Battery charging remaining time calculation method, device and storage medium

Abstract

The application discloses a battery charging remaining time calculation method, device and storage medium. The battery charging remaining time calculation method comprises the following steps: obtaining state information of a battery, wherein the state information is one or both of a battery voltage and a battery capacity; during the battery charging process, if the initial state information of the battery does not satisfy a preset condition, the remaining charging time of the battery is calculated based on a capacity mode; when the state information of the battery satisfies the preset condition, the remaining charging time is calculated based on a first voltage correction point mode until the charging is completed; or during the battery charging process, if the initial state information of the battery satisfies the preset condition, the remaining charging time is calculated based on a second voltage correction point mode until the charging is completed. The technical scheme provided by the application can solve the technical problem of low calculation accuracy caused by not considering voltage correction points when calculating the remaining time of the battery in the prior art.

Description

Technical Field

[0001] This invention relates to the field of battery technology, and in particular to a method, apparatus and storage medium for calculating the remaining charging time of a battery. Background Technology

[0002] When an electric vehicle is charging, it is necessary to calculate the remaining charging time and display the time information to the owner on the vehicle's instrument panel. The conventional calculation method is to calculate the remaining charging time using the battery's rated capacity, current remaining capacity, and real-time charging current.

[0003] Existing technologies offer various methods for calculating remaining charging time. One approach is to adjust the remaining charging time based on previous charging data. Another method involves establishing a charging time calculation model to obtain a remaining charging time that is closer to the actual time. Yet another method is to determine the relationship between charging data and the remaining charging time based on the charging data itself.

[0004] When charging a battery, due to its characteristics, the battery capacity increases rapidly with increasing voltage at the end of the charging process, requiring a voltage correction point to adjust the capacity. Current technology does not consider this voltage correction point when calculating remaining battery time, resulting in low estimation accuracy. Summary of the Invention

[0005] This invention provides a method, apparatus, and storage medium for calculating the remaining charging time of a battery, aiming to effectively solve the technical problem of low calculation accuracy caused by the failure to consider voltage correction points when calculating the remaining battery time in the prior art.

[0006] According to one aspect of the present invention, the present invention provides a method for calculating the remaining charging time of a battery, the method comprising:

[0007] Obtain battery status information, wherein the status information is one or both of battery voltage and battery charge;

[0008] During battery charging, if the initial state information of the battery does not meet the preset conditions, the remaining charging time is calculated based on the capacity mode. When the battery state information meets the preset conditions, the remaining charging time is calculated based on the first voltage correction point mode, until charging is completed; or...

[0009] During battery charging, if the initial state information of the battery meets the preset conditions, the remaining charging time is calculated based on the second voltage correction point mode until charging is completed.

[0010] Further, determining whether the status information meets preset conditions includes:

[0011] If the battery voltage is less than a preset correction point voltage, then the state information is determined not to meet the preset condition, wherein the correction point voltage is used to correct the battery charge; or,

[0012] If the battery voltage is greater than or equal to the correction point voltage, then the current battery level and the correction point level corresponding to the correction point voltage are obtained, and the difference between the battery level and the correction point level is calculated. If the difference is less than a preset power threshold, then it is determined that the state information does not meet the preset condition.

[0013] If the battery voltage is greater than or equal to the correction point voltage, and the power difference is greater than or equal to the power threshold, then the status information is determined to meet the preset condition.

[0014] Furthermore, the method includes:

[0015] Obtain the current charging data of the battery;

[0016] The current charging data is input into the neuron model to calculate the real-time value of the remaining charging time.

[0017] Obtain the continuous charging time for charging the battery;

[0018] The remaining charging time is updated based on the real-time value of the remaining charging time and the continuous charging time.

[0019] Furthermore, the calculation of the remaining charging time of the battery based on the capacity mode includes:

[0020] Obtain the first current charging data of the battery, wherein the first current charging data includes battery capacity, battery temperature, ambient temperature, and number of discharge cycles;

[0021] The first current charging data at the start of charging is input into the neuron model to calculate the initial value of the first remaining charging time.

[0022] Whenever the change in battery capacity reaches a preset threshold, the following operation is executed cyclically:

[0023] The first current charging data during the charging process is input into the neuron model to calculate the real-time value of the first remaining charging time.

[0024] Obtain the continuous charging time for charging the battery;

[0025] Calculate the difference between the initial value of the first remaining charging time and the continuous charging time to obtain the remaining charging time;

[0026] The remaining charging time is updated based on the current remaining charging time, the real-time value of the first remaining charging time, and the continuous charging time.

[0027] Wherein, when the battery voltage is less than a preset correction point voltage, the change threshold is a first threshold; when the battery voltage is greater than or equal to the correction point voltage, the change threshold is a second threshold; wherein, the first threshold is greater than the second threshold.

[0028] Further, calculating the remaining charging time based on the first voltage correction point mode includes:

[0029] Acquire the second current charging data of the battery, wherein the second current charging data includes the current maximum voltage of the cell, battery temperature, ambient temperature, and number of discharge cycles;

[0030] The second current charging data is input into the neuron model to calculate the real-time value of the second remaining charging time.

[0031] Obtain the continuous charging time for charging the battery;

[0032] The remaining charging time is updated based on the second real-time value of the remaining charging time and the continuous charging time.

[0033] Furthermore, the calculation of the remaining charging time based on the second voltage correction point mode includes:

[0034] Obtain the second current charging data of the battery, wherein the second current charging data includes the current maximum voltage of the cell, battery temperature, ambient temperature, and number of discharge cycles;

[0035] The second current charging data at the start of charging is input into the neuron model to calculate the initial value of the second remaining charging time;

[0036] Obtain the continuous charging time for charging the battery;

[0037] The remaining charging time is calculated based on the initial value of the second remaining charging time and the continuous charging time.

[0038] Furthermore, the method for calculating the remaining battery charging time also includes:

[0039] If the remaining charging time is calculated using the capacity mode when charging ends, then capacity charging data is obtained, wherein the capacity charging data includes the battery rated capacity, the battery capacity at the initial charging time, the accuracy of the remaining charging time, the actual charging time, and the requested charging current and the actual charging current during the charging process.

