Battery charging time prediction method and device, prediction equipment, product and medium

Abstract

The invention provides a battery charging time prediction method and device, prediction equipment, a product and a medium, and relates to the technical field of batteries. The method comprises the following steps: simulating a charging process of a battery in a power battery system according to parameters related to charging of the power battery system to obtain corresponding simulation parameters of the battery in the charging process; determining the real-time charging current of the battery according to the simulation parameters; and according to the real-time charging current, the charging time required for the battery to reach the target charge state is predicted. According to the scheme, the problem that the charging time of the power battery is difficult to accurately predict in the vehicle research and development stage in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the field of battery technology, and in particular to a battery charging time prediction method, device, prediction equipment, product and medium. Background Art

[0002] The battery is one of the core components of electric vehicles. The performance parameters of the battery will affect the performance of the entire vehicle. For example, the energy density and power of the battery will affect the vehicle's endurance, the discharge power will affect the vehicle's acceleration, and the fast charging performance will affect the vehicle's charging time.

[0003] When developing electric vehicles, the selection of the power battery system must match the needs of the entire vehicle. Taking charging as an example, if the charging time target is set according to the needs of the entire vehicle, then the power battery system, as a subsystem of the entire vehicle, needs to undertake the charging time target. Specifically, the charging time requirements need to be broken down into related items such as the battery cell, thermal management system, and electrical system to determine whether the selection of the power battery system can meet the needs of the entire vehicle.

[0004] However, existing technologies make it difficult to accurately predict the charging time of power batteries during the vehicle development stage, which is not conducive to the evaluation and optimization of the selection scheme of the power battery system. Summary of the invention

[0005] The embodiments of the present invention provide a battery charging time prediction method, device, prediction equipment, product and medium to solve the problem in the prior art that it is difficult to accurately predict the charging time of a power battery in the vehicle development stage.

[0006] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0007] According to one aspect of the present invention, a method for predicting battery charging time is provided, comprising:

[0008] According to the parameters related to the charging of the power battery system, a charging process of the battery in the power battery system is simulated to obtain the simulation parameters corresponding to the battery in the charging process;

[0009] Determining a real-time charging current of the battery according to the simulation parameters;

[0010] The charging time required for the battery to reach a target state of charge is predicted based on the real-time charging current.

[0011] Optionally, the parameters related to charging of the power battery system include: at least one thermal parameter related to temperature change of the power battery system during charging simulation, and at least one electrical parameter related to voltage of a battery cell in the power battery system;

[0012] The simulation parameters include at least two of a simulation temperature, a simulation voltage, and a simulation state of charge.

[0013] Optionally, the thermal parameters include battery cell mass, specific heat capacity, thermal conductivity and battery cell surface area;

[0014] The simulating the charging process of the battery in the power battery system according to the parameters related to the charging of the power battery system to obtain the simulation parameters corresponding to the battery in the charging process includes:

[0015] Determining the temperature rise rate of the battery according to the mass of the battery cell, the specific heat capacity, the thermal conductivity and the surface area of ​​the battery cell;

[0016] The simulation temperature is determined according to the temperature rise rate of the battery and the ambient temperature of the environment where the battery is located.

[0017] Optionally, the electrical parameters include: power supply electromotive force, capacitor polarization, chemical polarization, ohmic internal resistance and charging current of the battery;

[0018] The simulating the charging process of the battery in the power battery system according to the parameters related to the charging of the power battery system to obtain the simulation parameters corresponding to the battery in the charging process includes:

[0019] The simulation voltage is determined according to the power supply electromotive force, the capacitor polarization, the chemical polarization, the ohmic internal resistance and the charging current of the battery.

[0020] Optionally, the electrical parameters include: the charging current of the battery, the rated capacity of the power battery system and the initial state of charge of the battery;

[0021] The simulating the charging process of the battery in the power battery system according to the parameters related to the charging of the power battery system to obtain the simulation parameters corresponding to the battery in the charging process includes:

[0022] The simulated state of charge is determined based on an ampere-hour integration method according to the charging current of the battery, the rated capacity of the power battery system and the initial state of charge of the battery.

