Electric vehicle fast charging method, device, electronic device and storage medium

Abstract

Embodiments of the present specification disclose an electric vehicle fast charging method and device, electronic equipment and storage medium. The method comprises: after receiving a charging instruction, obtaining historical test data; constructing a current-capacity hyperbolic curve composite graph and a current-temperature hyperbolic curve composite graph in turn through a first test data set and a second test data set; determining a mutation intersection capacity value and a mutation intersection temperature value respectively; continuously monitoring the charging state of the target battery; comparing each real-time charging parameter with the mutation intersection capacity value and the mutation intersection temperature value; and finally determining the charging mode of the target battery in the current charging stage based on the comparison result, switching between interval charging mode and linear charging mode to keep the target battery at a high battery charging current throughout the charging process, reducing the charging time of the target battery, achieving the purpose of electric vehicle fast charging, and improving user satisfaction.

Description

TECHNICAL FIELD

[0001] The one or more embodiments of the present specification relate to the technical field of battery charging, and in particular to a method and device for fast charging of an electric vehicle, an electronic device, and a storage medium. BACKGROUND

[0002] With the rapid development of the electric vehicle industry, the fast charging mode of electric vehicles has become an unstoppable development trend. Users are increasingly demanding shorter charging times for electric vehicle batteries when using the battery management system. Therefore, there is a need for a method for fast charging of an electric vehicle to effectively improve the charging speed of the electric vehicle battery within the maximum safe charging range allowed by the battery. However, the common battery fast charging method often causes the average charging current of the vehicle battery to gradually decrease with changes in battery capacity or cell temperature during the charging process due to the existence of step change current mutations during the charging process, resulting in excessively long charging times and failing to meet the requirement of fast charging speed, which reduces user satisfaction during charging. SUMMARY

[0003] The embodiments of the present specification provide a method and device for fast charging of an electric vehicle, an electronic device, and a storage medium, and the technical solutions are as follows:

[0004] In a first aspect, the embodiments of the present specification provide a method for fast charging of an electric vehicle, and the method comprises:

[0005] obtaining historical test data based on a target battery model of a target electric vehicle, the historical test data comprising a first test data set and a second test data set, the first test data set being data obtained by testing the target battery through an interval charging method, and the second test data set being data obtained by testing the target battery through a linear interpolation charging method;

[0006] successively constructing a current-capacity hyperbolic curve composite graph and a current-temperature hyperbolic curve composite graph based on the first test data set and the second test data set, and determining a mutation intersection capacity value in the current-capacity hyperbolic curve composite graph and a mutation intersection temperature value in the current-temperature hyperbolic curve composite graph based on an extreme value algorithm;

[0007] continuously monitoring a charging state of the target battery to obtain real-time charging parameters, the real-time charging parameters comprising a real-time battery capacity and a real-time cell temperature;

[0008] The real-time battery capacity and the mutation intersection capacity value, and the real-time battery cell temperature and the mutation intersection temperature value are compared respectively to obtain comparison results, and a charging mode of the target battery in a current charging stage is determined based on the comparison results, the charging mode including an interval charging mode and a linear charging mode.

[0009] In a second aspect, a quick charging device for an electric vehicle is provided, and the device includes:

[0010] An acquisition module is configured to acquire historical test data based on a target battery model of a target electric vehicle, the historical test data including a first test data set and a second test data set, the first test data set being data obtained by testing the target battery through an interval charging method, and the second test data set being data obtained by testing the target battery through a linear interpolation charging method;

[0011] A construction module is configured to sequentially construct a current-capacity hyperbolic curve composite graph and a current-temperature hyperbolic curve composite graph based on the first test data set and the second test data set, and determine a mutation intersection capacity value in the current-capacity hyperbolic curve composite graph and a mutation intersection temperature value in the current-temperature hyperbolic curve composite graph based on an extreme value algorithm;

[0012] A monitoring module is configured to continuously monitor a charging state of the target battery to obtain real-time charging parameters, the real-time charging parameters including a real-time battery capacity and a real-time battery cell temperature;

[0013] A determination module is configured to compare the real-time battery capacity with the mutation intersection capacity value, and compare the real-time battery cell temperature with the mutation intersection temperature value, to obtain comparison results, and determine a charging mode of the target battery in a current charging stage based on the comparison results, the charging mode including an interval charging mode and a linear charging mode.

[0014] In a third aspect, an electronic device is provided, including a device processor and a memory;

[0015] The device processor is connected to the memory;

[0016] The memory is configured to store executable program codes;

[0017] The device processor runs a program corresponding to the executable program codes by reading the executable program codes stored in the memory, to perform the steps of the method provided in the first aspect or any possible implementation manner of the first aspect.

[0018] In a fourth aspect, a computer-readable storage medium is provided, and the computer-readable storage medium stores a computer program. The computer-readable storage medium stores instructions, which, when executed on a computer or device processor, cause the computer or device processor to perform the method provided in the first aspect or any possible implementation manner of the first aspect.

