CN113125967A - Lithium battery SOE calculation method based on temperature rise prediction - Google Patents
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- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 title claims abstract description 38
- 229910052744 lithium Inorganic materials 0.000 title claims abstract description 38
- 238000004364 calculation method Methods 0.000 title claims abstract description 28
- 238000000034 method Methods 0.000 claims abstract description 21
- 238000007599 discharging Methods 0.000 claims description 19
- 238000010438 heat treatment Methods 0.000 abstract description 2
- 238000012360 testing method Methods 0.000 description 8
- 238000005457 optimization Methods 0.000 description 4
- QSNQXZYQEIKDPU-UHFFFAOYSA-N [Li].[Fe] Chemical compound [Li].[Fe] QSNQXZYQEIKDPU-UHFFFAOYSA-N 0.000 description 3
- HBBGRARXTFLTSG-UHFFFAOYSA-N Lithium ion Chemical compound [Li+] HBBGRARXTFLTSG-UHFFFAOYSA-N 0.000 description 2
- 238000006243 chemical reaction Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000010354 integration Effects 0.000 description 2
- 229910001416 lithium ion Inorganic materials 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000008358 core component Substances 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 239000000446 fuel Substances 0.000 description 1
- 230000010287 polarization Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000012827 research and development Methods 0.000 description 1
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- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
- G01R31/3835—Arrangements for monitoring battery or accumulator variables, e.g. SoC involving only voltage measurements
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/10—Energy storage using batteries
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Abstract
The invention relates to a lithium battery SOE calculation method based on temperature rise prediction, which comprises the steps of obtaining a two-dimensional table T-Q-W of the temperature, the residual capacity and the discharge energy of a lithium battery; obtaining an OCV curve of the lithium battery; obtaining total battery discharge energy through an OCV curve, and calculating to obtain a temperature and discharge efficiency one-dimensional table T-b so as to obtain battery discharge energy efficiency b at different temperatures; obtaining the residual discharge energy W of the battery according to the temperature, the residual capacity and the discharge energy two-dimensional table T-Q-W; calculating SOE according to the battery discharge energy efficiency b and the residual discharge energy w; according to the invention, the latest temperature change rate a is obtained through continuous calculation of the latest data collected by the BMS, the predicted temperature T is re-estimated according to the latest temperature change rate a, and the predicted temperature T is continuously close to the actual temperature Treal at the time T through iteration of the whole process, so that the problem of calculation difference that the battery cannot release electric quantity at low temperature caused by battery heating can be greatly reduced.
Description
Technical Field
The invention belongs to the field of new energy automobile battery management systems, and particularly relates to the field of a lithium battery SOE calculation method based on a low-temperature environment.
Background
A Battery Management System (BMS), which is one of the core components of an electric vehicle, is always the key point of research and development of the electric vehicle, SOC, SOH, SOP, and SOE are the most critical parameters of the BMS, and during the running of the vehicle, a lithium Battery performs a complex chemical reaction, and the relation parameters of SOC, SOH, SOP, SOE, and the like cannot be directly obtained, and only the Battery voltage and temperature can be acquired by the BMS, and indirect estimation is performed through a lithium Battery model and an estimation algorithm; the SOE is similar to the residual oil quantity in the fuel vehicle, the SOE is the key of mileage calculation, accurate SOE calculation can effectively provide a reliable reference for the travel of a terminal user, and user experience is improved; however, since the internal resistance and polarization resistance of the lithium battery are multiplied in a low-temperature environment, the battery can more easily reach the cut-off voltage at a low temperature. Therefore, in a low-temperature environment, the SOE of the lithium battery is equal to the remaining battery capacity-the battery cannot release the battery at low temperature, the battery cannot release the battery at low temperature continuously changes along with the actual temperature of the battery in the running process of the electric vehicle, and the battery cannot release the battery at low temperature depends on the temperature at which the discharging is finished; and the lithium cell itself can carry out chemical reaction and generate heat at the in-process of discharging, so the lithium cell has obvious temperature rise at the in-process of discharging, consequently can not release electric quantity through current temperature calculation battery low temperature can and can not release electric quantity through the temperature calculation battery low temperature when discharging and have great difference.
