Method, apparatus and storage medium for determining remaining available energy of battery

Abstract

The application discloses a kind of determination method, device and storage medium of battery remaining available energy.Therein, the method comprises: obtaining the sampling information of battery in vehicle and the navigation information of vehicle, and sending sampling information and navigation information to cloud computing unit;Determine the first available discharge energy value of battery based on sampling information and navigation information, wherein the first available discharge energy value is used to represent the remaining available discharge energy of battery;Receive the second available discharge energy value fed back by cloud computing unit, wherein the second available discharge energy value is used to represent the remaining available discharge energy of battery determined by cloud computing unit based on sampling information and navigation information;The first available discharge energy value and the second available discharge energy value are fused to obtain the remaining available discharge energy value of battery, wherein the remaining available discharge energy value is used to represent the remaining available discharge energy of battery.The application solves the technical problem of low estimation accuracy of battery remaining available discharge energy.

Description

Technical Field

[0001] This invention relates to the field of vehicle technology, and more specifically, to a method, apparatus, and storage medium for determining the remaining usable energy of a battery. Background Technology

[0002] Electric vehicles are powered by batteries, but the remaining energy (State of Energy, SOE) of a battery cannot be directly measured and is affected by many factors. Therefore, it is difficult to accurately estimate the remaining usable energy of the battery, resulting in inaccurate estimates of the driving range of electric vehicles and causing range anxiety for passengers.

[0003] Currently, the main methods for estimating the remaining usable energy of a battery include: offline lookup table method, power integration method, closed-loop observation method, neural network method, SOE estimation based on future voltage prediction, and SOE estimation based on big data. Among these, the offline lookup table method, power integration method, and closed-loop observation method can only perform theoretical estimations and have certain errors. The neural network method has poor adaptability and can only be used within the data training range. Moreover, the model is complex and the computational load is large. Although the SOE estimation methods based on future voltage prediction and SOE estimation based on big data consider the influence of factors such as future operating conditions and temperature, and the estimation accuracy is relatively high, the difficulty in accurately predicting future operating conditions is the main factor affecting the prediction accuracy.

[0004] There is currently no effective solution to the technical problem of low accuracy in estimating the remaining usable discharge energy of the battery. Summary of the Invention

[0005] This invention provides a method, apparatus, and storage medium for determining the remaining usable energy of a battery, thereby at least addressing the technical problem of low accuracy in estimating the remaining usable discharge energy of a battery.

[0006] According to one aspect of the present invention, a method for determining the remaining usable energy of a battery is provided. The method may include: acquiring sampling information of a battery in a vehicle and navigation information of the vehicle, and sending the sampling information and navigation information to a cloud computing unit, wherein the sampling information includes multiple physical parameters of the battery, and the navigation information includes the current location information and target location information of the vehicle; determining a first usable discharge energy value of the battery based on the sampling information and navigation information, wherein the first usable discharge energy value is used to characterize the remaining usable discharge energy of the battery; receiving a second usable discharge energy value of the battery fed back by the cloud computing unit, wherein the second usable discharge energy value is used to characterize the remaining usable discharge energy of the battery determined by the cloud computing unit based on the sampling information and navigation information; fusing the first usable discharge energy value and the second usable discharge energy value to obtain a remaining usable discharge energy value of the battery, wherein the remaining usable discharge energy value is used to characterize the remaining usable discharge energy of the battery.

[0007] Optionally, the remaining usable discharge energy of the battery is associated with the battery's terminal voltage and state of charge (SOC). A first usable discharge energy value is determined based on sampling information and navigation information, including: determining the battery's terminal voltage based on sampling information and navigation information, and determining the battery's SOC based on sampling information. The SOC includes the battery's current SOC and its future SOC. The current SOC characterizes the battery's SOC in the current time period, and the future SOC characterizes the battery's SOC in a future time period. The first usable discharge energy value is determined based on the battery's terminal voltage, SOC, and a preset formula for calculating usable discharge energy.

[0008] Optionally, determining the battery terminal voltage based on sampling information and navigation information includes: determining a first estimated power of the battery based on navigation information, and determining a second estimated power of the battery based on the future state of charge and the future temperature of the battery, wherein the first estimated power is the power of the battery during the process of the vehicle traveling from the current position to the target position, and the second estimated power is the power of the battery from the time the vehicle reaches the target position until the battery reaches the discharge cutoff condition; the first estimated power and the second estimated power are respectively input into the battery model for estimation to obtain the first terminal voltage of the battery corresponding to the first estimated power and the second terminal voltage of the battery corresponding to the second estimated power.

[0009] Optionally, determining the first estimated power of the battery based on navigation information includes: determining the road conditions the vehicle travels through from its current location to its target location based on navigation information; determining the battery power when the vehicle travels through the road conditions based on the road conditions and the battery power corresponding to each road condition stored in history, and determining the battery power as the first estimated power of the battery.

[0010] Optionally, determining the state of charge (SOC) of the battery based on the sampled information includes: determining the current SOC of the battery based on the sampled information and a pre-estimation method, wherein the pre-estimation method includes at least one of the open-circuit voltage correction method, the ampere-hour integration method, and the Kalman filtering method; and determining the future SOC of the battery based on the current SOC of the battery and the ampere-hour integration method.

[0011] Optionally, determining that the battery has reached the discharge cutoff condition includes: determining that the battery has reached the discharge cutoff condition in response to the battery's terminal voltage being the battery's operating voltage in the vehicle's limp-home mode; and determining that the battery has reached the discharge cutoff condition in response to the battery's remaining usable capacity, as represented by its state of charge, reaching a minimum value.

[0012] Optionally, the first available discharge energy value and the second available discharge energy value are fused to obtain the remaining available discharge energy value of the battery, including: determining the weights corresponding to the first available discharge energy value and the second available discharge energy value based on a pre-set weight calculation formula; and adding the product of the first available discharge energy value and the weight corresponding to the first available discharge energy value and the product of the second available discharge energy value and the weight corresponding to the second available discharge energy value to obtain the available discharge energy value of the battery.

