CN115195525A - New energy battery pressure difference early warning system and method based on big data platform - Google Patents
New energy battery pressure difference early warning system and method based on big data platform Download PDFInfo
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- CN115195525A CN115195525A CN202210864026.5A CN202210864026A CN115195525A CN 115195525 A CN115195525 A CN 115195525A CN 202210864026 A CN202210864026 A CN 202210864026A CN 115195525 A CN115195525 A CN 115195525A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L58/00—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles
- B60L58/10—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60Q—ARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING OR SUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES IN GENERAL
- B60Q9/00—Arrangement or adaptation of signal devices not provided for in one of main groups B60Q1/00 - B60Q7/00, e.g. haptic signalling
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L2240/00—Control parameters of input or output; Target parameters
- B60L2240/40—Drive Train control parameters
- B60L2240/54—Drive Train control parameters related to batteries
- B60L2240/547—Voltage
Abstract
The invention discloses a new energy battery pressure difference early warning system and a new energy battery pressure difference early warning method based on a big data platform, wherein the system comprises a vehicle-mounted battery data acquisition module, a vehicle-mounted TBOX, a storage server and the big data platform; the vehicle-mounted battery data acquisition module acquires battery data of a vehicle and uploads the battery data to the storage server for storage through the vehicle-mounted TBOX; and the big data platform analyzes and processes the big data based on the data stored in the server to give an early warning prompt. The invention has the advantages that: the problem of the battery pressure difference can be early warned, so that the battery pressure difference is fed back to the TSP platform and timely contacted with a client through the platform for entering the station. The uncontrollable safety risks such as throwing, burning and the like caused by further aggravation of the pressure difference are avoided.
Description
Technical Field
The invention relates to the field of new energy automobile battery monitoring, in particular to a remote battery pressure difference early warning system and method based on a big data platform.
Background
The failure rate of the new energy automobile is a problem point that new energy is high. In the battery production process, the dust control problem, the module welding problem, the matching problem, the long copper bar bridging and the like can cause pressure difference, the battery does not have abnormity when the battery is operated at the beginning, the battery performance can be rapidly reduced along with the worst single battery core after 1-2 years, and when the vehicle gives an alarm, the single battery or the module reaches the unrepairable ground step and only can be used for replacing a package. The inconsistency of the single battery cell caused by too much differential pressure inducement is also a difficult point of battery improvement. Meanwhile, as the new energy automobile is greatly developed to solve the problem of mileage anxiety, a host factory tends to adopt a scheme of large batteries and high electric quantity, so that more monomers are used, and the single short plate effect is more obvious. Therefore, early warning of the battery differential pressure fault is achieved, safety throwing is reduced, and the safety of the battery is improved. In the prior art, battery temperature and voltage detection and alarm are only carried out through the BMS, but the battery temperature and voltage detection and alarm are limited by the space, the operational capability and the like of the BMS, and the aim of early warning cannot be fulfilled.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a remote battery pressure difference early warning system and method based on a big data platform.
In order to achieve the purpose, the invention adopts the technical scheme that: a new energy battery pressure difference early warning system based on a big data platform comprises a vehicle-mounted battery data acquisition module, a vehicle-mounted TBOX, a storage server and the big data platform;
the vehicle-mounted battery data acquisition module acquires battery data of a vehicle and uploads the battery data to the storage server for storage through the vehicle-mounted TBOX;
and the big data platform analyzes and processes the big data based on the data stored in the server to give an early warning prompt.
And after the big data platform analyzes the uploaded data, the TSP platform sends early warning information to the vehicle-mounted TBOX for vehicle-mounted vehicle reminding.
The vehicle-mounted TBOX uploads battery data of the vehicle and uploads position information of the vehicle at the same time; when the pressure difference early warning fault is analyzed, the big data platform sends early warning information and position information of a vehicle to a vehicle service station corresponding to the position of the vehicle, and simultaneously sends the early warning information and invites the station entering maintenance information to a vehicle machine TBOX (tunnel boring machine) of the vehicle or to a user Internet of vehicles (APP) for early warning and maintenance reminding.