Disclosure of Invention
In order to solve the problem that the calculation of the electric quantity which cannot be released at low temperature of the battery has large difference, the invention realizes the purpose through the following technical scheme:
a lithium battery SOE calculation method based on temperature rise prediction comprises the following steps
S1, obtaining a two-dimensional table T-Q-W of the temperature, the residual capacity and the discharge energy of the lithium battery;
s2, obtaining an OCV curve of the lithium battery;
s3, obtaining total battery discharge energy through an OCV curve, and calculating to obtain a temperature and discharge efficiency one-dimensional table T-b so as to obtain battery discharge energy efficiency b at different temperatures;
s4, searching a two-dimensional table T-Q-W of the temperature, the residual capacity and the discharge energy of the lithium battery according to the predicted temperature T and the real-time residual capacity Q to obtain the battery discharge residual discharge energy W;
and S5, calculating the SOE according to the battery discharge energy efficiency b and the residual discharge energy W, wherein the SOE in the S5 is the battery discharge energy efficiency b and the residual discharge energy W.
As a further optimization scheme of the present invention, the determination of the predicted temperature T and the real-time remaining capacity Q in S4 includes the following steps;
s41, judging whether the current lithium battery state is a power-on initialization state, acquiring the residual capacity at the initial discharge time as Q1 and the temperature as T1, if so, entering S42, and otherwise, entering S43;
s42, obtaining the temperature change rate a1 of the discharge, calculating the predicted temperature T in the initial state, wherein the real-time residual capacity Q is Q1, and the real-time temperature T is T1, and then entering S47;
s43, storing the residual capacity Q2 of the intermediate variable as Q1, and the temperature of the intermediate variable as T2 as T1, and simultaneously acquiring the residual capacity Q3 and the temperature T3 in the discharging process;
s44, judging whether a constraint condition is met between T3 and T2, if the temperature change meets the constraint condition, entering S45, and if not, entering S46;
s45, updating and calculating a corresponding temperature change rate a2, updating the predicted temperature T, updating the intermediate residual capacity Q2 to Q3, updating the intermediate variable temperature T2 to T3, and entering S47;
s46, keeping the predicted temperature T unchanged, enabling the real-time residual capacity Q to be Q3 and the real-time temperature T to be T3, and then entering S47;
and S47, obtaining the predicted temperature T and the real-time residual capacity Q under different conditions, judging whether the current lithium battery state is a power-off state, if so, terminating the circulation, otherwise, continuously circulating the steps.
As a further preferable aspect of the present invention, the temperature change rate a1 of the discharge in S42 is (battery end temperature Ta — battery start temperature Ts)/total discharge capacity Qa.
As a further preferable aspect of the present invention, the predicted temperature T in the initial state in S42 is a 1Q 1+ T1.
As a further optimization scheme of the present invention, the constraint condition satisfied between T3 and T2 in S44 is T3-T2> ═ Δ T.
As a further optimization of the present invention, the updated temperature change rate a2 in S45 is (T2-T3)/(Q2-Q3) × λ + a2 (1- λ).
As a further optimization of the present invention, the updated predicted temperature T in S45 is (a2 — Q3+ T2) × 1+ T (1- λ 1).
The invention has the beneficial effects that:
1) according to the invention, the latest temperature change rate a is obtained through the latest data collected by the BMS through continuous calculation, then the predicted temperature T is re-estimated according to the latest temperature change rate a, and the predicted temperature T is continuously close to the actual temperature Treal at the time T through iteration of the whole process, so that the problem of calculation difference that the battery cannot release electric quantity at low temperature caused by battery heating can be greatly reduced.
Drawings
FIG. 1 is a schematic diagram of the steps of the SOE calculation method of the present invention;
FIG. 2 is a schematic flow chart of the algorithm of the present invention;
FIG. 3 is a schematic diagram of an SOE accuracy test of a certain vehicle in a low temperature environment;
Detailed Description
The present application will now be described in further detail with reference to the drawings, it should be noted that the following detailed description is given for illustrative purposes only and is not to be construed as limiting the scope of the present application, as those skilled in the art will be able to make numerous insubstantial modifications and adaptations to the present application based on the above disclosure.
