Method and system for predicting residual electric quantity of electric vehicle

Abstract

The invention provides a method for predicting the remaining capacity of an electric vehicle. The method comprises the following steps: determining an initial rated capacity value of a power battery of the electric vehicle; acquiring operation state parameters of the power battery of the electric vehicle, and correcting the initial rated capacity value according to the operation state parameters of the power battery to obtain corrected rated capacity; and determining the remaining capacity of the electric vehicle based on the corrected rated capacity and the discharge current. According to the method, the actual working condition factors including temperature, current, discharge depth, service time and the like are considered to form the corresponding correction factors, and then the correction factors are used for correcting the rated capacity of the power battery, so that the accurate rated capacity is determined; it is ensured that the subsequently determined residual electric quantity state of the power battery is basically consistent with the actual state, so that the residual electric quantity error indication phenomenon is avoided, and accurate data support is provided for residual electric quantity reference and maintenance of subsequent user travel.

Description

Technical Field

[0001] This invention relates to the field of electric vehicles, and more particularly to a method and system for predicting the remaining battery power of an electric vehicle. Background Technology

[0002] Electric vehicles are now widely used. The remaining charge status of the power battery during operation is an important indicator of an electric vehicle, as it is related to the accurate estimation of the remaining driving range and maintenance.

[0003] In existing technologies, the remaining state of charge of an electric vehicle's power battery is calculated as follows: In this calculation method, the power battery's consumed capacity is calculated by obtaining the electric vehicle's discharge current I and continuous discharge time t. The calculation is then based on the initial rated capacity C. This method is relatively accurate in the early stages of electric vehicle use (i.e., within a certain usage period for newly manufactured electric vehicles). However, as the electric vehicle's service life continues, its rated capacity decreases with operating conditions. Current calculations do not consider this capacity decay, leading to inaccurate estimates of remaining power. For example, assuming an initial rated capacity of 100 amp-hours, but decreasing to 80 amp-hours, if the discharge capacity is consistently 30 amp-hours, the traditional calculation would be (100-30) / 100, resulting in a remaining power of 70%. However, the actual figure is (80-30) / 80, indicating a remaining power of 62.5%. This significant deviation affects the user's actual usage, potentially leading to breakdowns due to lack of power during travel. Furthermore, incorrect remaining power indications can also affect the user's actual maintenance procedures.

[0004] Therefore, in order to solve the above-mentioned technical problems, it is urgent to propose a new technical approach. Summary of the Invention

[0005] In view of this, the purpose of this invention is to provide a method and system for predicting the remaining power capacity of an electric vehicle. When predicting the remaining power capacity of a power battery, the method considers actual operating conditions, including temperature, current, depth of discharge, and service time, to form a corresponding correction factor. The rated capacity of the power battery is then corrected using the correction factor to determine an accurate rated capacity. This ensures that the subsequent determination of the remaining power capacity status of the power battery is basically consistent with the actual status, thereby avoiding incorrect indication of the remaining power capacity and providing more accurate data support for users' reference on remaining power capacity and maintenance.

[0006] The present invention provides a method for predicting the remaining battery power of an electric vehicle, comprising the following steps:

[0007] Determine the initial rated capacity value of the electric vehicle's power battery;

[0008] Obtain the operating status parameters of the electric vehicle's power battery, including: deep discharge cycles, battery operating temperature, discharge current, and battery service life.

[0009] The initial rated capacity value is corrected based on the operating status parameters of the power battery to obtain the corrected rated capacity;

[0010] The remaining battery power of the electric vehicle is determined based on the corrected rated capacity and discharge current.

[0011] Furthermore, the initial rated capacity value is corrected based on the operating status parameters of the power battery, resulting in the corrected rated capacity, which specifically includes:

[0012] The modified rated capacity model is constructed as follows:

[0013] ;

[0014] in: Indicates the corrected rated capacity. This indicates the battery temperature influence factor. This indicates the factor affecting the depth of battery discharge. This indicates the impact factor of high-current battery discharge. This represents the battery service life factor.

