Battery health estimation method and device, vehicle and computer storage medium

Abstract

The invention discloses a battery health estimation method and device, a vehicle and a computer storage medium, and relates to the technical field of batteries, and the method comprises the steps: obtaining the battery temperature and the historical use data of a vehicle battery in the vehicle, and obtaining the capacity health change trend and the internal resistance health change trend according to the battery temperature; estimating the capacity health degree of the vehicle battery according to the capacity health change trend and the battery historical use data, and estimating the internal resistance health degree according to the internal resistance health change trend and the battery historical use data; and determining the minimum health degree in the capacity health degree and the internal resistance health degree as the target health degree of the vehicle battery. The technical problem that the health degree estimation accuracy of the vehicle battery is low is solved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of battery technology, and in particular to a battery health estimation method, device, vehicle, and computer storage medium. Background Art

[0002] With the rapid development of new energy vehicles, the accuracy of power battery state of health (SOH) estimation directly affects the safety and service life of the battery. At present, the SOH estimation method of the battery is usually estimated by a filtering algorithm, and the filtering algorithm is usually based on linear or near-linear assumptions. The health of the battery does not change linearly, so the estimation accuracy is not high. Therefore, when the actual battery health has dropped below the safety threshold, the estimated battery health may still be above the safety threshold, which may lead to batteries with poor battery health still being used, which is prone to the risk of battery fire. Therefore, there is currently a technical problem of poor vehicle battery safety caused by low accuracy of vehicle battery health estimation.

[0003] The above content is only used to assist in understanding the technical solutions of the embodiments of the present application and does not constitute an admission that the above content is prior art. Summary of the Invention

[0004] The main purpose of the embodiments of the present application is to provide a battery health estimation method, device, vehicle and computer storage medium, aiming to solve the technical problem of poor vehicle battery safety caused by low accuracy in vehicle battery health estimation.

[0005] To achieve the above-mentioned objectives, an embodiment of the present application provides a battery health estimation method, the method comprising: obtaining a battery temperature and historical battery usage data of a vehicle battery in a vehicle, and obtaining a capacity health change trend and an internal resistance health change trend based on the battery temperature;

[0006] estimating the capacity health of the vehicle battery based on the capacity health change trend and the battery historical usage data, and estimating the internal resistance health based on the internal resistance health change trend and the battery historical usage data;

[0007] A minimum health state between the capacity health state and the internal resistance health state is determined as a target health state of the vehicle battery.

[0008] In one embodiment, the step of obtaining the capacity health change trend and the internal resistance health change trend according to the battery temperature includes:

[0009] If a target preset temperature corresponding to the battery temperature exists in a preset temperature trend database, the target capacity health change trend and target internal resistance health change trend of the target preset temperature obtained from the preset temperature trend database are used as the capacity health change trend and internal resistance health change trend of the battery temperature;

[0010] If the target preset temperature does not exist in the preset temperature trend database, searching the preset temperature trend database for a first preset temperature and a second preset temperature adjacent to the battery temperature, wherein the first preset temperature is greater than the battery temperature and the second preset temperature is less than the battery temperature;

[0011] Determining a capacity health change trend of the battery temperature between the first preset capacity health change trend and the second preset capacity health change trend according to a first preset capacity health change trend at the first preset temperature and a second preset capacity health change trend at the second preset temperature;

[0012] Based on a first preset internal resistance health change trend at the first preset temperature and a second preset internal resistance health change trend at the second preset temperature, the internal resistance health change trend of the battery temperature is determined between the first preset internal resistance health change trend and the second preset internal resistance health change trend.

[0013] In one embodiment, the preset temperature trend database includes a preset capacity health change trend and a preset internal resistance health change trend corresponding to a preset temperature, wherein the preset capacity health change trend includes a preset cycle curve and a preset storage curve; the method further includes:

[0014] Performing cyclic charge and discharge tests on the preset battery cells at multiple preset temperatures to obtain a preset cycle curve between a preset number of cycles and a preset cycle health at each preset temperature;

[0015] Performing a storage test on a preset battery cell at each preset temperature to obtain a preset storage curve between a preset storage time and a preset storage health at each preset temperature;

[0016] An internal resistance test is performed on a preset battery cell at each preset temperature to obtain a preset internal resistance health change trend between the preset internal resistance and the preset internal resistance health at each preset temperature.

[0017] In one embodiment, the step of estimating the capacity health of the vehicle battery based on the capacity health change trend and the battery historical usage data includes:

[0018] Obtaining the battery's cumulative storage time and battery cycle count from the battery's historical usage data, and obtaining a cycle curve and a storage curve from the capacity health change trend;

[0019] Obtaining the cycle health corresponding to the number of battery cycles from the cycle curve, and obtaining the storage health corresponding to the accumulated storage time of the battery from the storage curve;

[0020] Obtaining a cyclic attenuation coefficient and a storage attenuation coefficient, and performing a weighted summation of the cyclic health and the storage health according to the cyclic attenuation coefficient and the storage attenuation coefficient to obtain a first capacity health;

[0021] Obtaining the battery's charged capacity, battery operating time, and battery operating current when the vehicle is powered on, and the battery's uncharged capacity when the vehicle is powered off, and calculating, based on the battery operating time and the battery operating current, the charge and discharge amount of the vehicle battery within the battery operating time;

[0022] calculating a difference between the lower capacity of the battery and the upper capacity of the battery to obtain a capacity difference, using a ratio of the charge and discharge amount to the capacity difference as an ampere-hour integrated capacity, and using a ratio of the ampere-hour integrated capacity to a preset nominal capacity of the vehicle battery as a second capacity health indicator;

[0023] A minimum health level between the first capacity health level and the second capacity health level is determined as the capacity health level.

[0024] In one embodiment, the steps of obtaining the cyclic attenuation coefficient and storing the attenuation coefficient include:

[0025] Determining the accumulated battery cycle time and the total usage time of the vehicle battery from the historical battery usage data;

[0026] The ratio of the accumulated cycle time of the battery to the total usage time is used as the cycle attenuation coefficient, and the ratio of the accumulated storage time of the battery to the total usage time is used as the storage attenuation coefficient.

[0027] In one embodiment, the internal resistance health change trend includes a mapping relationship between a preset internal resistance and a preset health level, and also includes a mapping relationship between a preset usage time and a preset internal resistance. The step of estimating the internal resistance health level based on the internal resistance health change trend and the battery historical usage data includes:

[0028] determining a total usage time of the vehicle battery from the historical battery usage data;

[0029] The target internal resistance of the total usage time is determined from the internal resistance health change trend, and the internal resistance health degree corresponding to the target internal resistance is determined from the internal resistance health change trend.

[0030] In one embodiment, the battery health estimation method further includes:

[0031] Outputting a battery maintenance prompt when the target battery health is greater than a preset health and safety threshold and the target battery health is less than or equal to a preset warning health threshold;

[0032] When the target battery health is less than or equal to a preset health and safety threshold, outputting a battery life end prompt;

[0033] Among them, the preset warning health threshold is greater than the preset health safety threshold.

[0034] In addition, to achieve the above-mentioned purpose, an embodiment of the present application provides a battery health estimation device, the device comprising:

[0035] an acquisition module, configured to acquire a battery temperature and historical battery usage data of a vehicle battery in the vehicle, and acquire a capacity health change trend and an internal resistance health change trend based on the battery temperature;

[0036] an estimation module, configured to estimate the capacity health of the vehicle battery based on the capacity health change trend and the battery historical usage data, and to estimate the internal resistance health based on the internal resistance health change trend and the battery historical usage data;

[0037] A determination module is configured to determine a minimum health state between the capacity health state and the internal resistance health state as a target health state of the vehicle battery.

