Battery charging optimization method and device, vehicle and storage medium

Abstract

The invention relates to a battery charging optimization method and device, a vehicle and a storage medium. The method comprises the steps of obtaining a current battery health value, a battery nominal capacity, a battery theoretical cut-off charging voltage and a current user endurance demand based on a battery charging demand; determining a target charging electric quantity based on the current user endurance demand, the battery nominal capacity and the current battery health value, and determining a target charging cut-off voltage based on the battery theoretical cut-off charging voltage; and generating a charging optimization strategy according to the target charging electric quantity and the target charging cut-off voltage, and charging the battery by using the charging optimization strategy. Therefore, the charging amount and the charging cut-off voltage are properly reduced on the basis of the battery health degree, the battery temperature and the vehicle using requirement of a user, and the problem that the cycle life of the battery is seriously shortened due to the fact that the battery is charged according to fixed charging parameters and the actual aging state of the battery is not considered in the prior art is solved; and the battery capacity fading rate can be reduced on the premise of meeting the vehicle use requirement of a user.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle charging optimization, and in particular relates to a battery charging optimization method and device, a vehicle and a storage medium. BACKGROUND

[0002] As a core component of new energy vehicles, the performance of a battery pack is directly related to the endurance and service life of the vehicle. The state of health (SOH) of a battery is an important indicator of the performance of a battery pack, and the optimization of a charging strategy is of great significance to improving the state of health of a battery and prolonging the service life of a battery.

[0003] In related technologies, the most widely used charging method is constant current and constant voltage charging, which works in two stages of constant current and constant voltage. In the initial stage, the battery is quickly charged at a constant current, and when the battery voltage reaches a set threshold, the charging mode is switched to constant voltage.

[0004] However, this method charges the battery according to preset fixed charging parameters, without considering the actual aging state of the battery, which seriously reduces the cycle life of the battery and needs to be solved urgently. SUMMARY

[0005] The present application provides a battery charging optimization method and device, a vehicle and a storage medium to solve the problem that the prior art charges the battery according to fixed charging parameters without considering the actual aging state of the battery, which seriously reduces the cycle life of the battery, and to reduce the battery capacity decay rate while meeting the user's vehicle demand.

[0006] To achieve the above purpose, the first aspect of the present application proposes a battery charging optimization method, comprising the following steps:

[0007] Obtain the battery charging demand, and based on the battery charging demand, obtain the current battery health value, the battery nominal capacity, the battery theoretical cut-off charging voltage and the current user endurance demand;

[0008] Based on the current user endurance demand, the battery nominal capacity and the current battery health value, determine the target charging capacity, and based on the battery theoretical cut-off charging voltage, determine the target charging cut-off voltage;

[0009] Generate a charging optimization strategy according to the target charging capacity and the target charging cut-off voltage, and charge the battery using the charging optimization strategy.

[0010] According to one embodiment of the present application, the determination of the target charging capacity based on the preset energy consumption coefficient, the current user endurance demand, the battery nominal capacity and the current battery health value comprises:

[0011] multiply the current user endurance demand by a preset energy consumption coefficient to obtain a first product;

[0012] multiply the battery nominal capacity by the current battery health value to obtain a second product;

[0013] calculate a ratio of the first product and the second product, and multiply the ratio by a preset safety margin coefficient to obtain the target charging electric quantity.

[0014] According to an embodiment of the present application, the target charging cutoff voltage is determined based on the battery theoretical cutoff charging voltage, including:

[0015] based on a preset attenuation coefficient and the current battery health value, a current health attenuation pressure drop is calculated;

[0016] a current battery temperature is obtained, and based on the current battery temperature, a preset optimal charging temperature and a preset temperature coefficient, a current temperature compensation pressure drop is calculated;

[0017] based on the battery theoretical cutoff charging voltage, the current health attenuation pressure drop and the current temperature compensation pressure drop, the target charging cutoff voltage is calculated.

