CN111301219A - Electric vehicle battery control method, system, device and readable storage medium - Google Patents

Electric vehicle battery control method, system, device and readable storage medium Download PDF

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CN111301219A
CN111301219A CN202010128337.6A CN202010128337A CN111301219A CN 111301219 A CN111301219 A CN 111301219A CN 202010128337 A CN202010128337 A CN 202010128337A CN 111301219 A CN111301219 A CN 111301219A
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battery
current
calculating
power
residual
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CN111301219B (en
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刘学鹏
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Foshan Polytechnic
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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
    • 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
    • B60L58/12—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries responding to state of charge [SoC]
    • 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
    • B60L58/12—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries responding to state of charge [SoC]
    • B60L58/14—Preventing excessive discharging
    • 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
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/70—Energy storage systems for electromobility, e.g. batteries

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  • Life Sciences & Earth Sciences (AREA)
  • Sustainable Development (AREA)
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  • Power Engineering (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Secondary Cells (AREA)
  • Electric Propulsion And Braking For Vehicles (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)

Abstract

The invention discloses a method for controlling a battery of an electric vehicle, which comprises the following steps: acquiring output voltage and output current of a battery; calculating the current residual electric quantity; judging whether the current residual electric quantity is larger than a preset low-voltage threshold value or not, setting the discharge cutoff residual electric quantity as a preset low-electric-quantity threshold value when the current residual electric quantity is judged to be not larger than the preset low-voltage threshold value, calculating output power when the current residual electric quantity is judged to be not larger than the preset low-voltage threshold value, obtaining load power, judging whether the output power is smaller than the load power or not, setting the discharge cutoff residual electric quantity as the current residual electric quantity when the output power is judged to be not larger than the load power, controlling the battery; and judging whether the current residual capacity of the battery is smaller than the discharge ending residual capacity, controlling the battery to stop discharging when the judgment is yes, and controlling the battery to continue discharging when the judgment is no. Correspondingly, the invention also discloses a battery control system, equipment and a readable storage medium for the electric vehicle. The invention can avoid deep discharge of the battery and prolong the service life of the battery.

Description

Electric vehicle battery control method, system, device and readable storage medium
Technical Field
The present invention relates to a control technology, and more particularly, to a method, a system, a device and a readable storage medium for controlling a battery of an electric vehicle.
Background
In recent years, the demand for lithium iron phosphate batteries has increased greatly for many electric products, such as electric vehicles. The lithium battery can meet the energy requirement of the electric automobile, and the battery plays a great role in the field of future power energy. The lithium battery has different degrees of over-discharge phenomenon in the use process. Overdischarge of a lithium battery means that the discharge capacity of the lithium battery is greater than the rated capacity of the battery. If the battery is placed below a certain voltage, although the safety circuit inside the battery is activated, the life of the battery is damaged at this time, and even the battery end of life is advanced.
However, the prior art focuses on estimation of SOC and battery management systems, and does not perform battery control in terms of discharge cutoff threshold.
Disclosure of Invention
The technical problem to be solved by the present invention is to provide a method, a system, a device and a readable storage medium for controlling a battery of an electric vehicle, which can perform control according to a discharge cut-off threshold value to prevent deep discharge of the battery, thereby prolonging the service life of the battery.
In order to solve the technical problem, the invention provides a method for controlling a battery of an electric vehicle, which comprises the following steps: acquiring output voltage and output current of a battery; calculating the current residual capacity according to the output voltage; judging whether the current residual electric quantity is larger than a preset low-voltage threshold value or not, setting the discharging cut-off residual electric quantity as a preset low-electric-quantity threshold value if the current residual electric quantity is not larger than the preset low-voltage threshold value, calculating output power according to the output voltage and the output current if the current residual electric quantity is judged to be larger than the preset low-voltage threshold value, obtaining load power, judging whether the output power is smaller than the load power or not, setting the discharging cut-off residual electric quantity as the current residual electric quantity if the output power is judged to be smaller than the load power, controlling; and judging whether the current residual capacity of the battery is smaller than the discharge ending residual capacity, controlling the battery to stop discharging when the judgment is yes, and controlling the battery to continue discharging when the judgment is no.
