CN116298945A

CN116298945A - Method and device for determining remaining available energy of battery and storage medium

Info

Publication number: CN116298945A
Application number: CN202211591251.2A
Authority: CN
Inventors: 霍艳红; 张頔; 刘永山; 刘轶鑫; 翟一明; 郎锦峰; 马荣勇
Original assignee: FAW Group Corp
Current assignee: FAW Group Corp
Priority date: 2022-12-12
Filing date: 2022-12-12
Publication date: 2023-06-23

Abstract

The invention discloses a method and a device for determining remaining available energy of a battery and a storage medium. Wherein the method comprises the following steps: acquiring sampling information of a battery in a vehicle and navigation information of the vehicle, and sending the sampling information and the navigation information to a cloud computing unit; determining 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 for representing remaining available discharge energy of the battery; receiving a second available discharge energy value fed back by the cloud computing unit, wherein the second available discharge energy value is used for representing the residual available discharge energy of the battery determined by the cloud computing unit based on the sampling information and the navigation information; and fusing the first available discharge energy value and the second available discharge energy value to obtain a residual available discharge energy value of the battery, wherein the residual available discharge energy value is used for representing the residual available discharge energy of the battery. The invention solves the technical problem of low estimation accuracy of the residual available discharge energy of the battery.

Description

Method and device for determining remaining available energy of battery and storage medium

Technical Field

The invention relates to the technical field of vehicles, in particular to a method and a device for determining remaining available energy of a battery and a storage medium.

Background

The Energy Of the electric automobile is derived from a power battery, but the residual Energy (SOE) Of the battery cannot be directly measured and the influence factors Of the Energy State Of the battery are numerous, so that the residual available Energy Of the battery is difficult to accurately estimate, the estimation Of the driving range Of the electric automobile is inaccurate, and the mileage anxiety is brought to passengers.

Currently, the estimation method of the remaining available energy of the battery mainly comprises the following steps: an offline table look-up method, a power integration method, a closed-loop observation method, a neural network method, SOE prediction based on future voltage, SOE estimation based on big data and the like, wherein the offline table look-up method, the power integration method and the closed-loop observation method can only carry out theoretical estimation and have certain errors; the neural network method has poor adaptability, can only be used in a data training range, has complex model and large calculated amount; the SOE estimation method based on the future voltage prediction SOE and the big data considers the influence of factors such as the future working condition, temperature and the like, and the estimation precision is relatively high, but the difficulty in accurately predicting the future working condition is a main factor influencing the prediction precision.

Aiming at the technical problem of low estimation accuracy of the residual available discharge energy of the battery, no effective solution is proposed at present.

Disclosure of Invention

The embodiment of the invention provides a method, a device and a storage medium for determining remaining available energy of a battery, which are used for at least solving the technical problem of low estimation accuracy of the remaining available discharge energy of the battery.

According to an aspect of an embodiment of the present invention, there is provided a method of determining remaining available energy of a battery. 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 the navigation information to a cloud computing unit, wherein the sampling information comprises a plurality of physical parameters of the battery, and the navigation information comprises current position information of the vehicle and target position information of the vehicle; determining 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 for representing remaining available discharge energy of the battery; receiving 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 for representing the residual available discharge energy of the battery determined by the cloud computing unit based on the sampling information and the navigation information; and fusing the first available discharge energy value and the second available discharge energy value to obtain a residual available discharge energy value of the battery, wherein the residual available discharge energy value is used for representing the residual available discharge energy of the battery.

Optionally, the remaining available discharge energy of the battery is associated with a terminal voltage of the battery and a state of charge of the battery, and determining the first available discharge energy value of the battery based on the sampling information and the navigation information includes: determining a terminal voltage of the battery based on the sampling information and the navigation information, and determining a state of charge of the battery based on the sampling information, wherein the state of charge comprises a current state of charge of the battery and a future state of charge of the battery, the current state of charge is used for representing the state of charge of the battery in a current time period, and the future state of charge is used for representing 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 a terminal voltage of the battery, a state of charge of the battery, and a preset available discharge energy calculation formula.

Optionally, determining the terminal voltage of the battery based on the sampling information and the navigation information includes: determining a first estimated power of the battery based on the navigation information, and determining a second estimated power of the battery based on a future state of charge of the battery and a future temperature of the battery, wherein the first estimated power is the power of the battery in the process that the vehicle travels from a current position to a target position, and the second estimated power is the power of the battery in the process that the vehicle reaches the target position until the battery reaches a discharge cut-off condition; the first estimated power and the second estimated power are respectively input into a battery model for estimation, and a first terminal voltage of a battery corresponding to the first estimated power and a second terminal voltage of a battery corresponding to the second estimated power are obtained.

Optionally, determining the first estimated power of the battery based on the navigation information includes: determining road conditions of a road through which the vehicle passes in the process of traveling from the current position to the target position based on the navigation information; and determining the power of the battery when the vehicle passes through the road conditions based on the road conditions and the historically stored battery power corresponding to each road condition, and determining the battery power as the first estimated power of the battery.

Optionally, determining the state of charge of the battery based on the sampling information includes: determining the current state of charge of the battery based on the sampling information and a pre-estimation algorithm, wherein the pre-estimation algorithm at least comprises one of an open-circuit voltage correction method, an ampere-hour integration method and a Kalman filtering method; the future state of charge of the battery is determined based on the current state of charge of the battery and an ampere-hour integral method.

Optionally, determining that the battery reaches the discharge cutoff condition includes: responding to the terminal voltage of the battery as the working voltage of the battery of the vehicle in the limp home mode, and determining that the battery reaches a discharge cut-off condition; the method further includes determining that the battery reaches a discharge cutoff condition in response to a remaining available capacity of the battery, characterized by a state of charge of the battery, reaching a minimum value.

Optionally, fusing the first available discharge energy value and the second available discharge energy value to obtain a remaining available discharge energy value of the battery, including: determining weights corresponding to the first available discharge energy value and the second available discharge energy value based on a preset weight calculation formula; and adding the product of the weight corresponding to the first available discharge energy value and the product of the weight corresponding to the second available discharge energy value and the second available discharge energy value to obtain the available discharge energy value of the battery.

