JP6440377B2 - Secondary battery state detection device and secondary battery state detection method - Google Patents

Description

  The present invention relates to a secondary battery state detection device and a secondary battery state detection method.

  The secondary battery has an upper limit on the chargeable electric capacity, and the upper limit of SOC (State of Charge) is referred to as SOC at the limit of charge acceptance (full charge state). In order to obtain the accurate SOC of the secondary battery, it is necessary to obtain the charging rate based on the stable inter-terminal voltage of the secondary battery at the limit of charge acceptance and the SOC of the fully charged state of the charging rate.

  Such a fully charged state is a state in which charging has been completed by performing any of the methods described in “JIS D. 5301 .: 2006. 2.4.2 Charging section of lead acid battery for starting”. Say. However, in the case of a secondary battery mounted on a vehicle, it is difficult to execute the charging method as described above. For example, based on the methods shown in Patent Documents 1 to 3, the fully charged state It is done to ask for.

JP 2002-345162 A JP 2010-284038 A JP 2011-163789 A

  However, in the techniques disclosed in Patent Documents 1 and 3 and the like, it is determined that the battery is fully charged when the charging current of the secondary battery is equal to or lower than a predetermined threshold. However, in an actual vehicle, for example, as shown in FIG. In addition, since the user may get off in the operation time A, B before reaching the operation time C detected as full charge when the charging current becomes less than the threshold, until the full charge state is detected. It takes time, and in some cases, the fully charged state cannot be detected, so that there is a problem that the charging rate cannot be detected accurately.

  Further, the charging rate (SOC) in the secondary battery has a correlation with the voltage between the terminals of the secondary battery as shown by a solid line in FIG. 10, and depends on the internal state of the secondary battery, environmental conditions, etc. As shown by a broken line or an alternate long and short dash line in FIG. For example, in a liquid type lead-acid battery, stratification occurs in which concentrated sulfuric acid accumulates under a battery case during charging due to a difference in specific gravity between water and sulfuric acid, thereby forming a concentration gradient of sulfuric acid. Depending on the degree of stratification, the voltage between terminals and the charge acceptability change. Further, the inter-terminal voltage varies depending on the state quantity such as the capacity, liquid amount, weight, volume, etc. of the secondary battery, the environmental temperature around the secondary battery, and the like. During the operation of the secondary battery, one or a combination of these factors greatly affects the voltage between terminals. For this reason, for example, in the techniques disclosed in Patent Documents 1 and 2 and the like, the full charge state cannot be accurately detected due to the influence of the above-described fluctuation factors, and therefore the charge rate cannot be accurately detected. There is a problem.

  An object of the present invention is to provide a secondary battery detection device and a secondary battery state detection method capable of accurately detecting the charging rate of the secondary battery regardless of the state of the secondary battery or the usage state of the user. It is said.

In order to solve the above-described problems, the present invention provides a secondary battery state detection device for detecting a state of a secondary battery mounted on a vehicle, and measuring means for measuring the voltage, current, and temperature of the secondary battery. Discharge means for discharging the secondary battery; learning means for learning parameters of an electrical equivalent circuit of the secondary battery based on voltage and current values during discharge by the discharge means; and the secondary battery By estimation means for estimating a variation-induced state quantity that affects the estimation of the charging rate of the battery, the voltage, current, and temperature values of the secondary battery measured by the measurement means, and learning by the learning means Calculating means for calculating a charging rate of the secondary battery based on the obtained parameters of the equivalent circuit of the secondary battery and the variation-induced state quantity estimated by the estimating means; an open circuit voltage and a charge Correction means for correcting the seeking means based on the charging rate calculated by the calculating means, and the open circuit voltage of the secondary battery; It is characterized by having.
According to such a configuration, it becomes possible to accurately detect the charging rate of the secondary battery regardless of the state of the secondary battery or the usage state of the user.

Further, according to the present invention, the calculation means includes a value of the voltage, current, and temperature of the secondary battery measured before the vehicle stops, the fluctuation-induced state quantity estimated before the stop, The charging rate of the secondary battery is calculated based on the parameter of the equivalent circuit obtained therein.
According to such a configuration, it is possible to accurately detect the charging rate of the secondary battery regardless of the state of the secondary battery and without necessarily being in a fully charged state.

