WO2019184862A1 - 电动汽车及其数据处理系统和数据处理方法 - Google Patents

电动汽车及其数据处理系统和数据处理方法 Download PDF

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Publication number
WO2019184862A1
WO2019184862A1 PCT/CN2019/079486 CN2019079486W WO2019184862A1 WO 2019184862 A1 WO2019184862 A1 WO 2019184862A1 CN 2019079486 W CN2019079486 W CN 2019079486W WO 2019184862 A1 WO2019184862 A1 WO 2019184862A1
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Prior art keywords
bms
data
cloud server
electric vehicle
secondary data
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PCT/CN2019/079486
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English (en)
French (fr)
Inventor
冯天宇
林思岐
邓林旺
吕纯
杨子华
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比亚迪股份有限公司
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Publication of WO2019184862A1 publication Critical patent/WO2019184862A1/zh

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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
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00—Data switching networks
    • H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
    • H04L12/40—Bus networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00—Data switching networks
    • H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
    • H04L12/40—Bus networks
    • H04L12/40006—Architecture of a communication node
    • 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
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
    • H04W4/44—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/80—Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00—Data switching networks
    • H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
    • H04L12/40—Bus networks
    • H04L2012/40208—Bus networks characterized by the use of a particular bus standard
    • H04L2012/40215—Controller Area Network CAN
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00—Data switching networks
    • H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
    • H04L12/40—Bus networks
    • H04L2012/40267—Bus for use in transportation systems
    • H04L2012/40273—Bus for use in transportation systems the transportation system being a vehicle
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Definitions

  • the present disclosure relates to the field of electric vehicle technology, and in particular, to a data processing system for an electric vehicle, a data processing method for the electric vehicle, and an electric vehicle.
  • BMS Battery Management System
  • the BMS transmits the collected battery voltage, current, temperature, power, SOC (State of Charge) and other data to the vehicle terminal via the CAN (Controller Area Network) power network, and is uploaded by the vehicle terminal. To the server.
  • CAN Controller Area Network
  • the data transmitted by the BMS to the vehicle-mounted terminal is the data processed by the BMS in advance, and the vehicle-mounted terminal only transmits and receives the data sent by the BMS, and does not perform secondary processing or return to the BMS. It is used to update the BMS pre-stored reference curve, and the way of data transmission between the BMS and the vehicle-mounted terminal depends on the electric vehicle CAN power network.
  • the BMS Due to the processing speed and data storage space of the BMS and the vehicle terminal, the BMS cannot collect the voltage information of all the cells of the battery pack and upload it to the cloud server, and cannot process the information of all the monomers and the temperature, aging degree, current, etc. Change relationship
  • the present disclosure aims to solve at least one of the technical problems in the above technology to some extent.
  • the first object of the present disclosure is to provide a data processing system for an electric vehicle, which can continuously update a reference curve pre-stored in the BMS, and can accurately predict various status information of the power battery through the updated reference curve. It is convenient for the effective management of the power battery, which is beneficial to improving the service life of the power battery.
  • a second object of the present disclosure is to provide a data processing method for an electric vehicle.
  • a third object of the present disclosure is to propose an electric vehicle.
  • a first aspect of the present disclosure provides a data processing system for an electric vehicle, comprising a cloud server and a battery management system BMS disposed on the electric vehicle, wherein the BMS is used for collecting a state parameter of the plurality of single cells, and generating primary data according to the state parameters of the plurality of single cells, and transmitting the primary data to the cloud server, and receiving the secondary information fed back by the cloud server Data, and updating a reference curve pre-stored in the BMS according to the secondary data; the cloud server is configured to acquire a vehicle identification code VIN (Vehicle Identification Number) of the electric vehicle and the Level 1 data, and generating the secondary data according to the VIN and the primary data.
  • VIN Vehicle Identification Number
  • the state parameters of the plurality of single cells are collected by the BMS, and the first level data is generated according to the state parameters of the plurality of single cells, and the first level data is sent to the cloud server.
  • the cloud server generates secondary data according to the vehicle identification code VIN and the primary data of the electric vehicle, and receives the secondary data fed back by the cloud server through the BMS, and updates the reference curve pre-stored in the BMS according to the secondary data. Therefore, the reference curve pre-stored in the BMS can be continuously updated, and the updated reference curve can accurately predict the state information of the power battery, thereby facilitating effective management of the power battery, and is beneficial to improving the service life of the power battery.
  • the data processing system of the electric vehicle proposed according to the above embodiment of the present disclosure may further have the following additional technical features:
  • the BMS includes: a battery information collector BIC (Battery Information Collector), the plurality of BICs respectively corresponding to a plurality of single cells in the power battery, Collecting state parameters of the plurality of single cells; a battery control unit BCU (Battery Control Unit), the BCU is connected to the plurality of BICs, and communicates with the cloud server, the BCU And configured to generate the primary data according to the state parameter of the power battery, and receive secondary data fed back by the cloud server, and update a reference curve pre-stored in the BMS according to the secondary data.
  • a battery information collector BIC Battery Information Collector
  • BCU Battery Control Unit
  • the BCU includes: a first controller, configured to perform vehicle control according to a state parameter of the power battery; and a second controller, configured to communicate with the cloud server, and according to The state parameter of the power battery generates the first level data, and receives the secondary data fed back by the cloud server, and updates the reference curve prestored in the BMS according to the secondary data.
  • the data processing system of the electric vehicle further includes: a charging post for charging the electric vehicle, and when determining that the electric vehicle is in a constant current charging phase, by charging a CAN network or Communicating with the BMS to acquire the primary data, and send the primary data to the cloud server, and receive secondary data fed back by the cloud server, and pass the charging CAN network or The Bluetooth network feeds back to the BMS.
  • the data processing system of the electric vehicle further includes: an in-vehicle terminal, configured to send the first-level data to the cloud server, and receive secondary data fed back by the cloud server, and feed back To the BMS.
  • the secondary data includes a battery reference curve corresponding to the plurality of single cells.
  • a second aspect of the present disclosure provides a data processing method for an electric vehicle, wherein a battery management system BMS is disposed above the electric vehicle, and the method includes the following steps: the BMS collection a state parameter of the plurality of single cells, and generating first level data according to the state parameters of the plurality of single cells, and transmitting the first level data to the cloud server; the cloud server acquiring the vehicle identifier of the electric vehicle a code VIN, and generating the secondary data according to the VIN and the primary data; the BMS receiving secondary data fed back by the cloud server, and pre-preserving a reference to the BMS according to the secondary data The curve is updated.
  • the BMS collects state parameters of the plurality of single cells, generates first level data according to the state parameters of the plurality of single cells, and transmits the first level data to the cloud server.
  • the cloud server obtains the vehicle identification code VIN of the electric vehicle, and generates secondary data according to the VIN and the primary data.
  • the BMS receives the secondary data fed back by the cloud server, and updates the reference curve pre-stored in the BMS according to the secondary data. Therefore, the reference curve pre-stored in the BMS can be continuously updated, and the updated reference curve can accurately predict the state information of the power battery, thereby facilitating effective management of the power battery, and is beneficial to improving the service life of the power battery.
  • the data processing method of the electric vehicle according to the above embodiment of the present disclosure may further have the following additional technical features:
  • the data processing method of the electric vehicle further includes: charging the electric vehicle to charge the electric vehicle, and when determining that the electric vehicle is in a constant current charging phase, by charging a CAN network or a Bluetooth network with The BMS communicates to obtain the first-level data, and sends the first-level data to the cloud server, and receives secondary data fed back by the cloud server, and feeds back through the charging CAN network or the Bluetooth network. To the BMS.
  • the secondary data includes a battery reference curve corresponding to the plurality of single cells.
  • an embodiment of the third aspect of the present disclosure provides an electric vehicle, on which a battery management system BMS is disposed, wherein the BMS is used to: collect state parameters of a plurality of single cells And generating, according to the state parameters of the plurality of single cells, the first level data, and sending the first level data to the cloud server, so that the cloud server acquires the vehicle identification code VIN of the electric vehicle, and according to the The VIN and the primary data generate the secondary data; receive secondary data fed back by the cloud server, and update a reference curve pre-stored in the BMS according to the secondary data.