According to another aspect of the embodiment of the present invention, there is also provided a device for determining remaining available energy of a battery, including: the system comprises an acquisition unit, a cloud computing unit and a storage unit, wherein the acquisition unit is used for acquiring sampling information of a battery in a vehicle and navigation information of the vehicle and sending the sampling information and the navigation information to the cloud computing unit, the sampling information comprises a plurality of physical parameters of the battery, and the navigation information comprises current position information of the vehicle and target position information of the vehicle; a determining unit for determining 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 for representing remaining available discharge energy of the battery; the receiving unit is used for receiving 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 for representing the residual available discharge energy of the battery determined by the cloud computing unit based on the sampling information and the navigation information; and the fusion unit is used for fusing the first available discharge energy value and the second available discharge energy value to obtain a residual available discharge energy value of the battery, wherein the residual available discharge energy value is used for representing the residual available discharge energy of the battery.

According to another aspect of an embodiment of the present invention, there is also provided a computer-readable storage medium. The computer readable storage medium includes a stored program, wherein the program when run controls a device in which the computer readable storage medium is located to perform the method for determining remaining energy available from a battery according to the embodiment of the present invention.

According to another aspect of an embodiment of the present invention, there is also provided a processor. The processor is used for running a program, wherein the program executes the method for determining the remaining available energy of the battery according to the embodiment of the invention when running.

In the embodiment of the invention, the sampling information of the battery in the vehicle and the navigation information of the vehicle can be obtained, and the sampling information and the navigation information are sent to the cloud computing unit, wherein the sampling information comprises a plurality of physical parameters of the battery, and the navigation information comprises the current position information of the vehicle and the target position information of the vehicle; determining 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 for representing remaining available discharge energy of the battery; receiving 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 for representing the residual available discharge energy of the battery determined by the cloud computing unit based on the sampling information and the navigation information; and fusing the first available discharge energy value and the second available discharge energy value to obtain a residual available discharge energy value of the battery, wherein the residual available discharge energy value is used for representing the residual available discharge energy of the battery. In other words, in the 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 and calculated to obtain the remaining available discharge energy of the battery, so that compared with the method of predicting the remaining available discharge energy of the battery by the vehicle end alone or the cloud alone, the method of combining the prediction result of the vehicle end and the prediction result of the cloud to obtain the remaining available discharge energy of the battery can improve the prediction precision, achieve the purposes of improving the vehicle remaining mileage estimation precision and reducing the user mileage anxiety, solve the technical problem of low estimation precision of the remaining available discharge energy of the battery, and realize the technical effects of improving the prediction precision of the remaining available discharge energy of the battery and improving the vehicle safety and comfort.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention and together with the description serve to explain the invention and do not constitute a limitation on the invention. In the drawings:

FIG. 1 is a flow chart of a method of determining the remaining available energy of a battery according to an embodiment of the present invention;

FIG. 2 is a schematic diagram of a voltage sequence diagram according to an embodiment of the invention;

fig. 3 is a schematic view of a vehicle terminal unit according to an embodiment of the invention;

fig. 4 is a schematic diagram of a cloud computing unit according to an embodiment of the invention;

fig. 5 is a schematic diagram of a framework of a battery remaining usable energy estimation method provided in accordance with the present invention;

fig. 6 is a schematic diagram of a device for determining remaining available energy of a battery according to an embodiment of the present invention.

Detailed Description

In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.

It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

Example 1

In accordance with an embodiment of the present invention, there is provided an embodiment of a method of determining remaining available energy of a battery, it being noted that the steps illustrated in the flowchart of the figures may be performed in a computer system, such as a set of computer executable instructions, and, although a logical sequence is illustrated in the flowchart, in some cases, the steps illustrated or described may be performed in a different order than that illustrated herein.

Fig. 1 is a flowchart of a method of determining remaining available energy of a battery according to an embodiment of the present invention, as shown in fig. 1, the method may include the steps of:

step S101, sampling information of a battery in a vehicle and navigation information of the vehicle are obtained, and the sampling information and the navigation information are sent to a cloud computing unit, wherein the sampling information comprises a plurality of physical parameters of the battery, and the navigation information comprises current position information of the vehicle and target position information of the vehicle.

In the technical solution provided in the above step S101 of the present invention, the vehicle may sample the physical parameters related to the battery in real time to obtain sampling information, where the sampling information includes a plurality of physical parameters, for example, parameters such as voltage, current, temperature, etc. of the battery, and the navigation system of the vehicle may obtain navigation information of the vehicle, where the navigation information may include current location information of the vehicle and target location information corresponding to a destination to which the vehicle is to reach, and after the vehicle obtains the sampling information of the battery and the navigation information of the vehicle, the vehicle may calculate remaining available energy of the battery based on the obtained information, and in addition, the vehicle may send the obtained sampling information and the navigation information to the cloud computing unit, where the cloud computing unit may also calculate remaining available energy of the battery based on the received sampling information and the navigation information sent by the vehicle.

Step S102, determining 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 for representing the residual available discharge energy of the battery.

In the technical solution provided in the above step S102 of the present invention, after the sampling information and the navigation information are obtained, the vehicle may determine a first available discharge energy value of the battery based on the sampling information and the navigation information, where the first available discharge energy value is used to characterize the remaining available discharge energy of the battery.

Alternatively, since the available discharge energy Of the battery is related to the terminal voltage Of the battery, the State Of Charge (SOC) Of the battery, and the change Of the terminal voltage Of the battery depends on the operating power Of the battery, the SOC Of the battery, and the operating temperature Of the battery, the operating power, the SOC, and the operating temperature Of the battery in the future period Of time may be estimated based on the estimated future operating power, the estimated SOC, and the estimated future operating temperature Of the battery, and then the remaining available discharge energy Of the battery may be determined based on the estimated battery terminal voltage, the estimated future SOC, and the discharge cut-off condition Of the battery.