According to the present invention, the correction means executes a correction process when the current value of the secondary battery measured before the vehicle stops is smaller than the current value at the time of the previous correction. It is characterized by that.
According to such a configuration, the charging rate can be obtained more accurately by performing correction at a more accurate timing.

Further, the present invention is characterized in that the correction means executes a correction process when the current value of the secondary battery measured before the vehicle stops is smaller than 10A.
According to such a configuration, the charging rate can be obtained more accurately by performing correction at a timing at which the charging rate is high and more accurate.

Further, the present invention is characterized in that the learning means has an internal resistance as an equivalent circuit parameter, and executes a learning process based on internal resistance = (charging voltage−open circuit voltage) / charging current.
According to such a configuration, the charging rate can be obtained more accurately by using simple parameters.

Further, according to the present invention, the discharging means discharges the secondary battery at a predetermined frequency and current value, and the learning means has solution resistance, reaction resistance, and electric double layer capacity as equivalent circuit parameters. In addition, the equivalent circuit parameter learning process is executed on the basis of the discharge at a predetermined frequency and current value by the discharge means.
According to such a configuration, the charging rate can be obtained more accurately by using a plurality of parameters.

Further, the present invention is characterized in that the variation-induced state quantity includes at least one of a temperature, a stratification state, a polarization state, a deterioration state, a battery capacity, and a battery size of the secondary battery.
According to such a configuration, the charging rate can be accurately obtained regardless of the state of the secondary battery.

In addition, the present invention is characterized in that the state of deterioration of the secondary battery is obtained based on changes over time in liquid resistance , reaction resistance, and electric double layer capacity.
According to such a configuration, the charging rate can be accurately obtained regardless of the temporal change by accurately obtaining the temporal change of the secondary battery.

The present invention also provides a secondary battery state detection method for detecting a state of a secondary battery mounted on a vehicle, a measuring step for measuring the voltage, current, and temperature of the secondary battery, and the secondary battery. A discharge step of discharging the secondary battery, a learning step of learning parameters of an electrical equivalent circuit of the secondary battery based on values of voltage and current at the time of discharge in the discharge step, and estimation of a charging rate of the secondary battery An estimation step for estimating a variation-induced state quantity that affects the voltage, the voltage, current, and temperature values of the secondary battery measured in the measurement step, and the secondary obtained by learning in the learning step A calculation step for calculating a charging rate of the secondary battery based on a parameter of an equivalent circuit of the battery and the variation-induced state quantity estimated in the estimation step. A obtaining step for obtaining a charging rate from a relationship between the open circuit voltage and the charging rate; the obtaining step based on the charging rate calculated by the calculating step; and the open circuit voltage of the secondary battery. And a correction step for correcting.
According to such a method, it becomes possible to accurately detect the charging rate of the secondary battery regardless of the state of the secondary battery or the usage state of the user.

  According to the present invention, it is possible to provide a secondary battery detection device and a secondary battery state detection method capable of accurately detecting the charging rate of the secondary battery regardless of the state of the secondary battery or the usage state of the user. Is possible.

It is a figure which shows the structural example of the secondary battery state detection apparatus which concerns on embodiment of this invention. It is a block diagram which shows the detailed structural example of the control part of FIG. It is a figure which shows an example of the equivalent circuit of a secondary battery. It is a figure which shows the time change of the voltage and electric current of a secondary battery. It is a figure which shows the relationship between time and SOC. It is a figure which shows an example of the process performed in embodiment shown in FIG. 7 is a flowchart for explaining details of a process in step S22 shown in FIG. 6. 7 is a flowchart for explaining details of a process in step S23 shown in FIG. 6. It is a figure which shows the relationship between driving | running time and a charging current. It is a figure which shows the relationship between an open circuit voltage and a charging rate.

  Next, an embodiment of the present invention will be described.

