CN104375090B - Rechargeable lithium battery remaining capacity remote monitoring method - Google Patents

Rechargeable lithium battery remaining capacity remote monitoring method Download PDF

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Publication number
CN104375090B
CN104375090B CN201410648861.0A CN201410648861A CN104375090B CN 104375090 B CN104375090 B CN 104375090B CN 201410648861 A CN201410648861 A CN 201410648861A CN 104375090 B CN104375090 B CN 104375090B
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battery
information
output
monitoring
rbf
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CN104375090A (en
Inventor
郑可
侯兴哲
周孔均
杨芾藜
叶君
刘凯
刘型志
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ELECTRIC POWER RESEARCH INSTITUTE STATE GRID CHONGQING ELECTRIC POWER Co Ltd
Chongqing University
State Grid Corp of China SGCC
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ELECTRIC POWER RESEARCH INSTITUTE STATE GRID CHONGQING ELECTRIC POWER Co Ltd
Chongqing University
State Grid Corp of China SGCC
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Abstract

The invention provides a rechargeable lithium battery remaining capacity remote monitoring device and a monitoring method of the rechargeable lithium battery remaining capacity remote monitoring device. The monitoring method comprises the steps that battery remaining capacity information, battery remaining time information and battery health condition information on various working conditions are provided through a battery monitoring module; battery data collected by a wireless data transmission module composed of a single-chip microcomputer and a wireless transceiver chip are sent to a far-end receiving terminal; the receiving terminal processes signals, displays the battery remaining usage time information, the battery health condition information and other information in a displayer and gives a buzzer alarm when detecting that the remaining capacity is lower than a preset threshold value, so that battery capacity remote monitoring is achieved. The monitoring method is used for battery remaining capacity remote monitoring, the monitoring device is simple in structure, the monitoring method is convenient to operate, and the charge quantity of electricity stored in a storage battery can be accurate to a specific numerical value, so remote online accurate monitoring of the battery capacity is achieved completely.

