CN111639425A - Storage battery starting performance prediction method, storage medium and electronic device - Google Patents
Storage battery starting performance prediction method, storage medium and electronic device Download PDFInfo
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Abstract
The invention provides a storage battery starting performance prediction method, a storage medium and electronic equipment, wherein the method comprises the steps of obtaining the current voltage of a storage battery and the current corresponding to the current voltage, wherein the current voltage is positively correlated with the current; inputting the current voltage and the current into a preset resistance model for calculating the ohmic resistance of the storage battery to obtain the current ohmic resistance; calculating the current lowest terminal voltage of the storage battery according to the current ohmic resistor; and judging the starting performance of the storage battery according to the current lowest end voltage. By implementing the method, the storage battery SOF can be calculated no matter whether the storage battery has large charge and discharge current or small charge and discharge current, the calculation precision of the storage battery SOF is improved, the storage battery SOF can be updated in time, and the judgment reliability is improved.
Description
Technical Field
The invention relates to the technical field of automobiles, in particular to a storage battery starting performance prediction method, a storage medium and electronic equipment.
Background
With the implementation of a double-integral policy in the passenger car market, the requirement for fuel consumption of the whole car is more and more strict, and as a technical scheme for effectively balancing a fuel consumption target and a cost target, the starting and stopping technology of a traditional fuel Vehicle (ICEV) is powered by a lead-acid storage battery, and a traditional starter is started, so that the problems of long starting time, large engine shake, large noise and the like exist. 48 volt light Hybrid (MHEV) owing to adopt 48 volt lithium cell power supplies, Belt formula electricity generation starts the mode that all-in-one (Belt Starter Generator, BSG) started, and the start-up process is compared and is stopped in the ICEV and open and stop, has that the start-up time is short, and the engine shake is little, and the advantage that the noise is little is adopted by more and more host computer factories.
The idle start/stop function analyzes the state of the storage Battery through a Battery Sensor (IBS), and transmits the analysis parameter result to an engine management system to determine whether the engine is started or stopped. The starting performance (SOF) of the battery characterizes the lowest voltage during the next start of the battery, which is used to determine a condition for a start-stop actuation. Currently, the current SOF of storage batteries is calculated and updated by the large charge and discharge current of the storage battery during each start-up process. However, the starting and stopping processes of the MHEV are started by using a 48-volt lithium battery, and the frequency of starting the engine by using the storage battery is greatly reduced, so that the storage battery SOF cannot be calculated by using a small charging and discharging current of the storage battery in each starting process and cannot be updated in time.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a storage battery starting performance prediction method, a storage medium and electronic equipment.
The technical scheme of the invention provides a method for predicting the starting performance of a storage battery, which comprises the following steps:
acquiring the current voltage of a storage battery and the current corresponding to the current voltage, wherein the current voltage is positively correlated with the current;
inputting the current voltage and the current into a preset resistance model for calculating the ohmic resistance of the storage battery to obtain the current ohmic resistance;
calculating the current lowest terminal voltage of the storage battery according to the current ohmic resistor;
and judging the starting performance of the storage battery according to the current lowest end voltage.
Further, the acquiring a current voltage of the storage battery and a current corresponding to the current voltage, where the current voltage is positively correlated with the current, includes:
acquiring the voltage to be measured of the storage battery and the current to be measured corresponding to the voltage to be measured;
when the difference value of the sampling period of the voltage to be detected is two adjacent, the difference value of the voltage to be detected is smaller than a preset period threshold value, the difference value of the voltage to be detected is two adjacent, the difference value of the current to be detected is larger than a preset current threshold value, and when the current sampling number is larger than or equal to the preset sampling number threshold value, the voltage to be detected and the current to be detected are used as the current voltage and the current.