[0019] The technical solutions provided by some embodiments of the present specification have at least the following beneficial effects:

[0020] In one or more embodiments of the present specification, after receiving the charging instruction, the historical test data is obtained, the current-capacity hyperbolic curve composite graph and the current-temperature hyperbolic curve composite graph are sequentially constructed through the first test data set and the second test data set, the mutation intersection capacity value and the mutation intersection temperature value are determined respectively, the charging state of the target battery is continuously monitored, each real-time charging parameter is compared with the mutation intersection capacity value and the mutation intersection temperature value respectively, and finally the charging mode of the target battery in the current charging stage is determined based on the comparison result. The switching between the interval charging mode and the linear charging mode enables the target battery to maintain a high battery charging current throughout the entire charging process, reduces the charging time of the target battery, achieves the purpose of fast charging of the electric vehicle, and improves the user's use satisfaction. BRIEF DESCRIPTION OF DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required to be used in the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0022] Figure 1 A system architecture schematic diagram of an electric vehicle fast charging method provided by an embodiment of the present specification is shown in the figure.

[0023] Figure 2 A flowchart of an electric vehicle fast charging method provided by an embodiment of the present specification is shown in the figure.

[0024] Figure 3 A structural schematic diagram of an electric vehicle fast charging device provided by an embodiment of the present specification is shown in the figure.

[0025] Figure 4 A structural schematic diagram of an electronic device provided by an embodiment of the present specification is shown in the figure. DETAILED DESCRIPTION

[0026] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application.

[0027] The terms "first", "second", "third", and the like in the description and the claims of the present specification and the above-described drawings are used to distinguish different objects, and are not used to describe a particular order. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a list of steps or units is not limited to the listed steps or units, but can optionally include other steps or units not listed or can optionally include other steps or units inherent to such processes, methods, products or devices.

[0028] The following description provides examples and does not limit the scope, applicability or examples set forth in the claims. Changes can be made in the functions and arrangements of described elements without departing from the scope of the present specification. Various examples can appropriately omit, replace or add various processes or components. For example, the described methods can be performed in a different order from the described order, and various steps can be added, omitted or combined. In addition, features described with respect to some examples can be combined into other examples.

[0029] Please refer to Figure 1 , Figure 1 A system architecture schematic diagram of an electric vehicle fast charging method provided by an embodiment of the present specification is shown.

[0030] As Figure 1 shown, the system architecture of the electric vehicle fast charging method can at least include a terminal 10, a server 20 and a network 30.

[0031] The terminal 10 includes, but is not limited to, electronic devices such as smartphones, desktop computers, tablets, laptops, smart speakers, digital assistants, smart wearable devices, etc., and can also be software such as applications running on the above-mentioned electronic devices. Optionally, the operating system running on the electronic device can include, but is not limited to, Android system, IOS system, Linux, Windows, etc. Optionally, the terminal 10 provides fast charging services to users, and the terminal 10 can obtain the fast charging instructions of the application programming interface and send a fast charging request to the server 20.

[0032] The server 20 can provide background services for the terminal 10. According to a fast charging request sent by the terminal 10, the server 20 can obtain a series of fast charging instructions, and the server 20 transmits the fast charging instructions to other terminals 10 through the network 30. Specifically, the server 20 can be a physical server, a server cluster composed of multiple physical servers, or a distributed system. The server 20 can also be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and basic cloud computing services such as big data and artificial intelligence platforms.

[0033] The network 30 is a medium for providing a communication link between the terminal 10 and the server 20. The network 30 can include various connection types, such as wired, wireless communication links, or optical fiber cables, etc.

[0034] In addition, it should be noted that Figure 1 The system shown is only one provided by the present disclosure, and in actual application, other systems can also be included, for example, more terminals can be included.

[0035] In the embodiments of the present disclosure, the terminal 10 and the server 20 described above can be directly or indirectly connected through wired or wireless communication, which is not limited in the present disclosure.

[0036] Next, please refer to Figure 2 , Figure 2 The overall flowchart of the fast charging method provided by the embodiments of the present disclosure is shown, which can be used in the server 20.

[0037] As Figure 2 shown, the fast charging method can at least include the following steps:

[0038] Step 201, obtaining historical test data based on a target battery model of a target electric vehicle.

[0039] The historical test data includes a first test data set and a second test data set. The first test data set is data obtained by testing the target battery through the interval charging method, and the second test data set is data obtained by testing the target battery through the linear interpolation charging method.

[0040] In the embodiments of the present application, in order to perform fast charging on the target electric vehicle, the historical test data corresponding to the target battery model of the target electric vehicle can be determined first after receiving the fast charging instruction. The test data corresponding to all battery models currently available on the market are included in the charging system. The test data can be obtained by continuously charging each type of battery using interval charging method and linear interpolation charging method, and the battery parameter data of each type of battery can be monitored in real time. The battery parameter data includes real-time battery capacity, cell temperature, charging current and charging voltage during the charging process. Therefore, the historical test data of the target battery model can be divided into a first test data group and a second test data group. The first test data group includes the battery parameter data obtained by charging test of the target battery using interval charging method, and the second test data group includes the battery parameter data obtained by charging test of the target battery using linear interpolation charging method.