Description

A kind of charged lithium cells dump energy remote monitoring method
Technical field
The present invention relates to battery status detection field, particularly a kind of remote monitoring device of charged lithium cells dump energy And method.
Background technology
At present, from electric power direct current cabinet power supply to telecommunications and mobile communication equipment back-up source, from electric bicycle to electronic Automobile, from mobile phone to notebook computer, is found everywhere the application of rechargeable battery.The maximum feature of rechargeable battery is exactly can Discharge and recharge, correct discharge and recharge can sufficiently utilize battery, and incorrect discharge and recharge can shorten battery and even damage Bad battery.For timely rational discharge and recharge, as driver it should be understood that the fuel of automobile is indicated, user wants to know about chargeable The state-of-charge SOC (state of charge) of battery, especially in some important occasions, the residue electricity of rechargeable battery Amount instruction has been an especially important index.
But possibly cannot be close to for some particular band rechargeable battery equipment people, or be relatively stranded close to these equipment When difficult, battery dump energy is very difficult in understanding or detect these equipment by using conventional method, such as with energy-saving ring Guarantor's type solar recharging street lamp is fast-developing, and this environmental-friendly street lamp is installed in many places, yet with the unstable of solar energy Property, street lamp top cell dump energy there is also instability problem, therefore occasionally want to that top cell dump energy can be monitored Situation, but because street lamp is higher, traditional wire monitoring battery dump energy method obviously can not meet demand, therefore need to take one Planting long-range monitoring mode could realize the monitoring of now battery dump energy, be electricity with the fast development of wireless communication technology Pond quantity remote monitoring is provided may.
The content of the invention
One object of the present invention is just to provide a kind of charged lithium cells dump energy remote monitoring device, and it will can be supervised The charged lithium cells status information that survey is calculated is sent to distal end by way of radio communication, is easy to real-time monitoring.
The purpose of the invention realizes that it includes battery detection module, the first list by such technical scheme Piece machine, wireless transmission end, wireless receiving end, second singlechip, system supplymentary control alarm module and display;
The data monitoring end of battery detection module is connected with tested charged lithium cells, the data that battery detection module monitors are arrived Sent to wireless receiving end, the data is activation that wireless receiving end will receive to the second monolithic by single-chip microcomputer and wireless transmission end Machine, after second singlechip treatment, sends control information to system supplymentary and controls alarm module, is simultaneously emitted by display information to display Device.
Further, the battery detection module is MAX177050 battery meters.
Further, the wireless transmission end and wireless receiving end are nrf24L01 wireless transceiver chips.
Further, it is buzzer that the system supplymentary controls alarm module.
Another object of the present invention is just to provide a kind of charged lithium cells dump energy remote monitoring method, and it can be The near-end of charged lithium cells is monitored analysis to battery status information, obtains battery remaining power information, remaining battery time Information and battery health information, and sent by way of radio communication to distant place monitoring client.
The purpose of the invention is realized by such technical scheme, concretely comprised the following steps:
1) by battery detection module monitors and the status information of the tested charged lithium cells of record;
2) battery detection module carries out information processing to the charged lithium cells status information for monitoring, obtains remaining battery appearance Amount information, remaining battery temporal information and battery health information;
3) battery remaining power information, remaining battery temporal information and the battery health information obtained after processing pass through First single-chip microcomputer, wireless transmission end, wireless receiving end are sent to second singlechip;
4) second singlechip extracts battery remaining power information, remaining battery temporal information and battery health information, Send to display, while compared with predetermined threshold value, sending control instruction control system auxiliary control alarm module.
Further, step 1) the charged lithium cells status information include the current output voltage information of battery, output Output information about power when being input into information about power and discharging when current information, ambient temperature information, charging.
Further, step 2) described in be to the specific method that charged lithium cells status information carries out information processing:Using On-line prediction is carried out to battery SOC using RBF neural.
Further, use RBF neural battery SOC is carried out the specific method of on-line prediction for:Based on RBF nerve nets Network sets up SOC forecast models, is mainly designed in terms of network level, training level and node level three;Relevant with soc estimations Input variable, including total voltage, total current, minimum monomer voltage, highest monomer voltage, minimum node temperature, highest node In temperature, modules in the magnitude of voltage of each cell and each module the temperature value last moment of each node soc values, voltage In difference and temperature gap, last moment soc value, total voltage total current, minimum monomer voltage, highest monomer voltage, most are chosen High node temperature, minimum node temperature, mean temperature, total voltage variable quantity, SOC variable quantities totally 10 be input variable, with this Moment SOC is output variable, and it is 30 to set node in hidden layer, and the input matrix of its network is
X=(x1,x2,x3,x4,x5,x6,x7,x8,x9,x10)
The output function of RBF neural is:
Wherein, m represents hidden layer neuron nodes, the i.e. number at RBF center;Coefficient represents that hidden layer is arrived The connection weight of output layer, b represents the threshold value of output layer;
Wherein,The RBF of hidden layer is represented, | | x-cj| | represent Euclidean distance, cj(cj∈Rn) represent The center of hidden layer RBF;rj(rj∈ R) represent RBF width;
Output layer matrix is obtained to represent:
Y=HW+e
Wherein, y represents the desired output of output layer, and e represents the error between desired output y and network output f (x), W tables Show the connection weight of hidden layer and output layer, H represents regression matrix.
In RBF network structures, for training sample, generally taking performance indications is
Index E is the function on radial direction base center, width and weights, the training of RBF networks aiming at one group of sample, E is set to tend to minimum;
Output layer is obtained to be output as:
By adopting the above-described technical solution, the present invention has the advantage that:
The present invention is by by battery remaining power information, the remaining battery under the battery detection module various conditions of work of offer Temporal information and battery health information.And the Wireless Data Transmission mould by being made up of single-chip microcomputer and wireless transceiver chip Block by gathered battery data send to distal end receiving terminal, receiving terminal process signal and by remaining battery use time and The information such as battery health are shown in the display, and when finding that dump energy is less than predetermined threshold value, buzzing is alarmed, so that Realize that battery electric quantity remote is monitored.The present invention is remotely monitored for battery dump energy, and monitoring device constitutes simple, monitoring method It is easy to operate, can be as accurate as battery power storage quantity of electric charge concrete numerical value so that monitoring cell electricity quantity thoroughly realizes remote online Accurate monitoring.
Other advantages of the invention, target and feature will be illustrated in the following description to a certain extent, and And to a certain extent, based on being will be apparent to those skilled in the art to investigating hereafter, Huo Zheke To be instructed from the practice of the present invention.Target of the invention and other advantages can be wanted by following specification and right Book is sought to realize and obtain.
Brief description of the drawings
Brief description of the drawings of the invention is as follows.
Fig. 1 is structural representation of the invention;
Fig. 2 is flow chart of the method for the present invention;
Fig. 3 is nRF24L01 chip wiring diagrams.
Specific embodiment
The invention will be further described with reference to the accompanying drawings and examples.
The state-of-charge SOC of battery is used to reflect the residual capacity situation of battery, and this is to compare unification both at home and abroad at present Understanding, its ratio for being numerically defined as being accounted for for the remaining electricity of battery battery total capacity:
Soc=[Qm-Q(In)]/Qm
Q(In=t ∫ Indt)
In formula:Qm is battery maximum discharge capacity, is referred at ambient temperature, battery after fully charged work Untill making until battery discharges completely, its maximum ampere-hour numerical value that can be released, when being expressed as standard discharge current and electric discharge The product asked;Q (In) is the electricity of the battery release of t under standard discharge current I0.
As shown in figure 1, calculating battery SOC data by MAX177050 battery meters in the present invention, complete data and adopt After collection is calculated, institute's gathered data is transmitted away by wireless transport module, be wirelessly transferred is carried out using nrf24l01 chips Wireless data transceiving, nRF24L01 is that the monolithic of the ISM band for being operated in 2.4GHz~2.5GHz produced by NORDIC is wireless Transponder chip.Wireless transceiver includes:Frequency generator, enhanced SchockBurst mode controllers, power amplifier, Crystal oscillator, modulator and demodulator.Its chip wiring diagram is as shown in Figure 3.
In distance terminal equipment, there is wireless receiving terminal to receive transmitted wireless data, processed by second singlechip Analysis, and data display is realized battery dump energy is remotely monitored over the display.When discovery dump energy is touched less than 10% Transmit messages alarm device, realize that buzzing is alarmed.Its flow chart is as shown in Figure 2.
Finally illustrate, the above embodiments are merely illustrative of the technical solutions of the present invention and it is unrestricted, although with reference to compared with Good embodiment has been described in detail to the present invention, it will be understood by those within the art that, can be to skill of the invention Art scheme is modified or equivalent, and without deviating from the objective and scope of the technical program, it all should cover in the present invention Right in the middle of.