Further, the preset resistance model for calculating the ohmic resistance of the storage battery includes:
acquiring historical voltage of a historical storage battery and historical current corresponding to the historical voltage;
performing curve fitting on the historical voltage and the historical current to obtain a historical storage battery fitting function curve;
and calculating the minimum sum of squared differences of the historical voltage, the historical current and the historical storage battery fitting function curve by using a least square method to obtain the resistance model.
Further, the performing curve fitting on the historical voltage and the historical current to obtain a historical battery fitting function curve includes:
selecting a linear function as a function model to be selected according to the historical voltage and the historical current;
and respectively fitting the historical voltage, the historical current and the linear function to obtain a fitting function curve of the historical storage battery.
Further, the inputting the current voltage and the current into a preset resistance model for calculating ohmic resistance of the storage battery to obtain the current ohmic resistance includes:
the present ohmic resistance is calculated using the following equation:
wherein:
in the formula, R0Is the present ohmic resistance; n is the number of samples; i isiThe current of the ith sampling point is the current of the ith sampling point;
is the sum of the collected current; u shapeiThe current voltage of the ith sampling point;
is the sum of the collected current voltages.
Further, the calculating the current lowest terminal voltage of the storage battery according to the current ohmic resistance specifically includes:
calculating the current lowest end voltage by using the following formula:
Usof＝E-Imax*R0
wherein, UsofIs the current lowest terminal voltage; e is the current electromotive force of the storage battery; i ismaxThe maximum starting current of the starter.
Further, the determining the starting performance of the storage battery according to the current lowest-end voltage includes:
acquiring the lowest starting voltage of a starter;
when the current lowest end voltage is greater than or equal to the lowest starting voltage, the storage battery meets the next starting capability;
and when the lowest terminal voltage is less than the lowest starting voltage, the storage battery does not meet the next starting capability.
The technical solution of the present invention further provides a storage medium, where the storage medium stores computer instructions, and when a computer executes the computer instructions, the storage medium is used to execute all the steps of the storage battery starting performance prediction method.
The technical solution of the present invention also provides an electronic device, including:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the one processor to cause the at least one processor to perform:
acquiring the current voltage of a storage battery and the current corresponding to the current voltage, wherein the current voltage is positively correlated with the current;
inputting the current voltage and the current into a preset resistance model for calculating the ohmic resistance of the storage battery to obtain the current ohmic resistance;
calculating the current lowest terminal voltage of the storage battery according to the current ohmic resistor;
and judging the starting performance of the storage battery according to the current lowest end voltage.
After adopting above-mentioned technical scheme, have following beneficial effect: the current voltage and the current are input into a preset resistance model to obtain the current ohmic resistance, the current lowest end voltage of the storage battery is calculated according to the current ohmic resistance, whether the SOF of the storage battery meets the capability of starting a starter at the next time is judged according to the lowest end voltage, therefore, the SOF of the storage battery can be calculated no matter whether the storage battery has large charge and discharge current or has small charge and discharge current, the calculation precision of the SOF of the storage battery is improved, the SOF of the storage battery is updated in time, and the judgment reliability is improved.
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The disclosure of the present invention will become more readily understood by reference to the drawings. It should be understood that: these drawings are for illustrative purposes only and are not intended to limit the scope of the present disclosure. In the figure:
fig. 1 is a flowchart illustrating a method for predicting the starting performance of a battery according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a method for predicting the starting performance of a battery according to the preferred embodiment of the present invention;
fig. 3 is a schematic diagram of a hardware structure of an electronic device for battery start performance prediction according to the present invention.
Detailed Description
The following further describes embodiments of the present invention with reference to the accompanying drawings.
It is easily understood that according to the technical solution of the present invention, those skilled in the art can substitute various structures and implementation manners without changing the spirit of the present invention. Therefore, the following detailed description and the accompanying drawings are merely illustrative of the technical aspects of the present invention, and should not be construed as limiting or restricting the technical aspects of the present invention.