[0041] In an implementation manner, the historical test data is obtained based on the target battery model of the target electric vehicle, including:

[0042] determining the target battery model of the target electric vehicle;

[0043] determining the historical test data corresponding to the target battery model based on the test database.

[0044] In the embodiments of the present application, since the test data in the system includes data corresponding to all battery models currently available on the market, the target battery model of the target electric vehicle needs to be determined first from the charging instruction issued by the target user terminal or the remote touch screen. Then, the test data corresponding to all battery models can be grouped into a test database, in which each type of battery corresponds to a group of historical test data. Further, the determined target battery model is input into the test database, and the corresponding historical test data is output.

[0045] Step 202, constructing current-capacity hyperbolic curve composite graph and current-temperature hyperbolic curve composite graph based on the first test data group and the second test data group in sequence, and determining the mutation intersection capacity value in the current-capacity hyperbolic curve composite graph and the mutation intersection temperature value in the current-temperature hyperbolic curve composite graph based on the extremum algorithm.

[0046] In the embodiments of the present application, after obtaining the first test data set and the second test data set of the target battery model, the first test data set and the second test data set can be screened out to exclude accidental error data caused by sensor collection errors. Then, the test data can be filled in the specified rule table, such as the battery capacity, the cell temperature and the battery current table, or the target data required for subsequent construction of the target curve can be selected. Further, the initial current-capacity coordinate system and the initial current-temperature coordinate system are constructed, and the corresponding target data is respectively fitted in the current-capacity coordinate system according to the test grouping, to obtain the first current-capacity curve corresponding to the first test data set and the second current-capacity curve corresponding to the second test data set, and the current-capacity hyperbolic curve composite graph is obtained after merging, and the current-temperature hyperbolic curve composite graph is obtained in the same way. Then, in order to determine which target charging method corresponds to a larger battery current at the same time, so as to achieve the purpose of reducing the battery charging time, the extreme value algorithm can be used to determine the intersection extreme mutation point of the two test curves in the current-capacity hyperbolic curve composite graph, and the corresponding mutation intersection point capacity value is determined according to the intersection extreme mutation point, and the mutation intersection point temperature value in the current-temperature hyperbolic curve composite graph can be obtained in the same way.

[0047] In an implementation manner, the current-capacity hyperbolic curve composite graph and the current-temperature hyperbolic curve composite graph are sequentially constructed based on the first test data set and the second test data set, comprising:

[0048] The current-capacity test data and the current-temperature test data in the first test data set and the second test data set are determined respectively, the current-capacity test data is the test data corresponding to the fixed cell temperature, and the current-temperature test data is the test data corresponding to the fixed battery capacity.

[0049] The current-capacity test data and the current-temperature test data are sequentially fitted based on the test data grouping to obtain the current-capacity hyperbolic curve composite graph and the current-temperature hyperbolic curve composite graph, the current-capacity hyperbolic curve composite graph is the composite graph corresponding to the current-capacity test data, and the current-temperature hyperbolic curve composite graph is the composite graph corresponding to the current-temperature test data.

[0050] In the embodiments of the present application, the construction of the current-capacity hyperbolic curve composite graph and the current-temperature hyperbolic curve composite graph can first determine the current-capacity test data corresponding to the test when the temperature of the battery cell is fixed in the first test data set, and the current-temperature test data corresponding to the test when the battery capacity is fixed. Then, the initial current-capacity coordinate system and the initial current-temperature coordinate system are constructed, and the current-capacity test data is curve-fitted in the initial current-capacity coordinate system to obtain the first current-capacity curve, and the current-temperature test data is curve-fitted in the initial current-temperature coordinate system to obtain the first current-temperature curve. Similarly, the current-capacity test data corresponding to the test when the temperature of the battery cell is fixed in the second test data set, and the current-temperature test data corresponding to the test when the battery capacity is fixed are determined, the current-capacity test data is curve-fitted in the initial current-capacity coordinate system to obtain the second current-capacity curve, and the current-temperature test data is curve-fitted in the initial current-temperature coordinate system to obtain the second current-temperature curve. Finally, the first current-capacity curve and the second current-capacity curve in the current-capacity coordinate system are integrated to obtain the current-capacity hyperbolic curve composite graph, and the first current-temperature curve and the second current-temperature curve in the current-temperature coordinate system are integrated to obtain the current-temperature hyperbolic curve composite graph.

[0051] In an implementation manner, the extreme value algorithm is used to determine the sudden intersection point capacity value in the current-capacity hyperbolic curve composite graph and the sudden intersection point temperature value in the current-temperature hyperbolic curve composite graph, respectively, including:

[0052] The extreme value algorithm is used to determine the first curve sudden point in the current-capacity hyperbolic curve composite graph and the second curve sudden point in the current-temperature hyperbolic curve composite graph, respectively;

[0053] The abscissa values corresponding to the first curve sudden point and the second curve sudden point are determined respectively to obtain the sudden intersection point capacity value corresponding to the first curve sudden point and the sudden intersection point temperature value corresponding to the second curve sudden point.