[0023] Optionally, determining the real-time charging current of the battery according to the simulation parameter includes at least one of the following:

[0024] According to the simulated temperature and the simulated voltage, query a first charging matrix to determine a real-time charging current of the battery, wherein the first charging matrix represents a mapping relationship between temperature, voltage, and current;

[0025] According to the simulated temperature and the simulated state of charge, a second charging matrix is ​​queried to determine the real-time charging current of the battery, wherein the second charging matrix represents a mapping relationship between temperature, state of charge and current.

[0026] According to another aspect of the present invention, a battery charging time prediction device is provided, comprising:

[0027] A first processing module, configured to simulate a charging process of a battery in the power battery system according to parameters related to charging of the power battery system, and obtain simulation parameters corresponding to the battery in the charging process;

[0028] A second processing module, used for determining a real-time charging current of the battery according to the simulation parameters;

[0029] The first prediction module is used to predict the charging time required for the battery to reach a target state of charge according to the real-time charging current.

[0030] Optionally, the parameters related to charging of the power battery system include: at least one thermal parameter related to temperature change of the power battery system during charging simulation, and at least one electrical parameter related to voltage of a battery cell in the power battery system;

[0031] The simulation parameters include at least two of a simulation temperature, a simulation voltage, and a simulation state of charge.

[0032] Optionally, the thermal parameters include battery cell mass, specific heat capacity, thermal conductivity and battery cell surface area;

[0033] The first processing module comprises:

[0034] A first processing unit, configured to determine a temperature rise rate of the battery according to the mass of the battery cell, the specific heat capacity, the thermal conductivity coefficient and the surface area of ​​the battery cell;

[0035] The second processing unit is used to determine the simulation temperature according to the temperature rise rate of the battery and the ambient temperature of the environment where the battery is located.

[0036] Optionally, the electrical parameters include: power supply electromotive force, capacitor polarization, chemical polarization, ohmic internal resistance and charging current of the battery;

[0037] The first processing module comprises:

[0038] The third processing unit is used to determine the simulation voltage according to the power supply electromotive force, the capacitor polarization, the chemical polarization, the ohmic internal resistance and the charging current of the battery.

[0039] Optionally, the electrical parameters include: the charging current of the battery, the rated capacity of the power battery system and the initial state of charge of the battery;

[0040] The first processing module comprises:

[0041] The fourth processing unit is used to determine the simulated state of charge based on the ampere-hour integration method according to the charging current of the battery, the rated capacity of the power battery system and the initial state of charge of the battery.

[0042] Optionally, the second processing module includes:

[0043] a fifth processing unit, configured to query a first charging matrix to determine a real-time charging current of the battery according to the simulated temperature and the simulated voltage, wherein the first charging matrix represents a mapping relationship between temperature, voltage, and current;

[0044] The sixth processing unit is used to query a second charging matrix according to the simulated temperature and the simulated state of charge to determine the real-time charging current of the battery, wherein the second charging matrix represents a mapping relationship between temperature, state of charge and current.

[0045] According to another aspect of the present invention, a prediction device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor; when the processor executes the computer program, the battery charging time prediction method as described above is implemented.

[0046] According to another aspect of the present invention, a computer program product is provided, comprising computer instructions, which implement the steps of the above battery charging time prediction method when executed by a processor.

[0047] According to another aspect of the present invention, a readable storage medium is provided, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps in the above battery charging time prediction method are implemented.

[0048] The beneficial effects of the present invention are:

[0049] The above scheme simulates the charging process of the battery in the power battery system according to the parameters related to the charging of the power battery system, and can obtain the corresponding simulation parameters of the battery during the charging process, and further determine the real-time charging current of the battery according to the simulation parameters. In this way, the charging time required for the battery to reach the target state of charge can be more accurately predicted according to the real-time charging current of the battery, achieving the technical effect of accurately predicting the charging time of the power battery in the vehicle development stage. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 A flowchart of a battery charging time prediction method according to an embodiment of the present invention;

[0051] Figure 2 A flowchart of a battery charging time prediction method according to another embodiment of the present invention;

[0052] Figure 3 It is a structural diagram of a battery charging time prediction device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0054] The present invention aims to solve the problem in the prior art that it is difficult to accurately predict the charging time of a power battery during the vehicle development stage, and provides a battery charging time prediction method, device, prediction equipment, product and medium.