The terms of orientation of up, down, left, right, front, back, top, bottom, and the like referred to or may be referred to in this specification are defined relative to the configuration shown in the drawings, and are relative terms, and thus may be changed correspondingly according to the position and the use state of the device. Therefore, these and other directional terms should not be construed as limiting terms.
Fig. 1 is a flowchart illustrating a method for predicting the starting performance of a storage battery according to an embodiment of the present invention, which includes:
step S101: acquiring the current voltage of the storage battery and the current corresponding to the current voltage;
step S102: inputting the current voltage and current into a preset resistance model for calculating the ohmic resistance of the storage battery to obtain the current ohmic resistance;
step S104: calculating the current lowest terminal voltage of the storage battery according to the current ohmic resistance;
step S105: and judging the starting performance of the storage battery according to the current lowest end voltage.
Specifically, the method comprises the following steps: the current voltage and current of the storage Battery can be collected by a Battery Sensor (IBS) arranged on the storage Battery, the current voltage and current of the storage Battery at the same moment are collected by the IBS to form a current voltage set and sent to a controller, the controller executes the step S101 to obtain the current voltage and current of the storage Battery, the current voltage and current are positively correlated, namely the current voltage and current have the same changing direction, so that the current voltage and current are intensively distributed on two sides of a linear function relationship, then the step S102 is executed to input a preset resistance model to obtain the current ohmic resistance, and the step S103 is executed to calculate the current lowest end voltage of the storage Battery, thereby realizing that the storage Battery SOF can be calculated no matter whether the storage Battery has large charge and discharge current or has small charge and discharge current, improving the calculation precision of the storage Battery SOF, and realizing timely updating of the storage Battery SOF, and finally, step S104 is executed to judge whether the SOF of the storage battery meets the capability of starting the starter at the next time according to the current lowest end voltage, so that the judgment reliability is improved.
In this embodiment, the controller may be an Electronic Control Unit (ECU), a Body Controller (BCM), or another independent Control chip with Control capability, and in this embodiment, the controller is preferably an ECU.
The method for predicting the starting performance of the storage battery comprises the steps of obtaining the current voltage of the storage battery and the current corresponding to the current voltage, wherein the current voltage is in positive correlation with the current, inputting the current voltage and the current into a preset resistance model to obtain the current ohmic resistance, calculating the current lowest end voltage of the storage battery according to the current ohmic resistance, and judging whether the SOF of the storage battery meets the capability of starting a starter at the next time according to the lowest end voltage, so that the SOF of the storage battery can be calculated no matter the storage battery has large charging and discharging current or has small charging and discharging current, the calculation precision of the SOF of the storage battery is improved, the SOF of the storage battery can be updated in time, and the judgment reliability is improved.
In one embodiment, the preset resistance model for calculating the ohmic resistance of the storage battery may be an existing storage battery equivalent circuit model, and in order to further improve the calculation accuracy of the storage battery SOF, the resistance model in this embodiment is preferably obtained by the following steps:
acquiring historical voltage of a historical storage battery and historical current corresponding to the historical voltage;
performing curve fitting on the historical voltage and the historical current to obtain a historical storage battery fitting function curve;
and calculating the minimum sum of squared differences of the historical voltage, the historical current and a historical storage battery fitting function curve by using a least square method to obtain a resistance model.
Specifically, historical voltage of a historical storage battery and historical current corresponding to the historical voltage are collected through IBS, in order to improve accuracy, historical voltage and historical current can be collected 2000, a historical current and voltage set is formed and sent to a controller, curve fitting is conducted on the historical voltage and the historical current after the controller obtains the historical current and voltage set, a historical storage battery fitting function curve is obtained, a least square method is used for calculating the minimum sum of the historical voltage, the historical current and the square difference of the historical storage battery fitting function curve, a resistance model is obtained, when storage battery SOF judgment is conducted, the resistance model is preset in the controller, storage battery SOF can be updated timely, and judgment reliability is improved.