As an improvement of the above scheme, the step of calculating the current remaining capacity according to the output voltage includes: calculating a residual electric quantity estimated value; calculating an adjustable weight vector; calculating the current remaining capacity:
SOCj＝Y(SOC,wi,OCVj)+εj(1)
Figure BDA0002395099160000021
Figure BDA0002395099160000022
therein, SOCjFor the current remaining capacity, SOC is the estimated value of remaining capacity, OCVjTo output a voltage, wiFor adjustable weight vector value, BW is kernel parameter, N is iteration number, epsilonjIs a noise value, w0Is a preset initial vector value.
As an improvement of the above solution, the step of calculating the estimated remaining power amount includes: calculating a remaining power estimate according to the following formula:
Figure BDA0002395099160000023
wherein S is0To estimate the amount of charge at the beginning of the period, Q is the total charge of the battery, i is the output current, and t is the estimation period.
As an improvement of the above scheme, the step of calculating the adjustable weight vector includes: s1, generating an adjustable weight vector according to the initial value of the set adjustable weight vector; s2, acquiring a data sample of the output voltage, and generating a voltage sample; s3, calculating a current residual electric quantity set according to the formula (1), the formula (2) and the formula (3) according to the voltage sample and the adjustable weight vector; s4, respectively calculating a function sample set according to the residual power estimated value and the adjustable weight vector and a formula (2); s5, calculating the variance between the data sample and the function sample set to generate a variance set, and sequencing all variance values in the variance set to generate a variance sequencing set; s6, adjusting the sequence of the current residual electric quantity set according to the sequence in the variance sequencing set to generate a residual electric quantity sequencing set, and taking the first half part of the residual electric quantity sequencing set as an updating set; s7, judging whether the maximum variance value in the variance sorting set is smaller than a preset threshold value, if so, taking the corresponding weight in the updating set as a new adjustable weight vector; s8, judging whether the adjustable weight vector accords with normal distribution with the mean value of zero, if not, returning to the step S3.
As an improvement of the above scheme, the step of calculating the output power according to the output voltage and the output current comprises: the output power is calculated according to the following formula:
Po＝OCVj·i
wherein, PoFor output power, OCVjI is the output voltage and i is the output current.
The invention also discloses a battery control system of the electric vehicle, which comprises: the acquisition module is used for acquiring the output voltage and the output current of the battery; the current residual power calculation module is used for calculating the current residual power according to the output voltage; the device comprises a residual electric quantity judging module, a discharging cut-to-low electricity setting module, a load power obtaining module, a discharging cut-to-residual electricity judging module and a battery control module, wherein the residual electric quantity judging module is used for judging whether the current residual electric quantity is larger than a preset low voltage threshold value or not, setting the discharging cut-to-low electricity setting module, when the discharging cut-to-residual electricity is judged to be not larger than the preset low electricity threshold value, calculating output power according to output voltage and output current, obtaining the load power, judging whether the output power is smaller than the load power or not, when the discharging cut-off residual electricity is judged to be larger than the current residual electric quantity, and when the discharging; and the discharging ending judgment control module is used for judging whether the current residual capacity of the battery is smaller than the discharging ending residual capacity, controlling the battery to stop discharging when the current residual capacity of the battery is judged to be smaller than the discharging ending residual capacity of the battery, and controlling the battery to continue discharging when the current residual capacity of the battery is judged to be smaller than the discharging ending residual capacity of the battery.