(A) Description of Configuration of First Embodiment FIG. 1 is a diagram showing a power supply system of a vehicle having a secondary battery state detection device according to the first embodiment of the present invention. In this figure, the secondary battery state detection device 1 includes a control unit 10, a voltage sensor 11, a current sensor 12, a temperature sensor 13, and a discharge circuit 15 as main components, and detects the state of the secondary battery 14. To do. Here, the control unit 10 refers to outputs from the voltage sensor 11, the current sensor 12, and the temperature sensor 13 to detect the state of the secondary battery 14. The voltage sensor 11 detects the terminal voltage of the secondary battery 14 and notifies the control unit 10 of it. The current sensor 12 detects the current flowing through the secondary battery 14 and notifies the control unit 10 of the current. The temperature sensor 13 detects the secondary battery 14 itself or the surrounding environmental temperature, and notifies the control unit 10 of it. The discharge circuit 15 is configured by, for example, a semiconductor switch and a resistance element connected in series, and the secondary battery 14 is intermittently discharged when the control unit 10 performs on / off control of the semiconductor switch.

  The secondary battery 14 is composed of, for example, a lead storage battery, a nickel cadmium battery, a nickel hydrogen battery, or a lithium ion battery, and is charged by the alternator 16 to drive the starter motor 18 to start the engine and load 19 To supply power. The alternator 16 is driven by the engine 17 to generate AC power, convert it into DC power by a rectifier circuit, and charge the secondary battery 14.

  The engine 17 is composed of, for example, a reciprocating engine such as a gasoline engine and a diesel engine, a rotary engine, or the like, and is started by a starter motor 18 to drive driving wheels through a transmission to provide propulsive force to the vehicle. Drive to generate power. The starter motor 18 is constituted by, for example, a DC motor, generates a rotational force by the electric power supplied from the secondary battery 14, and starts the engine 17. The load 19 is configured by, for example, an electric steering motor, a defogger, an ignition coil, a car audio, a car navigation, and the like, and operates with electric power from the secondary battery 14.

  FIG. 2 is a diagram illustrating a detailed configuration example of the control unit 10 illustrated in FIG. 1. As shown in this figure, the control unit 10 includes a CPU (Central Processing Unit) 10a, a ROM (Read Only Memory) 10b, a RAM (Random Access Memory) 10c, a communication unit 10d, and an I / F (Interface) 10e. ing. Here, the CPU 10a controls each unit based on the program 10ba stored in the ROM 10b. The ROM 10b is configured by a semiconductor memory or the like, and stores a program 10ba or the like. The RAM 10c is configured by a semiconductor memory or the like, and stores data generated when the program ba is executed, and a parameter 10ca such as a table or a mathematical expression described later. The communication unit 10d communicates with an ECU (Electronic Control Unit) that is a host device and notifies the host device of the detected information. The I / F 10e converts the signal supplied from the voltage sensor 11, the current sensor 12, and the temperature sensor 13 into a digital signal and takes it in, and supplies a driving current to the discharge circuit 15 to control it.

(B) Description of Operation of Embodiment Next, the operation of the embodiment of the present invention will be described with reference to the drawings. In the embodiment of the present invention, while the vehicle is stopped, the control unit 10 controls the discharge circuit 15 to discharge the secondary battery 14 at a predetermined frequency and a predetermined current, and the voltage value and current at that time are discharged. The value is detected by the voltage sensor 11 and the current sensor 12, and a learning process is performed on the parameters of the electrical equivalent circuit of the secondary battery 14 based on the detected voltage value and current value and the voltage value and current value before discharging. To do. Here, the stop means a state in which the engine 17 is stopped and only a so-called dark current flows in the load 19.

  FIG. 3 is a diagram illustrating an example of an electrical equivalent circuit of the secondary battery 14. In this example, the equivalent circuit includes a reaction resistor Rct1 and an electric double layer capacitance C1 connected in parallel to a rhom that is a conductive resistance and a liquid resistance, and a reaction resistor Rct2 and an electric double layer capacitance C2 connected in parallel. They are connected in series. The CPU 10a of the control unit 10 performs learning processing on such parameters (element values) of the equivalent circuit using an algorithm such as a Kalman filter or a support vector machine. The CPU 10a stores the parameter of the equivalent circuit obtained by the learning process in the RAM 10c as the parameter 10ca.