In one embodiment, the curve fitting the historical voltage and the historical current to obtain a historical battery fitting function curve includes:
selecting a linear function as a function model to be selected according to the historical voltage and the historical current;
and respectively fitting the historical voltage, the historical current and the linear function to obtain a historical storage battery fitting function curve.
Specifically, the controller selects a linear function as a fitting objective function according to a Resistor-capacitor circuit (RC circuit) principle, and performs curve fitting on the historical voltage and the historical current, so that the historical current and voltage set is in a linear function relationship, and a historical storage battery fitting function curve is obtained, and therefore the storage battery SOF can be calculated no matter whether the storage battery is large in charging and discharging current or small in charging and discharging current, calculation accuracy of the storage battery SOF is improved, timely updating of the storage battery SOF is achieved, and judgment reliability is improved.
In one embodiment, in order to further improve the calculation accuracy of the SOF of the storage battery, update the SOF of the storage battery in time, and improve the determination reliability, the inputting the current voltage and the current into a preset resistance model for calculating the ohmic resistance of the storage battery to obtain the current ohmic resistance includes:
the current ohmic resistance is calculated using the following equation:
wherein:
in the formula, R0Is the present ohmic resistance; n is the number of samples; i isiThe current of the ith sampling point is the current of the ith sampling point;
is the sum of the collected current; u shapeiThe current voltage of the ith sampling point;
is the sum of the collected current voltages.
In one embodiment, the calculating the current lowest terminal voltage of the storage battery according to the current ohmic resistance specifically includes:
the current lowest voltage is calculated using the following equation:
Usof＝E-Imax*R0(2) formula (II)
Wherein, UsofIs the current lowest terminal voltage; e is the current electromotive force of the storage battery; i ismaxThe maximum starting current of the starter.
Specifically, the controller obtains a starting torque parameter T of the enginemaxThereby obtaining the maximum starting current I of the startermaxObtaining E according to the relation of the State of Charge (SOC) curve and the Open Circuit Voltage (OCV) curve of the current storage battery, and then calculating the current lowest end voltage U of the starter according to the formula (2)sofTherefore, whether the SOF of the storage battery meets the capability of starting the starter next time is judged, and the judgment reliability is improved.
Fig. 2 is a flowchart illustrating a method for predicting the starting performance of a storage battery according to the preferred embodiment of the present invention:
step S201: acquiring a voltage to be measured of the storage battery and a current to be measured corresponding to the voltage to be measured;
step S202: whether the difference value of the sampling periods of two adjacent voltages to be detected is smaller than a preset period threshold value or not;
step S203: whether the difference value of two adjacent voltages to be measured is greater than a preset voltage threshold value or not and whether the difference value of two adjacent currents to be measured is greater than a preset current threshold value or not;
step S204: whether the current sampling number is greater than or equal to a preset sampling number or not;
step S205: taking the voltage to be measured and the current to be measured as the current voltage and the current;
step S206: calculating the current ohmic resistance of the storage battery;
step S207: calculating the current lowest terminal voltage of the storage battery;
step S208: acquiring the lowest starting voltage of a starter;
step S209: whether the current lowest terminal voltage is greater than or equal to the lowest starting voltage or not;
step S210: the storage battery meets the next starting capability;
step S211: the battery does not satisfy the next starting capability.