  • the state parameters of the plurality of single cells are collected by the BMS, and the first level data is generated according to the state parameters of the plurality of single cells, and the first level data is sent to the cloud server to make the cloud server
  • the vehicle identification code VIN of the electric vehicle is obtained, and the secondary data is generated according to the VIN and the primary data, and then the secondary data fed back by the cloud server is received, and the reference curve pre-stored in the BMS is updated according to the secondary data. Therefore, the reference curve pre-stored in the BMS can be continuously updated, and the updated reference curve can accurately predict the state information of the power battery, thereby facilitating effective management of the power battery, and is beneficial to improving the service life of the power battery.
  • the electric vehicle proposed according to the above embodiment of the present disclosure may further have the following additional technical features:
  • the BMS includes: a plurality of battery collectors BIC respectively corresponding to a plurality of single cells in the power battery for collecting the plurality of single cells a status parameter; a battery control unit BCU, the BCU is connected to the plurality of BICs, and is in communication with the cloud server, the BCU is configured to generate the first level data according to a state parameter of the power battery, and receive The secondary data fed back by the cloud server, and updating the reference curve pre-stored in the BMS according to the secondary data.
  • the BCU includes: a first controller, configured to perform vehicle control according to a state parameter of the power battery; and a second controller, configured to communicate with the cloud server, and according to The state parameter of the power battery generates the first level data, and receives the secondary data fed back by the cloud server, and updates the reference curve prestored in the BMS according to the secondary data.
  • the electric vehicle further includes: an in-vehicle terminal, configured to send the first-level data to the cloud server, and receive secondary data fed back by the cloud server, and feed back to the BMS .
  • the secondary data includes a battery reference curve corresponding to the plurality of single cells.
  • FIG. 1 is a block diagram showing the structure of a data processing system of an electric vehicle according to an embodiment of the present disclosure
  • FIG. 2 is a block diagram showing the structure of a data processing system of an electric vehicle according to an embodiment of the present disclosure
  • FIG. 3 is a block diagram showing the structure of a data processing system of an electric vehicle according to another embodiment of the present disclosure
  • FIG. 4 is a block diagram showing the structure of a data processing system of an electric vehicle according to another embodiment of the present disclosure.
  • FIG. 5 is a structural block diagram of a data processing system of an electric vehicle according to still another embodiment of the present disclosure.
  • FIG. 6 is a flowchart of a data processing method of an electric vehicle according to an embodiment of the present disclosure
  • FIG. 7 is a structural block diagram of an electric vehicle according to an embodiment of the present disclosure.
  • FIG. 8 is a structural block diagram of an electric vehicle according to another embodiment of the present disclosure.
  • FIG. 1 is a block diagram showing the structure of a data processing system of an electric vehicle according to an embodiment of the present disclosure.
  • a data processing system of an electric vehicle includes a cloud server 10 and a battery management system BMS20 disposed above the electric vehicle.
  • the BMS 20 is configured to collect state parameters of the plurality of single cells, generate primary data according to the state parameters of the plurality of single cells, and send the primary data to the cloud server 10, and receive the secondary information fed back by the cloud server 10.
  • the data is updated according to the secondary data to a reference curve (for example, a battery reference curve) pre-stored in the BMS 20, wherein the pre-stored reference curve can be calibrated according to actual conditions.
  • the cloud server 10 is configured to acquire the vehicle identification code VIN and the primary data of the electric vehicle, and generate secondary data according to the VIN and the primary data.
  • the plurality of single cells described in this embodiment may be a plurality of single cells of the power battery in the electric vehicle
  • the first parameter described in this embodiment may be the middle of the BMS processed algorithm.
  • the parameter, and the first-level parameter may include a vehicle identification code VIN of the electric vehicle in which the plurality of single cells are located.
  • the state parameters of the plurality of single cells may include a voltage of the single battery, a battery equalization condition, a temperature of the single battery, a current of the single battery, a power of the single battery, and a single battery. SOC, etc.
  • the secondary data may include a battery reference curve corresponding to the plurality of single cells.
  • the battery reference curve may include a charge and discharge UI reference curve of the power battery, an OCV-Q reference curve, and Q-SOH. Reference curve, R-SOH-IT reference curve and historical self-discharge rate reference curve.
  • the BMS 20 can collect the state parameters of the plurality of single cells as described above at a preset time t. For example, the state parameters of the plurality of single cells are collected at time t (first time), and the BMS 20 can be based on the states of the plurality of single cells.
  • the parameter generates first-level data, wherein the first-level data may include peak positions and peak heights of first-order derivatives of all single-cell VQ curves obtained by using a BMS charging algorithm, and battery model RC network parameters obtained by using a BMS discharge algorithm, And all primary data as a function of temperature, current, SOC, and number of battery cycles.
  • the BMS 20 can transmit and receive the first-level data (that is, the first-level data generated based on the state parameters of the plurality of single cells at time t) through the 4G (the 4th Generation mobile communication technolog).
  • a module or other wireless device sends to the cloud server 10.
  • the cloud server 10 receives the primary data, and analyzes and saves the primary data to obtain the vehicle identification code VIN of the electric vehicle, and then searches for the vehicle identification code from the database of the cloud server 10 according to the vehicle identification code VIN.
  • the battery reference curve finally the cloud server 10 feeds back the generated secondary data to the BMS 20, and the cloud server 10 can also save the secondary data to the database.
  • the BMS 20 receives the secondary data fed back by the cloud server 10, and updates the reference curve pre-stored in the BMS 20 according to the secondary data (for example, replacing the pre-stored reference curve with the reference curve in the received secondary data) as A reference curve for battery prediction management.
  • the historical data of the electric vehicle described in this embodiment may include historical state parameters of the power battery (for example, state parameters of the plurality of single cells described above) and historical level data and secondary data of the power battery. .
  • the historical status parameter of the power battery may be sent by the BMS 20 to the cloud server 10.
  • the BMS 20 collects the state parameters of the plurality of single cells described above at 2*t time, and generates first-level data according to the state parameters of the plurality of single cells, and further the first-level data (ie, according to the 2*t time).
  • the primary data generated by the status parameters of the plurality of single cells is transmitted to the cloud server 10 through the provided 4G transceiver module or other wireless device.
  • the cloud server 10 receives the primary data, and analyzes and saves the primary data to obtain the vehicle identification code VIN of the electric vehicle, and then searches for the vehicle identification code from the database of the cloud server 10 according to the vehicle identification code VIN.
  • the historical data of the electric vehicle corresponding to the VIN, the preset algorithm, etc., and the second-level analysis of the primary data with the historical data and/or the preset algorithm to generate the secondary data, and finally the secondary level generated by the cloud server 10 The data is fed back to the BMS 20, and the cloud server 10 can also save the secondary data to the database.
  • the BMS 20 receives the secondary data fed back by the cloud server 10, and updates the reference curve pre-stored in the BMS 20 according to the secondary data as a reference curve for battery prediction management.
  • the BMS 20 continuously estimates and estimates the new first-level data and uploads it to the cloud server 10.
  • the cloud server 10 continuously generates new secondary data based on the historical data and returns (feedback) to the BMS 10. Continuous loop iteration, thereby making the overall battery system prediction result closer to the real state of the power battery, which is beneficial to effectively manage the power battery and improve the service life of the power battery.
  • the BMS may include a plurality of battery collectors BIC21 and a battery control unit BCU22.
  • the plurality of BICs 21 respectively correspond to a plurality of single cells in the power battery, and are used for collecting state parameters of the plurality of single cells.
  • the battery control unit BCU22 is connected to the plurality of BICs 21 and communicates with the cloud server 10.
  • the BCU 22 is configured to generate primary data according to the state parameters of the power battery, and receive the secondary data fed back by the cloud server 10, and the secondary data according to the secondary data.
  • the pre-stored reference curve is updated.
  • each BIC21 can send data to BCU22 via CAN, in-vehicle network FlexRay or Daisy Chain (daisy chain).
