Battery health state correction method and device and electronic equipment

Abstract

The invention discloses a battery health state correction method and device and electronic equipment. The method comprises the following steps: for a current charging process of a current charging pile and an electric vehicle, determining a current ratio representing charging conversion efficiency between the electric vehicle and the current charging pile; based on the current ratio and a historical ratio of the electric vehicle to the current charging pile, an identification result corresponding to the current charge state of the electric vehicle is determined, and the historical ratio is obtained based on the charging conversion efficiency between the corresponding current charging pile and the electric vehicle; and under the condition that the identification result indicates to be accurate, the initial health state of the electric vehicle is corrected based on the uncertainty corresponding to the multiple charging piles having charging interaction with the electric vehicle and the historical ratio of the electric vehicle to the multiple charging piles, and the target health state of the electric vehicle is obtained. The technical problem that the accuracy of the estimation result of the battery health state of the electric vehicle is not ideal in the prior art is solved.

Description

Technical Field

[0001] The present application relates to the field of battery management technology, and more specifically, to a battery health status correction method, device and electronic device. Background Art

[0002] Electric vehicle battery health management is the cornerstone of safe and reliable operation of electric vehicles. Accurate estimation of battery status, especially battery health status estimation, is the premise and basis of electric vehicle battery management. In the early stages of battery degradation, the decline in battery capacity is often not obvious, but in the later stages, the battery capacity decline will be more severe, which will have a greater impact on the endurance and use of electric vehicles. Therefore, accurately estimating the health status of electric vehicle batteries is of great significance to extending the service life and operating distance of electric vehicles. In related technologies, the estimation of battery health status is mainly based on the operating characteristics of the battery pack itself. Since the battery status cannot be obtained through measurement, and battery degradation is a time-varying, dynamic, and strongly nonlinear process, the error in the battery health status estimation result is large, and there is a problem that the accuracy of the battery health status estimation result of electric vehicles is not ideal.

[0003] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0004] The embodiments of the present application provide a battery health status correction method, device and electronic device to at least solve the technical problem of unsatisfactory accuracy of electric vehicle battery health status estimation results existing in the related art.

[0005] According to one aspect of an embodiment of the present application, a battery health state correction method is provided, comprising: determining a current ratio representing the charging conversion efficiency between the electric vehicle and the current charging pile for a current charging process of the electric vehicle; determining an identification result corresponding to the current charge state of the electric vehicle based on the current ratio and a historical ratio between the electric vehicle and the current charging pile, wherein the historical ratio is obtained based on the charging conversion efficiency between the corresponding current charging pile and the electric vehicle; when the identification result indicates that it is accurate, based on the uncertainties corresponding to a plurality of charging piles that have charging interactions with the electric vehicle, and the historical ratios between the electric vehicle and the plurality of charging piles, the initial health state of the electric vehicle is corrected to obtain a target health state of the electric vehicle, wherein the plurality of charging piles include the current charging pile, and the uncertainty represents the degree of deviation in the electric energy metering of the corresponding charging pile.

[0006] Optionally, for the current charging process of the current charging pile and the electric vehicle, a current ratio representing the charging conversion efficiency between the electric vehicle and the current charging pile is determined, including: using the current charging pile to detect the current charging process and obtain an electric energy measurement value; determining the change in the state of charge of the electric vehicle during the current charging process; and determining the current ratio based on the electric energy measurement value and the change in the state of charge.

[0007] Optionally, based on the current ratio, and the historical ratio of the electric vehicle to the current charging pile, an identification result corresponding to the current state of charge of the electric vehicle is determined, including: determining the fluctuation amount between the current ratio and the historical ratio; when the fluctuation amount is greater than or equal to a predetermined fluctuation value, determining that the identification result is that the current state of charge is inaccurate; when the fluctuation amount is less than the predetermined fluctuation value, determining that the identification result is that the current state of charge is accurate.

[0008] Optionally, based on the uncertainties corresponding to multiple charging piles that have charging interactions with the electric vehicle, and the historical ratios between the electric vehicle and the multiple charging piles, the initial health state of the electric vehicle is corrected to obtain the target health state of the electric vehicle, including: based on the uncertainties corresponding to multiple charging piles that have charging interactions with the electric vehicle, and the historical ratios between the electric vehicle and the multiple charging piles, determining a first capacity characteristic parameter indicating that the electric vehicle is in an initial health state, and a second capacity characteristic parameter indicating that the electric vehicle is in a target health state; based on the ratio between the second capacity characteristic parameter and the first capacity characteristic parameter, correcting the initial health state to obtain the target health state.

[0009] Optionally, based on the uncertainties corresponding to multiple charging piles that have charging interactions with the electric vehicle, and the historical ratios of the electric vehicle to the multiple charging piles, a first capacity characteristic parameter indicating that the electric vehicle is in an initial healthy state, and a second capacity characteristic parameter indicating that the electric vehicle is in a current healthy state are determined, including: among multiple charging piles, determining multiple initial piles where the electric vehicle is in an initial healthy state; based on the uncertainties corresponding to the multiple initial piles, obtaining weight coefficients corresponding to the multiple initial piles; based on the weight coefficients and historical ratios corresponding to the multiple initial piles, determining the first capacity characteristic parameter; based on the uncertainties corresponding to the multiple charging piles, obtaining weight coefficients corresponding to the multiple charging piles; based on the weight coefficients and historical ratios corresponding to the multiple charging piles, determining the second capacity characteristic parameter.