[0054] In the embodiments of the present application, taking the current-capacity hyperbolic composite graph as an example, first, the extreme value algorithm is used to determine the extreme points of the two current-capacity curves in the current-capacity hyperbolic composite graph, and then the target extreme point meeting the requirements is analyzed from all the extreme points through maximum value analysis, that is, on one side of the target extreme point, the maximum value of the first current-capacity curve is always greater than or equal to the maximum value of the second current-capacity curve, and on the other side of the target extreme point, the maximum value of the first current-capacity curve is always less than the maximum value of the second current-capacity curve, and the target extreme point is regarded as the first curve mutation point. Similarly, the second curve mutation point is determined in the current-temperature hyperbolic composite graph. Further, the abscissa value corresponding to the first curve mutation point, that is, the battery capacity at this time, is determined and regarded as the mutation intersection capacity value corresponding to the first curve mutation point, and similarly, the abscissa value corresponding to the second curve mutation point is determined and regarded as the mutation intersection temperature value corresponding to the second curve mutation point.

[0055] In step 203, the charging state of the target battery is continuously monitored to obtain real-time charging parameters.

[0056] The real-time charging parameters include real-time battery capacity and real-time cell temperature.

[0057] In the embodiments of the present application, in order to improve the charging speed of the target battery, the charging state of the target battery needs to be continuously monitored after the target battery is connected for charging, and the real-time charging parameters obtained are used to analyze the best charging mode at this time, so that the battery charging current is at the theoretical maximum safety value and the charging time is reduced.

[0058] The real-time charging parameters can include real-time battery capacity and real-time cell temperature of the target battery during charging.

[0059] In step 204, the real-time battery capacity and the mutation intersection capacity value, and the real-time cell temperature and the mutation intersection temperature value are compared respectively to obtain comparison results, and the charging mode of the target battery in the current charging stage is determined based on the comparison results.

[0060] The charging mode includes an interval charging mode and a linear charging mode.

[0061] In the embodiments of the present application, when the charging state of the target battery is continuously monitored, the real-time battery capacity and the determined mutation intersection capacity value, and the real-time cell temperature and the determined mutation intersection temperature value are continuously compared respectively, and continuously real-time comparison results are obtained. Then, according to the continuously real-time comparison results, the best charging mode of the target battery in the current charging stage is determined, so that the target battery maintains a high battery charging current from the beginning of charging to the completion of charging, and the charging time of the target battery is reduced.

[0062] wherein the optional charging mode includes an interval charging mode and a linear charging mode.

[0063] In an implementation, the comparing the real-time battery capacity with the mutation intersection capacity value and the real-time battery cell temperature with the mutation intersection temperature value respectively to obtain comparison results, and determining the charging mode of the target battery in the current charging stage based on the comparison results, includes:

[0064] comparing the real-time battery capacity with the mutation intersection capacity value to obtain a first comparison result;

[0065] comparing the real-time battery cell temperature with the mutation intersection temperature value to obtain a second comparison result;

[0066] combining the first comparison result and the second comparison result to obtain a judgment result, and determining the charging mode of the target battery in the current charging stage based on the judgment result.

[0067] In the embodiments of the present specification, the real-time battery capacity can be compared with the mutation intersection capacity value first to obtain a first comparison result, and then the real-time battery cell temperature can be compared with the mutation intersection temperature value to obtain a second comparison result. Then, the first comparison result and the second comparison result are combined to obtain a judgment result. The first comparison result can include two cases that the real-time battery capacity is not greater than the mutation intersection capacity value and the real-time battery capacity is greater than the mutation intersection capacity value, and the second comparison result can include two cases that the real-time battery cell temperature is not greater than the mutation intersection temperature value and the real-time battery cell temperature is greater than the mutation intersection temperature value. Therefore, when the combination judgment is performed, four comparison results need to be judged. Finally, the best charging mode corresponding to the target battery in the current charging stage is determined according to the judgment result.

[0068] In an implementation, the determining the charging mode of the target battery in the current charging stage based on the judgment result includes:

[0069] when the judgment result represents that the first comparison result satisfies a first condition and the second comparison result satisfies a second condition, determining that the charging mode of the target battery in the current charging stage is a linear difference charging mode, the first condition being that the real-time battery capacity is not greater than the mutation intersection capacity value, and the second condition being that the real-time battery cell temperature is not greater than the mutation intersection temperature value;

[0070] when the judgment result represents that the first comparison result does not satisfy the first condition or the second comparison result does not satisfy the second condition, determining that the charging mode of the target battery in the current charging stage is an interval charging mode.

[0071] In the embodiments of the present application, the determination result is divided into two types. When the determination result represents that the real-time battery capacity of the target battery is not greater than the mutation intersection capacity value, and the real-time battery cell temperature is not greater than the mutation intersection temperature value, it is determined that the charging mode of the target battery in the current charging stage is the linear difference charging mode. When the determination result represents that the real-time battery capacity of the target battery is greater than the mutation intersection capacity value or the real-time battery cell temperature is greater than the mutation intersection temperature value, it is determined that the charging mode of the target battery in the current charging stage is the interval charging mode.

