A battery monitoring method for new energy vehicles

Abstract

The present invention discloses a battery monitoring method for a new energy vehicle, which relates to the field of battery monitoring technology, and includes the following steps: S1, collecting driving parameters and battery change parameters of each driving of the vehicle; S2, generating a first thermal stability set and a second thermal stability set according to the driving parameters and battery change parameters of each driving of the vehicle, and determining the characteristic distribution space of the battery under the total driving time; S3, determining the monitoring result of the battery according to the characteristic distribution space of the battery under the total driving time. The present invention can perform data analysis on all driving formations of the battery, ensure that the data is comprehensive and accurate, effectively monitor the battery status, and ensure driving safety.

Description

Technical Field

[0001] The present invention relates to the technical field of battery monitoring, and in particular to a battery monitoring method for a new energy vehicle. Background Art

[0002] In recent years, electric vehicles are developing rapidly. Power batteries are the only power source for electric vehicles. Battery safety issues are becoming increasingly prominent, and one of the important factors affecting battery safety is battery capacity. Battery capacity decay is closely related to factors such as vehicle usage characteristics and external environment. It is difficult to directly calculate the remaining capacity of the power battery through a simple mathematical model, and it is even more difficult to determine whether the battery status is qualified through a simple mathematical model. Therefore, it is necessary to conduct a detailed analysis of the battery capacity problem. Summary of the invention

[0003] In order to solve the above problems, the present invention proposes a battery monitoring method for a new energy vehicle.

[0004] The technical solution of the present invention is: a battery monitoring method for a new energy vehicle comprises the following steps:

[0005] S1, collecting driving parameters and battery change parameters of each driving of the car;

[0006] S2. Generate a first thermal stability set and a second thermal stability set according to the driving parameters and battery change parameters of each driving of the vehicle, and determine the characteristic distribution space of the battery under the total driving time;

[0007] S3. Determine the monitoring result of the battery according to the characteristic distribution space of the battery under the total driving time.

[0008] Further, in S1, the driving parameters include driving distance and total driving time;

[0009] In S1, the battery change parameters include the initial battery capacity and the remaining battery capacity.

[0010] Furthermore, S2 includes the following sub-steps:

[0011] S21, constructing a thermal model for each driving according to the total driving time and battery change parameters of each driving;

[0012] S22, generating a driving split range according to the driving distance of each driving;

[0013] S23, taking the thermal models corresponding to the driving distance within the driving split range as the first thermally stable set, and taking the thermal models corresponding to the driving distance not within the driving split range as the second thermally stable set;

[0014] S24. Determine a characteristic distribution space of the battery under total driving time according to the first thermal stability set and the second thermal stability set.

[0015] The beneficial effect of the above further scheme is that in the present invention, the capacity change of the battery during each driving time is used to establish a thermal model, and all thermal model values ​​are split according to the different driving distances to obtain two thermal stability sets. Then, two thermal stability matrices are constructed using the two thermal stability sets, thereby obtaining the characteristic distribution space of the battery during the entire driving time, and the characteristic distribution space can characterize the capacity change of the battery during all driving processes.

[0016] Furthermore, in S21, the thermal model The expression is:

[0017] ;

[0018] In the formula, Indicates the initial time The initial battery capacity, Indicates the total driving time. Indicates driving time The actual current, Indicates the nominal capacity of the battery. Indicates driving time The standard current, represents the exponential function, represents a constant, Indicates the remaining battery capacity.

[0019] Standard current is a relative concept, which refers to the current value that the battery can provide under standard test conditions (such as specific temperature, discharge rate and load, etc.), from which the thermal changes of the battery are calculated.

[0020] Furthermore, in S22, the upper limit of the driving split range The calculation formula is:

[0021] ;

[0022] In the formula, Indicates the first driving distance, Indicates The driving distance, Indicates The driving distance, Indicates the total number of trips. represents the minimum function;

[0023] In S22, the lower limit of the driving split range The calculation formula is:

[0024] ;

[0025] In the formula, Represents a constant.

