A vehicle status monitoring system based on big data cloud platform

Abstract

The present invention relates to the technical field of vehicle status monitoring, and discloses a vehicle status monitoring system based on a big data cloud platform, comprising a vehicle status monitoring module, for monitoring the running status of a vehicle and obtaining real-time monitoring data; an analysis module, for performing comprehensive analysis on the real-time monitoring data, and judging whether a battery needs to be overhauled according to the analysis result; a push module, for pushing basic information data of a vehicle that needs to be overhauled to a management terminal; the running status of the vehicle is monitored and the real-time monitoring data of the vehicle is obtained through the vehicle status monitoring module; the real-time monitoring data is comprehensively analyzed through the analysis module, and judging whether a battery needs to be overhauled according to the analysis result; and the basic information data of the vehicle that needs to be overhauled is pushed to the management terminal through the push module; so that an administrator can overhaul the vehicle in time to avoid failures during the use of the vehicle or failure to achieve the expected endurance, which affects business activities.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle status monitoring, and in particular to a vehicle status monitoring system based on a big data cloud platform. Background Art

[0002] With the rapid development of new energy vehicles, the penetration rate of electric vehicles is gradually increasing, and more and more companies will choose electric vehicles when choosing commercial vehicles.

[0003] As the company has a large number of business vehicles, in order to ensure driving safety, electric vehicles will be manually inspected before each use. After manual inspection and confirmation that there are no problems, business activities can be carried out.

[0004] However, for electric vehicles, batteries are the core component of electric vehicles. The performance of batteries determines the range and power performance of electric vehicles. Manual inspection can only detect vehicle failures, but cannot inspect the performance of batteries. Battery performance problems cannot be discovered in time. When electric vehicles with poor battery performance are used for business activities, they are prone to failures or failure to achieve the expected range. Summary of the invention

[0005] The purpose of the present invention is to provide a vehicle status monitoring system based on a big data cloud platform to solve the following technical problems:

[0006] How to monitor the vehicle status and promptly repair electric vehicles whose battery performance does not meet the standards.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] A vehicle status monitoring system based on a big data cloud platform, the vehicle status monitoring system comprising:

[0009] The vehicle status monitoring module is used to monitor the running status of the vehicle and obtain the real-time monitoring data of the vehicle;

[0010] The analysis module is used to conduct a comprehensive analysis of the real-time monitoring data and determine whether the battery needs to be repaired based on the analysis results;

[0011] The push module is used to push the basic information data of the vehicle that needs to be repaired to the management terminal;

[0012] The real-time monitoring data includes the real-time ambient temperature outside the vehicle, the real-time temperature inside the vehicle, the real-time vehicle speed, the real-time power level and the real-time driving distance.

[0013] As a further solution of the present invention: the analysis process of the analysis module is:

[0014] S1: Obtain the real-time power curve Q(t) within the past preset time period through the vehicle status monitoring module, and obtain the number of charging times N through the real-time power curve Q(t), N≥2;

[0015] S2: Obtain the pre-charging power Q of the nth charging through the real-time power curve Q(t) in the past preset time period (n)b , time before charging t (n)b 、The charge after the n-1th charge Q (n-1)a and time t after charging (n-1)a , n∈N;

[0016] S3: Calculate the power Q before charging for the nth charging (n)b and the charge after the n-1th charge Q (n-1)a The power difference Q (n-1)c ;

[0017] S4: According to the power difference Q (n-1)c Get the standard travel distance S under standard conditions (n-1)p ;

[0018] S5: Set the standard travel distance S (n-1)p The time t after charging of the n-1th charging (n-1)a Time t before charging to the nth charging (n)b The real-time driving distance, real-time ambient temperature, real-time vehicle interior temperature and real-time vehicle speed are calculated according to the preset rules to obtain the charging time t of the n-1th charging. (n-1)a Time t before charging to the nth charging (n)b The battery status index between the preset time periods is calculated by the battery comprehensive status calculation formula;

[0019] S6: Perform a comprehensive analysis on the comprehensive battery status index and determine whether the battery needs maintenance based on the analysis results.

[0020] As a further solution of the present invention: in step S5, the preset rules include:

[0021]

[0022] Among them, T e (t) is the actual ambient temperature curve; T c (t) is the real-time temperature curve inside the vehicle; △T is the preset temperature difference; W n t (n-1)a to (n)b The actual temperature difference influence coefficient; μ1 is the first adjustment coefficient.

[0023] As a further solution of the present invention: the preset rules also include:

[0024]

[0025] Among them, T n t (n-1)a to (n)b The actual environmental impact coefficient; T0 is the preset ambient temperature; μ2 is the second adjustment coefficient.