[0072] In an implementation manner, the method further includes:

[0073] determining at least two charging mode intervals based on the mutation intersection capacity value and the mutation intersection temperature value, and setting a charging mode for each of the charging mode intervals;

[0074] querying a current charging mode interval corresponding to the real-time battery capacity and the real-time battery cell temperature, and determining the charging mode of the target battery in the current charging stage based on the current charging mode interval.

[0075] In the embodiments of the present application, when the charging state of the target battery is continuously monitored, a plurality of charging mode intervals can be determined based on the obtained mutation intersection capacity value and the mutation intersection temperature value. As an example, when two charging mode intervals are determined, a first charging mode interval and a second charging mode interval are determined based on the obtained mutation intersection capacity value and the mutation intersection temperature value, the charging mode corresponding to the first charging mode interval is the linear difference charging mode, and the charging mode corresponding to the second charging mode interval is the interval charging mode. Then, a current charging mode interval corresponding to the real-time battery capacity and the real-time battery cell temperature is queried, and the charging mode of the target battery in the current charging stage is determined according to the charging mode interval.

[0076] The above describes specific embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the acts or steps recited in the claims can be performed in a different order than that described in the embodiments and still achieve desirable results. In addition, the processes depicted in the figures do not necessarily require the particular order shown or sequential order in order to achieve the desired results. In some implementations, multitasking and parallel processing can be advantageous or necessary.

[0077] Next, please refer to Figure 3 , Figure 3 A structure schematic diagram of a quick charging device for an electric vehicle is shown. It should be noted that, Figure 3 The quick charging device for an electric vehicle shown is used to execute the application Figure 2The method of the embodiment shown, for ease of illustration, only shows parts related to the embodiment of the present application, and specific technical details not disclosed, please refer to the present application Figure 2 The embodiment shown.

[0078] As Figure 3 The electric vehicle fast charging device shown can at least include:

[0079] The acquisition module 301 is configured to acquire historical test data based on a target battery model of a target electric vehicle, the historical test data including a first test data set and a second test data set, the first test data set being data obtained by testing the target battery through an interval charging method, and the second test data set being data obtained by testing the target battery through a linear interpolation charging method;

[0080] The construction module 302 is configured to sequentially construct a current-capacity hyperbolic curve composite graph and a current-temperature hyperbolic curve composite graph based on the first test data set and the second test data set, and determine a mutation intersection capacity value in the current-capacity hyperbolic curve composite graph and a mutation intersection temperature value in the current-temperature hyperbolic curve composite graph based on an extreme value algorithm, respectively.

[0081] The monitoring module 303 is configured to continuously monitor a charging state of the target battery to obtain real-time charging parameters, the real-time charging parameters including a real-time battery capacity and a real-time cell temperature.

[0082] The determination module 304 is configured to compare the real-time battery capacity with the mutation intersection capacity value and the real-time cell temperature with the mutation intersection temperature value, respectively, to obtain a comparison result, and determine a charging mode of the target battery in a current charging phase based on the comparison result, the charging mode including an interval charging mode and a linear charging mode.

[0083] In an implementation manner, the acquisition module 301 is specifically configured to:

[0084] Determine a target battery model of a target electric vehicle;

[0085] Determine historical test data corresponding to the target battery model based on a test database.

[0086] In an implementation manner, the construction module 302 is specifically configured to:

[0087] Determine current-capacity test data and current-temperature test data in the first test data set and the second test data set, respectively, the current-capacity test data being test data corresponding to a fixed cell temperature, and the current-temperature test data being test data corresponding to a fixed battery capacity.

[0088] The current-capacity test data and the current-temperature test data are sequentially subjected to curve construction based on test data grouping, to obtain a current-capacity hyperbolic curve composite graph and a current-temperature hyperbolic curve composite graph, the current-capacity hyperbolic curve composite graph being a composite graph corresponding to the current-capacity test data, and the current-temperature hyperbolic curve composite graph being a composite graph corresponding to the current-temperature test data.

[0089] In an implementation manner, the construction module 302 is specifically further configured to:

[0090] determine a first curve mutation point in the current-capacity hyperbolic curve composite graph and a second curve mutation point in the current-temperature hyperbolic curve composite graph based on an extreme value algorithm;

[0091] determine horizontal coordinate values corresponding to the first curve mutation point and the second curve mutation point respectively, to obtain a mutation intersection capacity value corresponding to the first curve mutation point and a mutation intersection temperature value corresponding to the second curve mutation point.

[0092] In an implementation manner, the determination module 304 is specifically configured to:

[0093] compare the real-time battery capacity with the mutation intersection capacity value, to obtain a first comparison result;

[0094] compare the real-time battery cell temperature with the mutation intersection temperature value, to obtain a second comparison result;

[0095] combine the first comparison result and the second comparison result to obtain a judgment result, and determine the charging mode of the target battery in the current charging stage based on the judgment result.