  • the BCU 22 and all of the BICs 21 can be assembled with all of the battery cells pack inside the cabin of an electric vehicle.
  • BIC21 can be used for battery cell voltage sampling and monitoring, battery equalization, battery pack temperature sampling and monitoring.
  • BCU22 can be used for bus current detection, system insulation monitoring, battery system up/down management, battery system thermal management, battery state of charge SOC (State of Charge) estimation, battery health state SOH (State of Health) estimation, battery power state SOP (State of Power) estimation, fault diagnosis, vehicle communication and online program update, data recording.
  • the BCU 22 includes a first controller 22a and a second controller 22b.
  • the first controller 22a is configured to perform vehicle control according to the state parameter of the power battery.
  • the second controller 22b is configured to communicate with the cloud server 10, generate primary data according to the state parameters of the power battery, receive the secondary data fed back by the cloud server 10, and perform a reference curve pre-stored in the BMS according to the secondary data. Update.
  • the BCU 22 has a dual MCU (Micro Control Unit) with powerful data storage space and high-speed data processing speed (ie, the first controller 22a and the second controller 22b).
  • the utility model has the offline data processing capability, and can perform data interaction with the cloud server 10 by means of wireless communication through a wireless communication module. Further, the cloud server 10 performs cloud computing and big data analysis on the battery state information and the state parameters of the entire life cycle of the power battery, thereby realizing current state management and future state prediction of the power battery.
  • the data processing system of the electric vehicle further includes a charging post 30 for charging the electric vehicle, and when determining that the electric vehicle is in a constant current charging phase, Communicating with the BMS 20 through the charging CAN network to acquire primary data, and transmitting the primary data to the cloud server 10, and receiving the secondary data fed back by the cloud server 10, and feeding back to the BMS through the charging CAN network.
  • the state parameters of the plurality of single cells collected by the BMS 20 are relatively smooth, that is, the rate of change is relatively stable, thereby ensuring the accuracy of the primary data. Sex.
  • the charging pile 30 can determine in real time whether the electric vehicle is currently in the constant current charging phase, and if so, can communicate with the BMS through the charging CAN network to send an acquisition command to BMS20. After receiving the acquisition instruction, the BMS 20 may collect the state parameters of the plurality of single cells, and generate primary data according to the state parameters of the plurality of single cells, and return the primary data to the charging pile 30. .
  • the charging post 30 can send the first-level number to the cloud server 10 through the provided 4G transceiver module.
  • the cloud server 10 receives the primary data, and analyzes and saves the primary data to obtain the vehicle identification code VIN of the electric vehicle, and then searches for the vehicle identification code from the database of the cloud server 10 according to the vehicle identification code VIN.
  • the historical data of the electric vehicle corresponding to the VIN, the preset algorithm, and the like, and performing secondary analysis on the primary data with the historical data and/or the preset algorithm to generate the secondary data, and finally the cloud server 10 passes the 4G network.
  • the secondary data is fed back to the charging station 30.
  • the charging post 30 feeds back to the BMS 20 through the charging CAN network.
  • the BMS 20 receives the secondary data fed back by the charging station 30, and updates the reference curve pre-stored in the BMS 20 based on the secondary data as a reference curve for battery prediction management.
  • the charging post 30 can also be used to communicate with the BMS 20 via the Bluetooth network to obtain primary data when the electric vehicle is in the constant current charging phase, and send the primary data to the cloud server 10, and receive the cloud.
  • the secondary data fed back by the server 10 is fed back to the BMS 20 via the Bluetooth network.
  • the manufacturer can separately provide the BMS20 and the charging pile 30 with the Bluetooth transceiver module.
  • the charging transceiver 30 can realize the BMS20 through the Bluetooth transceiver module equipped with the Bluetooth transceiver module equipped with the BMS20.
  • the communication between the charging piles 30 is performed to obtain the first-level data, and then the first-level data is sent to the cloud server 10 through the 4G transceiver module provided by the cloud, and the cloud server 10 receives the first-level data and the first-level data.
  • the cloud server 10 receives the first-level data and the first-level data.
  • the charging post 30 feeds back to the BMS 20 by establishing a Bluetooth connection with the BMS 20.
  • the BMS 20 receives the secondary data fed back by the charging station 30, and updates the reference curve pre-stored in the BMS 20 based on the secondary data as a reference curve for battery prediction management.
  • the data processing system of the electric vehicle may not equip the BMS 20 with a wireless communication module (eg, a 4G transceiver module, a Bluetooth transceiver module), but only a wireless communication module (eg, a 4G transceiver module).
  • a wireless communication module eg, a 4G transceiver module, a Bluetooth transceiver module
  • the data transmission timing is limited to the constant current charging phase of the electric vehicle by the charging pile 30, while improving the calculation accuracy of the battery pack state parameter, the data computing load and the network transmission load are also greatly saved, and the wireless communication module is configured.
  • the charging pile 30 instead of the BMS 20, it is not necessary to occupy any space of the whole vehicle, which saves the development cost and the verification cost that the whole vehicle needs to be re-arranged.
  • the data processing system of the electric vehicle may further include an in-vehicle terminal 40 for transmitting primary data to the cloud server 10 and receiving secondary data fed back by the cloud server 10. And feedback to the BMS.
  • the in-vehicle terminal 40 can communicate with the BMS 20 through the electric vehicle power CAN network to acquire the primary data and transmit the primary data.
  • the cloud server 10 Up to the cloud server 10, and receiving the secondary data fed back by the cloud server 10, and feeding back to the BMS 20 through the electric vehicle power CAN network, so that the MS 20 receives the secondary data fed back by the vehicle terminal 40, and pre-stores the BMS 20 according to the secondary data.
  • the reference curve is updated to serve as a reference curve for battery prediction management.
  • the BMS 20 can monitor the connection state of the electric vehicle and the charging pile 30 in real time, and when the BMS 20 detects that the electric vehicle is disconnected from the charging pile 30, the vehicle terminal can be activated.
  • the 40G 4G transceiver module receives the secondary data fed back by the cloud server 10 through the 4G transceiver module configured by the vehicle terminal 40, and transmits the secondary data to the BMS 20 through the electric vehicle power CAN network.
  • the BMS 20 receives the secondary data fed back by the in-vehicle terminal 40, and updates the reference curve pre-stored in the BMS 20 according to the secondary data as a reference curve for battery prediction management.
  • the state parameters of the plurality of single cells are collected by the BMS, and the first level data is generated according to the state parameters of the plurality of single cells, and the first level data is sent to
  • the cloud server further generates secondary data according to the vehicle identification code VIN and the primary data of the electric vehicle through the cloud server, and receives the secondary data fed back by the cloud server through the BMS, and updates the reference curve pre-stored in the BMS according to the secondary data. . Therefore, the reference curve pre-stored in the BMS can be continuously updated, and the updated reference curve can accurately predict the state information of the power battery, thereby facilitating effective management of the power battery, and is beneficial to improving the service life of the power battery.
  • FIG. 6 is a flow chart of a data processing method of an electric vehicle according to an embodiment of the present disclosure.
  • a battery management system BMS is disposed above the electric vehicle.
  • a data processing method for an electric vehicle includes the following steps:
  • the BMS collects status parameters of the plurality of single cells, and generates primary data according to the status parameters of the plurality of single cells, and sends the primary data to the cloud server.
  • the cloud server acquires the vehicle identification code VIN of the electric vehicle, and generates secondary data according to the VIN and the primary data.
  • the BMS receives the secondary data fed back by the cloud server, and updates the reference curve pre-stored in the BMS according to the secondary data.
  • the data processing method of the electric vehicle further includes: charging the electric vehicle to charge the electric vehicle, and communicating with the BMS through the charging CAN network or the Bluetooth network when determining that the electric vehicle is in the constant current charging phase Acquire primary data, send the primary data to the cloud server, and receive the secondary data fed back by the cloud server, and feed back to the BMS through the charging CAN network or the Bluetooth network.
  • the secondary data includes a battery reference curve corresponding to the plurality of single cells.