[0026] As a further solution of the present invention: the preset rules also include:

[0027]

[0028] Among them, v n t (n-1)a to (n)b The actual vehicle speed influence coefficient; v s (t) is the actual vehicle speed curve; v0 is the preset vehicle speed; μ3 is the third adjustment coefficient.

[0029] As a further solution of the present invention: the preset rules also include:

[0030]

[0031] Among them, B n t (n-1)a to (n)b Battery status index; S S (t) is the actual distance curve; C is a preset constant; γ1 is the first weight coefficient; γ2 is the second weight coefficient; γ3 is the third weight coefficient; B0 is the preset battery state index.

[0032] As a further solution of the present invention: the battery comprehensive state calculation formula is:

[0033]

[0034] Among them, B s The comprehensive battery status index for the past preset time period; n-1 t (n-1)a to (n)b The weight coefficient of the battery state index, and δ1<δ2<…<δ n-1 <…<δ N-1 .

[0035] As a further solution of the present invention: the process of judging whether the battery needs to be repaired is as follows: the battery comprehensive status index B s Compare with the preset value R1;

[0036] When B s When ≥R1, no maintenance is required;

[0037] When B s < is less than R1, maintenance is required.

[0038] Advantages of the present invention:

[0039] The present invention monitors the operating state of the vehicle through a vehicle state monitoring module and obtains real-time monitoring data of the vehicle; and comprehensively analyzes the real-time monitoring data through an analysis module, and judges whether the battery needs to be maintained according to the analysis result; and then pushes the basic information data of the vehicle that needs to be maintained to the management terminal through a push module; enabling the administrator to timely perform maintenance on the vehicle according to the situation, avoiding failures or accidents during going out and affecting business activities. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The present invention will be further described below with reference to the accompanying drawings.

[0041] Figure 1 It is a system module framework diagram of an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0042] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0043] Please refer to Figure 1 As shown, in one embodiment, a vehicle state monitoring system based on a big data cloud platform is provided, including:

[0044] A vehicle state monitoring module for monitoring the operating state of the vehicle and obtaining real-time monitoring data of the vehicle;

[0045] An analysis module for comprehensively analyzing the real-time monitoring data and judging whether the battery needs to be maintained according to the analysis result;

[0046] A push module for pushing the basic information data of the vehicle that needs to be maintained to the management terminal;

[0047] Through the above technical solutions, in this embodiment, the vehicle state monitoring module monitors the operating state of the vehicle and obtains real-time monitoring data of the vehicle; and the analysis module comprehensively analyzes the real-time monitoring data and judges whether the battery needs to be maintained according to the analysis result; and then the push module pushes the basic information data of the vehicle that needs to be maintained to the management terminal; enabling the administrator to timely perform maintenance on the vehicle according to the situation, avoiding failures or accidents during going out and affecting business activities.

[0048] As an implementation mode of the present invention, the real-time monitoring data includes the real-time ambient temperature outside the vehicle, the real-time temperature inside the vehicle, the real-time vehicle speed, the real-time power and the real-time driving distance.

[0049] As an implementation manner of the present invention, the analysis process of the analysis module is:

[0050] S1: Obtain the real-time power curve Q(t) within the past preset time period through the vehicle status monitoring module, and obtain the number of charging times N through the real-time power curve Q(t), N≥2;

[0051] S2: Obtain the pre-charging power Q of the nth charging through the real-time power curve Q(t) in the past preset time period (n)b , time before charging t (n)b 、The charge after the n-1th charge Q (n-1)a and time t after charging (n-1)a , n∈N;

[0052] S3: Calculate the power Q before charging for the nth charging (n)b and the charge after the n-1th charge Q (n-1)a The power difference Q (n-1)c ;

[0053] S4: According to the power difference Q (n-1)c Get the standard travel distance S under standard conditions (n-1)p ;

[0054] S5: Set the standard travel distance S (n-1)p The time t after charging of the n-1th charging (n-1)a Time t before charging to the nth charging (n)b The real-time driving distance, real-time ambient temperature, real-time vehicle interior temperature and real-time vehicle speed are calculated according to the preset rules to obtain the charging time t of the n-1th charging. (n-1)a Time t before charging to the nth charging (n)b The battery status index between the preset time periods is calculated by the battery comprehensive status calculation formula;

[0055] S6: Perform a comprehensive analysis on the battery comprehensive status index and determine whether the battery needs to be repaired based on the analysis results;

