Battery pack charging and discharging power meter optimization method and device, electronic equipment and storage medium

Abstract

The invention relates to a battery pack charging and discharging power meter optimization method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining the current driving data of an electric vehicle, the current driving data comprising pedal opening data and battery pack state data in the current driving process of the electric vehicle; power output or power recovery is carried out on a battery pack in the current driving process of the electric vehicle according to the current charging and discharging power meter; according to the reference driving data and the current driving data of the electric vehicle, optimizing the current charging and discharging power table to obtain a target charging and discharging power table, so that the battery pack performs power output or power recovery according to the target charging and discharging power table; wherein the reference driving data comprises pedal opening degree data and battery pack state data in at least one historical driving process determined in the initial use stage of the battery pack in the electric vehicle. Therefore, the optimized target charging and discharging power meter can be more adaptive to the actual charging and discharging capacity of the current battery pack.

Description

Technical Field

[0001] The present disclosure relates to the field of batteries, and in particular to a method and device for optimizing a battery pack charge and discharge power meter, an electronic device, and a storage medium. Background Art

[0002] The power battery pack is a core component of new energy vehicles, such as electric vehicles. Accurately estimating the power battery pack's performance can improve the overall driving experience and prevent misuse. With the continuous iteration and upgrading of battery pack technology, product iteration cycles are becoming increasingly faster. To meet the product development cycle, smarter and more efficient methods are needed to estimate battery performance (i.e., the battery pack's charge and discharge capabilities).

[0003] In particular, the current battery management system (BMS) of the battery pack usually uses the battery's Beginning of Life (BOL) data (i.e., the battery pack's initial charge and discharge power table, which reflects the battery pack's initial charge and discharge capabilities) to perform charge and discharge management (i.e., power output or power recovery). However, as the battery pack's usage time increases, the battery pack will inevitably age, and the battery pack's charge and discharge performance will decline after aging. Therefore, the BOL data cannot well adapt to the actual charge and discharge capabilities of the battery pack in its current state. If the BOL data is always used for charge and discharge management, it is easy to cause a sudden voltage drop in the battery pack, triggering an undervoltage fault or accelerating the decay of the battery cell life. Moreover, when applied to the vehicle level, it will also lead to problems such as inaccurate mileage estimation, inaccurate power usage estimation, and power performance that cannot match the vehicle's requirements. Summary of the Invention

[0004] In view of this, the present disclosure proposes a battery pack charge and discharge power meter optimization method and device, electronic equipment and storage medium, which can make the optimized target charge and discharge power meter more adaptable to the actual charge and discharge capacity of the current battery pack.

[0005] According to one aspect of the present disclosure, a method for optimizing a battery pack charge and discharge power table is provided, wherein the battery pack is applied to an electric vehicle, and the method comprises: obtaining current driving data of the electric vehicle, the current driving data comprising pedal opening data and battery pack status data during the current driving process of the electric vehicle; wherein the battery pack during the current driving process of the electric vehicle outputs power or recovers power according to the current charge and discharge power table; and optimizing the current charge and discharge power table according to the baseline driving data of the electric vehicle and the current driving data to obtain a target charge and discharge power table, so that the battery pack outputs power or recovers power according to the target charge and discharge power table; wherein the baseline driving data comprises pedal opening data and battery pack status data during at least one historical driving process determined during the initial use phase of the battery pack in the electric vehicle.

[0006] In one possible implementation, the pedal opening data includes the pedal opening at each moment during driving; the battery pack status data includes the temperature, state of charge and voltage change rate of the battery pack at each moment during driving; wherein, the current charge and discharge power table is optimized according to the baseline driving data of the electric vehicle and the current driving data to obtain a target charge and discharge power table, including: by comparing the temperature, state of charge and pedal opening of the battery pack at each moment of the baseline driving data and the current driving data, the reference voltage change rate and the current voltage change rate at the same temperature, the same state of charge and the same pedal opening are determined from the baseline driving data and the current driving data; according to the error between the reference voltage change rate and the current voltage change rate, the current charge and discharge power table is optimized to obtain a target charge and discharge power table.

[0007] In one possible implementation, the voltage change rate includes: a maximum single-cell voltage change rate and a minimum single-cell voltage change rate; wherein, the current charge and discharge power table is optimized according to the error between the reference voltage change rate and the current voltage change rate to obtain a target charge and discharge power table, including: determining a first absolute error between the maximum single-cell voltage change rate in the reference voltage change rate and the maximum single-cell voltage change rate in the current voltage change rate, and determining a second absolute error between the minimum single-cell voltage change rate in the reference voltage change rate and the minimum single-cell voltage change rate in the current voltage change rate; when the first absolute error and the second absolute error meet preset optimization conditions, determining a power correction coefficient according to the reference voltage change rate and the current voltage change rate; and correcting the charge and discharge power corresponding to the temperature and charge state of the current voltage change rate in the current charge and discharge power table by using the power correction coefficient to obtain a target charge and discharge power table.

[0008] In one possible implementation, the preset optimization conditions include: when the temperature corresponding to the current voltage change rate is within a normal temperature range, the first absolute error and the second absolute error are both greater than a first error threshold; when the temperature corresponding to the current voltage change rate is within an abnormal temperature range, the first absolute error and the second absolute error are both greater than a second error threshold; wherein the second error threshold is greater than the first error threshold.

[0009] In one possible implementation, determining the power correction coefficient based on the reference voltage change rate and the current voltage change rate includes: determining a first ratio between the maximum single-cell voltage change rate in the reference voltage change rate and the maximum single-cell voltage change rate in the current voltage change rate, and determining a second ratio between the minimum single-cell voltage change rate in the reference voltage change rate and the minimum single-cell voltage change rate in the current voltage change rate; and determining the maximum value of the first ratio and the second ratio as the power correction coefficient.

[0010] In one possible implementation, the current charge and discharge power table includes a current discharge power table used by the battery pack for power output and a current charging power table used by the battery pack for power recovery; the pedal opening includes an accelerator pedal opening or a brake pedal opening; wherein, the current voltage change rate corresponding to the temperature and charge state in the current charge and discharge power table is corrected by the power correction coefficient to obtain a target charge and discharge power table, including: when the current voltage change rate corresponds to the accelerator pedal opening, the current voltage change rate corresponding to the temperature and charge state in the current discharge power table is corrected by the power correction coefficient to obtain a target discharge power table; when the current voltage change rate corresponds to the brake pedal opening, the current voltage change rate corresponding to the temperature and charge state in the current charging power table is corrected by the power correction coefficient to obtain a target charging power table.

[0011] In one possible implementation, the current driving data also includes a current driving trajectory corresponding to the current driving process, and the benchmark driving data also includes at least one historical driving trajectory corresponding to each historical driving process; wherein, the current charge and discharge power table is optimized based on the benchmark driving data of the electric vehicle and the current driving data to obtain a target charge and discharge power table, including: obtaining a target historical driving trajectory that matches the current driving trajectory by comparing the current driving trajectory with the historical driving trajectories of each historical driving process; optimizing the current charge and discharge power table based on the target benchmark driving data and the current driving data to obtain a target charge and discharge power table, the target benchmark driving data including the pedal opening data and battery pack status data in the historical driving process corresponding to the target historical driving trajectory.

[0012] According to another aspect of the present disclosure, a battery pack charge and discharge power table optimization device is provided, wherein the battery pack is applied to an electric vehicle, and the device includes: an acquisition module for acquiring current driving data of the electric vehicle, the current driving data including pedal opening data and battery pack status data during the current driving process of the electric vehicle; wherein the battery pack during the current driving process of the electric vehicle outputs power or recovers power according to the current charge and discharge power table; an optimization module for optimizing the current charge and discharge power table according to the baseline driving data of the electric vehicle and the current driving data to obtain a target charge and discharge power table, so that the battery pack outputs power or recovers power according to the target charge and discharge power table; wherein the baseline driving data includes pedal opening data and battery pack status data during at least one historical driving process determined during the initial use stage of the battery pack in the electric vehicle.