[0055] like Figure 1 As shown, one embodiment of the present invention provides a battery charging time prediction method, comprising:

[0056] Step 101 , simulating a charging process of a battery in a power battery system according to parameters related to charging of the power battery system, and obtaining simulation parameters corresponding to the battery in the charging process.

[0057] In some embodiments, parameters related to charging of the power battery system include: at least one thermal parameter related to the temperature change of the power battery system during the charging simulation process, and at least one electrical parameter related to the voltage of the battery cells in the power battery system; the simulation parameters include at least two of the simulated temperature, the simulated voltage and the simulated state of charge.

[0058] For example, thermal parameters may include at least one of the following: battery cell mass (m), the specific heat capacity (c), thermal conductivity (h) and battery cell surface area (S), and electrical parameters may include battery cell internal resistance (R), etc. It should be noted that in the early stages of power battery development, battery cell design and thermal management design are not yet mature, which makes it difficult to accurately and quickly predict the temperature changes of the power battery system. In an embodiment of the present invention, a battery cell internal resistance database can be established in advance. In this way, based on the database, the corresponding battery cell internal resistance (R) can be obtained by searching the database through parameters such as the battery cell system, power, energy density, and charging equivalent rate, and then the internal resistance (R) of the battery cell can be obtained. 2 R can estimate the self-generated heat of the power battery.

[0059] Step 102: determining the real-time charging current of the battery according to the simulation parameters.

[0060] It should be noted that a battery system charging model can be constructed. The battery system charging model can fit the temperature, voltage, and SOC during the charging process of the power battery system by fitting the charging control process of the power battery system, and obtain the corresponding simulation parameters of the battery during the charging process.

[0061] In the charging simulation process, simulation parameters (such as simulation temperature, simulation state of charge, simulation voltage) can be obtained according to the fitting, and the charging current of the battery at the next moment (that is, the real-time charging current of the battery) can be fitted. In this way, the real-time charging current of the battery during the charging process can be obtained through continuous iteration of simulation parameters during the charging simulation process, thus realizing the real-time simulation of the battery charging current.

[0062] Step 103: predicting the charging time required for the battery to reach a target state of charge according to the real-time charging current.

[0063] Here, the target state of charge (i.e., target SOC) can be understood as: a charging target set for charging simulation, that is, a SOC can be preset as the target state of charge. Therefore, when the simulated state of charge (SOC t ) reaches the target state of charge, it means that the current charging target has been completed. It should be noted that the target state of charge can be preset or calculated.

[0064] For example, the SOC step size can be set in advance (assuming it is 15%), and the sum of the initial state of charge (i.e., the initial SOC of the battery at the start time of battery charging, assumed to be 10%) and the preset SOC step size can be determined as the target state of charge (e.g., 15%+10%=25%). When the simulated state of charge of the battery reaches the target state of charge (e.g., 25%), it means that the charging target of this time has been achieved. After outputting the corresponding charging time (e.g., 1h), the current SOC (i.e., the simulated state of charge at the time when the last charging was completed, e.g., 25%) can be used as the initial SOC for the next charge. The initial SOC is added to the preset SOC step size to obtain the target state of charge for the next charge (e.g., 15%+25%=40%), and the next charging simulation is started. After the simulated charging reaches the target (e.g., 40%), the charging time corresponding to this charge (e.g., 0.8h) is output. By analogy, the charging time corresponding to different SOC intervals (i.e., each initial SOC to each corresponding target SOC) can be output. For example, the above battery system charging model can output: the charging time corresponding to the SOC interval [10%, 25%] is 1h, the charging time corresponding to the SOC interval [25%, 40%] is 0.8h, and so on.

[0065] In this way, after inputting relevant technical parameters (such as the thermal parameters and electrical parameters mentioned above) into the battery system charging model and setting conditions such as the initial SOC and SOC step size (or target SOC), the battery system charging model can quickly evaluate the charging time of the battery system in the early stage of solution selection, and can be applied to the evaluation and design optimization scenarios of battery system selection solutions.

[0066] In this embodiment, the charging process of the battery in the power battery system is simulated according to the parameters related to the charging of the power battery system, and the corresponding simulation parameters of the battery in the charging process can be obtained, and the real-time charging current of the battery can be further determined according to the simulation parameters. In this way, the charging time required for the battery to reach the target state of charge can be more accurately predicted according to the real-time charging current of the battery, achieving the technical effect of accurately predicting the charging time of the power battery in the vehicle development stage.