Alternatively, the estimation of the future power of the battery may be divided into two stages, wherein the first stage is the estimation of the power of the battery from the current position of the vehicle to the target position of the vehicle, and the second stage is the estimation of the power of the battery from the time when the vehicle reaches the destination until the battery reaches the discharge cutoff condition. The power of the battery in the first stage can be determined based on road conditions of various roads traversed by the vehicle when the vehicle travels from the current position to the target position, and the power of the battery in the second stage can be determined based on a battery discharge power map due to uncertainty of the road conditions of the vehicle.

For example, as can be seen from the foregoing description, the navigation information obtained by the vehicle includes the current position information of the vehicle and the target position information of the vehicle, and it is to be noted that the navigation information of the vehicle may also include road conditions to be passed through in the process of driving the vehicle from the current position to the target position, for example, high-speed road conditions, urban road conditions, suburban road conditions, mountain road conditions, and the like, based on which, when the battery power in the first stage is estimated, the sequence of the vehicle passing through each road condition may be determined according to the navigation information, for example, the vehicle may sequentially pass through urban road conditions, suburban road conditions, and high-speed road conditions in the process of driving the vehicle from the current position to the target position, and after determining each road condition to which the vehicle passes through, the battery power in each road condition may be determined according to the corresponding relationship between each road condition stored in history and the battery power. For the power estimation of the battery in the second stage, due to the uncertainty of the driving road condition after the vehicle reaches the destination, the future SOC of the battery and the future temperature of the battery can be estimated based on the sampling information, and then the estimated power of the battery in the second stage is determined from a battery discharge power map obtained by a pre-test based on the estimated future SOC of the battery and the future temperature of the battery, and the battery discharge power map contains the corresponding relation among the SOC of the battery, the battery temperature and the battery power.

Optionally, the battery SOC includes a current SOC of the battery for characterizing a percentage of a total battery charge that is currently remaining available of the battery and a future SOC of the battery for characterizing a percentage of the total battery charge that is remaining available of the battery over a future period of time. The current SOC of the battery can be estimated by using an open circuit voltage correction method, an ampere-hour integration method, a kalman filtering method or other methods based on the sampling information, and the future SOC of the battery can be determined by using the ampere-hour integration method according to a preset interval value of the SOC sequence and the current SOC of the battery.

Alternatively, for the prediction of the future temperature of the battery, the temperature change rate of the battery may be determined based on the temperature of the battery collected in the history, and then the future temperature of the battery may be determined based on the current temperature of the battery and the temperature change rate of the battery.

Alternatively, after estimating the future SOC of the battery and the future temperature of the battery, the estimated power of the battery in the second stage may be determined using a battery discharge power map obtained by a pre-test.

Optionally, after estimating the power, the battery SOC, and the battery temperature of the battery at each stage in the future, the estimation of the future terminal voltage may be performed based on the estimated battery power, battery SOC, and battery temperature and a predetermined battery model.

Optionally, after estimating the battery terminal voltage and the battery SOC of each stage in the future, a first available discharge energy value of the battery may be determined based on a preset available discharge energy calculation formula, and the first available discharge energy value may be used to characterize the remaining available discharge energy of the battery.

Step S103, receiving 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 for representing the residual available discharge energy of the battery determined by the cloud computing unit based on the sampling information and the navigation information.

In the technical solution provided in the above step S103 of the present invention, as known from the description in the above step S101, after the vehicle obtains the sampling information of the battery and the navigation information of the vehicle, the obtained information is further sent to the cloud computing unit, after the cloud computing unit receives the information, the cloud computing unit may determine a second available discharge energy value of the battery based on the received sampling information and the navigation information, and feed back the determined second available discharge energy value to the vehicle, and the vehicle may receive the second available discharge energy value fed back by the cloud computing unit, where the second remaining available discharge energy value may be 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.

Optionally, an available discharge energy estimation model is deployed in the cloud computing unit, and the available discharge energy estimation model is trained by offline charging and discharging data of the power battery assembly in advance, so that after the cloud computing unit receives the sampling information and the navigation information, the cloud computing unit can clean the received data by using the available discharge energy estimation model, and invalid data is removed, so that occupation of storage space of the cloud computing unit is reduced.

Optionally, after the data is cleaned, the available discharge energy estimation model of the cloud computing unit can obtain effective data, and further can estimate available discharge energy of the battery based on the cleaned effective data to obtain a second available discharge energy value, after the second available discharge energy value is obtained, the cloud computing unit can feed back the second available discharge energy value to the vehicle, and the vehicle can receive the second available discharge energy value fed back by the cloud computing unit.

Optionally, after obtaining the second available discharge energy value, the cloud computing unit may further update the model parameters of the available discharge energy estimation model based on the received data, so as to expand the applicability of the model.

Step S104, fusing the first available discharge energy value and the second available discharge energy value to obtain a residual available discharge energy value of the battery, wherein the residual available discharge energy value is used for representing the residual available discharge energy of the battery.

In the technical solution provided in the above 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 may be fused to obtain a remaining available discharge energy value of the battery, where the remaining available discharge energy value is used to represent the remaining available discharge energy of the battery.

Optionally, the vehicle may determine, according to a future working condition, a weight occupied by the first available discharge energy value and the second available discharge energy value, and further add a product of the first available discharge energy value and the weight occupied by the first available discharge energy value and a product of the second available discharge energy value and the weight occupied by the second available discharge energy value, so as to obtain a remaining available discharge energy value of the vehicle battery.

In the steps S101 to S104, 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 may be fused and calculated to obtain the remaining available discharge energy of the battery, so that compared with the method of obtaining the remaining available discharge energy of the battery by vehicle end prediction alone or cloud prediction alone, the method of combining the prediction result of the vehicle end and the prediction result of the cloud to obtain the remaining available discharge energy of the battery can improve the prediction precision, achieve the purposes of improving the estimation precision of the remaining mileage of the vehicle and reducing the anxiety of the user, solve the technical problem of low estimation precision of the remaining available discharge energy of the battery, realize the prediction precision of the remaining available discharge energy of the battery and improve the technical effects of safety and comfort of the vehicle.