[0038] In addition, to achieve the above-mentioned purpose, an embodiment of the present application also provides a vehicle, which includes: a memory, a processor, and a program of the battery health estimation method stored in the memory and runnable on the processor. When the program of the battery health estimation method is executed by the processor, the steps of the battery health estimation method as described above can be implemented.

[0039] In addition, to achieve the above-mentioned purpose, an embodiment of the present application also provides a computer-readable storage medium, on which a program for implementing the battery health estimation method is stored. When the program of the battery health estimation method is executed by a processor, the steps of the battery health estimation method as described above are implemented.

[0040] In addition, to achieve the above-mentioned purpose, an embodiment of the present application also provides a computer program product, including a computer program, which implements the steps of the battery health estimation method as described above when executed by a processor.

[0041] One or more technical solutions proposed in the embodiments of the present application have at least the following technical effects: In this embodiment, by obtaining the battery temperature and historical battery usage data, and obtaining the capacity health change trend and internal resistance health change trend through the battery temperature, it is possible to dynamically obtain the capacity health change trend and internal resistance health change trend through the battery temperature, rather than estimating the battery health based on a fixed trend. Since different battery temperatures have different impacts on the health of the vehicle battery, this embodiment obtains the capacity health change trend and internal resistance health change trend through the battery temperature, so that the accuracy of the battery health estimation can be improved subsequently.

[0042] Furthermore, in this embodiment, the capacity health is estimated based on the capacity health change trend and historical battery usage data, and the internal resistance battery health is estimated based on the internal resistance health change trend and historical battery usage data. Since the historical battery usage data can reflect the battery usage, and different battery usage conditions have different impacts on the battery health, the capacity health corresponding to the historical battery usage data can be determined by combining the historical battery usage data and the capacity health change trend. The internal resistance health corresponding to the historical battery usage data can also be determined by combining the internal resistance health change trend. The minimum of the internal resistance health and capacity health is determined as the target health of the vehicle battery. The battery health is not estimated using a simple linear or near-linear filtering algorithm. Instead, the vehicle battery health is determined by jointly determining the capacity health change trend, the internal resistance health change trend, and the historical battery usage data. This improves the accuracy of battery health estimation and reduces the situation where the actual battery health drops below a safety threshold while the estimated battery health is still above the safety threshold, resulting in the continued use of batteries with poor battery health. This can improve the safety of the vehicle battery and solve the technical problem of poor vehicle battery safety caused by low vehicle battery estimation accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the embodiments of the present application, and together with the specification are used to explain the principles of the embodiments of the present application.

[0044] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0045] Figure 1 This is a flow chart of an embodiment of a battery health estimation method according to an embodiment of the present application;

[0046] Figure 2This is a flow chart of another embodiment of the battery health estimation method according to an embodiment of the present application;

[0047] Figure 3 This is a flowchart of an example of a battery health estimation method according to an embodiment of the present application;

[0048] Figure 4 This is a schematic diagram of the module structure of the battery health estimation device according to an embodiment of the present application;

[0049] Figure 5 Schematic diagram of the device structure of the hardware operating environment involved in the battery health estimation method in the embodiment of the present application.

[0050] The purpose, features and advantages of the embodiments of the present application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0051] It should be understood that the specific embodiments described herein are merely used to explain the technical solutions of the embodiments of the present application and are not intended to limit the embodiments of the present application.

[0052] In order to better understand the technical solutions of the embodiments of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0053] With the rapid development of new energy vehicles, the accuracy of power battery state-of-health (SOH) estimation directly impacts battery safety and service life. Improving SOH estimation accuracy while ensuring safety has become a constant challenge for relevant R&D personnel. Batteries age continuously during use. Generally, when the SOH drops to 70%, it is considered that the battery no longer meets the requirements of electric vehicle operation. Traditional SOH estimation is primarily implemented using filtering algorithms. In practical applications, the accuracy of filtering algorithms in SOH estimation is around 5%. Therefore, the poor safety of vehicle batteries caused by low battery health estimation accuracy is a pressing technical issue that needs to be addressed.

[0054] In this embodiment, by obtaining battery temperature and historical battery usage data, and obtaining the capacity health change trend and internal resistance health change trend through the battery temperature, it is possible to dynamically obtain the capacity health change trend and internal resistance health change trend through the battery temperature, rather than estimating the battery health based on a fixed trend. Since different battery temperatures have different impacts on the health of the vehicle battery, this embodiment obtains the capacity health change trend and internal resistance health change trend through the battery temperature so that the accuracy of battery health estimation can be improved subsequently.

[0055] Furthermore, in this embodiment, the capacity health is estimated based on the capacity health change trend and historical battery usage data, and the internal resistance battery health is estimated based on the internal resistance health change trend and historical battery usage data. Since the historical battery usage data can reflect the battery usage, and different battery usage conditions have different impacts on the battery health, the capacity health corresponding to the historical battery usage data can be determined by combining the historical battery usage data and the capacity health change trend. The internal resistance health corresponding to the historical battery usage data can also be determined by combining the internal resistance health change trend. The minimum of the internal resistance health and capacity health is determined as the target health of the vehicle battery. The battery health is not estimated using a simple linear or near-linear filtering algorithm. Instead, the vehicle battery health is determined by jointly determining the capacity health change trend, the internal resistance health change trend, and the historical battery usage data. This improves the accuracy of battery health estimation and reduces the situation where the actual battery health drops below a safety threshold while the estimated battery health is still above the safety threshold, resulting in the continued use of batteries with poor battery health. This can improve the safety of the vehicle battery and solve the technical problem of poor vehicle battery safety caused by low vehicle battery estimation accuracy.

[0056] Based on this, the embodiment of the present application provides a battery health estimation method, referring to Figure 1 , Figure 1 This is a flowchart of the first embodiment of the battery health estimation method of the present application. The battery health estimation method includes steps S10 to S30:

[0057] Step S10, obtaining a battery temperature and historical battery usage data of a vehicle battery in the vehicle, and obtaining a capacity health change trend and an internal resistance health change trend based on the battery temperature;

[0058] It should be noted that the battery temperature can be detected by a temperature sensor installed on the vehicle battery, and the battery usage history data can reflect the usage of the vehicle battery. The battery usage history data may include the cumulative storage time of the vehicle battery, the number of battery cycles, the cumulative cycle time of the battery, and the total usage time, etc. This embodiment does not impose specific restrictions on this. The cumulative storage time of the battery refers to the time the vehicle battery is in a static state and not charged or discharged. The number of battery cycles refers to the number of times the vehicle battery is charged and discharged. The cumulative cycle time of the battery refers to the time the vehicle is charged and discharged. The total usage time refers to the time between the time the vehicle battery was first used after leaving the factory and the current time. The total usage time can be the sum of the cycle time and the storage time.

[0059] Different battery temperatures may result in different capacity health change trends and internal resistance health change trends. The capacity health change trend can reflect the relationship between health and capacity changes, and the internal resistance health change trend can reflect the relationship between health and internal resistance changes. The internal resistance health change trend can be represented as an internal resistance health change curve. The horizontal axis of the coordinate system of the internal resistance health change curve can be time, and the coordinate system of the internal resistance health change curve can have two vertical axes, namely internal resistance and health. The two vertical axes can share a horizontal axis, be on the same line, and do not overlap. The capacity health change trend can include a cycle curve and a storage curve. The cycle curve can be the relationship between the number of cycles and health, and the storage curve can reflect the relationship between storage time and health. The horizontal axis of the coordinate system of the cycle curve can be the number of cycles, and the vertical axis can be the cycle health. The horizontal axis of the coordinate system of the storage curve can be the storage time, and the vertical axis can be the internal resistance health.