Specifically, the method comprises the following steps: the controller executes step S201 to obtain the voltage U to be measured of the storage battery at the same moment through IBSiAnd the current I to be measurediAnd step S202 is executed to judge two adjacent voltages U to be measuredi、UjIs sampled over a period of time (i.e., T (U))i)-T(Uj) Whether or not less than a preset period threshold value T0If yes, executing step S203, otherwise executing step S201; the controller executes step S203 to determine two adjacent voltages U to be measuredi、UjDifference (i.e. U)i-Uj) Whether or not it is greater than a preset voltage threshold value U0And two adjacent currents I to be measuredi、IjDifference (i.e. I)i-Ij) Whether or not it is greater than a preset current threshold I0If the voltage to be detected and the current to be detected which are acquired by the IBS are positively correlated and meet the requirements, executing the step S204, otherwise executing the step S201; the controller executes step S204 to judge whether the current sampling number j is greater than or equal to the preset sampling number N, if so, the controller executes steps S205-S208, otherwise, the controller executes step S201; due to the lowest starting voltage U of the starterstarter_minClosely related to the SOC of the battery, when the SOC of the battery is high, U of the starterstarter_minIs relatively high, so that the controller can calibrate the lowest starting voltage U of the starter according to the actual test of the vehicle-mounted storage battery when executing the step S208starter_minAnd executing step S209 to judge the current lowest terminal voltage UsofWhether or not it is greater than the minimum starting voltageUstarter_minIf the output storage battery meets the next starting capability in the step S210, otherwise, the output storage battery does not meet the next starting capability in the step S211.
The method for predicting the starting performance of the storage battery obtains the voltage to be measured of the storage battery and the current to be measured corresponding to the voltage to be measured, judges the voltage to be measured and the current to be measured to enable the voltage to be measured to be in positive correlation with the current to be measured, obtains the current voltage and the current, inputs the current voltage and the current into a preset resistance model to obtain the current ohmic resistance, calculates the current lowest end voltage of the storage battery according to the current ohmic resistance, judges whether the SOF of the storage battery meets the capability of starting a starter at the next time according to the lowest end voltage, and accordingly calculates the SOF of the storage battery no matter the SOF of the storage battery is large in charging and discharging current or small in charging and discharging current, improves the calculation precision of the SOF of the storage battery, realizes timely updating of the SOF of.
Fig. 3 is a schematic diagram of a hardware structure of an electronic device for predicting battery start performance according to the present invention, which includes:
at least one processor 301; and the number of the first and second groups,
a memory 302 communicatively coupled to the at least one processor 301; wherein,
the memory 302 stores instructions executable by the one processor 301 to cause the at least one processor 301 to:
acquiring the current voltage of the storage battery and the current corresponding to the current voltage, wherein the current voltage is positively correlated with the current;
inputting the current voltage and current into a preset resistance model for calculating the ohmic resistance of the storage battery to obtain the current ohmic resistance;
calculating the current lowest terminal voltage of the storage battery according to the current ohmic resistance;
and judging the starting performance of the storage battery according to the current lowest end voltage.
In fig. 3, one processor 301 is taken as an example.
The Electronic device is preferably an Electronic Control Unit (ECU).
The electronic device may further include: an input device 303 and an output device 304.
The processor 301, the memory 302, the input device 303 and the display device 304 may be connected by a bus or other means, and are illustrated as being connected by a bus.
The memory 302, which is a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as program instructions/modules corresponding to the battery start-up performance prediction method in the embodiment of the present application, for example, the method flows shown in fig. 1 and fig. 2. The processor 301 executes various functional applications and data processing by running the nonvolatile software programs, instructions, and modules stored in the memory 302, that is, implements the battery start-up performance prediction method in the above-described embodiment.
The memory 302 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the battery start-up performance prediction method, and the like. Further, the memory 302 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, memory 302 optionally includes memory located remotely from processor 301, and these remote memories may be connected over a network to a device that performs the battery start-up performance prediction method. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 303 may receive an input of a user click and generate signal inputs related to user settings and function control of the battery start-up performance prediction method. The display device 304 may include a display screen or the like.
When the one or more modules are stored in the memory 302, the battery start-up performance prediction method in any of the above-described method embodiments is performed when executed by the one or more processors 301.
The product can execute the method provided by the embodiment of the application, and has the corresponding functional modules and beneficial effects of the execution method. For technical details that are not described in detail in this embodiment, reference may be made to the methods provided in the embodiments of the present application.
