Battery health status prediction method, battery management system and new energy vehicle

Abstract

The present invention discloses a battery state of health prediction method, comprising: testing the calendar life capacity decay rates of multiple sample batteries at multiple preset temperatures and multiple preset SOC ranges, and establishing a capacity decay rate-time database; obtaining a first time count matrix for the tested battery in an operating state and a second time count matrix for the tested battery in a dormant state; converting a first time matrix and a second time matrix based on the first time count matrix and a first time step, and a second time count matrix and a second time step, respectively, and adding the times corresponding to the two time matrices to obtain a total time matrix; searching the capacity decay rate corresponding to each time in the total time matrix from the capacity decay rate-time database to obtain a capacity decay rate matrix; and calculating a state of health matrix for the tested battery based on the capacity decay rate matrix. The present invention can improve the accuracy of battery state of health prediction. The present invention also provides a battery management system and a new energy vehicle.

Description

Technical Field

[0001] The present invention relates to the technical field of power batteries, and in particular to a battery health status prediction method, a battery management system and a new energy vehicle. Background Art

[0002] The lifespan of power batteries is a key issue for new energy vehicles. It's generally accepted in the power battery field that batteries can no longer be used in electric vehicles when their capacity drops to 80% of their rated capacity. The internal characteristics of individual cells, the power source assembly method, and the performance requirements of the vehicle are all closely linked to the battery's lifespan. A battery's calendar life refers to the lifespan from the date of manufacture to its expiration date, including the effects of operating conditions, temperature, cycling, storage, aging, and other factors. The end of life of a single battery in a system often impacts the operation of the entire system, causing overall system failure. Accurately predicting the battery's state of health (SOH), which can be understood as the percentage of a battery's current capacity compared to its factory capacity, is crucial not only for current battery usage but also for the recycling and reuse of used batteries. Therefore, accurate estimation of battery SOH and research on calendar life can further guide battery operation, provide data support for the development of battery health management systems, and are crucial for extending the service life of power batteries.

[0003] In the relevant existing technologies, the technical solutions for battery estimation mainly include: establishing a capacity decay rate-time database under different temperatures and different SOCs; calculating the temperature range of actual battery application and the distribution ratio at different temperatures and the proportion of different SOCs; converting the calendar life time according to the battery's factory time, calculating the calendar life time and the distribution ratio of each temperature to obtain the time occupied at each temperature, and then obtaining the time occupied at each temperature and each SOC according to the distribution ratio of each SOC, and finally obtaining the corresponding decay rate according to each time, and performing cumulative evaluation.

[0004] However, in actual applications, batteries have different calendar lives at different temperatures and SOCs. The aforementioned technical solution estimates the capacity decay rate at various temperatures and SOCs based on the battery's factory date and calendar life. This approach fails to analyze the battery's multiple states and continuous operating data throughout its lifecycle, resulting in low accuracy and reliability in lifespan prediction. Summary of the Invention

[0005] The present invention aims to address the problem that existing battery health status prediction methods are unable to monitor batteries in multiple states throughout their lifecycle. This invention provides a battery health status prediction method, a battery management system, and a new energy vehicle that can analyze the actual operating time of a battery in different states and dynamically monitor the battery's entire lifecycle, thereby improving the accuracy of battery health status prediction and the reliability of the prediction results.

[0006] To solve the above technical problems, an embodiment of the present invention discloses a battery health status prediction method, comprising:

[0007] (1) Test the capacity decay rate of multiple sample batteries at multiple preset temperatures and multiple preset SOC ranges during their calendar life, and establish a capacity decay rate-time database;

[0008] (2) obtaining a first time count matrix of the battery under test in an operating state and a second time count matrix of the battery under test in a dormant state, wherein the first time count matrix is ​​used to record the number of times the battery under test experiences a first time step in a plurality of preset temperature intervals and a plurality of preset SOC intervals in the operating state, and the second time count matrix is ​​used to record the number of times the battery under test experiences a second time step in a plurality of preset temperature intervals and a plurality of SOC intervals in the dormant state;

[0009] (3) converting a first time matrix based on the first time count matrix and the first time step, converting a second time matrix based on the second time count matrix and the second time step, adding each time in the first time matrix to each time at the corresponding position in the second time matrix to obtain a total time matrix for the battery to be tested;

[0010] (4) According to the capacity decay rate-time database, the capacity decay rate corresponding to each time element in the total time matrix is ​​searched to obtain the capacity decay rate matrix of the battery to be tested;

[0011] (5) The health status matrix of the battery to be tested is calculated based on the capacity decay rate matrix.

[0012] Using the above technical solution, the calendar life capacity decay of sample batteries at different temperatures and SOC ranges is tested and acquired, and a capacity decay rate-time database is established. The time at different temperatures and SOC ranges is dynamically recorded for the test battery in both the operating and dormant states, and the decay rate corresponding to the time is searched in the capacity decay rate-time database to obtain the health status of the test battery. The battery health status prediction method, battery management system, and storage medium of the present invention analyze the actual operating time of the battery under different states and dynamically monitor the battery's entire life cycle, improving the accuracy and reliability of battery health status prediction and providing data support for subsequent battery production, storage, and use.