The vehicle-mounted battery data acquisition module periodically sends data of the highest cell voltage, the lowest cell voltage, the battery SOC, the temperature and the current of the battery to the TBOX in a message mode.
A new energy battery pressure difference early warning method based on a big data platform comprises the following steps,
the battery data of the vehicle are collected in real time through a battery data collecting module and uploaded to a server;
the big data platform accesses the server to obtain battery data of the vehicle, analyzes the battery data to obtain whether the pressure difference of the battery meets the pressure difference early warning, and sends a pressure difference early warning signal to a user or a service station to perform the pressure difference early warning when the pressure difference early warning is met.
The big data platform preprocesses data in the server, eliminates invalid data, analyzes battery data in each vehicle use time period and/or historical pressure difference data, and sends out pressure difference early warning according to an analysis result.
The big data platform is internally provided with a current day pressure difference proportion early warning model, and the model is as follows: and judging the battery pressure difference after the vehicle is started at the same day, counting the number t1 of abnormal battery pressure difference messages of the vehicle and the number t2 of total uploaded messages after the vehicle is started, triggering pressure difference early warning when the value of t1/t2 is greater than an alarm ratio threshold value, and sending the pressure difference early warning by a large data platform.
The big data platform further comprises a historical pressure difference early warning model, under the model, battery data are analyzed and judged whether historical pressure difference judgment conditions are met, and after the historical pressure difference judgment conditions are met, the battery pressure difference is compared with a pressure difference threshold value at the moment to judge whether pressure difference early warning is conducted.
When the current of the battery is smaller than a set current threshold value, the duration time is larger than a time threshold value, and the temperature is larger than a set temperature threshold value, the condition that the current meets the historical pressure difference judgment condition at the moment is judged, a pressure difference threshold value is obtained based on the current SOC of the battery, the current battery pressure difference is compared with the battery pressure difference threshold value, judgment is carried out, an early warning prompt is given, and when the current battery pressure difference is larger than the battery pressure difference threshold value, a pressure difference early warning is given.
The method for eliminating invalid data of the big data platform comprises the steps of sequencing received battery message data according to a time sequence, and eliminating messages of which the battery data meet the conditions that the highest monomer voltage is less than 0.5V, the highest monomer voltage is more than 5V, the lowest monomer voltage is less than 0.5V, the lowest monomer voltage is more than 5V, the highest temperature is more than 125 ℃, the highest temperature is less than-40 ℃, the lowest temperature is more than 125 ℃ or the lowest temperature is less than-40 ℃.
The invention has the advantages that: the problem of the battery pressure difference can be early warned, so that the battery pressure difference is fed back to the TSP platform and timely contacted with a client through the platform for entering the station. The uncontrollable safety risks such as throwing, burning and the like caused by further aggravation of the pressure difference are avoided. The data are analyzed and judged by adopting a large data platform, the data are processed by the cloud, the calculation is more accurate, the calculation power is more sufficient, and the early warning is more accurate; the data is extracted, so that the interference of error data on the early warning accuracy is avoided; the car owner and the service station are informed in time, so that the car owner and the service station can be maintained conveniently and timely, the further deterioration of pressure difference abnormity is avoided, and the service life is prolonged.
Drawings
The contents of the expressions in the various figures of the present specification and the labels in the figures are briefly described as follows:
fig. 1 is a data transmission schematic diagram of a new energy battery differential pressure early warning system based on a big data platform.
Detailed Description
The following description of preferred embodiments of the invention will be made in further detail with reference to the accompanying drawings.