[0013] According to another aspect of the present disclosure, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above method.

[0014] According to another aspect of the present disclosure, a non-volatile computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above method are implemented.

[0015] According to another aspect of the present disclosure, a computer program product is provided, including a computer program, or a non-volatile computer-readable storage medium carrying the computer program, wherein the computer program implements the steps of the above method when executed by a processor.

[0016] According to various aspects of the present disclosure, by utilizing the pedal opening data and battery pack status data during the historical driving process determined in the initial use stage of the battery pack in the electric vehicle (equivalent to the battery pack non-aging stage, the new car use stage), as well as the pedal opening data and battery pack status data during the current driving process, the current charge and discharge power table used in the current journey of the battery pack is optimized, so that the optimized target charge and discharge power table can be more adapted to the actual charge and discharge capacity of the current battery pack (that is, the actual performance of the battery pack). Therefore, when the battery pack outputs power or recovers power according to the target charge and discharge rate, the number of times the battery pack triggers faults such as undervoltage can be reduced, the battery pack life attenuation rate can be alleviated, the estimation accuracy of the vehicle's mileage and battery power can be improved, and the battery pack power performance can better match the needs of the vehicle, which is conducive to improving the driving experience and reducing the probability of failure.

[0017] Further features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate exemplary embodiments, features, and aspects of the disclosure and, together with the description, serve to explain the principles of the disclosure.

[0019] Figure 1 A flowchart of a battery pack charging and discharging power meter optimization method according to an embodiment of the present disclosure is shown.

[0020] Figure 2 A schematic diagram of a battery pack charging and discharging power meter optimization system according to an embodiment of the present disclosure is shown.

[0021] Figure 3 A block diagram of a battery pack charging and discharging power meter optimization device according to an embodiment of the present disclosure is shown.

[0022] Figure 4 A block diagram of an electronic device 1900 according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0023] Various exemplary embodiments, features, and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numerals in the accompanying drawings represent elements with the same or similar functions. Although various aspects of the embodiments are shown in the accompanying drawings, the drawings are not necessarily drawn to scale unless otherwise indicated.

[0024] As used herein, the terms "comprises," "comprising," "having," or variations thereof are open ended and include one or more stated features, integers, elements, steps, parts, or functions, but do not preclude the presence or addition of one or more other features, integers, elements, steps, parts, functions, or groups thereof.

[0025] When an element is referred to as being "connected," "coupled," "responsive" or variations thereof to another element, it can be directly connected, coupled or responsive to the other element or intervening elements may be present.

[0026] Although the terms first, second, third, etc. may be used herein to describe various elements / operations, these elements / operations should not be limited by these terms. These terms are only used to distinguish one element / operation from another element / operation. Therefore, without departing from the teachings of the present invention, the first element / operation in some embodiments may be referred to as the second element / operation in other embodiments.

[0027] The word “exemplary” is used exclusively herein to mean “serving as an example, example, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.

[0028] In addition, numerous specific details are provided in the following detailed description to better illustrate the present disclosure. Those skilled in the art will appreciate that the present disclosure can be practiced without certain specific details. In some instances, methods, means, components, and circuits well known to those skilled in the art are not described in detail in order to highlight the main points of the present disclosure.

[0029] As mentioned above, the charge and discharge performance of the battery pack will decline after aging. Therefore, the charge and discharge power meter initially calibrated for the battery pack cannot well reflect the actual charge and discharge capacity of the battery pack in its current state. When applied to the vehicle level, it may lead to inaccurate estimation of the vehicle's mileage and battery power, and the battery pack's power performance cannot match the vehicle's needs. In addition, the battery pack and the vehicle controller interact in real time through a communication protocol, that is, the BMS will provide real-time feedback on the current allowable charge and discharge capacity of the battery pack. If the initial charge and discharge power meter is always used in the BMS to manage the charge and discharge of the battery pack, battery pack performance abuse will occur. For example, if the battery pack allows a discharge current of 100A at a certain temperature and SOC before aging, if the battery pack has aged, at the same temperature and SOC, if it is still discharged at 100A, it may cause a sudden voltage drop in the battery pack, triggering a voltage drop fault or accelerating the decay of the battery cell life, increasing the probability of battery pack failure and reducing the driving experience of the entire vehicle.

[0030] In view of this, the embodiments of the present disclosure propose a battery pack charge and discharge power meter optimization method and device, electronic device and storage medium, by utilizing the pedal opening data and battery pack status data during the historical driving process determined in the initial use stage of the battery pack in the electric vehicle (equivalent to the non-aging stage, the new car use stage), as well as the pedal opening data and battery pack status data during the current driving process, to optimize the current charge and discharge power meter currently used by the battery pack, so that the optimized target charge and discharge power meter can be more adapted to the actual charge and discharge capacity of the current battery pack (that is, the actual performance of the battery pack), and can also be continuously iterated and updated. The charge and discharge power meter used in the new battery pack solves the problem of abuse of the battery pack after aging of its power performance, and uses a target charge and discharge power meter that is more suitable for the actual performance of the battery pack for charge and discharge management, which can improve the driving experience of the entire vehicle and reduce the probability of failure. Specifically, since the BMS will provide real-time feedback on the current allowable charge and discharge capacity of the battery, when the battery pack is aged and the optimized target charge and discharge rate table is used for charge and discharge management, the allowable charge and discharge power can be appropriately reduced, thereby allowing the entire vehicle to reduce the number of times undervoltage or other faults are triggered, and improve the accuracy of the vehicle's mileage and battery power estimation, thereby improving the driving experience.

[0031] In practical applications, the battery pack charge and discharge power meter optimization method provided by the embodiment of the present disclosure can be deployed on a server, which can be located in the cloud or locally, and can be a physical device or a virtual device, such as a virtual machine, a container, etc., with a wireless communication function, wherein the wireless communication function can be set in the chip (system) or other parts or components of the server. It can refer to a device with a wireless connection function, and the wireless connection function means that it can communicate with the vehicle control unit (VCU) and the battery management system BMS in the electric vehicle through a wireless connection method such as Wi-Fi and a wireless network to receive the pedal opening data and battery pack status data sent by the VCU and the BMS, and execute the optimization method of the embodiment of the present disclosure. Of course, the battery pack charge and discharge power meter optimization method provided by the embodiment of the present disclosure can also be directly deployed in the vehicle control unit or the battery pack BMS or other processing units (such as a single-chip microcomputer, a microcontroller, etc.) of the electric vehicle to directly execute the optimization method of the embodiment of the present disclosure locally in the electric vehicle, and the embodiment of the present disclosure is not limited to this.

[0032] Figure 1 A flow chart of a method for optimizing a battery pack charge and discharge power meter according to an embodiment of the present disclosure is shown. The battery pack is applied to an electric vehicle, which may include an electric car, an electric bus, etc., and the present disclosure does not limit this. Figure 1 As shown, the method includes:

[0033] Step S11, obtaining current driving data of the electric vehicle, the current driving data including pedal opening data and battery pack status data during the current driving process of the electric vehicle; wherein the battery pack during the current driving process of the electric vehicle outputs power or recovers power according to the current charge and discharge power table;

[0034] Step S12: Optimize the current charge and discharge power table based on the baseline driving data and current driving data of the electric vehicle to obtain a target charge and discharge power table so that the battery pack can output power or recover power according to the target charge and discharge power table; wherein the baseline driving data includes pedal opening data and battery pack status data in at least one historical driving process determined during the initial use stage of the battery pack in the electric vehicle.

