimal control parameters, including: inputting the target control parameters into the optimal service life model to generate at least one reference control parameter; identifying the user's selection intention, and using the reference control parameters corresponding to the selection intention as the current optimal control parameters.

[0059] The reference control parameters may be understood as suggested control parameters recommended to the user.

[0060] It can be understood that the embodiments of the present application can determine the current optimal control parameters based on the user's selection, so as to obtain the user's intention through information interaction with the user, meet the usage needs of different users, and achieve the purpose of extending the service life of the power battery while improving the user's usage experience.

[0061] In some embodiments, the embodiments of the present application can also customize their own optimal life mode through APP (Application) to achieve the purpose of extending the service life of the power battery.

[0062] It should be noted that after selecting the life mode, the vehicle panel or APP will provide some different operating parameters or charging parameters, and provide multiple preset parameter values ​​for selection. Among them, the preset parameter values ​​are recommended values ​​confirmed by the car supplier, and the car supplier and / or the car repair shop or user are also allowed to modify them. The life mode will be different due to different specifications of the car, such as the battery chemical system, the capacity of the thermal management system, the charging configuration, etc. Usually the system will select one or more parameters, and the recommended parameter values ​​are based on knowing that it is a certain type of battery, such as a lithium-ion electrochemical system.

[0063] In the optimal battery life mode, the following parameters can be set in the embodiment of the present application:

[0064] 1) Setting the maximum upper limit and minimum lower limit of SOC (State of Charge), which can be set by technicians in this field according to actual conditions, and no specific limitation is made to this; for example, the minimum SOC level is set to 35% and the maximum SOC level is set to 80%, the minimum SOC value can be 5% higher than the standard mode, and the minimum SOC value is 10% lower than the maximum SOC value.

[0065] 2) Set a minimum cell voltage value, such as 3.0V, etc., without specific limitation.

[0066] 3) Setting the battery temperature during discharge, for example, the temperature of the battery pack can be maintained between 30-35° C., or between 25-30° C., etc., without specific limitation.

[0067] 4) Set the battery temperature to be maintained during charging. An appropriate battery temperature can reduce the attenuation of battery life. For example, the battery temperature can be set to a preset value, such as any value between 35-40°C, etc., without specific limitation. After the battery temperature is set, the battery temperature can be managed through the battery thermal management system.

[0068] 5) Setting the storage temperature of the battery. The storage temperature can be maintained between 15-20°C, or between 20-25°C, etc., without specific limitation.

[0069] 6) Setting the SOC value during storage. When the vehicle enters the storage phase, the storage time is set by the user through the interface. For example, the SOC value can be set to 50%, 40% or 30%, etc. At the same time, the vehicle has the ability to charge to a higher SOC value (60%) for the convenience of the user. For example, if the user sets the storage date, driving time, etc. through the interface, the controller can charge to the set SOC value after the storage date ends.

[0070] 7) Set the maximum charging rate. In life mode, the charging rate is relatively low. Configure the appropriate charging rate according to the fast or slow charging situation and the charging time required by the user. The more time, the lower the charging rate, the better the battery health. At the same time, the charging temperature should also be taken into account, such as 20-25℃. Use 1 / 3C charging, 15-20℃, 1 / 4C, 10-15℃, 1 / 5C, 0-10℃, 1 / 10C. At the same time, the user can enter the time of the next drive, which can be used to allocate charging time.

[0071] 8) Set the thermal balance during the discharge process and monitor it to keep it within the preset range. For example, the thermal balance is set to ≤20°C, and the battery pack cannot exceed 20°C when reaching thermal balance.

[0072] 9) Set the maximum discharge rate and provide the user with high, medium and low discharge rate options to ensure sufficient power for safe driving. For example, in the normal discharge process, the maximum allowable discharge rate is between 1C and 2C. In the best life mode, under the premise of meeting the user's safe driving standards, the maximum allowable discharge rate is below 1C, such as 0.8C.

[0073] 10) When the user is away for a long time while charging, the charging time is extended. Specifically: since the vehicle is connected to the charging power source for a long time, the battery SOC value will be maintained at a high value in the standard mode, such as around 90%, which can easily cause battery damage; therefore, in the life mode, the embodiment of the present application can set the SOC value during self-discharge to a lower value, so as to reduce the frequency of repeated charging when the charging cycle is started, such as 30% or 20%, etc., to avoid battery damage and achieve the purpose of extending the service life of the power battery.

[0074] In some embodiments, as the user uses the vehicle for a period of time, such as one month, three months, or half a year, the user's latest vehicle usage model is continuously updated based on GPS and big data information, and the key parameters of the battery are optimized. The optimal battery life model of the vehicle user is continuously optimized and then applied to the user's actual use. In actual use, the user's usage data continues to be collected based on GPS and the big data platform, and imported into the vehicle's usage model for optimization and continuous updating.