[0013] According to another specific embodiment of the present invention, the embodiment of the present invention discloses that step (2) further includes:

[0014] When the battery to be tested is in a running state, each time the battery to be tested experiences a first time step, an update and storage of the first time counting matrix is ​​triggered;

[0015] When the battery to be tested is in a dormant state, each time the battery to be tested experiences a second time step, the updating and storage of the second time counting matrix is ​​triggered.

[0016] According to another specific embodiment of the present invention, the embodiment of the present invention discloses that the multiple preset temperature intervals include a first preset temperature interval and a second preset temperature interval, the multiple preset SOC intervals include the first preset SOC interval, the first condition includes the first preset temperature interval and the first preset SOC interval, and the second condition includes the second preset temperature interval and the first preset SOC interval; wherein, in step (2), the specific method of obtaining the first time count matrix of the battery to be tested in the operating state and the second time count matrix of the battery to be tested in the dormant state is:

[0017] When the battery to be tested experiences a complete first time step or a complete second time step under the first condition, the elements corresponding to the first condition in the first time count matrix or the elements corresponding to the first condition in the second time count matrix are updated and stored; or when the battery to be tested experiences a complete first time step or a complete second time step under the second condition, the elements corresponding to the second condition in the first time count matrix or the elements corresponding to the second condition in the second time count matrix are updated and stored;

[0018] When the battery to be tested is under the first condition but has not experienced the complete first time step or the second time step and changes to the second condition, the time the current battery to be tested has experienced under the first condition is temporarily stored, and the time the battery to be tested has experienced under the second condition is continuously monitored. When the battery to be tested changes to the first condition, the time is continued to be recorded based on the temporarily stored time.

[0019] According to another specific embodiment of the present invention, the embodiment of the present invention discloses that in step (3), the first time matrix is ​​converted according to the first time count matrix and the first time step, and the second time matrix is ​​converted according to the second time count matrix and the second time step. The specific method is:

[0020] Multiplying each time count in the first time count matrix by the first time step to obtain a first time matrix;

[0021] Each time count in the second time count matrix is ​​multiplied by the second time step to obtain a second time matrix.

[0022] According to another specific embodiment of the present invention, the embodiment of the present invention discloses that in step (5), the specific method for calculating the health state matrix of the battery to be tested corresponding to the capacity decay rate matrix is:

[0023] By subtracting the integer 1 from each capacity decay rate, the health status of the battery to be tested in multiple preset temperature intervals and multiple preset SOC intervals is obtained to obtain a health matrix of the battery to be tested corresponding to the capacity decay rate.

[0024] According to another specific embodiment of the present invention, the embodiment of the present invention discloses that the battery health status prediction method also includes: multiplying the health status of the battery to be tested under multiple preset temperature intervals and multiple preset SOC intervals to obtain the health status of the battery to be tested during the monitoring period.

[0025] According to another specific embodiment of the present invention, the embodiment of the present invention discloses that in step (2), the first time step is set to 20 minutes and the second time step is set to 8 hours.

[0026] An embodiment of the present invention further discloses a battery management system, including a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to implement the steps of the battery health champion prediction method mentioned in any of the above embodiments.

[0027] According to another specific embodiment of the present invention, an embodiment of the present invention discloses that the battery management system also includes a counter and a timer, and the timer is used to record the time spent by the battery to be tested in a working state or a sleep state. When the time recorded by the timer reaches a first time step or a second time step, the number of times recorded in the corresponding counter is triggered to increase by one.

[0028] An embodiment of the present invention further discloses a new energy vehicle, comprising the battery management system mentioned in any of the above embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 A schematic diagram showing the overall process of a battery health status prediction method provided by a specific embodiment of the present invention is shown;

[0030] Figure 2 A block diagram of a battery management system according to a specific embodiment of the present invention is shown;

[0031] Figure 3 A block diagram of a new energy vehicle provided by a specific embodiment of the present invention is shown. DETAILED DESCRIPTION

[0032] The following is an explanation of the embodiments of the present invention by specific specific examples. Those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. Although the description of the present invention will be introduced in conjunction with the preferred embodiment, this does not mean that the features of this invention are limited to this embodiment. On the contrary, the purpose of introducing the invention in conjunction with the embodiment is to cover other options or modifications that may be extended based on the claims of the present invention. In order to provide a deep understanding of the present invention, the following description will contain many specific details. The present invention can also be implemented without using these details. In addition, in order to avoid confusion or blurring the focus of the present invention, some specific details will be omitted in the description. It should be noted that the embodiments of the present invention and the features in the embodiments can be combined with each other without conflict.

[0033] It should be noted that in this specification, similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0034] In the description of this embodiment, it should be noted that the terms "upper", "lower", "inner", "bottom", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, or are the orientations or positional relationships in which the inventive product is usually placed when in use. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, they cannot be understood as limitations on the present invention.

[0035] The terms “first”, “second”, etc. are only used for distinguishing descriptions and should not be understood as indicating or implying relative importance.

