A TSP data platform data processing system based on big data

Abstract

The present invention relates to the field of vehicle data processing technology, and discloses a TSP data platform data processing system based on big data. The TSP data platform data processing system based on big data collects and cleans the data each time, calculates the final value of the charging amount and the final value of the power consumption, and calculates the charging efficiency of the new energy vehicle based on the two final values ​​after cleaning. The display end of the remote vehicle monitoring end displays the data of each set, and the operation and maintenance personnel contact the owner in a variety of ways to prompt him to replace the battery of the new energy vehicle in time, so as to avoid the phenomenon that the new energy vehicle is short in battery life, resulting in a shorter battery life or a breakdown halfway due to lack of power, thereby improving the owner's experience when using the new energy vehicle.

Description

Technical Field

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

[0002] The TSP data platform is a platform that integrates data management and analysis functions, which can help enterprises effectively collect, store, process and analyze data. Through the TSP data platform, enterprises can achieve data integration and interoperability, so as to better use data assets for decision-making. At present, car companies or car service providers also use the TSP data platform to analyze the vehicle usage status in order to better serve car owners; at present, new energy vehicles usually use data analysis systems to analyze their own data so that car owners can grasp the status of the vehicle in time, but some car owners do not care about these data. When the battery life of the vehicle is insufficient, the owner fails to replace the battery in time, which leads to a shorter cruising range or a breakdown on the way, which affects the owner's experience of using the vehicle. Summary of the invention

[0003] The technical problem to be solved by the present invention is to overcome the shortcomings of the prior art and provide a TSP data platform data processing system based on big data.

[0004] In order to solve the above technical problems, the technical solution of the present invention is as follows:

[0005] A TSP data platform data processing system based on big data, characterized in that it includes a vehicle charging and discharging data acquisition module, a vehicle charging and discharging data analysis module, a cloud server and a remote vehicle monitoring terminal; the vehicle charging and discharging data acquisition module and the vehicle charging and discharging data analysis module share a digital tag, and the digital tag is unique and corresponds to a unique new energy vehicle, wherein the vehicle charging and discharging data acquisition module is composed of a charging data acquisition unit and a discharging data acquisition unit, the charging data acquisition unit is used to collect the charging amount Cd of the new energy vehicle, the charging amount Cd is collected every 5 minutes, the discharging data acquisition unit is used to collect the power consumption Xh of the vehicle when in use, and the vehicle charging and discharging data acquisition module sends the collected charging amount Cd and the consumed power Xh to the vehicle charging and discharging data analysis module through the network;

[0006] The vehicle charging and discharging data analysis module cleans the collected multiple charging amounts Cd and power consumption Xh according to an algorithm to obtain a charging amount final value Cdz and a power consumption final value Xhz. The vehicle charging and discharging data analysis module calculates the new energy vehicle charging efficiency CX according to the charging amount final value Cdz and the power consumption Xhz. The vehicle charging and discharging data analysis module groups the calculated new energy vehicle charging efficiency CX and its corresponding digital label and sends them to the cloud server;

[0007] The cloud server determines the degree of battery loss of the new energy vehicle according to the received new energy vehicle charging efficiency CX and the new energy vehicle charging efficiency CX in the corresponding digital tag group according to the judgment threshold, and estimates the life of the new energy vehicle battery according to the degree of battery loss of the new energy vehicle. The battery life of the new energy vehicle is divided into good, general and needs to be replaced, and the new energy vehicles are grouped according to the battery life, and the grouping results are sent to the remote vehicle monitoring terminal through the network;

[0008] When the remote vehicle monitoring terminal shows that the battery life of the new energy vehicle needs to be replaced, the operation and maintenance personnel contact the vehicle owner according to the digital label corresponding to the charging efficiency CX of the new energy vehicle, and remind the new energy vehicle that the battery needs to be replaced.

[0009] As a preferred solution of the TSP data platform data processing system based on big data of the present invention, the calculation expression of the final value Cdz of the charging capacity is as follows:

[0010]

[0011] In the formula, sj represents the total time spent on charging the vehicle. It indicates the number of times the charge capacity Cd is collected during this charging time, and Cd1+Cd2+...+Cdn indicates the sum of all charge capacities Cd collected this time.

[0012] As a preferred solution of the TSP data platform data processing system based on big data of the present invention, the calculation formula of the final value Xhz of power consumption is as follows:

[0013]

[0014] In the formula, sy represents the usage time of new energy after charging.