[0060] Step S20, estimating the capacity health of the vehicle battery based on the capacity health change trend and the battery historical usage data, and estimating the internal resistance health based on the internal resistance health change trend and the battery historical usage data;

[0061] It should be noted that both capacity health and internal resistance health can reflect the degree of aging of the vehicle battery. Capacity health and internal resistance health reflect the degree of aging of the vehicle battery from different dimensions respectively. Capacity health can reflect the energy storage capacity of the vehicle battery. The higher the capacity health, the stronger the energy storage capacity, which means the longer the vehicle battery's cruising range. The lower the capacity health, the weaker the energy storage capacity, which means the shorter the vehicle battery's cruising range. Internal resistance health can reflect the internal resistance state of the vehicle battery. The higher the internal resistance health, the lower the relative increase rate of the internal resistance in the vehicle battery and the higher the power output efficiency. Conversely, the lower the internal resistance health, the higher the relative increase rate of the internal resistance in the vehicle and the lower the power output efficiency of the vehicle battery. The capacity health change trend and the internal resistance health change trend corresponding to the battery temperature can be predetermined.

[0062] For example, the capacity health level corresponding to the battery's historical usage data may be determined from the capacity health change trend, or the internal resistance health level corresponding to the battery's historical usage data may be determined from the internal resistance health change trend.

[0063] Step S30 : determining the minimum health level among the capacity health level and the internal resistance health level as the target health level of the vehicle battery.

[0064] It should be noted that internal resistance and capacity are both key indicators for measuring battery health. Capacity decay will directly affect the cruising range of the vehicle battery, and increased internal resistance will lead to a decrease in the power output efficiency of the vehicle battery. For vehicle batteries, their performance is limited by worse indicators. For example, even if the capacity is high, excessive internal resistance will limit the available energy of the vehicle battery. Conversely, if the capacity is low, even low internal resistance will also lead to insufficient cruising range. Therefore, this embodiment determines the minimum health among the capacity health and internal resistance health as the target health of the vehicle battery, so that the actual health of the vehicle battery can be reflected by the target health. The target health can reflect the actual health of the vehicle battery.

[0065] For example, the minimum health value between the capacity health value and the internal resistance health value can be determined as the target health value of the vehicle. In this embodiment, by obtaining battery temperature and historical battery usage data, and then obtaining the capacity health change trend and the internal resistance health change trend based on the battery temperature, the capacity health change trend and the internal resistance health change trend can be dynamically obtained based on the battery temperature, rather than estimating the battery health based on a fixed trend. Because different battery temperatures have different impacts on the health of the vehicle battery, this embodiment obtains the capacity health change trend and the internal resistance health change trend based on the battery temperature to improve the accuracy of subsequent battery health estimation.

[0066] Furthermore, in this embodiment, the capacity health is estimated based on the capacity health change trend and historical battery usage data, and the internal resistance battery health is estimated based on the internal resistance health change trend and historical battery usage data. Since the historical battery usage data can reflect the battery usage, and different battery usage conditions have different impacts on the battery health, the capacity health corresponding to the historical battery usage data can be determined by combining the historical battery usage data and the capacity health change trend. The internal resistance health corresponding to the historical battery usage data can also be determined by combining the internal resistance health change trend. The minimum of the internal resistance health and capacity health is determined as the target health of the vehicle battery. The battery health is not estimated using a simple linear or near-linear filtering algorithm. Instead, the vehicle battery health is determined by jointly determining the capacity health change trend, the internal resistance health change trend, and the historical battery usage data. This improves the accuracy of battery health estimation and reduces the situation where the actual battery health drops below a safety threshold while the estimated battery health is still above the safety threshold, resulting in the continued use of batteries with poor battery health. This can improve the safety of the vehicle battery and solve the technical problem of poor vehicle battery safety caused by low vehicle battery estimation accuracy.

[0067] In a feasible embodiment, step S10 further includes steps S11 to S14:

[0068] Step S11: If a target preset temperature corresponding to the battery temperature exists in the preset temperature trend database, the target capacity health change trend and target internal resistance health change trend at the target preset temperature obtained from the preset temperature trend database are used as the capacity health change trend and internal resistance health change trend at the battery temperature;

[0069] It should be noted that the preset temperature trend database stores preset capacity health change trends and preset internal resistance health change trends corresponding to multiple preset temperatures. The preset temperature trend database may be predetermined. When the preset temperature trend database contains a target preset temperature corresponding to the battery temperature, it indicates that the preset temperature trend database contains the corresponding capacity health change trends and internal resistance health change trends, and the corresponding battery temperature can be directly retrieved from the preset temperature trend database.

[0070] In addition, in other embodiments, in the preset temperature trend database, each preset temperature may have a preset capacity health change trend and a preset internal resistance health change trend corresponding to one or more preset operating conditions, that is, each preset operating condition at each preset temperature has a preset capacity health change trend and a preset internal resistance health change trend, and each preset temperature may have multiple preset capacity health change trends and preset internal resistance health change trends. The preset operating condition can represent the operating condition of the vehicle, and the multiple preset operating conditions may include CLTC (China Light-duty Vehicle Test Cycle) operating conditions, high-temperature fast charging, high-speed driving, etc. This embodiment does not specifically limit this.

[0071] When a target preset temperature for the battery temperature exists in the preset temperature trend database, and there are preset capacity health change trends and preset internal resistance health change trends corresponding to multiple preset operating conditions at the target preset temperature, the operating condition of the vehicle in which the vehicle battery is located can be obtained, and the target operating condition corresponding to the operating condition can be searched among the multiple preset operating conditions. The target capacity health change trend and target internal resistance health change trend of the target operating condition can be used as the capacity health change trend and internal resistance health change trend of the battery temperature. When there is only one preset capacity health change trend and preset internal resistance health change trend under one preset operating condition at the target preset temperature, the preset capacity health change trend and preset internal resistance health change trend under that preset operating condition can be directly used as the capacity health change trend and internal resistance health change trend corresponding to the battery temperature.

[0072] In the preset temperature trend database, each preset temperature has at least one preset capacity health change trend and preset internal resistance health change trend under a commonly used preset operating condition, so that when the capacity health change trend and internal resistance health change trend corresponding to the battery temperature are actually obtained, they can be matched with the current operating condition of the vehicle, thereby facilitating the acquisition of more accurate capacity change trends and internal resistance change trends, so as to subsequently improve the accuracy of battery health estimation.

[0073] For example, if a target preset temperature corresponding to the battery temperature exists in the preset temperature trend database, and the number of preset operating conditions corresponding to the target preset temperature is one, the preset internal resistance health change trend and the preset capacity health change trend of the preset operating condition at the target preset temperature are used as the capacity health change trend and the internal resistance health change trend of the battery temperature. If multiple preset operating conditions exist at the target preset temperature, the vehicle's current operating condition is obtained, and a target operating condition is determined from the multiple preset operating conditions at the target preset temperature. The target capacity health change trend and the target internal resistance health change trend of the target operating condition are used as the capacity health change trend and the internal resistance health change trend of the battery temperature. If no operating condition exists among the multiple preset operating conditions at the target preset temperature, a target common operating condition is determined from the multiple preset operating conditions, and the target capacity health change trend and the target internal resistance health change trend of the target common operating condition are used as the capacity health change trend and the internal resistance health change trend of the battery temperature. Alternatively, any target operating condition can be determined from the multiple preset operating conditions, and this embodiment does not specifically limit this. The target common working condition can be determined based on actual conditions, and this embodiment does not impose any specific limitation on this. The preset working conditions of the common working conditions can be marked with common labels so that the target common working condition can be determined in each preset working condition.