The lithium battery SOE calculation method based on temperature rise prediction as shown in FIGS. 1 to 3 comprises a lithium battery SOE calculation method based on temperature rise prediction, wherein the method calculates the temperature at the discharge cut-off through temperature rise prediction, recalculates the SOE according to the predicted temperature at the discharge cut-off, and reduces the SOE error caused by temperature rise; the specific principle is as follows:
since temperature change is a slow process, the rate of temperature change in a short time is approximately the same in a stable discharge condition; therefore, the battery residual capacity q1 corresponding to the time t1 and the battery residual capacity q2 corresponding to the time t2 can be calculated by ampere-hour integration of the current according to the temperature collected by the BMS at the time t1 and the temperature collected by the BMS at the time t2, and the rate of change a of the temperature from the time t1 to the time t2 is equal to (the temperature at the time t 2-the temperature at the time t 1)/(the residual capacity q 2-the residual capacity q 1);
assuming that the working condition of the automobile at the future time in the short-time running process is similar to the current working condition, the rate of temperature change at the future time is approximately equal to a, assuming that the residual capacity at the future time t is qt, and the temperature at the future time t is the rate of temperature change a (the residual capacity qt-the battery residual capacity q1) + t 1; the working condition of the automobile can be greatly changed in the running discharging process, the temperature rise rate a is changed in real time, T1, T2, q1 and q2 are updated through the latest data collected by the BMS, the latest a is obtained through calculation, the predicted temperature T is estimated again according to the latest a, and the predicted temperature T is enabled to be continuously close to the actual temperature Treal at the T moment through iteration of the whole process;
because the discharge energy efficiency b of the battery at different temperatures in the discharge process is influenced by temperature change, the battery is seriously polarized and has small voltage under the low-temperature environment, the released energy is also small, and the temperature and the energy efficiency are in positive correlation; therefore, the loss in the discharging process in a certain period of time is between the discharging energy loss corresponding to the starting temperature and the discharging energy loss corresponding to the ending temperature of the process, and then the loss in the discharging process in a certain period of time can be approximately equal to the average value of the discharging energy loss corresponding to the starting temperature and the discharging energy loss corresponding to the ending temperature; the temperature rise in the lithium battery discharging process is closely related to parameters such as the specific heat capacity, the environmental temperature, the PACK temperature, the internal resistance of PACK, the PACK current and the residual capacity of the lithium battery; the BMS can measure PACK temperature and present current through the sensors and estimate remaining capacity by ampere-hour integration of the current.
The SOE calculation method comprises the following steps: testing the discharge energy of the battery discharged under different temperature stable working conditions, and making the data obtained by the test into a two-dimensional table of temperature, residual capacity and SOE; and searching a two-dimensional table of the temperature, the SOC and the SOE according to the predicted temperature T and the predicted residual capacity Q, and performing bilinear interpolation to obtain the SOE.
The specific operation is as follows:
firstly, testing calibration data
S1, obtaining a two-dimensional table T-Q-W of the temperature, the residual capacity and the discharge energy of the lithium battery;
firstly, testing the total discharge capacity Qa and the discharge energy W1 of 0.33C current discharge at a certain temperature Tn, wherein the temperature change rate a1 of discharge in the 0.33C discharge process is (battery termination temperature Ta-battery starting temperature Ts)/total discharge capacity Qa;
then adjusting the temperature Tn to obtain three tables, namely a one-dimensional table T-Q of temperature and total discharge capacity, a two-dimensional table T-Q-W of temperature and residual capacity and discharge energy, and a one-dimensional table T-a of temperature change rate;
(1) discharging to discharge cutoff voltage at 1/3C (A) at room temperature;
(2) standing at room temperature for no less than 30min or enterprise-specified standing time (no more than 60 min);
(3) under the condition of room temperature, when the constant current of a battery of 1/3C (A) is charged to the charging termination voltage specified by the enterprise, the battery is charged at constant voltage, and when the charging termination current is reduced to 0.05C (A), the charging is stopped, and the lithium ion storage battery is kept still for 1 hour after the charging (or kept still for no more than 1 hour specified by the enterprise);
(4) standing the battery for not less than 1 hour (1 hour for a ternary battery and 2 hours for a lithium iron battery) at the temperature to be tested until the temperature of the battery reaches the temperature to be tested;
(5) discharging to a discharge cutoff voltage at a temperature to be tested at 1/3C (A) current;
(6) the battery start temperature T, the battery end temperature T, the total discharge capacity Q (in AH), and the discharge energy W1 (in WH) were recorded (5).