[0036] In the description of this embodiment, it should be noted that, unless otherwise specified or limited, the terms "disposed," "connected," and "connected" should be understood broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal connections between two components. Those skilled in the art will understand the specific meanings of the above terms in this embodiment based on specific circumstances.

[0037] To make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0038] See also Figure 1 , Figure 1 The figure shows an overall flow chart of a method for predicting the state of health of a battery provided by an embodiment of the present invention.

[0039] like Figure 1 As shown, an embodiment of the present invention provides a battery health status prediction method, the method comprising:

[0040] Step 101: respectively testing the capacity decay rates of a plurality of sample batteries over their calendar life at a plurality of preset temperatures and a plurality of preset SOC ranges, and establishing a capacity decay rate-time database.

[0041] Among them, SOC (State of Charge) is the ratio of the current remaining power of the battery to its capacity in a fully charged state, usually expressed as a percentage. For example, when SOC = 0, it means that the battery is fully discharged, and when SOC = 100%, it means that the battery is fully charged. It is understandable that the capacity decay rate corresponding to the battery under different environmental conditions is different, and accordingly, the calendar life is also different. The environmental conditions of this embodiment take the SOC range and temperature as examples. In order to accurately predict the calendar life of the battery, the embodiment pre-acquires the capacity decay rate-time database of the sample battery at different temperatures and different SOC ranges.

[0042] Specifically, the operator conducts calendar aging test on the sample battery in accordance with the "Lithium-ion Power Battery Single Calendar Life Test Method", and tests the sample battery in multiple preset temperature ranges (for example, T≤0℃, 0℃<T≤15℃, 15℃<T≤45℃、T> The capacity fade rate over calendar life is calculated at 45°C and multiple preset SOC intervals (e.g., 0%-30%, 30%-70%, 70%-100%) to obtain a capacity fade rate-time database.

[0043] It should be noted that the above division methods of the preset temperature range and the preset SOC range are only exemplary, not restrictive. According to needs, the methods of dividing the preset temperature range and the preset SOC range can also be other range intervals. For example, multiple preset temperature ranges can be divided into T≤-15°C, -15°C<T≤5°C, 5°C<T≤25°C, 25°C<T≤45°C, 45°C<T≤65°C, and multiple preset SOC ranges can be divided into 0%-15%, 15%-30%, 30%-50%, 50%-70%, 70%-90%, 90%-100%.

[0044] For example, data analysis of the capacity decay rate reaching 20% of the test sample battery under each temperature range (T≤0°C, 0°C<T≤15°C, 15°C<T≤45°C, T>45°C) and different SOC ranges (0%-30%, 30%-70%, 70%-100%).

[0045] Exemplarily, the relationship between the capacity decay rate and the time data of the sample battery under the condition of 15°C<T≤45°C and the SOC range of 0%-30% is shown in Table 1. When the capacity decay rate is 20%, the corresponding time data is the calendar life of the sample battery under the condition of 15°C<T≤45°C and the SOC range of 0%-30%. In this embodiment, it is set that when the capacity decay rate of the sample battery reaches 20%, it means the end of the life.

[0046] Table 1: Relationship between capacity decay rate and time data under the conditions of temperature 15°C-45°C and SOC range 0%-30%

[0047]

[0048]

[0049] Step 102: Obtain the first time count matrix of the battery under test in the operating state and the second time count matrix of the battery under test in the sleep state. The first time count matrix is used to record the number of times the battery under test experiences the first time step in the operating state under multiple preset temperature ranges and multiple preset SOC ranges, and the second time count matrix is used to record the number of times the battery under test experiences the second time step in the sleep state under multiple preset temperature ranges and multiple preset SOC ranges.

[0050] According to another embodiment of the present invention, when the battery under test is in the operating state, each time the battery under test experiences a first time step, it triggers an update and storage of the first time count matrix; when the battery under test is in the sleep state, each time the battery under test experiences a second time step, it triggers an update and storage of the second time count matrix.

[0051] It should be noted that the one preset temperature interval and one SOC interval mentioned in the embodiment of the present invention constitute a set of conditions, and multiple preset temperature intervals and multiple SOC intervals can be combined to form multiple sets of conditions.

[0052] According to another embodiment of the present invention, a counter and a timer are provided for each set of conditions. The timer is used to record the time that the battery to be tested spends in the working state or the sleep state. When the time recorded by the timer reaches the first time step or the second time step, the number of times recorded in the corresponding counter is triggered to increase by one.