[0013] According to another aspect of the present invention, a device for determining the remaining usable energy of a battery is also provided, comprising: an acquisition unit, configured to acquire sampling information of a battery in a vehicle and navigation information of the vehicle, and send the sampling information and navigation information to a cloud computing unit, wherein the sampling information includes multiple physical parameters of the battery, and the navigation information includes the current location information of the vehicle and the target location information of the vehicle; a determination unit, configured to determine a first usable discharge energy value of the battery based on the sampling information and the navigation information, wherein the first usable discharge energy value is used to characterize the remaining usable discharge energy of the battery; a receiving unit, configured to receive a second usable discharge energy value of the battery fed back by the cloud computing unit, wherein the second usable discharge energy value is used to characterize the remaining usable discharge energy of the battery determined by the cloud computing unit based on the sampling information and the navigation information; and a fusion unit, configured to fuse the first usable discharge energy value and the second usable discharge energy value to obtain a remaining usable discharge energy value of the battery, wherein the remaining usable discharge energy value is used to characterize the remaining usable discharge energy of the battery.

[0014] According to another aspect of the present invention, a computer-readable storage medium is also provided. The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to perform the method for determining the remaining usable battery energy according to the embodiments of the present invention.

[0015] According to another aspect of the present invention, a processor is also provided. The processor is used to run a program, wherein the program executes the method for determining the remaining usable battery energy according to the embodiments of the present invention.

[0016] In this embodiment of the invention, sampling information of the battery in the vehicle and navigation information of the vehicle can be acquired, and the sampling information and navigation information can be sent to the cloud computing unit. The sampling information includes multiple physical parameters of the battery, and the navigation information includes the current location information and the target location information of the vehicle. A first available discharge energy value of the battery is determined based on the sampling information and navigation information, wherein the first available discharge energy value is used to characterize the remaining available discharge energy of the battery. A second available discharge energy value of the battery is received from the cloud computing unit, wherein the second available discharge energy value is used to characterize the remaining available discharge energy of the battery determined by the cloud computing unit based on the sampling information and navigation information. The first available discharge energy value and the second available discharge energy value are fused to obtain the remaining available discharge energy value of the battery, wherein the remaining available discharge energy value is used to characterize the remaining available discharge energy of the battery. In other words, in this embodiment of the invention, the first available discharge energy value of the battery estimated by the vehicle and the second available discharge energy value estimated by the cloud computing unit can be fused together to calculate the remaining available discharge energy of the battery. Compared with predicting the remaining available discharge energy of the battery solely through the vehicle or solely through the cloud, this method of combining the prediction results from the vehicle and the cloud to obtain the remaining available energy of the battery can improve the prediction accuracy, thereby improving the accuracy of the vehicle's remaining range estimation, reducing user range anxiety, solving the technical problem of low estimation accuracy of the remaining available discharge energy of the battery, and achieving the technical effect of improving the prediction accuracy of the remaining available discharge energy of the battery, and improving vehicle safety and comfort. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0018] Figure 1 This is a flowchart of a method for determining the remaining usable energy of a battery according to an embodiment of the present invention;

[0019] Figure 2 This is a schematic diagram of a voltage sequence spectrum according to an embodiment of the present invention;

[0020] Figure 3 This is a schematic diagram of a vehicle terminal unit according to an embodiment of the present invention;

[0021] Figure 4 This is a schematic diagram of a cloud computing unit according to an embodiment of the present invention;

[0022] Figure 5 This is a schematic diagram of the framework of a battery remaining usable energy estimation method provided by the present invention;

[0023] Figure 6 This is a schematic diagram of a device for determining the remaining usable energy of a battery according to an embodiment of the present invention. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] Example 1

[0027] According to an embodiment of the present invention, an embodiment of a method for determining the remaining usable energy of a battery is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0028] Figure 1 This is a flowchart of a method for determining the remaining usable energy of a battery according to an embodiment of the present invention, such as... Figure 1 As shown, the method may include the following steps:

[0029] Step S101: Obtain the sampling information of the battery in the vehicle and the navigation information of the vehicle, and send the sampling information and navigation information to the cloud computing unit. The sampling information includes multiple physical parameters of the battery, and the navigation information includes the current location information of the vehicle and the target location information of the vehicle.

[0030] In the technical solution provided in step S101 of the present invention, the vehicle can sample battery-related physical parameters in real time to obtain sampling information. The sampling information includes multiple physical parameters, such as battery voltage, current, and temperature. In addition, the vehicle's navigation system can acquire the vehicle's navigation information, which may include the vehicle's current location information and the target location information corresponding to the destination the vehicle wants to reach. After acquiring the battery's sampling information and the vehicle's navigation information, the vehicle can calculate the remaining usable energy of the battery based on the acquired information. Furthermore, the vehicle can also send the acquired sampling information and navigation information to a cloud computing unit. After receiving the sampling information and navigation information sent by the vehicle, the cloud computing unit can also calculate the remaining usable energy of the battery based on the received information.

[0031] Step S102: Determine the first available discharge energy value of the battery based on the sampling information and navigation information, wherein the first available discharge energy value is used to characterize the remaining available discharge energy of the battery.

[0032] In the technical solution provided by step S102 of the present invention, after obtaining the sampling information and navigation information, the vehicle can determine the first available discharge energy value of the battery based on the sampling information and navigation information, wherein the first available discharge energy value is used to characterize the remaining available discharge energy of the battery.

[0033] Optionally, since the battery's available discharge energy is related to the battery's terminal voltage and state of charge (SOC), and the change in the battery's terminal voltage depends on the battery's operating power, SOC, and operating temperature, the battery's operating power, SOC, and operating temperature can be predicted in the future. Then, based on the predicted future operating power, future SOC, and future operating temperature, the battery's terminal voltage can be predicted, and finally, based on the predicted battery terminal voltage, future SOC, and battery discharge cutoff conditions, the remaining available discharge energy of the battery can be determined.

[0034] Optionally, the prediction of future battery power can be divided into two stages. The first stage is the battery power prediction from the vehicle's current location to its target location, and the second stage is the battery power prediction from the time the vehicle reaches its destination until the battery reaches its discharge cutoff condition. The battery power in the first stage can be determined based on the road conditions along the route the vehicle takes from its current location to its target location. Due to the uncertainty of road conditions, the battery power in the second stage can be determined based on the battery discharge power spectrum.