[0075] The following is an explanation of the method for optimizing the service life of a power battery through a specific embodiment, wherein: Figure 6 As shown, the system for optimizing the service life of the power battery includes: a controller, a sensor, a GPS, a vehicle control panel / application APP and a big data platform. The sensors may include temperature sensors, voltage sensors, current sensors, etc. The controller can output control instructions based on the acquired information, such as discharge instructions, charging instructions, thermal management instructions, etc.

[0076] based on Figure 6 systems such as Figure 7 As shown, the method for optimizing the service life of a power battery includes the following steps:

[0077] The first step is to preset parameter values. The parameter values ​​have initial optimal default values, and users can set them accordingly through the vehicle panel or mobile phone application APP according to their needs. The parameters are the relevant key parameter values ​​of the above embodiments.

[0078] In the second step, the preset parameter values ​​are transmitted to the battery management system controller through CAN (Controller Area Network) network or WiFi (Wireless Fidelity), and the vehicle usage model in the controller stores the parameter values ​​in accordance with the specified format requirements. Among them, the vehicle usage model can regularly obtain vehicle usage data information from the big data platform through T-box (Telematics BOX), filter, analyze and extract key parameters of vehicle usage information, such as SOC, voltage, current, temperature, output power, charging information, thermal management and other information. For example, by analyzing the SOC usage range, the user's power demand can be understood, which is used to configure the minimum and maximum SOC values; for example, by analyzing the vehicle speed information, the user's actual discharge power demand can be understood, and the battery power limit can be configured more reasonably according to the required power; for example, by analyzing the battery temperature information, the temperature environment of the battery can be understood, which is used to set some key parameters of battery thermal management, such as the configuration of heating power, heating time or whether cooling is turned on, etc., and the user's key parameter thresholds can be updated on this basis.

[0079] In the third step, the service life model in the controller can call these key parameter thresholds, configure them according to different requirements such as charging, discharging or storage, and collect information such as temperature, current, voltage and other parameters in real time to control the output, such as output power, heating or cooling, etc., to ensure that the vehicle battery is used within the set key parameter threshold range and achieve the purpose of extending the battery life.

[0080] The fourth step is the actual use of the vehicle by the user. The vehicle needs to be equipped with a T-box and a GPS device. The vehicle data such as speed, battery current, voltage, temperature, SOC, heating or cooling, etc. are uploaded to the big data platform through the T-box. At the same time, the GPS collects the location information of the entire vehicle in real time and transmits it to the big data platform in real time.

[0081] According to the method for optimizing the service life of a power battery proposed in the embodiment of the present application, by adding a battery optimal life mode, the purpose of extending the battery service life is achieved, the cost-effectiveness of the vehicle is improved, the optimal use performance of the battery is improved, the battery is protected more reasonably and effectively, battery abuse is prevented, and the safety of the power battery is improved; at the same time, combined with GPS and big data information, the user's usage environment, driving habits and other information are accurately obtained, so that the optimal life mode is more customized, intelligent and personalized, thereby improving the user experience.

[0082] Next, a device for optimizing the service life of a power battery proposed in accordance with an embodiment of the present application will be described with reference to the accompanying drawings.

[0083] Figure 8 It is a block diagram of a device for optimizing the service life of a power battery according to an embodiment of the present application.

[0084] like Figure 8 As shown, the service life optimization device 10 of a power battery includes: an acquisition module 100 , a matching module 200 and an optimization module 300 .

[0085] Among them, the acquisition module 100 is used to obtain the current parameters of the power battery when it is detected that the vehicle is in the life mode; the matching module 200 is used to identify the user's current control intention and match the target control parameters of the power battery corresponding to the current control intention; the optimization module 300 is used to optimize the target control parameters of the power battery according to the current parameters, obtain the current optimal control parameters of the power battery, and control the power battery to perform charging and / or discharging actions based on the current optimal control parameters, so that the power battery is in the best service life.

[0086] In the embodiment of the present application, the optimization module 300 is used to: match the optimal service life model of the power battery based on the current parameters; input the target control parameters into the optimal service life model to generate the current optimal control parameters.

[0087] In an embodiment of the present application, the optimization module 300 is further used to input the target control parameter into the optimal service life model to generate at least one reference control parameter; identify the user's selection intention, and use the reference control parameter corresponding to the selection intention as the current optimal control parameter.

[0088] It should be noted that the aforementioned explanation of the embodiment of the method for optimizing the service life of a power battery is also applicable to the device for optimizing the service life of a power battery of this embodiment, and will not be repeated here.