[0015] Xh1+Xh2+Xh3+...+Xhn represents the sum of the power consumption Xh collected by the discharge data collection unit within the usage time sy of the new energy after charging.

[0016] Xh1+Xh2+Xh3+...+Xhn represents the number of power consumption Xh collected within the usage time sy.

[0017] As a preferred solution of the TSP data platform data processing system based on big data described in the present invention, the vehicle charging and discharging data analysis module temporarily stores the calculated final value of charging capacity Cdz and final value of power consumption Xhz in the storage medium set inside it.

[0018] As a preferred solution of the TSP data platform data processing system based on big data of the present invention, the calculation formula of the charging efficiency CX of the new energy vehicle is as follows:

[0019]

[0020] In the formula, Xhz-Cdz represents the energy loss or storage value of the battery during the period after charging is completed and before charging begins again. It indicates the ratio of the battery's energy loss during charge and discharge overcharge to the charge amount. When the ratio is high, it means that the battery's energy loss is large and the charging efficiency is low. When the ratio is low, it means that the battery's energy loss is small and the charging efficiency is high.

[0021] As a preferred solution of the TSP data platform data processing system based on big data of the present invention, the vehicle charging and discharging data analysis module groups the calculated new energy vehicle charging efficiency CX and its corresponding digital label into:

[0022] (CX1, bq1),..., (CX n , bq n )in,

[0023] bq1, ..., bq n Indicates the number of the digital label, CX1, ..., CX n Indicates the digital label bq G1 ,...,bq Gn The corresponding new energy vehicle charging efficiency CX value;

[0024] The vehicle charging and discharging data analysis module sends the grouping to the cloud server.

[0025] As a preferred solution of the TSP data platform data processing system based on big data described in the present invention, the cloud server stores the received formation, analyzes the charging efficiency CX value of the new energy vehicles in the formation, and determines the battery life of multiple new energy vehicles.

[0026] As a preferred solution of the TSP data platform data processing system based on big data of the present invention, the battery life standards of the multiple new energy vehicles are judged as follows:

[0027] When the charging efficiency of new energy vehicles is 0%≤CX≤10%, the battery life of new energy vehicles is judged to be good;

[0028] When the charging efficiency of new energy vehicles is 10%<CX≤50%, the battery life of new energy vehicles is judged to be normal;

[0029] When the charging efficiency of new energy vehicles CX>50%, it is determined that the new energy vehicles need to replace the battery.

[0030] As a preferred solution of the TSP data platform data processing system based on big data of the present invention, the cloud server performs grouping according to the battery life combined with the digital tags shared by the vehicle charging and discharging data acquisition module and the vehicle charging and discharging data analysis module, and the grouping method is as follows:

[0031] The battery life of new energy vehicles is good:

[0032] {(CX L1 , bq L1 ),...,(CX Ln , bq Ln )};

[0033] The battery life of new energy vehicles is generally:

[0034] {(CX Y1 , bq Y1 ),...,(CX Yn , bq Yn )};

[0035] The battery life of new energy vehicles needs to be replaced:

[0036] {(CX G1 , bq G1 ),...,(CX Gn , bq Gn )};

[0037] And CX L1 ,...,CX Ln , CX Y1 ,...,GX Yn ,

[0038] CX G1 ,...,GX Gn For CX1,...,CX n The values ​​in

[0039] bqLl ,...,bq Ln ,bq yl ,...,bq yn ,

[0040] bq G1 ,...,bq Gn is the number of the digital label bq1, ..., bq n The number in;

[0041] The cloud server sends the grouped collection to the remote vehicle monitoring terminal.

[0042] As a preferred solution of the TSP data platform data processing system based on big data of the present invention, wherein: the remote vehicle monitoring terminal displays the received set on its display terminal, and the operation and maintenance personnel select the bq in the group set that needs to be replaced according to the battery life of the new energy vehicle G1 ,...,bq Gn Contact the vehicle owner to replace the vehicle battery.