  Note that the equivalent circuit shown in FIG. 3 is an example, and there may be one reaction resistor and one electric double layer capacitance connected in parallel, or three or more reaction resistors and electric double layer capacitances. May be. Moreover, it is good also as a structure only of resistance, without having an electric double layer capacity | capacitance.

  Next, when the engine 17 is started and the vehicle is in a driving state, the CPU 10a of the control unit 10 measures the voltage value V and the current value I of the secondary battery 14 with a predetermined cycle by the voltage sensor 11 and the current sensor 12. These measured values are stored in the RAM 10c as the parameter 10ca.

  Further, the CPU 10a acquires the variation-induced state quantity of the secondary battery 14 at a predetermined cycle, and stores it in the RAM 10c as the parameter 10ca. Here, the fluctuation-induced state quantity refers to a state quantity of a factor (cause) that causes the secondary battery 14 to deviate (fluctuate) from the reference state. As this variation-induced state quantity, for example, there is a temperature T. FIG. 4 is a diagram illustrating an example of temporal changes in voltage and current during the charging process of the secondary battery 14. As shown in FIG. 4, when the temperature of the secondary battery 14 is lower than the reference state, the terminal voltage and the charging current of the secondary battery 14 are out of the reference state indicated by the solid line, as indicated by the broken line. . More specifically, when charging the secondary battery 14, the alternator 16 performs charging with a constant current when the charging rate is low. In FIG. 4, the solid line current graph shown below is constant regardless of the passage of time until time T1, and the solid line voltage graph shown above increases with the passage of time. And if a voltage becomes larger than a predetermined voltage threshold value (a dashed-dotted line), it will transfer to constant voltage charge from constant current charge. As a result, after time T1, the voltage becomes constant and the current decreases as the charging progresses. And when an electric current becomes smaller than a predetermined electric current threshold value (a dashed-dotted line), it determines with a full charge state. When the temperature of the secondary battery 14 is low, the voltage exceeds the voltage threshold at time T2 (<T1), as indicated by a broken line. Further, since the current becomes smaller than the current threshold at a timing earlier than the reference state, it is erroneously determined that the battery is fully charged.

  As described above, as the variation-induced state quantity, for example, temperature T can be cited as an example, but in addition to this, for example, stratification St, polarization Pl, degradation state Dt, battery capacity Cp, and The battery size Sz can be used as the variation-induced state quantity. The stratified St refers to the state of the layer formed by the ion concentration of the electrolyte solution of the secondary battery 14, and the polarization Pl refers to the state where the electrode potential deviates from the static potential due to, for example, charging and discharging, The deterioration state Dt refers to the deterioration state of the secondary battery 14 (for example, SOH (State of Health)), and the battery capacity Cp refers to the capacity of the secondary battery 14 that can be charged and discharged at that time. The size Sz refers to the chargeable / dischargeable capacity in the initial stage of the secondary battery 14. The battery size Sz is a constant value associated with the passage of time, but other values are values that vary with the passage of time. In the following description, the temperature T, the stratification St, and the polarization Pl are described as examples of the variation-causing state quantity. However, the deterioration state Dt, the battery capacity Cp, and the battery size Sz are used. May be.

  When the vehicle is stopped, the CPU 10a detects the voltage value V and current value I of the secondary battery 14 measured immediately before the stop, and the temperature T, the stratification St, And polarization Pl is acquired from RAM10c.

  Next, when the CPU 10a has not executed correction processing for the OCV-SOC correlation equation (described later) before (this is the first time), or the current value I acquired this time and the previous stop time When the current value I acquired this time is smaller than the current value I acquired last time, the OCV-SOC correlation equation correction process is executed.

As a correction process of the OCV-SOC correlation equation, first, the CPU 10a performs stratification as a charge voltage measured immediately before stopping, an open circuit voltage measured during stopping, and a variation-induced state quantity acquired immediately before stopping. ΔV is calculated by applying St and St1 and polarization Pl to the following equation (1), and ΔV, current value I, Rohm, Rct1, Rct2, and offset value Y0 measured immediately before stopping are expressed by Substituting into (2), the SOC value is calculated. In the equation (1), St represents a voltage due to the stratified St, and Pl represents a voltage due to the polarization Pl. Moreover, A1 of Formula (2) shows a predetermined constant. Further, since the values of the stratified St and the polarization Pl change under the influence of the temperature, it is desirable to correct the detected temperature T. Furthermore, although the equation (2) is a first-order exponential function, it may be a higher-order exponential function or a logarithmic function.