[0010] Optionally, based on the uncertainties corresponding to multiple charging piles that have charging interactions with the electric vehicle, and the historical ratios of the electric vehicle with the multiple charging piles, the initial health state of the electric vehicle is corrected to obtain the target health state of the electric vehicle, including: based on the uncertainties corresponding to multiple charging piles that have charging interactions with the electric vehicle, and the historical ratios of the electric vehicle with the multiple charging piles, the initial health state of the electric vehicle is corrected to obtain an intermediate health state; obtaining historical behavior data of the electric vehicle, wherein the historical behavior data represents the behavioral laws of the charging and discharging depth of the electric vehicle; based on the historical behavior data, determining a first aging coefficient; based on the first aging coefficient, correcting the intermediate health state to obtain the target health state.

[0011] Optionally, based on the first aging coefficient, the intermediate health state is corrected to obtain the target health state, including: obtaining temperature change data of the area where the electric vehicle is located; determining the second aging coefficient based on the temperature change data; based on the first aging coefficient and the second aging coefficient, correcting the intermediate health state to obtain the target health state.

[0012] According to another aspect of an embodiment of the present application, a battery health state correction device is provided, including: a charging conversion efficiency determination module, for determining a current ratio representing the charging conversion efficiency between the electric vehicle and the current charging pile for the current charging process of the electric vehicle; an identification result determination module, for determining an identification result corresponding to the current charge state of the electric vehicle based on the current ratio and a historical ratio between the electric vehicle and the current charging pile, wherein the historical ratio is obtained based on the charging conversion efficiency between the corresponding current charging pile and the electric vehicle; a target health state determination module, for correcting the initial health state of the electric vehicle based on the uncertainties corresponding to a plurality of charging piles that have charging interactions with the electric vehicle and the historical ratios between the electric vehicle and the plurality of charging piles, when the identification result indicates that the identification result is accurate, to obtain a target health state of the electric vehicle, wherein the plurality of charging piles include the current charging pile, and the uncertainty represents the degree of deviation in the electric energy metering of the corresponding charging pile.

[0013] According to another aspect of an embodiment of the present application, a non-volatile storage medium is provided, wherein the non-volatile storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing any one of the battery health status correction methods.

[0014] According to another aspect of an embodiment of the present application, an electronic device is provided, comprising: one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by one or more processors, the one or more processors implement any one of the battery health status correction methods.

[0015] In the embodiment of the present application, the current ratio representing the charging conversion efficiency between the electric vehicle and the current charging pile is determined for the current charging process of the current charging pile and the electric vehicle; based on the current ratio and the historical ratio between the electric vehicle and the current charging pile, the identification result corresponding to the current state of charge of the electric vehicle is determined, wherein the historical ratio is obtained based on the charging conversion efficiency between the corresponding current charging pile and the electric vehicle; when the identification result indicates that it is accurate, based on the uncertainties corresponding to the multiple charging piles that have charging interactions with the electric vehicle, and the historical ratios between the electric vehicle and the multiple charging piles, the initial health state of the electric vehicle is corrected to obtain the target health state of the electric vehicle, wherein the multiple charging piles include the current charging pile, and the uncertainty represents the degree of deviation of the corresponding charging pile in the energy metering. The purpose of correcting the current health state of the electric vehicle by using the uncertainty of the charging pile and the initial health state of the electric vehicle is achieved, and the technical effect of improving the accuracy of the estimation result of the battery health state of the electric vehicle is achieved, thereby solving the technical problem of the unsatisfactory accuracy of the estimation result of the battery health state of the electric vehicle existing in the related art. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0017] Figure 1 is a flow chart of an optional battery health status correction method provided according to an embodiment of the present application;

[0018] Figure 2 It is a flowchart of an optional battery health status correction method provided according to an embodiment of the present application;

[0019] Figure 3 is a schematic diagram of an optional battery health status correction method provided according to an embodiment of the present application;

[0020] Figure 4 It is a schematic diagram of an optional battery health status correction device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0022] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0023] For the convenience of description, some nouns or terms involved in the embodiments of the present application are explained below:

[0024] SoC (State of Charge) refers to the ratio of the current remaining power of the battery to the power of the battery when it is fully charged.

[0025] SoH (State of Health) refers to the ratio of the current maximum capacity of the battery to the rated capacity of the battery. It reflects the aging degree and performance degradation of the battery and is an indicator to quantify the aging degree of the vehicle battery pack.

[0026] According to an embodiment of the present application, an embodiment of a method for correcting a battery health status is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0027] Figure 1 is a flow chart of a battery health status correction method according to an embodiment of the present application. Figure 1 As shown, the method comprises the following steps:

[0028] Step S102, determining a current ratio representing the charging conversion efficiency between the electric vehicle and the current charging pile for the current charging process of the electric vehicle;

[0029] It can be understood that during the current charging process of the electric vehicle, the current ratio of the charging conversion efficiency between the electric vehicle currently being charged and the charging pile is determined, and the above charging conversion efficiency reflects the conversion efficiency of the charging pile electric energy to the electric vehicle battery energy. By determining the charging conversion efficiency between the electric vehicle and the charging pile, the battery health status can be effectively detected, and a corresponding battery management strategy can be formulated according to the battery health status to optimize battery energy management and reduce the battery aging rate.

