CN112714156A - Cloud BMS (battery management system) cooperative management method and system and vehicle - Google Patents
Cloud BMS (battery management system) cooperative management method and system and vehicle Download PDFInfo
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- CN112714156A CN112714156A CN202011502473.3A CN202011502473A CN112714156A CN 112714156 A CN112714156 A CN 112714156A CN 202011502473 A CN202011502473 A CN 202011502473A CN 112714156 A CN112714156 A CN 112714156A
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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
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
- B60R16/00—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for
- B60R16/02—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
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- G—PHYSICS
- G08—SIGNALLING
- G08C—TRANSMISSION SYSTEMS FOR MEASURED VALUES, CONTROL OR SIMILAR SIGNALS
- G08C17/00—Arrangements for transmitting signals characterised by the use of a wireless electrical link
- G08C17/02—Arrangements for transmitting signals characterised by the use of a wireless electrical link using a radio link
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M10/00—Secondary cells; Manufacture thereof
- H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
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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
- H04L67/125—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks involving control of end-device applications over a network
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- 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]
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- 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
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/10—Energy storage using batteries
Abstract
The invention relates to the technical field of data processing, in particular to a cloud BMS (battery management system) cooperative management method, a system and a vehicle, wherein battery operation data are uploaded to a cloud in real time, and the cloud matches and downloads corresponding management parameters according to the battery operation data and manages batteries according to the management parameters; according to the method, the real-time running state and data of the battery are uploaded to a big data processing cloud platform, a differentiated management control strategy of the power battery is completed through a big data processing model constructed by machine learning, and is finally downloaded to a BMS main control unit, and the BMS main control unit is used for completing the performance and function differentiation optimization control of the power battery pack; the cloud collaborative management, the full-life-cycle management and the personalized management of the power battery are stronger, so that the power battery is safer and more reliable.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a cloud BMS (battery management system) cooperative management method, a cloud BMS cooperative management system and a vehicle.
Background
The bms (battery Management system), namely the battery Management system, is a key link for connecting the most core component of the electric vehicle, namely, the power battery, with the entire vehicle. Generally, a BMS includes a master control unit and a plurality of slave control units, the slave control units are directly connected to battery cells of a battery pack to collect voltage, current, temperature, etc. of the battery cells, and the master control unit manages the plurality of slave control units through a CAN bus or Daisy Chain communication, etc. Aiming at BMS technology, as one of the most core electric control components of a new energy automobile, the BMS technology is inevitably faced with the following problems. Firstly, compared with a fuel automobile, the fuel automobile has short endurance mileage and long charging time, and is a pain point of the electric automobile; meanwhile, the safety problem of the electric automobile is always the focus of industry attention, and most of the safety problems of the electric automobile are directly or indirectly related to a battery system at present; furthermore, battery life has been an important issue for electric vehicles, and almost all battery manufacturers are developing technologies to prolong battery life. With the gradual improvement of the function management and performance requirements of the power battery, the cross effect of multiple influence factors on the state of the power battery in the whole life cycle is considered, so that all change characteristics of the power battery can be represented once and for all by using a 'perfect' model, and the whole process of battery application cannot be accurately matched due to BMS parameter calibration based on laboratory sample data, and continuous correction must be performed in the process; therefore, algorithms, parameters and strategies which are uniformly set in the traditional BMS when the BMS leaves a factory have more hidden dangers and problems for managing different power batteries with state changes all the time.
The BMS serves as a brain of the battery system, but the conventional BMS manages different power batteries, the states of which change from moment to moment, in batches according to a management algorithm, parameters and policies that are uniformly set at the time of factory shipment. Aiming at the states of different vehicles, the system needs to master in real time and continuously and differentially optimize a BMS control strategy, and meanwhile, problems which possibly occur need to be prevented and preprocessed in time, so that the whole battery pack can be ensured to stably operate under a safe condition. Therefore, a series of performance and safety problems embodied in the power battery and the whole vehicle are faced, and only a single development link of individual products can be considered, and the whole development process needs to be started.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the cloud BMS cooperative management method and system and the vehicle are capable of updating the BMS.
In order to solve the above technical problems, a first technical solution adopted by the present invention is:
a cloud BMS cooperative management method,
and uploading the battery operation data to a cloud end in real time, matching the corresponding management parameters according to the battery operation data by the cloud end, downloading the management parameters and managing the battery according to the management parameters.