[0074] Step S12: if the target preset temperature does not exist in the preset temperature trend database, searching the preset temperature trend database for a first preset temperature and a second preset temperature adjacent to the battery temperature, wherein the first preset temperature is greater than the battery temperature and the second preset temperature is less than the battery temperature;

[0075] Step S13, determining a battery temperature capacity health change trend between the first preset capacity health change trend and the second preset capacity health change trend at the second preset temperature based on the first preset capacity health change trend at the first preset temperature and the second preset capacity health change trend at the second preset temperature;

[0076] Step S14, determining the internal resistance health change trend of the battery temperature between the first preset internal resistance health change trend and the second preset internal resistance health change trend at the second preset temperature based on the first preset internal resistance health change trend.

[0077] It should be noted that if the target preset temperature does not exist in the preset temperature trend database, it indicates that the capacity health change trend and internal resistance health change trend corresponding to the battery temperature do not exist in the preset temperature trend database. The first preset temperature and the second preset temperature are both adjacent to the battery temperature. The battery temperature is between the first preset temperature and the second preset temperature. Among the preset temperatures greater than the battery temperature, the first preset temperature is the preset temperature closest to the battery temperature. Among the preset temperatures less than the battery temperature, the second preset temperature is the preset temperature closest to the battery temperature.

[0078] The absolute value of the difference between the first preset temperature and the second preset temperature is calculated to obtain a first temperature difference, and the absolute value of the difference between the first preset temperature and the battery temperature is calculated to obtain a second temperature difference. The ratio of the second temperature difference to the first temperature difference is used as the adjustment ratio. The capacity health trend can be determined based on the adjustment ratio, the first preset capacity health trend, and the second preset capacity health trend. The internal resistance health trend can also be determined based on the adjustment ratio, the first preset internal resistance health trend, and the second preset internal resistance health trend. This can subsequently improve the accuracy of battery health estimation.

[0079] The adjustment ratio can be the ratio of the second temperature difference to the first temperature difference. The first preset capacity health trend can be adjusted by adjusting the ratio and the second preset capacity health trend, or by adjusting the ratio and the second preset capacity health trend to adjust the first preset capacity health trend, resulting in a capacity health trend. The first preset internal resistance health trend can be adjusted by adjusting the ratio and the second preset internal resistance health trend, or by adjusting the ratio and the second preset internal resistance health trend to adjust the first preset internal resistance health trend, resulting in a internal resistance health trend. Linear interpolation processing can then be performed along a certain gradient to obtain the capacity health trend and internal resistance health trend associated with the battery temperature.

[0080] For example, taking the first preset temperature as t1, the second preset temperature as t2, the battery temperature as tx, the first preset internal resistance health change trend as C1(i), and the second preset internal resistance health change trend as C2(i) as an example, then for each moment i, the internal resistance health change trend Cx(i) of the battery temperature can be expressed as: Cx(i) = C2(i) + [(tx-t2) / (t1-t2)] * [C1(i)-C2(i)]. Wherein, [(tx-t2) / (t1-t2)] can be the adjustment ratio. The first preset capacity health change trend can include a first preset cycle curve and a first preset storage curve, and the second preset capacity health change trend can include a second preset cycle curve and a second preset storage curve; the capacity health change trend can include a cycle curve and a storage curve. Taking the first preset cycle curve as Y1(n), the second preset cycle curve as Y2(n), the first preset storage curve as K1(m), and the second preset storage curve as K2(m) as an example, then for each cycle number n, the cycle curve Yx(n) of the battery temperature can be expressed as: Yx(n) = Y2(n) + [(tx-t2) / (t1-t2)] * [Y1(n)-Y2(n)]. n can be a positive integer. Then, for each storage time length m, the storage curve Kx(m) of the battery temperature can be expressed as Kx(m) = K2(m) + [(tx-t2) / (t1-t2)] * [K1(m)-K2(m)].

[0081] In addition, in other embodiments, if there are multiple preset operating conditions at the first preset temperature and multiple preset operating conditions at the second preset temperature, the current operating condition of the vehicle can be obtained, and a first target operating condition of the operating condition can be determined among the multiple preset operating conditions at the first preset temperature, and a second target operating condition can be determined among the multiple preset operating conditions at the second preset temperature. The preset capacity health change trend and the preset internal resistance health change trend of the first target condition can be used as the first preset capacity health change trend and the first preset internal resistance health change trend, and the preset capacity health change trend and the preset internal resistance health change trend of the second target condition can be used as the second preset capacity health change trend and the second preset internal resistance health change trend.

[0082] When there are multiple preset operating conditions at the first preset temperature and the number of preset operating conditions at the second preset temperature is 1, the first target operating condition can be determined among the multiple preset operating conditions at the first preset temperature, and the preset capacity health change trend and the preset internal resistance health change trend of the first target operating condition can be used as the first preset capacity health change trend and the first preset internal resistance health change trend, and the preset capacity health change trend and the preset internal resistance health change trend of the preset operating condition at the second preset temperature can be used as the second preset capacity health change trend and the second preset internal resistance health change trend.

[0083] When there are multiple preset operating conditions at the second preset temperature and the number of preset operating conditions at the first preset temperature is 1, the second target operating condition of the operating condition can be determined from the multiple preset operating conditions at the second preset temperature, and the preset capacity health change trend and the preset internal resistance health change trend of the second target operating condition can be used as the second preset capacity health change trend and the second preset internal resistance health change trend, and the preset capacity health change trend and the preset internal resistance health change trend of the preset operating condition at the first preset temperature can be used as the first preset capacity health change trend and the first preset internal resistance health change trend.

[0084] When the number of preset operating conditions at the first preset temperature is 1 and the number of preset operating conditions at the second preset temperature is 1, the preset capacity health change trend and the preset internal resistance health change trend of the preset operating condition at the first preset temperature are used as the first preset capacity health change trend and the first preset internal resistance health change trend, and the preset capacity health change trend and the preset internal resistance health change trend of the preset operating condition at the second preset temperature are used as the second preset capacity health change trend and the second preset internal resistance health change trend.

[0085] This embodiment determines the healthy change trend of the internal resistance and the healthy change trend of the capacity of the battery temperature through the linear interpolation method, thereby achieving more accurate acquisition of the trend corresponding to the battery temperature, thereby facilitating the subsequent improvement of the estimation accuracy of the battery health.

[0086] In a possible embodiment, please refer to Figure 2 The battery health estimation method further includes: obtaining a preset temperature trend database, the preset temperature trend database including a preset capacity health change trend and a preset internal resistance health change trend corresponding to a preset temperature, the preset capacity health change trend including a preset cycle curve and a preset storage curve; the step of obtaining the preset temperature trend database may include steps A10 to A30:

[0087] Step A10, performing cyclic charge and discharge tests on the preset battery cells at multiple preset temperatures, respectively, to obtain a preset cycle curve between a preset number of cycles and a preset cycle health at each preset temperature;

[0088] Step A20, performing a storage test on a preset battery cell at each preset temperature to obtain a preset storage curve between a preset storage time and a preset storage health at each preset temperature;

[0089] Step A30 , performing an internal resistance test on a preset battery cell at each preset temperature to obtain a preset internal resistance health change trend between the preset internal resistance and the preset internal resistance health at each preset temperature.