As an improvement of the above scheme, the current remaining power calculating module includes: the estimated value calculating unit is used for calculating the estimated value of the residual electric quantity; the weight calculation unit is used for calculating an adjustable weight vector; the residual power calculating unit is used for calculating the current residual power:
SOCj＝Y(SOC,wi,OCVj)+εj(1)
Figure BDA0002395099160000031
Figure BDA0002395099160000032
therein, SOCjFor the current remaining capacity, SOC is the estimated value of remaining capacity, OCVjTo output a voltage, wiFor adjustable weight vector value, BW is kernel parameter, N is iteration number, epsilonjIs a noise value, w0Is a preset initial vector value.
As an improvement of the above scheme, the weight calculation unit includes: the initial weight setting subunit is used for generating an adjustable weight vector according to the initial value of the set adjustable weight vector; the sample acquisition subunit is used for acquiring a data sample of the output voltage and generating a voltage sample; the residual electricity set calculating subunit is used for calculating a current residual electricity set according to the voltage sample and the adjustable weight vector and according to a formula (1), a formula (2) and a formula (3); the function sample calculation subunit is used for calculating a function sample set according to the remaining power estimated value and the adjustable weight vector and the formula (2); the variance calculation sorting subunit is used for calculating the variance between the data sample and the function sample set to generate a variance set, sorting all variance values in the variance set and generating a variance sorting set; the updating set generating subunit is used for adjusting the sequence of the current residual electric quantity set according to the sequence in the variance sorting set to generate a residual electric quantity sorting set, and taking the first half part of the residual electric quantity sorting set as an updating set; the weight updating subunit is used for judging whether the maximum variance value in the variance sorting set is smaller than a preset threshold value or not, and if so, taking the corresponding weight in the updating set as a new adjustable weight vector; and the termination judgment subunit is used for judging whether the adjustable weight vector conforms to the normal distribution with the mean value of zero or not, and returning to the residual power set calculation subunit if the adjustable weight vector does not conform to the normal distribution with the mean value of zero.
The invention also discloses a computer device, which comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the steps of any one of the methods when executing the computer program.
The invention also discloses a computer-readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, realizes the steps of the method of any of the above.
The implementation of the invention has the following beneficial effects:
the electric vehicle battery control method, the electric vehicle battery control system, the electric vehicle battery control equipment and the readable storage medium can be controlled according to the discharge cut-off threshold value, so that deep discharge of the battery is avoided, and the service life of the battery is prolonged.
Specifically, after the output voltage and the output current of the battery are obtained, the current residual capacity is calculated according to the output voltage, whether the current residual capacity is larger than a preset low-voltage threshold value or not is judged, if the current residual capacity is judged to be not larger than the preset low-voltage threshold value, the current residual capacity is over-low, the discharging cut-off residual capacity is set to be the preset low-capacity threshold value, therefore, the discharging of the battery is stopped under the preset low-capacity threshold value, the over-discharging phenomenon that the discharging capacity of the battery is larger than the preset low-capacity is prevented, and the. If the judgment is yes, calculating the output power according to the output voltage and the output current, acquiring the load power, judging whether the output power is smaller than the load power, if so, indicating that the current power can cause the residual electric quantity to be smaller than the required discharge electric quantity, and setting the discharge cut-off residual electric quantity as the current residual electric quantity, so that the over-discharge phenomenon that the discharge electric quantity is larger than the residual electric quantity can be effectively prevented by the threshold value of the discharge cut-off residual electric quantity, and the battery loss is reduced; and finally, judging whether the current battery residual capacity is smaller than the discharge cut-off residual capacity or not, if so, controlling the battery to stop discharging so as to reduce the battery loss, and if not, indicating that the current battery is not over-discharged, and controlling the battery to continue discharging.
Drawings
FIG. 1 is a general flow chart of a method for controlling a battery of an electric vehicle according to the present invention;
FIG. 2 is a flowchart of a battery control method for an electric vehicle according to the present invention for calculating a current remaining capacity based on an output voltage;
FIG. 3 is a flowchart of an electric vehicle battery control method of the present invention for calculating an adjustable weight vector;
FIG. 4 is a schematic diagram of the battery control system of the electric vehicle according to the present invention;
FIG. 5 is a schematic diagram of a current remaining power calculating module of the battery control system of the electric vehicle according to the present invention;
fig. 6 is a schematic structural diagram of a weight calculation unit of the electric vehicle battery control system of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings. It is only noted that the invention is intended to be limited to the specific forms set forth herein, including any reference to the drawings, as well as any other specific forms of embodiments of the invention.