Claims (1)

1. a kind of charged lithium cells dump energy remote monitoring method, it is characterised in that comprise the following steps that:
1) by battery detection module monitors and the status information of the tested charged lithium cells of record;
2) battery detection module carries out information processing to the charged lithium cells status information for monitoring, obtains battery remaining power letter Breath, remaining battery temporal information and battery health information;
3) battery remaining power information, remaining battery temporal information and the battery health information obtained after processing pass through first Single-chip microcomputer, wireless transmission end, wireless receiving end are sent to second singlechip;
4) second singlechip extracts battery remaining power information, remaining battery temporal information and battery health information, sends To display, while compared with predetermined threshold value, sending control instruction control system auxiliary control alarm module;
Step 1) the charged lithium cells status information includes current output voltage information, output current information, the ring of battery Output information about power when being input into information about power and discharging when border temperature information, charging;
Step 2) described in be to the specific method that charged lithium cells status information carries out information processing:Using RBF neural On-line prediction is carried out to battery SOC;
Use RBF neural battery SOC is carried out the specific method of on-line prediction for:SOC is set up based on RBF neural pre- Model is surveyed, is mainly designed in terms of network level, training level and node level three;In the input variable relevant with soc estimations, Including total voltage, total current, minimum monomer voltage, highest monomer voltage, minimum node temperature, highest node temperature, each mould The soc values of the temperature value last moment of each node, voltage difference and temperature in the magnitude of voltage of each cell and each module in block In difference, choose last moment soc value, total voltage total current, minimum monomer voltage, highest monomer voltage, highest node temperature, Minimum node temperature, mean temperature, total voltage variable quantity, SOC variable quantities totally 10 be input variable, with moment SOC as defeated Go out variable, it is 30 to set node in hidden layer, and the input matrix of its network is
X=(x1,x2,x3,x4,x5,x6,x7,x8,x9,x10)
The output function of RBF neural is:
Wherein, m represents hidden layer neuron nodes, the i.e. number at RBF center;Coefficient represents hidden layer to output The connection weight of layer, b represents the threshold value of output layer;
Wherein,The RBF of hidden layer is represented, | | x-cj| | represent Euclidean distance, cj(cj∈Rn) represent implicit The center of layer RBF;rj(rj∈ R) represent RBF width;
Output layer matrix is obtained to represent:
Y=HW+e
Wherein, y represents the desired output of output layer, and e represents the error between desired output y and network output f (x), and W represents hidden Connection weight containing layer Yu output layer, H represents regression matrix;
In RBF network structures, for training sample, generally taking performance indications is
Index E is the function on radial direction base center, width and weights, and the training of RBF networks makes E aiming at one group of sample Tend to minimum;
Output layer is obtained to be output as:
CN201410648861.0A 2014-11-12 2014-11-12 Rechargeable lithium battery remaining capacity remote monitoring method Active CN104375090B (en)

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CN105277896B (en) * 2015-10-26 2018-01-26 安徽理工大学 Lithium battery method for predicting residual useful life based on ELM MUKF
CN105652206A (en) * 2015-12-26 2016-06-08 深圳市沃特玛电池有限公司 Battery pack state-of-charge (Soc) evaluation method and battery pack Soc evaluation system
CN105590439A (en) * 2016-01-07 2016-05-18 苏州市职业大学 Wireless management and prediction device for capacity of small-capacity batteries and control method
CN105823989A (en) * 2016-05-04 2016-08-03 安徽工程大学 Improved battery SOC prediction method for RBF neural network
CN106408123A (en) * 2016-09-21 2017-02-15 深圳市沃特玛电池有限公司 Optimal charging current estimation method based on neural network model
CN106530103A (en) * 2016-10-11 2017-03-22 北京农业智能装备技术研究中心 Aviation plant protection operation real-time supervision system
CN106740131B (en) * 2016-12-20 2019-11-29 山东元齐新动力科技有限公司 The monitoring method of electric quantity of batteries of electric vehicle, apparatus and system, monitoring server
CN107825975A (en) * 2017-10-20 2018-03-23 四川省守望信息科技有限责任公司 Electric car charging intelligent management system
CN107845839A (en) * 2017-10-20 2018-03-27 四川省守望信息科技有限责任公司 Electric car automatic charge control method
CN108344951A (en) * 2018-02-26 2018-07-31 广东翔龙航空技术有限公司 A kind of unmanned plane battery capacity on-line monitoring method
CN108490250B (en) * 2018-03-26 2020-05-22 武汉三合鼎盛科技股份有限公司 Intelligent building power monitoring method
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