The above-described method of this embodiment is further described below.

As an alternative embodiment, step S102, determining a first available discharge energy value of the battery based on the sampling information and the navigation information, includes: determining a terminal voltage of the battery based on the sampling information and the navigation information, and determining a state of charge of the battery based on the sampling information, wherein the state of charge comprises a current state of charge of the battery and a future state of charge of the battery, the current state of charge is used for representing the state of charge of the battery in a current time period, and the future state of charge is used for representing 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 a terminal voltage of the battery, a state of charge of the battery, and a preset available discharge energy calculation formula.

In this embodiment, since the remaining available discharge energy of the battery is related to the terminal voltage of the battery and the state of charge of the battery, and since the terminal voltage of the battery is influenced by the battery-related physical parameter and the navigation information, the terminal voltage of the battery may be determined based on the sampled information and the navigation information, and the state of charge of the battery may be determined based on the sampled information, wherein the state of charge includes a current state of charge of the battery and a future state of charge of the battery, wherein the current state of charge of the battery is used to characterize the state of charge of the battery over a current period of time, and the future state of charge of the battery is used to characterize the state of charge of the battery over the future period of time.

Alternatively, since the change of the terminal voltage of the battery depends on the operating power of the battery, the SOC of the battery, and the operating temperature of the battery, the operating power, the SOC, and the operating temperature of the battery may be estimated in the future period of time based on the change, and then the terminal voltage of the battery may be estimated based on the estimated future operating power, future SOC, and future operating temperature of the battery.

Alternatively, a first estimated power of the battery may be determined based on the navigation information, and a second estimated power of the battery may be determined based on a future state of charge of the battery and a future temperature of the battery, wherein the first estimated power is a power of the battery during a travel of the vehicle from the current location to the target location, and the second estimated power is a power of the battery during a travel from the vehicle to the target location until the battery reaches a discharge cutoff condition.

For example, when determining the first estimated power of the battery, the road condition through which the vehicle travels from the current position to the target position may be determined based on the navigation information, and then the power of the battery passing through each road condition in the process of traveling from the current position to the target position may be determined based on the road condition and the battery power corresponding to each road condition stored in the history. For example, the vehicle may sequentially pass through urban road conditions, suburban road conditions and high-speed road conditions in the process of traveling from the current position to the target position, after determining road conditions through which the vehicle travels in the process of traveling to the target position, the battery power when the vehicle travels through each road condition may be determined according to the corresponding relation between each road condition and the battery power stored in the history, and the determined battery power corresponding to each road condition may be used as the first estimated power of the battery.

Optionally, for the estimation of the power of the battery in the process from when the vehicle reaches the target position until the battery reaches the discharge cut-off condition, the power of the battery cannot be determined based on the road condition due to the uncertainty of the driving road condition after the vehicle reaches the destination, based on this, the estimation of the power of the battery in the stage from when the vehicle reaches the destination until the battery reaches the cut-off condition can be determined based on a battery discharge power map, wherein the battery discharge power map includes the correspondence relationship between the battery SOC, the battery temperature and the battery power, based on this, the battery SOC and the battery temperature after the vehicle reaches the destination can be predicted first, and then the battery power can be found from the battery discharge power map based on the predicted battery SOC and the battery temperature.

Optionally, after estimating the SOC and the battery temperature of the battery, the estimated power of the battery may be determined from the battery discharge power map based on the estimated SOC and the battery temperature.

Optionally, after estimating the battery power, the battery SOC and the battery temperature, the estimation of the future terminal voltage may be performed based on the estimated battery power, the estimated battery SOC and the estimated battery temperature and a predetermined battery model.

Optionally, after determining the future terminal voltage of the battery and the future SOC of the battery, determining whether the battery reaches a discharge cutoff condition based on the future terminal voltage of the battery and the future SOC of the battery, wherein when the terminal voltage of the battery is the operating voltage of the battery in the limp-home mode in response to the battery, it is determined that the battery reaches the discharge cutoff condition; the method further includes determining that the battery reaches a discharge cutoff condition in response to a remaining available capacity of the battery, characterized by a state of charge of the battery, reaching a minimum value.

Optionally, after determining the future terminal voltage of the battery and the battery SOC, a coordinate system may be constructed with the battery SOC as an abscissa and the battery terminal voltage as an ordinate to obtain a future voltage sequence map, and fig. 2 is a schematic diagram of a voltage sequence map according to an embodiment of the present invention, and as shown in fig. 2, the battery SOC may be divided at fixed intervals, and then, a first available discharge energy value of the battery may be determined based on the following available discharge energy calculation formula.

Wherein E is _RDE For a first available discharge energy value, U _pre,j The battery terminal voltage in the jth SOC interval, delta SOC is the SOC interval, C _bat Is a battery parameter.

As an alternative embodiment, the vehicle may further receive a second available discharge energy value of the battery fed back by the cloud computing unit, where 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.

In this embodiment, an available discharge energy estimation model is deployed in the cloud computing unit, and the available discharge energy estimation model is trained by offline charging and discharging data of the power battery assembly in advance, based on the available discharge energy estimation model, after the cloud computing unit receives sampling information and navigation information, the cloud computing unit can clean the received data, and invalid data is removed, so that occupation of storage space of the cloud computing unit is reduced.

As an alternative embodiment, step S104, fusing the first available discharge energy value and the second available discharge energy value to obtain a remaining available discharge energy value of the battery, includes: determining weights corresponding to the first available discharge energy value and the second available discharge energy value based on a preset weight calculation formula; and adding the product of the weight corresponding to the first available discharge energy value and the product of the weight corresponding to the second available discharge energy value and the second available discharge energy value to obtain the available discharge energy value of the battery.

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 may be fused to obtain a remaining available discharge energy value of the battery, where the remaining available discharge energy value is used to represent the remaining available discharge energy of the battery.