Fig. 1 shows a general flowchart of a battery control method for an electric vehicle according to the present invention, which includes:
and S101, acquiring the output voltage and the output current of the battery.
And S102, calculating the current residual capacity according to the output voltage.
S103, judging whether the current residual capacity is larger than a preset low voltage threshold value.
And S104, when the judgment result is no, setting the discharge cut-off residual capacity as a preset low-capacity threshold value.
And S105, when the judgment result is yes, calculating output power according to the output voltage and the output current, acquiring load power, judging whether the output power is smaller than the load power, setting the discharge cut-off residual capacity as the current residual capacity when the judgment result is yes, and controlling the battery to continue discharging and finishing the electric vehicle battery control method when the judgment result is no.
And S106, judging whether the current battery residual capacity is smaller than the discharge ending residual capacity, controlling the battery to stop discharging when the current battery residual capacity is judged to be yes, and controlling the battery to continue discharging when the current battery residual capacity is judged to be not to be any.
The electric vehicle battery control method provided by the invention is used for controlling according to the discharge cut-off threshold value, so that the deep discharge of the battery is avoided, and the service life of the battery is prolonged.
Specifically, after the output voltage and the output current of the battery are obtained, the current residual capacity is calculated according to the output voltage, whether the current residual capacity is larger than a preset low-voltage threshold value or not is judged, if the current residual capacity is judged to be not larger than the preset low-voltage threshold value, the current residual capacity is over-low, the discharging cut-off residual capacity is set to be the preset low-capacity threshold value, therefore, the discharging of the battery is stopped under the preset low-capacity threshold value, the over-discharging phenomenon that the discharging capacity of the battery is larger than the preset low-capacity is prevented, and the. If the judgment is yes, calculating the output power according to the output voltage and the output current, acquiring the load power, judging whether the output power is smaller than the load power, if so, indicating that the current power can cause the residual electric quantity to be smaller than the required discharge electric quantity, and setting the discharge cut-off residual electric quantity as the current residual electric quantity, so that the over-discharge phenomenon that the discharge electric quantity is larger than the residual electric quantity can be effectively prevented by the threshold value of the discharge cut-off residual electric quantity, and the battery loss is reduced; and finally, judging whether the current battery residual capacity is smaller than the discharge cut-off residual capacity or not, if so, controlling the battery to stop discharging so as to reduce the battery loss, and if not, indicating that the current battery is not over-discharged, and controlling the battery to continue discharging.
Steps S101 to S106 are continuously performed in a loop. A new cycle will be entered after one cycle is completed. In a new control cycle, starting from step S101, a new output voltage and output current are obtained, then a discharge cut-off remaining capacity is set, and the discharge state of the battery is controlled according to the discharge cut-off remaining capacity, so as to continuously prevent the over-discharge of the battery and prolong the service life of the battery.
Further, the step of calculating the current remaining capacity according to the output voltage includes:
s201, calculating a residual electric quantity pre-estimated value;
s202, calculating an adjustable weight vector;
s203, calculating the current remaining capacity:
SOCj＝Y(SOC,wi,OCVj)+εj(1)
Figure BDA0002395099160000061
Figure BDA0002395099160000062
therein, SOCjFor the current remaining capacity, SOC is the estimated value of remaining capacity, OCVjTo output a voltage, wiFor adjustable weight vector value, BW is kernel parameter, N is iteration number, epsilonjIs a noise value, w0Is a preset initial vector value.