[0035] In step S11, the pedal opening data includes the pedal opening at each moment during the driving process, and the pedal opening may include the accelerator pedal opening or the brake pedal opening. It should be understood that the pedal opening under different working conditions and at different moments during the vehicle's driving process is different. It can be seen that the vehicle controller VCU in the electric vehicle can obtain the pulse width modulation (PWM) signal converted from the pedal opening size to obtain the pedal opening of the accelerator pedal or the brake pedal during the vehicle's driving process, and thus can obtain the pedal opening data during the current driving process. The embodiment of the present disclosure does not limit the method for obtaining the pedal opening.

[0036] In step S11, the battery pack status data may include the battery pack temperature, state of charge, and voltage change rate at various moments during driving. Optionally, the voltage change rate may include the rate of change of the total battery pack voltage or the rate of change of the cell voltage of any cell in the battery pack. In practical applications, the battery pack's battery management system can monitor the battery pack temperature, state of charge, and cell voltage of each cell in the battery pack in real time during vehicle driving. The total battery pack voltage can, for example, be the average of the cell voltages of each cell in the battery pack. It should be understood that knowing the cell voltage of each cell at various moments during vehicle driving also provides the total battery pack voltage or the cell voltage of a cell at various moments. Based on the total battery pack voltage or cell voltage at various moments, the voltage change rate at each moment can be calculated. For example, the voltage change rate at a current moment can be equal to the difference between the cell voltage at the current moment and the cell voltage at the previous moment, divided by the time between the current moment and the previous moment. The disclosed embodiments do not limit the method for obtaining the battery pack temperature, state of charge, and voltage change rate; as long as the relevant data can be obtained, it is sufficient.

[0037] As described above, the optimization method of the embodiment of the present disclosure can be executed by the server. When the vehicle controller obtains the pedal opening data and the battery management system obtains the battery pack status data, the pedal opening data and the battery pack status data can be sent to the server to be stored in the server and execute the optimization method of the embodiment of the present disclosure; of course, if the optimization method of the embodiment of the present disclosure is executed by the vehicle controller or the BMS controller, the vehicle controller and the BMS controller can transmit the pedal opening data or the battery pack status data to each other to execute the optimization method of the embodiment of the present disclosure, and the embodiment of the present disclosure does not limit this.

[0038] It is understandable that a vehicle's driving process will have acceleration, deceleration, and downhill operating stages. During the acceleration phase, the battery pack needs to output power, and the battery pack voltage decreases. Therefore, the voltage change rate during the acceleration phase can be understood as the voltage drop rate. However, since the battery pack can recover power during the deceleration and downhill phases, the battery pack voltage increases. Therefore, the voltage change rate during the deceleration and downhill phases can be understood as the voltage rise rate.

[0039] In step S11, the current charge and discharge power table of the battery pack can be understood as the charge and discharge power table currently used by the battery pack. The charge and discharge power table currently used can be the initial charge and discharge power table of the battery pack, or it can be the charge and discharge power table optimized by one or more optimization methods. The embodiment of the present disclosure does not limit this. Among them, the charge and discharge power table includes a discharge power table used by the battery pack for power output and a charging power table used by the battery pack for power recovery, so that the battery pack can output power (equivalent to discharge) or recover power (equivalent to charging) according to the current charge and discharge power table. Among them, the discharge power table can include the discharge power (that is, the maximum allowable discharge power) at different temperatures and different SOCs, and the charging power table can include the charging power (that is, the maximum allowable charging power) at different temperatures and different SOCs. For example, Table 1 shows a discharge power table. As shown in Table 1, the discharge power table shows the discharge power at different temperatures and different SOCs.

[0040] Table 1 Discharge power table

[0041]

[0042] Among them, SOC0 can represent the initial state of charge, which can be the state of charge in a fully discharged state, that is, the state of charge is 0%, SOC m It can represent the end state of charge, which can be the state of charge in a fully charged state, that is, the state of charge is 100%. The SOC can be divided into m equal parts from 0% to 100%, for example, it can be divided into multiple parts in increments of 5% or 10%. It should be understood that SOC mIt can also represent any state of charge in an incompletely charged state, indicating a range from SOC0 to SOC m m equal parts between. T rn The battery temperature represents the reference temperature and can be divided from low to high within the operating temperature range of the battery pack. The operating temperature range includes the minimum temperature limit to the maximum temperature limit allowed by the battery pack. For example, the operating temperature range can be divided into 5°C or 10°C increments between -30°C and 65°C. nm Represents the battery temperature T rn , State of Charge (SOC) m The discharge power (or discharge power state, State Of Power, SOP) under the condition of 100V / 100V is 0.1V, and the other values are deduced by analogy.

[0043] In actual applications, the current charge and discharge power table of the battery pack can be written into the BMS controller of the battery pack as the charge and discharge power table of the whole vehicle power demand during the current driving process of the electric vehicle to control the charge and discharge power of the battery pack. For example, during the driving of the battery vehicle, the whole vehicle controller adjusts the power demand size (the pedal opening is an element of the whole vehicle power demand) and requests the BMS to output power. The BMS then queries the current discharge power table to obtain the maximum allowable discharge power under the current temperature and current SOC, and outputs power according to the maximum allowable discharge power.

[0044] In step S12, the initial use stage of the battery pack in the electric vehicle can be understood as the stage where the battery pack has not aged significantly, or the new vehicle use stage. Therefore, pedal opening data and battery pack status data of at least one historical driving process determined in the initial use stage of the battery pack in the electric vehicle can be obtained as benchmark driving data, and the benchmark driving data can be used as a basis to determine whether the current charge and discharge power meter needs to be optimized and the degree of optimization. In practical applications, for example, pedal opening data and battery pack status data of at least one historical driving process collected within a period of time after the user starts using the electric vehicle (that is, the initial use stage, such as within 3 months, within half a year, within a year, etc.) can be obtained as benchmark driving data. Among them, a historical driving process can be a driving process from starting and powering on the electric vehicle to shutting down and powering off the engine, and a historical driving process can correspond to a driving trajectory, or a driving path.

[0045] It should be understood that a user's driving journeys within a certain period of time may be repetitive. For example, if a user drives from location A to location B 20 times and from location A to location C 4 times in a month, then the journey from location A to location B is a historical driving process, and the journey from location A to location C is a historical driving process. Therefore, by statistically analyzing the pedal opening data and battery pack status data of different historical driving processes in the initial use phase, a curve of the pedal opening changing over time in different historical driving processes and a curve of the battery pack status (temperature, state of charge, voltage change rate) changing over time can be obtained. The curve of the pedal opening changing over time can be defined as the user's driving habits. Then, by performing big data analysis on the curves of the pedal opening changing over time and the curves of the battery pack status changing over time in different historical driving processes and combining them with analysis algorithms such as fuzzy algorithms, the pedal opening data and battery pack status data of different historical driving processes can be obtained as benchmark driving data. Of course, the pedal opening data and battery status data obtained from the first completion of each historical driving process can also be directly used as the benchmark driving data. For example, the pedal opening data and battery status data collected from place A to place B for the first time can be used as the benchmark driving data corresponding to the historical driving process from place A to place B. This embodiment of the present disclosure does not limit this.

[0046] According to the optimization method of the embodiment of the present disclosure, by utilizing the pedal opening data and battery pack status data during the historical driving process determined in the initial use stage of the battery pack in the electric vehicle (equivalent to the battery pack non-aging stage, the new car use stage), as well as the pedal opening data and battery pack status data during the current driving process, the current charge and discharge power table used in the current driving process of the battery pack is optimized. The optimized target charge and discharge power table can be made more adapted to the actual charge and discharge capacity of the current battery pack (that is, the actual performance of the battery pack). Therefore, when the battery pack outputs power or recovers power according to the target charge and discharge rate, the number of times the battery pack triggers faults such as undervoltage can be reduced, the battery pack life attenuation rate can be alleviated, and the estimation accuracy of the vehicle's mileage and battery power can be improved. The battery pack's power performance is more in line with the needs of the vehicle, which is conducive to improving the driving experience and reducing the probability of failure.