The battery data change of the vehicle monitored in real time is analyzed to give early warning, the safety of the battery is reminded, a user can maintain the battery in time conveniently, and further deterioration of the battery is avoided. The characteristics of strong calculation power of big data and big storage data of the server are utilized, and the method is applied to the field of early warning of the differential pressure of the power battery of the new energy electric vehicle, so that the current situation that the traditional vehicle can be maintained only when problems occur is changed. The problem of the battery differential pressure is early warned, so that the battery differential pressure is fed back to the TSP platform and timely contacts a client to enter the station through the platform for processing. The uncontrollable safety risks such as throwing, burning and the like caused by further aggravation of the pressure difference are avoided. The specific scheme is as follows:
as shown in fig. 1, a new energy battery differential pressure early warning system based on a big data platform comprises a vehicle-mounted battery data acquisition module, a vehicle-mounted TBOX, a storage server and a big data platform;
the vehicle-mounted battery data acquisition module acquires battery data of a vehicle and uploads the battery data to the storage server for storage through the vehicle-mounted TBOX;
and the big data platform analyzes and processes the big data based on the data stored in the server to give an early warning prompt.
The vehicle-mounted battery data acquisition module detects data such as the highest cell voltage, the lowest cell voltage, the battery SOC, the temperature and the current data of the battery through a BMS sensor, a current sensor and the like, and the data are uploaded to the server through TBOX. The vehicle-mounted battery data acquisition module periodically sends data of the highest single voltage, the lowest single voltage, the battery SOC, the temperature and the current of the battery to the TBOX in a message mode. The battery data can be periodically acquired in a mode of acquiring once in 10ms or 10s, then the acquired battery data is stamped with a corresponding timestamp to form a data message, and the data message is uploaded to a server for storage. Because battery electric quantity is big more, the battery monomer is more, has caused when gathering the biggest monomer voltage and the lowest monomer voltage, the data bulk of uploading just also has become, for example need gather the voltage of uploading each battery, sampling period is once for 10ms simultaneously, the message data of gathering like this is very much, can't handle and give the early warning in local BMS, thereby this application is saved and is given the warning through the data analysis of big data platform call server in through the server.
The big data platform analyzes the battery data according to various models defined by the big data platform and then gives out judgment to judge whether to give out early warning, and if the big data platform does not need to give out pressure difference early warning, the big data platform is not operated; if the situation that early warning needs to be given is judged, the big data platform can give early warning to the user and the service station respectively, wherein the step of giving early warning to the user comprises the step of sending early warning information to the vehicle-mounted TBOX through the TSP platform and then forwarding the early warning information to the vehicle-mounted TBOX, and the vehicle-mounted TBOX gives early warning reminding through a voice or display screen mode. Or send early warning information to the car networking APP that the vehicle corresponds through the TSP platform, directly inform the user this pressure differential early warning information through the APP. And inform the service station generally for the 4S shop repair spot that the vehicle maintained, with data and pressure differential warning propelling movement to the service station, make things convenient for the service station in time to contact the car owner and overhaul the maintenance, avoid further worsening.
Further, the vehicle-mounted TBOX uploads the battery data of the vehicle and uploads the position information of the vehicle at the same time; when the pressure difference early warning fault is analyzed, the big data platform sends early warning information and position information of a vehicle to a vehicle service station corresponding to the position of the vehicle, and simultaneously sends the early warning information and invites the station entering maintenance information to a vehicle machine TBOX of the vehicle or a user internet of vehicles APP for early warning reminding and maintenance reminding. Just so can inform user and service station two-way notice, in time solve the early warning information that appears, in time overhaul the maintenance, GPS positional information can be with early warning information propelling movement to nearest service station, will maintain information transmission such as address information and the contact means of station simultaneously and remind in user's car networking APP or the car machine, also convenience of customers in time sends the vehicle to service station and overhauls.
The application also provides a new energy battery pressure difference early warning method based on the big data platform, which comprises the steps of collecting vehicle battery data in real time through a battery data collecting module and uploading the vehicle battery data to a server; the big data platform accesses the server to obtain battery data of the vehicle, analyzes the battery data to obtain whether the pressure difference of the battery meets the pressure difference early warning, and sends out a pressure difference early warning signal to a user or a service station to perform pressure difference early warning when the pressure difference early warning is met.