In order to solve the above technical problem, the second technical solution adopted by the present invention is:
a cloud BMS cooperative management system comprises
The cloud BMS cooperative management platform is used for matching corresponding management parameters according to the battery operation data;
the BMS main control unit collects battery operation data and controls the battery pack according to the management parameters; and
and the wireless bidirectional data transmission module realizes data interaction between the cloud BMS cooperative management platform and the BMS main control unit.
In order to solve the above technical problems, the third technical solution adopted by the present invention is:
a vehicle comprises the BMS main control unit and a wireless bidirectional data transmission module.
The invention has the beneficial effects that: the method comprises the steps that the real-time running state and data of a battery are uploaded to a big data processing cloud platform, a differentiated management control strategy of the power battery is completed through a big data processing model constructed through machine learning, and finally the strategy is downloaded to a BMS main control unit, and the BMS main control unit is used for completing performance and function differentiation optimization control of a power battery pack; the cloud collaborative management, the full-life-cycle management and the personalized management of the power battery are stronger, so that the power battery is safer and more reliable.
Drawings
Fig. 1 is a schematic flow chart of a cloud BMS cooperative management system according to an embodiment of the present invention.
Detailed Description
In order to explain technical contents, achieved objects, and effects of the present invention in detail, the following description is made with reference to the accompanying drawings in combination with the embodiments.
A cloud BMS cooperative management method,
and uploading the battery operation data to a cloud end in real time, matching the corresponding management parameters according to the battery operation data by the cloud end, downloading the management parameters and managing the battery according to the management parameters.
Preferably, the cloud fits a charging data curve of each battery cell according to the battery operation data, calculates the capacity difference between each battery cell in the battery pack and predicts the equalization time, and the equalization time is packaged in the management parameters.
From the above description, the adjustment and equalization are realized by charging each battery cell, so that the consistency of each battery cell is ensured, and the health state of the battery pack is stable.
Preferably, the battery operation data includes operation information, road condition information and environment information;
and the cloud adjusts a battery charge and discharge power management strategy and a heat management strategy according to the contained running information, road condition information and environment information.
According to the description, the battery charging and discharging power management strategy and the thermal management (heating or refrigerating) strategy are adjusted in real time on the cloud BMS management platform according to the intelligent network information and the big data accumulated in the operation process and according to the multi-source information such as the operation path, the ambient temperature and the real-time road condition, and the safe and reliable operation of the power battery system is ensured.
Preferably, the battery operating data includes battery state of charge/depth of discharge, energy state, power state, state of health, and remaining usable life.
From the above description, it can be seen that the cloud-side continuous estimation of the state of charge/discharge depth, the energy state, the power state, the health state and the remaining available life of the battery has the characteristics of high robustness, high accuracy, fast convergence, high noise immunity and the like, and for different power batteries, the accuracy of each state of the power battery is improved, and the driving range and the service life of the battery are prolonged.
Preferably, the cloud end adopts machine learning to construct an analysis model, and continuously performs iterative optimization on battery operation data of each battery cell of the BMS uploaded in real time so as to match management parameters of the optimal state of the battery.
A cloud BMS cooperative management system comprises
The cloud BMS cooperative management platform is used for matching corresponding management parameters according to the battery operation data;
the BMS main control unit collects battery operation data and controls the battery pack according to the management parameters; and
and the wireless bidirectional data transmission module realizes data interaction between the cloud BMS cooperative management platform and the BMS main control unit.
Preferably, the battery pack comprises a slave control BCU unit and a battery monomer, the slave control BCU unit collects the voltage and the temperature of the battery monomer, the slave control BCU unit is provided with a battery active/passive equalization circuit, and the slave control BCU unit performs equalization control on the battery monomer through the battery active/passive equalization circuit.
Preferably, the cloud end fits a charging data curve of each battery monomer according to the battery operation data, calculates the capacity difference among each battery monomer in the battery pack and predicts the equalization time;
and the slave control BCU unit performs balance control on the single battery through balance time.
Preferably, the BMS master control unit further includes a sensor subunit, and the sensor subunit acquires operation information, road condition information, and environmental information;
and the cloud BMS cooperative management platform adjusts a battery charge and discharge power management strategy and a heat management strategy according to the contained running information, road condition information and environment information.
A vehicle comprises the BMS main control unit and a wireless bidirectional data transmission module.
The invention has the beneficial effects that: the method comprises the steps that the real-time running state and data of a battery are uploaded to a big data processing cloud platform, a differentiated management control strategy of the power battery is completed through a big data processing model constructed through machine learning, and finally the strategy is downloaded to a BMS main control unit, and the BMS main control unit is used for completing performance and function differentiation optimization control of a power battery pack; the cloud collaborative management, the full life cycle management and the personalized management of the power battery are stronger.