  • the BMS collects the state parameters of the plurality of single cells, and generates the first level data according to the state parameters of the plurality of single cells, and sends the first level data to the The cloud server, then the cloud server obtains the vehicle identification code VIN of the electric vehicle, and generates secondary data according to the VIN and the primary data.
  • the BMS receives the secondary data fed back by the cloud server, and the reference curve pre-stored in the BMS according to the secondary data. Update. Therefore, the reference curve pre-stored in the BMS can be continuously updated, and the updated reference curve can accurately predict the state information of the power battery, thereby facilitating effective management of the power battery, and is beneficial to improving the service life of the power battery.
  • FIG. 7 is a structural block diagram of an electric vehicle according to an embodiment of the present disclosure.
  • a battery management system BMS20 is disposed above the electric vehicle 200, wherein the BMS 20 is configured to collect state parameters of a plurality of single cells, and generate primary data according to state parameters of the plurality of single cells, and Sending the primary data to the cloud server 10, so that the cloud server 10 acquires the vehicle identification code VIN of the electric vehicle 200, and generates secondary data according to the VIN and the primary data; receives the secondary data fed back by the cloud server 10, and according to the second The level data updates the reference curve pre-stored in the BMS.
  • the BMS 20 includes a plurality of battery collectors BIC21 and a battery control unit BCU22.
  • the plurality of BICs 21 respectively correspond to a plurality of single cells in the power battery, and are used for collecting state parameters of the plurality of single cells.
  • the battery control unit BCU22 is connected to the plurality of BICs 21 and communicates with the cloud server 10.
  • the BCU 22 is configured to generate primary data according to the state parameters of the power battery, and receive the secondary data fed back by the cloud server 10, and the secondary data according to the secondary data.
  • the pre-stored reference curve is updated.
  • the BCU 22 includes a first controller 22a and a second controller 22b.
  • the first controller 22a is configured to perform vehicle control according to the state parameter of the power battery.
  • the second controller 22b is configured to communicate with the cloud server 10, generate first-level data according to the state parameter of the power battery, and receive the secondary data fed back by the cloud server 10, and the reference curve pre-stored in the BMS 20 according to the secondary data. Update.
  • the electric vehicle further includes an in-vehicle terminal 40 for transmitting first-level data to the cloud server 10, and receiving secondary data fed back by the cloud server 10, and feeding back to the BMS 20 .
  • the secondary data includes a battery reference curve corresponding to the plurality of single cells.
  • an electric vehicle collects state parameters of a plurality of single cells through a BMS, generates first-level data according to state parameters of the plurality of single cells, and transmits the first-level data to the cloud server,
  • the cloud server obtains the vehicle identification code VIN of the electric vehicle, generates secondary data according to the VIN and the primary data, and then receives the secondary data fed back by the cloud server, and updates the reference curve pre-stored in the BMS according to the secondary data. Therefore, the reference curve pre-stored in the BMS can be continuously updated, and the updated reference curve can accurately predict the state information of the power battery, thereby facilitating effective management of the power battery, and is beneficial to improving the service life of the power battery.
  • first and second are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated.