[0030] In an optional embodiment, for the current charging process of the current charging pile and the electric vehicle, a current ratio representing the charging conversion efficiency between the electric vehicle and the current charging pile is determined, including: using the current charging pile to detect the current charging process and obtain an electric energy measurement value; determining the change in the state of charge of the electric vehicle during the current charging process; and determining the current ratio based on the electric energy measurement value and the change in the state of charge.

[0031] It can be understood that during the current charging process of the electric vehicle, the charging process of the current charging pile is subjected to electric energy detection. The electric energy metering function of the current charging pile is used to accurately record the electric energy metering value charged into the electric vehicle battery. At the same time, the state of charge of the electric vehicle is recorded before and after charging, and the change in the state of charge is obtained based on the state of charge before and after charging. Based on the electric energy metering value of the above-mentioned charging pile and the change in the state of charge of the electric vehicle before and after charging, the current ratio of the charging conversion efficiency between the electric vehicle and the charging pile is obtained. By utilizing the electric energy metering function of the charging pile, the accuracy of the electric energy metering value used is ensured, thereby improving the accuracy of the battery charging conversion efficiency results, and providing data support for optimizing battery energy management.

[0032] Optionally, during the current charging process of the electric vehicle, the current electric energy metering value of the charging pile is recorded as E, and the change in the state of charge of the electric vehicle before and after charging is △SoC. Then, the current ratio k of the charging conversion efficiency between the electric vehicle and the charging pile during the i-th charging of the electric vehicle is i The formula is:

[0033]

[0034] Where i represents the i-th charge, E i Indicates the electric energy measurement value of the charging pile during the i-th charging, △SoC i It represents the change in the state of charge of the electric vehicle before and after charging during the i-th charging.

[0035] Step S104, determining an identification result corresponding to the current state of charge of the electric vehicle based on the current ratio and the historical ratio between the electric vehicle and the current charging pile, wherein the historical ratio is obtained based on the charging conversion efficiency between the corresponding current charging pile and the electric vehicle;

[0036] It can be understood that during the current charging process of the electric vehicle, the current ratio of the charging conversion efficiency between the electric vehicle currently being charged and the charging pile is determined. The current ratio of the charging conversion efficiency between the electric vehicle and the current charging pile is compared with the historical ratio of the charging conversion efficiency to obtain the recognition result of the current state of charge of the electric vehicle, that is, whether the estimation result of the battery state of charge of the current electric vehicle is accurate. The above-mentioned historical ratio of the charging conversion efficiency between the electric vehicle and the current charging pile is obtained according to the historical ratio of the charging conversion efficiency between the electric vehicle and the current charging pile during the historical charging process of the electric vehicle. By determining the change process of the charging conversion efficiency between the electric vehicle and the current charging pile, the charge state change trend of the electric vehicle battery can be effectively detected, and the change of the battery health state can be identified, thereby optimizing the battery charging strategy, reducing further damage to the battery, and extending the battery life.

[0037] In an optional embodiment, based on the current ratio and the historical ratio of the electric vehicle to the current charging pile, an identification result corresponding to the current state of charge of the electric vehicle is determined, including: determining the fluctuation amount between the current ratio and the historical ratio; when the fluctuation amount is greater than or equal to a predetermined fluctuation value, determining that the identification result is that the current state of charge is inaccurate; when the fluctuation amount is less than the predetermined fluctuation value, determining that the identification result is that the current state of charge is accurate.

[0038] It can be understood that the current ratio of the charging conversion efficiency between the electric vehicle and the current charging pile and the historical ratio of the charging conversion efficiency are compared and the difference is taken to obtain the fluctuation between the current ratio and the historical ratio. If the above fluctuation is greater than or equal to the predetermined fluctuation value, the recognition result of the current state of charge of the electric vehicle is inaccurate, that is, the estimation result of the battery state of charge of the current electric vehicle is inaccurate; if the above fluctuation is less than the predetermined fluctuation value, the recognition result of the current state of charge of the electric vehicle is accurate, that is, the estimation result of the battery state of charge of the current electric vehicle is accurate. By determining the fluctuation between the current ratio and the historical ratio of the electric vehicle, the change in the battery health state can be determined, and the battery charging strategy can be adjusted, such as optimizing the charging current, adjusting the charging termination conditions, etc., to reduce battery aging and improve charging efficiency.

[0039] Step S106, when the identification result indicates that it is accurate, based on the uncertainties corresponding to the multiple charging piles that have charging interactions with the electric vehicle, and the historical ratios of the electric vehicle with the multiple charging piles, the initial health state of the electric vehicle is corrected to obtain the target health state of the electric vehicle, wherein the multiple charging piles include the current charging pile, and the uncertainty represents the degree of deviation in the electric energy metering of the corresponding charging pile.

[0040] It can be understood that when the recognition result of the current state of charge of the electric vehicle is accurate, that is, when the estimation result of the battery state of charge of the electric vehicle is accurate, the initial health state of the electric vehicle is corrected according to the uncertainties corresponding to the multiple charging piles that have charging interactions with the electric vehicle, and the historical ratios corresponding to the multiple charging piles that have charging interactions with the electric vehicle, to obtain the target health state of the electric vehicle. The uncertainty of the above-mentioned charging pile refers to the measure of the measurement error that may be generated by the charging pile in the process of electric energy metering, which reflects the degree of deviation between the electric energy metering value and the true value of the charging pile. By introducing the uncertainty of the charging pile and correcting the health state of the electric vehicle battery, the accuracy of the battery health state estimation can be effectively improved, the battery utilization efficiency can be improved, and unnecessary energy waste can be reduced.