[0096] In an implementation manner, the determination module 304 is specifically further configured to:

[0097] when the judgment result represents that the first comparison result satisfies a first condition and the second comparison result satisfies a second condition, determine that the charging mode of the target battery in the current charging stage is a linear difference charging mode, the first condition being that the real-time battery capacity is not greater than the mutation intersection capacity value, and the second condition being that the real-time battery cell temperature is not greater than the mutation intersection temperature value;

[0098] when the judgment result represents that the first comparison result does not satisfy the first condition or the second comparison result does not satisfy the second condition, determine that the charging mode of the target battery in the current charging stage is an interval charging mode.

[0099] In an implementation manner, the determination module 304 is specifically further configured to:

[0100] At least two charging mode intervals are determined based on the mutation intersection capacity value and the mutation intersection temperature value, and a charging mode is set for each of the charging mode intervals;

[0101] The current charging mode interval corresponding to the real-time battery capacity and the real-time cell temperature is queried, and the charging mode of the target battery in the current charging stage is determined based on the current charging mode interval.

[0102] Those skilled in the art can clearly understand that the technical solutions of the embodiments of the present application can be implemented by means of software and / or hardware. The "unit" and "module" in the specification refer to software and / or hardware that can independently complete or cooperate with other components to complete a specific function, and the hardware may, for example, be a field programmable gate array (FPGA), an integrated circuit (IC), etc.

[0103] The various processing units and / or modules of the embodiments of the present application can be implemented by analog circuits that implement the functions of the embodiments of the present application, or can be implemented by software that executes the functions of the embodiments of the present application.

[0104] Next, please refer to Figure 4 , Figure 4 A structural schematic diagram of an electronic device provided by an embodiment of the present specification is shown.

[0105] As Figure 4 shown, the electronic device 400 can include at least one device processor 401, at least one network interface 404, a user interface 403, a memory 405, and at least one communication bus 402.

[0106] The communication bus 402 can be used to realize the connection and communication of the above-mentioned components.

[0107] The user interface 403 can include a key, and the optional user interface can also include a standard wired interface, a wireless interface.

[0108] The network interface 404 can include, but is not limited to, a Bluetooth module, an NFC module, a Wi-Fi module, etc.

[0109] The device processor 401 can include one or more processing cores. The device processor 401 connects various parts within the entire electronic device 400 by various interfaces and lines, executes various functions of the electronic device 400 and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 405, and calling data stored in the memory 405. Alternatively, the device processor 401 can be implemented in at least one of a hardware form of a DSP, an FPGA, and a PLA. The device processor 401 can integrate one or a combination of a CPU, a GPU, and a modem. Among them, the CPU mainly processes operating systems, user interfaces, and application programs; the GPU is responsible for rendering and drawing the content required to be displayed on the display screen; and the modem is used for processing wireless communication. It can be understood that the above-mentioned modem can also not be integrated into the device processor 401, but can be implemented by a separate chip.

[0110] The memory 405 can include a RAM and can also include a ROM. Alternatively, the memory 405 includes a non-transitory computer readable medium. The memory 405 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 405 can include a program storage area and a data storage area, wherein the program storage area can store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area can store data involved in the above-mentioned various method embodiments, etc. The memory 405 can also be at least one storage device located away from the aforementioned device processor 401. As shown, the memory 405 as a computer storage medium can include an operating system, a network communication module, a user interface module, and program instructions. Figure 4 As shown, the memory 405 as a computer storage medium can include an operating system, a network communication module, a user interface module, and program instructions.

[0111] Specifically, the device processor 401 can be used to call the electric vehicle fast charging application stored in the memory 405, and specifically perform the following operations:

[0112] obtain historical test data based on a target battery model of the target electric vehicle, the historical test data including a first test data set and a second test data set, the first test data set being data obtained by testing the target battery through an interval charging method, and the second test data set being data obtained by testing the target battery through a linear interpolation charging method;

[0113] construct a current-capacity hyperbolic curve composite graph and a current-temperature hyperbolic curve composite graph in sequence based on the first test data set and the second test data set, and respectively determine a mutation intersection capacity value in the current-capacity hyperbolic curve composite graph and a mutation intersection temperature value in the current-temperature hyperbolic curve composite graph based on an extreme value algorithm.

[0114] continuously monitoring a state of charge of the target battery to obtain real-time charging parameters, the real-time charging parameters including a real-time battery capacity and a real-time cell temperature;

[0115] comparing the real-time battery capacity with the mutation intersection capacity value and comparing the real-time cell temperature with the mutation intersection temperature value respectively to obtain comparison results, and determining a charging mode of the target battery in a current charging stage based on the comparison results, the charging mode including an interval charging mode and a linear charging mode.

[0116] As an option of the embodiment of the present specification, the historical test data corresponding to the target battery model of the target electric vehicle is obtained based on the target battery model of the target electric vehicle, including:

[0117] determining a target battery model of a target electric vehicle;

[0118] determining historical test data corresponding to the target battery model based on a test database.