[0067] In some embodiments, the thermal parameters include battery cell mass, specific heat capacity, thermal conductivity and battery cell surface area; in step 101, simulating the charging process of the battery in the power battery system according to the parameters related to the charging of the power battery system to obtain the corresponding simulation parameters of the battery in the charging process includes:

[0068] Step 1011, determining the temperature rise rate of the battery according to the mass of the battery cell, the specific heat capacity, the thermal conductivity coefficient and the surface area of ​​the battery cell.

[0069] It should be noted that the heat sources of the power battery system during the charging process mainly include: the self-generated heat of the power battery system and the exchange heat output by the power battery thermal management system. The self-generated heat of the power battery system mainly includes ohmic heat and polarization heat. Therefore, when simulating the charging process of the battery in the power battery system, the temperature rise rate of the power battery system during the fast charging process can be fitted by establishing a corresponding thermal model based on the heat generated by the battery cell and the heat exchange of the cold plate.

[0070] In some specific embodiments, the thermal model can be expressed as:

[0071]

[0072] Among them, Q n It represents the thermal conductivity of the battery cell; m represents the mass of the battery cell; and c represents the specific heat capacity.

[0073] Here, the product mc of the battery cell mass m and the specific heat capacity c represents the heat capacity of the battery cell. The heat capacity can be used to describe the heat absorbed or released by the battery cell when the temperature changes. It indicates the change of heat per unit time during the temperature change of the battery cell, that is, the temperature rise rate of the battery.

[0074] Among them, the thermal model includes a heat generation model and a heat conduction model.

[0075] The heat generation model can be expressed as:

[0076]

[0077] Where I represents the charging and discharging current of the power battery; T abs is the adiabatic temperature of the battery cell; U OCV Indicates the electromotive force of the power supply; U t Indicates the dynamic voltage of the battery cell; represents the heat of reaction, I(U ocv -U t ) represents Joule heat.

[0078] It should be noted that Joule heat mainly includes the heat generated by ohmic internal resistance and the heat generated by polarization internal resistance. In practical applications, the heat generated by side reactions can usually be ignored.

[0079] The heat conduction model can be expressed as:

[0080] Q n =hS(T bat -T amp )

[0081] Where h is the thermal conductivity; S is the surface area of ​​the battery cell; T bat Indicates the battery cell temperature; T amp Indicates the ambient temperature.

[0082] It should be noted that the thermal management system of the power battery system includes PTC heating method, heat flow heating method, etc. The heat conduction part in the battery system charging usually includes heat conduction, thermal radiation and convection heat transfer. Here, the heat conduction model uses heat conduction as the main heat exchange method.

[0083] Step 1012: determining the simulation temperature according to the temperature rise rate of the battery and the ambient temperature of the environment where the battery is located.

[0084] It should be noted that the ambient temperature during charging has a significant impact on the charging time of the power battery system. For example, the charging capacity of the power battery system at low temperatures will be reduced compared to that at normal temperature, so the charging time when charging in a low temperature environment is relatively long. Therefore, the embodiment of the present invention takes into account the influence of ambient temperature in the charging time prediction, so as to obtain a more accurate battery charging time prediction result.

[0085] Specifically, according to the formula: T sys =T amp +ΔT*dt, determines the simulated temperature of the battery.

[0086] Among them, T sysIndicates the power battery system temperature; T amp represents the ambient temperature; ΔT represents the rate of temperature rise.

[0087] Here, the temperature rise rate can be calculated according to the formula: Sure.

[0088] Through the above steps, the battery temperature fitting under different charging states (such as thermal management on / off) can be achieved.

[0089] In some embodiments, the electrical parameters include: power supply electromotive force, capacitor polarization, chemical polarization, ohmic internal resistance and charging current of the battery; in step 101, the charging process of the battery in the power battery system is simulated according to the parameters related to the charging of the power battery system, and the simulation parameters corresponding to the battery during the charging process are obtained, including: determining the simulation voltage according to the power supply electromotive force, the capacitor polarization, the chemical polarization, the ohmic internal resistance and the charging current of the battery.