[0041] In an optional embodiment, based on the uncertainties corresponding to the multiple charging piles that have charging interactions with the electric vehicle, and the historical ratios of the electric vehicle with the multiple charging piles, the initial health state of the electric vehicle is corrected to obtain the target health state of the electric vehicle, including: based on the uncertainties corresponding to the multiple charging piles that have charging interactions with the electric vehicle, and the historical ratios of the electric vehicle with the multiple charging piles, determining a first capacity characteristic parameter indicating that the electric vehicle is in an initial health state, and a second capacity characteristic parameter indicating that the electric vehicle is in a target health state; based on the ratio between the second capacity characteristic parameter and the first capacity characteristic parameter, correcting the initial health state to obtain the target health state.

[0042] It can be understood that according to the uncertainties corresponding to the multiple charging piles that have charging interactions with the electric vehicle, and the historical ratios corresponding to the multiple charging piles that have charging interactions with the electric vehicle, the first capacity characteristic parameter of the battery when the electric vehicle is in the initial health state, and the second capacity characteristic parameter of the battery when the electric vehicle is in the target health state are determined. The above-mentioned capacity characteristic parameters are used to represent the relationship between the available capacity and the state of charge of the battery under different states of charge. Based on the ratio between the above-mentioned second capacity characteristic parameter and the first capacity characteristic parameter, the initial health state of the electric vehicle is corrected to obtain the target health state of the electric vehicle. Through the capacity characteristic parameters of the battery, the remaining capacity of the battery can be accurately predicted, which can assist in the fault diagnosis and prevention of the battery and improve the safety and service life of the battery.

[0043] In an optional embodiment, based on the uncertainties corresponding to a plurality of charging piles that have charging interactions with the electric vehicle, and the historical ratios of the electric vehicle to the plurality of charging piles, a first capacity characteristic parameter indicating that the electric vehicle is in an initial healthy state, and a second capacity characteristic parameter indicating that the electric vehicle is in a current healthy state are determined, including: determining a plurality of initial piles in which the electric vehicle is in an initial healthy state among a plurality of charging piles; obtaining weight coefficients corresponding to the plurality of initial piles based on the uncertainties corresponding to the plurality of initial piles; determining the first capacity characteristic parameter based on the weight coefficients and historical ratios corresponding to the plurality of initial piles; obtaining weight coefficients corresponding to the plurality of charging piles based on the uncertainties corresponding to the plurality of charging piles; determining the second capacity characteristic parameter based on the weight coefficients and historical ratios corresponding to the plurality of charging piles.

[0044] It can be understood that when the electric vehicle is in the initial health state, multiple charging piles with which there is charging interaction are taken as initial piles, and the uncertainties corresponding to the initial piles are determined. Based on the uncertainties corresponding to the multiple initial piles, the weight coefficients corresponding to the multiple initial piles are obtained. According to the weight coefficients and historical ratios corresponding to the above multiple initial piles, the first capacity characteristic parameter of the battery of the electric vehicle in the initial health state is obtained. Determine the uncertainties corresponding to the multiple charging piles with which there is charging interaction when the electric vehicle is in the target health state, and based on the above uncertainties, obtain the weight coefficients corresponding to the multiple charging piles with which there is charging interaction when the electric vehicle is in the target health state. Based on the weight coefficients and historical ratios corresponding to the above multiple charging piles, the second capacity characteristic parameter of the battery of the electric vehicle in the target health state is obtained. By collecting and analyzing the charging history data of the electric vehicle at multiple charging piles, combined with the uncertainty of the electric energy measurement of the charging piles, the health state of the battery can be estimated more accurately, reducing the estimation error caused by the data deviation of a single charging pile or the change of the working environment of the electric vehicle.

[0045] Optionally, based on the uncertainties u corresponding to the multiple initial piles, the weight coefficients corresponding to the multiple initial piles are obtained: According to the weight coefficients and historical ratios corresponding to the above-mentioned multiple initial piles, the first capacity characteristic parameter P0 of the battery of the electric vehicle in the initial healthy state is obtained. The formula of P0 is:

[0046]

[0047] Among them, u n It represents the uncertainty of the initial pile corresponding to the nth charging. Indicates the weight coefficient of the initial pile corresponding to the nth charging.

[0048] In an optional embodiment, based on the uncertainties corresponding to the multiple charging piles that have charging interactions with the electric vehicle, and the historical ratios of the electric vehicle with the multiple charging piles, the initial health state of the electric vehicle is corrected to obtain the target health state of the electric vehicle, including: based on the uncertainties corresponding to the multiple charging piles that have charging interactions with the electric vehicle, and the historical ratios of the electric vehicle with the multiple charging piles, the initial health state of the electric vehicle is corrected to obtain an intermediate health state; acquiring historical behavior data of the electric vehicle, wherein the historical behavior data represents the behavioral laws of the charging and discharging depth of the electric vehicle; determining a first aging coefficient based on the historical behavior data; and correcting the intermediate health state based on the first aging coefficient to obtain the target health state.