[0015] Furthermore, the battery temperature influence factor was determined using the following method. :

[0016] ;

[0017] Where: T represents the temperature at which the battery operates. This indicates the upper limit of the specified operating temperature range for the power battery. This indicates that the operating temperature T of the power battery exceeds The cumulative time factor is b, which is a constant coefficient, and e represents the natural constant.

[0018] Furthermore, the influence factor of battery depth discharge was determined using the following method. :

[0019] ;

[0020] in: Indicates the number of deep discharge cycles of an electric vehicle's power battery. This indicates the number of times the electric vehicle's power battery has been incompletely discharged to a deep discharge state. Indicates the number of times an electric vehicle's battery has been fully discharged to a deep discharge. , and This represents a constant coefficient.

[0021] Furthermore, the influence factor of high-current battery discharge was determined using the following method. :

[0022] ;

[0023] in: This indicates that the discharge current is less than or equal to the maximum allowable discharge current of the power battery. The influence coefficient of current discharge on capacity under certain conditions. This indicates that the discharge current is greater than the maximum allowable discharge current of the power battery. The influence coefficient of discharge on capacity under certain conditions, where I is the discharge current of the power battery. This represents the duration coefficient of high current.

[0024] Furthermore, the remaining battery power of the electric vehicle is determined based on the corrected rated capacity and discharge current as follows:

[0025] SOC indicates the actual remaining state of charge of the power battery.

[0026] Accordingly, the present invention also provides an electric vehicle remaining power prediction system, including a detection unit and a controller;

[0027] The detection unit is used to detect and output the operating status parameters of the electric vehicle's power battery;

[0028] The controller is used to receive the operating status parameters output by the detection unit, and determine the remaining power status of the electric vehicle according to the remaining power prediction method described above based on the operating status parameters.

[0029] Furthermore, the detection unit includes a current sensor and a temperature sensor. The current sensor is used to detect the discharge current of the electric vehicle's power battery, and the temperature sensor is used to detect the operating temperature of the electric vehicle's power battery.

[0030] The beneficial effects of this invention are as follows: By considering actual operating conditions, including temperature, current, depth of discharge, and service time, this invention forms a corresponding correction factor. The rated capacity of the power battery is then corrected using this correction factor, thereby determining an accurate rated capacity. This ensures that the remaining power status of the power battery is basically consistent with the actual status, thus avoiding incorrect indication of remaining power and providing more accurate data support for users' reference of remaining power and maintenance. Attached Figure Description

[0031] The present invention will be further described below with reference to the accompanying drawings and embodiments:

[0032] Figure 1 This is a schematic diagram of the process of the present invention.

[0033] Figure 2 This is a schematic diagram of the system structure of the present invention. Detailed Implementation

[0034] The present invention will be further described in detail below:

[0035] The present invention provides a method for predicting the remaining battery power of an electric vehicle, comprising the following steps:

[0036] S1. Determine the initial rated capacity value of the electric vehicle's power battery;

[0037] Obtain the operating status parameters of the electric vehicle's power battery, including: deep discharge cycles, battery operating temperature, discharge current, and battery service life.

[0038] The initial rated capacity value is corrected based on the operating status parameters of the power battery to obtain the corrected rated capacity;

[0039] The remaining battery capacity of an electric vehicle is determined based on the corrected rated capacity and discharge current. This method considers actual operating conditions, including temperature, current, depth of discharge, and service time, to create a corresponding correction factor. This correction factor is then used to adjust the rated capacity of the power battery, thus determining an accurate rated capacity. This ensures that the subsequent determination of the remaining battery capacity is largely consistent with the actual state, avoiding incorrect remaining battery capacity indications and providing more accurate data support for users' remaining battery capacity reference and maintenance.

[0040] In this embodiment, the initial rated capacity value is corrected based on the operating state parameters of the power battery to obtain the corrected rated capacity, specifically including:

[0041] The modified rated capacity model is constructed as follows:

[0042] ;

[0043] in: Indicates the corrected rated capacity. This indicates the battery temperature influence factor. This indicates the factor affecting the depth of battery discharge. This indicates the impact factor of high-current battery discharge. This represents the battery service life factor. In the above, various factors work together to correct the initial rated capacity, thereby correcting it to the actual rated capacity state at the current point in time. This effectively ensures the accuracy of the final remaining power state determination. Regarding the battery service life factor... Different types of power batteries, such as lithium iron phosphate batteries, ternary lithium batteries, and lithium cobalt oxide batteries, have different service time factors. Generally speaking, manufacturers will provide corresponding time decay factors according to different types of batteries.