[0018] According to an embodiment of the present application, the battery is charged by using the charging optimization strategy, including:

[0019] the real-time voltage and the real-time SOC of the battery in the charging process are monitored;

[0020] based on the charging optimization strategy, the charging current and the charging voltage are adjusted according to the real-time voltage and the real-time SOC until the real-time voltage meets the target charging cutoff voltage and / or the real-time SOC meets the target charging electric quantity.

[0021] According to an embodiment of the present application, the target charging cutoff voltage is:

[0022] V cutoff = V base -ΔV SOH +ΔV temp ;

[0023] wherein, V cutoff is the target charging cutoff voltage, V base is the battery theoretical cutoff charging voltage, ΔV SOH is the current health attenuation pressure drop, and ΔV temp is the current temperature compensation pressure drop.

[0024] According to the battery charging optimization method proposed in the embodiment of the present application, by obtaining the current battery health value, battery nominal capacity, battery theoretical cut-off charging voltage and current user endurance requirements, the target charging power can be determined based on the current user endurance requirements, battery nominal capacity and current battery health value, and the target charging cut-off voltage can be determined based on the battery theoretical cut-off charging voltage; a charging optimization strategy is generated based on the target charging power and target charging cut-off voltage, and the battery is charged using the charging optimization strategy. Thus, by moderately reducing the charging power and charging cut-off voltage based on battery health, battery temperature and user vehicle use requirements, the problem of the existing technology of charging the battery based on fixed charging parameters without considering the actual aging state of the battery, resulting in a serious reduction in the battery cycle life, is solved. The battery capacity attenuation rate can be reduced while meeting the user's vehicle use requirements.

[0025] To achieve the above objectives, a second embodiment of the present application provides a battery charging optimization device, comprising:

[0026] An acquisition module is used to obtain a battery charging requirement and, based on the battery charging requirement, obtain a current battery health value, a battery nominal capacity, a battery theoretical cut-off charging voltage, and a current user endurance requirement;

[0027] a determination module, configured to determine a target charging power based on the current user endurance requirement, the battery nominal capacity, and the current battery health value, and to determine a target charging cutoff voltage based on the battery theoretical charging cutoff voltage;

[0028] The charging module is used to generate a charging optimization strategy according to the target charging power and the target charging cut-off voltage, and charge the battery using the charging optimization strategy.

[0029] According to one embodiment of the present application, the determining module is specifically configured to:

[0030] Multiplying the current user endurance requirement by a preset energy consumption coefficient to obtain a first product;

[0031] multiplying the battery nominal capacity by the current battery health value to obtain a second product;

[0032] The ratio of the first product to the second product is calculated, and the ratio is multiplied by a preset safety margin coefficient to obtain the target charging power.

[0033] According to one embodiment of the present application, the determining module is specifically configured to:

[0034] Calculating a current health decay voltage drop based on a preset decay coefficient and the current battery health value;

[0035] obtain a current battery temperature, and calculate a current temperature compensation voltage drop based on the current battery temperature, a preset optimal charging temperature, and a preset temperature coefficient;

[0036] calculate the target charging cutoff voltage based on the battery theoretical cutoff charging voltage, the current health attenuation voltage drop, and the current temperature compensation voltage drop.

[0037] According to an embodiment of the present application, the charging module is specifically used for:

[0038] monitoring a real-time voltage and a real-time SOC of the battery during charging;

[0039] adjusting a charging current and a charging voltage according to the real-time voltage and the real-time SOC based on the charging optimization strategy until the real-time voltage meets the target charging cutoff voltage and / or the real-time SOC meets the target charging electric quantity.

[0040] According to an embodiment of the present application, the target charging cutoff voltage is:

[0041] V cutoff = V base - ΔV SOH + ΔV temp ;

[0042] wherein, V cutoff is the target charging cutoff voltage, V base is the battery theoretical cutoff charging voltage, ΔV SOH is the current health attenuation voltage drop, and ΔV temp is the current temperature compensation voltage drop.