[0053] Specifically, the actual operating time of the battery to be tested in the running state and the sleep state is collected respectively. The battery to be tested is a power battery installed on a new energy vehicle. The battery management system of the new energy vehicle monitors and manages the temperature, SOC and health status of the battery. During the use of the new energy vehicle, the battery to be tested can obtain the first time count matrix and the second time count matrix under multiple preset temperatures and multiple preset SOC intervals in two states according to the running state and sleep state of the battery to be tested. For example, when the battery to be tested is in the running state, the battery to be tested may be in multiple preset temperature T intervals (for example, T≤0℃, 0℃<T≤15℃, 15℃<T≤45℃、T> 45℃) and multiple preset SOC intervals (for example, 0%-30%, 30%-70%, 70%-100%), a timer and a counter are configured for each temperature interval and SOC interval combination condition. For example, when the battery to be tested is at a temperature of T≤0℃ and an SOC interval of 0%-30%, the timer under this condition records the time. When the timer records that the battery to be tested has experienced a first time step under this condition, the counter under this condition will increase by 1. At this time, the first time matrix will be triggered to update the value under this condition and save it. Similarly, when the battery to be tested is in a dormant state, the battery to be tested will be in multiple preset temperatures T (for example, T≤0℃, 0℃<T≤15℃, 15℃<T≤45℃、T> 45℃) and multiple preset SOC intervals (for example, 0%-30%, 30%-70%, 70%-100%), a timer and a counter are configured for each temperature interval and SOC interval combination condition. For example, when the battery to be tested is at a temperature of T≤0℃ and the SOC interval is 0%-30%, the timer under this condition records the time. When the timer records that the battery to be tested has experienced a second time step under this condition, the counter under this condition will increase by 1. At this time, the second time matrix will be triggered to update the value under this condition and save it.

[0054] In another embodiment, a timer and a counter are used together under multiple conditions. Specifically, when the battery to be tested is in operation, the battery to be tested may be in multiple preset temperature T intervals (for example, T≤0℃, 0℃<T≤15℃, 15℃<T≤45℃、T> 45℃) and multiple preset SOC intervals (for example, 0%-30%, 30%-70%, 70%-100%), a set of timers and counters are configured for each condition combined with all temperature intervals and SOC intervals. For example, when the battery to be tested is at a temperature of T≤0℃ and an SOC interval of 0%-30%, the timer under this condition records the time. When the timer records that the battery to be tested has experienced a first time step under this condition, the counter under this condition will increase by 1. At this time, the first time matrix will be triggered to update the value under this condition and save it. Similarly, when the battery to be tested is in a dormant state, the battery to be tested will be in multiple preset temperatures T (for example, T≤0℃, 0℃<T≤15℃, 15℃<T≤45℃、T> 45℃) and multiple preset SOC intervals (for example, 0%-30%, 30%-70%, 70%-100%), a set of timers and counters are configured for each condition combined with all temperature intervals and SOC intervals. For example, when the battery to be tested is at a temperature of T≤0℃ and an SOC interval of 0%-30%, the timer under this condition records the time. When the timer records that the battery to be tested has experienced a second time step under this condition, the counter under this condition will increase by 1. At this time, the second time matrix will be triggered to update the value under this condition and save it.

[0055] According to another embodiment of the present invention, the multiple preset temperature intervals include a first preset temperature interval and a second preset temperature interval, the multiple preset SOC intervals include a first preset SOC interval, the first condition includes the first preset temperature interval and the first preset SOC interval, and the second condition includes the second preset temperature interval and the first preset SOC interval.

[0056] In some embodiments, multiple preset temperature intervals include but are not limited to the above-mentioned first preset temperature interval and second preset temperature interval, and multiple preset SOC intervals include but are not limited to the first preset SOC interval. The preset temperature intervals and preset SOC intervals can be set according to the actual usage of the battery to be tested.

[0057] According to another embodiment of the present invention, a specific method for obtaining a first time count matrix of the battery under test in the running state and a second time count matrix of the battery under test in the dormant state is as follows:

[0058] When the battery to be tested experiences a complete first time step or a complete second time step under the first condition, the elements corresponding to the first condition in the first time count matrix or the elements corresponding to the first condition in the second time count matrix are updated and stored; or when the battery to be tested experiences a complete first time step or a complete second time step under the second condition, the elements corresponding to the second condition in the first time count matrix or the elements corresponding to the second condition in the second time count matrix are updated and stored;

[0059] When the battery to be tested is under the first condition but has not experienced the complete first time step or the second time step and changes to the second condition, the time the current battery to be tested has experienced under the first condition is temporarily stored, and the time the battery to be tested has experienced under the second condition is continuously monitored. When the battery to be tested changes to the first condition, the time is continued to be recorded based on the temporarily stored time.

[0060] Specifically, when the current battery to be tested is in the first condition (operating state, temperature is T≤0℃, SOC range is 0%-30%), the timer under this condition starts timing, and when the time recorded by the timer reaches the first time step, the trigger counter is increased by 1; at this time, the battery to be tested is still in the first condition, and the timer under this condition continues timing, and when the time recorded by the timer has not reached the first time step, when the battery to be tested changes to the second condition (operating state, temperature is 0℃<T≤15℃, SOC range is 0%-30%), the timer under the first condition temporarily stores the time experienced by the battery to be tested in the storage area of ​​the timer itself or the storage area of ​​the battery management system, and triggers the timer under the second condition to start timing, and when the time recorded by the timer reaches the first time step, the trigger counter under this condition is increased by 1; at this time, the battery to be tested The battery is still in the second condition, and the timer under this condition continues to count. When the time recorded by the timer has not reached the first time step, when the battery to be tested changes to the third condition (dormant state, temperature is 0℃<T≤15℃, SOC range is 30%-70%), the timer under the second condition temporarily stores the time experienced by the battery to be tested in the storage area of ​​the timer itself or the storage area of ​​the battery management system, triggering the timer under the third condition to start timing. When the time recorded by the timer reaches the second time step, the counter under this condition is triggered to increase by 1; at this time, if the battery to be tested recovers to the first condition, the timer will start counting from the previously stored time. When the time recorded by the timer reaches the first time step, the counter is triggered to increase by 1. According to the actual use of the battery to be tested, the above process is repeated to realize the detection of the entire life cycle of the battery.