[0047] As described above, the pedal opening data includes the pedal opening at each moment during driving; the battery pack status data includes the battery pack temperature, state of charge, and voltage change rate at each moment during driving. In step S12, the current charge and discharge power table can be optimized based on the baseline driving data and the current driving data of the electric vehicle to obtain a target charge and discharge power table, which may include:

[0048] Step S121, by comparing the battery pack temperature, state of charge, and pedal opening at each moment in the reference driving data and the current driving data, determining a reference voltage change rate and a current voltage change rate at the same temperature, state of charge, and pedal opening from the reference driving data and the current driving data;

[0049] Step S122 , optimizing the current charge and discharge power table according to the error between the reference voltage change rate and the current voltage change rate to obtain a target charge and discharge power table.

[0050] For example, assuming that the battery pack temperature at a certain moment t in the current driving data is 25°C, the state of charge is 30%, the pedal opening is 10%, and the voltage change rate is 5mV / s; by comparing the battery pack temperature, state of charge, and pedal opening at each moment in the benchmark driving data and the current driving data, the voltage change rate of 3.5mV / s when the temperature is 25°C, the state of charge is 30%, and the pedal opening is 10% is searched from the benchmark driving data. Then the voltage change rate of 5mV / s in the current driving data is the current voltage change rate, and the benchmark driving data is the same as the voltage change rate of 5mV / s. The voltage change rate of 3.5mV / s in the figure is the reference voltage change rate. It should be understood that if the voltage change rate that satisfies the temperature of 25°C, the state of charge of 30%, and the pedal opening of 10% is not found in the reference driving data, it means that there is no corresponding reference voltage change rate at the moment t. At this time, the voltage change rate with the same temperature, the same state of charge, and the same pedal opening at the next moment can be searched from the reference driving data based on the temperature, state of charge, and pedal opening of the battery pack at the next moment in the current driving data. The embodiment of the present disclosure does not limit this.

[0051] It should be understood that through step S121, one or more groups of reference voltage change rates and current voltage change rates with the same temperature, the same state of charge and the same pedal opening can be searched out. Then, in step S122, the charge and discharge power at the temperature and state of charge corresponding to each group of rates in the current charge and discharge power table can be optimized based on the error between the reference voltage change rate and the current voltage change rate for each group of rates with the same temperature, the same state of charge and the same pedal opening to obtain the target charge and discharge power table.

[0052] In one possible implementation, in step S122, for each group of reference voltage change rate Vst1 and current voltage change rate Vst2 at the same temperature, the same state of charge and the same pedal opening, the absolute error |Vst1-Vst2| between each group of reference voltage change rate and the current voltage change rate can be calculated. When the absolute error |Vst1-Vst2| is greater than a preset optimization condition, the ratio [Vst1 / Vst2] between the reference voltage change rate and the current voltage change rate is used as a power correction coefficient β=[Vst1 / Vst2], wherein the preset optimization condition may, for example, include an absolute error greater than a specified error threshold (the specified error threshold can be customized, for example, it can be 0mV / s, etc.), thereby obtaining the power correction coefficient corresponding to each group of rates, and then based on the power correction coefficient corresponding to each group of rates, the charging and discharging power corresponding to the temperature and state of charge of each group of rates in the current charging and discharging power table can be optimized to obtain an optimized target charging and discharging power table.

[0053] Among them, based on the power correction coefficient corresponding to each group of rates, optimizing the charge and discharge power at the temperature and charge state corresponding to each group of rates in the current charge and discharge power table can include: determining whether each group of rates corresponds to the acceleration working condition stage or the deceleration or downhill working condition stage based on whether the pedal opening corresponding to each group of rates is the accelerator pedal opening or the brake pedal opening. Assuming that a certain group of rates is determined to correspond to the acceleration working condition stage, then the group of rates is optimized for the current discharge power table. If the discharge power at the temperature and charge state corresponding to the group of rates in the current discharge power table is P0, then the target discharge power after correcting the discharge power P0 using the power correction coefficient can be P=P0*β, that is, the power correction coefficient can be multiplied by the charge and discharge power at the temperature and charge state corresponding to each group of rates in the current charge and discharge power table to obtain the target charge and discharge power at the temperature and charge state corresponding to each group of rates in the target charge and discharge power table, thereby obtaining the optimized target charge and discharge power table. It should be understood that if a set of reference voltage change rates and the current voltage change rate correspond to a deceleration or downhill operating stage, then the current charging power table is optimized. Similarly, the optimization method of P=P0*β can be used to optimize the charging power corresponding to the temperature and charge state in the current charging power table. This will not be elaborated here.

[0054] For example, assume that Table 1 is the current discharge power table used by the battery pack. If the temperature corresponding to the current voltage change rate in a certain rate group is T r1 , the state of charge is SOC0, and the corresponding power correction coefficient is determined to be β, then the power correction coefficient β can be compared with the temperature T in Table 1 r1 , discharge power SOP under state of charge SOC0 10 Multiplication is SOP 10*β, and then the discharge power SOP in Table 1 can be 10 Revised to SOP 10 *β, to obtain the optimized target discharge power table.

[0055] According to an embodiment of the present disclosure, by optimizing the current charge and discharge power meter based on the error between the reference voltage change rate and the current voltage change rate at the same temperature, the same state of charge and the same pedal opening, the optimized target charge and discharge power meter can be made more adapted to the actual charge and discharge capacity of the current battery pack, thereby helping to improve the driving experience of the entire vehicle and reduce the probability of failure.

[0056] It can be known that any battery pack is composed of multiple single cells connected in series. During the use of the battery pack, the performance of the single cells may vary greatly. The single cell voltage of some cells may drop first or rise to the danger zone first. In particular, as the battery pack gradually ages, the single cell voltage change rate during the use of the battery pack will also change accordingly. Therefore, in order to prevent any single cell voltage in the battery pack from suddenly dropping or rising, thereby causing damage to the battery pack, and at the same time optimizing the charge and discharge power meter using the voltage change rate, optionally, the voltage change rate may specifically include: the maximum single cell voltage change rate (i.e., the change rate of the maximum single cell voltage in the battery pack) and the minimum single cell voltage change rate (i.e., the change rate of the minimum single cell voltage in the battery pack), so as to optimize the current charge and discharge power meter based on the two dimensions of the maximum single cell voltage change rate and the minimum single cell voltage change rate. Specifically, in one possible implementation, the above step S122 optimizes the current charge and discharge power meter according to the error between the reference voltage change rate and the current voltage change rate to obtain the target charge and discharge power meter, which may include:

[0057] Step S1221, determining a first absolute error between a maximum cell voltage change rate in the reference voltage change rate and a maximum cell voltage change rate in the current voltage change rate, and determining a second absolute error between a minimum cell voltage change rate in the reference voltage change rate and a minimum cell voltage change rate in the current voltage change rate;

[0058] Step S1222, when the first absolute error and the second absolute error meet a preset optimization condition, determine a power correction coefficient according to the reference voltage change rate and the current voltage change rate;

[0059] Step S1223 , correcting the charge and discharge power at the temperature and state of charge corresponding to the current voltage change rate in the current charge and discharge power table using the power correction coefficient to obtain a target charge and discharge power table.

[0060] As described above, step S121 can be used to search for one or more groups of reference voltage change rates and current voltage change rates at the same temperature, the same state of charge, and the same pedal opening. For each group of rates, the charging and discharging power corresponding to the temperature and state of charge of each group of rates (that is, the current voltage change rate corresponding to the temperature and state of charge) can be optimized according to the optimization process of steps S1221 to S1223 to obtain an optimized target charging and discharging power table.