[0026] Further, S24 includes the following sub-steps:

[0027] S241, forming a row according to each thermal model value in the first thermal stability set The first thermal stability matrix of the column is composed of a row according to the thermal model values ​​in the second thermal stability set. The second thermal stability matrix of the column, where represents the number of thermal model values ​​of the first thermally stable set, represents the number of thermal model values ​​of the second thermal stability set;

[0028] S242, completing the first thermal stability matrix and the second thermal stability matrix to obtain a first thermal matrix and a second thermal matrix;

[0029] S243, transposing the first thermal matrix, and multiplying the transposed first thermal matrix and the second thermal matrix to obtain a comprehensive thermal matrix;

[0030] S244. Use the comprehensive thermal matrix to obtain the characteristic distribution space of the battery under the total driving time.

[0031] The beneficial effect of the above further scheme is that: in the present invention, the thermal model value is split by different driving distances to obtain two thermal stability sets, and the thermal stability values ​​of the two thermal stability sets correspond to two matrices. The two matrices are transposed and multiplied to obtain a multi-dimensional comprehensive thermal matrix, which contains elements of multiple rows and columns, is not one-dimensional, and can be used to calculate feature distribution characteristics.

[0032] In S242, select and The maximum value of Maximum, then fill the second thermal stability matrix into one row A matrix of columns with missing columns filled with 1.

[0033] Further, in S244, the characteristic distribution space of the battery under the total driving time is The expression is:

[0034] ;

[0035] In the formula, represents the comprehensive heat matrix, represents the number of thermal model values ​​of the first thermally stable set, represents the number of thermal model values ​​of the second thermally stable set, represents the dimension of the comprehensive heat matrix, represents the first heat matrix, represents the second heat matrix.

[0036] The comprehensive heat matrix is ​​a square matrix with the same number of rows and columns, and its dimension is the number of rows or columns.

[0037] Furthermore, S3 includes the following sub-steps:

[0038] S31, determining the attenuation coefficient of the battery according to the characteristic distribution space of the battery under the total driving time;

[0039] S32, determining whether the attenuation coefficient of the battery is greater than or equal to one half, if so, the monitoring result of the battery is unqualified, otherwise, the monitoring result of the battery is qualified.

[0040] Furthermore, in S31, the attenuation coefficient of the battery The calculation formula is:

[0041] ;

[0042] In the formula, Indicates the initial time of the first trip The initial battery capacity, Indicates Initial time of driving The initial battery capacity, Indicates Initial time of driving The initial battery capacity, represents the characteristic distribution space of the battery under the total driving time, Indicates the nominal capacity of the battery. Indicates the total number of trips. Represents the maximum value function.

[0043] The beneficial effects of the present invention are as follows: the present invention discloses a battery monitoring method for a new energy vehicle, which utilizes the capacity change and driving distance of the battery of the new energy vehicle during each driving process to construct two thermally stable sets, utilizes the two thermally stable sets to establish two one-dimensional matrices, and performs padding and transposition on the one-dimensional matrices to obtain a multi-dimensional thermal comprehensive matrix, which can be used to generate a feature distribution space, thereby determining the final battery monitoring result; the present invention can perform data analysis on all driving formations of the battery, ensure that the data is comprehensive and accurate, effectively monitor the battery condition, and ensure driving safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 The present invention is a flow chart of a battery monitoring method for new energy vehicles. DETAILED DESCRIPTION

[0045] The embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0046] like Figure 1 As shown, the present invention provides a battery monitoring method for a new energy vehicle, comprising the following steps:

[0047] S1, collecting driving parameters and battery change parameters of each driving of the car;

[0048] S2. Generate a first thermal stability set and a second thermal stability set according to the driving parameters and battery change parameters of each driving of the vehicle, and determine the characteristic distribution space of the battery under the total driving time;

[0049] S3. Determine the monitoring result of the battery according to the characteristic distribution space of the battery under the total driving time.

[0050] In the embodiment of the present invention, in S1, the driving parameters include the driving distance and the total driving time;

[0051] In S1, the battery change parameters include the initial battery capacity and the remaining battery capacity.