[0090] It should be noted that during the charging process of the power battery, the voltage is affected by ohmic polarization, electrochemical polarization, and concentration polarization, and is offset from the power source electromotive force. Therefore, the above battery system charging model can fit the voltage of the power battery system through a second-order equivalent circuit model. Among them, the main parameters include the ohmic internal resistance of the battery cell, two second-order polarization internal resistances and capacitance.

[0091] Specifically, according to the formula: U t =U OCV -U C -U d -IR ohm , determine the battery voltage (ie, simulation voltage).

[0092] Among them, U t Indicates the dynamic voltage of the battery cell (i.e., simulation voltage); U OCV Indicates the electromotive force of the power supply; U C Indicates capacitor polarization; U d represents chemical polarization; I represents the charge and discharge current of the power battery (i.e. the charging current mentioned above); R ohm Represents the internal resistance in ohms.

[0093] In some embodiments, the electrical parameters include: the charging current of the battery, the rated capacity of the power battery system and the initial state of charge of the battery; in step 101, the charging process of the battery in the power battery system is simulated according to the parameters related to the charging of the power battery system to obtain the simulation parameters corresponding to the battery during the charging process, including: based on the ampere-hour integration method, according to the charging current of the battery, the rated capacity of the power battery system and the initial state of charge of the battery, determining the simulated state of charge.

[0094] It should be noted that, on the one hand, different charging starting SOCs (that is, the SOC of the battery before charging starts, that is, the initial state of charge of the battery) correspond to different starting charging rates, and the starting charging rate has a greater impact on the charging time; on the other hand, since the charging capacity of the power battery will weaken at a high SOC, in order to ensure charging safety, the charging current needs to decrease with the increase of SOC. Therefore, different ending SOC (that is, the target state of charge) settings will have a significant impact on the charging time.

[0095] In some optional examples, during the charging process, the cumulative charging capacity may be calculated by ampere-hour integration, and the simulated state of charge of the power battery may be fitted according to the cumulative charging capacity and the rated capacity of the battery system.

[0096] Specifically, according to the formula: SOC t =SOC0+Idt / C, determine the simulated state of charge of the battery.

[0097] Among them, SOC t It represents the simulated state of charge of the battery (i.e. the current SOC); SOC0 represents the initial state of charge of the battery (i.e. the initial SOC); I represents the charging current; and C represents the rated capacity of the power battery system.

[0098] Here, I / C represents the ratio of the charging current I to the rated capacity C of the battery. I / C can describe the charging rate or charging ratio, and dt represents the time change.

[0099] Optionally, in step 102, determining the real-time charging current of the battery according to the simulation parameter includes at least one of the following:

[0100] (i) querying a first charging matrix according to the simulated temperature and the simulated voltage to determine a real-time charging current of the battery, wherein the first charging matrix represents a mapping relationship between temperature, voltage, and current.

[0101] It should be noted that this method of determining the real-time charging current is more suitable for ternary power batteries.

[0102] (ii) querying a second charging matrix according to the simulated temperature and the simulated state of charge to determine a real-time charging current of the battery, wherein the second charging matrix represents a mapping relationship between temperature, state of charge, and current.

[0103] It should be noted that this method of determining the real-time charging current is more suitable for lithium iron phosphate batteries.

[0104] In this embodiment, the real-time charging current of the battery (which can also be understood as the charging current of the battery at the next moment) can be obtained by querying the corresponding charging matrix according to the actual situation. In this way, the overall charging time required for the battery to be accumulated from the initial SOC to the target SOC can be obtained by integrating the time of the charging process according to the real-time charging current, the target SOC (i.e., the target state of charge), the initial SOC, and the rated capacity of the power battery system. In this way, based on the ampere-hour integration, a rapid estimation of the power battery charging time is achieved.

[0105] It should be noted that, in the above embodiments, Figure 2 As shown, the battery in the target charging model can be charged and simulated based on the empirical data of the same thermal management system and the same system cells as the power battery system, and then the temperature rise and SOC (or voltage) can be fitted. According to the fitting results (i.e., simulation parameters, such as simulated temperature T, simulated state of charge, and simulated voltage), the charging matrix can be queried to obtain the real-time current. According to the real-time charging current and the rated capacity of the power battery system, the charging time in different SOC ranges can be finally obtained, thereby realizing a rapid evaluation of the charging time of the power battery system.