[0089] According to the power battery service life optimization device proposed in the embodiment of the present application, by adding the battery optimal life mode, the purpose of extending the battery service life is achieved, the cost-effectiveness of the vehicle is improved, and the optimal use performance of the battery is improved, the battery is protected more reasonably and effectively, battery abuse is prevented, and the safety of the power battery is improved; at the same time, combined with GPS and big data information, the user's usage environment, driving habits and other information are accurately obtained, so that the optimal life mode is more customized, intelligent and personalized, thereby improving the user experience.

[0090] Fig. 9 A schematic diagram of the structure of a vehicle provided in an embodiment of the present application. The vehicle may include:

[0091] A memory 901 , a processor 902 , and a computer program stored in the memory 901 and executable on the processor 902 .

[0092] When the processor 902 executes the program, the service life optimization method of the power battery provided in the above embodiment is implemented.

[0093] Furthermore, the vehicle also includes:

[0094] The communication interface 903 is used for communication between the memory 901 and the processor 902 .

[0095] The memory 901 is used to store computer programs that can be executed on the processor 902 .

[0096] The memory 901 may include a high-speed RAM (Random Access Memory) memory, and may also include a non-volatile memory, such as at least one disk memory.

[0097] If the memory 901, the processor 902 and the communication interface 903 are implemented independently, the communication interface 903, the memory 901 and the processor 902 can be connected to each other through a bus and communicate with each other. The bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Fig. 9 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0098] Optionally, in a specific implementation, if the memory 901, the processor 902 and the communication interface 903 are integrated on a chip, the memory 901, the processor 902 and the communication interface 903 can communicate with each other through an internal interface.

[0099] The processor 902 may be a CPU (Central Processing Unit), or an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present application.

[0100] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above method for optimizing the service life of a power battery.

[0101] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms are not necessarily directed to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0102] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0103] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0104] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array, a field programmable gate array, etc.

[0105] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0106] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for optimizing the service life of a power battery, characterized in that: The following steps are involved: When it is detected that the vehicle is in the life mode, the current parameters of the power battery are obtained, the current parameters including: operating condition information, mileage, usage of the power battery, and temperature, current, and voltage; Identifying a user's current control intention and matching a target control parameter of the power battery corresponding to the current control intention, wherein the current control intention includes a charging control intention and a discharging control intention; and Optimizing the target control parameters of the power battery according to the current parameters to obtain the current optimal control parameters of the power battery, and controlling the power battery to perform a charging action and / or a discharging action based on the current optimal control parameters so that the power battery is in an optimal service life; The optimizing the target control parameters of the power battery according to the current parameters to obtain the current optimal control parameters of the power battery includes: Matching the optimal service life model of the power battery based on the current parameters, the optimal service life model includes key parameters, and the key parameters include: SOC upper and lower limits, minimum cell voltage value, SOC value during storage, charging rate, discharge rate, charging time and temperature control parameters; Inputting the target control parameter into the optimal service life model to generate the current optimal control parameter; The step of inputting the target control parameter into the optimal service life model to generate the current optimal control parameter comprises: Inputting the target control parameter into the optimal service life model to generate at least one reference control parameter; The user's selection intention is identified, and the reference control parameter corresponding to the selection intention is used as the current optimal control parameter.

2. The method according to claim 1, characterized in that The matching of the optimal service life model of the power battery based on the current parameters includes: Collecting current environment information of the vehicle; The optimal service life model is matched based on the current parameters and the current environmental information.

3. The method according to claim 2, characterized in that The matching of the optimal service life model of the power battery based on the current parameters also includes: Identify the identity information of the user, and match the driving habits of the user according to the identity information; The optimal service life model is matched based on the current parameters, the current environmental information and the driving habits.

4. A device for optimizing the service life of a power battery, characterized in that: include: An acquisition module, used to acquire current parameters of the power battery when detecting that the vehicle is in the life mode, the current parameters including: operating condition information, mileage, usage of the power battery, and temperature, current, and voltage; a matching module, used to identify a user's current control intention and match a target control parameter of the power battery corresponding to the current control intention, wherein the current control intention includes a charging control intention and a discharging control intention; and an optimization module, configured to optimize the target control parameters of the power battery according to the current parameters, obtain the current optimal control parameters of the power battery, and control the power battery to perform a charging action and / or a discharging action based on the current optimal control parameters, so that the power battery is in an optimal service life; Matching the optimal service life model of the power battery based on the current parameters, the optimal service life model includes key parameters, and the key parameters include: SOC upper and lower limits, minimum cell voltage value, SOC value during storage, charging rate, discharge rate, charging time and temperature control parameters; inputting the target control parameters into the optimal service life model to generate the current optimal control parameters; The optimization module is further used to input the target control parameter into the optimal service life model to generate at least one reference control parameter; identify the user's selection intention, and use the reference control parameter corresponding to the selection intention as the current optimal control parameter.

5. A vehicle, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for optimizing the service life of a power battery as described in any one of claims 1 to 3.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the service life optimization method of a power battery as described in any one of claims 1 to 3.

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