ΔV = charge voltage−open circuit voltage + St + Pl (1)

SOC = A1 × exp (ΔV, I, Rohm, Rct1, Rct2) + Y0 (2)

  Based on the voltage, current, and temperature values of the secondary battery measured over time before the vehicle stopped, the variation-induced state quantity estimated before the vehicle stopped, and the equivalent circuit parameters obtained during the stop SOC is obtained from the equations (1) and (2). FIG. 5 shows an example in which the obtained SOC is plotted with respect to the time when the voltage, current, and temperature values of the secondary battery are measured. By using the relations of the equations (1) and (2), it is possible to estimate the SOC at an arbitrary time point as shown in FIG. Therefore, the charge rate of the secondary battery can be estimated from the acquired value immediately before the stop regardless of the state of the secondary battery or the use state of the user.

  Next, the CPU 10a obtains an open circuit voltage OCV (Open Circuit Voltage) of the secondary battery 14. Specifically, the voltage of the secondary battery 14 is measured when a certain time or more has elapsed since the engine 17 was stopped, or the voltage change of the secondary battery 14 after the engine 17 was stopped is constant. A voltage after a lapse of time or more is predicted, and this is defined as OCV.

  Subsequently, the CPU 10a obtains the SOC by applying the OCV to the OCV-SOC correlation equation, compares the obtained SOC with the SOC obtained by the above-described equations (1) and (2), and these match. In this case, it is determined that the OCV-SOC correlation formula is correct, and in other cases, the OCV-SOC correlation formula is corrected. As a correction method, for example, the OCV-SOC correlation equation is expressed by a linear function (for example, SOC = a · OCV + b). By correcting the value of b, which is an intercept of this linear function, the OCV-SOC correlation formula is corrected. The SOC obtained by applying the OCV to the SOC correlation equation is matched with the SOC obtained by the equations (1) and (2). Since a and b have temperature dependence, it is desirable to correct these a and b depending on the temperature.

  As described above, when the OCV-SOC correlation formula is corrected, the SOC can be accurately obtained from the OCV thereafter based on the corrected OCV-SOC correlation formula.

  The OCV-SOC correlation equation correction process is executed when the current value measured immediately before the engine 17 is stopped is smaller than the previous measurement value. Here, a small current value indicates a large SOC, and a larger SOC can correct the OCV-SOC correlation equation more accurately. For this reason, when the current value is smaller than the previous time, the OCV-SOC correlation equation can be made more accurate by correcting the OCV-SOC correlation equation. However, when the current value continues to be larger than the previous value, the OCV-SOC correlation equation is not corrected. For example, a predetermined period (for example, three months) has elapsed since the correction processing was performed. In such a case, the OCV-SOC correlation equation can be made to correspond to a change with time by executing the correction process unconditionally.

(C) Description of Detailed Operation of Embodiment Next, the detailed operation of the embodiment will be described with reference to FIGS. FIG. 6 is a flowchart for explaining details of processing executed in the embodiment shown in FIG. When the processing of this flowchart is started, the following steps are executed.

  In step S10, for example, the CPU 10a refers to the current value or voltage value of the secondary battery 14, determines whether or not the vehicle is stopped, and determines that the vehicle is stopped (step S10: Yes). The process proceeds to step S11, and otherwise (step S10: No), the process proceeds to step S15.

  In step S11, the CPU 10a determines whether or not a predetermined condition indicating that the state of the secondary battery 14 is stable is satisfied, and determines that the predetermined condition is satisfied (step S11: Yes). ), The process proceeds to step S12, and otherwise (step S11: No), the process proceeds to step S14. More specifically, for example, the current flowing from the secondary battery 14 to the load 19 is equal to or lower than a predetermined threshold, the voltage of the secondary battery 14 is equal to or lower than the predetermined threshold, and communication by the communication unit 10d is performed. If not, the process proceeds to step S12 assuming that a predetermined condition is satisfied.