The output voltage OCVjAnd the current remaining capacity SOCjIs the same, i.e. the output voltage OCV is detected a plurality of timesjThen the corresponding current remaining capacity SOC can be calculatedj。
The current remaining power needs to be described according to the estimated value of the remaining power and the adjustable weight vector. The following describes a calculation method of the remaining power estimation value and the adjustable weight vector.
Further, the step of calculating the estimated remaining power includes: calculating a remaining power estimate according to the following formula:
Figure BDA0002395099160000063
wherein S is0To estimate the amount of charge at the beginning of the period, Q is the total charge of the battery, i is the output current, and t is the estimation period.
Further, the step of calculating the adjustable weight vector comprises:
s301, generating an adjustable weight vector according to an initial value of the set adjustable weight vector;
s302, acquiring a data sample of the output voltage, and generating a voltage sample;
s303, calculating a current residual electric quantity set according to the voltage sample and the adjustable weight vector and a formula (1), a formula (2) and a formula (3);
s304, respectively calculating a function sample set according to a formula (2) according to the residual power estimated value and the adjustable weight vector;
s305, calculating the variance between the data sample and the function sample set to generate a variance set, and sequencing all variance values in the variance set to generate a variance sequencing set;
s306, adjusting the sequence of the current residual electric quantity set according to the sequence in the variance sequencing set to generate a residual electric quantity sequencing set, and taking the first half part of the residual electric quantity sequencing set as an updating set;
it should be noted that, the variances corresponding to the first half of the remaining power ordered set are all smaller than the second half, so that the first half of the remaining power ordered set is used as an update set, and an adjustable weight vector which is close to an actual value can be calculated is determined.
S307, judging whether the maximum variance value in the variance sorting set is smaller than a preset threshold value, and if so, taking the corresponding weight in the updating set as a new adjustable weight vector.
It should be noted that, each calculation cycle generates an update set, but if the weight corresponding to the update set is used as a new adjustable weight vector, it is determined whether the maximum variance value in the variance ordered set is smaller than a preset threshold, and if the maximum variance value is determined to be smaller than the preset threshold, the weight corresponding to the update set is used as a new adjustable weight vector.
S308, judging whether the adjustable weight vector accords with normal distribution with the mean value of zero, judging whether the adjustable weight vector accords with the normal distribution with the mean value of zero, and returning to the step S303 if the adjustable weight vector does not accord with the normal distribution with the mean value of zero.
The adjustable weight vector satisfies normal distribution, so that the adjusting time can be shortened, the error is reduced, and the situation that the calculation cannot be carried out due to abnormal fluctuation of the adjustable weight vector and even the calculation enters a dead cycle is avoided.
Further, the step of calculating the output power according to the output voltage and the output current includes: the output power is calculated according to the following formula:
Po＝OCVj·i
wherein, PoFor output power, OCVjI is the output voltage and i is the output current.
Correspondingly, the invention also discloses an electric vehicle battery control system 100, which comprises:
the acquisition module 1 is used for acquiring the output voltage and the output current of the battery;
the current residual capacity calculating module 2 is used for calculating the current residual capacity according to the output voltage;
the residual electric quantity judging module 3 is used for judging whether the current residual electric quantity is larger than a preset low voltage threshold value;
a discharging cut-off low power setting module 4 for setting the discharging cut-off remaining power as a preset low power threshold value when the judgment is negative,
the discharging cut-off residual setting module 5 is used for calculating output power according to the output voltage and the output current when the judgment result is yes, acquiring load power, judging whether the output power is smaller than the load power, setting discharging cut-off residual electric quantity as current residual electric quantity when the judgment result is yes, and controlling the battery to continue discharging and finishing calling the electric vehicle battery control system when the judgment result is no;
and the discharging ending judgment control module 6 is used for judging whether the current battery residual capacity is smaller than the discharging ending residual capacity or not, controlling the battery to stop discharging when the judgment is yes, and controlling the battery to continue discharging when the judgment is no.
The electric vehicle battery control method provided by the invention is used for controlling according to the discharge cut-off threshold value, so that the deep discharge of the battery is avoided, and the service life of the battery is prolonged.