[0061] Specifically, when the battery management system detects that the battery to be tested is in an operating state, the temperature detection module, SOC detection module and timer in the battery management system will dynamically and in real time monitor the operating data of the battery to be tested; when the battery management system detects that the battery to be tested is in a dormant state, the battery management system will also monitor the battery to be tested offline. Therefore, the battery management system will be provided with a timed wake-up module, which will wake up once every second time step. At this time, the temperature detection module, SOC detection module and timer will monitor the battery to be tested, thereby realizing the monitoring of the entire life cycle of the battery to be tested.

[0062] It should be noted that recording the time of the battery to be tested under its current temperature range and SOC range conditions by counting with a counter to indirectly record and store the time instead of directly recording and storing the time with a timer is beneficial to reducing the large amount of storage space occupied by the test data.

[0063] Step 103: Calculate a first time matrix based on the first time count matrix and the first time step, and convert a second time matrix based on the second time count matrix and the second time step. Add each time in the first time matrix to each time at the corresponding position in the second time matrix to obtain a total time matrix for the battery to be tested.

[0064] According to another embodiment of the present invention, each time counting element in the first time counting matrix is ​​multiplied by the first time step to obtain the first time matrix; each time counting element in the second time counting matrix is ​​multiplied by the second time step to obtain the second time matrix.

[0065] Specifically, each element in the first time count matrix is ​​multiplied by the first time step to obtain each element in the first time matrix. Similarly, each element in the second time count matrix is ​​multiplied by the second time step to obtain each element in the second time matrix. The elements in the first time matrix and the elements in the second time matrix are added together after unifying the time unit to obtain the total time matrix of the battery under test, that is, the time records of different temperature intervals and different SOC intervals throughout the battery under test life cycle.

[0066] For example, the total time matrix of the battery to be tested in each temperature range and SOC range is shown in Table 2.

[0067] Table 2: Total time matrix based on each temperature range and SOC range

[0068]

[0069]

[0070] Among them, t a1It represents the sum of the time when the battery under test is in the operating state and the time when it is in the dormant state under the conditions of T ≤ 0°C and the SOC range of 0% - 30%; t b1 It represents the sum of the time when the battery under test is in the operating state and the time when it is in the dormant state under the conditions of T ≤ 0°C and the SOC range of 30% - 70%; t c1 It represents the sum of the time when the battery under test is in the operating state and the time when it is in the dormant state under the conditions of T ≤ 0°C and the SOC range of 70% - 100%; t a2 It represents the sum of the time when the battery under test is in the operating state and the time when it is in the dormant state under the conditions of 0°C < T ≤ 15°C and the SOC range of 0% - 30%; t b2 It represents the sum of the time when the battery under test is in the operating state and the time when it is in the dormant state under the conditions of 0°C < T ≤ 15°C and the SOC range of 30% - 70%; t c2 It represents the sum of the time when the battery under test is in the operating state and the time when it is in the dormant state under the conditions of 0°C < T ≤ 15°C and the SOC range of 70% - 100%; t a3 It represents the sum of the time when the battery under test is in the operating state and the time when it is in the dormant state under the conditions of 15°C < T ≤ 45°C and the SOC range of 0% - 30%; t b3 It represents the sum of the time when the battery under test is in the operating state and the time when it is in the dormant state under the conditions of 15°C < T ≤ 45°C and the SOC range of 30% - 70%; t c3 It represents the sum of the time when the battery under test is in the operating state and the time when it is in the dormant state under the conditions of 15°C < T ≤ 45°C and the SOC range of 70% - 100%; t a4 It represents the sum of the time when the battery under test is in the operating state and the time when it is in the dormant state under the conditions of T > 45°C and the SOC range of 0% - 30%; t b4 It represents the sum of the time when the battery under test is in the operating state and the time when it is in the dormant state under the conditions of T > 45°C and the SOC range of 30% - 70%; t c4 It represents the sum of the time when the battery under test is in the operating state and the time when it is in the dormant state under the conditions of T > 45°C and the SOC range of 70% - 100%.

[0071] Step 104: According to the capacity attenuation rate - time database, find the capacity attenuation rate corresponding to each time element in the total time matrix to obtain the capacity attenuation rate matrix of the battery under test;

[0072] Specifically, according to each time element in the total time matrix, and the temperature range and SOC range corresponding to each time element, the corresponding capacity decay rate is searched in the capacity decay rate-time database, and each capacity decay rate is matched to the corresponding temperature and SOC range conditions, thereby establishing a capacity decay rate matrix.