[0090] It should be noted that the model of the preset battery cell is the same as the model of the vehicle battery, so that the preset internal resistance health change trend, preset storage curve and preset cycle curve tested by the preset battery cell are more compatible with the vehicle battery. The cyclic charge and discharge test refers to the cyclic charge and discharge of the preset battery cell and the detection of the preset cycle health after each cycle of charge and discharge. For example, during each cyclic charge and discharge, the preset battery cell can be discharged to the cut-off voltage with a constant current, and the discharge time and current integral value can be recorded to calculate the actual discharge capacity. The actual discharge capacity of the preset battery cell can also be detected by a battery capacity detection device. This embodiment does not make specific restrictions on this. The ratio of the actual discharge capacity to the nominal capacity of the preset battery cell can be used as the preset cycle health.

[0091] A cyclic charge-discharge test is performed at each preset temperature. In this embodiment, multiple preset battery cells may exist, each with its own corresponding preset battery cell, thereby facilitating more accurate determination of the preset cycle curve at the preset temperature. Cyclic charge-discharge tests, storage tests, and internal resistance tests are performed at each preset temperature. A new preset battery cell is used for each new test at each preset temperature, and each preset battery cell uses the same battery model, thereby ensuring the accuracy of the preset storage curve and the preset internal resistance health change trend.

[0092] Exemplarily, performing a storage test at a preset temperature involves placing a preset battery cell at a preset temperature, allowing the preset battery cell to rest without undergoing cyclic charge and discharge cycles, and testing the preset storage health of the preset battery cell at different preset storage durations. During the storage test, the preset battery cell may be subjected to an accelerated aging test to obtain the preset storage health at a longer preset storage duration, thereby improving the comprehensiveness of the preset storage curve. For example, the preset storage health may be the ratio of the current capacity of the preset battery cell at the preset storage duration to the nominal capacity of the preset battery cell, etc., which is not specifically limited in this embodiment.

[0093] Performing an internal resistance test at each preset temperature refers to detecting the preset internal resistance health corresponding to the preset battery cell at different preset internal resistances. For example, when the preset internal resistance of the preset battery cell is Rnow, the preset internal resistance health of the preset battery cell can be (Rend-Rnow) / (Rend-Rbegin), wherein Rend is the internal resistance at the end of the life of the preset battery cell, and Rbegin is the internal resistance when the preset battery cell is first used. The internal resistance test can also include testing the preset internal resistance of the preset battery cell at different usage times. The preset internal resistance at different usage times can be tested through accelerated aging tests, and then the preset internal resistance health change trend includes not only the mapping relationship between the preset internal resistance and the preset internal resistance health, but also the mapping relationship between the preset internal resistance and the preset usage time.

[0094] In other embodiments, multiple preset operating conditions may be determined. Under each preset operating condition, a cyclic charge-discharge test, a storage test, and an internal resistance test are performed on the preset battery cells at each preset temperature. This allows for the generation of a preset cycle curve, a preset storage curve, and a preset internal resistance health trend for each preset temperature under each preset operating condition. That is, each preset temperature may have multiple preset cycle curves, preset storage curves, and preset internal resistance health trends. In other embodiments, the preset battery cells at multiple preset temperatures may be tested directly under a commonly used preset operating condition. For each preset temperature, the corresponding preset cycle curve, preset storage curve, and preset internal resistance health trend may be 1. Commonly used preset operating conditions may include CLTC operating conditions, or may be commonly used operating conditions for the vehicle model in which the vehicle battery is installed. This embodiment does not specifically limit this.

[0095] In a feasible embodiment, step S20 further includes steps S21 to S26:

[0096] Step S21, obtaining the battery's cumulative storage time and battery cycle count from the battery's historical usage data, and obtaining a cycle curve and a storage curve from the capacity health change trend;

[0097] Step S22, obtaining the cycle health corresponding to the number of battery cycles from the cycle curve, and obtaining the storage health corresponding to the accumulated storage time of the battery from the storage curve;

[0098] Step S23: obtaining a cyclic attenuation coefficient and a storage attenuation coefficient, and performing a weighted summation of the cyclic health and the storage health according to the cyclic attenuation coefficient and the storage attenuation coefficient to obtain a first capacity health;

[0099] It should be noted that the cumulative battery storage time represents the length of time the vehicle battery is stationary and not undergoing charge and discharge cycles, while the battery cycle count represents the number of times the vehicle battery undergoes charge and discharge cycles. The capacity health trend includes a cycle curve and a storage curve. The cycle curve includes a mapping relationship between multiple preset cycle counts and their corresponding preset cycle health levels, while the storage curve includes a mapping relationship between multiple preset storage times and their corresponding preset storage health levels.

[0100] The cycle health of the battery can be found in the cycle curve based on the number of cycles, and the storage health corresponding to the cumulative storage time of the battery can be found in the storage curve. The cycle attenuation coefficient can represent the ratio of the battery cycle charge and discharge time to the total usage time of the vehicle battery, and the storage attenuation coefficient can represent the vehicle battery stationary time, that is, the ratio of the battery cumulative storage time to the total usage time. Different cycle charge and discharge times and different cumulative battery storage times have different effects on the vehicle battery capacity. For example, the cycle charge and discharge time of electric vehicles such as taxis is generally longer than the battery stationary time, while the cycle charge and discharge time of private electric vehicles is generally shorter than the battery stationary time. Therefore, the loss on the battery is also different, and the impact on the battery health is also different. Therefore, it is necessary to perform a weighted summation of the cycle health and storage health based on the cycle attenuation coefficient and the storage attenuation coefficient to obtain the first capacity health.

[0101] Exemplarily, the cycle health corresponding to the number of battery cycles is obtained from the cycle curve, and the storage health corresponding to the cumulative storage time of the battery is obtained from the storage curve; the product of the cycle attenuation coefficient and the cycle health is calculated to obtain a first value, the product of the storage attenuation coefficient and the storage health is calculated to obtain a second value, and the sum of the first value and the second value is used as the first capacity health. In other embodiments, the first capacity health can also be directly used as the capacity health. This embodiment improves the accuracy of the first capacity health by obtaining the capacity health change trend corresponding to the battery temperature, rather than determining the capacity health through a fixed capacity health change trend. Because different battery temperatures have different effects on the battery health, this embodiment improves the estimation accuracy of the battery health by considering the effect of the battery temperature on the battery health.