[0040] The difference between the requested charging current and the actual charging current is integrated over time to obtain the first charging capacity difference;

[0041] Calculate the difference between the rated capacity of the battery and the capacity at the initial charging moment of the battery to obtain the first initial capacity difference;

[0042] The accuracy of the first charging data is calculated based on the first charging power difference, the first initial power difference, and the actual charging time, using the following formula:

[0043] P1 = (ΔIt1 / ΔAH1) * Tact

[0044] Wherein, P1 represents the first charging data accuracy, ΔIt1 represents the first charging power difference, ΔAH1 represents the first initial power difference, and Tact represents the actual charging time;

[0045] If the accuracy of the first charging data is less than the accuracy of the remaining charging time, then the capacity charging data and the current charging data are entered into the capacity-based data pool to optimize the neuron model.

[0046] Furthermore, the method for calculating the remaining battery charging time also includes:

[0047] If the remaining charging time is calculated using either the first voltage correction point mode or the second voltage correction point mode when charging ends, then voltage correction point charging data is obtained. The voltage correction point charging data includes the battery rated capacity, the battery capacity corresponding to the voltage correction point, the accuracy of the remaining charging time, the actual charging time, and the requested charging current and the actual charging current during the charging process after the voltage correction point.

[0048] The difference between the requested charging current and the actual charging current is integrated over time to obtain the second charging capacity difference;

[0049] Calculate the difference between the battery's rated capacity and the battery capacity corresponding to the voltage correction point to obtain the second initial capacity difference;

[0050] The accuracy of the second charging data is calculated based on the second charging power difference, the second initial power difference, and the actual charging time, using the following formula:

[0051] P2 = (ΔIt2 / ΔAH2) * Tact

[0052] Wherein, P2 represents the second charging data accuracy, ΔIt2 represents the second charging power difference, ΔAH2 represents the second initial power difference, and Tact represents the actual charging time;

[0053] If the accuracy of the second charging data is less than the accuracy of the remaining charging time, then the voltage correction point charging data and the current charging data are entered into the voltage correction point data pool to optimize the neuron model.

[0054] According to another aspect of the present invention, the present invention also provides a battery charging remaining time calculation device, the device comprising:

[0055] An information acquisition module is used to acquire battery status information, wherein the status information is one or both of battery voltage and battery charge.

[0056] The first calculation module is used to calculate the remaining charging time of the battery based on the capacity mode if the initial state information of the battery does not meet the preset conditions during the battery charging process, and to calculate the remaining charging time based on the first voltage correction point mode when the state information of the battery meets the preset conditions, until the charging is completed.

[0057] The second calculation module is used to calculate the remaining charging time based on the second voltage correction point mode if the initial state information of the battery meets the preset conditions during the battery charging process, until the charging is completed.

[0058] According to another aspect of the invention, the invention also provides a storage medium storing a plurality of instructions adapted to be loaded by a processor to execute any of the battery charge remaining time calculation methods described above.

[0059] Through one or more embodiments of the above embodiments of the present invention, at least the following technical effects can be achieved:

[0060] In the technical solution disclosed in this invention, at the start of charging, it is determined whether the battery has reached the voltage correction point and whether the battery status information meets preset conditions. Based on the battery status, a time calculation mode is determined. The battery can calculate the remaining charging time entirely based on capacity mode, or first based on capacity mode and then switch to the first voltage correction point mode, or it can calculate the remaining charging time entirely based on the second voltage correction point mode. By determining the calculation mode based on battery voltage and battery capacity, the accuracy of the DC charging remaining time can be guaranteed even when the remaining battery capacity is inaccurate. This solves the problems of inaccurate DC charging remaining time and frequent jumps, ensuring the accuracy of the charging remaining time calculation throughout the entire lifespan under various operating conditions.

[0061] Furthermore, under various calculation modes, this solution can acquire charging data in real time and input it into the neural network model to obtain an accurate initial value of the remaining DC charging time. During the charging process, the frequency of updating the remaining time is determined according to the increase in power, and the updated value is generated by the previous frame of data and the current data. Even if the current fluctuates dynamically, the stability and accuracy of the remaining DC charging time can be guaranteed. The neural network model is used when calculating the time, and the data is filtered to optimize the model. It has self-learning capabilities and can continuously optimize the accuracy of the remaining charging time based on real vehicle DC charging data, which can avoid the problem of inaccurate remaining charging time after battery aging. Attached Figure Description

[0062] The technical solution and other beneficial effects of the present invention will become apparent from the following detailed description of specific embodiments of the invention, in conjunction with the accompanying drawings.

[0063] Figure 1 A flowchart illustrating the steps of a method for calculating the remaining charging time of a battery, as provided in an embodiment of the present invention;

[0064] Figure 2 A capacity-patterned neuron model is provided in this embodiment of the invention;

[0065] Figure 3 A neuron model for voltage correction point mode provided in an embodiment of the present invention;

[0066] Figure 4 This is a flowchart of the training process for a neuron model.

[0067] Figure 5 This is a schematic diagram of a battery charging remaining time calculation device provided in an embodiment of the present invention. Detailed Implementation

[0068] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0069] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the term "and / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Furthermore, the character " / " in this document, unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship.

[0070] Figure 1 The diagram shows a flowchart of the battery charging remaining time calculation method provided in an embodiment of the present invention. According to one aspect of the present invention, a battery charging remaining time calculation method is provided, the method comprising:

[0071] Step 101: Obtain the battery status information, wherein the status information is one or both of battery voltage and battery charge;

[0072] Step 102: During battery charging, if the initial state information of the battery does not meet the preset conditions, the remaining charging time of the battery is calculated based on the capacity mode. When the state information of the battery meets the preset conditions, the remaining charging time is calculated based on the first voltage correction point mode until charging is completed.

[0073] Step 103: During battery charging, if the initial state information of the battery meets the preset conditions, the remaining charging time is calculated based on the second voltage correction point mode until charging is completed.

[0074] The following is a detailed description of steps 101 to 103 above.

[0075] In step 101, the battery status information is obtained, wherein the status information is one or both of battery voltage and battery charge.

[0076] For example, during battery charging, due to battery characteristics, the battery capacity increases rapidly with increasing voltage at the end of the charging process, requiring correction at a voltage correction point. This solution determines the remaining charging time calculation mode based on battery data at the voltage correction point during battery charging. Specifically, battery status information is used to determine whether the battery has reached the voltage correction point and whether the calculated capacity value at the voltage correction point matches the actual value; this is generally determined based on real-time acquired battery voltage and capacity.