[0073] In some embodiments, some time elements in the total time matrix can be found in the capacity decay rate-time database to correspond to corresponding times, thereby obtaining corresponding capacity decay rates. However, other time elements in the total time matrix cannot be found in the capacity decay rate-time database to correspond to corresponding times, thereby obtaining corresponding capacity decay rates. When a one-to-one correspondence cannot be found, interpolation methods can be used to obtain the missing data in the capacity decay rate-time database. Such interpolation methods include but are not limited to linear interpolation, polynomial interpolation, spline interpolation, and the like.

[0074] For example, assume that a time element in the total time matrix is ​​obtained under the conditions of a temperature of 15°C-45°C and an SOC range of 0%-30%, that is, the capacity decay rate corresponding to this time element can be found in Table 1. When the value of this time element is 6 months, the corresponding capacity decay rate is 1.8%. When the value of this time element is 10 months, the corresponding capacity decay rate cannot be found in Table 1. In this embodiment, a linear interpolation method (i.e., numerical estimation is performed based on the two data adjacent to the point to be interpolated in the known data sequence) is adopted. Two sets of data, A1 (9, 2.5%) and A2 (12, 3.1%), are selected. A1, A2 and the value of the time element 10 are substituted into formula (1), and the capacity decay rate corresponding to the time element is calculated to be 2.7%.

[0075]

[0076] Wherein, (x0, y0) and (x1, y1) are two sets of known data adjacent to the point to be interpolated. In the above embodiment, if x is 10, then y is calculated to be 2.7%.

[0077] It should be noted that the above embodiment is merely illustrative and not restrictive. As needed, other methods and steps may be used to solve the capacity decay rate corresponding to the time element that cannot be found in the capacity decay rate-time database.

[0078] Step 105: Calculate the health status matrix of the battery to be tested according to the capacity decay rate matrix.

[0079] According to another embodiment of the present invention, by subtracting the integer 1 from each capacity attenuation rate respectively, the health state of the battery under test in multiple preset temperature intervals and multiple preset SOC intervals is obtained, so as to obtain the health matrix of the battery under test corresponding to the capacity attenuation rate.

[0080] According to another embodiment of the present invention, the health states of the battery under test in multiple preset temperature intervals and multiple preset SOC intervals are multiplied to obtain the health state of the battery under test during the monitoring period.

[0081] Specifically, by subtracting the integer 1 from each capacity attenuation rate respectively, the health state of the battery under test in multiple preset temperature intervals and multiple preset SOC intervals is obtained, and the health states of each battery under test are multiplied to obtain the health state of the battery under test during the monitoring period, which is convenient for more clearly reflecting the capacity attenuation situation of the battery under test under the actual operating state and the health state of the battery under test.

[0082] Exemplarily, the health state matrix of the battery under test is shown in Equation (2).

[0083]

[0084] Where, SOH a1 represents the health state of the battery under test under the condition that T ≤ 0°C and the SOC interval is 0% - 30%; SOH b1 represents the health state of the battery under test under the condition that T ≤ 0°C and the SOC interval is 30% - 70%; SOH c1 represents the health state of the battery under test under the condition that T ≤ 0°C and the SOC interval is 70% - 100%; SOH a2 represents the health state of the battery under test under the condition that 0°C < T ≤ 15°C and the SOC interval is 0% - 30%; SOH b2 represents the health state of the battery under test under the condition that 0°C < T ≤ 15°C and the SOC interval is 30% - 70%; SOH c2 represents the health state of the battery under test under the condition that 0°C < T ≤ 15°C and the SOC interval is 70% - 100%; SOH a3 represents the health state of the battery under test under the condition that 15°C < T ≤ 45°C and the SOC interval is 0% - 30%; SOH b3 represents the health state of the battery under test under the condition that 15°C < T ≤ 45°C and the SOC interval is 30% - 70%; SOH c3 represents the health state of the battery under test under the condition that 15°C < T ≤ 45°C and the SOC interval is 70% - 100%; SOH a4 represents the health state of the battery under test under the condition that T > 45°C and the SOC interval is 0% - 30%; SOHb4 Indicates the health status of the battery under test under the conditions of T>45℃ and SOC range of 30%-70%; SOH c4 Indicates the health status of the battery under test under the conditions of T>45℃ and SOC range of 70%-100%.

[0085] For example, the health status of the battery to be tested during the monitoring period can be obtained by formula (3).

[0086]

[0087] In some embodiments, the rows of the first time count matrix represent the number of times the battery to be tested experiences a first time step at the same preset temperature and multiple preset SOCs, the columns of the first time count matrix represent the number of times the battery to be tested experiences the first time step at the same preset SOC and multiple preset temperatures, the rows of the second time count matrix represent the number of times the battery to be tested experiences a second time step at the same preset temperature and multiple preset SOCs, the columns of the second time count matrix represent the number of times the battery to be tested experiences the second time step at the same preset SOC and multiple preset temperatures, the rows of the health status matrix of the battery to be tested represent the health status of the battery to be tested at the same preset temperature and multiple preset SOCs, and the columns of the health status matrix of the battery to be tested represent the health status at the same preset SOC and multiple preset temperatures.