[0061] In step S1221, the maximum cell voltage change rate Vst among the reference voltage change rates is 0,mas The maximum single voltage change rate Vst in the current voltage change rate n,mas The first absolute error between can be expressed as X1 = |Vst 0,mas -Vst n,mas |, the minimum single voltage change rate Vst in the reference voltage change rate 0,min The minimum single voltage change rate Vst in the current voltage change rate n,min The second absolute error between can be expressed as X2 = |Vst 0,min -Vst n,min |.

[0062] In step S1222, the preset optimization condition may be, for example, that both the first absolute error and the second absolute error are greater than a specified error threshold. In this case, when the first absolute error and the second absolute error corresponding to a certain set of rates are greater than the specified error threshold, the power correction coefficient corresponding to the set of rates may be determined based on the ratio between the set of reference voltage change rates and the current voltage change rate. It should be understood that if any of the first absolute error and the second absolute error corresponding to a certain set of rates does not meet the preset optimization condition, the charge and discharge power at the temperature and state of charge corresponding to the set of rates may not be optimized. In this way, by ensuring that both the first absolute error and the second absolute error meet the preset optimization conditions before executing the optimization step, false triggering of the optimization of the current charge and discharge power table can be avoided as much as possible.

[0063] In step S1222, determining the power correction factor based on the reference voltage change rate and the current voltage change rate may include: determining a first ratio between the maximum cell voltage change rate in the reference voltage change rate and the maximum cell voltage change rate in the current voltage change rate; and determining a second ratio between the minimum cell voltage change rate in the reference voltage change rate and the minimum cell voltage change rate in the current voltage change rate; and determining the maximum value of the first ratio and the second ratio as the power correction factor. In this way, an accurate power correction factor can be effectively determined.

[0064] The first ratio between the maximum cell voltage change rate in the reference voltage change rate and the maximum cell voltage change rate in the current voltage change rate can be expressed as β1=[Vst 0,mas / Vst n,mas ], which can also be called the maximum cell voltage correction coefficient. The second ratio between the minimum cell voltage change rate in the reference voltage change rate and the minimum cell voltage change rate in the current voltage change rate can be expressed as β2=[Vst 0,min / Vst n,min ], also known as the minimum cell voltage correction factor. When the maximum cell voltage correction factor differs from the minimum cell voltage correction factor, the larger of the two correction factors can be selected as the power correction factor for the charge and discharge power at the current voltage change rate corresponding to the temperature and state of charge. It should be understood that for each set of reference voltage change rates and current voltage change rates, the power correction factor corresponding to each set of rates can be determined using the above method.

[0065] As described above, the current charge and discharge power table includes a current discharge power table used by the battery pack for power output and a current charge power table used by the battery pack for power recovery; the pedal opening includes an accelerator pedal opening or a brake pedal opening; in step S1223, the charge and discharge power corresponding to the temperature and state of charge of the current voltage change rate in the current charge and discharge power table is corrected by the power correction coefficient to obtain a target charge and discharge power table, which may include:

[0066] When the current voltage change rate corresponds to the accelerator pedal opening, the discharge power corresponding to the temperature and state of charge in the current voltage change rate in the current discharge power table is corrected by the power correction coefficient to obtain the target discharge power table;

[0067] When the current voltage change rate corresponds to the brake pedal opening, the charging power corresponding to the temperature and state of charge in the current charging power table is corrected by the power correction coefficient to obtain the target charging power table.

[0068] It is understood that if the current voltage change rate corresponds to the accelerator pedal opening, it means that the electric vehicle is in the acceleration phase at the time corresponding to the current voltage change rate, and the battery pack is performing power output (i.e., discharging). Therefore, in this case, the discharge power corresponding to the temperature and state of charge of the current voltage change rate in the current discharge power table can be corrected according to the power correction coefficient corresponding to the set of rates to obtain an optimized target discharge power table; if the current voltage change rate corresponds to the brake pedal opening, it means that the electric vehicle is in the deceleration or downhill phase at the time corresponding to the current voltage change rate, and the battery pack is performing power recovery (i.e., charging). Therefore, in this case, the charging power corresponding to the temperature and state of charge of the current voltage change rate in the current charging power table can be corrected according to the power correction coefficient corresponding to the set of rates to obtain an optimized target charging power table. It should be understood that for each set of reference voltage change rates and current voltage change rates that meet the preset optimization conditions, the discharge power in the current discharge power table or the charging power table in the current charging power table corresponding to each set of rates can be corrected in the above manner, and this is not limited in the embodiments of the present disclosure.

[0069] Among them, the process of correcting the charge and discharge power at the temperature and state of charge corresponding to the current voltage change rate in the current charge and discharge power table can specifically include: multiplying the power correction coefficient corresponding to the current voltage change rate in any group of rates determined by the charge and discharge power at the temperature and state of charge corresponding to the current voltage change rate in the group of rates in the current charge and discharge power table (that is, correcting the current charge and discharge power), and obtaining the target charge and discharge power at the temperature and state of charge in the target charge and discharge power table. For example, if the pedal opening corresponding to the current voltage change rate in a certain group of rates is the accelerator pedal opening, then the group of rates optimizes the current discharge power table. If the discharge power at the temperature and state of charge corresponding to the group of rates (that is, the current voltage change rate) in the current discharge power table is P0, then the target discharge power after correcting the discharge power P0 using the power correction coefficient can be P=P0*β. If the pedal opening corresponding to the current voltage change rate in a certain group of rates is the brake pedal opening, then the current discharge power table is optimized. The current charging power corresponding to the temperature and charge state of the current voltage change rate in the current charging power table can also be corrected by referring to the correction method of P=P0*β. That is, the charging power corresponding to the temperature and charge state of the current voltage change rate in the current charging power table is multiplied by the corresponding power correction coefficient, which will not be elaborated here.

[0070] According to the embodiment of the present disclosure, by using the maximum single cell voltage change rate and the minimum single cell voltage change rate to determine the power correction coefficient, and then correcting the charging and discharging power in the current charging and discharging power table that is not suitable for the actual performance of the current battery pack, it is possible to optimize the current charging and discharging power table more safely and reliably, which is beneficial to reducing the probability of battery pack failure and improving the service life of the battery pack.

[0071] Considering that the voltage change rate of the battery pack is different at different temperatures, different error thresholds can be set for different temperature ranges in the preset optimization conditions to further improve the accuracy of triggering the optimization logic. Therefore, in one possible implementation, in step S1222, the preset optimization conditions may include: when the temperature corresponding to the current voltage change rate is within the normal temperature range, the first absolute error and the second absolute error are both greater than the first error threshold; when the temperature corresponding to the current voltage change rate is within the abnormal temperature range, the first absolute error and the second absolute error are both greater than the second error threshold; wherein the second error threshold is greater than the first error threshold. In this way, the normal temperature range and the abnormal temperature range, as well as the first error threshold and the second error threshold, can be utilized to minimize false triggering of the optimization of the current charge and discharge power meter, thereby improving the optimization accuracy of the current charge and discharge power meter.

[0072] It should be understood that the temperature corresponding to the current voltage change rate is also the temperature corresponding to a set of the current voltage change rate and the reference voltage change rate. The normal temperature range can be understood as the temperature range when the battery pack operates at normal temperature, for example, the normal temperature range can include 0°C to 45°C. The abnormal temperature range can be understood as the temperature range when the battery pack operates at abnormal temperature, for example, the abnormal temperature range can include -30°C to 0°C and 45°C to 65°C.

[0073] The second error threshold corresponding to the abnormal temperature range is greater than the first error threshold corresponding to the normal temperature range, which can increase the fault tolerance of the optimization conditions when the battery pack is in the abnormal temperature range and minimize the false triggering of the optimized charge and discharge power meter. It should be understood that those skilled in the art can customize the first error threshold and the second error threshold according to actual needs, as long as the second error threshold is greater than the first error threshold. For example, the first error threshold can be 5mv / s and the second error threshold can be 10mv / s. When the temperature corresponding to the current voltage change rate is between 0°C and 45°C, the optimization of the current charge and discharge power meter is triggered when X1 and X2 are greater than 5mv / s (i.e., executing steps S1222 to S1223). When the temperature corresponding to the current voltage change rate is between -30°C and 0°C or between 45°C and 65°C, the optimization of the current charge and discharge power meter is triggered when X1 and X2 are greater than 10mv / s (i.e., executing steps S1222 to S1223).