The big data platform preprocesses data in the server, eliminates invalid data, analyzes battery data in each vehicle use time period and/or historical pressure difference data, and sends out pressure difference early warning according to an analysis result. The method for rejecting invalid data on the big data platform comprises the steps of sorting received battery message data according to a time sequence, and rejecting messages of which the battery data meets the conditions that the highest monomer voltage is less than 0.5V, or the highest monomer voltage is more than 5V, or the lowest monomer voltage is less than 0.5V, or the lowest monomer voltage is more than 5V, or the highest temperature is more than 125 ℃, or the highest temperature is less than-40 ℃, or the lowest temperature is more than 125 ℃ or the lowest temperature is less than-40 ℃.
Thereby big data platform adopts multiple model to carry out the analysis to the data of battery and gives early warning information, can in time give the early warning when appearing unusually, and the model in the big data platform can set up according to the demand, and this application provides two kinds of analytical model, current day pressure differential proportion threshold value model and historical pressure differential early warning model.
Under the current day differential pressure proportion early warning model: and judging the battery pressure difference after the vehicle is started at the same day, counting the number t1 of abnormal battery pressure difference messages of the vehicle and the number t2 of total uploaded messages after the vehicle is started, triggering pressure difference early warning when the value of t1/t2 is greater than an alarm ratio threshold value, and sending the pressure difference early warning by a large data platform.
And under the historical differential pressure early warning model, analyzing the battery data to judge whether the historical differential pressure judgment condition is met, and comparing the battery differential pressure with a differential pressure threshold value at the moment to judge whether differential pressure early warning is carried out or not. When the current of the battery is smaller than a set current threshold value, the duration time is larger than a time threshold value, and the temperature is larger than a set temperature threshold value, the condition that the current meets the historical pressure difference judgment condition at the moment is judged, a pressure difference threshold value is obtained based on the current SOC of the battery, the current battery pressure difference is compared with the battery pressure difference threshold value, judgment is carried out, an early warning prompt is given, and when the current battery pressure difference is larger than the battery pressure difference threshold value, a pressure difference early warning is given.
The technical scheme of the application comprises the following parts: BMS data acquisition module, current and voltage sensor, TBOX and gateway, big data platform, server, user terminal.
1. The BMS is used as a data acquisition module and can acquire battery data, the data comprises time, highest cell voltage, lowest cell voltage, charging state, SOC, current, temperature and the like, a periodic acquisition mode is adopted, the data acquired each time are packaged to form a message, and then the message is uploaded to a server.
2. The current and voltage sensor is used for acquiring the current and the total voltage of the battery and the single voltage in the running process of the vehicle in real time.
3. BMS memory space is limited, can't store a large amount of historical data, and battery data can be sent to on-vehicle TBOX and gateway, and on-vehicle TBOX receives the back and forwards relevant data to server storage.
4. The server accepts the TBOX data and stores it.
5. And the big data platform is used for preprocessing, modeling, analyzing and displaying the data. The algorithm is as follows:
pretreatment: namely, the invalid data is deleted, and the data with disordered received time is sorted according to the time sequence. The specific invalid data conditions are as follows: and removing abnormal data of the highest monomer voltage <0.5V | | the highest monomer voltage >5V data | | the lowest monomer voltage <0.5V | | the lowest monomer voltage >5V invalid data | | | the highest temperature >125 ℃ | | | the highest temperature < -40 ℃ and | | | the lowest temperature >125 ℃ | | | | the lowest temperature < -40 ℃. And false alarm of follow-up algorithm due to invalid data is prevented.