[0119] As an option of the embodiment of the present specification, the current-capacity hyperbolic curve composite graph and the current-temperature hyperbolic curve composite graph are sequentially constructed based on the first test data set and the second test data set, including:

[0120] determining current-capacity test data and current-temperature test data in the first test data set and the second test data set respectively, the current-capacity test data being test data corresponding to a fixed cell temperature, and the current-temperature test data being test data corresponding to a fixed battery capacity;

[0121] sequentially performing curve construction on the current-capacity test data and the current-temperature test data based on test data grouping to obtain a current-capacity hyperbolic curve composite graph and a current-temperature hyperbolic curve composite graph, the current-capacity hyperbolic curve composite graph being a composite graph corresponding to the current-capacity test data, and the current-temperature hyperbolic curve composite graph being a composite graph corresponding to the current-temperature test data.

[0122] As an option of the embodiment of the present specification, the mutation intersection capacity value in the current-capacity hyperbolic curve composite graph and the mutation intersection temperature value in the current-temperature hyperbolic curve composite graph are determined based on an extreme value algorithm, including:

[0123] determining a first curve mutation point in the current-capacity hyperbolic curve composite graph and a second curve mutation point in the current-temperature hyperbolic curve composite graph based on an extreme value algorithm;

[0124] Determine the abscissa value corresponding to the first curve mutation point and the second curve mutation point respectively, obtain the mutation intersection capacity value corresponding to the first curve mutation point and the mutation intersection temperature value corresponding to the second curve mutation point.

[0125] As an option of the embodiment of the present specification, the comparing the real-time battery capacity with the mutation intersection capacity value and the real-time battery cell temperature with the mutation intersection temperature value respectively to obtain comparison results, and determining the charging mode of the target battery in the current charging stage based on the comparison results, comprises:

[0126] Comparing the real-time battery capacity with the mutation intersection capacity value to obtain a first comparison result;

[0127] Comparing the real-time battery cell temperature with the mutation intersection temperature value to obtain a second comparison result;

[0128] Combining the first comparison result and the second comparison result to obtain a judgment result, and determining the charging mode of the target battery in the current charging stage based on the judgment result.

[0129] As an option of the embodiment of the present specification, the determining the charging mode of the target battery in the current charging stage based on the judgment result, comprises:

[0130] When the judgment result represents that the first comparison result satisfies a first condition and the second comparison result satisfies a second condition, determining that the charging mode of the target battery in the current charging stage is a linear difference charging mode, the first condition is that the real-time battery capacity is not greater than the mutation intersection capacity value, and the second condition is that the real-time battery cell temperature is not greater than the mutation intersection temperature value;

[0131] When the judgment result represents that the first comparison result does not satisfy the first condition or the second comparison result does not satisfy the second condition, determining that the charging mode of the target battery in the current charging stage is an interval charging mode.

[0132] As an option of the embodiment of the present specification, the method further comprises:

[0133] Determining at least two charging mode intervals based on the mutation intersection capacity value and the mutation intersection temperature value, and setting a charging mode for each of the charging mode intervals;

[0134] Querying the current charging mode interval corresponding to the real-time battery capacity and the real-time battery cell temperature, and determining the charging mode of the target battery in the current charging stage based on the current charging mode interval.

[0135] The embodiments of the present specification further provide a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the steps of the above method. The computer readable storage medium can include, but is not limited to, any type of disk, including a floppy disk, an optical disk, a DVD, a CD-ROM, a micro drive, and a magneto-optical disk, a ROM, a RAM, an EPROM, an EEPROM, a DRAM, a VRAM, a flash memory device, a magnetic card or an optical card, a nano system (including a molecular memory IC), or any type of medium or device suitable for storing instructions and / or data.

[0136] It should be noted that, for the foregoing method embodiments, in order to simply describe, they are all expressed as a combination of a series of actions, but those skilled in the art should know that the present application is not limited to the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should know that the embodiments described in the specification all belong to preferred embodiments, and the actions and modules involved are not necessarily necessary for the present application.

[0137] In the above embodiments, the description of each embodiment is focused on, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0138] In several embodiments provided in the present application, it should be understood that the disclosed device can be implemented by other ways. For example, the device embodiments described above are only schematic, and the division of the units is only a logical function division, and there can be another division way in actual implementation, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some service interface, device or unit, and can be electrical or other forms.

[0139] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, that is, they can be located in one place, or can be distributed on a plurality of network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0140] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0141] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable memory. Based on such understanding, the technical solutions of the present application, essentially or in other words, the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a memory and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned memory includes: a U disk, a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store program codes.

[0142] A person of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be executed by a program instructing relevant hardware, and the program can be stored in a computer readable memory, and the memory can include: a flash disk, a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a magnetic disk or an optical disk, etc.

[0143] The above describes specific embodiments of the present specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be executed in an order different from that in the embodiments and still achieve the desired result. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are possible or can be advantageous.