[0088] In another specific embodiment, the meanings represented by the rows and columns of the above three matrices are interchangeable. Specifically, the columns of the first time counting matrix represent the number of times the battery to be tested experiences the first time step at the same preset temperature and multiple preset SOCs, the rows of the first time counting matrix represent the number of times the battery to be tested experiences the first time step at the same preset SOC and multiple preset temperatures, the columns of the second time counting matrix represent the number of times the battery to be tested experiences the second time step at the same preset temperature and multiple preset SOCs, the rows of the second time counting matrix represent the number of times the battery to be tested experiences the second time step at the same preset SOC and multiple preset temperatures, the columns of the health status matrix of the battery to be tested represent the health status of the battery to be tested at the same preset temperature and multiple preset SOCs, and the rows of the health status matrix of the battery to be tested represent the health status at the same preset SOC and multiple preset temperatures.

[0089] In some embodiments, the present invention further provides a first time step of 20 minutes and a second time step of 8 hours. The operator can select the first and second time steps according to actual needs to more completely detect the full life cycle of the battery under test.

[0090] See also Figure 2 , Figure 2 A block diagram of a battery management system provided by an embodiment of the present invention is shown.

[0091] like Figure 2 As shown, the battery management system includes a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to implement the steps of the battery health status prediction method provided in the above embodiment. These components are interconnected through a bus system and / or other forms of connection mechanisms (not shown in the figure). It should be noted that Figure 2 The components and structure of the battery management system 200 shown are merely exemplary and non-limiting. The battery management system 200 may also have other components and structures as needed.

[0092] The memory 201 is used to store various data and executable program instructions generated during the relevant operation process, such as for storing various application programs or algorithms for implementing various specific functions. It can include one or more computer program products, which can include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory can include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory can include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0093] The processor 202 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other form of processing unit with data processing capabilities and / or instruction execution capabilities, and may be other components in the battery management system 200 to perform desired functions.

[0094] In one example, the battery management system 200 further includes an output device that can output various information (eg, images or sounds) to the outside (eg, a user), and can include one or more of a display device, a speaker, and the like.

[0095] The communication interface can be an interface of any currently known communication protocol, such as a wired interface or a wireless interface, wherein the communication interface may include one or more serial ports, USB interfaces, Ethernet ports, WiFi, wired networks, DVI interfaces, device integrated interconnection modules or other suitable ports, interfaces, or connections.

[0096] Furthermore, the battery management system also includes a counter and a timer. The timer is used to record the time that the battery to be tested spends in the working state or the sleep state. When the time recorded by the timer reaches the first time step or the second time step, the number of times recorded in the corresponding counter is triggered to increase by one.

[0097] In one embodiment, a counter and a timer are provided for each preset temperature range and SOC range. In other words, each monitoring condition is independently timed and counted. When the battery under test is within the current preset temperature range and SOC range, and the time recorded by the timer reaches the first time step or the second time step, the number of times recorded in the corresponding counter is triggered to increase by one. When the time recorded by the timer does not reach the first time step or the second time step, and the battery under test is within another preset temperature range and SOC range, the time recorded by the timer is temporarily stored in the timer. When the battery under test is again within the current preset temperature range and SOC range, the timer starts counting from the last temporarily stored time.

[0098] In another embodiment, a counter and a timer are used under all preset temperature intervals and SOC interval conditions. When the battery to be tested is in the current preset temperature interval and SOC interval, when the time recorded by the timer reaches the first time step or the second time step, the number of times recorded in the corresponding counter is triggered to increase once; when the time recorded by the timer does not reach the first time step or the second time step, and the battery to be tested is in other preset temperature intervals and SOC intervals, the time recorded in the timer is temporarily stored in the storage space through a preset program. When the battery to be tested is in the current preset temperature interval and SOC interval again, the time corresponding to the current preset temperature interval and SOC interval is found through the preset program, and the timer starts timing from the time of the last temporary storage in the storage space.

[0099] In some embodiments, the embodiments of the present invention further provide a non-transitory computer-readable storage medium, characterized in that a computer program is stored thereon, and when the program is executed by a processor, the battery health state prediction method provided in the above embodiment is implemented. Wherein, program instructions are stored on the computer-readable storage medium, and when the program instructions are executed by a computer or processor, they are used to execute the corresponding steps of the battery health state prediction method of the embodiment of the present invention. The computer-readable storage medium may include, but is not limited to, any type of disk, including a floppy disk, an optical disk, a DVD, a CD-ROM, a micro drive and a magneto-optical disk, a ROM, a RAM, an EPROM, an EEPROM, a DRAM, a VRAM, a flash memory device, a magnetic card or an optical card, a nanosystem (including a molecular memory IC), or any type of medium or device suitable for storing instructions and / or data.

[0100] The battery management system and storage medium of the embodiment of the present invention can implement the aforementioned battery health state prediction method, and therefore have the same advantages as the aforementioned battery health state prediction method.

[0101] See also Figure 3 , Figure 3A block diagram of a new energy vehicle provided by an embodiment of the present invention is shown.

[0102] like Figure 3 As shown, the new energy vehicle according to the embodiment of the present invention includes the battery management system provided by the above embodiment.