[0052] In this embodiment of the present invention, S2 includes the following sub-steps:

[0053] S21, constructing a thermal model for each driving according to the total driving time and battery change parameters of each driving;

[0054] S22, generating a driving split range according to the driving distance of each driving;

[0055] S23, taking the thermal models corresponding to the driving distance within the driving split range as the first thermally stable set, and taking the thermal models corresponding to the driving distance not within the driving split range as the second thermally stable set;

[0056] S24. Determine a characteristic distribution space of the battery under total driving time according to the first thermal stability set and the second thermal stability set.

[0057] In the present invention, the capacity change of the battery during each driving time is used to establish a thermal model, and all thermal model values ​​are split according to the different driving distances to obtain two thermal stability sets. The two thermal stability sets are then used to construct two thermal stability matrices, thereby obtaining the characteristic distribution space of the battery during the entire driving time, which can characterize the capacity change of the battery during all driving processes.

[0058] In the embodiment of the present invention, in S21, the thermal model The expression is:

[0059] ;

[0060] In the formula, Indicates the initial time The initial battery capacity, Indicates the total driving time. Indicates driving time The actual current, Indicates the nominal capacity of the battery. Indicates driving time The standard current, represents the exponential function, represents a constant, Indicates the remaining battery capacity.

[0061] Standard current is a relative concept, which refers to the current value that the battery can provide under standard test conditions (such as specific temperature, discharge rate and load, etc.), from which the thermal changes of the battery are calculated.

[0062] In the embodiment of the present invention, in S22, the upper limit of the driving split range The calculation formula is:

[0063] ;

[0064] In the formula, Indicates the first driving distance, Indicates The driving distance, Indicates The driving distance, Indicates the total number of trips. represents the minimum function;

[0065] In S22, the lower limit of the driving split range The calculation formula is:

[0066] ;

[0067] In the formula, Represents a constant.

[0068] In this embodiment of the present invention, S24 includes the following sub-steps:

[0069] S241, forming a row according to each thermal model value in the first thermal stability set The first thermal stability matrix of the column is composed of a row according to the thermal model values ​​in the second thermal stability set. The second thermal stability matrix of the column, where represents the number of thermal model values ​​of the first thermally stable set, represents the number of thermal model values ​​of the second thermal stability set;

[0070] S242, completing the first thermal stability matrix and the second thermal stability matrix to obtain a first thermal matrix and a second thermal matrix;

[0071] S243, transposing the first thermal matrix, and multiplying the transposed first thermal matrix and the second thermal matrix to obtain a comprehensive thermal matrix;

[0072] S244. Use the comprehensive thermal matrix to obtain the characteristic distribution space of the battery under the total driving time.

[0073] In the present invention, different driving distances are used to split the thermal model values ​​to obtain two thermal stability sets, and the thermal stability values ​​of the two thermal stability sets correspond to two matrices. The two matrices are transposed and multiplied to obtain a multi-dimensional comprehensive thermal matrix, which contains elements of multiple rows and columns, is not one-dimensional, and can be used to calculate feature distribution characteristics.

[0074] In S242, select and The maximum value of Maximum, then fill the second thermal stability matrix into one row A matrix of columns with missing columns filled with 1.

[0075] In the embodiment of the present invention, in S244, the characteristic distribution space of the battery under the total driving time is The expression is:

[0076] ;

[0077] In the formula, represents the comprehensive heat matrix, represents the number of thermal model values ​​of the first thermally stable set, represents the number of thermal model values ​​of the second thermally stable set, represents the dimension of the comprehensive heat matrix, represents the first heat matrix, represents the second heat matrix.

[0078] The comprehensive heat matrix is ​​a square matrix with the same number of rows and columns, and its dimension is the number of rows or columns.

[0079] In this embodiment of the present invention, S3 includes the following sub-steps:

[0080] S31, determining the attenuation coefficient of the battery according to the characteristic distribution space of the battery under the total driving time;

[0081] S32, determining whether the attenuation coefficient of the battery is greater than or equal to one half, if so, the monitoring result of the battery is unqualified, otherwise, the monitoring result of the battery is qualified.

[0082] In the embodiment of the present invention, in S31, the attenuation coefficient of the battery The calculation formula is:

[0083] ;

[0084] In the formula, Indicates the initial time of the first trip The initial battery capacity, Indicates Initial time of driving The initial battery capacity, Indicates Initial time of driving The initial battery capacity, represents the characteristic distribution space of the battery under the total driving time, Indicates the nominal capacity of the battery. Indicates the total number of trips. Represents the maximum value function.