The electronic device of embodiments of the present invention exists in a variety of forms, including but not limited to:
(1) an Electronic Control Unit (ECU) is also called a "traveling computer" or a "vehicle-mounted computer". The digital signal processor mainly comprises a microprocessor (CPU), a memory (ROM and RAM), an input/output interface (I/O), an analog-to-digital converter (A/D), a shaping circuit, a driving circuit and other large-scale integrated circuits.
(2) Mobile communication devices, which are characterized by mobile communication capabilities and are primarily targeted at providing voice and data communications. Such terminals include smart phones (e.g., iphones), multimedia phones, functional phones, and low-end phones, among others.
(3) The ultra-mobile personal computer equipment belongs to the category of personal computers, has calculation and processing functions and generally has the characteristic of mobile internet access. Such terminals include PDA, MID, and UMPC devices, among others.
(4) Portable entertainment devices such devices may display and play multimedia content. Such devices include audio and video players (e.g., ipods), handheld game consoles, electronic books, as well as smart toys and portable car navigation devices.
(5) The server is similar to a general computer architecture, but has higher requirements on processing capability, stability, reliability, safety, expandability, manageability and the like because of the need of providing highly reliable services.
(6) And other electronic devices with data interaction functions.
Furthermore, the logic instructions in the memory 302 may be implemented in software functional units and stored in a computer readable storage medium when sold or used as a stand-alone product. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a mobile terminal (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the embodiment of the present invention. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the embodiments of the present invention, and not to limit the same; although embodiments of the present invention have been described in detail with reference to the foregoing embodiments, those skilled in the art will understand that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (9)
1. A method for predicting the starting performance of a storage battery is characterized by comprising the following steps:
acquiring the current voltage of a storage battery and the current corresponding to the current voltage, wherein the current voltage is positively correlated with the current;
inputting the current voltage and the current into a preset resistance model for calculating the ohmic resistance of the storage battery to obtain the current ohmic resistance;
calculating the current lowest terminal voltage of the storage battery according to the current ohmic resistor;
and judging the starting performance of the storage battery according to the current lowest end voltage.
2. The method for predicting the starting performance of the storage battery according to claim 1, wherein the obtaining a present voltage of the storage battery and a present current corresponding to the present voltage, the present voltage being positively correlated with the present current, comprises:
acquiring the voltage to be measured of the storage battery and the current to be measured corresponding to the voltage to be measured;
when the difference value of the sampling period of the voltage to be detected is two adjacent, the difference value of the voltage to be detected is smaller than a preset period threshold value, the difference value of the voltage to be detected is two adjacent, the difference value of the current to be detected is larger than a preset current threshold value, and when the current sampling number is larger than or equal to the preset sampling number threshold value, the voltage to be detected and the current to be detected are used as the current voltage and the current.
3. The battery start-up performance prediction method of claim 1, wherein the predetermined resistance model for calculating the ohmic resistance of the battery comprises:
acquiring historical voltage of a historical storage battery and historical current corresponding to the historical voltage;
performing curve fitting on the historical voltage and the historical current to obtain a historical storage battery fitting function curve;
and calculating the minimum sum of squared differences of the historical voltage, the historical current and the historical storage battery fitting function curve by using a least square method to obtain the resistance model.
4. The battery starting performance prediction method of claim 3, wherein said curve fitting said historical voltage and said historical current to obtain a historical battery fit function curve comprises:
selecting a linear function as a function model to be selected according to the historical voltage and the historical current;
and respectively fitting the historical voltage, the historical current and the linear function to obtain a fitting function curve of the historical storage battery.
5. The battery start-up performance prediction method of claim 4, wherein inputting the present voltage and the present current into a preset resistance model for calculating an ohmic resistance of the battery to derive a present ohmic resistance comprises:
the present ohmic resistance is calculated using the following equation:
wherein:
in the formula, R0Is the present ohmic resistance; n is the number of samples; i isiThe current of the ith sampling point is the current of the ith sampling point;
is the sum of the collected current; u shapeiThe current voltage of the ith sampling point;
is the sum of the collected current voltages.