[0043] The beneficial effects of the present invention are:

[0044] The present invention collects and cleans the data each time, calculates the final value Cdz of the charging amount and the final value Xhz of the power consumption, calculates the charging efficiency CX of the new energy vehicle according to the two final values ​​after cleaning, and then groups the charging efficiency CX of the new energy vehicle and its corresponding digital label and sends them to the cloud server. The cloud server determines the battery life of multiple new energy vehicles according to these data, and groups them into a set and sends them to the remote vehicle monitoring end. The display end of the remote vehicle monitoring end displays the data of each set. The operation and maintenance personnel find the owner of the corresponding vehicle when purchasing the vehicle according to the bqG1, ..., bqGn digital labels in the group set that need to be replaced according to the battery life of the new energy vehicle, and contact the owner in various ways to prompt him to replace the battery of the new energy vehicle in time, so as to avoid the phenomenon that the new energy vehicle is short in battery life or breaks down due to lack of power halfway due to insufficient battery life, thereby improving the owner's experience when using the new energy vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0046] Figure 1 It is a schematic diagram of the system flow of the present invention. DETAILED DESCRIPTION

[0047] In order to make the content of the present invention more clearly understood, the present invention is further described in detail below according to specific implementation modes and in combination with the accompanying drawings.

[0048] See also Figure 1 , a TSP data platform data processing system based on big data, including a vehicle charging and discharging data acquisition module, a vehicle charging and discharging data analysis module, a cloud server and a remote vehicle monitoring terminal.

[0049] In order to ensure that the data obtained from each new energy vehicle is not confused when it is aggregated, it is necessary to set a unique digital label for it to distinguish it, and the vehicle charging and discharging data acquisition module and the vehicle charging and discharging data analysis module share a digital label, and each digital label is not repeated. Then, when an abnormality is found in a new energy vehicle during the subsequent data analysis process, the abnormal vehicle can be quickly identified.

[0050] The vehicle charging and discharging data acquisition module is composed of a charging data acquisition unit and a discharging data acquisition unit. The charging data acquisition unit is used to collect the charging amount Cd of new energy vehicles. The charging amount is collected every 5 minutes. The discharging data acquisition unit is used to collect the power consumption Xh of the vehicle when it is in use. The vehicle charging and discharging data acquisition module sends the collected charging amount Cd and power consumption Xh to the vehicle charging and discharging data analysis module through the network. The vehicle charging and discharging data analysis module cleans the collected multiple charging amounts Cd and power consumption Xh according to the algorithm to obtain the final value of the charging amount Cdz and the final value of the power consumption Xhz. The corresponding calculation method is as follows:

[0051] The calculation expression of the final value of charge capacity Cdz is as follows:

[0052]

[0053] In the formula, sj represents the total time spent on charging the vehicle. It indicates the number of times the charge capacity Cd is collected during this charging time, and Cd1+Cd2+...+Cdn indicates the sum of all charge capacities Cd collected this time.

[0054] The final value of power consumption Xhz is calculated as follows:

[0055]

[0056] In the formula, sy represents the usage time of new energy after charging.

[0057] Xh1+Xh2+Xh3+...+Xhn represents the sum of the power consumption Xh collected by the discharge data collection unit within the usage time sy of the new energy after charging.

[0058] Xh1+Xh2+Xh2+...+Xhn represents the number of power consumption Xh collected within the usage time sy.

[0059] By cleaning the collected data, the impact of occasional abnormal data on the final data can be reduced, the data accuracy in subsequent calculations can be improved, and misjudgment caused by large errors can be reduced.

[0060] When these final values ​​are calculated, the vehicle charging and discharging data analysis module temporarily stores these final values ​​and waits for the next calculation.

[0061] The vehicle charging and discharging data analysis module cleans the collected multiple charging amounts Cd and power consumption Xh according to the algorithm to obtain the final value of charging amount Cdz and the final value of power consumption. The vehicle charging and discharging data analysis module calculates the final value of charging amount Cdz and power consumption Xhz according to the final value of charging amount

[0062] The calculation method of new energy vehicle charging efficiency CX is as follows:

[0063] The calculation formula for the charging efficiency CX of new energy vehicles is as follows:

[0064]

[0065] In the formula, Xhz-Cdz represents the energy loss or storage value of the battery during the period after charging is completed and before charging begins again. It indicates the ratio of the battery's energy loss during charge and discharge overcharge to the charge amount. When the ratio is high, it means that the battery's energy loss is large and the charging efficiency is low. When the ratio is low, it means that the battery's energy loss is small and the charging efficiency is high.

[0066] Battery charging efficiency is an important indicator for judging the battery life of new energy vehicles. Therefore, the charging efficiency of the vehicle is calculated based on the charging and discharging data of each time, so that the new energy vehicle charging efficiency CX calculated each time is in the latest state, and the battery life status of the new energy vehicle can be updated in real time.