[0049] It can be understood that according to the uncertainties corresponding to the multiple charging piles that have charging interactions with the electric vehicle, and the historical ratios of the electric vehicle to the multiple charging piles, the initial health state of the electric vehicle is corrected to obtain the intermediate health state. The historical behavior data of the electric vehicle is obtained, and the first aging coefficient of the battery is determined based on the historical behavior data of the electric vehicle. The above-mentioned historical behavior data of the electric vehicle is the behavioral law representing the depth of charge and discharge of the electric vehicle, which can be used to analyze the impact of different charging states on battery life and understand the performance of the battery under different load conditions. Based on the first aging coefficient of the above-mentioned battery, the intermediate health state of the battery is corrected to obtain the target health state of the battery. By introducing the historical behavior data representing the depth of charge and discharge of the electric vehicle, the estimation error caused by differences in charging habits is reduced, making the evaluation of the health state of the electric vehicle battery more comprehensive and accurate, and providing strong technical support for the performance improvement and improvement of electric vehicles.

[0050] Optionally, based on the ratio between the second capacity characteristic parameter P1 and the first capacity characteristic parameter P0, the initial health state SoH0 is corrected to obtain the intermediate health state SoH'1, and the formula of SoH'1 is:

[0051]

[0052] In an optional embodiment, based on the first aging coefficient, the intermediate health state is corrected to obtain the target health state, including: obtaining temperature change data of the area where the electric vehicle is located; determining the second aging coefficient based on the temperature change data; based on the first aging coefficient and the second aging coefficient, correcting the intermediate health state to obtain the target health state.

[0053] It can be understood that after the intermediate health state of the electric vehicle battery is obtained based on the first aging coefficient, the intermediate health state of the electric vehicle battery is further corrected according to the environment in which the electric vehicle is located. The temperature change data of the environment in the area where the electric vehicle is located is obtained, and the second aging coefficient of the battery is obtained according to the above temperature change data. Based on the first aging coefficient and the second aging coefficient of the battery, the intermediate health state of the battery is corrected to obtain the target health state of the battery. Since the ambient temperature of the electric vehicle has an important influence on the health state of the battery, when correcting the health state of the electric vehicle, the influence of the ambient temperature on the health state of the battery is considered to reduce the adverse effects of temperature on the battery life, improve the accuracy of the estimation results of the health state of the electric vehicle battery, and enhance the overall performance and use efficiency of the electric vehicle.

[0054] Through the above step S102, for the current charging process of the current charging pile and the electric vehicle, the current ratio representing the charging conversion efficiency between the electric vehicle and the current charging pile is determined; step S104, based on the current ratio and the historical ratio of the electric vehicle to the current charging pile, the identification result corresponding to the current state of charge of the electric vehicle is determined, wherein the historical ratio is obtained based on the charging conversion efficiency between the corresponding current charging pile and the electric vehicle; step S106, when the identification result indicates that it is accurate, based on the uncertainties corresponding to the multiple charging piles that have charging interactions with the electric vehicle, and the historical ratios of the electric vehicle and the multiple charging piles, the initial health state of the electric vehicle is corrected to obtain the target health state of the electric vehicle, wherein the multiple charging piles include the current charging pile, and the uncertainty represents the degree of deviation of the corresponding charging pile in the energy metering. The purpose of correcting the current health state of the electric vehicle by using the uncertainty of the charging pile and the initial health state of the electric vehicle can be achieved, and the technical effect of improving the accuracy of the estimation result of the battery health state of the electric vehicle is achieved, thereby solving the technical problem of the unsatisfactory accuracy of the estimation result of the battery health state of the electric vehicle existing in the related art.

[0055] Based on the above embodiments and optional embodiments, the present application proposes an optional implementation method, which provides a method for detecting the measurement accuracy of a vehicle-mounted SoC (i.e., battery state of charge) / SoH (i.e., battery state of health), and a method for estimating SoC / SoH, which solves the practical problem that related technical estimation methods are difficult to meet the needs of electric vehicle users.

[0056] First, the accuracy of the on-board SoC / SoH measurement is detected based on the electric energy metering value of the charging pile, and the estimation of the on-board SoC / SoH is realized at the same time. The estimation method of the related technology is generally based on the characteristics of the on-board battery itself to establish a SoC / SoH estimation model, but due to the high nonlinearity of the on-board battery system, the accuracy of the estimation model is difficult to guarantee; secondly, based on the data-driven method, an artificial intelligence algorithm is used to predict SoC / SoH. This method is highly dependent on real data, and its generalization ability is affected by the algorithm itself, data dispersion, etc., and it is difficult to guarantee the accuracy of the prediction. Since the electric energy metering value of the charging pile is strongly correlated with the on-board SoC / SoH value, and the relationship is roughly linear, the SoC / SoH estimation method based on the electric energy metering of the charging pile can effectively make up for the shortcomings of the low prediction accuracy of the related technical estimation method and improve the accuracy of the detection data of the on-board BMS (Battery Management System).

[0057] Figure 2 is a flowchart of an optional battery health status correction method provided according to an embodiment of the present application, such as Figure 2 As shown, the battery health status correction method is divided into two steps: step S1: obtaining the electric energy-SoC characteristic curve of the vehicle battery in the initial state (that is, obtaining the first capacity characteristic parameter P0); step S2: detecting the SoC / SoH measurement accuracy and compensating for the change of the SoH value.