[0077] At the beginning of charging, the battery may be in any state, such as being completely depleted, having any charge level, or having a significant amount of charge remaining, or being close to being fully charged, for example, having a battery voltage greater than the voltage correction point.

[0078] This solution provides three time calculation modes based on battery characteristics: capacity mode, first voltage correction point mode, and second voltage correction point mode. Specifically, one or both of the battery voltage and battery capacity need to be obtained to determine the battery's state, and then the most suitable time calculation mode can be determined.

[0079] Specifically, when the vehicle is first connected to the power supply and the power source begins to provide current to the vehicle for charging, it is determined whether the battery status information meets preset conditions. If the battery status information does not meet the preset conditions, step 102 is executed; otherwise, step 103 is executed.

[0080] In step 102, during battery charging, if the initial state information of the battery does not meet the preset conditions, the remaining charging time of the battery is calculated based on the capacity mode. When the state information of the battery meets the preset conditions, the remaining charging time is calculated based on the first voltage correction point mode until charging is completed.

[0081] For example, the battery status information includes battery voltage and battery charge, with preset conditions being voltage-related thresholds and charge-related thresholds. If the battery status information immediately after power is connected does not meet the preset conditions, it indicates that the battery charge is low and has not reached the voltage correction point; in this case, the remaining charging time is calculated directly using capacity mode. Capacity mode calculates the remaining charging time based on the real-time changes in battery capacity (charge).

[0082] During the charging process, the battery capacity gradually increases, and the battery cell voltage gradually rises. When the battery voltage is greater than the correction point voltage, the battery status information is checked again to see if it meets the preset conditions. If it does not meet the conditions, it means that the current capacity mode can still accurately calculate the remaining charging time, and the capacity mode is used to continue charging until the charging is completed.

[0083] If the battery status information meets the preset conditions, it means that the current capacity mode has a large error in calculating the remaining charging time. Switch to the first voltage correction point mode to calculate the remaining charging time until charging is completed.

[0084] In step 103, during battery charging, if the initial state information of the battery meets the preset conditions, the remaining charging time is calculated based on the second voltage correction point mode until charging is completed.

[0085] For example, in this calculation method, when the power is turned on, it is determined that the battery voltage is greater than the correction point voltage, and using the capacity mode will produce a large calculation error. Therefore, the second voltage correction point mode is directly used to calculate the remaining charging time until charging is completed. In the voltage correction point mode, the update frequency of the remaining charging time is not controlled according to the real-time changes in the power level, and the specific calculation method is different from that of the capacity mode.

[0086] Further, determining whether the status information meets preset conditions includes:

[0087] If the battery voltage is less than a preset correction point voltage, then the state information is determined not to meet the preset condition, wherein the correction point voltage is used to correct the battery charge; or,

[0088] If the battery voltage is greater than or equal to the correction point voltage, then the current battery level and the correction point level corresponding to the correction point voltage are obtained, and the difference between the battery level and the correction point level is calculated. If the difference is less than a preset power threshold, then it is determined that the state information does not meet the preset condition.

[0089] If the battery voltage is greater than or equal to the correction point voltage, and the power difference is greater than or equal to the power threshold, then the status information is determined to meet the preset condition.

[0090] For example, the battery status information includes one or both of battery voltage and battery capacity. When the fast charging gun is plugged in to start charging, the current maximum battery voltage is determined, and the current battery capacity within the cell is obtained. Then, the battery status is judged, and whether the battery status information meets the preset conditions is specifically divided into two groups of cases.

[0091] The first method is to determine whether the battery voltage is greater than the correction point voltage. If the maximum voltage of the cell is not greater than the correction point voltage, then the battery status information does not meet the preset conditions.

[0092] The second approach involves determining the battery voltage is greater than the correction point voltage. Then, the battery level needs to be assessed. The current State of Charge (SOC) value is subtracted from the SOC value corresponding to the voltage correction point to obtain the battery level difference. If this difference is less than a preset battery level threshold, the battery status information is determined to not meet the preset condition. For example, if |current SOC value - SOC value corresponding to the voltage correction point| ≤ 5%, the battery status information is determined to not meet the preset condition, and a capacity-based remaining charging time calculation method is executed.

[0093] In this scheme, the remaining charging time needs to be calculated based on neurons. The neuron model in this scheme is introduced below.

[0094] The factors affecting the remaining DC charging time are as follows: battery rated capacity, battery pack remaining capacity (capacity at the initial charging moment), battery temperature, external ambient temperature, cumulative equivalent discharge cycles, the difference between the requested current and the actual charging current, and the maximum cell voltage.

[0095] When a vehicle is fast-charging, all the above-mentioned influencing factors are used as input parameters, and the actual time used when fully charged is used as the output variable. Neuron mathematical models based on the remaining time of DC charging based on capacity and the remaining time of DC charging based on voltage correction point are established respectively.

[0096] Figure 2 A capacity-patterned neuron model is provided in this embodiment of the invention, which has the following relationship:

[0097] T s=w1x1+w2x2+w3x3+w4x4+w5x5+w6x6+a;

[0098] Figure 3 A neuron model for voltage correction point mode provided in this embodiment of the invention has the following relationship:

[0099] T v =z1v1+z2v2+z3v3+z4v4+z5v5+b;

[0100] Among them, T s Represents the remaining DC charging time based on capacity; T v denoted by , represents the remaining DC charging time based on the voltage correction point; x and z represent the inputs of the neurons, i.e., the aforementioned influencing factors; w and v represent the weights; a and b represent the thresholds of the neurons, i.e., the compensation coefficients.

[0101] Figure 4 This is a flowchart illustrating the training process of a neuron model. The process involves training the neuron model using sample data from a data pool to obtain weights and thresholds. Figure 4 As shown, once the model training is complete, inputting a set of input data will yield the predicted value of the remaining charging time.

[0102] Furthermore, the method includes:

[0103] Obtain the current charging data of the battery;

[0104] The current charging data is input into the neuron model to calculate the real-time value of the remaining charging time.

[0105] Obtain the continuous charging time for charging the battery;

[0106] The remaining charging time is updated based on the real-time value of the remaining charging time and the continuous charging time.