[0085] Those skilled in the art will appreciate that the embodiments described herein are intended to help readers understand the principles of the present invention, and should be understood that the protection scope of the present invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific variations and combinations that do not deviate from the essence of the present invention based on the technical revelations disclosed by the present invention, and these variations and combinations are still within the protection scope of the present invention.

Claims

1. A battery monitoring method for a new energy vehicle, characterized in that: The following steps are involved: S1, collecting driving parameters and battery change parameters of each driving of the car; S2. Generate a first thermal stability set and a second thermal stability set according to the driving parameters and battery change parameters of each driving of the vehicle, and determine the characteristic distribution space of the battery under the total driving time; S3. Determine the monitoring result of the battery according to the characteristic distribution space of the battery under the total driving time; The S2 comprises the following sub-steps: S21, constructing a thermal model for each driving according to the total driving time and battery change parameters of each driving; S22, generating a driving split range according to the driving distance of each driving; S23, taking the thermal models corresponding to the driving distance within the driving split range as the first thermally stable set, and taking the thermal models corresponding to the driving distance not within the driving split range as the second thermally stable set; S24, determining a characteristic distribution space of the battery under total driving time according to the first thermal stability set and the second thermal stability set; The S21, thermal model The expression is: ； In the formula, Indicates the initial time The initial battery capacity, Indicates the total driving time. Indicates driving time The actual current, Indicates the nominal capacity of the battery. Indicates driving time The standard current, represents the exponential function, represents a constant, Indicates the remaining battery capacity; In S22, the upper limit of the driving split range The calculation formula is: ； In the formula, Indicates the first driving distance, Indicates The driving distance, Indicates The driving distance, Indicates the total number of trips. represents the minimum function; In S22, the lower limit of the driving split range The calculation formula is: ； In the formula, represents a constant; The S24 comprises the following sub-steps: S241, forming a row according to each thermal model value in the first thermal stability set The first thermal stability matrix of the column is composed of a row according to the thermal model values ​​in the second thermal stability set. The second thermal stability matrix of the column, where represents the number of thermal model values ​​of the first thermally stable set, represents the number of thermal model values ​​of the second thermal stability set; S242, completing the first thermal stability matrix and the second thermal stability matrix to obtain a first thermal matrix and a second thermal matrix; S243, transposing the first thermal matrix, and multiplying the transposed first thermal matrix and the second thermal matrix to obtain a comprehensive thermal matrix; S244, using a comprehensive thermal matrix to obtain a characteristic distribution space of the battery under total driving time; In S244, the characteristic distribution space of the battery under the total driving time The expression is: ； In the formula, represents the comprehensive heat matrix, represents the number of thermal model values ​​of the first thermally stable set, represents the number of thermal model values ​​of the second thermally stable set, represents the dimension of the comprehensive heat matrix, represents the first heat matrix, represents the second heat matrix.

2. The battery monitoring method for new energy vehicles according to claim 1, characterized in that: In S1, the driving parameters include driving distance and total driving time; In S1, the battery change parameters include the initial battery capacity and the remaining battery capacity.

3. The battery monitoring method for new energy vehicles according to claim 1, characterized in that: The S3 comprises the following sub-steps: S31, determining the attenuation coefficient of the battery according to the characteristic distribution space of the battery under the total driving time; S32, determining whether the attenuation coefficient of the battery is greater than or equal to one half, if so, the monitoring result of the battery is unqualified, otherwise, the monitoring result of the battery is qualified.

4. The battery monitoring method for new energy vehicles according to claim 3, characterized in that: In S31, the attenuation coefficient of the battery The calculation formula is: ； In the formula, Indicates the initial time of the first trip The initial battery capacity, Indicates Initial time of driving The initial battery capacity, Indicates Initial time of driving The initial battery capacity, represents the characteristic distribution space of the battery under the total driving time, Indicates the nominal capacity of the battery. Indicates the total number of trips. Represents the maximum value function.

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