[0035] For example, as described above, the navigation information obtained by the vehicle includes the vehicle's current location and target location. It should be noted that the vehicle's navigation information may also include the road conditions the vehicle will encounter on its journey from the current location to the target location, such as highway conditions, urban conditions, suburban conditions, and mountain conditions. Based on this, when estimating the battery power in the first stage, the order in which the vehicle encounters each road condition can be determined according to the navigation information. For example, the vehicle will encounter urban conditions, suburban conditions, and highway conditions in sequence on its journey from the current location to the target location. After determining the road conditions the vehicle will encounter, the battery power of the vehicle during each road condition can be determined according to the historically stored correspondence between each road condition and the battery power. Regarding the power prediction of the battery in the second stage, due to the uncertainty of the road conditions after the vehicle reaches its destination, the future SOC and future temperature of the battery can be predicted based on the sampling information. Then, based on the predicted future SOC and future temperature of the battery, the predicted power of the battery in the second stage can be determined from the battery discharge power spectrum obtained from the pre-test. It should be noted that the battery discharge power spectrum includes the correspondence between the battery SOC, battery temperature and battery power.

[0036] Optionally, the battery SOC includes the current SOC and the future SOC. The current SOC represents the percentage of the battery's current remaining usable capacity relative to its total capacity, while the future SOC represents the percentage of the battery's remaining usable capacity relative to its total capacity over a future time period. The current SOC can be estimated based on sampled information using various methods such as open-circuit voltage correction, ampere-hour integration, or Kalman filtering. The future SOC can be determined using ampere-hour integration based on a pre-set SOC sequence interval and the current SOC.

[0037] Optionally, for the prediction of the future temperature of the battery, the battery temperature change rate can be determined first based on the historically collected battery temperature, and then the future temperature of the battery can be determined based on the current temperature of the battery and the battery temperature change rate.

[0038] Optionally, after estimating the future SOC and future temperature of the battery, the estimated power of the battery in the second stage can be determined using the battery discharge power spectrum obtained from the preliminary test.

[0039] Optionally, after estimating the battery power, battery SOC, and battery temperature for each future stage, the future terminal voltage can be predicted based on the estimated battery power, battery SOC, and battery temperature and a pre-determined battery model.

[0040] Optionally, after estimating the battery terminal voltage and battery SOC for each future stage, a first available discharge energy value of the battery can be determined based on a preset formula for calculating available discharge energy. This first available discharge energy value can be used to characterize the remaining available discharge energy of the battery.

[0041] Step S103: Receive the second available discharge energy value of the battery fed back by the cloud computing unit, wherein the second available discharge energy value is used to characterize the remaining available discharge energy of the battery determined by the cloud computing unit based on sampling information and navigation information.

[0042] In the technical solution provided by step S103 of the present invention, as can be seen from the description of step S101 above, after the vehicle obtains the battery sampling information and the vehicle navigation information, it also sends the obtained information to the cloud computing unit. After receiving the information, the cloud computing unit can determine the second available discharge energy value of the battery based on the received sampling information and navigation information, and feed back the determined second available energy value to the vehicle. The vehicle can receive the second available discharge energy value fed back by the cloud computing unit. The second remaining available energy value can be used to characterize the remaining available discharge energy of the battery determined by the cloud computing unit based on the sampling information and navigation information.

[0043] Optionally, the cloud computing unit is equipped with an available discharge energy estimation model, which is pre-trained using offline charge and discharge data of the power battery assembly. Based on this, when the cloud computing unit receives sampling information and navigation information, it can use the available discharge energy estimation model to clean the received data and remove invalid data, thereby reducing the storage space occupied by the cloud computing unit.

[0044] Optionally, after cleaning the data, the cloud computing unit's available discharge energy estimation model can obtain effective data, and then estimate the battery's available discharge energy based on the cleaned effective data to obtain a second available discharge energy value. After obtaining the second available discharge energy value, the cloud computing unit can feed the second available discharge energy value back to the vehicle, and the vehicle can receive the second available discharge energy value fed back by the cloud computing unit.

[0045] Optionally, after obtaining the second available discharge energy value, the cloud computing unit can also update the model parameters of the available discharge energy estimation model based on the data received this time, so as to expand the applicability of the model.

[0046] Step S104: The first available discharge energy value and the second available discharge energy value are fused to obtain the remaining available discharge energy value of the battery, wherein the remaining available discharge energy value is used to characterize the remaining available discharge energy of the battery.

[0047] In the technical solution provided by step S104 of the present invention, after the vehicle determines the first available discharge energy value of the battery and receives the second available discharge energy value of the battery fed back by the cloud computing unit, the first available discharge energy value and the second available discharge energy value can be fused to obtain the remaining available discharge energy value of the battery, wherein the remaining available discharge energy value is used to characterize the remaining available discharge energy of the battery.

[0048] Optionally, the vehicle can determine the weights of the first available discharge energy value and the second available discharge energy value based on future operating conditions, and then add the product of the first available discharge energy value and its weight to the product of the second available discharge energy value and its weight to obtain the remaining available discharge energy value of the vehicle battery.

[0049] In steps S101 to S104 above, the first available discharge energy value of the battery estimated by the vehicle and the second available discharge energy value estimated by the cloud computing unit can be fused together to calculate the remaining available discharge energy of the battery. Compared with obtaining the remaining available discharge energy of the battery by predicting solely from the vehicle or solely from the cloud, this method of combining the prediction results from the vehicle and the cloud to obtain the remaining available energy of the battery can improve the prediction accuracy, thereby improving the accuracy of vehicle remaining range estimation, reducing user range anxiety, solving the technical problem of low estimation accuracy of battery remaining available discharge energy, and achieving the technical effect of improving the prediction accuracy of battery remaining available discharge energy and improving vehicle safety and comfort.

[0050] The method described in this embodiment will be further described below.

[0051] As an optional embodiment, step S102, determining the first available discharge energy value of the battery based on sampling information and navigation information, includes: determining the battery's terminal voltage based on sampling information and navigation information, and determining the battery's state of charge based on sampling information, wherein the state of charge includes the battery's current state of charge and the battery's future state of charge, the current state of charge being used to characterize the battery's state of charge in the current time period, and the future state of charge being used to characterize the battery's state of charge in a future time period; determining the first available discharge energy value of the battery based on the battery's terminal voltage, the battery's state of charge, and a preset formula for calculating available discharge energy.

[0052] In this embodiment, since the remaining usable discharge energy of the battery is related to the battery's terminal voltage and state of charge (SOC), and since the battery's terminal voltage is affected by battery-related physical parameters and navigation information, and the battery's SOC is affected by battery-related physical parameters, the battery's terminal voltage can be determined first based on sampling information and navigation information, and the battery's SOC can be determined based on sampling information. The SOC includes the battery's current SOC and the battery's future SOC. The current SOC is used to characterize the battery's SOC in the current time period, and the future SOC is used to characterize the battery's SOC in the future time period.