  • features defining “first” and “second” may include one or more of the features either explicitly or implicitly.
  • the meaning of "a plurality” is two or more unless specifically and specifically defined otherwise.
  • the terms “installation”, “connected”, “connected”, “fixed”, and the like, are to be understood broadly, and may be either a fixed connection or a detachable connection, unless explicitly stated or defined otherwise. , or integrated; can be mechanical connection, or can be electrical connection; can be directly connected, or can be indirectly connected through an intermediate medium, can be the internal communication of two elements or the interaction of two elements.
  • the specific meanings of the above terms in the present disclosure can be understood by those skilled in the art on a case-by-case basis.
  • the first feature "on” or “under” the second feature may be a direct contact of the first and second features, or the first and second features may be indirectly through an intermediate medium, unless otherwise explicitly stated and defined. contact.
  • the first feature "above”, “above” and “above” the second feature may be that the first feature is directly above or above the second feature, or merely that the first feature level is higher than the second feature.
  • the first feature “below”, “below” and “below” the second feature may be that the first feature is directly below or obliquely below the second feature, or merely that the first feature level is less than the second feature.

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Abstract

本公开公开了一种电动汽车及其数据处理系统和数据处理方法，所述数据处理系统包括云服务器和设置在电动汽车之上的电池管理系统BMS，其中，BMS，用于采集多个单体电池的状态参数，并根据多个单体电池的状态参数生成一级数据，以及将一级数据发送至云服务器，并且接收云服务器反馈的二级数据，并根据二级数据对BMS中预存的参考曲线进行更新；云服务器，用于获取电动汽车的车辆标识码VIN和一级数据，并根据VIN和一级数据生成二级数据。由此，可不断对BMS中预存的参考曲线进行更新，通过更新后的参考曲线能够准确预估动力电池的各项状态信息，便于对动力电池进行有效管理，有利于提高动力电池的使用寿命。

Description

电动汽车及其数据处理系统和数据处理方法
相关申请的交叉引用
本申请基于申请号为201810287040.7，申请日为2018年03月30日的中国专利申请提出，并要求该中国专利申请的优先权，该中国专利申请的全部内容在此引入本申请作为参考。
技术领域
本公开涉及电动汽车技术领域，特别涉及一种电动汽车的数据处理系统、一种电动汽车的数据处理方法和一种电动汽车。
背景技术
BMS(Battery Management System，电池管理系统)作为电池管理单元，对电动汽车在全生命周期的正常运行有着不可替代的作用。相关技术中，传统BMS的主要功能包括电池信息采集、电池参数估算、均衡管理、热管理、保护、诊断等功能。BMS将采集到的电池电压、电流、温度、电量、SOC(State of Charge，荷电状态)等数据，通过CAN(Controller Area Network，控制器局域网络)动力网传输给车载终端，由车载终端上传至服务器。
需要特别说明的是，BMS传输给车载终端的数据都是由BMS预先处理后的数据，且车载终端只对BMS发来的数据进行收发和传输，不做二次处理、也不回传给BMS用于更新BMS预存的参考曲线，且BMS与车载终端的数据传输的方式依托于电动汽车CAN动力网。
然而，上述技术中存在如下缺点：
(1)受限于BMS与车载终端的处理速度和数据存储空间，BMS无法采集电池包全部单体的电压信息上传至云端服务器，也无法处理全体单体的信息与温度、老化程度、电流等的变化关系；
(2)受限于电动汽车CAN动力网负载率，BMS上传的数据无法包括全部电池单体的全部历史充放电数据；
(3)受限于技术与成本，BMS上传的数据没有做二次处理与比较，也没有下载回传给BMS，用于更新BMS算法中的参考曲线。
发明内容
本公开旨在至少在一定程度上解决上述技术中的技术问题之一。
为此，本公开的第一个目的在于提出一种电动汽车的数据处理系统，可不断对BMS中预存的参考曲线进行更新，通过更新后的参考曲线能够准确预估动力电池的各项状态信息，便于对动力电池进行有效管理，有利于提高动力电池的使用寿命。
本公开的第二个目的在于提出一种电动汽车的数据处理方法。
本公开的第三个目的在于提出一种电动汽车。
为达到上述目的，本公开第一方面实施例提出了一种电动汽车的数据处理系统，包括云服务器和设置在所述电动汽车之上的电池管理系统BMS，其中，所述BMS，用于采集多个单体电池的状态参数，并根据所述多个单体电池的状态参数生成一级数据，以及将所述一级数据发送至所述云服务器，并且接收所述云服务器反馈的二级数据，并根据所述二级数据对所述BMS中预存的参考曲线进行更新；所述云服务器，用于获取所述电动汽车的车辆标识码VIN(Vehicle Identification Number，车辆识别代码)和所述一级数据，并根据所述VIN和所述一级数据生成所述二级数据。
根据本公开实施例的电动汽车的数据处理系统，通过BMS采集多个单体电池的状态参数，并根据多个单体电池的状态参数生成一级数据，以及将一级数据发送至云服务器，进而通过云服务器根据电动汽车的车辆标识码VIN和一级数据生成二级数据，且通过BMS接收云服务器反馈的二级数据，并根据二级数据对BMS中预存的参考曲线进行更新。由此，可不断对BMS中预存的参考曲线进行更新，通过更新后的参考曲线能够准确预估动力电池的各项状态信息，便于对动力电池进行有效管理，有利于提高动力电池的使用寿命。
另外，根据本公开上述实施例提出的电动汽车的数据处理系统还可以具有如下附加的技术特征：
根据本公开的一个实施例，所述BMS包括：多个电池采集器BIC(Battery Information Collector，电池信息采集器)，所述多个BIC分别与动力电池中的多个单体电池相对应，用于采集所述多个单体电池的状态参数；电池控制单元BCU(Battery Control Unit，电池控制单元)，所述BCU与所述多个BIC相连，并与所述云服务器进行通信，所述BCU用于根据所述动力电池的状态参数生成所述一级数据，并接收所述云服务器反馈的二级数据，以及根据所述二级数据对所述BMS中预存的参考曲线进行更新。
根据本公开的一个实施例，所述BCU包括：第一控制器，用于根据所述动力电池的状态参数进行整车控制；第二控制器，用于与所述云服务器进行通信，并根据所述动力电池的状态参数生成所述一级数据，并接收所述云服务器反馈的二级数据，以及根据所述二级数据对所述BMS中预存的参考曲线进行更新。
根据本公开的一个实施例，上述电动汽车的数据处理系统还包括：充电桩，用于对所述电动汽车进行充电，且在判断所述电动汽车处于恒流充电阶段时，通过充电CAN网络或 蓝牙网络与所述BMS进行通信以获取所述一级数据，并将所述一级数据发送至所述云服务器，以及接收所述云服务器反馈的二级数据，并通过所述充电CAN网络或蓝牙网络反馈至所述BMS。
根据本公开的一个实施例，上述电动汽车的数据处理系统还包括：车载终端，用于将所述一级数据发送至所述云服务器，以及接收所述云服务器反馈的二级数据，并反馈至所述BMS。