[0074] As described above, the baseline driving data includes pedal opening data and battery pack status data from at least one historical driving process determined during the initial use phase of the battery pack in the electric vehicle. It should be understood that the user's driving habits and driving trajectories during different driving processes of the electric vehicle are different, so the pedal opening data and battery pack status data during different driving processes are likely to be different. However, the driving habits and driving trajectories during the same driving process are the same or similar, so the pedal opening data and battery pack status data during the same driving process are likely to be the same or similar. In this embodiment of the present disclosure, a target historical driving process having the same or similar driving trajectory as the current driving process can also be determined from at least one historical driving process, so that the baseline driving data corresponding to the target historical driving process can be used to optimize the current charge and discharge power table. This can further improve the optimization accuracy of the current charge and discharge power table and obtain a more accurate target charge and discharge power table that better matches the actual performance of the current battery pack.

[0075] Therefore, in one possible implementation, the current driving data further includes a current driving trajectory corresponding to the current driving process, and the reference driving data further includes a historical driving trajectory corresponding to at least one historical driving process. In the above step S12, the current charge and discharge power table is optimized based on the reference driving data and the current driving data of the electric vehicle to obtain a target charge and discharge power table, which may include:

[0076] Step S100 , obtaining a target historical driving trajectory that matches the current driving trajectory by comparing the current driving trajectory with the historical driving trajectories of various historical driving processes;

[0077] Step S200: Optimize the current charge and discharge power table based on the target benchmark driving data and the current driving data to obtain a target charge and discharge power table. The target benchmark driving data includes the pedal opening data and the battery pack status data during the historical driving process corresponding to the target historical driving trajectory.

[0078] In practical applications, electric vehicles are typically equipped with a positioning system, such as a GPS positioning system. This positioning system can be used to obtain the real-time spatial position (e.g., longitude and latitude) of the electric vehicle during travel, and thus the corresponding driving trajectory of the electric vehicle (i.e., the spatial position of the vehicle during travel). This allows the electric vehicle's driving trajectory (i.e., the spatial position of the electric vehicle during travel) to distinguish different driving processes. Optionally, the driving trajectory corresponding to a driving process can include at least the spatial position of the starting point and the spatial position of the end point, and can also include the spatial positions of multiple positioning points throughout the entire driving process, which is not limited in the embodiments of the present disclosure.

[0079] It should be understood that if the optimization method of the embodiment of the present disclosure is executed by the server, the positioning system in the electric vehicle can send the spatial position information (that is, the current driving trajectory) collected during the current driving process of the electric vehicle to the vehicle controller, and the vehicle controller sends the current driving trajectory to the server to execute the optimization method of the embodiment of the present disclosure in the server. Of course, the positioning system can also directly send the collected spatial position information (that is, the current driving trajectory) to the server, and this embodiment of the present disclosure is not limited to this. Alternatively, if the optimization method of the embodiment of the present disclosure is executed by the vehicle controller or BMS control, the positioning system can directly send the collected spatial position information (that is, the current driving trajectory) to the vehicle controller or BMS controller, and this embodiment of the present disclosure is not limited to this.

[0080] In step S100, the current driving trajectory is optionally compared with the historical driving trajectories of each historical driving process to obtain a target historical driving trajectory that matches the current driving trajectory. For example, this may include calculating the similarity between the current driving trajectory and each historical driving trajectory (equivalent to calculating the similarity between the spatial position in the current driving trajectory and the spatial position in each historical driving trajectory), and using the historical driving trajectory with a similarity exceeding a specified threshold (e.g., 90%) as the target historical driving trajectory that matches the current driving trajectory. A person skilled in the art may use a similarity algorithm known in the art, such as cosine similarity, Euclidean distance, or the like, to calculate the similarity between the current driving trajectory and each historical driving trajectory, and this is not limited in the present embodiment.

[0081] Taking into account that if the driving trajectories are the same, the starting and ending points must be the same, in order to improve the efficiency of driving trajectory comparison, in step S100, optionally, the target historical driving trajectory that matches the current driving trajectory can be obtained by directly judging whether the starting and ending points of the current driving trajectory are the same as the starting and ending points of each historical driving trajectory. That is, the historical driving trajectory with the same starting and ending points as the current driving trajectory can be used as the target historical driving trajectory that matches the current driving trajectory. This is not limited in the embodiments of the present disclosure.

[0082] Among them, the baseline driving data can also be understood as the data collected when the user drives the electric vehicle on a usual route (for example, from the company to home) in the initial use stage. If the target historical driving trajectory that matches the current driving trajectory is not determined through step S100, it means that the electric vehicle may currently be traveling on a new route. For example, the user may drive the electric vehicle for a self-driving tour, and the current driving data collected in this case is likely to be significantly different from the baseline driving data. Therefore, in this case, the current charge and discharge power meter may not be optimized based on the current driving data of the current driving process to avoid miscorrection of the current charge and discharge power meter, which is beneficial to improving the reliability of the charge and discharge power meter.

[0083] After obtaining the target historical driving trajectory that matches the current driving trajectory, in step S200, the target reference driving data and the current driving data can be used to optimize the current charge and discharge power table to obtain the target charge and discharge power table, referring to the implementation of steps S121 to S122 and steps S1221 to S1223 in the above-mentioned embodiments of the present disclosure. For example, the optimization process may include: comparing the battery pack temperature, state of charge, and pedal opening of the target reference driving data and the current driving data at each moment, determining the reference voltage change rate and the current voltage change rate at the same temperature, state of charge, and pedal opening from the target reference driving data and the current driving data; and optimizing the current charge and discharge power table based on the error between the reference voltage change rate and the current voltage change rate to obtain the target charge and discharge power table. The optimization process may refer to the implementation of steps S1221 to S1223 above, which will not be described in detail here.

[0084] According to an embodiment of the present disclosure, by determining a target historical driving trajectory that matches the current driving trajectory, and optimizing the current charge and discharge power meter based on the pedal opening data and battery pack status data of the historical driving process corresponding to the target historical driving trajectory, the optimization accuracy of the current charge and discharge power meter can be improved, and a target charge and discharge power meter that is more accurate and more suitable for the actual performance of the current battery pack can be obtained.

[0085] Based on the optimization method provided by the above embodiment of the present disclosure, Figure 2 A schematic diagram of a battery pack charge and discharge power meter optimization system according to an embodiment of the present disclosure is shown as follows: Figure 2 As shown, the system includes a server, a vehicle controller, a BMS, a battery pack, and an accelerator pedal and a brake pedal, wherein the optimization method provided in the embodiment of the present disclosure can be deployed on the server, and the opening size of the accelerator pedal or the brake pedal can be converted into a PWM signal and input into the vehicle controller. The vehicle controller adjusts the size of the vehicle power demand and requests the BMS to output or recover power. During driving, the vehicle controller and the BMS respectively upload the pedal opening data, battery pack status data and driving trajectory data (such as spatial position, driving speed, etc.) of the current driving process to the server. The server executes the optimization method provided in the embodiment of the present disclosure based on the pre-stored benchmark driving data and the received current driving data to obtain the target charge and discharge power table and return it to the BMS, so that the BMS controls the battery pack to output power or recover power based on the target charge and discharge power table.