The modeling algorithm: divided into two types of early warning
And (3) early warning and judging the pressure difference ratio in the same day: the daily differential pressure proportion is to prevent the sudden situation that the single body is suddenly over-pressurized or under-pressurized due to aging, liquid leakage or other abnormity of the batteries of certain vehicles, and if the proportion of the accumulated message number t1 and the total message number t1 of the certain vehicle in the differential pressure early warning process on a certain day is higher than a defined proportion threshold value t and the message number t1 is greater than the message number threshold value, the differential pressure early warning is triggered. The proportional threshold t and the message number threshold can be debugged and calibrated. Firstly, a differential pressure early warning process refers to a vehicle starting working process, when a vehicle is started, early warning is started, and when the vehicle is flamed out, the early warning process is ended; in the early warning process, messages are uploaded periodically; when the total number of messages in the early warning process is larger than the threshold value of the number of messages and the ratio of the accumulated number of messages t1 generated by the pressure difference early warning to the total number of messages t2 in the process is larger than the proportional threshold value, the early warning is sent out, and the purpose of the early warning is as follows: when the total number of the messages is larger than the threshold value of the number of the messages, the purpose is to avoid that the data volume caused by the transient start that the vehicle is flamed out just after being started is too small, and the early warning accuracy is influenced; and then when the total number of messages is larger than a certain number, if sample data is enough, the proportion of the message condition with abnormal voltage difference to the total number needs to be verified, if the proportion is lower, the message condition with abnormal voltage difference possibly caused by data transmission or interference does not need to be pre-warned, and if the proportion is higher, the risk of abnormal voltage difference exists, and the pre-warning of the voltage difference is needed.
Early warning of historical pressure difference: because all the monomer voltages acquired by the background at present are not necessarily values at the same moment, the current fluctuation of the external discharge working condition is severe. If the differential pressure value at a certain moment is used as a judgment condition, the possibility of erroneous judgment is high. The judgment of the excessive voltage difference of the discharge state is obtained by adopting a static voltage method, and the condition of meeting the static state is as follows: the current is less than or equal to 5A, the differential pressure threshold value is kept after 5 minutes, and the temperature is more than 15 ℃. The OCV is also more accurate because the battery is in a steady state stage at this time.
The above parameters can be calibrated. When the vehicle battery is in a steady state, the battery is subjected to pressure difference judgment, when the current is less than 5A and lasts for five minutes and the battery temperature is greater than 15 ℃, the battery is in a steady state at the moment, the big data platform looks up a table based on the uploaded SOC of the battery at the moment to obtain a discharging pressure difference threshold at the moment, the real-time pressure difference at the moment is compared with the discharging pressure difference threshold, when the current is greater than the discharging pressure difference threshold, the big data platform gives out early warning, and otherwise, the big data platform does not give out early warning; because different SOC power generation differential pressure thresholds are different, the method and the device set a data table in advance for inquiring, and meanwhile, different types may be different, and the method and the device can be calibrated in advance according to actual vehicle batteries.
6. After the big data platform warns that the electric vehicle battery has the pressure difference problem through the above strategy, the geographical position of the vehicle, information such as the specific pressure difference value can be actively displayed on the platform. Thereby feeding back the service station to invite the vehicle to get in for maintenance.
In summary, the scheme has the advantages that the problem of the battery pressure difference can be early warned in advance, so that the battery pressure difference is fed back to the TSP platform and timely contacts with a client to enter the station through the platform. The uncontrollable safety risks such as throwing, burning and the like caused by further aggravation of the pressure difference are avoided.
It is clear that the specific implementation of the invention is not restricted to the above-described modes, and that various insubstantial modifications of the inventive concept and solution are within the scope of protection of the invention.
Claims (10)
1. The utility model provides a new forms of energy battery pressure difference early warning system based on big data platform which characterized in that: the system comprises a vehicle-mounted battery data acquisition module, a vehicle-mounted TBOX, a storage server and a big data platform;
the vehicle-mounted battery data acquisition module acquires battery data of a vehicle and uploads the battery data to the storage server for storage through the vehicle-mounted TBOX;
and the big data platform analyzes and processes the big data based on the data stored in the server to give an early warning prompt.
2. The new energy battery pressure difference early warning system based on the big data platform as claimed in claim 1, characterized in that: and after the big data platform analyzes the uploaded data, the TSP platform sends early warning information to the vehicle-mounted TBOX for vehicle-mounted vehicle reminding.
3. The new energy battery pressure difference early warning system based on the big data platform as claimed in claim 1 or 2, characterized in that: the vehicle-mounted TBOX uploads battery data of the vehicle and uploads position information of the vehicle at the same time; when the pressure difference early warning fault is analyzed, the big data platform sends early warning information and position information of a vehicle to a vehicle service station corresponding to the position of the vehicle, and simultaneously sends the early warning information and invites the in-station maintenance information to be sent to a vehicle machine TBOX or a user internet of vehicles APP for early warning and maintenance reminding.