[0067] The vehicle charging and discharging data analysis module sends the calculated new energy vehicle charging efficiency CX and its corresponding digital label grouping to the cloud server, where the new energy vehicle charging efficiency CX and its corresponding digital label grouping are recorded as:

[0068] (CX1,bq1),...,(CX n , bqn), where

[0069] bq1, ..., bq n Indicates the number of the digital label, CX1, ..., CX n Indicates the digital label bqG1 ,...,bq Gn The corresponding new energy vehicle charging efficiency CX value.

[0070] The cloud server determines the degree of battery loss of the new energy vehicle according to the judgment threshold value based on the received new energy vehicle charging efficiency CX and the new energy vehicle charging efficiency CX in the corresponding digital tag group, and estimates the life of the new energy vehicle battery according to the degree of battery loss of the new energy vehicle. The battery life of the new energy vehicle is divided into good, general and needs to be replaced, and the new energy vehicles are grouped according to the battery life, and the grouping results are sent to the remote vehicle monitoring terminal through the network. The specific classification standards are as follows:

[0071] When the charging efficiency of new energy vehicles is 0%≤CX≤10%, the battery life of new energy vehicles is judged to be good;

[0072] When the charging efficiency of new energy vehicles is 10%<CX≤50%, the battery life of new energy vehicles is judged to be normal;

[0073] When the charging efficiency of new energy vehicles CX>50%, it is determined that the new energy vehicles need to replace the battery.

[0074] The cloud server groups and aggregates the battery life according to the digital tags shared by the vehicle charging and discharging data acquisition module and the vehicle charging and discharging data analysis module. The grouping and aggregation method is as follows:

[0075] The battery life of new energy vehicles is good:

[0076] {(CX L1 , bq L1 ),...,(CX Ln , bq Ln )};

[0077] The battery life of new energy vehicles is generally:

[0078] {(CX Y1 , bq Y1 ),...,(CX Yn , bq Yn )};

[0079] New energy vehicle battery life needs to be replaced:

[0080] {(CX G1 , bq G1 ) ， ...,(CX Gn , bq Gn )};

[0081] And CX L1 ,...,CX Ln , CXY1 ,...,CX Yn ,

[0082] CX G1 ,...,CX Gn For CX1,...,CX n The values ​​in

[0083] bq L1 ,...,bq Ln , bq Y1 ,...,bq Yn ,

[0084] bq G1 ,...,bq Gn is the number of the digital label bq1, ..., bq n The number in .

[0085] The cloud server sends the grouped collection to the remote vehicle monitoring terminal, which displays the received collection on its display terminal. The operation and maintenance personnel select the bq in the grouped collection that needs to be replaced according to the battery life of the new energy vehicle. G1 ,...,bq Gn Contact the vehicle owner to replace the vehicle battery, collect and clean the data each time, calculate the final value of the charging amount Cdz and the final value of the power consumption Xhz, and calculate the new energy vehicle charging efficiency CX based on these two final values ​​after cleaning, and then group the new energy vehicle charging efficiency CX and its corresponding digital label and send them to the cloud server. The cloud server determines the battery life of multiple new energy vehicles based on these data, and groups them into sets and sends them to the remote vehicle monitoring end. The display end of the remote vehicle monitoring end displays the data of each set, and the operation and maintenance personnel select the bq in the group set that needs to be replaced according to the battery life of the new energy vehicle G1 ,...,bq Gn The digital tag can be used to find the owner of the corresponding vehicle when purchasing the vehicle, and the owner can be contacted through various means to remind him / her to replace the battery of the new energy vehicle in time to avoid the phenomenon that the new energy vehicle has a shorter range or runs out of power and breaks down halfway due to insufficient battery life, thereby improving the owner's experience when using new energy vehicles.

[0086] In addition to the above embodiments, the present invention may also have other implementation modes; any technical solutions formed by equivalent replacement or equivalent transformation shall fall within the protection scope required by the present invention.