Claims

1. A method for fast charging of an electric vehicle, characterized in that: The method comprises: Acquiring historical test data based on a target battery model of a target electric vehicle, the historical test data including a first test data group and a second test data group, the first test data group being data obtained by testing the target battery using an interval charging method, and the second test data group being data obtained by testing the target battery using a linear interpolation charging method; Determine current-capacity test data and current-temperature test data in the first test data group and the second test data group, respectively, wherein the current-capacity test data is test data corresponding to a fixed cell temperature, and the current-temperature test data is test data corresponding to a fixed battery capacity; Based on the test data grouping, the current-capacity test data and the current-temperature test data are respectively constructed to obtain a current-capacity hyperbola composite graph and a current-temperature hyperbola composite graph, wherein the current-capacity hyperbola composite graph is a composite graph corresponding to the current-capacity test data, and the current-temperature hyperbola composite graph is a composite graph corresponding to the current-temperature test data; Determine a first curve mutation point in the current-capacity hyperbola composite graph and a second curve mutation point in the current-temperature hyperbola composite graph based on an extreme value algorithm; Determine the horizontal coordinate values ​​corresponding to the mutation point of the first curve and the mutation point of the second curve respectively, and obtain the mutation intersection capacity value corresponding to the mutation point of the first curve and the mutation intersection temperature value corresponding to the mutation point of the second curve; Continuously monitoring the charging state of the target battery to obtain real-time charging parameters, wherein the real-time charging parameters include real-time battery capacity and real-time battery cell temperature; The real-time battery capacity is compared with the mutation intersection capacity value, and the real-time battery cell temperature is compared with the mutation intersection temperature value to obtain comparison results, and the charging mode of the target battery in the current charging stage is determined based on the comparison results. The charging mode includes an interval charging mode and a linear charging mode.

2. The method according to claim 1, characterized in that The acquiring of historical test data based on a target battery model of a target electric vehicle includes: Determine the target battery model for the target electric vehicle; Determine historical test data corresponding to the target battery model based on a test database.

3. The method according to claim 1, characterized in that The comparing the real-time battery capacity with the mutation intersection capacity value, and the real-time battery cell temperature with the mutation intersection temperature value, respectively, to obtain comparison results, and determining the charging mode of the target battery in the current charging stage based on the comparison results, includes: Comparing the real-time battery capacity with the mutation intersection capacity value to obtain a first comparison result; Comparing the real-time battery cell temperature with the mutation intersection temperature value to obtain a second comparison result; The first comparison result and the second comparison result are combined and judged to obtain a judgment result, and the charging mode of the target battery in the current charging stage is determined based on the judgment result.

4. The method according to claim 3, characterized in that The determining, based on the judgment result, a charging mode of the target battery in the current charging stage, includes: When the judgment result is characterized by the first comparison result satisfying a first condition and the second comparison result satisfying a second condition, determining that the charging mode of the target battery in the current charging stage is a linear difference charging mode, the first condition being that the real-time battery capacity is not greater than the mutation intersection capacity value, and the second condition being that the real-time battery cell temperature is not greater than the mutation intersection temperature value; When the judgment result indicates that the first comparison result does not satisfy the first condition or the second comparison result does not satisfy the second condition, it is determined that the charging mode of the target battery in the current charging stage is the interval charging mode.

5. The method according to claim 1, wherein The method further comprises: Determine at least two charging mode intervals based on the mutation intersection capacity value and the mutation intersection temperature value, and set a charging mode for each of the charging mode intervals respectively; A current charging mode interval corresponding to the real-time battery capacity and the real-time battery cell temperature is queried, and a charging mode of the target battery in a current charging stage is determined based on the current charging mode interval.

6. A fast charging device for electric vehicles, characterized in that: The device comprises: an acquisition module, configured to acquire historical test data based on a target battery model of a target electric vehicle, the historical test data comprising a first test data group and a second test data group, the first test data group being data obtained by testing the target battery using an interval charging method, and the second test data group being data obtained by testing the target battery using a linear interpolation charging method; A construction module, configured to respectively determine current-capacity test data and current-temperature test data in the first test data group and the second test data group, wherein the current-capacity test data is test data corresponding to a fixed cell temperature and the current-temperature test data is test data corresponding to a fixed battery capacity; Based on the test data grouping, the current-capacity test data and the current-temperature test data are respectively constructed to obtain a current-capacity hyperbola composite graph and a current-temperature hyperbola composite graph, wherein the current-capacity hyperbola composite graph is a composite graph corresponding to the current-capacity test data, and the current-temperature hyperbola composite graph is a composite graph corresponding to the current-temperature test data; Determine a first curve mutation point in the current-capacity hyperbola composite graph and a second curve mutation point in the current-temperature hyperbola composite graph based on an extreme value algorithm; Determine the horizontal coordinate values ​​corresponding to the mutation point of the first curve and the mutation point of the second curve respectively, and obtain the mutation intersection capacity value corresponding to the mutation point of the first curve and the mutation intersection temperature value corresponding to the mutation point of the second curve; A monitoring module is used to continuously monitor the charging state of the target battery and obtain real-time charging parameters, wherein the real-time charging parameters include real-time battery capacity and real-time battery cell temperature; A determination module is used to compare the real-time battery capacity with the mutation intersection capacity value, and the real-time battery cell temperature with the mutation intersection temperature value, respectively, to obtain comparison results, and determine the charging mode of the target battery in the current charging stage based on the comparison results, wherein the charging mode includes an interval charging mode and a linear charging mode.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, wherein the computer-readable storage medium stores instructions, which, when the instructions are executed on a computer or a processor, cause the computer or processor to execute the steps of the method according to any one of claims 1 to 5.

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