[0106] In the embodiment of the present invention, the charging process of the battery in the power battery system is simulated according to the parameters related to the charging of the power battery system, and the corresponding simulation parameters of the battery in the charging process can be obtained, and the real-time charging current of the battery can be further determined according to the simulation parameters. In this way, the charging time required for the battery to reach the target state of charge can be more accurately predicted according to the real-time charging current of the battery, achieving the technical effect of accurately predicting the charging time of the power battery in the vehicle development stage.

[0107] like Figure 3 As shown, an embodiment of the present invention further provides a battery charging time prediction device, comprising:

[0108] A first processing module 31 is used to simulate the charging process of the battery in the power battery system according to the parameters related to the charging of the power battery system, and obtain the simulation parameters corresponding to the battery in the charging process;

[0109] A second processing module 32, used to determine the real-time charging current of the battery according to the simulation parameters;

[0110] The first prediction module 33 is used to predict the charging time required for the battery to reach a target state of charge according to the real-time charging current.

[0111] In this embodiment, the charging process of the battery in the power battery system is simulated according to the parameters related to the charging of the power battery system, and the corresponding simulation parameters of the battery in the charging process can be obtained, and the real-time charging current of the battery can be further determined according to the simulation parameters. In this way, the charging time required for the battery to reach the target state of charge can be more accurately predicted according to the real-time charging current of the battery, achieving the technical effect of accurately predicting the charging time of the power battery in the vehicle development stage.

[0112] Optionally, the parameters related to charging of the power battery system include: at least one thermal parameter related to temperature change of the power battery system during charging simulation, and at least one electrical parameter related to voltage of a battery cell in the power battery system;

[0113] The simulation parameters include at least two of a simulation temperature, a simulation voltage, and a simulation state of charge.

[0114] Optionally, the thermal parameters include battery cell mass, specific heat capacity, thermal conductivity and battery cell surface area;

[0115] The first processing module 31 includes:

[0116] A first processing unit, configured to determine a temperature rise rate of the battery according to the mass of the battery cell, the specific heat capacity, the thermal conductivity coefficient and the surface area of ​​the battery cell;

[0117] The second processing unit is used to determine the simulation temperature according to the temperature rise rate of the battery and the ambient temperature of the environment where the battery is located.

[0118] Optionally, the electrical parameters include: power supply electromotive force, capacitor polarization, chemical polarization, ohmic internal resistance and charging current of the battery;

[0119] The first processing module 31 includes:

[0120] The third processing unit is used to determine the simulation voltage according to the power supply electromotive force, the capacitor polarization, the chemical polarization, the ohmic internal resistance and the charging current of the battery.

[0121] Optionally, the electrical parameters include: the charging current of the battery, the rated capacity of the power battery system and the initial state of charge of the battery;

[0122] The first processing module 31 includes:

[0123] The fourth processing unit is used to determine the simulated state of charge based on the ampere-hour integration method according to the charging current of the battery, the rated capacity of the power battery system and the initial state of charge of the battery.

[0124] Optionally, the second processing module 32 includes:

[0125] a fifth processing unit, configured to query a first charging matrix to determine a real-time charging current of the battery according to the simulated temperature and the simulated voltage, wherein the first charging matrix represents a mapping relationship between temperature, voltage, and current;

[0126] The sixth processing unit is used to query a second charging matrix according to the simulated temperature and the simulated state of charge to determine the real-time charging current of the battery, wherein the second charging matrix represents a mapping relationship between temperature, state of charge and current.

[0127] It should be noted here that the above-mentioned battery charging time prediction device provided by the embodiment of the present invention can implement all the method steps implemented by the above-mentioned battery charging time prediction method embodiment, and can achieve the same technical effect. The parts and beneficial effects of this embodiment that are the same as those of the method embodiment will not be described in detail here.

[0128] An embodiment of the present application also provides a prediction device, including a memory, a processor, and a computer program stored in the memory and executable on the processor; when the processor executes the computer program, the battery charging time prediction method as described above is implemented.

[0129] The present application also provides a computer program product, including computer instructions, which, when executed by a processor, implement the above Figure 1 The various processes of the method embodiment shown can achieve the same technical effect, and will not be described again here to avoid repetition.