[0043] According to the battery charging optimization device provided by the embodiment of the present application, by obtaining a current battery health value, a battery nominal capacity, a battery theoretical cutoff charging voltage, and a current user endurance requirement, the target charging electric quantity can be determined based on the current user endurance requirement, the battery nominal capacity, and the current battery health value, and the target charging cutoff voltage can be determined based on the battery theoretical cutoff charging voltage; the charging optimization strategy is generated according to the target charging electric quantity and the target charging cutoff voltage, and the battery is charged by using the charging optimization strategy. Therefore, by moderately reducing the charging electric quantity and the charging cutoff voltage based on the battery health degree, the battery temperature, and the user vehicle demand, the problem that the battery cycle life is seriously reduced due to that the battery is charged according to the fixed charging parameters without considering the actual aging state of the battery in the prior art is solved, and the battery capacity attenuation rate can be reduced on the premise of meeting the user vehicle demand.

[0044] To achieve the above object, the 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 battery charging optimization method as described in the above embodiments.

[0045] To achieve the above object, the fourth aspect of the present application provides a computer readable storage medium, which stores a computer program executable by a processor to implement the battery charging optimization method as described in the above embodiments.

[0046] Additional aspects and advantages of the present application will be made apparent by the following description and the accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0047] The above and / or additional aspects and advantages of the present application will become apparent and be readily appreciated from the following description, including the accompanying drawings.

[0048] Figure 1 A flow chart of a battery charging optimization method according to an embodiment of the present application;

[0049] Figure 2 A flow chart of another battery charging optimization method according to an embodiment of the present application;

[0050] Figure 3 A block schematic diagram of a battery charging optimization apparatus according to an embodiment of the present application;

[0051] Figure 4 A structure schematic diagram of a vehicle according to an embodiment of the present application. DETAILED DESCRIPTION

[0052] The embodiments of the present application are described in detail below with reference to the accompanying drawings. The same or similar components are denoted by the same or similar reference numerals throughout the drawings, and a repeated description of the same or similar components is omitted. The embodiments described below are examples for explaining the present application, and are not intended to limit the present application.

[0053] The battery charging optimization method, apparatus, vehicle and storage medium according to embodiments of the present application are described below with reference to the accompanying drawings. First, the battery charging optimization method according to embodiments of the present application is described with reference to the accompanying drawings.

[0054] Figure 1 A flow chart of a battery charging optimization method according to an embodiment of the present application.

[0055] As Figure 1As shown, the battery charging optimization method includes the following steps:

[0056] In step S101 , a battery charging requirement is obtained, and based on the battery charging requirement, the current battery health value, the battery nominal capacity, the battery theoretical cut-off charging voltage, and the current user endurance requirement are obtained.

[0057] It's understood that battery charging demand refers to whether the battery currently needs charging. This can be triggered manually by the user through the vehicle's central control screen, a mobile app, or a button on the charging device. Alternatively, the vehicle's intelligent system can predict the user's charging need based on their historical driving data and charging habits, automatically initiating charging at the appropriate time. The battery health value measures the battery's current health, typically expressed as a percentage. A lower health value indicates greater battery aging and potential performance degradation. This value can be obtained through the battery management system. The battery's nominal capacity refers to the rated capacity marked on the battery at the factory, representing the battery's maximum energy storage capacity under ideal conditions. This can be obtained from the battery's technical specifications or the vehicle's manual. The theoretical charge cutoff voltage refers to the maximum voltage allowed during charging, also available from the battery's technical specifications or the vehicle's manual. Exceeding this voltage may lead to overcharging, potentially causing safety issues. The range requirement refers to the required driving distance the battery can support. For example, a user may want an electric vehicle to travel a longer distance on a single charge. The range requirement can be calculated based on historical vehicle usage data, categorized by weekdays and weekends.

[0058] In step S102 , a target charging power is determined based on the current user endurance requirement, the battery nominal capacity, and the current battery health value, and a target charging cut-off voltage is determined based on the battery theoretical cut-off charging voltage.