根据本公开的一个实施例，所述二级数据包括所述多个单体电池对应的电池参考曲线。
为达到上述目的，本公开第二方面实施例提出了一种电动汽车的数据处理方法，其中，在所述电动汽车之上设置有电池管理系统BMS，所述方法包括以下步骤：所述BMS采集多个单体电池的状态参数，并根据所述多个单体电池的状态参数生成一级数据，以及将所述一级数据发送至云服务器；所述云服务器获取所述电动汽车的车辆标识码VIN，并根据所述VIN和所述一级数据生成所述二级数据；所述BMS接收所述云服务器反馈的二级数据，并根据所述二级数据对所述BMS中预存的参考曲线进行更新。
根据本公开实施例的电动汽车的数据处理方法，首先BMS采集多个单体电池的状态参数，并根据多个单体电池的状态参数生成一级数据，以及将一级数据发送至云服务器，然后云服务器获取电动汽车的车辆标识码VIN，并根据VIN和一级数据生成二级数据，最后BMS接收云服务器反馈的二级数据，并根据二级数据对BMS中预存的参考曲线进行更新。由此，可不断对BMS中预存的参考曲线进行更新，通过更新后的参考曲线能够准确预估动力电池的各项状态信息，便于对动力电池进行有效管理，有利于提高动力电池的使用寿命。
另外，根据本公开上述实施例提出的电动汽车的数据处理方法还可以具有如下附加的技术特征：
根据本公开的一个实施例，上述电动汽车的数据处理方法还包括：充电桩对所述电动汽车进行充电，且在判断所述电动汽车处于恒流充电阶段时，通过充电CAN网络或蓝牙网络与所述BMS进行通信以获取所述一级数据，并将所述一级数据发送至所述云服务器，以及接收所述云服务器反馈的二级数据，并通过所述充电CAN网络或蓝牙网络反馈至所述BMS。
根据本公开的一个实施例，所述二级数据包括所述多个单体电池对应的电池参考曲线。
为达到上述目的，本公开第三方面实施例提出了一种电动汽车，在所述电动汽车之上设置有电池管理系统BMS，其中，所述BMS用于：采集多个单体电池的状态参数，并根据所述多个单体电池的状态参数生成一级数据，以及将所述一级数据发送至云服务器，以使所述云服务器获取所述电动汽车的车辆标识码VIN，并根据所述VIN和所述一级数据生 成所述二级数据；接收所述云服务器反馈的二级数据，并根据所述二级数据对所述BMS中预存的参考曲线进行更新。
根据本公开实施例的电动汽车，通过BMS采集多个单体电池的状态参数，并根据多个单体电池的状态参数生成一级数据，以及将一级数据发送至云服务器，以使云服务器获取电动汽车的车辆标识码VIN，并根据VIN和一级数据生成二级数据，而后接收云服务器反馈的二级数据，并根据二级数据对BMS中预存的参考曲线进行更新。由此，可不断对BMS中预存的参考曲线进行更新，通过更新后的参考曲线能够准确预估动力电池的各项状态信息，便于对动力电池进行有效管理，有利于提高动力电池的使用寿命。
另外，根据本公开上述实施例提出的电动汽车还可以具有如下附加的技术特征：
根据本公开的一个实施例，所述BMS包括：多个电池采集器BIC，所述多个BIC分别与动力电池中的多个单体电池相对应，用于采集所述多个单体电池的状态参数；电池控制单元BCU，所述BCU与所述多个BIC相连，并与所述云服务器进行通信，所述BCU用于根据所述动力电池的状态参数生成所述一级数据，并接收所述云服务器反馈的二级数据，以及根据所述二级数据对所述BMS中预存的参考曲线进行更新。
根据本公开的一个实施例，所述BCU包括：第一控制器，用于根据所述动力电池的状态参数进行整车控制；第二控制器，用于与所述云服务器进行通信，并根据所述动力电池的状态参数生成所述一级数据，并接收所述云服务器反馈的二级数据，以及根据所述二级数据对所述BMS中预存的参考曲线进行更新。
根据本公开的一个实施例，上述电动汽车还包括：车载终端，用于将所述一级数据发送至所述云服务器，以及接收所述云服务器反馈的二级数据，并反馈至所述BMS。
根据本公开的一个实施例，所述二级数据包括所述多个单体电池对应的电池参考曲线。
本公开附加的方面的优点将在下面的描述中部分给出，部分将从下面的描述中变得明显，或通过本公开的实践了解到。
附图说明
图1是根据本公开一个实施例的电动汽车的数据处理系统的结构框图；
图2是根据本公开一个具体实施例的电动汽车的数据处理系统的结构框图；
图3是根据本公开另一个具体实施例的电动汽车的数据处理系统的结构框图；
图4是根据本公开另一个实施例的电动汽车的数据处理系统的结构框图；
图5是根据本公开又一个实施例的电动汽车的数据处理系统的结构框图；
图6是根据本公开一个实施例的电动汽车的数据处理方法的流程图；
图7是根据本公开一个实施例的电动汽车的结构框图；以及
图8是根据本公开另一个实施例的电动汽车的结构框图。
具体实施方式
下面详细描述本公开的实施例，所述实施例的示例在附图中示出，其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施例是示例性的，旨在用于解释本公开，而不能理解为对本公开的限制。
下面结合附图来描述本公开实施例的电动汽车的数据处理系统、电动汽车的数据处理方法和电动汽车。
图1是根据本公开一个实施例的电动汽车的数据处理系统的结构框图。
如图1所示，本公开实施例的电动汽车的数据处理系统包括：云服务器10和设置在电动汽车之上的电池管理系统BMS20。
其中，BMS20用于采集多个单体电池的状态参数，并根据多个单体电池的状态参数生成一级数据，以及将一级数据发送至云服务器10，并且接收云服务器10反馈的二级数据，并根据二级数据对BMS20中预存的参考曲线(例如，电池参考曲线)进行更新，其中，预存的参考曲线可根据实际情况进行标定。云服务器10用于获取电动汽车的车辆标识码VIN和一级数据，并根据VIN和一级数据生成二级数据。应说明的是，该实施例中所描述的多个单体电池可为电动汽车中动力电池的多个单体电池，该实施例中所描述的一级参数可为经BMS处理后的算法中间参数，并且该一级参数中可包括上述多个单体电池所在电动汽车的车辆标识码VIN。
在本公开的实施例中，多个单体电池的状态参数可包括单体电池的电压、电池均衡情况、单体电池的温度、单体电池的电流、单体电池的电量、单体电池的SOC等。
在本公开的一个实施例中，二级数据可包括多个单体电池对应的电池参考曲线，例如，电池参考曲线可包括动力电池的充放电U-I参考曲线、OCV-Q参考曲线、Q-SOH参考曲线、R-SOH-I-T参考曲线和历史自放电率参考曲线等。
BMS20可以每隔预设时间t采集上述的多个单体电池的状态参数，如在t时刻(首次)采集到多个单体电池的状态参数，BMS20则可根据该多个单体电池的状态参数生成一级数据，其中，该一级数据可包括利用BMS充电算法求得的所有单体电池V-Q曲线一阶导数的峰位、峰高，利用BMS放电算法求得的电池模型RC网络参数，以及全部一级数据与温度、电流、SOC和电池循环次数的函数关系。然后BMS20可将该一级数据(即，根据t时刻的多个单体电池的状态参数生成的一级数据)通过配有的4G(the 4th Generation mobile communication technolog，第四代移动通信技术)收发模块或其它无线装置发送至云服务器10。
云服务器10接收该一级数据，并对该一级数据进行分析与保存以获取电动汽车的车辆标识码VIN，然后可根据该车辆标识码VIN从云服务器10的数据库中查找与该车辆标识码VIN对应的电动汽车的历史数据、预设算法等，并跟该历史数据和/或预设算法对该一级数据进行二级分析，以生成二级数据(例如，上述多个单体电池对应的电池参考曲线)，最后云服务器10将生成的二级数据反馈至BMS20，同时云服务器10还可将该二级数据保存至数据库中。BMS20接收云服务器10反馈的二级数据，并根据该二级数据对BMS20中预存的参考曲线进行更新(例如，将预存的参考曲线替换为接收到的二级数据中的参考曲线)，以作为电池预测管理的参考曲线。
需要说明的是，该实施例中所描述的电动汽车的历史数据可包括动力电池的历史状态参数(例如，上述多个单体电池的状态参数)和动力电池的历史一级数据和二级数据。其中，动力电池的历史状态参数可以是BMS20发送给云端服务器10的。
BMS20在2*t时刻采集到上述的多个单体电池的状态参数，并根据该多个单体电池的状态参数生成一级数据，进而将该一级数据(即，根据2*t时刻的多个单体电池的状态参数生成的一级数据)通过配有的4G收发模块或其它无线装置发送至云服务器10。云服务器10接收该一级数据，并对该一级数据进行分析与保存以获取电动汽车的车辆标识码VIN，然后可根据该车辆标识码VIN从云服务器10的数据库中查找与该车辆标识码VIN对应的电动汽车的历史数据、预设算法等，并跟该历史数据和/或预设算法对该一级数据进行二级分析，以生成二级数据，最后云服务器10将生成的二级数据反馈至BMS20，同时云服务器10还可将该二级数据保存至数据库中。BMS20接收云服务器10反馈的二级数据，并根据该二级数据对BMS20中预存的参考曲线进行更新，以作为电池预测管理的参考曲线。
随着动力电池充放电循环的深入，BMS20不断拟合估算得到新的一级数据并上传至云服务器10，云服务器10根据历史数据不断生成新的二级数据并回传(反馈)至BMS10，不断的循环迭代，由此，能够使整个电池系统预测结果更接近动力电池的真实状态，有利于对动力电池进行有效管理，提高动力电池的使用寿命。
根据本公开的一个实施例，如图2所示，BMS可包括多个电池采集器BIC21和电池控制单元BCU22。