[0053] Optionally, since the change in battery terminal voltage depends on the battery's operating power, battery SOC, and battery operating temperature, the battery's operating power, SOC, and operating temperature can be estimated in the future. Then, the battery terminal voltage can be estimated based on the estimated future operating power, future SOC, and future operating temperature.

[0054] Optionally, a first estimated power of the battery can be determined based on navigation information, and a second estimated power of the battery can be determined based on the future state of charge and the future temperature of the battery. The first estimated power is the power of the battery during the process of the vehicle traveling from the current position to the target position, and the second estimated power is the power of the battery from the time the vehicle reaches the target position until the battery reaches the discharge cutoff condition.

[0055] For example, when determining the initial estimated power of the battery, the road conditions along the route the vehicle will take from its current location to the target location can be determined first based on navigation information. Then, based on the road conditions and the battery power corresponding to each historically stored road condition, the battery power for each road condition along the route can be determined. For instance, the vehicle will sequentially pass through urban, suburban, and highway conditions along the route. After determining the road conditions along the route, the battery power for each road condition along the route can be determined based on the historically stored correspondence between road conditions and battery power. The determined battery power for each road condition is then used as the initial estimated power of the battery.

[0056] Optionally, regarding the estimation of battery power from the moment the vehicle arrives at the target location until the battery reaches the discharge cutoff condition, due to the uncertainty of road conditions after the vehicle arrives at the destination, it is no longer possible to determine the battery power based on road conditions. Therefore, the battery power estimation for the period from the moment the vehicle arrives at the destination until the battery reaches the cutoff condition can be determined based on a battery discharge power spectrum. This battery discharge power spectrum contains the correspondence between battery SOC, battery temperature, and battery power. Based on this, the battery SOC and battery temperature after the vehicle arrives at the destination can be predicted first, and then the battery power can be found from the battery discharge power spectrum based on the predicted battery SOC and battery temperature.

[0057] Optionally, the battery SOC includes the current SOC and the future SOC. The current SOC represents the percentage of the battery's current remaining usable capacity relative to its total capacity, while the future SOC represents the percentage of the battery's remaining usable capacity relative to its total capacity over a future time period. The current SOC can be estimated based on sampled information using various methods such as open-circuit voltage correction, ampere-hour integration, or Kalman filtering. The future SOC can be determined using ampere-hour integration based on a pre-set SOC sequence interval and the current SOC.

[0058] Optionally, for the prediction of the future temperature of the battery, the battery temperature change rate can be determined first based on the historically collected battery temperature, and then the future temperature of the battery can be determined based on the current temperature of the battery and the battery temperature change rate.

[0059] Optionally, after estimating the battery's SOC and temperature, the estimated power of the battery can be determined from the battery discharge power spectrum based on the estimated battery SOC and temperature.

[0060] Optionally, after estimating the battery power, battery SOC, and battery temperature, the future terminal voltage can be predicted based on the estimated battery power, battery SOC, and battery temperature and a predetermined battery model.

[0061] Optionally, after determining the future terminal voltage and future SOC of the battery, it can be determined whether the battery has reached the discharge cutoff condition based on the future terminal voltage and future SOC of the battery. Specifically, the battery is determined to have reached the discharge cutoff condition when the battery terminal voltage is the operating voltage of the battery in the vehicle's limp home mode; the battery is determined to have reached the discharge cutoff condition when the remaining usable capacity of the battery, as represented by the state of charge, reaches the minimum value.

[0062] Optionally, after determining the future terminal voltage and state of charge (SOC) of the battery, a coordinate system can be constructed with the battery SOC as the x-axis and the battery terminal voltage as the y-axis to obtain a future voltage sequence map. Figure 2 This is a schematic diagram of a voltage sequence spectrum according to an embodiment of the present invention, such as... Figure 2 As shown, the battery SOC can be divided at fixed intervals, and then the first available discharge energy value of the battery can be determined based on the following formula for calculating available discharge energy.

[0063]

[0064] Among them, E RDE U is the first available discharge energy value. pre,j Let C be the battery terminal voltage within the j-th SOC interval, ΔSOC be the SOC interval, and C be the voltage at the battery terminal. bat These are battery parameters.

[0065] As an alternative embodiment, the vehicle may also receive a second available discharge energy value of the battery fed back by the cloud computing unit, wherein the second available discharge energy value is used to characterize the remaining available discharge energy of the battery determined by the cloud computing unit based on sampling information and navigation information.

[0066] In this embodiment, the cloud computing unit is equipped with an available discharge energy estimation model, which is pre-trained using offline charge and discharge data of the power battery assembly. Based on this, when the cloud computing unit receives sampling information and navigation information, it can use the available discharge energy estimation model to clean the received data and remove invalid data, thereby reducing the storage space occupied by the cloud computing unit.

[0067] Optionally, after cleaning the data, the cloud computing unit's available discharge energy estimation model can obtain effective data, and then estimate the battery's available discharge energy based on the cleaned effective data to obtain a second available discharge energy value. After obtaining the second available discharge energy value, the cloud computing unit can feed the second available discharge energy value back to the vehicle, and the vehicle can receive the second available discharge energy value fed back by the cloud computing unit.

[0068] As an optional embodiment, step S104, which merges the first available discharge energy value and the second available discharge energy value to obtain the remaining available discharge energy value of the battery, includes: determining the weights corresponding to the first available discharge energy value and the second available discharge energy value based on a pre-set weight calculation formula; and adding the product of the first available discharge energy value and the weight corresponding to the first available discharge energy value and the product of the second available discharge energy value and the weight corresponding to the second available discharge energy value to obtain the available discharge energy value of the battery.

[0069] In this embodiment, after the vehicle determines the first available discharge energy value of the battery and receives the second available discharge energy value of the battery determined by the cloud computing unit, the first available discharge energy value and the second available discharge energy value can be fused to obtain the remaining available discharge energy value of the battery, wherein the remaining available discharge energy value is used to characterize the remaining available discharge energy of the battery.