[0059] It is understandable that for battery packs with low battery health, if full charging operations are continued, the precipitation of lithium ions on the surface of the negative electrode will be significantly aggravated, and the positive electrode material will also cause cracking due to stress concentration. These factors will greatly increase the capacity decay rate of the battery and seriously affect the battery’s service life and performance stability. However, if the charge level is too low, it will trigger the need for frequent charging, which not only increases the number of charging times and time costs, but also causes users’ battery life anxiety and affects the user experience. Therefore, in actual applications, the target charging capacity of the battery can be reasonably determined by comprehensively considering the current user’s battery life requirements, the nominal capacity of the battery, and the current battery health value, so as to ensure that while ensuring battery performance, it can also meet the user’s daily use needs.

[0060] In addition, the theoretical charge cut-off voltage of a lithium iron phosphate battery during charging is generally set to 3.65V. However, for a battery with a certain degree of aging, if 3.65V is still used as the charge cut-off voltage, it will lead to an excessively high cut-off voltage during actual charging. This high voltage condition will inevitably accelerate the capacity decay rate inside the battery, thereby significantly reducing the cycle life of the battery. In addition, when the battery is charged in a low-temperature environment, the viscosity of the electrolyte will increase with the decrease of temperature, which can directly lead to a significant hindrance to the migration and movement of lithium ions in the electrolyte, ultimately causing a significant decline in charging efficiency. If charging is still carried out according to the charge cut-off voltage at normal temperature under such low-temperature conditions, it is extremely likely to cause the generation of lithium dendrites. Once these lithium dendrites are formed, not only will they cause internal short-circuit problems in the battery, but they may even trigger serious safety hazards. Therefore, when charging the battery in a low-temperature environment, a more cautious strategy can be adopted, i.e., using a relatively low charge cut-off voltage to ensure the safety and effectiveness of the charging process. Similarly, when charging in a high-temperature environment, if an excessively high charge cut-off voltage is used, it may cause the decomposition of the electrolyte and damage the stability of the solid electrolyte interface film, which will have a negative impact on the life of the battery. Therefore, when charging in a high-temperature environment, a lower charge cut-off voltage also needs to be adjusted to maintain the overall performance of the battery and prolong its service life.

[0061] For ease of understanding, how to determine the target charge capacity and the target charge cut-off voltage is described in detail below.

[0062] As a possible implementation manner, in some embodiments, the target charge capacity is determined based on a preset energy consumption coefficient, a current user endurance requirement, a battery nominal capacity, and a current battery health value, including: multiplying the current user endurance requirement by the preset energy consumption coefficient to obtain a first product; multiplying the battery nominal capacity by the current battery health value to obtain a second product; calculating a ratio of the first product to the second product, and multiplying the ratio by a preset safety margin coefficient to obtain the target charge capacity.

[0063] Specifically, as Figure 2As shown, the target charging power is calculated as follows: the current user's endurance demand is multiplied by the preset energy consumption coefficient to obtain the required power (i.e., the first product), wherein the preset energy consumption coefficient can be calculated based on the user's historical vehicle usage data. The battery's nominal capacity is multiplied by the current battery health value to obtain the battery's current maximum capacity (i.e., the second product). The required power divided by the battery's current maximum capacity is the required actual charging power. However, in order to ensure that emergencies can be dealt with in actual use, a certain amount of endurance margin can be added to the required actual charging power, and the required actual charging power is multiplied by the safety margin coefficient (a safety factor greater than 1, which can be 1.1 in the embodiment of the present application) to obtain the final target charging power. The target charging power not only takes into account the endurance demand, but also takes into account the battery's health and the uncertainty in actual use, providing a more reliable basis for the charging strategy.

[0064] That is, the target charging capacity is:

[0065]

[0066] Among them, SOC target Target charging capacity (%), D req is the current user's endurance requirement (km), η is the preset energy consumption coefficient (kWh / km), C nominal is the nominal capacity of the battery (Ah), SOH is the current battery health value (%), and γ is the preset safety margin coefficient.

[0067] For example, the nominal capacity of a lithium iron phosphate battery is C nominal =60Ah, current battery health value SOH=85%, current user endurance requirement D req =80km, the preset energy consumption coefficient η=0.15kWh / km.