Example one
A cloud BMS cooperative management method,
and uploading the battery operation data to a cloud end in real time, matching the corresponding management parameters according to the battery operation data by the cloud end, downloading the management parameters and managing the battery according to the management parameters.
And the cloud end fits a charging data curve of each battery monomer according to the battery operation data, calculates the capacity difference between each battery monomer in the battery pack and predicts the equalization time, and the equalization time is packaged in the management parameters.
The battery operation data comprises operation information, road condition information and environment information;
and the cloud adjusts a battery charge and discharge power management strategy and a heat management strategy according to the contained running information, road condition information and environment information.
The battery operating data includes battery state of charge/depth of discharge, energy state, power state, state of health, and remaining usable life.
The cloud side adopts machine learning to construct an analysis model, and continuous iterative optimization is carried out on battery operation data of each battery cell of the BMS uploaded in real time, so that management parameters of the optimal state of the battery are matched.
Example two
A cloud BMS cooperative management system comprises
The cloud BMS cooperative management platform is used for building a big data analysis model by utilizing huge data storage and high-efficiency data calculation analysis computing capacity of a cloud server for real-time operation data of the battery uploaded to the cloud, continuously performing iterative optimization on nonstationary change and multidimensional huge battery data of each battery monomer of the BMS uploaded in real time so as to match management parameters of the latest state of the battery, downloading the cooperative management data to a BMS main control unit through wireless transmission, and further realizing more powerful cloud cooperative management, full life cycle management and personalized management on the power battery;
the BMS main control unit is used for carrying out battery pack state calculation, charge and discharge control, thermal management control, safety control and the like;
the slave control BCU unit is a slave control unit of the BMS, is used for collecting the voltage and the temperature of a single battery and is provided with a battery active/passive equalization circuit; and
the wireless bidirectional data transmission module is used for receiving the information and data of the related battery of the BMS main control board and uploading the related data to the cloud BMS platform; and receiving the battery pack state and various control instructions processed by the cloud BMS platform, downloading the battery pack state and various control instructions to the BMS main control unit, and performing differentiated battery performance optimization by the BMS main control unit in a coordinated control mode through the BCU.
Wherein
The BMS main control unit is connected with the bidirectional wireless data transmission module and is communicated with the slave control BCU unit in a daisy chain communication mode; the battery operation data collected by the slave BCU unit is uploaded to the cloud end in real time through the wireless transmission module by the BMS main control unit while the slave BCU unit monitors and manages the battery. The cloud BMS cooperative management platform adopts a machine learning method to construct a big data analysis model through huge data storage and data calculation analysis operation, and continuous iteration is carried out on non-steady change and multidimensional huge battery data of each battery monomer of the BMS uploaded in real time so as to match the management parameters of the latest state of the power battery. And finally, downloading the optimized management data to the BMS main control unit through the wireless data transmission module, and the BMS main control unit executes related functions and cooperatively controls the slave control BCU unit to complete the performance optimized management of the power battery.
Cloud BMS manages platform function in coordination including:
the cloud BMS system state is jointly estimated in real time, battery state cloud joint estimation such as battery state of charge (SOC)/depth of discharge (DOD), energy State (SOE), power State (SOP), state of health (SOH), Remaining Usable Life (RUL) can be realized, the characteristics such as high robustness, high accuracy, fast convergence and high noise immunity are realized, aiming at different power batteries, the accuracy of each state of the power battery is improved, and the driving range and the service life of the battery are prolonged.
The battery pack battery monomer full-time equalization of the cloud battery pack, the phenomenon of overall performance reduction and health condition deterioration of the battery pack caused by the inconsistency of large-capacity battery monomers universally existing in the power battery pack can be achieved, a charging data curve of each monomer can be fitted based on massive battery monomer data of the cloud, then the capacity difference between every two monomers in the battery pack is calculated, the equalization time is accurately predicted, a control instruction is issued to a BMS main control unit through a cloud BMS management platform, further, the equalization execution is carried out by a BCU slave control unit, the consistency of each monomer of the battery is guaranteed, and the health state of the battery pack is stable.