[0107] For example, the current charging data is data acquired in real time during the charging process based on the sampling time, or characteristic parameters of the battery, such as one or more of the following: rated capacity of the battery pack, remaining capacity of the battery pack, battery temperature, external ambient temperature, cumulative equivalent discharge cycle count, the difference between the requested current and the actual charging current, and the maximum cell voltage value, etc. The neuron model is a neural network model used to train data and continuously optimize the model to obtain the best calculation results. The real-time remaining charging time value is the remaining time calculated by the neuron model based on the current charging data at the current moment. However, this remaining time is not directly used as the final result displayed to the customer. Instead, the remaining time calculated at the previous moment and this remaining time are used to calculate a more accurate remaining charging time value using a formula.

[0108] The first voltage correction point mode calculates the remaining charging time based on the capacity mode. Therefore, the capacity mode and the first voltage correction point mode have a similar calculation process, but the current charging data differs between the two modes. Both the capacity mode and the first voltage correction point mode require obtaining the real-time value of the remaining charging time and the continuous charging time during the calculation process, and the specific calculation processes are as follows.

[0109] Example 1

[0110] Furthermore, the calculation of the remaining charging time of the battery based on the capacity mode includes:

[0111] Obtain the first current charging data of the battery, wherein the first current charging data includes battery capacity, battery temperature, ambient temperature, and number of discharge cycles;

[0112] The first current charging data at the start of charging is input into the neuron model to calculate the initial value of the first remaining charging time Ts.

[0113] Whenever the change in battery capacity reaches a preset threshold, the following operation is executed cyclically:

[0114] The first current charging data during the charging process is input into the neuron model to calculate the real-time value of the first remaining charging time Tp.

[0115] Obtain the continuous charging time Tpass for charging the battery;

[0116] Calculate the difference between the initial value of the first remaining charging time Ts and the continuous charging time Tpass to obtain the remaining charging time T;

[0117] The remaining charging time T is updated based on the current remaining charging time T, the first real-time value of the remaining charging time Tp, and the continuous charging time Tpass.

[0118] Wherein, when the battery voltage is less than a preset correction point voltage, the change threshold is a first threshold; when the battery voltage is greater than or equal to the correction point voltage, the change threshold is a second threshold; wherein, the first threshold is greater than the second threshold.

[0119] For example, in Embodiment 1, the remaining charging time is calculated based on capacity during the entire charging process. The remaining charging time is calibrated once every time the State of Charge (SOC) changes by a preset value during charging. Specifically, the update frequency is slightly lower when the battery voltage is lower than a preset correction point voltage; for example, the remaining charging time is updated every 5% change in SOC during charging. When the battery voltage is greater than or equal to the correction point voltage, the calibration frequency becomes higher; for example, the remaining charging time is calibrated every 1% change in SOC during charging. This solution updates the remaining charging time in real time, and every 5% change in SOC, the latest collected charging data is input into the neural network model, and the remaining charging time is calibrated based on the output result to improve the accuracy of time assessment.

[0120] When fast charging begins, it checks if the battery voltage (maximum cell voltage) is greater than the correction point voltage. If the maximum cell voltage is not greater than the correction point voltage, or if the maximum cell voltage is greater than the correction point voltage but the battery capacity does not meet the preset conditions (e.g., |current SOC value - SOC value corresponding to the voltage correction point| ≤ 5%), then the remaining charging time calculation method based on capacity mode is executed, with the following steps:

[0121] The first current charging data of the battery is obtained. At the initial moment of charging, the first current charging data includes the remaining capacity of the battery pack, the battery temperature, the external ambient temperature, and the cumulative equivalent discharge cycle count.

[0122] Calculate the initial value of the remaining charging time Ts based on this data and the trained neuron model;

[0123] After the charging current is applied, obtain the continuous charging time Tpass for charging the battery, which represents the actual time elapsed from the current moment.

[0124] Then calculate the countdown of the remaining charging time. The remaining charging time T is obtained from the difference between the initial value of the first remaining charging time Ts and the continuous charging time Tpass. T = Ts - Tpass.

[0125] During the charging process, whenever the SOC changes by a preset value (e.g., 5%), the remaining charging time is calculated based on the first current charging data corresponding to the time after the change. For example, the remaining charging time Tp during the process is obtained based on the battery capacity, battery temperature, external ambient temperature, cumulative equivalent discharge cycle count, and a trained neuron model.

[0126] Finally, the remaining charging time T is updated based on the current remaining charging time T, the first real-time value of the remaining charging time Tp, and the continuous charging time Tpass, i.e., T = T - (T / Tp) * Tpass;

[0127] At the end of charging, determine whether the maximum voltage of the battery cell is greater than the voltage correction point. If the maximum voltage of the battery cell is not greater than the correction point voltage, continue to repeat the previous steps to update the remaining charging time.

[0128] If the maximum cell voltage is greater than the correction point voltage, and the battery capacity does not meet the preset conditions (e.g., |current SOC value - SOC value corresponding to the voltage correction point| ≤ 5%), then the capacity-based remaining charging time calculation method continues to be executed. However, the frequency of obtaining the remaining charging time based on the neural network model increases, and the SOC change threshold changes from the first threshold to the second threshold. For example, instead of the original 5% change in SOC, it changes to 1% change in SOC, meaning that the data is calibrated once for every 1% change in SOC during charging.

[0129] Following the same logic as the steps above, the specific calculation steps for this capacity model are as follows:

[0130] Based on the changed battery capacity, battery temperature, external ambient temperature, and cumulative equivalent discharge cycle count, the remaining charging time Tp during the process is obtained using a neuron model.

[0131] After obtaining the Tp value, the remaining charging time is still calculated using T = T - (T / Tp) * Tpass until charging is complete.

[0132] Charging is complete when the user unplugs the power or the battery is fully charged. After charging is complete, the system checks the integral of the difference between the requested current and the actual charging current throughout the entire charging process. If the data error is large, no data is recorded. If the error is small, the data set and the actual charging time are recorded in the capacity-based data pool.

[0133] When new data is entered into the data pool, the neuron model needs to be retrained to update the weights and thresholds of the neuron model, thereby enabling self-learning of the remaining charging time.