Optionally, the first available discharge energy value and the second available discharge energy value are both corresponding to confidence coefficients, for convenience of description, the confidence coefficient corresponding to the first available discharge energy value may be referred to as a first confidence coefficient, the confidence coefficient corresponding to the second available discharge energy value may be referred to as a second confidence coefficient, where the confidence coefficient has a value range of [0,1], where the first confidence coefficient is related to a battery temperature and a battery SOC and road conditions, and assuming that the road conditions include urban road conditions, suburban road conditions and high-speed road conditions, table 1 shows a corresponding relationship between the first confidence coefficient and the battery temperature and the battery SOC in an urban road condition, it is required to be described that, when the road conditions are high-speed road conditions, the confidence coefficient corresponding to the same battery temperature and the battery SOC may be reduced by 0.2, and, when the road conditions are high-speed road conditions, the confidence coefficient corresponding to the same battery temperature and the battery SOC may be reduced by 0.1, based on this, it may be determined that the confidence coefficient corresponding to the battery SOC and the first confidence coefficient and the second confidence coefficient may be calculated from the first confidence coefficient and the first confidence coefficient may be set in advance by using a corresponding equation between the first confidence coefficient and the second confidence coefficient.

TABLE 1 correspondence between first confidence coefficient and battery temperature and battery SOC under urban road conditions

Optionally, after determining the first confidence coefficient, the following confidence calculation formula may be used to determine a second confidence coefficient corresponding to the second available discharge energy value.

Second confidence coefficient=1-first confidence coefficient

Alternatively, after determining the first confidence coefficient and the second confidence coefficient, weights corresponding to the first available discharge energy value and the second available discharge energy value may be determined based on the following weight calculation formula, and for convenience of explanation, the weights corresponding to the first available discharge energy value may be referred to as first weights and the weights corresponding to the second available discharge energy value may be referred to as second weights.

Second weight = second confidence coefficient/(second confidence coefficient + first confidence coefficient)

First weight=1-second weight

Alternatively, after determining the first weight and the second weight, the product of the weight corresponding to the first available discharge energy value and the product of the weight corresponding to the second available discharge energy value and the first available discharge energy value may be added to obtain the available discharge energy value of the battery, that is, the remaining available discharge energy value=the first available discharge energy value×the first weight+the second available discharge energy value×the second weight.

Example 2

The technical solution of the embodiment of the present invention will be illustrated in the following with reference to a preferred embodiment.

The energy of the electric automobile is derived from a power battery, but the residual energy of the battery cannot be directly measured and the influence factors of the energy state of the battery are numerous, so that the residual available energy of the battery is difficult to accurately estimate, the driving range estimation of the electric automobile is inaccurate, and the mileage anxiety is brought to passengers.

At present, the estimation method of the residual energy of the battery mainly comprises the following steps: the method comprises an off-line table look-up method, a power integration method, a closed-loop observation method, a neural network method, SOE prediction based on future voltage, SOE estimation based on big data and the like, wherein the off-line table look-up method, the power integration method and the closed-loop observation method can only theoretically estimate the residual energy of the battery and cannot directly predict the residual available discharge energy of the battery; the neural network method has poor adaptability, can only be used in a data training range, has complex model and large calculated amount; the SOE estimation method based on the future voltage prediction SOE and the big data considers the influence of factors such as the future working condition, temperature and the like, and the estimation precision is relatively high, but the difficulty in accurately predicting the future working condition is a main factor influencing the prediction precision.

However, according to the method for determining the remaining available energy of the battery provided by the embodiment of the invention, sampling information of the battery in the vehicle and navigation information of the vehicle are obtained, and a first available discharge energy value of the battery is determined based on the obtained sampling information and navigation information, wherein the first available discharge energy value is used for representing the remaining available discharge energy of the battery, the obtained sampling information and navigation information can also be sent to a cloud computing unit, and the cloud computing unit can determine a second available discharge energy value of the battery based on the sampling information and the navigation information, wherein the second available discharge energy value is used for representing the remaining available discharge energy of the battery determined by the cloud computing unit; and fusing the first available discharge energy value of the battery determined by the vehicle with the second available discharge energy value determined by the cloud computing unit to obtain a residual available discharge energy value of the battery, wherein the residual available discharge energy value is used for representing the residual available discharge energy of the battery. The method for obtaining the residual available discharge energy of the battery by combining the prediction result of the vehicle end and the prediction result of the cloud end can improve the prediction precision, achieve the purposes of improving the vehicle residual mileage estimation precision and reducing the user mileage anxiety, solve the technical problem of low estimation precision of the residual available discharge energy of the battery, realize the prediction precision of the residual available discharge energy of the battery and improve the technical effects of vehicle safety and comfort compared with the method for obtaining the residual available discharge energy of the battery by the vehicle end prediction alone or the cloud end prediction alone.

The vehicle terminal unit and the cloud computing unit provided by the embodiment of the invention are further described below:

fig. 3 is a schematic view of a vehicle terminal unit according to an embodiment of the invention. As shown in fig. 3, the vehicle terminal unit includes a battery information acquisition module, a sampling information transmission 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 transmission module; the battery information acquisition module is used for acquiring battery voltage, current and temperature information in real time; the sampling information sending module is used for sending the sampled voltage, current, temperature and other information to the sampling information receiving module, and the sampling information receiving module is used for receiving the sampled voltage, current, temperature and other information; the data processing module is used for preprocessing and converting the received voltage, current and temperature information into physical quantities with practical physical significance; the available discharge energy state estimation module is used for estimating available discharge energy of the battery according to the received information; the data storage module is used for storing the SOE finally calculated and output by the vehicle terminal unit and taking the SOE finally calculated and output by the vehicle terminal unit as an initial SOE reference value of the next driving cycle; the state estimation data sending module is used for sending SOE information to the whole vehicle controller for residual mileage estimation.