[0058] Step S1: obtaining an electric energy-SoC characteristic curve of the vehicle battery in the initial state;

[0059] Step S101: Select a charging pile and determine the uncertainty u of the electric energy measurement of the charging pile;

[0060] Step S102: Use the charging piles to charge the electric vehicle in turn, record the ratio of the electric energy metering value E of each charging pile to the change in the vehicle-mounted SoC value before and after charging (i.e., the charging conversion efficiency between the electric vehicle and the charging pile), then the current ratio k of the charging conversion efficiency between the electric vehicle and the charging pile when the electric vehicle is charged for the i-th time i The formula is:

[0061]

[0062] Where i represents the i-th charge, E i Indicates the electric energy measurement value of the charging pile during the i-th charging, △SoC i It represents the change in the state of charge of the electric vehicle before and after charging during the i-th charging.

[0063] Step S103: Using the reciprocal of the uncertainty of the charging pile's power measurement as the weight coefficient, calculate the power-SoC characteristic curve of the electric vehicle in its initial state, and its slope is P0. The formula for P0 is:

[0064]

[0065] where u n represents the uncertainty of the corresponding initial charging pile during the nth charging, and represents the weight coefficient of the corresponding initial charging pile during the nth charging.

[0066] Figure 3 is a schematic diagram of an optional method for correcting the state of health of the battery provided by an embodiment of the present application. As Figure 3 shown, when obtaining the power-SoC characteristic curve of the battery, its slope P0 is the first capacity characteristic parameter of the battery. The weight coefficient is the reciprocal of the uncertainty of the power measurement of the charging pile. Based on the charging conversion efficiency and the weight coefficient between the electric vehicle and the charging pile, the first capacity characteristic parameter P0 of the battery is determined, and then the power-SoC characteristic curve of the battery is obtained.

[0067] Step S2: Detect the accuracy of SoC / SoH measurement and compensate for changes in the SoH value.

[0068] Step S201: After the electric vehicle is put into use, record the interaction information with the charging pile during each charging process;

[0069] Step S202: During multiple charging processes of the electric vehicle at the same charging pile, if the ratio k i of the power measurement value of the charging pile to the change in SoC fluctuates, and the fluctuation amount is △k i , and △k i ≥u, that is, the fluctuation amount is greater than or equal to the predetermined fluctuation value (i.e., the uncertainty u of this charging pile), it indicates that the estimated value of the on-vehicle SoC is inaccurate;

[0070] Step S203: If in Step S202, the maximum change amount of k i does not exceed the uncertainty of the charging pile, that is, △k i <u, then use the interaction information during the charging process of the electric vehicle with multiple charging piles to obtain the power-SoC characteristic curve of the electric vehicle in its current state, and its slope is P1. When P1 < P0, it indicates that the capacity of the on-vehicle battery has changed, and the ratio of the current capacity to the initial capacity is P1 / P0;

[0071] Step S204: Correct the initial state of health SoH0 of the battery according to the first capacity characteristic parameter P0 and the second capacity characteristic parameter P1;

[0072] Optionally, based on the ratio between the second capacity characteristic parameter P1 and the first capacity characteristic parameter P0, the initial health state SoH0 is corrected to obtain the intermediate health state SoH'1, and the formula of SoH'1 is:

[0073]

[0074] Step S205: Correct the intermediate health state based on the intermediate health state SoH'1, the first aging coefficient and the second aging coefficient to obtain the target health state SoH1.

[0075] This completes the detection and estimation correction of the vehicle-mounted SoC / SoH measurement accuracy, provides a new technical solution for the detection of vehicle-mounted SoC / SoH, and improves the accuracy of the vehicle-mounted BMS system detection data.

[0076] The above optional implementation manner achieves at least the following effects: by introducing uncertainty information of the charging pile, the accuracy of the battery capacity characteristic parameters of the electric vehicle is improved, thereby improving the accuracy of the battery health status correction result; by introducing a first battery aging coefficient based on the historical behavior data of the electric vehicle, and a second battery aging coefficient based on the temperature change data, the influence of human factors and environmental factors on the battery health status correction result is reduced, thereby further improving the accuracy of the battery health status correction result.

[0077] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0078] In this embodiment, a battery health status correction device is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the terms "module" and "device" can implement a combination of software and / or hardware for a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0079] According to an embodiment of the present application, a device embodiment for implementing a battery health status correction method is also provided. Figure 4 is a schematic diagram of a battery health status correction device according to an embodiment of the present application, such as Figure 4 As shown, the battery health state correction device includes a charging conversion efficiency determination module 402, an identification result determination module 404, and a target health state determination module 406. The device is described below.

[0080] A charging conversion efficiency determination module 402, a charging conversion efficiency determination module, for determining a current ratio representing the charging conversion efficiency between the electric vehicle and the current charging pile for the current charging process of the electric vehicle;

[0081] The identification result determination 404 is connected to the charging conversion efficiency determination module 402, and is used for the identification result determination module to determine the identification result corresponding to the current state of charge of the electric vehicle based on the current ratio and the historical ratio between the electric vehicle and the current charging pile, wherein the historical ratio is obtained based on the charging conversion efficiency between the corresponding current charging pile and the electric vehicle;

[0082] The target health status determination module 406 is connected to the identification result determination 404 and is used for the target health status determination module. When the identification result indicates that it is accurate, the initial health status of the electric vehicle is corrected based on the uncertainties corresponding to the multiple charging piles that have charging interactions with the electric vehicle and the historical ratios of the electric vehicle with the multiple charging piles to obtain the target health status of the electric vehicle, wherein the multiple charging piles include the current charging pile, and the uncertainty represents the degree of deviation in the electric energy metering of the corresponding charging pile.