[0068] First, the unit conversion of the battery nominal capacity can be performed, namely:

[0069] C nominal =60Ah×400V=24000Wh=24kWh;

[0070]

[0071] That is to say, under the above conditions, charging the battery to about 71.17% of its energy can meet the needs of the vehicle and can protect the battery health to the greatest extent.

[0072] As a possible implementation manner, in some embodiments, the target charging cutoff voltage is determined based on the theoretical cutoff charging voltage of the battery, including: calculating a current health attenuation voltage drop based on a preset attenuation coefficient and a current battery health value; obtaining a current battery temperature, and calculating a current temperature compensation voltage drop based on the current battery temperature, a preset optimal charging temperature and a preset temperature coefficient; calculating the target charging cutoff voltage based on the theoretical cutoff charging voltage of the battery, the current health attenuation voltage drop and the current temperature compensation voltage drop.

[0073] As shown in Figure 2 , for the calculation of the target charging cutoff voltage, the current battery health value and the battery temperature can be taken into account, so as to optimize the charging cutoff voltage. Specifically, the current health attenuation voltage drop is calculated first, that is:

[0074] ΔV SOH = k aging ×(1-SOH);

[0075] Wherein, ΔV SOH is the current health attenuation voltage drop, k aging is a preset attenuation coefficient, which can be taken as 0.8V / 100%, and SOH is the current battery health value.

[0076] For example, for a lithium iron phosphate battery with a current battery health value of 85%, the current health attenuation voltage drop determined by health attenuation is:

[0077] ΔV SOH = 0.8×(1-85%) = 0.12(V);

[0078] Secondly, the current temperature compensation voltage drop is calculated, and the charging cutoff voltage needs to be moderately reduced when the battery temperature is lower or higher than the preset optimal charging temperature (which can be taken as 25℃), that is:

[0079]

[0080] Wherein, ΔV temp is the current temperature compensation voltage drop, T opt is the preset optimal charging temperature, k clod is the preset temperature coefficient, which can be taken as -2V / ℃ when the current battery temperature is less than the preset optimal charging temperature, and -3V / ℃ when the current battery temperature is greater than the preset optimal charging temperature.

[0081] For example, when the current battery temperature is 0℃, the current temperature compensation voltage drop is:

[0082] ΔV temp = -2×(25-0) = -50(mV) = -0.05(V);

[0083] The current battery temperature is 30℃, and the current temperature compensation voltage drop is:

[0084] AV temp = -3x(30-25) = -15(mV) = -0.015(V).

[0085] After calculating the current health attenuation voltage drop and the current temperature compensation voltage drop, the target charging cutoff voltage is combined with the theoretical cutoff charging voltage of the battery, and the target charging cutoff voltage is:

[0086] V cutoff = V base - AV SOH + AV temp ;

[0087] Wherein, V cutoff is the target charging cutoff voltage, V base is the theoretical cutoff charging voltage of the battery (i.e. 3.65V), AV SOH is the current health attenuation voltage drop, and AV temp is the current temperature compensation voltage drop.

[0088] For example, the current battery health value of the lithium iron phosphate battery is 85%, and the current battery temperature is 0℃, the target charging cutoff voltage is:

[0089] V cutoff = 3.65-0.12+(-0.05) = 3.38(V).

[0090] In step S103, according to the target charging capacity and the target charging cutoff voltage, a charging optimization strategy is generated, and the battery is charged by using the charging optimization strategy.

[0091] That is, after calculating the target charging capacity and the target charging cutoff voltage, a charging optimization strategy suitable for the current vehicle battery condition can be generated based on the target charging capacity and the target charging cutoff voltage. The system can fully utilize the charging optimization strategy to perform scientific and reasonable charging operation on the battery, ensure that the battery reaches the expected capacity target while maintaining a safe working voltage range, thereby effectively prolonging the service life of the battery and improving the overall efficiency of charging.

[0092] As a possible implementation, in some embodiments, charging the battery by using the charging optimization strategy includes: monitoring the real-time voltage and real-time SOC of the battery during charging; based on the charging optimization strategy, adjusting the charging current and charging voltage according to the real-time voltage and real-time SOC until the real-time voltage meets the target charging cutoff voltage and / or the real-time SOC meets the target charging capacity.