[0102] In other embodiments, the first capacity health can also be determined based on historical capacity health. For example, historical cycle health, historical capacity health, and historical usage duration can be determined from historical battery usage data. The historical cycle health is the cycle health most recently calculated before the vehicle is currently powered on. The historical capacity health is the cycle health most recently calculated before the vehicle is currently powered on. The historical usage duration is the duration between the first use of the vehicle battery and the current power-on. After the vehicle is powered on, the current battery temperature of the vehicle battery can be obtained, and a first duration of the battery temperature can be recorded. The cycle health reduction between the last moment of the historical usage duration and the end of the first duration can be obtained from the battery temperature cycle curve. The difference between the historical cycle health and the cycle health reduction can be used as the cycle health. The storage health reduction between the last moment of the historical usage duration and the end of the first duration can be obtained from the battery temperature storage curve. The difference between the historical storage health and the storage health reduction can be used as the storage health. The cycle attenuation coefficient and the storage attenuation coefficient are then combined to perform a weighted summation of the storage health and cycle health to obtain the first capacity health. For example, the historical usage time of the battery is ta. In the historical usage time ta, there are time periods t1, t2 and t3. The sum of t1, t2 and t3 is equal to ta. The battery temperatures corresponding to t1, t2 and t3 are c1, c2 and c3 respectively. The battery temperatures in the same time period are the same. Then the cycle health corresponding to the end time t1 is the cycle health corresponding to the end time t1 in the cycle curve of c3; the cycle health at the end time t2 is the cycle health of t1 minus the decrease in cycle health between the end time t1 and the end time t2 in the cycle curve of c2; the battery health at the end time t3 is = the cycle health of t2 minus the decrease in cycle health between the end time t2 and the end time t3 in the cycle curve of c3.

[0103] Step S24, obtaining the battery power-up capacity, battery operating time, battery operating current when the vehicle is powered on, and the battery power-down capacity when the vehicle is powered off, and calculating the charge and discharge amount of the vehicle battery within the battery operating time based on the battery operating time and the battery operating current;

[0104] Step S25, calculating the difference between the battery's lower capacity and the battery's upper capacity to obtain a capacity difference, using the ratio of the charge and discharge capacity to the capacity difference as the ampere-hour integrated capacity, and using the ratio of the ampere-hour integrated capacity to the preset nominal capacity of the vehicle battery as the second capacity health indicator;

[0105] Step S26 : Determine the minimum health level between the first capacity health level and the second capacity health level as the capacity health level.

[0106] It should be noted that when the vehicle is powered on, it indicates that the vehicle has begun to be used, and the battery charge capacity represents the capacity at the time the vehicle is powered on. The battery charge capacity can be the battery capacity when the vehicle was last powered off, or the capacity corresponding to the voltage at the time the vehicle was powered on can be found in the preset voltage-capacity mapping relationship between the preset voltage and the preset battery capacity, and this capacity can be used as the power-on capacity. For example, if the duration between the last time the vehicle was powered off and the current time it was powered on is greater than the preset idle time, the battery charge capacity corresponding to the voltage at the time the vehicle was powered on is found in the preset voltage-capacity mapping relationship; if the duration between the last time the vehicle was powered off and the current time it was powered on is less than or equal to the preset idle time, the battery capacity at the time it was last powered off is used as the battery charge capacity.

[0107] The battery operating time can be the duration between the vehicle's power-up and power-down. The battery operating current can be the current after the vehicle is powered on. The battery's reduced capacity can be found in a preset voltage-capacity mapping relationship. The battery's reduced capacity corresponding to the voltage at the time the vehicle was powered off can be found in the preset voltage-capacity mapping relationship. The second capacity health is calculated, while the first capacity health is determined based on the capacity health change trend and historical battery usage data.

[0108] For example, the formula for calculating the second capacity health may be Formula 1:

[0109] SOHr=Q(now) / Qb=[∫Idt / (SOC1-SOC0)] / Qb (Formula 1);

[0110] Where SOHr is the second capacity health indicator, Q(now) is the current capacity of the vehicle battery, Qb is the nominal capacity of the vehicle battery, ∫Idt is the charge and discharge capacity, which is obtained by integrating the battery operating current. SOC0 is the battery charge level, and SOC1 is the battery charge level. ∫Idt / (SOC1-SOC0) is the integrated ampere-hour capacity.

[0111] After determining the first and second capacity healths, the smallest health can be selected as the capacity health, thereby avoiding the situation where a battery with poor battery health due to a high capacity health continues to be used, thereby improving battery safety.

[0112] In a feasible embodiment, step S23 further includes steps S231 and S232:

[0113] Step S231, determining the battery cumulative cycle time and the total usage time of the vehicle battery from the battery history usage data;

[0114] Step S232: The ratio of the accumulated cycle time of the battery to the total usage time is used as the cycle attenuation coefficient, and the ratio of the accumulated storage time of the battery to the total usage time is used as the storage attenuation coefficient.

[0115] It should be noted that the cumulative cycle time of the battery is the total time for the vehicle battery to be cyclically charged and discharged, and the total usage time is the total usage time of the vehicle battery. The total usage time can be the time between the beginning of use of the vehicle battery and the current moment. The sum of the cumulative cycle time of the battery and the cumulative storage time of the battery is equal to the total usage time.

[0116] In other embodiments, the vehicle model of the vehicle battery can be obtained, and the cycle time and storage time of other vehicles with the same vehicle model can be obtained. The cycle time of each vehicle can be counted to obtain the total cycle time. The storage time of each vehicle can be counted to obtain the total storage time. The sum of the total cycle time and the total storage time can be used as the total timer length. The ratio of the total cycle time to the total timer length can be used as the cycle attenuation coefficient, and the ratio of the total storage time to the total timer length can be used as the storage attenuation coefficient. Furthermore, the storage attenuation coefficient and the cycle attenuation coefficient can be determined without the vehicle itself having to record the storage time and cycle time in real time, thereby reducing the operating burden of the vehicle.

[0117] In a feasible embodiment, the internal resistance health change trend includes a mapping relationship between a preset internal resistance and a preset health level, and also includes a mapping relationship between a preset usage time and a preset internal resistance. Step S20 further includes steps B10 to B20:

[0118] Step B10, determining the total usage time of the vehicle battery from the historical battery usage data;

[0119] Step B20: determining a target internal resistance for the total usage time in the internal resistance health change trend, and determining an internal resistance health degree corresponding to the target internal resistance from the internal resistance health change trend.

[0120] It should be noted that the internal resistance health trend includes the mapping relationship between the preset internal resistance and the preset health level, as well as the mapping relationship between the preset usage time and the preset internal resistance. Therefore, the target internal resistance corresponding to the total usage time can be obtained from the internal resistance health trend, and then the internal resistance health level corresponding to the target internal resistance can be obtained from the internal resistance health trend. The total usage time is the duration from the first use of the vehicle battery to the current moment.

[0121] Since the internal resistance health change trend corresponds to the current battery temperature of the vehicle battery, the internal resistance health can be determined more accurately through the internal resistance health change trend, thereby improving the estimation accuracy of the battery health.

[0122] In other embodiments, the internal resistance health can also be determined based on the historical internal resistance health. For example, the historical internal resistance health and the historical usage time can be determined from the historical battery usage data. The historical internal resistance health is the internal resistance health calculated most recently before the vehicle is powered on this time, and the historical usage time is the time between the first use of the vehicle battery and the current power-on. After the vehicle is powered on, the current battery temperature of the vehicle battery can be obtained, the first duration of the battery temperature can be recorded, and the reduction in internal resistance health between the last moment of the historical usage time and the end moment of the first duration can be obtained from the internal resistance health change trend of the battery temperature. The difference between the historical internal resistance health and the reduction in internal resistance health can be used as the internal resistance health. Furthermore, the impact of different battery temperatures on health during historical use can also be taken into account, thereby facilitating improved accuracy in health estimation.

[0123] In a feasible embodiment, the battery health estimation method further includes steps C10 to C20:

[0124] Step C10: Outputting a battery maintenance prompt when the target battery health is greater than a preset health and safety threshold and the target battery health is less than or equal to a preset warning health threshold;

[0125] Step C20: Outputting a battery life end prompt when the target battery health is less than or equal to a preset health and safety threshold;

[0126] Among them, the preset warning health threshold is greater than the preset health safety threshold.