[0134] Example 2

[0135] Further, calculating the remaining charging time based on the first voltage correction point mode includes:

[0136] Acquire the second current charging data of the battery, wherein the second current charging data includes the current maximum voltage of the cell, battery temperature, ambient temperature, and number of discharge cycles;

[0137] The second current charging data is input into the neuron model to calculate the real-time value of the second remaining charging time, Tv.

[0138] Obtain the continuous charging time Tpass for charging the battery;

[0139] The remaining charging time T is updated based on the second real-time value of the remaining charging time Tv and the continuous charging time Tpass;

[0140] For example, in Embodiment 2, two modes were used to calculate the remaining charging time during the entire charging process: first, the capacity mode was used, and then the voltage correction point mode was used to calculate the remaining charging time.

[0141] First, the remaining charging time is calculated based on capacity. At the end of charging, it is determined whether the battery voltage (maximum cell voltage) is greater than the correction point voltage. If the maximum cell voltage is greater than the correction point voltage, and the battery capacity meets preset conditions (e.g., |current SOC value - SOC value corresponding to the voltage correction point| > 5%), it indicates that the current SOC assessment has a large error. The capacity mode calculation method will result in low accuracy of the remaining charging time. Therefore, it is necessary to switch to the first voltage correction point mode calculation method. The steps are as follows:

[0142] The second current charging data of the battery is obtained. At the initial moment of charging, the second current charging data includes the current maximum voltage of the cell, the battery temperature, the ambient temperature, and the number of discharge cycles.

[0143] The second current charging data at the mode switching moment is input into the neuron model to calculate the real-time value of the second remaining charging time Tv.

[0144] Get the continuous charging time Tpass of the battery, which represents the actual time elapsed since the current moment;

[0145] Then, the remaining charging time T is updated according to the second real-time value of the remaining charging time Tv and the continuous charging time Tpass. The remaining charging time is continuously updated according to T = T - (T / Tv) * Tpass until charging is completed.

[0146] Charging is complete when the user unplugs the power or the battery is fully charged. When charging is complete, the difference between the requested current and the actual charging current from the time the voltage correction point mode was switched to is integrated. If the data error is large, no data is recorded. If the error is small, the data after switching to the voltage correction point calculation mode and the actual charging time are recorded in the data pool based on the voltage correction point mode.

[0147] When new data is entered into the data pool, the neuron model needs to be retrained to update the weights and thresholds of the neuron model, thereby enabling self-learning of the remaining charging time.

[0148] Example 3

[0149] Furthermore, the calculation of the remaining charging time based on the second voltage correction point mode includes:

[0150] Obtain the second current charging data of the battery, wherein the second current charging data includes the current maximum voltage of the cell, the battery temperature, the ambient temperature, and the number of discharge cycles;

[0151] The second current charging data at the start of charging is input into the neuron model to calculate the initial value of the second remaining charging time Tt.

[0152] Obtain the continuous charging time Tpass for charging the battery;

[0153] The remaining charging time T is calculated based on the second initial value of the remaining charging time Tt and the continuous charging time Tpass;

[0154] For example, in Embodiment 3, the remaining charging time is calculated based on the second voltage correction point mode during the entire charging process.

[0155] When fast charging begins, it checks if the battery voltage (maximum cell voltage) is greater than the correction point voltage. If the maximum cell voltage is greater than the correction point voltage, and the battery capacity meets preset conditions, such as |current SOC value - SOC value corresponding to the voltage correction point| > 5%, then the remaining charging time calculation method based on the voltage correction point mode is executed, with the following steps:

[0156] The second current charging data of the battery is obtained. At the initial moment of charging, the second current charging data includes the current maximum voltage of the cell, the battery temperature, the ambient temperature, and the number of discharge cycles.

[0157] The second current charging data at the initial charging moment is input into the neuron model to calculate the initial value of the second remaining charging time Tt.

[0158] After the charging current is applied, obtain the continuous charging time Tpass for charging the battery, which represents the actual time elapsed from the current moment.

[0159] Then, the countdown timer for the remaining charging time is calculated. The remaining charging time T is obtained from the difference between the initial value of the first remaining charging time Ts and the continuous charging time Tpass, where T = Tt - Tpass.

[0160] Charging is complete when the user unplugs the power or the battery is fully charged. When charging is complete, the difference between the requested current from the trigger voltage correction point to the charging completion point and the actual charging current is integrated. If the data error is large, no data is recorded. If the error is small, the data set and the actual charging time are recorded in the data pool based on the voltage correction point mode.

[0161] When new data is entered into the data pool, the neuron model needs to be retrained to update the weights and thresholds of the neuron model, thereby enabling self-learning of the remaining charging time.

[0162] When the vehicle is DC charged, not every charging data can be entered into the data pool. The data needs to be screened for reasonableness, and only reasonable data will be entered into the data pool. For example, if the remaining battery pack capacity is not accurately estimated or the integral of the difference between the requested current and the actual charging current is too large, it will affect the actual charging time. These scenarios are abnormal and data under these scenarios need to be removed to ensure the accuracy of the data in the data pool.

[0163] The following sections introduce the format rules for the DC charging remaining time data pool based on the capacity mode and the format rules for the DC charging remaining time data pool based on the end voltage correction point mode.

[0164] Furthermore, the method for calculating the remaining battery charging time also includes:

[0165] If the remaining charging time is calculated using the capacity mode when charging ends, then capacity charging data is obtained, wherein the capacity charging data includes the battery rated capacity, the battery capacity at the initial charging time, the accuracy of the remaining charging time, the actual charging time, and the requested charging current and the actual charging current during the charging process.

[0166] The difference between the requested charging current and the actual charging current is integrated over time to obtain the first charging capacity difference;

[0167] Calculate the difference between the rated capacity of the battery and the capacity at the initial charging moment of the battery to obtain the first initial capacity difference;

[0168] The accuracy of the first charging data is calculated based on the first charging power difference, the first initial power difference, and the actual charging time, using the following formula:

[0169] P1 = (ΔIt1 / ΔAH1) * Tact

[0170] Wherein, P1 represents the first charging data accuracy, ΔIt1 represents the first charging power difference, ΔAH1 represents the first initial power difference, and Tact represents the actual charging time;

[0171] If the accuracy of the first charging data is less than the accuracy of the remaining charging time, then the capacity charging data and the current charging data are entered into the capacity-based data pool to optimize the neuron model.