[0103] The new energy vehicle of the embodiment of the present invention, through the battery management system provided by the above embodiment, can analyze the actual operating time of the battery in the new energy vehicle under different conditions, and can dynamically monitor the entire life cycle of the battery, thereby improving the accuracy of the battery health status prediction and improving the reliability of the prediction results.

[0104] It should be noted that, in the examples and description of the present invention, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a" does not exclude the presence of additional identical elements in the process, method, article, or device comprising the element.

[0105] Although the present invention has been illustrated and described with reference to certain preferred embodiments thereof, it should be understood by those skilled in the art that the above description is provided as a further detailed description of the present invention in conjunction with specific embodiments thereof, and that the specific implementation of the present invention is not limited to these descriptions. Those skilled in the art may make various changes in form and details, including simple deductions or substitutions, without departing from the spirit and scope of the present invention.

Claims

1. A method for predicting battery health status, characterized in that: include: (1) Test the capacity decay rate of multiple sample batteries in multiple preset temperature ranges and multiple preset SOC ranges during calendar life, and establish a capacity decay rate-time database; (2) obtaining a first time count matrix of the battery under test in an operating state and a second time count matrix of the battery under test in a dormant state, wherein the first time count matrix is ​​used to record the number of times the battery under test experiences a first time step in the operating state, respectively, at the plurality of preset temperature intervals and the plurality of preset SOC intervals, and the second time count matrix is ​​used to record the number of times the battery under test experiences a second time step in the dormant state, respectively, at the plurality of preset temperature intervals and the plurality of SOC intervals; (3) Calculating a first time matrix based on the first time count matrix and the first time step, and converting a second time matrix based on the second time count matrix and the second time step, and adding each time in the first time matrix to each time at a corresponding position in the second time matrix to obtain a total time matrix for the battery to be tested; (4) searching the capacity decay rate corresponding to each time element in the total time matrix according to the capacity decay rate-time database to obtain the capacity decay rate matrix of the battery to be tested; (5) Calculating a health status matrix of the battery to be tested based on the capacity decay rate matrix; wherein, the health status of the battery to be tested in multiple preset temperature intervals and multiple preset SOC intervals is obtained by subtracting the integer 1 from each element in the capacity decay rate matrix, so as to obtain the health status matrix of the battery to be tested.

2. The battery health status prediction method according to claim 1, characterized in that: Step (2) also includes: When the battery to be tested is in a running state, each time the battery to be tested experiences one of the first time steps, the updating and storage of the first time counting matrix is ​​triggered once; When the battery under test is in a dormant state, each time the battery under test experiences one of the second time steps, the updating and storage of the second time counting matrix is ​​triggered.

3. The battery health status prediction method according to claim 2, wherein: The plurality of preset temperature intervals include a first preset temperature interval and a second preset temperature interval, the plurality of preset SOC intervals include a first preset SOC interval, the first condition includes the first preset temperature interval and the first preset SOC interval, and the second condition includes the second preset temperature interval and the first preset SOC interval; wherein, in step (2), the specific method of obtaining the first time count matrix of the battery to be tested in the running state and the second time count matrix of the battery to be tested in the dormant state is: When the battery to be tested experiences a complete first time step or a complete second time step under a first condition, the elements corresponding to the first condition in the first time count matrix or the elements corresponding to the first condition in the second time count matrix are updated and stored; or when the battery to be tested experiences a complete first time step or a complete second time step under a second condition, the elements corresponding to the second condition in the first time count matrix or the elements corresponding to the second condition in the second time count matrix are updated and stored; When the battery to be tested is under the first condition and has not experienced the complete first time step or the second time step and becomes under the second condition, the time the battery to be tested currently experiences under the first condition is temporarily stored, and the time the battery to be tested experiences under the second condition is continuously monitored. When the battery to be tested becomes under the first condition, the time is continued to be recorded based on the temporarily stored time.

4. The battery health status prediction method according to claim 3, wherein: In step (3), the specific method of converting the first time matrix according to the first time count matrix and the first time step, and converting the second time matrix according to the second time count matrix and the second time step is: Multiplying each time counting element in the first time counting matrix by the first time step to obtain the first time matrix; Each time count element in the second time count matrix is ​​multiplied by the second time step to obtain the second time matrix.

5. The battery health status prediction method according to claim 4, wherein: Also includes: The health states of the battery to be tested in the plurality of the preset temperature intervals and the plurality of the preset SOC intervals are multiplied to obtain the health state of the battery to be tested within a monitoring period.

6. The battery health status prediction method according to claim 5, characterized in that: In step (2), the first time step is set to 20 minutes, and the second time step is set to 8 hours.

7. A battery management system 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 battery health state prediction method according to any one of claims 1 to 6.

8. A battery management system according to claim 7, characterized in that: A timer and a counter are also provided. The timer is used to record the time that the battery to be tested has spent in the working state or the dormant state. When the time recorded by the timer reaches the first time step or the second time step, the number of times recorded in the corresponding counter is triggered to increase by one.

9. A new energy vehicle, characterized in that: Comprising a battery management system as claimed in any one of claims 7 or 8.

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