[0070] Optionally, both the first available discharge energy value and the second available discharge energy value correspond to a confidence coefficient. For ease of explanation, the confidence coefficient corresponding to the first available discharge energy value can be called the first confidence coefficient, and the confidence coefficient corresponding to the second available discharge energy value can be called the second confidence coefficient. The range of the confidence coefficient is [0, 1]. The first confidence coefficient is related to battery temperature, battery SOC, and road conditions. Assuming that road conditions include urban road conditions, suburban road conditions, and highway road conditions, Table 1 shows the correspondence between the first confidence coefficient and battery temperature and battery SOC under urban road conditions. Further explanation is needed. Yes, when the road condition is a highway, the confidence coefficient corresponding to the same battery temperature and battery SOC can be reduced by 0.2. Similarly, when the road condition is a highway, the confidence coefficient corresponding to the same battery temperature and battery SOC can be reduced by 0.1. Based on this, the first confidence coefficient corresponding to each battery temperature and battery SOC can be found from the correspondence table between the first confidence coefficient and battery temperature and battery SOC based on the estimated battery temperature and battery SOC. After determining the first confidence coefficient, the second confidence coefficient corresponding to the second available discharge energy value can be determined using the pre-set confidence calculation formula.

[0071] Table 1. Correspondence between the first confidence level coefficient and battery temperature and battery SOC under urban road conditions.

[0072]

[0073] Optionally, after determining the first confidence coefficient, the second confidence coefficient corresponding to the second available discharge energy value can be determined using the following confidence calculation formula.

[0074] Second confidence coefficient = 1 - First confidence coefficient

[0075] Optionally, after determining the first confidence coefficient and the second confidence coefficient, the weights corresponding to the first available discharge energy value and the second available discharge energy value can be determined based on the following weight calculation formula. For ease of explanation, the weight corresponding to the first available discharge energy value can be called the first weight, and the weight corresponding to the second available discharge energy value can be called the second weight.

[0076] Second weight = Second confidence coefficient / (Second confidence coefficient + First confidence coefficient)

[0077] First weight = 1 - Second weight

[0078] Optionally, after determining the first weight and the second weight, the product of the first available discharge energy value and the weight corresponding to the first available discharge energy value and the product of the second available discharge energy value and the weight corresponding to the second available discharge energy value can be added to obtain the battery's available discharge energy value. That is, the remaining available discharge energy value = first available discharge energy value × first weight + second available discharge energy value × second weight.

[0079] Example 2

[0080] The technical solutions of the embodiments of the present invention will be illustrated below with reference to preferred embodiments.

[0081] Electric vehicles are powered by batteries, but the remaining energy of the battery cannot be directly measured and the state of energy of the battery is affected by many factors. Therefore, it is difficult to accurately estimate the remaining usable energy of the battery, which makes the estimated driving range of electric vehicles inaccurate and causes range anxiety for passengers.

[0082] Currently, the main methods for estimating the remaining energy of a battery include: offline lookup table method, power integration method, closed-loop observation method, neural network method, SOE estimation based on future voltage prediction, and SOE estimation based on big data. Among these, the offline lookup table method, power integration method, and closed-loop observation method can only estimate the remaining energy of the battery theoretically and cannot directly predict the remaining usable discharge energy. The neural network method has poor adaptability and can only be used within the data training range. Moreover, the model is complex and the computational load is large. Although the SOE estimation methods based on future voltage prediction and SOE estimation based on big data consider the influence of factors such as future operating conditions and temperature, and the estimation accuracy is relatively high, the difficulty in accurately predicting future operating conditions is the main factor affecting the prediction accuracy.

[0083] However, the method for determining the remaining usable energy of a battery proposed in this embodiment of the invention acquires sampling information of the battery in the vehicle and navigation information of the vehicle, determines a first usable discharge energy value of the battery based on the acquired sampling information and navigation information, wherein the first usable discharge energy value is used to characterize the remaining usable discharge energy of the battery, and can also send the acquired sampling information and navigation information to a cloud computing unit, wherein the cloud computing unit can determine a second usable discharge energy value of the battery based on the sampling information and navigation information, wherein the second usable discharge energy value is used to characterize the remaining usable discharge energy of the battery determined by the cloud computing unit; and fuses the first usable discharge energy value of the battery determined by the vehicle and the second usable discharge energy value determined by the cloud computing unit to obtain the remaining usable discharge energy value of the battery, wherein the remaining usable discharge energy value is used to characterize the remaining usable discharge energy of the battery. By combining the first available discharge energy value of the battery estimated by the vehicle with the second available discharge energy value estimated by the cloud computing unit, the remaining available discharge energy of the battery can be calculated. Compared with the prediction of the remaining available discharge energy of the battery by the vehicle alone or by the cloud alone, this method of combining the prediction results of the vehicle and the cloud can improve the prediction accuracy, thereby improving the accuracy of the vehicle's remaining range estimation, reducing users' range anxiety, solving the technical problem of low estimation accuracy of the remaining available discharge energy of the battery, and achieving the technical effect of improving the prediction accuracy of the remaining available discharge energy of the battery, improving vehicle safety and comfort.

[0084] The vehicle terminal unit and cloud computing unit provided in the embodiments of the present invention will be further described below:

[0085] Figure 3 This is a schematic diagram of a vehicle terminal unit according to an embodiment of the present invention. Figure 3As shown, the vehicle terminal unit includes a battery information acquisition module, a sampling information sending module, a sampling information receiving module, a data processing module, an available discharge energy state estimation module, a data storage module, and a state estimation data sending module. The battery information acquisition module is used for real-time acquisition of battery voltage, current, and temperature information. The sampling information sending module sends the sampled voltage, current, and temperature information to the sampling information receiving module, which in turn receives the sampled voltage, current, and temperature information. The data processing module preprocesses the received voltage, current, and temperature information, converting it into physical quantities with actual physical meaning. The available discharge energy state estimation module estimates the battery's available discharge energy based on the received information. The data storage module stores the final SOE calculated by the vehicle terminal unit for this driving cycle and uses it as the initial SOE reference value for the next driving cycle. The state estimation data sending module sends the SOE information to the vehicle controller for remaining range estimation.

[0086] Figure 4 This is a schematic diagram of a cloud computing unit according to an embodiment of the present invention. Figure 4 As shown, the cloud computing unit includes a data receiving module, a data cleaning module, a feature parameter extraction module, a state estimation module, and a data sending module. The data receiving module receives sampled data sent by the vehicle terminal computing unit. The data cleaning module removes outlier data from the sampled data. The feature parameter extraction module extracts features from the received parameters, which serve as input information for the state estimation module to ensure the accuracy of SOE state estimation. The state estimation module performs SOE state estimation based on a trained model. The data sending module sends the estimated SOE state value to the vehicle terminal computing unit.