[0172] For example, the format rules for the DC charging remaining time data pool based on capacity mode are as follows:

[0173] Each time charging begins, the remaining battery pack capacity, battery temperature, ambient temperature, and cumulative equivalent discharge cycles are recorded at the initial moment of charging. The integral of the difference between the requested current and the actual charging current during the entire charging process, as well as the actual charging time, are also recorded.

[0174] Let ΔIt1 = the integral of the difference between the charging current and the actual charging current during the entire process from the start of charging to the completion of charging;

[0175] ΔAH1 = Rated battery capacity – Remaining battery pack capacity at the initial moment of charging (battery capacity);

[0176] Tcr = Accuracy requirement for remaining charging time;

[0177] Tact = Actual charging time;

[0178] For the DC charging remaining time data pool based on capacity mode, if (ΔIt1 / ΔAH1)*Tact>Tcr, then the data set is not recorded; otherwise, it is considered valid data and is entered into the capacity mode data pool to optimize the neuron model.

[0179] Furthermore, the method for calculating the remaining battery charging time also includes:

[0180] If the remaining charging time is calculated using either the first voltage correction point mode or the second voltage correction point mode when charging ends, then voltage correction point charging data is obtained. The voltage correction point charging data includes the battery rated capacity, the battery capacity corresponding to the voltage correction point, the accuracy of the remaining charging time, the actual charging time, and the requested charging current and the actual charging current during the charging process after the voltage correction point.

[0181] The difference between the requested charging current and the actual charging current is integrated over time to obtain the second charging capacity difference;

[0182] Calculate the difference between the battery's rated capacity and the battery capacity corresponding to the voltage correction point to obtain the second initial capacity difference;

[0183] The accuracy of the second charging data is calculated based on the second charging power difference, the second initial power difference, and the actual charging time, using the following formula:

[0184] P2 = (ΔIt2 / ΔAH2) * Tact

[0185] Wherein, P2 represents the second charging data accuracy, ΔIt2 represents the second charging power difference, ΔAH2 represents the second initial power difference, and Tact represents the actual charging time;

[0186] If the accuracy of the second charging data is less than the accuracy of the remaining charging time, then the voltage correction point charging data and the current charging data are entered into the voltage correction point data pool to optimize the neuron model.

[0187] For example, the format rules for the DC charging remaining time data pool based on the end voltage correction point mode are as follows:

[0188] Each time the battery voltage (current maximum cell voltage) reaches the set correction point voltage, the battery temperature, external ambient temperature, and cumulative equivalent discharge cycle count at that moment are recorded. The integral of the difference between the requested current and the actual charging current during the entire process from the trigger voltage correction point to the completion of charging, as well as the charging time used from the trigger voltage correction point to the completion of charging, are also recorded.

[0189] ΔIt2 = Integral of the difference between the requested charging current and the actual charging current from the trigger voltage correction point to the completion of charging;

[0190] ΔAH2 = Battery rated capacity – Remaining capacity at the voltage correction point;

[0191] λ = (Battery rated capacity – Remaining capacity at the voltage correction point) / Battery pack rated capacity;

[0192] SOC = Current remaining battery pack capacity / Rated battery pack capacity;

[0193] For the DC charging remaining time data pool based on the end voltage correction point, if (ΔIt2 / ΔAH2)*Tact>λ*Tcr, then the data set is not recorded; otherwise, it is considered valid data and is entered into the data pool based on the voltage correction point mode to optimize the neuron model.

[0194] Through one or more embodiments of the above embodiments of the present invention, at least the following technical effects can be achieved:

[0195] In the technical solution disclosed in this invention, at the start of charging, it is determined whether the battery has reached the voltage correction point and whether the battery status information meets preset conditions. Based on the battery status, a time calculation mode is determined. The battery can calculate the remaining charging time entirely based on capacity mode, or first based on capacity mode and then switch to the first voltage correction point mode, or it can calculate the remaining charging time entirely based on the second voltage correction point mode. By determining the calculation mode based on battery voltage and battery capacity, the accuracy of the DC charging remaining time can be guaranteed even when the remaining battery capacity is inaccurate. This solves the problems of inaccurate DC charging remaining time and frequent jumps, ensuring the accuracy of the charging remaining time calculation throughout the entire lifespan under various operating conditions.

[0196] Furthermore, under various calculation modes, this solution can acquire charging data in real time and input it into the neural network model to obtain an accurate initial value of the remaining DC charging time. During the charging process, the frequency of updating the remaining time is determined according to the increase in power, and the updated value is generated by the previous frame of data and the current data. Even if the current fluctuates dynamically, the stability and accuracy of the remaining DC charging time can be guaranteed. The neural network model is used when calculating the time, and the data is filtered to optimize the model. It has self-learning capabilities and can continuously optimize the accuracy of the remaining charging time based on real vehicle DC charging data, which can avoid the problem of inaccurate remaining charging time after battery aging.

[0197] Based on the same inventive concept as the battery charging remaining time calculation method in this embodiment of the invention, this embodiment of the invention provides a battery charging remaining time calculation device. Please refer to... Figure 5 The device includes:

[0198] The information acquisition module 201 is used to acquire the status information of the battery, wherein the status information is one or both of battery voltage and battery charge.

[0199] The first calculation module 202 is used to calculate the remaining charging time of the battery based on the capacity mode if the initial state information of the battery does not meet the preset conditions during the battery charging process, and to calculate the remaining charging time based on the first voltage correction point mode when the state information of the battery meets the preset conditions, until the charging is completed.

[0200] The second calculation module 203 is used to calculate the remaining charging time based on a second voltage correction point mode, until charging is completed, if the initial state information of the battery meets preset conditions during battery charging. Further, the device is also used to:

[0201] If the battery voltage is less than a preset correction point voltage, then the state information is determined not to meet the preset condition, wherein the correction point voltage is used to correct the battery charge; or,

[0202] If the battery voltage is greater than or equal to the correction point voltage, then the current battery level and the correction point level corresponding to the correction point voltage are obtained, and the difference between the battery level and the correction point level is calculated. If the difference is less than a preset power threshold, then it is determined that the state information does not meet the preset condition.

[0203] If the battery voltage is greater than or equal to the correction point voltage, and the power difference is greater than or equal to the power threshold, then the status information is determined to meet the preset condition.