Specifically, after the obtaining module 1 obtains the output voltage and the output current of the battery, the current remaining power calculating module 2 calculates the current remaining power according to the output voltage, then the remaining power judging module 3 judges whether the current remaining power is greater than a preset low voltage threshold, if not, the current remaining power is too low, the discharging cut-off remaining power setting module 4 sets the discharging cut-off remaining power as the preset low power threshold, so that the battery is ensured to stop discharging under the preset low power threshold, and an over-discharging phenomenon that the discharging amount of the battery is greater than the preset low power is prevented, so that the battery loss is reduced. If the judgment is yes, the discharging cut-off residual setting module 5 calculates the output power according to the output voltage and the output current, obtains the load power, and judges whether the output power is smaller than the load power, if so, the discharging cut-off residual setting module 5 sets the discharging cut-off residual power as the current residual power, so that the discharging cut-off residual power is a threshold value which can effectively prevent the over-discharging phenomenon that the discharging power is larger than the residual power, and the battery loss is reduced; finally, the discharging-ending judgment control module 6 judges whether the current battery residual capacity is smaller than the discharging-ending residual capacity, if so, the battery is controlled to stop discharging, so that the battery loss is reduced, if not, the battery can be controlled to continue discharging.
It should be noted that the functional modules are called in a loop continuously. A new cycle will be entered after one cycle is completed. In a new control cycle, the acquisition module 1 is called to acquire a new output voltage and output current, then other modules are called to set the discharge cut-off residual capacity, and the discharge state of the battery is controlled according to the discharge cut-off residual capacity, so that the over-discharge condition of the battery is continuously prevented, and the service life of the battery is prolonged.
Further, the current remaining capacity calculation module 2 includes:
a prediction value calculation unit 21 for calculating a remaining power prediction value;
a weight calculation unit 22, configured to calculate an adjustable weight vector;
the remaining power calculating unit 23 is configured to calculate a current remaining power:
SOCj＝Y(SOC,wi,OCVj)+εj(1)
Figure BDA0002395099160000091
Figure BDA0002395099160000092
therein, SOCjFor the current remaining capacity, SOC is the estimated value of remaining capacity, OCVjTo output a voltage, wiFor adjustable weight vector value, BW is kernel parameter, N is iteration number, epsilonjIs a noise value, w0Is a preset initial vector value.
The output voltage OCVjAnd the current remaining capacity SOCjIs the same, i.e. the output voltage OCV is detected a plurality of timesjThen the corresponding current remaining capacity SOC can be calculatedj。
The current remaining power needs to be described according to the estimated value of the remaining power and the adjustable weight vector. The following describes a calculation method of the remaining power estimation value and the adjustable weight vector.
Further, the estimation value calculation unit 21 calculates the estimation value of the remaining power according to the following formula:
Figure BDA0002395099160000093
wherein S is0To estimate the amount of charge at the beginning of the period, Q is the total charge of the battery, i is the output current, and t is the estimation period.
Further, the weight calculation unit 22 includes:
an initial weight setting subunit 221, configured to generate an adjustable weight vector according to an initial value of the set adjustable weight vector;
a sample acquiring subunit 222, configured to acquire a data sample of the output voltage, and generate a voltage sample;
the residual electricity set calculating subunit 223 is configured to calculate, according to the voltage sample and the adjustable weight vector, a current residual electricity set according to the formula (1), the formula (2), and the formula (3);
the function sample calculation subunit 224 is configured to calculate a function sample set according to the formula (2) according to the estimated remaining power value and the adjustable weight vector;
a variance calculating and sorting subunit 225, configured to calculate a variance between the data sample and the function sample set, generate a variance set, sort all variance values in the variance set, and generate a variance sorting set;
an update set generation subunit 226, configured to adjust an order of the current remaining power set according to the order in the variance ordered set to generate a remaining power ordered set, and use a first half of the remaining power ordered set as an update set;
it should be noted that, the variances corresponding to the first half of the remaining power ordered set are all smaller than the second half, so the update set generation subunit 226 uses the first half of the remaining power ordered set as an update set, thereby determining an adjustable weight vector that can be calculated to be close to an actual value.