[0083] In a battery health state correction device provided by an embodiment of the present application, a charging conversion efficiency determination module 402 is set, and the charging conversion efficiency determination module is used to determine the current ratio of the charging conversion efficiency between the electric vehicle and the current charging pile for the current charging process of the current charging pile and the electric vehicle; the recognition result determination 404 is connected to the charging conversion efficiency determination module 402, and is used for the recognition result determination module, which is used to determine the recognition result corresponding to the current charge state of the electric vehicle based on the current ratio and the historical ratio of the electric vehicle to the current charging pile, wherein the historical ratio is obtained based on the charging conversion efficiency between the corresponding current charging pile and the electric vehicle; the target health state determination module 406 is connected to the recognition result determination 404, and is used for the target health state determination module, which is used to correct the initial health state of the electric vehicle based on the uncertainties corresponding to the multiple charging piles that have charging interactions with the electric vehicle, and the historical ratios of the electric vehicle and the multiple charging piles respectively, when the recognition result indicates that it is accurate, to obtain the target health state of the electric vehicle, wherein the multiple charging piles include the current charging pile, and the uncertainty represents the degree of deviation in the electric energy metering of the corresponding charging pile. The purpose of using the uncertainty of the charging pile and the initial health state of the electric vehicle to correct the current health state of the electric vehicle is achieved, and the technical effect of improving the accuracy of the estimation results of the health state of the electric vehicle battery is achieved, thereby solving the technical problem of unsatisfactory accuracy of the estimation results of the health state of the electric vehicle battery existing in the related technology.

[0084] It should be noted that the above modules can be implemented by software or hardware. For example, for the latter, it can be implemented in the following ways: the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0085] It should be noted that the charging conversion efficiency determination module 402, the identification result determination 404, and the target health state determination module 406 correspond to steps S102 to S106 in the embodiment, and the examples and application scenarios implemented by the modules and the corresponding steps are the same, but are not limited to the contents disclosed in the above embodiments. It should be noted that the modules as part of the device can be run in a computer terminal.

[0086] It should be noted that the optional or preferred implementation of this embodiment can refer to the relevant description in the embodiment, which will not be repeated here.

[0087] The above-mentioned battery health status correction device may also include a processor and a memory. The charging conversion efficiency determination module 402, the identification result determination 404, the target health status determination module 406, etc. are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize the corresponding functions.

[0088] The processor includes a kernel, which retrieves the corresponding program unit from the memory. There can be one or more kernels. The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one storage chip.

[0089] An embodiment of the present application provides a non-volatile storage medium on which a program is stored. When the program is executed by a processor, a method for correcting the battery health status is implemented.

[0090] The embodiment of the present application provides an electronic device, which includes a processor, a memory, and a program stored in the memory and can be run on the processor. When the processor executes the program, the following steps are implemented: for the current charging process of the current charging pile and the electric vehicle, determine the current ratio representing the charging conversion efficiency between the electric vehicle and the current charging pile; based on the current ratio and the historical ratio of the electric vehicle to the current charging pile, determine the identification result corresponding to the current state of charge of the electric vehicle, wherein the historical ratio is obtained based on the charging conversion efficiency between the corresponding current charging pile and the electric vehicle; when the identification result indicates that it is accurate, based on the uncertainties corresponding to the multiple charging piles that have charging interactions with the electric vehicle, and the historical ratios of the electric vehicle and the multiple charging piles, respectively, correct the initial health state of the electric vehicle to obtain the target health state of the electric vehicle, wherein the multiple charging piles include the current charging pile, and the uncertainty represents the degree of deviation of the corresponding charging pile in the electric energy metering. The device in this article can be a server, a PC, etc.

[0091] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program that is initialized with the following method steps: determining a current ratio representing the charging conversion efficiency between the electric vehicle and the current charging pile for the current charging process of the electric vehicle; determining an identification result corresponding to the current charge state of the electric vehicle based on the current ratio and the historical ratio of the electric vehicle to the current charging pile, wherein the historical ratio is obtained based on the charging conversion efficiency between the corresponding current charging pile and the electric vehicle; when the identification result indicates that it is accurate, based on the uncertainties corresponding to the multiple charging piles that have charging interactions with the electric vehicle, and the historical ratios of the electric vehicle to the multiple charging piles, the initial health state of the electric vehicle is corrected to obtain the target health state of the electric vehicle, wherein the multiple charging piles include the current charging pile, and the uncertainty represents the degree of deviation in the electric energy metering of the corresponding charging pile.

[0092] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0093] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0094] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0095] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0096] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0097] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0098] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0099] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0100] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0101] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A battery health status correction method, characterized in that: include: For a current charging process of a current charging pile and an electric vehicle, determining a current ratio representing a charging conversion efficiency between the electric vehicle and the current charging pile; Determine an identification result corresponding to a current state of charge of the electric vehicle based on the current ratio and a historical ratio between the electric vehicle and the current charging pile, wherein the historical ratio is obtained based on a charging conversion efficiency between the corresponding current charging pile and the electric vehicle; When the identification result indicates that it is accurate, based on the uncertainties corresponding to the multiple charging piles that have charging interactions with the electric vehicle and the historical ratios of the electric vehicle with the multiple charging piles, the initial health state of the electric vehicle is corrected to obtain the target health state of the electric vehicle, wherein the multiple charging piles include the current charging pile, and the uncertainty represents the degree of deviation in the electric energy metering of the corresponding charging piles.