6. The battery start-up performance prediction method of claim 1, wherein said calculating a present lowest end voltage of said battery based on said present ohmic resistance comprises:
calculating the current lowest end voltage by using the following formula:
Usof＝E-Imax*R0
wherein, UsofIs the current lowest terminal voltage; e is the current electromotive force of the storage battery; i ismaxThe maximum starting current of the starter.
7. The battery starting performance prediction method according to any one of claims 1 to 6, wherein the determining the starting performance of the battery based on the current lowest-end voltage includes:
acquiring the lowest starting voltage of a starter;
when the current lowest end voltage is greater than or equal to the lowest starting voltage, the storage battery meets the next starting capability;
and when the lowest terminal voltage is less than the lowest starting voltage, the storage battery does not meet the next starting capability.
8. A storage medium storing computer instructions for performing all the steps of the battery start-up performance prediction method according to any one of claims 1 to 7 when the computer instructions are executed by a computer.
9. An electronic device, comprising:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the one processor to cause the at least one processor to perform:
acquiring the current voltage of a storage battery and the current corresponding to the current voltage, wherein the current voltage is positively correlated with the current;
inputting the current voltage and the current into a preset resistance model for calculating the ohmic resistance of the storage battery to obtain the current ohmic resistance;
calculating the current lowest terminal voltage of the storage battery according to the current ohmic resistor;
and judging the starting performance of the storage battery according to the current lowest end voltage.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112172601A (en) * | 2020-10-06 | 2021-01-05 | 青岛灵珑智能装备科技有限责任公司 | Safety early warning method for battery of electric vehicle |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108808778A (en) * | 2018-06-20 | 2018-11-13 | 国网江苏省电力有限公司泰州供电分公司 | A kind of intelligent battery charging-discharging structure |
| CN109782178A (en) * | 2019-01-29 | 2019-05-21 | 中国铁塔股份有限公司 | A kind of battery core Rong Fangfa and core capacitance device |
| US20190178950A1 (en) * | 2017-12-13 | 2019-06-13 | Ningde Amperex Technology Limited | Battery state monitoring method and apparatus |
| CN109917298A (en) * | 2017-12-13 | 2019-06-21 | 北京创昱科技有限公司 | A kind of cell charge state prediction method and system |
| CN110931902A (en) * | 2020-02-19 | 2020-03-27 | 深圳奥特迅电力设备股份有限公司 | Storage battery pack online maintenance method and system |
-
2020
- 2020-05-26 CN CN202010457236.3A patent/CN111639425B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20190178950A1 (en) * | 2017-12-13 | 2019-06-13 | Ningde Amperex Technology Limited | Battery state monitoring method and apparatus |
| CN109917298A (en) * | 2017-12-13 | 2019-06-21 | 北京创昱科技有限公司 | A kind of cell charge state prediction method and system |
| CN108808778A (en) * | 2018-06-20 | 2018-11-13 | 国网江苏省电力有限公司泰州供电分公司 | A kind of intelligent battery charging-discharging structure |
| CN109782178A (en) * | 2019-01-29 | 2019-05-21 | 中国铁塔股份有限公司 | A kind of battery core Rong Fangfa and core capacitance device |
| CN110931902A (en) * | 2020-02-19 | 2020-03-27 | 深圳奥特迅电力设备股份有限公司 | Storage battery pack online maintenance method and system |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112172601A (en) * | 2020-10-06 | 2021-01-05 | 青岛灵珑智能装备科技有限责任公司 | Safety early warning method for battery of electric vehicle |
| CN112172601B (en) * | 2020-10-06 | 2021-06-22 | 千黎（苏州）电源科技有限公司 | Safety early warning method for battery of electric vehicle |
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