[0086] In actual applications, in order to improve the communication efficiency between the server and the electric vehicle, after the server obtains the power correction coefficient of the charge and discharge power to be corrected in the current charge and discharge power table, the power correction coefficient can be returned to the BMS or the vehicle controller. In this way, the charge and discharge power to be corrected in the current charge and discharge power table can be corrected by the vehicle controller or the BMS controller based on the power correction coefficient returned by the server to obtain the target charge and discharge power table. That is, the correction step of the charge and discharge power in the current charge and discharge power table can be executed by the server, or by the BMS or the vehicle controller, and this is not limited in the embodiments of the present disclosure.

[0087] According to the system and method of the embodiments of the present disclosure, the pedal opening data and battery pack status data of different historical driving processes can be recorded by relying on the server, and the preset optimization conditions for triggering the current charge and discharge power meter can be found through fixed-time data optimization, and the current charge and discharge power meter can be optimized by determining the power correction coefficient after the preset optimization conditions are triggered. In this way, the charge and discharge power meter used by the battery pack can be continuously iterated and updated to make the current charge and discharge power meter used by the battery pack adapt to the actual performance of the current battery pack, thereby solving the problem of abuse of the battery pack after aging of the power performance, and controlling the battery pack for power output or power recovery through the target charge and discharge power meter that is more adapted to the actual performance of the current battery pack, which can effectively improve the driving experience of the entire vehicle and reduce the probability of failure.

[0088] Figure 3 A block diagram of a battery pack charge and discharge power meter optimization device according to an embodiment of the present disclosure is shown. The battery pack is applied to an electric vehicle, and the device includes:

[0089] An acquisition module 301 is configured to acquire current driving data of the electric vehicle, the current driving data including pedal opening data and battery pack status data during the current driving process of the electric vehicle; wherein the battery pack during the current driving process of the electric vehicle performs power output or power recovery according to a current charge and discharge power table;

[0090] The optimization module 302 is used to optimize the current charge and discharge power table based on the baseline driving data of the electric vehicle and the current driving data to obtain a target charge and discharge power table, so that the battery pack can output power or recover power according to the target charge and discharge power table; wherein the baseline driving data includes pedal opening data and battery pack status data in at least one historical driving process determined during the initial use stage of the battery pack in the electric vehicle.

[0091] In one possible implementation, the pedal opening data includes the pedal opening at each moment during driving; the battery pack status data includes the temperature, state of charge and voltage change rate of the battery pack at each moment during driving; wherein, the current charge and discharge power table is optimized according to the baseline driving data of the electric vehicle and the current driving data to obtain a target charge and discharge power table, including: by comparing the temperature, state of charge and pedal opening of the battery pack at each moment of the baseline driving data and the current driving data, the reference voltage change rate and the current voltage change rate at the same temperature, the same state of charge and the same pedal opening are determined from the baseline driving data and the current driving data; according to the error between the reference voltage change rate and the current voltage change rate, the current charge and discharge power table is optimized to obtain a target charge and discharge power table.

[0092] In one possible implementation, the voltage change rate includes: a maximum single-cell voltage change rate and a minimum single-cell voltage change rate; wherein, the current charge and discharge power table is optimized according to the error between the reference voltage change rate and the current voltage change rate to obtain a target charge and discharge power table, including: determining a first absolute error between the maximum single-cell voltage change rate in the reference voltage change rate and the maximum single-cell voltage change rate in the current voltage change rate, and determining a second absolute error between the minimum single-cell voltage change rate in the reference voltage change rate and the minimum single-cell voltage change rate in the current voltage change rate; when the first absolute error and the second absolute error meet preset optimization conditions, determining a power correction coefficient according to the reference voltage change rate and the current voltage change rate; and correcting the charge and discharge power corresponding to the temperature and charge state of the current voltage change rate in the current charge and discharge power table by using the power correction coefficient to obtain a target charge and discharge power table.

[0093] In one possible implementation, the preset optimization conditions include: when the temperature corresponding to the current voltage change rate is within a normal temperature range, the first absolute error and the second absolute error are both greater than a first error threshold; when the temperature corresponding to the current voltage change rate is within an abnormal temperature range, the first absolute error and the second absolute error are both greater than a second error threshold; wherein the second error threshold is greater than the first error threshold.

[0094] In one possible implementation, determining the power correction coefficient based on the reference voltage change rate and the current voltage change rate includes: determining a first ratio between the maximum single-cell voltage change rate in the reference voltage change rate and the maximum single-cell voltage change rate in the current voltage change rate, and determining a second ratio between the minimum single-cell voltage change rate in the reference voltage change rate and the minimum single-cell voltage change rate in the current voltage change rate; and determining the maximum value of the first ratio and the second ratio as the power correction coefficient.

[0095] In one possible implementation, the current charge and discharge power table includes a current discharge power table used by the battery pack for power output and a current charging power table used by the battery pack for power recovery; the pedal opening includes an accelerator pedal opening or a brake pedal opening; wherein, the current voltage change rate corresponding to the temperature and charge state in the current charge and discharge power table is corrected by the power correction coefficient to obtain a target charge and discharge power table, including: when the current voltage change rate corresponds to the accelerator pedal opening, the current voltage change rate corresponding to the temperature and charge state in the current discharge power table is corrected by the power correction coefficient to obtain a target discharge power table; when the current voltage change rate corresponds to the brake pedal opening, the current voltage change rate corresponding to the temperature and charge state in the current charging power table is corrected by the power correction coefficient to obtain a target charging power table.

[0096] In one possible implementation, the current driving data also includes a current driving trajectory corresponding to the current driving process, and the benchmark driving data also includes at least one historical driving trajectory corresponding to each historical driving process; wherein, the current charge and discharge power table is optimized based on the benchmark driving data of the electric vehicle and the current driving data to obtain a target charge and discharge power table, including: obtaining a target historical driving trajectory that matches the current driving trajectory by comparing the current driving trajectory with the historical driving trajectories of each historical driving process; optimizing the current charge and discharge power table based on the target benchmark driving data and the current driving data to obtain a target charge and discharge power table, the target benchmark driving data including the pedal opening data and battery pack status data in the historical driving process corresponding to the target historical driving trajectory.

[0097] According to the optimization device of the embodiment of the present disclosure, by utilizing the pedal opening data and battery pack status data during the historical driving process determined in the initial use stage of the battery pack in the electric vehicle (equivalent to the non-aging stage, the new car use stage), as well as the pedal opening data and battery pack status data during the current driving process, the current charge and discharge power meter currently used by the battery pack is optimized. The optimized target charge and discharge power meter can be made more adapted to the actual charge and discharge capacity of the current battery pack, so that when the battery pack outputs power or recovers power according to the target charge and discharge rate, the number of times the battery pack triggers faults such as undervoltage can be reduced, the battery pack life attenuation rate can be alleviated, and the estimation accuracy of the vehicle's mileage and battery power can be improved, which is conducive to improving the driving experience and reducing the probability of failure.

[0098] In some embodiments, the functions or modules included in the device provided by the embodiments of the present disclosure can be used to execute the method described in the above method embodiments. The specific implementation can refer to the description of the above method embodiments. For the sake of brevity, it will not be repeated here.

[0099] An embodiment of the present disclosure further provides an electronic device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above method.

[0100] An embodiment of the present disclosure further provides a non-volatile computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the above method when executed by a processor.

[0101] An embodiment of the present disclosure further provides a computer program product, including a computer program, or a non-volatile computer-readable storage medium carrying the computer program, wherein the computer program implements the steps of the above method when executed by a processor.

[0102] Figure 4 FIG1 shows a block diagram of an electronic device 1900 according to an embodiment of the present disclosure. For example, the electronic device 1900 can be provided as a server, a vehicle controller or a BMS controller. Figure 4 The electronic device 1900 includes a processing component 1922, which further includes one or more processors, and a memory resource represented by a memory 1932 for storing instructions executable by the processing component 1922, such as an application. The application stored in the memory 1932 may include one or more modules, each corresponding to a set of instructions. In addition, the processing component 1922 is configured to execute the instructions to perform the above-described method.