A weight updating subunit 227, configured to determine whether the maximum variance value in the variance sorting set is smaller than a preset threshold, and if so, take the corresponding weight in the updating set as a new adjustable weight vector;
it should be noted that, each calculation cycle generates an update set, but if the weight corresponding to the update set is used as a new adjustable weight vector, it needs to see whether the maximum variance value in the variance ordered set is smaller than a preset threshold, and if the variance value is determined to be small enough, the weight update subunit 227 can use the weight corresponding to the update set as a new adjustable weight vector.
And a termination judgment subunit 228, configured to judge whether the adjustable weight vector conforms to a normal distribution with a mean value of zero, and if not, return to the residual power set calculation subunit 223.
The adjustable weight vector satisfies normal distribution, so that the adjusting time can be shortened, the error is reduced, and the situation that the calculation cannot be carried out due to abnormal fluctuation of the adjustable weight vector and even the calculation enters a dead cycle is avoided.
Further, the discharge cutoff to remaining setting module 5 calculates the output power according to the following formula:
Po＝OCVj·i
wherein, PoFor output power, OCVjI is the output voltage and i is the output current.
Correspondingly, the invention also discloses computer equipment which comprises a memory and a processor, wherein the memory stores computer programs, and the processor realizes the steps of any one of the methods when executing the computer programs.
Accordingly, the invention also discloses a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any of the above.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention.

Claims (10)

1. A method for controlling a battery of an electric vehicle, comprising:
acquiring output voltage and output current of a battery;
calculating the current residual capacity according to the output voltage;
judging whether the current residual capacity is larger than a preset low voltage threshold value or not,
if not, setting the discharge cut-off residual capacity as the preset low-capacity threshold value,
if so, calculating output power according to the output voltage and the output current, acquiring load power, judging whether the output power is smaller than the load power, if so, setting the discharge cut-off residual capacity as the current residual capacity, and if not, controlling the battery to continue discharging and finishing the electric vehicle battery control method;
and judging whether the current battery residual capacity is smaller than the discharge ending residual capacity, controlling the battery to stop discharging when the judgment is yes, and controlling the battery to continue discharging when the judgment is no.
2. The battery control method for electric vehicles according to claim 1, wherein the step of calculating the current remaining capacity based on the output voltage comprises:
calculating a residual electric quantity estimated value;
calculating an adjustable weight vector;
calculating the current remaining capacity:
SOCj＝Y(SOC,wi,OCVj)+εj(1)
Figure FDA0002395099150000011
Figure FDA0002395099150000012
therein, SOCjFor the current residual capacity, SOC is the estimated value of residual capacity, OCVjIs the output voltage, wiFor adjustable weight vector value, BW is kernel parameter, N is iteration number, epsilonjIs a noise value, w0Is a preset initial vector value.
3. The battery control method for electric vehicles according to claim 2, wherein the step of calculating the estimated value of remaining charge comprises:
calculating the estimated remaining power value according to the following formula:
Figure FDA0002395099150000021
wherein S is0To estimate the amount of charge at the beginning of the period, Q is the total charge of the battery, i is the output current, and t is the estimation period.
4. The method of claim 3, wherein the step of calculating the adjustable weight vector comprises:
s1, generating an adjustable weight vector according to the initial value of the set adjustable weight vector;
s2, acquiring a data sample of the output voltage, and generating a voltage sample;
s3, calculating a current residual electric quantity set according to the formula (1), the formula (2) and the formula (3) according to the voltage sample and the adjustable weight vector;
s4, respectively calculating a function sample set according to a formula (2) according to the residual power estimated value and the adjustable weight vector;
s5, calculating the variance between the data sample and the function sample set to generate a variance set, and sequencing all variance values in the variance set to generate a variance sequencing set;
s6, adjusting the sequence of the current residual electric quantity set according to the sequence in the variance sorting set to generate a residual electric quantity sorting set, and taking the first half part of the residual electric quantity sorting set as an updating set;
s7, judging whether the maximum variance value in the variance sorting set is smaller than a preset threshold value, if so, taking the corresponding weight in the updating set as a new adjustable weight vector;
s8, judging whether the adjustable weight vector accords with normal distribution with the mean value of zero, judging whether the adjustable weight vector accords with the normal distribution with the mean value of zero, returning to the step S3.