[0056] Through the above technical solution, the analysis module of this embodiment first obtains the real-time power curve Q(t) in the past preset time period through the vehicle status monitoring module, and obtains the number of charging times N through the real-time power curve Q(t), N≥2; then obtains the pre-charging power Q of the nth charging through the real-time power curve Q(t) in the past preset time period (n)b , time before charging t(n)b 、The charge after the n-1th charge Q (n-1)a and time t after charging (n-1)a , n∈N; then calculate the charge before the nth charge Q (n)b and the charge after the n-1th charge Q (n-1)a The power difference Q (n-1)c ; Then according to the power difference Q (n-1)c Get the standard travel distance S under standard conditions (n-1)p ; Then the standard travel distance S (n-1)p The time t after charging of the n-1th charging (n-1)a Time t before charging to the nth charging (n)b The real-time driving distance, real-time ambient temperature, real-time vehicle interior temperature and real-time vehicle speed are calculated according to the preset rules to obtain the charging time t of the n-1th charging. (n-1)a Time t before charging to the nth charging (n)b The battery status index between the preset time periods is calculated by the battery comprehensive status calculation formula; finally, the battery comprehensive status index and the basic status index are comprehensively analyzed, and it is determined whether the battery needs to be repaired according to the analysis results;

[0057] It should be noted that the standard state is a preset ambient temperature of T0, a preset temperature difference between the inside and outside of the vehicle of ΔT, a preset vehicle speed of v0, and a preset battery state index of B0; the number of charging times N and the pre-charging power Q of the nth charging are obtained through the real-time power curve Q(t). (n)b , time before charging t (n)b 、The charge after the n-1th charge Q (n-1)a and time t after charging (n-1)a This is prior art and will not be described in detail here.

[0058] As an implementation manner of the present invention, in step S5, the preset rule includes:

[0059]

[0060] Among them, T e (t) is the actual ambient temperature curve; T c (t) is the real-time temperature curve inside the vehicle; ΔT is the preset temperature difference; W n t (n-1)a to (n)b The actual temperature difference influence coefficient; μ1 is the first adjustment coefficient;

[0061] Through the above technical solution, this embodiment t (n-1)a to (n)b The actual ambient accumulated temperature; t (n-1)a to (n)b The actual accumulated temperature inside the vehicle; t (n-1)a to (n)b The temperature difference between the actual ambient cumulative temperature and the actual vehicle interior cumulative temperature; ΔT*(t (n)b -t (n-1)a ) is t (n-1)a to (n)b The preset cumulative temperature difference; t (n-1)a to (n)b The difference between the actual ambient cumulative temperature and the actual in-car cumulative temperature and the preset cumulative temperature difference; the greater the temperature difference, the greater the impact on the standard travel distance; therefore, the actual temperature difference influence coefficient W n The bigger;

[0062] It should be noted that the first adjustment coefficient μ1 is a preset value, which is set based on experience and will not be described in detail here.

[0063] As an implementation manner of the present invention, the preset rules further include:

[0064]

[0065] Among them, T n t (n-1)a to (n)b The actual environmental impact coefficient; T0 is the preset ambient temperature; μ2 is the second adjustment coefficient;

[0066] Through the above technical solution, in this embodiment, T0*(t (n)b -t (n-1)a ) is t (n-1)a to (n)b The preset ambient cumulative temperature; t (n-1)a to (n)b The actual environment cumulative temperature and the preset environment cumulative temperature are the difference between the actual environment cumulative temperature and the preset environment cumulative temperature. The larger the difference between the actual environment cumulative temperature and the preset environment cumulative temperature, the greater the impact on the standard travel distance. Therefore, the actual environment impact coefficient T n The bigger;

[0067] It should be noted that the second adjustment coefficient μ2 is a preset value, which is set based on experience and will not be described in detail here.

[0068] As an implementation manner of the present invention, the preset rules further include:

[0069]

[0070] Among them, vn t (n-1)a to (n)b The actual vehicle speed influence coefficient; v s (t) is the actual vehicle speed curve; v0 is the preset vehicle speed; μ3 is the third adjustment coefficient;

[0071] Through the above technical solution, this embodiment t (n-1)a to (n)b The actual accumulated speed; v0*(t (n)b -t (n-1)a ) is t (n-1)a to (n)b The preset cumulative speed of t (n-1)a to (n)b The actual accumulated speed and the preset accumulated speed are the accumulated difference of the vehicle speed; the larger the accumulated speed difference is, the greater the impact on the standard travel distance is; therefore, the actual speed influence coefficient v n The bigger;

[0072] It should be noted that the third adjustment coefficient μ3 is a preset value, which is set based on experience and will not be described in detail here.