[0127] It should be noted that the preset health and safety threshold can be 70% or 80%, etc., and this embodiment does not specifically limit this. When the target battery health is less than the preset health and safety threshold, it means that the battery health is too low and it is not recommended to continue using it. If it is continued to be used, there will be a risk of lithium precipitation and fire. The battery life end prompt indicates that the vehicle battery has reached the end of its service life and it is not recommended to continue using it. The battery maintenance prompt is used to remind the user that the vehicle battery life is about to end and the vehicle battery needs maintenance.

[0128] The preset warning health threshold is lower than the preset health and safety threshold. When the target battery health is lower than or equal to the preset warning health threshold and higher than the preset health and safety threshold, the user is prompted to perform battery maintenance to extend battery life. For example, the preset warning health threshold may be 85%, 86%, etc., and this embodiment does not specifically limit this.

[0129] In other embodiments, a battery maintenance recommendation is output when the number of sudden changes in the target battery health is detected to be greater than a preset threshold. The preset threshold can be determined based on actual conditions, for example, it can be a value of 5 or 6, and this embodiment does not impose a specific limitation on this. A sudden change in target battery health refers to a difference between the target battery health and the historical target battery health being greater than a preset difference. The preset difference can be determined based on actual conditions and is not specifically limited in this embodiment. The historical target battery health can be the target battery health calculated at the previous time step of the target battery health.

[0130] When it is detected that the number of sudden changes in the target battery health exceeds a preset threshold, battery usage data corresponding to each sudden change in the target battery health is obtained. Battery usage data may include user habits regarding vehicle battery usage. Target user behaviors whose frequency exceeds a preset high-frequency threshold may be identified from each battery usage data set. Battery maintenance recommendations may include recommendations to reduce the target user behaviors. For example, the target user behavior may be a low vehicle battery or frequent fast charging, etc., although this embodiment does not specifically limit this.

[0131] For a better understanding of this embodiment, please refer to Figure 3 The process of this embodiment is briefly described as follows: Step X10: Start; Step X20: Detect the battery temperature; Step X30: Obtain the cycle curve, storage curve, and internal resistance health change trend corresponding to the battery temperature; Step X31a: Obtain the cycle health corresponding to the number of battery cycles in the cycle curve, and obtain the storage health corresponding to the accumulated storage time in the storage curve. Then, Step X32 is executed: SOHa = Cycle Health * Cycle Attenuation Coefficient j1% + Storage Health * Storage Attenuation Coefficient j2%. Both the Cycle Attenuation Coefficient and the Storage Attenuation Coefficient are less than 1. SOHa represents the capacity health, which can be directly calculated as Cycle Health * Cycle Attenuation Coefficient j1% + Storage Health * Storage Attenuation Coefficient j2%. After step X30, step X31b is performed: the internal resistance health SOHb is obtained from the internal resistance health change trend. Then, step X40 can be performed: SOHm = min(SOHa, SOHb), where SOHm is the target battery health, and min(SOHa, SOHb) represents the smaller of the capacity health SOHa and the internal resistance health SOHb. Step X50: SOHm is less than the preset health and safety threshold; that is, it is determined whether the target battery health is less than or equal to the preset health and safety threshold. If so, step X60 is performed: a battery end-of-life notification is output. If the target battery health is greater than the preset health and safety threshold, the process returns to step X20.

[0132] This application also provides a battery health estimation device, please refer to Figure 4 , the device comprises:

[0133] An acquisition module 10 is used to obtain the battery temperature and battery history data of the vehicle battery in the vehicle, and obtain the capacity health change trend and the internal resistance health change trend based on the battery temperature;

[0134] An estimation module 20 is configured to estimate the capacity health of the vehicle battery based on the capacity health change trend and the battery's historical usage data, and to estimate the internal resistance health based on the internal resistance health change trend and the battery's historical usage data;

[0135] The determination module 30 is configured to determine the minimum health state among the capacity health state and the internal resistance health state as the target health state of the vehicle battery.

[0136] The battery health estimation device provided in the embodiments of this application utilizes the battery health estimation method described in the aforementioned embodiments, aiming to address the technical issue of low accuracy in vehicle battery health estimation. Compared to the prior art, the battery health estimation method provided in the embodiments of this application achieves the same beneficial effects as those provided in the aforementioned embodiments. Other technical features of the battery health estimation device are the same as those disclosed in the aforementioned embodiments and are not further detailed here.

[0137] The present application provides a vehicle, which includes a vehicle body, a vehicle battery and a controller, wherein the controller and the vehicle battery are both arranged in the vehicle body, and the controller includes at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the battery health estimation method in the above-mentioned embodiment one.

[0138] Reference below Figure 5 , which shows a schematic diagram of the structure of an electronic device suitable for implementing the embodiments of the present application. The electronic devices in the embodiments of the present application may include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), in-vehicle terminals (such as in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 5 The vehicle shown is merely an example and should not limit the functionality and scope of use of the embodiments of the present application.

[0139] like Figure 5As shown, the vehicle may include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes based on programs stored in a read-only memory 1002 or programs loaded from a storage device 1003 into a random access memory 1004. Random access memory 1004 also stores various programs and data required for vehicle operation. Processing device 1001, read-only memory 1002, and random access memory 1004 are interconnected via a bus 1005. An input / output interface 1006 is also connected to the bus. Typically, the following systems may be connected to input / output interface 1006: input devices 1007 including, for example, a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speakers, and vibrator; storage device 1003 including, for example, a magnetic tape or hard disk; and communication device 1009. Communication device 1009 may allow the vehicle to communicate with other devices wirelessly or wired to exchange data. Although the figures show a vehicle with various systems, it should be understood that it is not required to implement or have all of the systems shown. More or fewer systems may be implemented or have alternatively.

[0140] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device 1003, or installed from a read-only memory 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are performed.

[0141] The vehicle provided in this application utilizes the battery health estimation method described in the aforementioned embodiment, resolving the technical issue of low accuracy in vehicle battery health estimation. Compared to the prior art, the vehicle provided in this application achieves the same beneficial effects as the battery health estimation method described in the aforementioned embodiment. Other technical features of this vehicle are the same as those disclosed in the aforementioned embodiment and are not further detailed here.

[0142] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0143] The above are only specific embodiments of the present application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0144] This embodiment provides a computer-readable storage medium having computer-readable program instructions stored thereon, and the computer-readable program instructions are used to execute the battery health estimation method in the above-mentioned embodiment 1.

[0145] The computer-readable storage medium provided in the embodiment of the present application can be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor devices, equipment or devices, or any combination thereof. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable EPROM (Electrical Programmable Read Only Memory, read-only memory) or flash memory, an optical fiber, a portable compact disk CD-ROM (compact discread-only memory, read-only memory), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this embodiment, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in combination with an instruction execution device, device or device. The program code contained on the computer-readable storage medium can be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency, radio frequency) and the like, or any suitable combination thereof.

[0146] The computer-readable storage medium may be included in the vehicle, or may exist independently without being installed in the vehicle.

[0147] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the vehicle, the vehicle is enabled to: obtain the battery temperature and battery historical usage data of the vehicle battery in the vehicle, and obtain the capacity health change trend and internal resistance health change trend based on the battery temperature; estimate the capacity health of the vehicle battery based on the capacity health change trend and the battery historical usage data, and estimate the internal resistance health based on the internal resistance health change trend and the battery historical usage data; determine the minimum health between the capacity health and the internal resistance health as the target health of the vehicle battery.