S2, obtaining an OCV curve of the lithium battery, namely the OCV curve of 0.33C current discharge under the test temperature T3; (1) discharging to discharge cutoff voltage at 1/3C (A) at room temperature;
(2) standing at room temperature for no less than 30min or enterprise-specified standing time (no more than 60 min);
(3) under the condition of room temperature, when the constant current of a battery of 1/3C (A) is charged to the charging termination voltage specified by the enterprise, the battery is charged at constant voltage, and when the charging termination current is reduced to 0.05C (A), the charging is stopped, and the lithium ion storage battery is kept still for 1 hour after the charging (or kept still for no more than 1 hour specified by the enterprise);
(4) standing the battery for not less than 1 hour (1 hour for a ternary battery and 2 hours for a lithium iron battery) at the temperature to be tested until the temperature of the battery reaches the temperature to be tested;
(5) discharging at the temperature needing to be tested by current of 1/3C (A), standing for not less than 1 hour (1 hour of a ternary battery and 2 hours of an lithium iron battery) every 5 percent of the capacity of the battery at the current temperature, and recording the current OCV;
(6) the correspondence of SOC to OCV and the total discharge capacity (in AH) were calculated and recorded.
S3, obtaining total battery discharge energy through an OCV curve, and calculating a temperature and discharge efficiency one-dimensional table T-b to further obtain battery discharge energy efficiency b at different temperatures;
multiplying the discharge current of the battery under the condition of temperature Tn by the OCV obtained in S2, and then integrating to obtain total discharge energy W2 of the battery; then, according to the temperature point of S1, a one-dimensional table T-b of temperature and discharge efficiency is calculated; wherein, the battery discharge energy efficiency b is discharge energy W1/total battery discharge energy W2 at different temperatures; the battery discharge energy efficiency b in the discharge process is approximately equal to (the discharge energy efficiency corresponding to the starting temperature and the discharge energy efficiency corresponding to the ending temperature)/2;
secondly, carrying out specific algorithm calculation
S41, judging whether the current lithium battery state is a power-on initialization state, acquiring the residual capacity at the initial discharge time as Q1 and the temperature as T1, if so, entering S42, and otherwise, entering S43;
s42, obtaining a temperature change rate of discharge a1, where a1 is (battery end temperature Ta — battery start temperature Ts)/total discharge capacity Qa, and calculating a predicted temperature T in an initial state, where a1 is Q1+ T1 is the predicted temperature T in the initial state; at this time, the real-time remaining capacity Q is Q1, the real-time temperature Tcur is T1, and then the process proceeds to S47;
s43, storing the residual capacity Q2 of the intermediate variable as Q1, and the temperature of the intermediate variable as T2 as T1, and simultaneously acquiring the residual capacity Q3 and the temperature T3 in the discharging process;
s44, judging whether a constraint condition is met between T3 and T2, namely, entering S45 when the temperature change T3-T2> -delta T, or entering S46;
s45, updating and calculating a corresponding temperature change rate a2, and performing filtering processing, where λ is a first-order lag filter coefficient, where a2 is (T2-T3)/(Q2-Q3) λ + a2 (1- λ), and updating a predicted temperature T, where a2 is-Q3 + T2) λ 1+ T (1- λ 1), and λ 1 is a first-order lag filter coefficient; updating the intermediate residual capacity Q2 to Q3 and the intermediate variable temperature T2 to T3, and then entering S47;
s46, keeping the predicted temperature T unchanged, wherein the real-time residual capacity Q is Q3, the real-time temperature Tcur is T3, and then entering S47;
s47, calculating the SOE at the initial discharge time, and then entering S48;
searching a temperature, residual capacity and discharge energy two-dimensional table T-Q-W by using the predicted temperature T and the real-time residual capacity Q obtained under different conditions in the step, and then obtaining the battery discharge residual discharge energy W of the battery at the predicted temperature T by making a bilinear difference;
similarly, the battery discharge energy efficiency b is obtained by combining the obtained predicted temperature T with the temperature and discharge efficiency one-dimensional table T-b in the step S3;
then, the obtained battery discharge energy efficiency b and the obtained residual discharge energy W are taken into the SOE (initial discharge time SOE-battery discharge energy efficiency b-residual discharge energy W) to obtain the SOE;
and S48, judging whether the current lithium battery state is a power-off state, if so, terminating the circulation, otherwise, continuously circulating the steps.
As shown in fig. 3, a sample vehicle is subjected to an SOE accuracy test in a low-temperature environment, and the sample vehicle is tested under a working condition with a speed of about 80km/h, because the speed of the whole vehicle is basically constant, the higher the positive correlation between the SOE and the actual remaining mileage of the sample vehicle is, the more accurate the SOE is proved to be, and the closer the theoretical remaining mileage calculated by the SOE is to the actual remaining mileage; the SOE without temperature prediction is the problem that the calculation of the obvious low-temperature SOE is low when the SOE is calculated according to the real-time temperature; as shown by the sample car test results: the calculated SOE with the temperature prediction added can calculate the theoretical remaining mileage more accurately than the calculated SOE without adding the temperature prediction.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention.