Fig. 4 is a schematic diagram of a cloud computing unit according to an embodiment of the invention. As shown in fig. 4, the cloud computing unit includes a data receiving module, a data cleaning module, a feature parameter extracting module, a state estimating module, and a data transmitting module; the data receiving module is used for receiving the sampling data sent by the vehicle terminal computing unit; the data cleaning module is used for removing abnormal data in the sampled data; the characteristic parameter extraction module is used for extracting characteristics of the received parameters and used as input information of the state estimation module to ensure SOE state estimation accuracy; the state estimation module is used for carrying out SOE state estimation according to the trained model; the data transmission module is used for transmitting the estimated SOE state value to the vehicle terminal calculation unit.

The method for estimating the remaining available energy of the battery provided by the embodiment of the invention is further described below:

the residual available discharge energy of the battery is directly influenced by the future terminal voltage and the discharge cut-off point, and the future terminal voltage is related to the future working condition and the battery temperature rise. Therefore, the establishment of the battery remaining available discharge energy estimation algorithm may be performed according to the framework shown in fig. 5, fig. 5 is a schematic diagram of the framework of the battery remaining energy estimation method provided by the invention, as shown in fig. 5, the current SOC estimation and the future power estimation may be performed based on the sampled battery operation data, the historical storage data, the GPS positioning system data and the navigation system data, respectively, the current SOC estimation and the future power estimation may be performed, the future SOC may be further estimated based on the estimated current SOC, the future temperature estimation may be performed according to the estimated future power, the future parameters of the battery model may be estimated based on the estimated future SOC and the future temperature, the discharge cut-off condition of the battery may be calculated according to the future temperature and the future power, the future end voltage estimation may be performed based on the future end voltage, the future SOC and the discharge cut-off condition obtained by sampling, the available discharge energy estimation of the battery may be performed based on the available discharge energy of the single body, and the estimated available discharge energy may be performed finally, the estimated available discharge energy of the battery may be calculated and the available discharge energy of the vehicle may be calculated based on the estimated available discharge energy of the cloud end calculation unit.

The following further describes the processes of future power estimation, current SOC estimation, future SOC estimation, discharge cut-off condition determination, future temperature estimation, future model parameter prediction, future terminal voltage estimation, single-body residual dischargeable energy estimation, power battery assembly available discharge energy estimation, and vehicle cloud fusion available discharge energy estimation provided by the embodiments of the present invention:

future power estimation: the future power estimation is divided into two stages, wherein the first stage is the power estimation from the current location to the destination, and the second stage is the power estimation from the destination to the cut-off SOC, and the power estimation is concretely as follows;

the first stage is the power estimation between the current location of the vehicle and the destination: the method comprises the steps of obtaining the current road condition of the whole vehicle and a destination to be reached by navigation according to GPS positioning, determining working conditions which can pass in the middle, such as a high-speed working condition, a city working condition, a suburban working condition, a mountain working condition and the like, determining the sequence and required time of passing through the working conditions in the process of reaching the destination according to navigation information, and then determining the power value of a battery in the process of reaching the destination according to the power of the battery corresponding to the working conditions stored in history. If the navigation destination information is not available, the power corresponding to the battery at the current positioning position of the GPS can be used as the power corresponding to the battery under the future working condition, and if the GPS signal is not available, the historical average power stored in the readable memory is used as the power under the future working condition until the GPS signal is available.

The second phase is power estimation after destination up to cut-off SOC: and determining the power after the destination according to a battery allowable discharge power map obtained by a pre-test according to the estimated SOC and the ambient temperature of the battery due to uncertain working conditions.

Current SOC estimation: the current state of charge can be fusion estimated by adopting common SOC estimation methods, such as open circuit voltage correction, ampere-hour integration, kalman filtering and the like.

Estimating the future SOC: the future SOC estimation can be set with the interval value of the future SOC sequence according to the requirement, and the future SOC change sequence can be easily obtained by adopting ampere-hour integration according to the current SOC estimation result.

SOC _j ＝SOC ₀ -j·ΔSOC

And (3) determining discharge cut-off conditions: because the battery production process can generate inconsistency and the use process can increase inconsistency, the capacity of each battery cell in the battery assembly is different, after the discharge cut-off SOC is determined according to the future power and the future temperature change, when a certain low-capacity or low-SOC single battery reaches the cut-off SOC, other single batteries with relatively higher capacity or relatively higher initial SOC can not reach the preset cut-off SOC, so when the available discharge energy of each single battery is estimated, the dischargeable capacity of each single battery when reaching the cut-off SOC is estimated, and therefore the capacity value which can be discharged at least when reaching the cut-off SOC is found, and the corresponding cut-off SOC is determined according to the capacity value and the initial SOC of each single battery.

Estimating the future temperature: future temperature predictions may be predicted based on the current temperature of the battery and the rate of change of the temperature of the battery, or estimated from a thermal model of the battery.

Future model parameter prediction: the parameters of the model needed by the estimation of the available discharge energy are related to the adopted battery model, the parameters needed by different models are different, an equivalent circuit model is taken as an example, the equivalent circuit model mainly comprises the parameters of future ohmic internal resistance, polarized capacitance, polarized internal resistance and the like, the ohmic internal resistance, polarized internal resistance and polarized capacitance corresponding to different temperatures and different SOCs can be obtained by adopting an off-line test method, and then the corresponding internal resistance and capacitance values are obtained by adopting a table look-up mode through future SOC sequences and temperature sequences. Taking the Rint equivalent circuit model without considering the polarization voltage as an example, the ohmic internal resistance can be directly checked according to the temperature and the SOC: r is R _0,j ＝f(T _j ,SOC _j )。

Estimating the voltage of a future terminal: after the future power, the future SOC temperature and the battery model parameters are determined, the future terminal voltage can be estimated according to the adopted battery model. For future terminal voltage sequences U _pre,j Can be based on Rint model according to future average power P _pre Calculated as shown in the following formula.

P _pre ＝U _pre,j ·I _pre,j ＝(OCV _j -I _pre,j R _0,j )I _pre,j

R _0,j I _pre,j ² -OCV _j ·I _pre,j +P _pre ＝0

U _pre,j ＝OCV _j -I _pre,j R _0,j

Estimating residual dischargeable energy of the monomer: and when the future power, the future terminal voltage and the future SOC are determined, the available discharge energy of each single body can be obtained by using a residual discharge energy estimation approximation formula.