5. The method for controlling a battery of an electric vehicle according to claim 1, wherein the step of calculating an output power based on the output voltage and the output current comprises:
calculating the output power according to the following formula:
Po＝OCVj·i
wherein, the PoFor said output power, OCVjIs the output voltage, i is the output current.
6. An electric vehicle battery control system, comprising:
the acquisition module is used for acquiring the output voltage and the output current of the battery;
the current residual power calculation module is used for calculating the current residual power according to the output voltage;
a remaining power determining module for determining whether the current remaining power is greater than a preset low voltage threshold,
a discharging cut-off to low power setting module for setting the discharging cut-off remaining power as the preset low power threshold value if the judgment is negative,
the discharging cut-off residual setting module is used for calculating output power according to the output voltage and the output current when the judgment result is yes, acquiring load power, judging whether the output power is smaller than the load power, setting discharging cut-off residual capacity as current residual capacity when the judgment result is yes, controlling the battery to continue discharging and finishing calling the electric vehicle battery control system when the judgment result is no;
and the discharging ending judgment control module is used for judging whether the current battery residual capacity is smaller than the discharging ending residual capacity or not, controlling the battery to stop discharging when the current battery residual capacity is judged to be yes, and controlling the battery to continue discharging when the current battery residual capacity is judged to be not.
7. The electric vehicle battery control system of claim 6, wherein the current remaining capacity calculation module comprises:
the estimated value calculating unit is used for calculating the estimated value of the residual electric quantity;
the weight calculation unit is used for calculating an adjustable weight vector;
a remaining power calculating unit for calculating the current remaining power:
SOCj＝Y(SOC,wi,OCVj)+εj(1)
Figure FDA0002395099150000031
Figure FDA0002395099150000032
therein, SOCjFor the current residual capacity, SOC is the estimated value of residual capacity, OCVjIs the output voltage, wiFor adjustable weight vector value, BW is kernel parameter, N is iteration number, epsilonjIs a noise value, w0Is a preset initial vector value.
8. The electric vehicle battery control system of claim 6, wherein the weight calculation unit comprises:
the initial weight setting subunit is used for generating an adjustable weight vector according to the initial value of the set adjustable weight vector;
the sample acquisition subunit is used for acquiring a data sample of the output voltage and generating a voltage sample;
the residual electricity set calculating subunit is used for calculating a current residual electricity set according to the voltage sample and the adjustable weight vector and according to a formula (1), a formula (2) and a formula (3);
the function sample calculation subunit is used for calculating a function sample set according to the remaining power estimated value and the adjustable weight vector and a formula (2);
the variance calculation sorting subunit is used for calculating the variance between the data sample and the function sample set to generate a variance set, sorting all the variance values in the variance set and generating a variance sorting set;
an update set generation subunit, configured to adjust an order of the current remaining power set according to the order in the variance ordered set to generate a remaining power ordered set, and use a first half of the remaining power ordered set as an update set;
a weight updating subunit, configured to determine whether the maximum variance value in the variance sorting set is smaller than a preset threshold, and if so, take the corresponding weight in the updating set as a new adjustable weight vector;
and the termination judgment subunit is used for judging whether the adjustable weight vector conforms to normal distribution with the mean value of zero, and returning to the residual electricity set calculation subunit if the adjustable weight vector does not conform to the normal distribution with the mean value of zero.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 5.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 5.
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