[0130] Those skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware, or may be accomplished by instructing related hardware through a computer program, wherein the computer program includes instructions for executing part or all of the steps of the above method; and the computer program may be stored in a readable storage medium, and the storage medium may be any form of storage medium.

[0131] A computer-readable storage medium according to an embodiment of the present invention stores a program or instruction thereon, and when the program or instruction is executed by a processor, the steps in the battery charging time prediction method described above are implemented, and the same technical effect can be achieved. To avoid repetition, it is not repeated here. The computer-readable storage medium is, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0132] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary personnel in this technical field, several improvements and modifications can be made without departing from the principles described in the present invention. These improvements and modifications are also within the scope of protection of the present invention.

Claims

1. A battery charging time prediction method, characterized in that: include: According to the parameters related to the charging of the power battery system, a charging process of the battery in the power battery system is simulated to obtain the simulation parameters corresponding to the battery in the charging process; Determining a real-time charging current of the battery according to the simulation parameters; The charging time required for the battery to reach a target state of charge is predicted based on the real-time charging current.

2. The method according to claim 1, characterized in that The parameters related to the charging of the power battery system include: at least one thermal parameter related to the temperature change of the power battery system during the charging simulation process, and at least one electrical parameter related to the voltage of the battery cell in the power battery system; The simulation parameters include at least two of a simulation temperature, a simulation voltage, and a simulation state of charge.

3. The method according to claim 2, characterized in that The thermal parameters include battery cell mass, specific heat capacity, thermal conductivity and battery cell surface area; The simulating the charging process of the battery in the power battery system according to the parameters related to the charging of the power battery system to obtain the simulation parameters corresponding to the battery in the charging process includes: Determining the temperature rise rate of the battery according to the mass of the battery cell, the specific heat capacity, the thermal conductivity and the surface area of ​​the battery cell; The simulation temperature is determined according to the temperature rise rate of the battery and the ambient temperature of the environment where the battery is located.

4. The method according to claim 2, characterized in that: The electrical parameters include: power supply electromotive force, capacitor polarization, chemical polarization, ohmic internal resistance and charging current of the battery; The simulating the charging process of the battery in the power battery system according to the parameters related to the charging of the power battery system to obtain the simulation parameters corresponding to the battery in the charging process includes: The simulation voltage is determined according to the power supply electromotive force, the capacitor polarization, the chemical polarization, the ohmic internal resistance and the charging current of the battery.

5. The method according to claim 2, characterized in that: The electrical parameters include: the charging current of the battery, the rated capacity of the power battery system and the initial state of charge of the battery; The simulating the charging process of the battery in the power battery system according to the parameters related to the charging of the power battery system to obtain the simulation parameters corresponding to the battery in the charging process includes: The simulated state of charge is determined based on an ampere-hour integration method according to the charging current of the battery, the rated capacity of the power battery system and the initial state of charge of the battery.

6. The method according to claim 2, characterized in that Determining the real-time charging current of the battery according to the simulation parameter includes at least one of the following: According to the simulated temperature and the simulated voltage, query a first charging matrix to determine a real-time charging current of the battery, wherein the first charging matrix represents a mapping relationship between temperature, voltage, and current; According to the simulated temperature and the simulated state of charge, a second charging matrix is ​​queried to determine the real-time charging current of the battery, wherein the second charging matrix represents a mapping relationship between temperature, state of charge and current.

7. A battery charging time prediction device, characterized in that: include: A first processing module, configured to simulate a charging process of a battery in the power battery system according to parameters related to charging of the power battery system, and obtain simulation parameters corresponding to the battery in the charging process; A second processing module, used for determining a real-time charging current of the battery according to the simulation parameters; The first prediction module is used to predict the charging time required for the battery to reach a target state of charge according to the real-time charging current.

8. A prediction device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor; characterized in that: When the processor executes the computer program, the battery charging time prediction method according to any one of claims 1 to 6 is implemented.

9. A computer program product, characterized in that The method comprises computer instructions, which, when executed by a processor, implement the steps of the battery charging time prediction method according to any one of claims 1 to 6.

10. A readable storage medium having a program or instruction stored thereon, characterized in that: When the program or instruction is executed by a processor, the steps in the battery charging time prediction method according to any one of claims 1 to 6 are implemented.

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