Power cell assembly available discharge energy estimation: the dischargeable energy of each single body can be accumulated to obtain the dischargeable energy of the power battery assembly.

Vehicle cloud fusion can be estimated by using discharge energy: the vehicle end and the cloud end available discharge energy are subjected to fusion estimation to obtain final available discharge energy, the cloud end calculation unit calculates according to the received all-condition data, and the calculation result is fed back to the vehicle terminal calculation unit; the vehicle terminal unit adopts a power battery assembly available discharge energy estimation method based on future power estimation to estimate available discharge energy in real time, and an available discharge energy value in an available storage module is used during initial power-up.

The vehicle terminal unit and cloud end available discharge energy fusion processing: the vehicle terminal unit can perform fusion processing on the available discharge energy value estimated locally in real time and the available discharge energy value fed back by the cloud computing unit, weight adjustment is performed according to working conditions, and a relatively accurate available discharge energy estimated value is obtained, wherein the available discharge energy values calculated by the vehicle terminal unit and the cloud computing unit respectively have corresponding confidence coefficient, the confidence coefficient ranges from 0 to 1, the confidence coefficient of the available discharge energy estimated value of the vehicle terminal unit is related to temperature, the battery state of charge range and working condition complexity, the confidence coefficient corresponding to each temperature and the battery SOC can be determined according to a corresponding relation table of the confidence coefficient and the temperature and the battery SOC, and further the weight corresponding to the available discharge energy value estimated by the vehicle terminal unit and the available discharge energy value determined by the cloud computing unit is determined based on the determined confidence coefficient.

Cloud SOE weight = cloud SOE confidence/(cloud SOE confidence + terminal SOE confidence)

Terminal SOE weight = 1-cloud SOE weight

Terminal output soe=cloud soe+terminal SOE weight

Example 3

According to the embodiment of the invention, a device for determining the residual available energy of the battery is also provided. The determination device of the remaining battery available energy may be used to perform the determination method of the remaining battery available energy in embodiment 1.

Fig. 6 is a schematic diagram of a device for determining remaining available energy of a battery according to an embodiment of the present invention. As shown in fig. 6, the determination device 600 of the remaining available energy of the battery may include: an acquisition unit 601, a determination unit 602, a reception unit 603, and a fusion unit 604.

The acquiring unit 601 is configured to acquire sampling information of a battery in a vehicle and navigation information of the vehicle, and send the sampling information and the navigation information to the cloud computing unit, where the sampling information includes a plurality of physical parameters of the battery, and the navigation information includes current position information of the vehicle and target position information of the vehicle;

a determining unit 602, configured to determine a first available discharge energy value of the battery based on the sampling information and the navigation information, where the first available discharge energy value is used to characterize a remaining available discharge energy of the battery;

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

and a fusion unit 604, configured 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, where the remaining available discharge energy value is used to characterize the remaining available discharge energy of the battery.

Optionally, the remaining available discharge energy of the battery is related to a terminal voltage of the battery and a state of charge of the battery, the determining unit 602 comprises: the first determining module is used for determining the terminal voltage of the battery based on the sampling information and the navigation information and determining the state of charge of the battery based on the sampling information, wherein the state of charge comprises the current state of charge of the battery and the future state of charge of the battery, the current state of charge is used for representing the state of charge of the battery in the current time period, and the future state of charge is used for representing the state of charge of the battery in the future time period; the first determining module is used for determining a first available discharge energy value of the battery based on the terminal voltage of the battery, the charge state of the battery and a preset available discharge energy calculation formula.

Optionally, the first determining module includes: the first determination submodule is used for determining first estimated power of the battery based on navigation information and determining second estimated power of the battery based on future charge state of the battery and future temperature of the battery, wherein the first estimated power is power of the battery in the process that the vehicle runs from a current position to a target position, and the second estimated power is power of the battery in the process that the vehicle starts to reach the target position until the battery reaches a discharge cut-off condition; the estimating sub-module is used for inputting the first estimated power and the second estimated power into the battery model respectively for estimating, so as 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.

Optionally, the first determining submodule is further used for determining road conditions of a road, which the vehicle passes through in the process of driving from the current position to the target position, based on the navigation information; and determining the power of the battery when the vehicle passes through the road conditions based on the road conditions and the historically stored battery power corresponding to each road condition, and determining the battery power as the first estimated power of the battery.

Optionally, the first determining module is further configured to determine a current state of charge of the battery based on the sampling information and a prediction algorithm, where the prediction algorithm at least includes one of an open-circuit voltage correction method, an ampere-hour integration method, and a kalman filtering method; the future state of charge of the battery is determined based on the current state of charge of the battery and an ampere-hour integral method.

Optionally, the first determining module is further configured to determine that the battery reaches a discharge cutoff condition when the terminal voltage of the battery is the operating voltage of the battery in the limp home mode of the vehicle; when the remaining available capacity of the battery, characterized in response to the state of charge of the battery, reaches a minimum value, it is determined that the battery reaches a discharge cutoff condition.

Optionally, the fusing unit 604 includes: the third determining module is used for determining weights corresponding to the first available discharge energy value and the second available discharge energy value based on a preset weight calculation formula; and the calculation module is used for adding the product of the weight corresponding to the first available discharge energy value and the product of the weight corresponding to the second available discharge energy value and the second available discharge energy value to obtain the available discharge energy value of the battery.