Claims (7)
1. A lithium battery SOE calculation method based on temperature rise prediction is characterized by comprising the following steps: s1, acquiring a two-dimensional table T-Q-W of the temperature, the residual capacity and the discharge energy of the lithium battery;
s2, obtaining an OCV curve of the lithium battery;
s3, obtaining total battery discharge energy through an OCV curve, and calculating a temperature and discharge efficiency one-dimensional table T-b to further obtain battery discharge energy efficiency b at different temperatures;
s4, searching a two-dimensional table T-Q-W of the temperature, the residual capacity and the discharge energy of the lithium battery according to the obtained predicted temperature T and the real-time residual capacity Q to obtain the discharge residual discharge energy W of the battery;
and S5, calculating the SOE according to the battery discharge energy efficiency b and the residual discharge energy W, wherein the SOE is the battery discharge energy efficiency b and the residual discharge energy W.
2. The lithium battery SOE calculation method based on temperature rise prediction according to claim 1, characterized in that: the determination of the predicted temperature T and the real-time remaining capacity Q in S4 includes the following steps;
s41, judging whether the current lithium battery state is a power-on initialization state, acquiring the residual capacity at the initial discharge time as Q1 and the temperature as T1, if so, entering S42, and otherwise, entering S43;
s42, obtaining the discharge temperature change rate a1, calculating the predicted temperature T in the initial state, where the real-time residual capacity Q is Q1 and the real-time temperature Tcur is T1, and then entering S47;
s43, storing the residual capacity Q2 of the intermediate variable as Q1, and the temperature of the intermediate variable as T2 as T1, and simultaneously acquiring the residual capacity Q3 and the temperature T3 in the discharging process;
s44, judging whether a constraint condition is met between T3 and T2, if the temperature change meets the constraint condition, entering S45, and if not, entering S46;
s45, updating and calculating a corresponding temperature change rate a2, updating the predicted temperature T, updating the intermediate residual capacity Q2 to Q3, updating the intermediate variable temperature T2 to T3, and entering S47;
s46, keeping the predicted temperature T unchanged, wherein the real-time residual capacity Q is Q3, the real-time temperature Tcur is T3, and then entering S47;
and S47, obtaining the predicted temperature T and the real-time residual capacity Q under different conditions, judging whether the current lithium battery state is a power-off state, if so, terminating the circulation, otherwise, continuously circulating the steps.
3. The lithium battery SOE calculation method based on temperature rise prediction according to claim 2, characterized in that: the rate of change a1 of the temperature of the discharge in S42 ═ battery end temperature Ta — battery start temperature Ts)/total discharge capacity Qa.
4. The lithium battery SOE calculation method based on temperature rise prediction according to claim 2, characterized in that: the predicted temperature T at the initial state in S42 is a 1Q 1+ T1.
5. The lithium battery SOE calculation method based on temperature rise prediction according to claim 2, characterized in that: the constraint condition satisfied between T3 and T2 in S44 is T3-T2> ═ Δ T.
6. The lithium battery SOE calculation method based on temperature rise prediction according to claim 2, characterized in that: the updated temperature change rate a2 in S45 is (T2-T3)/(Q2-Q3) × λ + a2 (1- λ), where λ is a first order lag filter coefficient.
7. The lithium battery SOE calculation method based on temperature rise prediction according to claim 2, characterized in that: the predicted temperature T updated in S45 is (a2 × Q3+ T2) × 1+ T (1- λ 1), where λ 1 is a first-order lag filter coefficient.
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| CN114734819A (en) * | 2022-03-07 | 2022-07-12 | 江铃汽车股份有限公司 | Electric automobile driving range calculation method and system, storage medium and electric automobile |
| WO2024022569A1 (en) * | 2022-07-23 | 2024-02-01 | Sveuciliste U Zagrebu Fakultet Elektrotehnike I Racunarstva | Method for experimental determination of battery parameters and their use |
| WO2024120501A1 (en) * | 2022-12-07 | 2024-06-13 | 湖北亿纬动力有限公司 | Battery remaining charging time computing method and apparatus, electronic device, and storage medium |
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