[0093] Specifically, during actual charging, the system can monitor parameters such as the voltage and SOC of the battery in real time. When it is found that the real-time voltage is close to or reaches the target charging cutoff voltage, or the real-time SOC is close to or reaches the target charging capacity, the system will automatically adjust the charging current and charging voltage to avoid overcharging or undercharging. This dynamic adjustment process can ensure that the battery remains in a safe and efficient state during charging. Through real-time monitoring and adjustment, the system can also effectively prevent safety hazards caused by battery overheating, overvoltage, and other problems, further improving the safety and stability of the battery.

[0094] It should be noted that in reality, the situation that simultaneously meets the target charging capacity and the target charging cutoff voltage may not always exist, and needs to be handled flexibly according to specific circumstances, giving priority to the safety of the battery while trying to meet the user's endurance needs. For example, if the real-time SOC reaches the target charging capacity first, but the real-time voltage has not reached the target charging cutoff voltage, it may be because the user needs low endurance, so the calculated target charging capacity is also low. In this case, the vehicle battery can continue to be charged until the real-time voltage of the battery reaches the target charging cutoff voltage. At this time, the actual SOC of the battery may be slightly higher than the target charging capacity, but it is still within the safe range. If the real-time voltage reaches the target charging cutoff voltage first, and the real-time SOC has not reached the target charging capacity, it may be because the battery health is poor or the charging environment temperature is low, so the calculated target charging cutoff voltage is low. In this case, charging can be stopped directly to avoid damage to the battery caused by high voltage. At this time, the actual SOC of the battery will be lower than the target charging capacity, but it can still meet most of the user's needs.

[0095] According to the battery charging optimization method proposed in the embodiments of the present application, by obtaining the current battery health value, the battery nominal capacity, the battery theoretical cutoff charging voltage and the current user endurance demand, the target charging capacity can be determined based on the current user endurance demand, the battery nominal capacity and the current battery health value, and the target charging cutoff voltage can be determined based on the battery theoretical cutoff charging voltage; according to the target charging capacity and the target charging cutoff voltage, a charging optimization strategy is generated, and the battery is charged using the charging optimization strategy. Therefore, by moderately reducing the charging capacity and the charging cutoff voltage based on the battery health, the battery temperature and the user's vehicle demand, the problem that the battery cycle life is seriously reduced due to the fact that the existing technology charges the battery according to fixed charging parameters without considering the actual aging state of the battery is solved, and the battery capacity decay rate can be reduced under the premise of meeting the user's vehicle demand.

[0096] Second, the battery charging optimization device according to the embodiments of the present application is described with reference to the accompanying drawings.

[0097] Figure 3is a block schematic diagram of an optimization device for battery charging according to an embodiment of the present application.

[0098] As shown in Figure 3 the optimization device for battery charging 10 comprises an acquisition module 100, a determination module 200 and a charging module 300.

[0099] The acquisition module 100 is configured to acquire a battery charging demand, and acquire a current battery health value, a battery nominal capacity, a battery theoretical cut-off charging voltage and a current user endurance demand based on the battery charging demand.

[0100] The determination module 200 is configured to determine a target charging capacity based on the current user endurance demand, the battery nominal capacity and the current battery health value, and determine a target charging cut-off voltage based on the battery theoretical cut-off charging voltage.

[0101] The charging module 300 is configured to generate a charging optimization strategy according to the target charging capacity and the target charging cut-off voltage, and charge the battery by using the charging optimization strategy.

[0102] Optionally, in some embodiments, the determination module 200 is specifically configured to:

[0103] multiply the current user endurance demand by a preset energy consumption coefficient to obtain a first product;

[0104] multiply the battery nominal capacity by the current battery health value to obtain a second product;

[0105] calculate a ratio of the first product to the second product, and multiply the ratio by a preset safety margin coefficient to obtain the target charging capacity.