The intelligent management system comprises a cloud intelligent active safety management system, a battery charging and discharging power management strategy and a thermal management (heating or refrigerating) strategy are adjusted in real time on a cloud BMS management platform according to intelligent network information and big data accumulated in the operation process and according to multi-source information such as an operation path, ambient temperature, real-time road conditions and the like, so that the safe and reliable operation of a power battery system is ensured; uploading battery input and output characteristics and battery performance data under different working condition environments based on a large number of BMSs, and constructing a full life cycle safety monitoring and fault diagnosis mechanism of the power battery; in addition, the thermal field change analysis of the battery system is carried out through the voltage and the temperature of each battery monomer collected by the BCU slave controller and the change condition of the contact resistance of the high-voltage loop monitored by the BMS master controller, and then the sub-health state of the power battery is timely pre-warned and interfered.
EXAMPLE III
A vehicle comprising the BMS host control unit and the wireless bi-directional data transmission module of embodiment two.
In conclusion, the cloud-based BMS cooperative management strategy based on big data is adopted, the BMS main control unit is connected with the bidirectional wireless data transmission unit, each data of the power battery pack is uploaded to the cloud in real time, a machine learning method is adopted to construct a big data analysis model by utilizing huge data storage and data calculation and analysis operation of a cloud server, and continuous iteration is carried out on non-steady change and multidimensional huge battery data of each battery monomer of the BMS uploaded in real time, so that the management parameters of the latest state of the power battery are matched, and the cloud-based BMS system state of the BMS power battery system is jointly estimated in real time; the battery single bodies of the cloud battery pack are balanced all the time; cloud intelligent active safety management and the like. The hidden danger and the problem that the algorithm, the parameter and the strategy which are uniformly set when the traditional BMS leaves a factory are directed at managing different power batteries with state changing constantly are solved, so that the traditional BMS has stronger cloud collaborative management, full-life-cycle management and personalized management, and the power batteries are safer and more reliable.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all equivalent changes made by using the contents of the present specification and the drawings, or applied directly or indirectly to the related technical fields, are included in the scope of the present invention.
Claims (10)
1. A cloud BMS cooperative management method is characterized in that,
and uploading the battery operation data to a cloud end in real time, matching the corresponding management parameters according to the battery operation data by the cloud end, downloading the management parameters and managing the battery according to the management parameters.
2. The cloud-based BMS cooperative management method of claim 1, wherein the cloud-based BMS cooperative management method comprises the steps of fitting a charging data curve of each battery cell according to battery operation data, calculating a capacity difference between each battery cell in the battery pack and predicting equalization time, and the equalization time is packaged in management parameters.
3. The cloud BMS cooperative management method of claim 1, wherein the battery operation data comprises operation information, traffic information, and environmental information;
and the cloud adjusts a battery charge and discharge power management strategy and a heat management strategy according to the contained running information, road condition information and environment information.
4. The cloud-based BMS collaborative management method according to claim 1, wherein the battery operation data comprises battery state of charge/depth of discharge, energy state, power state, state of health, and remaining available life.
5. The cloud-based BMS cooperative management method according to claim 1, wherein the cloud-based BMS cooperative management method is characterized in that a machine learning construction analysis model is adopted in the cloud-based BMS, and continuous iterative optimization is performed on battery operation data of each battery cell of the BMS uploaded in real time so as to match management parameters of the optimal state of the battery.
6. A cloud BMS cooperative management system is characterized by comprising
The cloud BMS cooperative management platform is used for matching corresponding management parameters according to the battery operation data;
the BMS main control unit collects battery operation data and controls the battery pack according to the management parameters; and
and the wireless bidirectional data transmission module realizes data interaction between the cloud BMS cooperative management platform and the BMS main control unit.
7. The cloud BMS cooperative management system of claim 6, wherein the battery pack comprises a slave BCU unit and a battery cell, the slave BCU unit collects voltage and temperature of the battery cell, the slave BCU unit is provided with a battery active/passive equalization circuit, and the slave BCU unit performs equalization control on the battery cell through the battery active/passive equalization circuit.
8. The cloud-based BMS cooperative management system of claim 7, wherein the cloud-based BMS cooperative management system is configured to fit a charging data curve for each battery cell according to battery operating data, calculate a capacity difference between each battery cell in the battery pack, and predict equalization time;
and the slave control BCU unit performs balance control on the single battery through balance time.
9. The cloud BMS cooperative management system of claim 7, wherein the BMS master control unit further comprises a sensor subunit, the sensor subunit obtaining operation information, road condition information, and environment information;
and the cloud BMS cooperative management platform adjusts a battery charge and discharge power management strategy and a heat management strategy according to the contained running information, road condition information and environment information.
10. A vehicle comprising the BMS master control unit of any one of claims 6 to 9 and a wireless bi-directional data transmission module.
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