其中，多个BIC21分别与动力电池中的多个单体电池相对应，用于采集多个单体电池的状态参数。电池控制单元BCU22与多个BIC21相连，并与云服务器10进行通信，BCU22用于根据动力电池的状态参数生成一级数据，并接收云服务器10反馈的二级数据，以及根据二级数据对BMS20中预存的参考曲线进行更新。
其中，每个BIC21均可通过CAN、车载网络FlexRay或Daisy Chain(菊花链)将数据发送至BCU22。
在该实施例中，BCU22和所有的BIC21可与所有的电池单体pack一起装配在电动汽车的车舱内部。
BIC21可用于电池单体电压采样和监控、电池均衡、电池包温度采样和监控，BCU22可用于母线电流检测、系统绝缘监测、电池系统上/下电管理、电池系统热管理、电池荷电状态SOC(State of Charge)估算、电池健康状态SOH(State of Health)估算、电池功率状态SOP(State of Power)估算、故障诊断、整车通讯及在线程序更新、数据记录等。
如图3所示，BCU22包括第一控制器22a和第二控制器22b。其中，第一控制器22a用于根据动力电池的状态参数进行整车控制。第二控制器22b用于与云服务器10进行通信，并根据动力电池的状态参数生成一级数据，并接收云服务器10反馈的二级数据，以及根据二级数据对BMS中预存的参考曲线进行更新。
需要说明的是，在该实施例中，BCU22具有强大的数据存储空间与高速数据处理速度的双MCU(Micro Control Unit,微控制单元)(即，第一控制器22a和第二控制器22b)，具有离线数据处理能力，并可通过无线通讯模块，借助无线通讯方式与云服务器10进行数据交互。进而由云服务器10对动力电池整个生命周期的电池状态信息和状态参数进行云计算与大数据分析，可实现对动力电池的当前状态管理与未来状态预测。
为了防止BMS20与云服务器10的无线通信出现故障，导致BMS20与云服务器10无法进行通讯的问题。根据本公开的一个实施例，如图4所示，上述电动汽车的数据处理系统还包括充电桩30，充电桩30用于对电动汽车进行充电，且在判断电动汽车处于恒流充电阶段时，通过充电CAN网络与BMS20进行通信以获取一级数据，并将一级数据发送至云服务器10，以及接收云服务器10反馈的二级数据，并通过充电CAN网络反馈至BMS。其中需要说明的是，当电动汽车当前处于恒流充电阶段时，BMS20所采集的多个单体电池的状态参数的变化较平滑，即其变化率较稳定，由此能够保证一级数据的准确性。
在用户利用充电桩30对电动汽车进行充电的过程中，充电桩30可实时判断电动汽车当前是否处于恒流充电阶段，如果是，则可通过充电CAN网络与BMS进行通信，以发送获取指令至BMS20。BMS20在接收到该获取指令后，可采集上述的多个单体电池的状态参数，并根据该多个单体电池的状态参数生成一级数据，以及将该一级数据回传至充电桩30。
充电桩30在接收到该一级数据后，可通过配有的4G收发模块将该一级数发送至云服务器10。云服务器10接收该一级数据，并对该一级数据进行分析与保存以获取电动汽车的车辆标识码VIN，然后可根据该车辆标识码VIN从云服务器10的数据库中查找与该车辆标识码VIN对应的电动汽车的历史数据、预设算法等，并跟该历史数据和/或预设算法对该一级数据进行二级分析，以生成二级数据，最后云服务器10通过4G网络将该二级数据 反馈至充电桩30。充电桩30在接收到该二级数据后，通过充电CAN网络反馈至BMS20。BMS20接收充电桩30反馈的二级数据，并根据该二级数据对BMS20中预存的参考曲线进行更新，以作为电池预测管理的参考曲线。
如图4所示，充电桩30还可用于在判断电动汽车处于恒流充电阶段时，通过蓝牙网络与BMS20进行通信以获取一级数据，并将一级数据发送至云服务器10，以及接收云服务器10反馈的二级数据，并通过蓝牙网络反馈至BMS20。生产厂商可分别为上述的BMS20和充电桩30配备蓝牙收发模块，充电桩30在判断电动汽车处于恒流充电阶段时，可通过自身配备的蓝牙收发模块与BMS20配备的蓝牙收发模块，实现BMS20和充电桩30之间的通信以获取上述的一级数据，而后将该一级数据通过自身配有的4G收发模块发送至云服务器10，云服务器10接收该一级数据，并对该一级数据进行分析与保存以获取电动汽车的车辆标识码VIN，然后可根据该车辆标识码VIN从云服务器10的数据库中查找与该车辆标识码VIN对应的电动汽车的历史数据、预设算法等，并跟该历史数据和/或预设算法对该一级数据进行二级分析，以生成二级数据，最后云服务器10通过4G网络将该二级数据反馈至充电桩30。充电桩30在接收到该二级数据后，通过与BMS20建立蓝牙连接反馈至BMS20。BMS20接收充电桩30反馈的二级数据，并根据该二级数据对BMS20中预存的参考曲线进行更新，以作为电池预测管理的参考曲线。
在本公开的其它实施例中，上述电动汽车的数据处理系统可不给BMS20配备无线通信模块(例如，4G收发模块、蓝牙收发模块)，而仅将无线通信模块(例如，4G收发模块)设置在充电桩30之上。由此，数据传输时机仅限于利用充电桩30对电动车辆进行恒流充电阶段，在提高电池包状态参数计算精度的同时，也大大节省了数据运算负荷以及网络传输负荷，并且将无线通信模块配置在充电桩30而不是BMS20，不需要占用整车任何空间，节省了整车重新布局需消耗的开发成本与验证成本。
为了防止充电桩30与云服务器10或BMS20与云服务器10的无线通信出现故障，或者当BMS20监测到电动汽车没有与充电桩30连接时，导致BMS20无法接收到云服务器10反馈的二级数据而无法对BMS20中预存的参考曲线进行更新等问题。根据本公开的一个实施例，如图5所示，上述电动汽车的数据处理系统还可包括车载终端40，用于将一级数据发送至云服务器10，以及接收云服务器10反馈的二级数据，并反馈至BMS。
例如，当充电桩30与云服务器10或BMS20与云服务器10的无线通信出现故障时，可利用车载终端40通过电动汽车动力CAN网络与BMS20进行通信以获取一级数据，并将一级数据发送至云服务器10，以及接收云服务器10反馈的二级数据，并通过电动汽车动力CAN网络反馈至BMS20，以使MS20接收车载终端40反馈的二级数据，并根据该二级数据对BMS20中预存的参考曲线进行更新，以作为电池预测管理的参考曲线。
再例如，在用户利用充电桩30对电动汽车进行充电的过程中，BMS20可实时监测电动汽车与充电桩30连接状态，当BMS20监测到电动汽车与充电桩30断开连接时，可启动车载终端40配置的4G收发模块，通过车载终端40配置的4G收发模块接收云服务器10反馈的二级数据，并将该二级数据通过电动汽车动力CAN网络传送至BMS20。BMS20接收车载终端40反馈的二级数据，并根据该二级数据对BMS20中预存的参考曲线进行更新，以作为电池预测管理的参考曲线。
综上，根据本公开实施例的电动汽车的数据处理系统，通过BMS采集多个单体电池的状态参数，并根据多个单体电池的状态参数生成一级数据，以及将一级数据发送至云服务器，进而通过云服务器根据电动汽车的车辆标识码VIN和一级数据生成二级数据，且通过BMS接收云服务器反馈的二级数据，并根据二级数据对BMS中预存的参考曲线进行更新。由此，可不断对BMS中预存的参考曲线进行更新，通过更新后的参考曲线能够准确预估动力电池的各项状态信息，便于对动力电池进行有效管理，有利于提高动力电池的使用寿命。
图6是根据本公开一个实施例的电动汽车的数据处理方法的流程图。在本公开的实施例中，在电动汽车之上设置有电池管理系统BMS。
如图6所示，本公开实施例的电动汽车的数据处理方法，包括以下步骤：
S1，BMS采集多个单体电池的状态参数，并根据多个单体电池的状态参数生成一级数据，以及将一级数据发送至云服务器。
S2，云服务器获取电动汽车的车辆标识码VIN，并根据VIN和一级数据生成二级数据。
S3，BMS接收云服务器反馈的二级数据，并根据二级数据对BMS中预存的参考曲线进行更新。
根据本公开的一个实施例，上述电动汽车的数据处理方法还包括：充电桩对电动汽车进行充电，且在判断电动汽车处于恒流充电阶段时，通过充电CAN网络或蓝牙网络与BMS进行通信以获取一级数据，并将一级数据发送至云服务器，以及接收云服务器反馈的二级数据，并通过充电CAN网络或蓝牙网络反馈至BMS。
根据本公开的一个实施例，二级数据包括多个单体电池对应的电池参考曲线。
需要说明的是，本公开实施例的电动汽车的数据处理方法的其他具体实施方式可参照上述实施例的电动汽车的数据处理系统的具体实施方式。
综上，根据本公开实施例的电动汽车的数据处理方法，首先BMS采集多个单体电池的状态参数，并根据多个单体电池的状态参数生成一级数据，以及将一级数据发送至云服务器，然后云服务器获取电动汽车的车辆标识码VIN，并根据VIN和一级数据生成二级数据，最后BMS接收云服务器反馈的二级数据，并根据二级数据对BMS中预存的参考曲线 进行更新。由此，可不断对BMS中预存的参考曲线进行更新，通过更新后的参考曲线能够准确预估动力电池的各项状态信息，便于对动力电池进行有效管理，有利于提高动力电池的使用寿命。
图7是根据本公开一个实施例的电动汽车的结构框图。
如图7所示，在电动汽车200之上设置有电池管理系统BMS20，其中，BMS20用于采集多个单体电池的状态参数，并根据多个单体电池的状态参数生成一级数据，以及将一级数据发送至云服务器10，以使云服务器10获取电动汽车200的车辆标识码VIN，并根据VIN和一级数据生成二级数据；接收云服务器10反馈的二级数据，并根据二级数据对BMS中预存的参考曲线进行更新。
根据本公开的一个实施例，参照图2，BMS20包括多个电池采集器BIC21和电池控制单元BCU22。