[0073] As an implementation manner of the present invention, the preset rules further include:

[0074]

[0075] Among them, B n t (n-1)a to (n)b Battery status index; S S (t) is the actual distance curve; C is a preset constant; γ1 is the first weight coefficient; γ2 is the second weight coefficient; γ3 is the third weight coefficient; B0 is the preset battery status index;

[0076] Through the above technical solution, this embodiment t (n-1)a to (n)b The actual cumulative driving distance; t (n-1)a to (n)b The preset travel distance under the actual state; t (n-1)a to (n)b The difference between the actual cumulative driving distance and the preset travel distance; the larger the distance difference, the better the battery performance, and the battery status index B n The bigger;

[0077] It should be noted that the preset constant C, the first weight coefficient γ1, the second weight coefficient γ2, the third weight coefficient γ3, and the battery preset state index B0 are preset values, which are set according to experience and will not be elaborated here.

[0078] As an implementation manner of the present invention, the battery comprehensive state calculation formula is:

[0079]

[0080] Wherein, B s is the battery comprehensive state index in the past preset time period; δ n-1 is the weight coefficient of the battery state index from t (n-1)a to t (n)b , and δ1 < δ2 < … < δ n-1 <… < δ N-1 ;

[0081] Through the above technical solution, in this embodiment, the battery comprehensive state index B in the past preset time period is calculated by the formula s ; the battery comprehensive state is evaluated more accurately;

[0082] It should be noted that the weight coefficient δ n-1 is a preset value, which is set according to experience and will not be elaborated here.

[0083] As an implementation manner of the present invention, the judgment process for determining whether the battery needs to be repaired is: comparing the battery comprehensive state index B s in the past preset time period with the preset value R1;

[0084] When B s ≥ R1, no repair is required;

[0085] When B s < R1, repair is required.

[0086] Through the above technical solution, in this embodiment, the battery comprehensive state index B s in the past preset time period is compared with the preset value R1; when B s ≥ R1, the battery state meets the standard and no repair is required; when B s < R1, the battery state does not meet the standard and repair is required;

[0087] It should be noted that the preset value R1 is a preset value, which is set according to experience and will not be elaborated here.

[0088] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A vehicle status monitoring system based on a big data cloud platform, characterized in that: The vehicle status monitoring system comprises: The vehicle status monitoring module is used to monitor the running status of the vehicle and obtain the real-time monitoring data of the vehicle; The analysis module is used to conduct a comprehensive analysis of the real-time monitoring data and determine whether the battery needs to be repaired based on the analysis results; The push module is used to push the basic information data of the vehicle that needs to be repaired to the management terminal; The real-time monitoring data includes the real-time ambient temperature outside the vehicle, the real-time temperature inside the vehicle, the real-time vehicle speed, the real-time power and the real-time driving distance; The analysis process of the analysis module is as follows: S1: Obtain the real-time power curve within the preset time period through the vehicle status monitoring module , and through the real-time power curve Get the number of charging times , ; S2: Real-time power curve within the past preset time period Get the The power before charging , Before charging , No. The amount of power after charging and time after charging , ; S3: Calculate the The power before charging and The amount of power after charging The power difference ; S4: According to the power difference Get the standard travel distance under standard conditions ; S5: Standard travel distance With Time after charging for the first charge To Time before charging for the first charge The real-time driving distance, real-time ambient temperature, real-time vehicle interior temperature and real-time vehicle speed are obtained according to the preset rules. Time after charging for the first charge To Time before charging for the first charge The battery status index between the preset time periods is calculated by the battery comprehensive status calculation formula; S6: Perform a comprehensive analysis on the battery comprehensive status index and determine whether the battery needs to be repaired based on the analysis results; In step S5, the preset rules include: in, is the actual ambient temperature curve; It is the real-time temperature curve inside the car; is the preset temperature difference; for to The actual temperature difference influence coefficient; is the first adjustment coefficient; The preset rules also include: in, for to Actual environmental impact coefficient; is the preset ambient temperature; is the second adjustment factor; The preset rules also include: in, for to The actual vehicle speed influence coefficient; is the actual vehicle speed curve; is the preset vehicle speed; is the third adjustment factor; The preset rules also include: in, for to Battery status index; is the actual distance curve; is a preset constant; is the first weight coefficient; is the second weight coefficient; is the third weight coefficient; Preset status index for battery; The battery comprehensive status calculation formula is: in, The comprehensive battery status index for the past preset time period; for to The weight coefficient of the battery status index, and ; The process of judging whether the battery needs to be repaired is as follows: the battery comprehensive status index of the past preset time period is calculated. With the default value To compare; when No maintenance is required; when When the fault occurs, maintenance is required.

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