[0103] The electronic device 1900 may further include a power supply component 1926 configured to perform power management of the electronic device 1900, a wired or wireless network interface 1950 configured to connect the electronic device 1900 to a network, and an input / output interface 1958 (I / O interface). The electronic device 1900 may operate based on an operating system stored in the memory 1932, such as Windows Server 2003. TM , Mac OS X TM , Unix TM ,Linux TM , FreeBSD TM or similar.

[0104] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 1932 including computer program instructions that can be executed by the processing component 1922 of the electronic device 1900 to perform the above method.

[0105] A computer-readable storage medium can be a tangible device that can hold and store programs / instructions used by an instruction execution device. A computer-readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination thereof. As used herein, a computer-readable storage medium is not to be construed as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through an electrical wire.

[0106] The computer programs (or computer-readable program instructions) described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions to be stored in the computer-readable storage medium in each computing / processing device.

[0107] The computer program (or computer program instructions) for performing the operations of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages such as Smalltalk, C++, and conventional procedural programming languages such as "C" or similar programming languages. The computer readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, by utilizing state information of computer-readable program instructions to personalize and customize an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), the electronic circuit can execute the computer-readable program instructions to implement various aspects of the present disclosure.

[0108] Various aspects of the present disclosure are described herein with reference to flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present disclosure. It should be understood that each block of the flowcharts and / or block diagrams, and combinations of blocks in the flowcharts and / or block diagrams, can be implemented by computer-readable program instructions.

[0109] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processor of the computer or other programmable data processing device, a device is generated that implements the functions / actions specified in one or more blocks in the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium, where these instructions cause the computer, programmable data processing device, and / or other device to operate in a specific manner. Thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing various aspects of the functions / actions specified in one or more blocks in the flowchart and / or block diagram.

[0110] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operational steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more blocks in the flowchart and / or block diagram.

[0111] The flow charts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the systems, methods and computer program products according to multiple embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a part of a module, program segment or instruction, and the part of the module, program segment or instruction contains one or more executable instructions for realizing the prescribed logical function. In some alternative implementations, the functions marked in the box can also occur in a sequence different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the prescribed function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0112] While various embodiments of the present disclosure have been described above, the foregoing description is intended to be illustrative, non-exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is selected to best explain the principles of the embodiments, their practical applications, or technological improvements in the marketplace, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method for optimizing a battery pack charge and discharge power meter, wherein the battery pack is applied to an electric vehicle, characterized in that: The method comprises: Acquiring current driving data of the electric vehicle, the current driving data including pedal opening data and battery pack status data during the current driving process of the electric vehicle; wherein the battery pack during the current driving process of the electric vehicle outputs power or recovers power according to a current charge and discharge power table; Based on the baseline driving data and the current driving data of the electric vehicle, the current charge and discharge power table is optimized to obtain a target charge and discharge power table, so that the battery pack can output power or recover power according to the target charge and discharge power table; wherein, the baseline driving data includes pedal opening data and battery pack status data in at least one historical driving process determined during the initial use stage of the battery pack in the electric vehicle.

2. The method according to claim 1, characterized in that The pedal opening data includes the pedal opening at each moment during driving; the battery pack status data includes the temperature, state of charge, and voltage change rate of the battery pack at each moment during driving; The step of optimizing the current charge and discharge power table according to the benchmark driving data and the current driving data of the electric vehicle to obtain a target charge and discharge power table includes: By comparing the battery pack temperature, state of charge, and pedal opening at each moment of the reference driving data and the current driving data, a reference voltage change rate and a current voltage change rate at the same temperature, state of charge, and pedal opening are determined from the reference driving data and the current driving data; The current charge and discharge power table is optimized according to the error between the reference voltage change rate and the current voltage change rate to obtain a target charge and discharge power table.

3. The method according to claim 2, characterized in that The voltage change rate includes: a maximum cell voltage change rate and a minimum cell voltage change rate; wherein, optimizing the current charge and discharge power table according to the error between the reference voltage change rate and the current voltage change rate to obtain a target charge and discharge power table includes: Determine a first absolute error between a maximum cell voltage change rate in the reference voltage change rates and a maximum cell voltage change rate in the current voltage change rates, and determine a second absolute error between a minimum cell voltage change rate in the reference voltage change rates and a minimum cell voltage change rate in the current voltage change rates; When the first absolute error and the second absolute error meet a preset optimization condition, determining a power correction coefficient according to the reference voltage change rate and the current voltage change rate; The charge and discharge power at the temperature and state of charge corresponding to the current voltage change rate in the current charge and discharge power table is corrected by using the power correction coefficient to obtain a target charge and discharge power table.

4. The method according to claim 3, characterized in that The preset optimization conditions include: When the temperature corresponding to the current voltage change rate is within a normal temperature range, both the first absolute error and the second absolute error are greater than a first error threshold; When the temperature corresponding to the current voltage change rate is within an abnormal temperature range, both the first absolute error and the second absolute error are greater than a second error threshold; The second error threshold is greater than the first error threshold.

5. The method according to claim 3 or 4, characterized in that The determining of the power correction coefficient according to the reference voltage change rate and the current voltage change rate includes: Determine a first ratio between a maximum cell voltage change rate in the reference voltage change rates and a maximum cell voltage change rate in the current voltage change rates, and determine a second ratio between a minimum cell voltage change rate in the reference voltage change rates and a minimum cell voltage change rate in the current voltage change rates; The maximum value of the first ratio and the second ratio is determined as the power correction factor.

6. The method according to claim 3 or 4, characterized in that The current charge and discharge power table includes a current discharge power table used by the battery pack for power output and a current charge power table used by the battery pack for power recovery; the pedal opening includes an accelerator pedal opening or a brake pedal opening; The target charge and discharge power table is obtained by correcting the charge and discharge power corresponding to the temperature and state of charge of the current voltage change rate in the current charge and discharge power table using the power correction coefficient, including: When the current voltage change rate corresponds to the accelerator pedal opening, the discharge power corresponding to the temperature and state of charge in the current voltage change rate in the current discharge power table is corrected by the power correction coefficient to obtain a target discharge power table; When the current voltage change rate corresponds to the brake pedal opening, the charging power corresponding to the temperature and state of charge of the current voltage change rate in the current charging power table is corrected using the power correction coefficient to obtain a target charging power table.

7. The method according to any one of claims 1 to 4, characterized in that The current driving data also includes a current driving trajectory corresponding to the current driving process, and the reference driving data also includes at least one historical driving trajectory corresponding to each of the historical driving processes; The step of optimizing the current charge and discharge power table according to the benchmark driving data and the current driving data of the electric vehicle to obtain a target charge and discharge power table includes: By comparing the current driving trajectory with the historical driving trajectories of each historical driving process, a target historical driving trajectory that matches the current driving trajectory is obtained; The current charge and discharge power table is optimized according to the target benchmark driving data and the current driving data to obtain a target charge and discharge power table. The target benchmark driving data includes the pedal opening data and the battery pack status data during the historical driving process corresponding to the target historical driving trajectory.

8. A battery pack charge and discharge power meter optimization device, wherein the battery pack is used in an electric vehicle, characterized in that: The device comprises: an acquisition module, configured to acquire current driving data of the electric vehicle, the current driving data including pedal opening data and battery pack status data during the current driving process of the electric vehicle; wherein the battery pack during the current driving process of the electric vehicle outputs power or recovers power according to a current charge and discharge power table; An optimization module is used to optimize the current charge and discharge power table based on the baseline driving data of the electric vehicle and the current driving data to obtain a target charge and discharge power table, so that the battery pack can output power or recover power according to the target charge and discharge power table; wherein the baseline driving data includes pedal opening data and battery pack status data in at least one historical driving process determined during the initial use stage of the battery pack in the electric vehicle.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 7.

10. A non-volatile computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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