其中，多个BIC21分别与动力电池中的多个单体电池相对应，用于采集多个单体电池的状态参数。电池控制单元BCU22与多个BIC21相连，并与云服务器10进行通信，BCU22用于根据动力电池的状态参数生成一级数据，并接收云服务器10反馈的二级数据，以及根据二级数据对BMS中预存的参考曲线进行更新。
参照图3，BCU22包括：第一控制器22a和第二控制器22b。
其中，第一控制器22a用于根据动力电池的状态参数进行整车控制。第二控制器22b，用于与云服务器10进行通信，并根据动力电池的状态参数生成一级数据，并接收云服务器10反馈的二级数据，以及根据二级数据对BMS20中预存的参考曲线进行更新。
根据本公开的一个实施例，如图8所示，上述电动汽车还包括车载终端40，用于将一级数据发送至云服务器10，以及接收云服务器10反馈的二级数据，并反馈至BMS20。
根据本公开的一个实施例，二级数据包括多个单体电池对应的电池参考曲线。
需要说明的是，本公开实施例的电动汽车的其他具体实施方式可参照上述实施例的电动汽车的数据处理系统具体实施方式。
综上，根据本公开实施例的电动汽车，通过BMS采集多个单体电池的状态参数，并根据多个单体电池的状态参数生成一级数据，以及将一级数据发送至云服务器，以使云服务器获取电动汽车的车辆标识码VIN，并根据VIN和一级数据生成二级数据，而后接收云服务器反馈的二级数据，并根据二级数据对BMS中预存的参考曲线进行更新。由此，可不断对BMS中预存的参考曲线进行更新，通过更新后的参考曲线能够准确预估动力电池的各项状态信息，便于对动力电池进行有效管理，有利于提高动力电池的使用寿命。
另外，根据本公开实施例的电动汽车的其他构成及其作用对本领域的技术人员而言是已知的，为减少冗余，此处不做赘述。
在本公开的描述中，需要理解的是，术语“中心”、“纵向”、“横向”、“长度”、“宽度”、“厚度”、“上”、“下”、“前”、“后”、“左”、“右”、“竖直”、“水平”、“顶”、“底”、“内”、“外”、“顺时针”、“逆时针”、“轴向”、“径向”、“周向”等指示的方位或位置关系为基于附图所示的方位或位置关系，仅是为了便于描述本公开和简化描述，而不是指示或暗示所指的装置或元件必须具有特定的方位、以特定的方位构造和操作，因此不能理解为对本公开的限制。
此外，术语“第一”、“第二”仅用于描述目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有“第一”、“第二”的特征可以明示或者隐含地包括一个或者更多个该特征。在本公开的描述中，“多个”的含义是两个或两个以上，除非另有明确具体的限定。
在本公开中，除非另有明确的规定和限定，术语“安装”、“相连”、“连接”、“固定”等术语应做广义理解，例如，可以是固定连接，也可以是可拆卸连接，或成一体；可以是机械连接，也可以是电连接；可以是直接相连，也可以通过中间媒介间接相连，可以是两个元件内部的连通或两个元件的相互作用关系。对于本领域的普通技术人员而言，可以根据具体情况理解上述术语在本公开中的具体含义。
在本公开中，除非另有明确的规定和限定，第一特征在第二特征“上”或“下”可以是第一和第二特征直接接触，或第一和第二特征通过中间媒介间接接触。而且，第一特征在第二特征“之上”、“上方”和“上面”可是第一特征在第二特征正上方或斜上方，或仅仅表示第一特征水平高度高于第二特征。第一特征在第二特征“之下”、“下方”和“下面”可以是第一特征在第二特征正下方或斜下方，或仅仅表示第一特征水平高度小于第二特征。
在本说明书的描述中，参考术语“一个实施例”、“一些实施例”、“示例”、“具体示例”、或“一些示例”等的描述意指结合该实施例或示例描述的具体特征、结构、材料或者特点包含于本公开的至少一个实施例或示例中。在本说明书中，对上述术语的示意性表述不必须针对的是相同的实施例或示例。而且，描述的具体特征、结构、材料或者特点可以在任一个或多个实施例或示例中以合适的方式结合。此外，在不相互矛盾的情况下，本领域的技术人员可以将本说明书中描述的不同实施例或示例以及不同实施例或示例的特征进行结合和组合。
尽管上面已经示出和描述了本公开的实施例，可以理解的是，上述实施例是示例性的，不能理解为对本公开的限制，本领域的普通技术人员在本公开的范围内可以对上述实施例进行变化、修改、替换和变型。

Claims (14)

  1. 一种电动汽车的数据处理系统，其特征在于，包括云服务器和设置在所述电动汽车之上的电池管理系统BMS，其中，
    所述BMS，用于采集多个单体电池的状态参数，并根据所述多个单体电池的状态参数生成一级数据，以及将所述一级数据发送至所述云服务器，并且接收所述云服务器反馈的二级数据，并根据所述二级数据对所述BMS中预存的参考曲线进行更新；
    所述云服务器，用于获取所述电动汽车的车辆标识码VIN和所述一级数据，并根据所述VIN和所述一级数据生成所述二级数据。
  2. 如权利要求1所述的电动汽车的数据处理系统，其特征在于，所述BMS包括：
    多个电池采集器BIC，所述多个BIC分别与动力电池中的多个单体电池相对应，用于采集所述多个单体电池的状态参数；
    电池控制单元BCU，所述BCU与所述多个BIC相连，并与所述云服务器进行通信，所述BCU用于根据所述动力电池的状态参数生成所述一级数据，并接收所述云服务器反馈的二级数据，以及根据所述二级数据对所述BMS中预存的参考曲线进行更新。
  3. 如权利要求1或2所述的电动汽车的数据处理系统，其特征在于，所述BCU包括：
    第一控制器，用于根据所述动力电池的状态参数进行整车控制；
    第二控制器，用于与所述云服务器进行通信，并根据所述动力电池的状态参数生成所述一级数据，并接收所述云服务器反馈的二级数据，以及根据所述二级数据对所述BMS中预存的参考曲线进行更新。
  4. 如权利要求1至3中任意一项所述的电动汽车的数据处理系统，其特征在于，还包括：
    充电桩，用于对所述电动汽车进行充电，且在判断所述电动汽车处于恒流充电阶段时，通过充电CAN网络或蓝牙网络与所述BMS进行通信以获取所述一级数据，并将所述一级数据发送至所述云服务器，以及接收所述云服务器反馈的二级数据，并通过所述充电CAN网络或蓝牙网络反馈至所述BMS。
  5. 如权利要求1至4中任意一项所述的电动汽车的数据处理系统，其特征在于，还包括：
    车载终端，用于将所述一级数据发送至所述云服务器，以及接收所述云服务器反馈的二级数据，并反馈至所述BMS。
  6. 如权利要求1至5中任意一项所述的电动汽车的数据处理系统，其特征在于，所述二级数据包括所述多个单体电池对应的电池参考曲线。
  7. 一种电动汽车的数据处理方法，其特征在于，其中，在所述电动汽车之上设置有电池管理系统BMS，所述方法包括以下步骤：
    所述BMS采集多个单体电池的状态参数，并根据所述多个单体电池的状态参数生成一级数据，以及将所述一级数据发送至云服务器；
    所述云服务器获取所述电动汽车的车辆标识码VIN，并根据所述VIN和所述一级数据生成所述二级数据；
    所述BMS接收所述云服务器反馈的二级数据，并根据所述二级数据对所述BMS中预存的参考曲线进行更新。
  8. 如权利要求7所述的电动汽车的数据处理方法，其特征在于，还包括：
    充电桩对所述电动汽车进行充电，且在判断所述电动汽车处于恒流充电阶段时，通过充电CAN网络或蓝牙网络与所述BMS进行通信以获取所述一级数据，并将所述一级数据发送至所述云服务器，以及接收所述云服务器反馈的二级数据，并通过所述充电CAN网络或蓝牙网络反馈至所述BMS。
  9. 如权利要求7或8所述的电动汽车的数据处理方法，其特征在于，所述二级数据包括所述多个单体电池对应的电池参考曲线。
  10. 一种电动汽车，其特征在于，在所述电动汽车之上设置有电池管理系统BMS，其中，所述BMS用于：
    采集多个单体电池的状态参数，并根据所述多个单体电池的状态参数生成一级数据，以及将所述一级数据发送至云服务器，以使所述云服务器获取所述电动汽车的车辆标识码VIN，并根据所述VIN和所述一级数据生成所述二级数据；
    接收所述云服务器反馈的二级数据，并根据所述二级数据对所述BMS中预存的参考曲线进行更新。
  11. 如权利要求10所述的电动汽车，其特征在于，所述BMS包括：
    多个电池采集器BIC，所述多个BIC分别与动力电池中的多个单体电池相对应，用于采集所述多个单体电池的状态参数；
    电池控制单元BCU，所述BCU与所述多个BIC相连，并与所述云服务器进行通信，所述BCU用于根据所述动力电池的状态参数生成所述一级数据，并接收所述云服务器反馈的二级数据，以及根据所述二级数据对所述BMS中预存的参考曲线进行更新。
  12. 如权利要求10或11所述的电动汽车，其特征在于，所述BCU包括：
    第一控制器，用于根据所述动力电池的状态参数进行整车控制；
    第二控制器，用于与所述云服务器进行通信，并根据所述动力电池的状态参数生成所述一级数据，并接收所述云服务器反馈的二级数据，以及根据所述二级数据对所述BMS中 预存的参考曲线进行更新。
  13. 如权利要求10至12中任意一项所述的电动汽车，其特征在于，还包括：
    车载终端，用于将所述一级数据发送至所述云服务器，以及接收所述云服务器反馈的二级数据，并反馈至所述BMS。
  14. 如权利要求10至13中任意一项所述的电动汽车，其特征在于，所述二级数据包括所述多个单体电池对应的电池参考曲线。
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