[0148] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a LAN (local area network) or WAN (wide area network), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0149] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the equipment, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based device that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0150] The modules involved in the embodiments described in this disclosure may be implemented in software or hardware, wherein the name of a module does not necessarily limit the unit itself.

[0151] The computer-readable storage medium provided in the embodiments of this application stores computer-readable program instructions for executing the aforementioned battery health estimation method, aiming to address the technical issue of low accuracy in vehicle battery health estimation. Compared to the prior art, the computer-readable storage medium provided in the embodiments of this application offers the same benefits as the battery health estimation method provided in the aforementioned embodiments, and will not be further elaborated here.

[0152] An embodiment of the present application also provides a computer program product, including a computer program, which implements the steps of the battery health estimation method as described above when the computer program is executed by a processor.

[0153] The computer program product provided in the embodiments of this application is intended to address the technical issue of low accuracy in vehicle battery health estimation. Compared to the prior art, the computer program product provided in the embodiments of this application has the same beneficial effects as the battery health estimation method provided in the aforementioned embodiments, and will not be further elaborated here.

[0154] The above are only preferred embodiments of the embodiments of the present application, and do not limit the patent scope of the embodiments of the present application. Any equivalent structure or equivalent process transformation made using the contents of the description and drawings of the embodiments of the present application, or directly or indirectly applied in other related technical fields, are also included in the patent processing scope of the embodiments of the present application.

Claims

1. A battery health estimation method, characterized in that: The method comprises: Obtaining a battery temperature and historical battery usage data of a vehicle battery in the vehicle, and obtaining a capacity health change trend and an internal resistance health change trend based on the battery temperature; estimating the capacity health of the vehicle battery based on the capacity health change trend and the battery historical usage data, and estimating the internal resistance health based on the internal resistance health change trend and the battery historical usage data; A minimum health state between the capacity health state and the internal resistance health state is determined as a target health state of the vehicle battery.

2. The battery health estimation method according to claim 1, wherein: The step of obtaining the capacity health change trend and the internal resistance health change trend according to the battery temperature includes: If a target preset temperature corresponding to the battery temperature exists in a preset temperature trend database, the target capacity health change trend and target internal resistance health change trend of the target preset temperature obtained from the preset temperature trend database are used as the capacity health change trend and internal resistance health change trend of the battery temperature; If the target preset temperature does not exist in the preset temperature trend database, searching the preset temperature trend database for a first preset temperature and a second preset temperature adjacent to the battery temperature, wherein the first preset temperature is greater than the battery temperature and the second preset temperature is less than the battery temperature; Determining a capacity health change trend of the battery temperature between the first preset capacity health change trend and the second preset capacity health change trend according to a first preset capacity health change trend at the first preset temperature and a second preset capacity health change trend at the second preset temperature; Based on a first preset internal resistance health change trend at the first preset temperature and a second preset internal resistance health change trend at the second preset temperature, the internal resistance health change trend of the battery temperature is determined between the first preset internal resistance health change trend and the second preset internal resistance health change trend.

3. The battery health estimation method according to claim 1, wherein: The preset temperature trend database includes a preset capacity health change trend and a preset internal resistance health change trend corresponding to a preset temperature, wherein the preset capacity health change trend includes a preset cycle curve and a preset storage curve; The method further comprises: Performing cyclic charge and discharge tests on the preset battery cells at multiple preset temperatures to obtain a preset cycle curve between a preset number of cycles and a preset cycle health at each preset temperature; Performing a storage test on a preset battery cell at each preset temperature to obtain a preset storage curve between a preset storage time and a preset storage health at each preset temperature; An internal resistance test is performed on a preset battery cell at each preset temperature to obtain a preset internal resistance health change trend between the preset internal resistance and the preset internal resistance health at each preset temperature.

4. The battery health estimation method according to claim 1, wherein: The step of estimating the capacity health of the vehicle battery based on the capacity health change trend and the battery historical usage data includes: Obtaining the battery's cumulative storage time and battery cycle count from the battery's historical usage data, and obtaining a cycle curve and a storage curve from the capacity health change trend; Obtaining the cycle health corresponding to the number of battery cycles from the cycle curve, and obtaining the storage health corresponding to the accumulated storage time of the battery from the storage curve; Obtaining a cyclic attenuation coefficient and a storage attenuation coefficient, and performing a weighted summation of the cyclic health and the storage health according to the cyclic attenuation coefficient and the storage attenuation coefficient to obtain a first capacity health; Obtaining the battery's charged capacity, battery operating time, and battery operating current when the vehicle is powered on, and the battery's uncharged capacity when the vehicle is powered off, and calculating, based on the battery operating time and the battery operating current, the charge and discharge amount of the vehicle battery within the battery operating time; calculating a difference between the lower capacity of the battery and the upper capacity of the battery to obtain a capacity difference, using a ratio of the charge and discharge capacity to the capacity difference as an ampere-hour integrated capacity, and using a ratio of the ampere-hour integrated capacity to a preset nominal capacity of the vehicle battery as a second capacity health indicator; A minimum health level between the first capacity health level and the second capacity health level is determined as the capacity health level.

5. The battery health estimation method according to claim 4, wherein: The steps of obtaining the cyclic attenuation coefficient and storing the attenuation coefficient include: Determining the accumulated battery cycle time and the total usage time of the vehicle battery from the historical battery usage data; The ratio of the accumulated cycle time of the battery to the total usage time is used as the cycle attenuation coefficient, and the ratio of the accumulated storage time of the battery to the total usage time is used as the storage attenuation coefficient.

6. The battery health estimation method according to claim 1, wherein: The internal resistance health change trend includes a mapping relationship between a preset internal resistance and a preset health level, and also includes a mapping relationship between a preset usage time and a preset internal resistance; The step of estimating the internal resistance health status based on the internal resistance health change trend and the battery historical usage data includes: determining a total usage time of the vehicle battery from the historical battery usage data; The target internal resistance of the total usage time is determined from the internal resistance health change trend, and the internal resistance health degree corresponding to the target internal resistance is determined from the internal resistance health change trend.

7. The battery health estimation method according to any one of claims 1 to 6, characterized in that: The battery health estimation method further includes: Outputting a battery maintenance prompt when the target battery health is greater than a preset health and safety threshold and the target battery health is less than or equal to a preset warning health threshold; When the target battery health is less than or equal to a preset health and safety threshold, outputting a battery life end prompt; Among them, the preset warning health threshold is greater than the preset health safety threshold.

8. A battery health estimation device, characterized in that: The device comprises: an acquisition module, configured to acquire a battery temperature and historical battery usage data of a vehicle battery in the vehicle, and acquire a capacity health change trend and an internal resistance health change trend based on the battery temperature; an estimating module, configured to estimate the capacity health of the vehicle battery based on the capacity health change trend and the battery historical usage data, and to estimate the internal resistance health based on the internal resistance health change trend and the battery historical usage data; A determination module is configured to determine a minimum health state between the capacity health state and the internal resistance health state as a target health state of the vehicle battery.

9. A vehicle, characterized in that: The vehicle includes a vehicle body, a vehicle battery and a controller, wherein the controller and the vehicle battery are both arranged in the vehicle body, and the controller is used to execute the steps of implementing the battery health estimation method according to any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, on which a program for implementing the battery health estimation method is stored. The program for implementing the battery health estimation method is executed by a processor to implement the steps of the battery health estimation method according to any one of claims 1 to 7.

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