[0044] In this embodiment, the battery temperature influence factor is determined by the following method. :

[0045] ;

[0046] Where: T represents the temperature at which the battery operates. This indicates the upper limit of the specified operating temperature range for the power battery. This indicates that the operating temperature T of the power battery exceeds The cumulative time factor, where b is a constant coefficient and e represents the natural constant. Temperature is one of the factors affecting the rated capacity degradation of power batteries. At low temperatures, the capacity of power batteries will decrease, but this decrease is generally recoverable. As the temperature gradually increases, the activity of the medium inside the power battery increases, thus allowing the rated capacity to gradually recover to its initial state (meaning the battery has not experienced significant degradation and has recovered to its initial state, or the difference between the battery capacity and the initial capacity is less than the set value, which can also be considered the initial state). However, when the battery's operating temperature is too high, it will lead to the decomposition of the medium inside the power battery and electrode aging, resulting in a decrease in capacity. Furthermore, it is also related to the duration of the excessively high temperature. Therefore, in the above process, these factors are all considered to ensure the accuracy of the subsequent result evaluation. Different types of power batteries have different temperature durations, and their values ​​are different. A corresponding relationship table can be set, and the value can be determined by looking up the table based on the current battery type and the duration of high temperature accumulation. b is a fitting constant coefficient, which can be determined through prior experiments.

[0047] In this embodiment, the battery depth discharge influence factor is determined by the following method. :

[0048] ;

[0049] in: Indicates the number of deep discharge cycles of an electric vehicle's power battery. This indicates the number of times the electric vehicle's power battery has been incompletely discharged to a deep discharge state. Indicates the number of times an electric vehicle's battery has been fully discharged to a deep discharge. , and These are constant coefficients, which are related to the number of deep discharge cycles. Samples of the same type and model of power batteries can be taken and deep discharge experiments can be conducted. Then, the three coefficients can be determined by fitting existing methods, thereby establishing a corresponding relationship table. The coefficients can be determined by looking up the table. The deep discharge of a power battery will affect its capacity. Its active material structure is loose, and the amount of material participating in the reaction is reduced, thus affecting the capacity of the power battery. However, different discharge depths have different degrees. Generally speaking, a discharge depth of 80%-95% is defined as incomplete deep discharge, and when the discharge depth reaches 95% or more, it is considered as complete deep discharge of the power battery. Therefore, the influence of the number of deep discharge cycles is fully considered. As the number of deep discharge cycles increases, the rated capacity of the power battery will decrease faster.

[0050] In this embodiment, the battery high-current discharge influence factor is determined by the following method. :

[0051] ;

[0052] in: This indicates that the discharge current is less than or equal to the maximum allowable discharge current of the power battery. The influence coefficient of current discharge on capacity under certain conditions. This indicates that the discharge current is greater than the maximum allowable discharge current of the power battery. The influence coefficient of discharge on capacity under certain conditions, where I is the discharge current of the power battery. This represents the duration coefficient of high current. Discharge current is a factor affecting the capacity of a power battery. Generally, users try to avoid high-current discharge of the power battery. However, in actual driving, road conditions, such as steep inclines and heavy loads (e.g., a vehicle can carry 5 people, but different people have different weights; when each person is heavy, even on a flat road, the power battery may experience high-current discharge), all contribute to high-current discharge. Power batteries typically have a nominal maximum discharge current, such as 20A. However, in reality, under the aforementioned conditions, this will exceed 20A, thus affecting the battery's capacity. The above approach considers both the impact of the high-current value and the duration factor to ensure the accuracy of the final result.

[0053] In this embodiment, the remaining battery power of the electric vehicle is determined based on the corrected rated capacity and the discharge current as follows:

[0054] SOC indicates the actual remaining state of charge of the power battery.