Claims

1. A TSP data platform data processing system based on big data, characterized by: It includes vehicle charging and discharging data acquisition module, vehicle charging and discharging data analysis module, cloud server and remote vehicle monitoring terminal; The vehicle charging and discharging data acquisition module and the vehicle charging and discharging data analysis module share a digital tag, and the digital tag is unique and corresponds to a unique new energy vehicle, wherein the vehicle charging and discharging data acquisition module is composed of a charging data acquisition unit and a discharging data acquisition unit, and the charging data acquisition unit is used to collect the charging amount of the new energy vehicle , the charge amount The data is collected every 5 minutes. The discharge data collection unit is used to collect the power consumption of the vehicle when it is in use. The vehicle charging and discharging data acquisition module collects the charging amount and power consumption Send to the vehicle charging and discharging data analysis module via the network; The vehicle charging and discharging data analysis module collects multiple charging quantities and power consumption Clean it according to the algorithm to get the final value of the charge And the final value of power consumption The vehicle charging and discharging data analysis module is based on the charging amount final value charging amount final value and power consumption Calculate the charging efficiency of new energy vehicles The vehicle charging and discharging data analysis module calculates the charging efficiency of new energy vehicles The corresponding digital tags are grouped and sent to the cloud server; The cloud server receives the charging efficiency of the new energy vehicle The charging efficiency of new energy vehicles in the grouping with their corresponding digital labels Determine the degree of battery loss of new energy vehicles according to the determination threshold, and estimate the life of the new energy vehicle battery according to the degree of battery loss of the new energy vehicle, wherein the battery life of the new energy vehicle is divided into good, average, and needs to be replaced, and the new energy vehicles are grouped according to the battery life, and the grouping results are sent to the remote vehicle monitoring terminal through the network; When the remote vehicle monitoring terminal shows that the battery life of the new energy vehicle needs to be replaced, the operation and maintenance personnel will The corresponding digital tag contacts the vehicle owner, reminding him that the battery of the new energy vehicle needs to be replaced.

2. A TSP data platform data processing system based on big data according to claim 1, characterized in that: The final value of the charge The calculation expression is as follows: , in the formula Indicates the total time spent on charging the vehicle. Indicates the charging capacity during this charging time The number of collections, Indicates all the charging amounts collected this time The sum of .

3. The TSP data platform data processing system based on big data according to claim 1 is characterized by: The final value of power consumption The calculation formula is as follows: , in the formula, Indicates the usage time of new energy after charging. Indicates the usage time of new energy after charging The power consumption collected by the internal discharge data acquisition unit The sum of n represents the usage time The power consumption collected The number of .

4. A TSP data platform data processing system based on big data according to claim 2 or 3, characterized in that: The vehicle charging and discharging data analysis module calculates the final value of the charging capacity And the final value of power consumption Temporarily stored in the storage medium provided inside it.

5. A TSP data platform data processing system based on big data according to claim 4, characterized in that: The new energy vehicle charging efficiency The calculation formula is as follows: , in the formula, It indicates the energy loss or storage value of the battery during the period of time after charging is completed and before charging starts again. It indicates the ratio of the battery's energy loss during the charging and discharging process to the amount of charge. When the ratio is high, it means that the battery's energy loss is large and the charging efficiency is low. When the ratio is low, it means that the battery's energy loss is small and the charging efficiency is high.

6. A TSP data platform data processing system based on big data according to claim 5, characterized in that: The vehicle charging and discharging data analysis module calculates the charging efficiency of new energy vehicles And its corresponding digital label group is recorded as: ,in, Indicates the number of the digital label, Indicates the digital labels Corresponding new energy vehicle charging efficiency Numeric value; The vehicle charging and discharging data analysis module sends the grouping to the cloud server.

7. A TSP data platform data processing system based on big data according to claim 6, characterized in that: The cloud server stores the received groupings and calculates the charging efficiency of the new energy vehicles in the groupings. The numerical values ​​are analyzed to determine the battery life of multiple new energy vehicles.

8. The TSP data platform data processing system based on big data according to claim 7 is characterized in that: The battery life standards for the multiple new energy vehicles are as follows: 0%≤ New Energy Vehicle Charging Efficiency When ≤10%, the battery life of the new energy vehicle is judged to be good; 10%<New Energy Vehicle Charging Efficiency When ≤50%, the battery life of new energy vehicles is judged to be average; New energy vehicle charging efficiency When it is greater than 50%, it is determined that the new energy vehicle needs to replace the battery.

9. A TSP data platform data processing system based on big data according to claim 8, characterized in that: The cloud server performs grouping according to the battery life combined with the digital tags shared by the vehicle charging and discharging data acquisition module and the vehicle charging and discharging data analysis module. The grouping method is as follows: The battery life of new energy vehicles is good: ; The battery life of new energy vehicles is generally: ; The battery life of new energy vehicles needs to be replaced: ; and , , for The values ​​in , , Number of the digital label The number in; The cloud server sends the grouped collection to the remote vehicle monitoring terminal.

10. A TSP data platform data processing system based on big data according to claim 9, characterized in that: The remote vehicle monitoring terminal displays the received set on its display terminal, and the operation and maintenance personnel select the group set that needs to be replaced according to the battery life of the new energy vehicle. Contact the vehicle owner to replace the vehicle battery.

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