[0106] Optionally, in some embodiments, the determination module 200 is specifically configured to:

[0107] calculate a current health attenuation pressure drop based on a preset attenuation coefficient and the current battery health value;

[0108] acquire a current battery temperature, and calculate a current temperature compensation pressure drop based on the current battery temperature, a preset optimal charging temperature and a preset temperature coefficient;

[0109] calculate the target charging cut-off voltage based on the battery theoretical cut-off charging voltage, the current health attenuation pressure drop and the current temperature compensation pressure drop.

[0110] Optionally, in some embodiments, the charging module 300 is specifically configured to:

[0111] monitor a real-time voltage and a real-time SOC of the battery in a charging process;

[0112] Based on the charging optimization strategy, the charging current and the charging voltage are adjusted according to the real-time voltage and the real-time SOC until the real-time voltage meets the target charging cutoff voltage and / or the real-time SOC target charging electric quantity.

[0113] Optionally, in some embodiments, the target charging cutoff voltage is:

[0114] V cutoff = V base - ΔV SOH + ΔV temp ;

[0115] Wherein, V cutoff is the target charging cutoff voltage, V base is the theoretical cutoff charging voltage of the battery, ΔV SOH is the current health attenuation voltage drop, and ΔV temp is the current temperature compensation voltage drop.

[0116] It should be noted that the foregoing explanation of the battery charging optimization method embodiment is also applicable to the battery charging optimization device of this embodiment, which will not be described here.

[0117] The battery charging optimization device provided by the embodiments of the present application can obtain the current battery health value, the battery nominal capacity, the theoretical cutoff charging voltage of the battery and the current user endurance requirement, determine the target charging electric quantity based on the current user endurance requirement, the battery nominal capacity and the current battery health value, determine the target charging cutoff voltage based on the theoretical cutoff charging voltage of the battery, generate a charging optimization strategy according to the target charging electric quantity and the target charging cutoff voltage, and charge the battery using the charging optimization strategy. Thus, by moderately reducing the charging electric quantity and the charging cutoff voltage based on the battery health, the battery temperature and the user vehicle demand, the problem that the battery cycle life is seriously reduced due to the fact that the prior art charges the battery according to fixed charging parameters without considering the actual aging state of the battery is solved, and the battery capacity attenuation rate can be reduced under the premise of meeting the user vehicle demand.

[0118] Figure 4 The vehicle provided by the embodiments of the present application provides a structural schematic diagram of the vehicle. The vehicle can include:

[0119] The memory 401, the processor 402 and the computer program stored in the memory 401 and executable on the processor 402.

[0120] The processor 402 implements the battery charging optimization method provided in the above embodiments when executing the program.

[0121] Further, the vehicle further includes:

[0122] The communication interface 403 is configured to communicate between the memory 401 and the processor 402.

[0123] The memory 401 is configured to store a computer program executable in the processor 402.

[0124] The memory 401 can include a high-speed RAM (Random Access Memory) memory, and can further include a nonvolatile memory, for example, at least one disk memory.

[0125] If the memory 401, the processor 402 and the communication interface 403 are independently implemented, the communication interface 403, the memory 401 and the processor 402 can be connected 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 the convenience of representation, Figure 4 In the figure, only one thick line is used to represent the bus, but it does not mean that there is only one bus or only one type of bus.

[0126] Optionally, in a specific implementation, if the memory 401, the processor 402 and the communication interface 403 are integrated on a chip, the memory 401, the processor 402 and the communication interface 403 can communicate with each other through an internal interface.

[0127] The processor 402 can 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.

[0128] The embodiments of the present application further provide a computer readable storage medium, which stores a computer program, and the program is executed by the processor to implement the above battery charging optimization method.

[0129] In addition, the terms "first", "second", etc. are used only to describe purposes and can not be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "a plurality of" is at least two, for example, two, three, etc., unless otherwise explicitly and specifically limited.

[0130] In the description of the present application, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present application, the illustrative description of the above terms is not necessarily directed to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in any one or more embodiments or examples. Furthermore, the person skilled in the art can combine and combine the different embodiments or examples described in the present application and the features of the different embodiments or examples without contradiction.