[0087] The following is a further description of the method for estimating the remaining usable energy of a battery provided in the embodiments of the present invention:

[0088] The remaining usable discharge energy of a battery is directly affected by the future terminal voltage and the discharge cutoff point, and the future terminal voltage is related to future operating conditions and battery temperature rise. Therefore, the algorithm for estimating the remaining usable discharge energy of a battery can be established according to... Figure 5 The framework shown is used for this purpose. Figure 5 This is a schematic diagram of the framework of a battery remaining energy estimation method provided by the present invention, as shown below. Figure 5As shown, based on sampled battery operating data, historical stored data, GPS positioning system data, and navigation system data, the current SOC and future power can be estimated respectively. Then, the future SOC can be estimated based on the estimated current SOC, and the future battery temperature can be estimated based on the estimated future power. Next, the future parameters of the battery model can be estimated based on the estimated future SOC and future temperature, and the discharge cutoff condition of the battery can be calculated based on the future temperature and future power. Then, the future terminal voltage can be estimated based on the future SOC, the estimated future parameters of the battery model, and the future power, and the available discharge energy of a single cell can be estimated based on the estimated future terminal voltage, future SOC, and discharge cutoff condition. Then, the available discharge energy of the battery pack can be estimated based on the available discharge energy of the single cell. Finally, the available discharge energy estimated by the vehicle terminal computing unit and the available discharge energy estimated by the cloud computing unit are fused for calculation to achieve vehicle-cloud collaborative available discharge energy estimation.

[0089] The following provides a further description of the processes provided in this invention, including future power estimation, current SOC estimation, future SOC estimation, discharge cutoff condition determination, future temperature estimation, future model parameter prediction, future terminal voltage estimation, single-cell remaining dischargeable energy estimation, power battery pack available dischargeable energy estimation, and vehicle-cloud fusion available dischargeable energy estimation.

[0090] Future power forecast: Future power forecast is divided into two stages. The first stage is the power forecast from the current location to the destination, and the second stage is the power forecast from the destination until the end of the SOC, as detailed below;

[0091] The first stage involves power estimation from the vehicle's current location to its destination: Based on GPS positioning, the current road conditions and the navigation destination are obtained, determining the driving conditions encountered along the way, such as highway, urban, suburban, and mountainous conditions. The sequence and time required for each driving condition are determined based on navigation information. Then, the battery power for each driving condition is calculated using historically stored battery power data. If there is no navigation destination information, the battery power at the current GPS location can be used as the future battery power. If there is no GPS signal, the historical average power stored in the readable storage is used as the future power until a GPS signal is available.

[0092] The second stage is the power prediction from the destination until the end of the SOC: Since the operating conditions are uncertain after the destination, the power after the destination is determined by the battery's allowable discharge power spectrum obtained through preliminary tests based on the battery's estimated SOC and ambient temperature.

[0093] Current State of Charge (SOC) estimation: The current state of charge can be estimated using common SOC estimation methods, such as open-circuit voltage correction, ampere-hour integration, Kalman filtering, and other methods combined.

[0094] Future SOC Prediction: The interval value of the future SOC sequence can be set as needed. At the same time, based on the current SOC estimation results, the future SOC change sequence can be easily obtained by using ampere-hour integration.

[0095] SOC j =SOC0-j·ΔSOC

[0096] Determining the discharge cutoff condition: Due to inconsistencies in the battery manufacturing process and increased inconsistencies during use, the capacity of each individual cell in the battery pack varies. After determining the discharge cutoff SOC based on future power and temperature changes, when a cell with low capacity or low SOC reaches the cutoff SOC, other cells with relatively high capacity or relatively high initial SOC may not have reached the predetermined cutoff SOC. Therefore, when estimating the available discharge energy of each cell, it is necessary to first estimate the discharge capacity of each cell when it reaches the cutoff SOC, thereby finding the minimum discharge capacity value that can be reached at the cutoff SOC. Based on this capacity value and the initial SOC of each cell, the corresponding cutoff SOC is determined.

[0097] Future temperature prediction: Future temperature prediction can be based on the current temperature of the battery and the rate of temperature change of the battery, or it can be estimated based on the battery thermal model.

[0098] Future model parameter prediction: The model parameters required for estimating available discharge energy are related to the battery model used. Different models require different parameters. Taking the equivalent circuit model as an example, the equivalent circuit model mainly includes parameters such as future ohmic internal resistance, polarization capacitance, and polarization resistance. Offline testing methods can be used to obtain the ohmic internal resistance, polarization resistance, and polarization capacitance corresponding to different temperatures and SOCs. Then, the corresponding internal resistance and capacitance values ​​can be obtained by looking up tables using the future SOC and temperature sequences. For example, using the Rint equivalent circuit model without considering polarization voltage, the ohmic internal resistance can be directly looked up from a table based on temperature and SOC: R 0,j =f(T) j SOC j ).

[0099] Future terminal voltage prediction: Once the future power, future SOC, future temperature, and battery model parameters are determined, the future terminal voltage can be predicted based on the adopted battery model. For the future terminal voltage sequence U... pre,j It can be based on the Rint model, according to the future average power P pre The calculation yields the result shown in the following formula.

[0100] P pre =U pre,j ·I pre,j =(OCV) j -I pre,j R 0,j )I pre,j

[0101] R 0,j I pre,j 2 -OCV j ·I pre,j +P pre =0

[0102]

[0103] U pre,j =OCV j -I pre,j R 0,j

[0104] Estimation of remaining dischargeable energy per cell: Once the future power, future terminal voltage and future SOC are determined in the above steps, the available discharge energy of each cell can be obtained using an approximate formula for estimating remaining discharge energy.

[0105] Estimation of available discharge energy of power battery pack: The available discharge energy of the power battery pack can be obtained by summing the discharge energy of each cell.

[0106] Vehicle-cloud fusion available discharge energy estimation: The available discharge energy of the vehicle and the cloud is fused and estimated to obtain the final available discharge energy. The cloud computing unit performs calculations based on the received full-condition data and feeds back the calculation results to the vehicle terminal computing unit. The vehicle terminal unit uses a power battery assembly available discharge energy estimation method based on future power prediction to estimate the available discharge energy in real time. The available discharge energy value in the storage module is available at the initial power-on.