[0204] Furthermore, the first computing module 202 is also used for:

[0205] Obtain the current charging data of the battery;

[0206] The current charging data is input into the neuron model to calculate the real-time value of the remaining charging time.

[0207] Obtain the continuous charging time for charging the battery;

[0208] The remaining charging time is updated based on the real-time value of the remaining charging time and the continuous charging time.

[0209] Furthermore, the first computing module 202 is also used for:

[0210] Obtain the first current charging data of the battery, wherein the first current charging data includes battery capacity, battery temperature, ambient temperature, and number of discharge cycles;

[0211] The first current charging data at the start of charging is input into the neuron model to calculate the initial value of the first remaining charging time.

[0212] Whenever the change in battery capacity reaches a preset threshold, the following operation is executed cyclically:

[0213] The first current charging data during the charging process is input into the neuron model to calculate the real-time value of the first remaining charging time.

[0214] Obtain the continuous charging time for charging the battery;

[0215] Calculate the difference between the initial value of the first remaining charging time and the continuous charging time to obtain the remaining charging time;

[0216] The remaining charging time is updated based on the current remaining charging time, the real-time value of the first remaining charging time, and the continuous charging time.

[0217] Wherein, when the battery voltage is less than a preset correction point voltage, the change threshold is a first threshold; when the battery voltage is greater than or equal to the correction point voltage, the change threshold is a second threshold; wherein, the first threshold is greater than the second threshold.

[0218] Furthermore, the first computing module 202 is also used for:

[0219] Acquire the second current charging data of the battery, wherein the second current charging data includes the current maximum voltage of the cell, battery temperature, ambient temperature, and number of discharge cycles;

[0220] The second current charging data is input into the neuron model to calculate the real-time value of the second remaining charging time.

[0221] Obtain the continuous charging time for charging the battery;

[0222] The remaining charging time is updated based on the second real-time value of the remaining charging time and the continuous charging time.

[0223] Furthermore, the second computing module 203 is also used for:

[0224] Obtain the second current charging data of the battery, wherein the second current charging data includes the current maximum voltage of the cell, battery temperature, ambient temperature, and number of discharge cycles;

[0225] The second current charging data at the start of charging is input into the neuron model to calculate the initial value of the second remaining charging time;

[0226] Obtain the continuous charging time for charging the battery;

[0227] The remaining charging time is calculated based on the initial value of the second remaining charging time and the continuous charging time.

[0228] Furthermore, the device is also used for:

[0229] If the remaining charging time is calculated using the capacity mode when charging ends, then capacity charging data is obtained, wherein the capacity charging data includes the battery rated capacity, the battery capacity at the initial charging time, the accuracy of the remaining charging time, the actual charging time, and the requested charging current and the actual charging current during the charging process.

[0230] The difference between the requested charging current and the actual charging current is integrated over time to obtain the first charging capacity difference;

[0231] Calculate the difference between the rated capacity of the battery and the capacity at the initial charging moment of the battery to obtain the first initial capacity difference;

[0232] The accuracy of the first charging data is calculated based on the first charging power difference, the first initial power difference, and the actual charging time, using the following formula:

[0233] P1 = (ΔIt1 / ΔAH1) * Tact

[0234] Wherein, P1 represents the first charging data accuracy, ΔIt1 represents the first charging power difference, ΔAH1 represents the first initial power difference, and Tact represents the actual charging time;

[0235] If the accuracy of the first charging data is less than the accuracy of the remaining charging time, then the capacity charging data and the current charging data are entered into the capacity-based data pool to optimize the neuron model.

[0236] Furthermore, the device is also used for:

[0237] If the remaining charging time is calculated using either the first voltage correction point mode or the second voltage correction point mode when charging ends, then voltage correction point charging data is obtained. The voltage correction point charging data includes the battery rated capacity, the battery capacity corresponding to the voltage correction point, the accuracy of the remaining charging time, the actual charging time, and the requested charging current and the actual charging current during the charging process after the voltage correction point.

[0238] The difference between the requested charging current and the actual charging current is integrated over time to obtain the second charging capacity difference;

[0239] Calculate the difference between the battery's rated capacity and the battery capacity corresponding to the voltage correction point to obtain the second initial capacity difference;

[0240] The accuracy of the second charging data is calculated based on the second charging power difference, the second initial power difference, and the actual charging time, using the following formula:

[0241] P2 = (ΔIt2 / ΔAH2) * Tact

[0242] Wherein, P2 represents the second charging data accuracy, ΔIt2 represents the second charging power difference, ΔAH2 represents the second initial power difference, and Tact represents the actual charging time;

[0243] If the accuracy of the second charging data is less than the accuracy of the remaining charging time, then the voltage correction point charging data and the current charging data are entered into the voltage correction point data pool to optimize the neuron model.

[0244] Other aspects and implementation details of the battery charging remaining time calculation device are the same as or similar to the battery charging remaining time calculation method described above, and will not be repeated here.

[0245] According to another aspect of the invention, the invention also provides a storage medium storing a plurality of instructions adapted to be loaded by a processor to execute any of the battery charge remaining time calculation methods described above.

[0246] In summary, although the present invention has been disclosed above with reference to preferred embodiments, the above preferred embodiments are not intended to limit the present invention. Those skilled in the art can make various modifications and refinements without departing from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention shall be determined by the scope defined in the claims.

Claims

1. A method for calculating the remaining charging time of a battery, characterized in that, The method for calculating the remaining battery charging time includes: Obtain battery status information, wherein the status information is one or both of battery voltage and battery charge; During battery charging, if the initial state information of the battery does not meet the preset conditions, the remaining charging time is calculated based on the capacity mode. When the battery state information meets the preset conditions, the remaining charging time is calculated based on the first voltage correction point mode, until charging is completed; or... During battery charging, if the initial state information of the battery meets the preset conditions, the remaining charging time is calculated based on the second voltage correction point mode until charging is completed. The calculation of the remaining charging time of the battery based on the capacity mode includes: Obtain the first current charging data of the battery; The first current charging data at the start of charging is input into the neuron model to calculate the initial value of the remaining charging time for the first charging step. Whenever the change in battery capacity reaches a preset threshold, the following operation is executed repeatedly: The first current charging data during the charging process is input into the neuron model to calculate the real-time value of the first remaining charging time. Obtain the continuous charging time for charging the battery; Calculate the difference between the initial value of the first remaining charging time and the continuous charging time to obtain the remaining charging time; The remaining charging time is updated based on the current remaining charging time, the real-time value of the first remaining charging time, and the continuous charging time. When the battery voltage is less than a preset correction point voltage, the change threshold is a first threshold; when the battery voltage is greater than or equal to the correction point voltage, the change threshold is a second threshold; the first threshold is greater than the second threshold.