[0131] Although the embodiments of the present application have been shown and described above, it is understood that the above-described embodiments are exemplary and can not be construed as limiting the present application, and those skilled in the art can make changes, modifications, replacements and variations to the above-described embodiments within the scope of the present application.

Claims

1. A battery charging optimization method, characterized in that: The following steps are involved: Obtaining a battery charging requirement, and based on the battery charging requirement, obtaining a current battery health value, a battery nominal capacity, a battery theoretical cut-off charging voltage, and a current user endurance requirement; Determining a target charging capacity based on the current user endurance requirement, the battery nominal capacity, and the current battery health value, and determining a target charging cutoff voltage based on the battery theoretical charging cutoff voltage; A charging optimization strategy is generated according to the target charging power and the target charging cut-off voltage, and the battery is charged using the charging optimization strategy.

2. The method according to claim 1, characterized in that The determining of the target charging power based on the preset energy consumption coefficient, the current user endurance requirement, the battery nominal capacity, and the current battery health value includes: Multiplying the current user endurance requirement by a preset energy consumption coefficient to obtain a first product; multiplying the battery nominal capacity by the current battery health value to obtain a second product; The ratio of the first product to the second product is calculated, and the ratio is multiplied by a preset safety margin coefficient to obtain the target charging power.

3. The method according to claim 1, characterized in that The determining of the target charging cut-off voltage based on the battery theoretical charging cut-off voltage includes: Calculating a current health decay voltage drop based on a preset decay coefficient and the current battery health value; Obtaining a current battery temperature, and calculating a current temperature-compensated voltage drop based on the current battery temperature, a preset optimal charging temperature, and a preset temperature coefficient; The target charging cut-off voltage is calculated based on the battery theoretical charging cut-off voltage, the current health attenuation voltage drop, and the current temperature-compensated voltage drop.

4. The method according to claim 1, wherein The method of charging the battery by using the charging optimization strategy includes: Monitor the real-time voltage and SOC of the battery during charging; Based on the charging optimization strategy, the charging current and the charging voltage are adjusted according to the real-time voltage and the real-time SOC until the real-time voltage meets the target charging cut-off voltage and / or the target charging capacity of the real-time SOC.

5. The method according to claim 3, characterized in that The target charge cut-off voltage is: V cutoff =V base -ΔV SOH +ΔV temp ; Among them, V cutoff is the target charge cut-off voltage, V base The theoretical cut-off charging voltage of the battery, ΔV SOH is the current health decay voltage drop, ΔV temp is the current temperature compensated voltage drop.

6. A battery charging optimization device, characterized in that: include: An acquisition module is used to obtain a battery charging requirement and, based on the battery charging requirement, obtain a current battery health value, a battery nominal capacity, a battery theoretical cut-off charging voltage, and a current user endurance requirement; a determination module, configured to determine a target charging power based on the current user endurance requirement, the battery nominal capacity, and the current battery health value, and to determine a target charging cutoff voltage based on the battery theoretical charging cutoff voltage; The charging module is used to generate a charging optimization strategy according to the target charging power and the target charging cut-off voltage, and charge the battery using the charging optimization strategy.

7. The device according to claim 6, characterized in that The determining module is specifically configured to: Multiplying the current user endurance requirement by a preset energy consumption coefficient to obtain a first product; multiplying the battery nominal capacity by the current battery health value to obtain a second product; The ratio of the first product to the second product is calculated, and the ratio is multiplied by a preset safety margin coefficient to obtain the target charging power.

8. The device according to claim 6, characterized in that The determining module is specifically configured to: Calculating a current health decay voltage drop based on a preset decay coefficient and the current battery health value; Obtaining a current battery temperature, and calculating a current temperature-compensated voltage drop based on the current battery temperature, a preset optimal charging temperature, and a preset temperature coefficient; The target charging cut-off voltage is calculated based on the battery theoretical charging cut-off voltage, the current health attenuation voltage drop, and the current temperature-compensated voltage drop.

9. 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 battery charging optimization method according to any one of claims 1 to 5.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the battery charging optimization method according to any one of claims 1 to 5.

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