[0107] Vehicle terminal unit and cloud-based available discharge energy fusion processing: The vehicle terminal unit can fuse the locally estimated real-time available discharge energy value and the available discharge energy value calculated and fed back by the cloud computing unit, and adjust the weights according to the operating conditions to obtain a relatively accurate estimated value of available discharge energy. The available discharge energy values ​​calculated by the vehicle terminal unit and the cloud computing unit each have corresponding confidence coefficients, with confidence coefficients ranging from 0 to 1. The confidence coefficient of the available discharge energy estimated by the vehicle terminal unit is related to temperature, battery state of charge range, and operating condition complexity. The confidence coefficient corresponding to each temperature and battery state of charge can be determined according to the correspondence table between confidence coefficient, temperature, and battery state of charge (SOC). Then, based on the determined confidence coefficients, the weights corresponding to the available discharge energy values ​​estimated by the vehicle terminal unit and the available discharge energy values ​​determined by the cloud computing unit are determined.

[0108] Cloud SOE weight = Cloud SOE confidence score / (Cloud SOE confidence score + Terminal SOE confidence score)

[0109] Terminal SOE weight = 1 - Cloud SOE weight

[0110] Terminal output SOE = Cloud SOE * Cloud SOE weight + Terminal SOE * Terminal SOE weight

[0111] Example 3

[0112] According to an embodiment of the present invention, a device for determining the remaining usable energy of a battery is also provided. It should be noted that this device for determining the remaining usable energy of a battery can be used to execute the method for determining the remaining usable energy of a battery in Embodiment 1.

[0113] Figure 6 This is a schematic diagram of a device for determining the remaining usable energy of a battery according to an embodiment of the present invention. Figure 6 As shown, the device 600 for determining the remaining usable energy of a battery may include: an acquisition unit 601, a determination unit 602, a receiving unit 603, and a fusion unit 604.

[0114] The acquisition unit 601 is used to acquire the sampling information of the battery in the vehicle and the navigation information of the vehicle, and send the sampling information and navigation information to the cloud computing unit. The sampling information includes multiple physical parameters of the battery, and the navigation information includes the current location information of the vehicle and the target location information of the vehicle.

[0115] The determining unit 602 is used to determine the first available discharge energy value of the battery based on the sampling information and navigation information, wherein the first available discharge energy value is used to characterize the remaining available discharge energy of the battery;

[0116] The receiving unit 603 is used to receive the second available discharge energy value of the battery fed back by the cloud computing unit, wherein the second available discharge energy value is used to characterize the remaining available discharge energy of the battery determined by the cloud computing unit based on sampling information and navigation information;

[0117] The fusion unit 604 is used to fuse the first available discharge energy value and the second available discharge energy value to obtain the remaining available discharge energy value of the battery, wherein the remaining available discharge energy value is used to characterize the remaining available discharge energy of the battery.

[0118] Optionally, the remaining usable discharge energy of the battery is associated with the battery's terminal voltage and state of charge (SOC). The determining unit 602 includes: a first determining module, configured to determine the battery's terminal voltage based on sampling information and navigation information, and to determine the battery's SOC based on the sampling information, wherein the SOC includes the battery's current SOC and the battery's future SOC, the current SOC characterizing the battery's SOC in the current time period, and the future SOC characterizing the battery's SOC in a future time period; and the first determining module, configured to determine a first usable discharge energy value of the battery based on the battery's terminal voltage, the battery's SOC, and a preset formula for calculating usable discharge energy.

[0119] Optionally, the first determining module includes: a first determining submodule, used to determine a first estimated power of the battery based on navigation information, and a second estimated power of the battery based on the future state of charge and the future temperature of the battery, wherein the first estimated power is the power of the battery during the process of the vehicle traveling from the current position to the target position, and the second estimated power is the power of the battery from the time the vehicle reaches the target position until the battery reaches the discharge cutoff condition; and a predicting submodule, used to input the first estimated power and the second estimated power into the battery model for prediction, respectively, to obtain the first terminal voltage of the battery corresponding to the first estimated power and the second terminal voltage of the battery corresponding to the second estimated power.

[0120] Optionally, the first determining submodule is further configured to determine the road conditions that the vehicle will pass through during its journey from the current location to the target location based on navigation information; determine the battery power when the vehicle passes through the road conditions based on the road conditions and the battery power corresponding to each road condition stored in history, and determine the battery power as the first estimated power of the battery.

[0121] Optionally, the first determining module is further configured to determine the current state of charge of the battery based on the sampled information and a pre-estimation method, wherein the pre-estimation method includes at least one of the open-circuit voltage correction method, the ampere-hour integration method, and the Kalman filtering method; and to determine the future state of charge of the battery based on the current state of charge of the battery and the ampere-hour integration method.

[0122] Optionally, the first determining module is further configured to determine that the battery has reached the discharge cutoff condition when the battery terminal voltage is the battery operating voltage of the vehicle in limp-home mode; and to determine that the battery has reached the discharge cutoff condition when the remaining usable capacity of the battery, as represented by the battery's state of charge, reaches a minimum value.

[0123] Optionally, the fusion unit 604 includes: a third determining module, used to determine the weights corresponding to the first available discharge energy value and the second available discharge energy value based on a pre-set weight calculation formula; and a calculation module, used to add the product of the first available discharge energy value and the weight corresponding to the first available discharge energy value and the product of the second available discharge energy value and the weight corresponding to the second available discharge energy value to obtain the available discharge energy value of the battery.

[0124] In this embodiment, the acquisition unit is used to acquire sampling information of the battery in the vehicle and navigation information of the vehicle, and send the sampling information and navigation information to the cloud computing unit; the determination unit is used to determine a first available discharge energy value of the battery based on the sampling information and navigation information, wherein the first available discharge energy value is used to characterize the remaining available discharge energy of the battery; the receiving unit is used to receive a second available discharge energy value of the battery fed back by the cloud computing unit, wherein the second available discharge energy value is used to characterize the remaining available discharge energy of the battery determined by the cloud computing unit based on the sampling information and navigation information; and the fusion unit is used to fuse the first available discharge energy value and the second available discharge energy value to obtain a remaining available discharge energy value of the battery, wherein the remaining available discharge energy value is used to characterize the remaining available discharge energy of the battery. In other words, in this embodiment of the invention, the first available discharge energy value of the battery estimated by the vehicle and the second available discharge energy value estimated by the cloud computing unit can be fused together to calculate the remaining available discharge energy of the battery. Compared with obtaining the remaining available discharge energy of the battery by predicting solely from the vehicle or solely from the cloud, this method of combining the prediction results from the vehicle and the cloud to obtain the remaining available energy of the battery can improve the prediction accuracy, thereby improving the accuracy of vehicle remaining range estimation, reducing user range anxiety, solving the technical problem of low estimation accuracy of remaining available discharge energy of the battery, and achieving the technical effect of improving the prediction accuracy of remaining available discharge energy of the battery, and improving vehicle safety and comfort.