4. The new energy battery differential pressure early warning system based on the big data platform as claimed in any one of claims 1-3, characterized in that: the vehicle-mounted battery data acquisition module periodically sends the data of the highest cell voltage, the lowest cell voltage, the battery SOC, the temperature and the current of the battery to the TBOX in a message mode.
5. A new energy battery pressure difference early warning method based on a big data platform is characterized in that: comprises the steps of (a) preparing a mixture of a plurality of raw materials,
the battery data of the vehicle are collected in real time through a battery data collecting module and uploaded to a server;
the big data platform accesses the server to obtain battery data of the vehicle, analyzes the battery data to obtain whether the pressure difference of the battery meets the pressure difference early warning, and sends a pressure difference early warning signal to a user or a service station to perform the pressure difference early warning when the pressure difference early warning is met.
6. The new energy battery pressure difference early warning method based on the big data platform as claimed in claim 5, characterized in that: the big data platform preprocesses data in the server, eliminates invalid data, analyzes battery data in each vehicle use time period and/or historical pressure difference data, and sends out pressure difference early warning according to an analysis result.
7. The new energy battery pressure difference early warning method based on the big data platform as claimed in claim 6, characterized in that: the big data platform is internally provided with a current day pressure difference proportion early warning model, and the model is as follows: and judging the battery pressure difference after the vehicle is started at the same day, counting the number t1 of abnormal battery pressure difference messages of the vehicle and the number t2 of total uploaded messages after the vehicle is started, triggering pressure difference early warning when the value of t1/t2 is greater than an alarm ratio threshold value, and sending the pressure difference early warning by a large data platform.
8. The new energy battery pressure difference early warning method based on the big data platform as claimed in claim 5 or 6, characterized in that: the big data platform further comprises a historical pressure difference early warning model, under the model, battery data are analyzed and judged whether historical pressure difference judging conditions are met, and after the historical pressure difference judging conditions are met, the battery pressure difference is compared with a pressure difference threshold value at the moment to judge whether pressure difference early warning is conducted.
9. The new energy battery pressure difference early warning method based on the big data platform as claimed in claim 8, characterized in that: when the current of the battery is smaller than a set current threshold value, the duration time is larger than a time threshold value, and the temperature is larger than a set temperature threshold value, the condition that the current meets the historical pressure difference judgment condition at the moment is judged, a pressure difference threshold value is obtained based on the current SOC of the battery, the current battery pressure difference is compared with the battery pressure difference threshold value, judgment is carried out, an early warning prompt is given, and when the current battery pressure difference is larger than the battery pressure difference threshold value, a pressure difference early warning is given.
10. The new energy battery pressure difference early warning method based on the big data platform as claimed in any one of claims 5-9, characterized in that: the method for eliminating invalid data of the big data platform comprises the steps of sequencing received battery message data according to a time sequence, and eliminating messages of which the battery data meet the conditions that the highest monomer voltage is less than 0.5V, or the highest monomer voltage is more than 5V, or the lowest monomer voltage is less than 0.5V, or the lowest monomer voltage is more than 5V, or the highest temperature is more than 125 ℃, or the highest temperature is less than-40 ℃, or the lowest temperature is more than 125 ℃ or the lowest temperature is less than-40 ℃.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115959004A (en) * | 2022-12-06 | 2023-04-14 | 北汽福田汽车股份有限公司 | Vehicle safety monitoring system and method, vehicle-mounted communication terminal, vehicle and server |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115959004A (en) * | 2022-12-06 | 2023-04-14 | 北汽福田汽车股份有限公司 | Vehicle safety monitoring system and method, vehicle-mounted communication terminal, vehicle and server |
| CN115959004B (en) * | 2022-12-06 | 2024-04-05 | 北汽福田汽车股份有限公司 | Vehicle safety monitoring system and method, vehicle-mounted communication terminal, vehicle and server |
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