2. The method for calculating the remaining battery charging time as described in claim 1, characterized in that, Determining whether the status information meets the preset conditions includes: If the battery voltage is less than a preset correction point voltage, then the state information is determined not to meet the preset condition, wherein the correction point voltage is used to correct the battery charge; or, If the battery voltage is greater than or equal to the correction point voltage, then the current battery level and the correction point level corresponding to the correction point voltage are obtained, and the difference between the battery level and the correction point level is calculated. If the difference is less than a preset power threshold, then it is determined that the state information does not meet the preset condition. If the battery voltage is greater than or equal to the correction point voltage, and the power difference is greater than or equal to the power threshold, then the status information is determined to meet the preset condition.

3. The method for calculating remaining battery charging time as described in claim 1, characterized in that, The first current charging data includes battery capacity, battery temperature, ambient temperature, and number of discharge cycles.

4. The method for calculating the remaining battery charging time as described in claim 1, characterized in that, The calculation of the remaining charging time based on the first voltage correction point mode includes: Acquire the second current charging data of the battery, wherein the second current charging data includes the current maximum voltage of the cell, battery temperature, ambient temperature, and number of discharge cycles; The second current charging data is input into the neuron model to calculate the real-time value of the second remaining charging time. Obtain the continuous charging time for charging the battery; The remaining charging time is updated based on the second real-time value of the remaining charging time and the continuous charging time.

5. The method for calculating the remaining battery charging time as described in claim 1, characterized in that, The calculation of the remaining charging time based on the second voltage correction point mode includes: Obtain the second current charging data of the battery, wherein the second current charging data includes the current maximum voltage of the cell, battery temperature, ambient temperature, and number of discharge cycles; The second current charging data at the start of charging is input into the neuron model to calculate the initial value of the second remaining charging time; Obtain the continuous charging time for charging the battery; The remaining charging time is calculated based on the initial value of the second remaining charging time and the continuous charging time.

6. The method for calculating the remaining battery charging time as described in claim 1, characterized in that, The method for calculating the remaining battery charging time also includes: If the remaining charging time is calculated using the capacity mode when charging ends, then capacity charging data is obtained, wherein the capacity charging data includes the battery rated capacity, the battery capacity at the initial charging time, the accuracy of the remaining charging time, the actual charging time, and the requested charging current and the actual charging current during the charging process. The difference between the requested charging current and the actual charging current is integrated over time to obtain the first charging capacity difference; Calculate the difference between the rated capacity of the battery and the capacity at the initial charging moment of the battery to obtain the first initial capacity difference; The accuracy of the first charging data is calculated based on the first charging power difference, the first initial power difference, and the actual charging time, using the following formula: P1=(ΔIt1 / ΔAH1)*Tact, Wherein, P1 represents the first charging data accuracy, ΔIt1 represents the first charging power difference, ΔAH1 represents the first initial power difference, and Tact represents the actual charging time; If the accuracy of the first charging data is less than the accuracy of the remaining charging time, then the capacity charging data and the current charging data are entered into the capacity-based data pool to optimize the neuron model.

7. The method for calculating remaining battery charging time as described in claim 1, characterized in that, The method for calculating the remaining battery charging time also includes: If the remaining charging time is calculated using either the first voltage correction point mode or the second voltage correction point mode when charging ends, then voltage correction point charging data is obtained. The voltage correction point charging data includes the battery rated capacity, the battery capacity corresponding to the voltage correction point, the accuracy of the remaining charging time, the actual charging time, and the requested charging current and the actual charging current during the charging process after the voltage correction point. The difference between the requested charging current and the actual charging current is integrated over time to obtain the second charging capacity difference; Calculate the difference between the battery's rated capacity and the battery capacity corresponding to the voltage correction point to obtain the second initial capacity difference; The accuracy of the second charging data is calculated based on the second charging power difference, the second initial power difference, and the actual charging time, using the following formula: P2=(ΔIt2 / ΔAH2)* Tact Wherein, P2 represents the second charging data accuracy, ΔIt2 represents the second charging power difference, ΔAH2 represents the second initial power difference, and Tact represents the actual charging time; If the accuracy of the second charging data is less than the accuracy of the remaining charging time, then the voltage correction point charging data and the current charging data are entered into the voltage correction point data pool to optimize the neuron model.

8. A battery charging remaining time calculation device, characterized in that, The device includes: An information acquisition module is used to acquire battery status information, wherein the status information is one or both of battery voltage and battery charge. A first calculation module is used to calculate the remaining charging time of the battery based on a capacity mode if the initial state information of the battery does not meet a preset condition during battery charging, and to calculate the remaining charging time based on a first voltage correction point mode when the battery state information meets the preset condition, until charging is completed. The calculation of the remaining charging time based on the capacity mode includes: acquiring the battery's first current charging data; inputting the first current charging data at the start of charging into a neural network model to calculate an initial value of the first remaining charging time; whenever the change in battery capacity reaches a preset change threshold, repeatedly performing the following operations: inputting the first current charging data during charging into the neural network model to calculate a real-time value of the first remaining charging time; acquiring the continuous charging time for charging the battery; calculating the difference between the initial value of the first remaining charging time and the continuous charging time to obtain the remaining charging time; updating the remaining charging time based on the current remaining charging time, the real-time value of the first remaining charging time, and the continuous charging time; when the battery voltage is less than a preset correction point voltage, the change threshold is a first threshold; when the battery voltage is greater than or equal to the correction point voltage, the change threshold is a second threshold; the first threshold is greater than the second threshold. The second calculation module is used to calculate the remaining charging time based on the second voltage correction point mode if the initial state information of the battery meets the preset conditions during the battery charging process, until the charging is completed.

9. A storage medium, characterized in that, The storage medium stores a plurality of instructions adapted for loading by a processor to execute the battery charging remaining time calculation method as described in any one of claims 1 to 7.

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