[0125] Example 4

[0126] According to an embodiment of the present invention, a computer-readable storage medium is also provided, the storage medium including a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to execute the method for determining the remaining available energy of the battery in Embodiment 1.

[0127] Example 5

[0128] According to an embodiment of the present invention, a processor is also provided for running a program, wherein the program executes the method for determining the remaining available energy of the battery in Embodiment 1.

[0129] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0130] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0131] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of modules can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection between units or modules, and can be electrical or other forms.

[0132] The units described as separate components may or may not be physically separate. Similarly, the components shown as units may or may not be physical units; they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0133] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0134] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0135] The above are merely preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for determining the remaining usable energy of a battery, characterized in that, Applied to vehicles, including: The system acquires sampling information of the battery in the vehicle and navigation information of the vehicle, and sends the sampling information and navigation information to the cloud computing unit. The sampling information includes multiple physical parameters of the battery, and the navigation information includes the current location information of the vehicle and the target location information of the vehicle. The first available discharge energy value of the battery is determined based on the sampling information and the navigation information, wherein the first available discharge energy value is used to characterize the remaining available discharge energy of the battery; The cloud computing unit receives a second available discharge energy value of the battery, wherein the second available discharge energy value is used to characterize the remaining available discharge energy of the battery determined by the cloud computing unit based on the sampling information and the navigation information. The first available discharge energy value and the second available discharge energy value are fused together to obtain the remaining available discharge energy value of the battery, wherein the remaining available discharge energy value is used to characterize the remaining available discharge energy of the battery.

2. The method according to claim 1, characterized in that, The remaining usable discharge energy of the battery is associated with the battery's terminal voltage and the battery's state of charge. Determining the first usable discharge energy value of the battery based on the sampling information and the navigation information includes: The terminal voltage of the battery is determined based on the sampling information and the navigation information, and the state of charge of the battery is determined based on the sampling information. The state of charge includes the current state of charge of the battery and the future state of charge of the battery. The current state of charge is used to characterize the state of charge of the battery in the current time period, and the future state of charge is used to characterize the state of charge of the battery in a future time period. The first available discharge energy value of the battery is determined based on the battery's terminal voltage, the battery's state of charge, and a preset formula for calculating available discharge energy.

3. The method according to claim 2, characterized in that, Determining the battery terminal voltage based on the sampling information and the navigation information includes: The first estimated power of the battery is determined based on the navigation information, and the second estimated power of the battery is determined based on the future state of charge and the future temperature of the battery. The first estimated power is the power of the battery during the process of the vehicle traveling from the current position to the target position, and the second estimated power is the power of the battery from the time the vehicle reaches the target position until the battery reaches the discharge cutoff condition. The first estimated power and the second estimated power are respectively input into the battery model for estimation, to obtain the first terminal voltage of the battery corresponding to the first estimated power and the second terminal voltage of the battery corresponding to the second estimated power.

4. The method according to claim 3, characterized in that, Determining the first estimated power of the battery based on the navigation information includes: Based on the navigation information, determine the road conditions the vehicle will encounter during its journey from the current location to the target location; Based on the road conditions and the battery power corresponding to each road condition stored in history, the power of the battery when the vehicle passes through the road conditions is determined, and the power is determined as the first estimated power of the battery.

5. The method according to claim 2, characterized in that, Determining the state of charge of the battery based on the sampled information includes: The current state of charge of the battery is determined based on the sampling information and the estimation method, wherein the estimation method includes at least one of the open-circuit voltage correction method, the ampere-hour integration method and the Kalman filtering method; The future state of charge of the battery is determined based on the current state of charge of the battery and the ampere-hour integration method.

6. The method according to claim 3, characterized in that, Determining that the battery has reached the discharge cutoff condition includes: In response to the battery's terminal voltage being the battery's operating voltage in the vehicle's limp-home mode, it is determined that the battery has reached the discharge cutoff condition. When the remaining usable capacity of the battery, as represented by its state of charge, reaches a minimum value, it is determined that the battery has reached the discharge cutoff condition.

7. The method according to claim 1, characterized in that, The step of fusing the first available discharge energy value and the second available discharge energy value to obtain the remaining available discharge energy value of the battery includes: Based on a pre-defined weighting calculation formula, the weights corresponding to the first available discharge energy value and the second available discharge energy value are determined. The usable discharge energy value of the battery is obtained by adding the product of the first available discharge energy value and the weight corresponding to the first available discharge energy value and the product of the second available discharge energy value and the weight corresponding to the second available discharge energy value.

8. A device for determining the remaining usable energy of a battery, characterized in that, include: An acquisition unit is used to acquire sampling information of the battery in the vehicle and navigation information of the vehicle, and send the sampling information and navigation information to a cloud computing unit. The sampling information includes multiple physical parameters of the battery, and the navigation information includes the current location information of the vehicle and the target location information of the vehicle. A determining unit is configured to determine a first available discharge energy value of the battery based on the sampling information and the navigation information, wherein the first available discharge energy value is used to characterize the remaining available discharge energy of the battery; A receiving unit is configured to receive a second available discharge energy value of the battery fed back by the cloud computing unit, wherein the second available discharge energy value is used to characterize the remaining available discharge energy of the battery determined by the cloud computing unit based on the sampling information and the navigation information; A fusion unit is used to fuse the first available discharge energy value and the second available discharge energy value to obtain the remaining available discharge energy value of the battery, wherein the remaining available discharge energy value is used to characterize the remaining available discharge energy of the battery.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein when the program is run by a processor, it controls the device on which the storage medium resides to perform the method of any one of claims 1 to 7.

10. A processor, characterized in that, The processor is used to run a program, wherein the program executes the method according to any one of claims 1 to 7 when it runs.

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