In this embodiment, the acquiring unit is configured to acquire sampling information of a battery in a vehicle and navigation information of the vehicle, and send the sampling information and the navigation information to the cloud computing unit; a determining unit for determining 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 for representing remaining available discharge energy of the battery; the receiving unit is used for receiving 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 for representing the residual available discharge energy of the battery determined by the cloud computing unit based on the sampling information and the navigation information; and the fusion unit is used for fusing the first available discharge energy value and the second available discharge energy value to obtain a residual available discharge energy value of the battery, wherein the residual available discharge energy value is used for representing the residual available discharge energy of the battery. In other words, in the 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 and calculated to obtain the remaining available discharge energy of the battery, so that compared with the method that the remaining available discharge energy of the battery is obtained by vehicle end prediction alone or cloud prediction alone, the method that the remaining available discharge energy of the battery is obtained by combining the prediction result of the vehicle end and the prediction result of the cloud can improve the prediction precision, achieve the purposes of improving the estimation precision of the remaining mileage of the vehicle and reducing the anxiety of the user, solve the technical problem of low estimation precision of the remaining available discharge energy of the battery, realize the prediction precision of the remaining available discharge energy of the battery and improve the technical effects of vehicle safety and comfort.

Example 4

According to an embodiment of the present invention, there is also provided a computer-readable storage medium including a stored program, wherein the apparatus in which the computer-readable storage medium is controlled to execute the method of determining the remaining usable energy of the battery in embodiment 1 when the program is run.

Example 5

According to an embodiment of the present invention, there is also provided a processor for running a program, wherein the program, when running, performs the method of determining the remaining available energy of the battery in embodiment 1.

The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.

In the foregoing embodiments of the present invention, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.

In the several embodiments provided in the present application, it should be understood that the disclosed technology content may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and for example, the division of modules may be a logic function division, and there may be another division manner in actual implementation, for example, multiple modules or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method of the various embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.

The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.

Claims

1. A method of determining remaining energy available from a battery, for use in a vehicle, comprising:

acquiring sampling information of a battery in the vehicle and navigation information of the vehicle, and sending the sampling information and the navigation information to a cloud computing unit, wherein the sampling information comprises a plurality of physical parameters of the battery, and the navigation information comprises current position information of the vehicle and target position information of the vehicle;

determining a first available discharge energy value for the battery based on the sampling information and the navigation information, wherein the first available discharge energy value is used to characterize a remaining available discharge energy of the battery;

receiving 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 for representing the residual available discharge energy of the battery determined by the cloud computing unit based on the sampling information and the navigation information;

And fusing the first available discharge energy value and the second available discharge energy value to obtain a residual available discharge energy value of the battery, wherein the residual available discharge energy value is used for representing the residual available discharge energy of the battery.

2. The method of claim 1, wherein the remaining available discharge energy of the battery is associated with a terminal voltage of the battery and a state of charge of the battery, the determining a first available discharge energy value of the battery based on the sampling information and the navigation information comprising:

determining a terminal voltage of the battery based on the sampling information and the navigation information, and determining a state of charge of the battery based on the sampling information, wherein the state of charge comprises a current state of charge of the battery used for characterizing the state of charge of the battery in a current time period and a future state of charge of the battery used for characterizing the state of charge of the battery in a future time period;

and determining a first available discharge energy value of the battery based on the terminal voltage of the battery, the charge state of the battery and a preset available discharge energy calculation formula.

3. The method of claim 2, wherein the determining the terminal voltage of the battery based on the sampling information and the navigation information comprises:

determining a first estimated power of the battery based on the navigation information, and determining a second estimated power of the battery based on a future state of charge of the battery and a future temperature of the battery, wherein the first estimated power is the power of the battery during a process of the vehicle traveling from a current position to a target position, and the second estimated power is the power of the battery during a process of the vehicle reaching the target position until the battery reaches a discharge cutoff condition;

and respectively inputting the first estimated power and the second estimated power into a battery model for estimation to obtain a first terminal voltage of the battery corresponding to the first estimated power and a second terminal voltage of the battery corresponding to the second estimated power.

4. The method of claim 3, wherein the determining the first predicted power of the battery based on the navigation information comprises:

determining road conditions of the vehicle passing through in the process of driving from the current position to the target position based on the navigation information;

And determining the power of the battery when the vehicle passes through the road condition based on the road condition and the historically stored battery power corresponding to each road condition, and determining the power as the first estimated power of the battery.

5. The method of claim 2, wherein the determining the state of charge of the battery based on the sampling information comprises:

determining the current state of charge of the battery based on the sampling information and a pre-estimation algorithm, wherein the pre-estimation algorithm at least comprises one of an open-circuit voltage correction method, an ampere-hour integration method and a 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 integral.

6. The method of claim 3, wherein said determining that the battery has reached a discharge cutoff condition comprises:

determining that the battery reaches a discharge cutoff condition in response to the terminal voltage of the battery being the operating voltage of the battery of the vehicle in a limp home mode;

and determining that the battery reaches a discharge cutoff condition in response to the remaining available capacity of the battery, characterized by the state of charge of the battery, reaching a minimum value.

7. The method of claim 1, wherein fusing the first available discharge energy value and the second available discharge energy value to obtain a remaining available discharge energy value of the battery comprises:

determining weights corresponding to the first available discharge energy value and the second available discharge energy value based on a preset weight calculation formula;

and adding the product of the weight corresponding to the first available discharge energy value and the product of the weight corresponding to the second available discharge energy value and the first available discharge energy value to obtain the available discharge energy value of the battery.

8. A device for determining remaining available energy of a battery, comprising:

the vehicle navigation system comprises an acquisition unit, a cloud computing unit and a storage unit, wherein the acquisition unit is used for acquiring sampling information of a battery in the vehicle and navigation information of the vehicle, and sending the sampling information and the navigation information to the cloud computing unit, wherein the sampling information comprises a plurality of physical parameters of the battery, and the navigation information comprises current position information of the vehicle and target position information of the vehicle;

a determining unit 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 a remaining available discharge energy of the battery;

The receiving unit is used for receiving a second available discharge energy value of the battery, which is fed back by the cloud computing unit, wherein the second available discharge energy value is used for representing the residual available discharge energy of the battery, which is determined by the cloud computing unit based on the sampling information and the navigation information;

and the fusion unit is used for fusing the first available discharge energy value and the second available discharge energy value to obtain a residual available discharge energy value of the battery, wherein the residual available discharge energy value is used for representing the residual available discharge energy of the battery.

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

10. A processor for running a program, wherein the program when run performs the method of any one of claims 1 to 7.