[0055] Accordingly, the present invention also provides an electric vehicle remaining power prediction system, including a detection unit and a controller;

[0056] The detection unit is used to detect and output the operating status parameters of the electric vehicle's power battery;

[0057] The controller is used to receive the operating status parameters output by the detection unit, and determine the remaining power status of the electric vehicle according to the remaining power prediction method described above based on the operating status parameters. The controller outputs the determined remaining power status to the vehicle display device for the user to view.

[0058] Specifically, the detection unit includes a current sensor and a temperature sensor. The current sensor is used to detect the discharge current of the electric vehicle's power battery, and the temperature sensor is used to detect the operating temperature of the electric vehicle's power battery. The controller can be the electric vehicle's on-board controller, and the temperature sensor and current sensor can be components from the power battery's BMS management system. The controller can determine the number of deep discharge cycles of the power battery by using the voltage and current information obtained from the BMS management system.

[0059] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for predicting the remaining battery power of an electric vehicle, characterized in that: Includes the following steps: Determine the initial rated capacity value of the electric vehicle's power battery; Obtain the operating status parameters of the electric vehicle's power battery, including: deep discharge cycles, battery operating temperature, discharge current, and battery service life. The initial rated capacity value is corrected based on the operating status parameters of the power battery to obtain the corrected rated capacity; The remaining battery power of the electric vehicle is determined based on the corrected rated capacity and discharge current.

2. The method for predicting the remaining battery power of an electric vehicle according to claim 1, characterized in that: The initial rated capacity value is corrected based on the operating status parameters of the power battery to obtain the corrected rated capacity, which specifically includes: The modified rated capacity model is constructed as follows: ； in: Indicates the corrected rated capacity. This indicates the battery temperature influence factor. This indicates the factor affecting the depth of battery discharge. This indicates the impact factor of high-current battery discharge. This represents the battery service life factor.

3. The method for predicting the remaining battery power of an electric vehicle according to claim 2, characterized in that: The battery temperature influence factor was determined using the following method. : ； Where: T represents the temperature at which the battery operates. This indicates the upper limit of the specified operating temperature range for the power battery. This indicates that the operating temperature T of the power battery exceeds The cumulative time factor is b, which is a constant coefficient, and e represents the natural constant.

4. The method for predicting the remaining battery power of an electric vehicle according to claim 2, characterized in that: The battery depth discharge influencing factor was determined using the following method. : ； in: Indicates the number of deep discharge cycles of an electric vehicle's power battery. This indicates the number of times the electric vehicle's power battery has been incompletely discharged to a deep discharge state. Indicates the number of times an electric vehicle's battery has been fully discharged to a deep discharge. , and This represents a constant coefficient.

5. The method for predicting the remaining battery power of an electric vehicle according to claim 2, characterized in that: The influence factor of high-current battery discharge was determined using the following method. : ； in: This indicates that the discharge current is less than or equal to the maximum allowable discharge current of the power battery. The influence coefficient of current discharge on capacity under certain conditions. This indicates that the discharge current is greater than the maximum allowable discharge current of the power battery. The influence coefficient of discharge on capacity under certain conditions, where I is the discharge current of the power battery. This represents the duration coefficient of high current.

6. The method for predicting the remaining battery power of an electric vehicle according to claim 2, characterized in that: The remaining battery power of the electric vehicle is determined based on the corrected rated capacity and discharge current as follows: SOC indicates the actual remaining state of charge of the power battery.

7. A system for predicting the remaining battery power of an electric vehicle, characterized in that: Includes a detection unit and a controller; The detection unit is used to detect and output the operating status parameters of the electric vehicle's power battery; The controller is used to receive the operating status parameters output by the detection unit, and determine the remaining power status of the electric vehicle according to the remaining power prediction method according to any one of claims 1-6 based on the operating status parameters.

8. The electric vehicle remaining power prediction system according to claim 7, characterized in that: The detection unit includes a current sensor and a temperature sensor. The current sensor is used to detect the discharge current of the electric vehicle's power battery, and the temperature sensor is used to detect the operating temperature of the electric vehicle's power battery.

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