2. The method according to claim 1, characterized in that: The determining of a current ratio representing a charging conversion efficiency between the electric vehicle and the current charging pile for the current charging process of the electric vehicle includes: Using the current charging pile, the current charging process is tested for electric energy to obtain an electric energy measurement value; Determining a change in the state of charge of the electric vehicle during a current charging process; The current ratio is determined based on the electric energy measurement value and the charge state change.

3. The method according to claim 1, characterized in that The determining, based on the current ratio and the historical ratio between the electric vehicle and the current charging pile, an identification result corresponding to the current state of charge of the electric vehicle includes: determining an amount of fluctuation between the current ratio and the historical ratio; In a case where the fluctuation amount is greater than or equal to a predetermined fluctuation value, determining that the identification result is that the current state of charge is inaccurate; In a case where the fluctuation amount is less than the predetermined fluctuation value, it is determined that the identification result is that the current state of charge is accurate.

4. The method according to claim 1, characterized in that: The method corrects the initial health state of the electric vehicle based on the uncertainties corresponding to the multiple charging piles that have charging interactions with the electric vehicle, and the historical ratios of the electric vehicle to the multiple charging piles, to obtain the target health state of the electric vehicle, including: Based on the uncertainties corresponding to the multiple charging piles that have charging interactions with the electric vehicle, and the historical ratios of the electric vehicle to the multiple charging piles, determine a first capacity characteristic parameter indicating that the electric vehicle is in the initial health state, and a second capacity characteristic parameter indicating that the electric vehicle is in the target health state; Based on the ratio between the second capacity characteristic parameter and the first capacity characteristic parameter, the initial health state is corrected to obtain the target health state.

5. The method according to claim 4, characterized in that The method of determining the first capacity characteristic parameter indicating that the electric vehicle is in the initial health state and the second capacity characteristic parameter indicating that the electric vehicle is in the current health state based on the uncertainties corresponding to the multiple charging piles that have charging interactions with the electric vehicle and the historical ratios of the electric vehicle to the multiple charging piles, includes: Among the plurality of charging piles, determining a plurality of initial piles at which the electric vehicle is in the initial healthy state; Based on the uncertainties respectively corresponding to the multiple initial piles, obtaining weight coefficients respectively corresponding to the multiple initial piles; Determining the first capacity characteristic parameter based on the weight coefficients and historical ratios respectively corresponding to the multiple initial piles; Based on the uncertainties respectively corresponding to the plurality of charging piles, obtaining weight coefficients respectively corresponding to the plurality of charging piles; The second capacitive parameter is determined based on the weight coefficients and historical ratios respectively corresponding to the multiple charging piles.

6. The method according to any one of claims 1 to 5, characterized in that: The method corrects the initial health state of the electric vehicle based on the uncertainties corresponding to the multiple charging piles that have charging interactions with the electric vehicle, and the historical ratios of the electric vehicle to the multiple charging piles, to obtain the target health state of the electric vehicle, including: Based on the uncertainties corresponding to the multiple charging piles that have charging interactions with the electric vehicle, and the historical ratios of the electric vehicle to the multiple charging piles, the initial health state of the electric vehicle is corrected to obtain an intermediate health state; Acquiring historical behavior data of the electric vehicle, wherein the historical behavior data represents behavior patterns of charge and discharge depth of the electric vehicle; Based on the historical behavior data, determining a first aging coefficient; Based on the first aging coefficient, the intermediate health state is corrected to obtain the target health state.

7. The method according to claim 6, characterized in that The correcting the intermediate health state based on the first aging coefficient to obtain the target health state includes: Acquiring temperature change data of the area where the electric vehicle is located; determining a second aging coefficient based on the temperature change data; The intermediate health state is corrected based on the first aging coefficient and the second aging coefficient to obtain the target health state.

8. A battery health status correction device, characterized in that: include: A charging conversion efficiency determination module, for determining a current ratio representing the charging conversion efficiency between the electric vehicle and the current charging pile for the current charging process of the electric vehicle; an identification result determination module, configured to determine an identification result corresponding to a current state of charge of the electric vehicle based on the current ratio and a historical ratio between the electric vehicle and the current charging pile, wherein the historical ratio is obtained based on a charging conversion efficiency between the corresponding current charging pile and the electric vehicle; A target health status determination module is used to correct the initial health status of the electric vehicle based on the uncertainties corresponding to the multiple charging piles that have charging interactions with the electric vehicle and the historical ratios of the electric vehicle to the multiple charging piles, so as to obtain the target health status of the electric vehicle when the identification result indicates that it is accurate, wherein the multiple charging piles include the current charging pile, and the uncertainty represents the degree of deviation in the electric energy metering of the corresponding charging piles.

9. A non-volatile storage medium, characterized in that: The non-volatile storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the battery health status correction method described in any one of claims 1 to 7.

10. An electronic device, characterized in that: include: One or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the battery health status correction method described in any one of claims 1 to 7.

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