  In step S12, the CPU 10a performs a learning process for each parameter of the equivalent circuit of the secondary battery 14 shown in FIG. Specifically, the CPU 10a controls the discharge circuit 15 to discharge the secondary battery 14 at a predetermined frequency and a predetermined current. Then, the voltage value and current value at that time are acquired from the voltage sensor 11 and the current sensor 12, and a learning process is performed on the parameters of the electrical equivalent circuit of the secondary battery 14 based on the voltage value and current value before discharging. . As the learning process, for example, an algorithm such as a Kalman filter or a support vector machine can be used.

  In step S13, the CPU 10a stores the parameter of the equivalent circuit obtained by the learning process in step S12 in the RAM 10c as the parameter 10ca.

  In step S14, the CPU 10a determines whether or not the vehicle is in operation. If it is determined that the vehicle is in operation (step S14: Yes), the process proceeds to step S15. Otherwise, the process returns to step S11. The same processing as described above is repeated. The determination as to whether or not the vehicle is in operation can be made by referring to the current value or voltage value of the secondary battery 14, for example.

  In step S <b> 15, the CPU 10 a acquires the variation-caused state quantity. More specifically, the CPU 10a acquires the temperature T, the stratification St, the polarization Pl, the deterioration state Dt, the battery capacity Cp, and the battery size Sz as variation-induced state quantities. Here, the temperature T is acquired from the temperature sensor 13. Further, since the battery size Sz is a fixed value, a value stored in advance is acquired from, for example, the RAM 10c. The stratified St, the polarization Pl, the deterioration state Dt, and the battery capacity Cp can be obtained by referring to, for example, an integrated value of the current flowing through the secondary battery 14 and an internal resistance at the time of charge / discharge. In particular, the deterioration state Dt of the secondary battery 14 can be obtained based on changes over time in the conductive resistance / liquid resistance, reaction resistance, and electric double layer capacity. Further, the deterioration state Dt, the battery capacity Cp, and the battery size Sz are not used in the expressions (1) and (2), but these may be included in the expressions (1) and (2).

  In step S <b> 16, the CPU 10 a acquires the voltage value and current value of the secondary battery 14 at that time from the voltage sensor 11 and the current sensor 12.

  In step S17, the CPU 10a stores the variation-induced state quantity acquired in step S15 and the voltage value and current value acquired in step S16 as parameters 10ca in the RAM 10c.

  In step S18, the CPU 10a determines whether or not the vehicle is stopped. If it is determined that the vehicle is stopped (step S18: Yes), the process proceeds to step S19, and otherwise (step S18: No). Returns to step S15 and repeats the same process as described above. Whether the vehicle is stopped can be determined by referring to the current value or voltage value of the secondary battery 14 as described above.

  In step S19, the CPU 10a determines whether or not this time is the first process, and if it is determined that the process is the first process (step S19: Yes), the process proceeds to step S22, and otherwise (step S19: No). ) Proceeds to step S20. More specifically, for example, in the assembly line, when it is the first process after the secondary battery 14 is mounted, or when the user replaces the secondary battery 14 after the vehicle is delivered and is the first process. Determines Yes and proceeds to step S22.

  In step S20, the CPU 10a compares the current value acquired in step S16 with the current value acquired in step S16 and the current value acquired in step S16 in the previous process. If the current value is smaller than the previous current value ( In step S20: Yes, the process proceeds to step S22. In other cases (step S20: No), the process proceeds to step S21. Here, the reason for comparing the current value is that when the current value (value of the charging current) is small, it indicates that the charging rate of the secondary battery 14 is high, and when the charging rate is high, with higher accuracy, The OCV-SOC correlation equation can be corrected. For this reason, in this embodiment, when the current value is compared and the current value is smaller than the previous time, the SOC correction / calculation process in step S22 described later is executed.

  In step S21, the CPU 10a determines whether or not a predetermined period (for example, three months) has elapsed since the last execution of the SOC correction / calculation process, and determines that it has elapsed (step S21: Yes). The process proceeds to step S22, and otherwise the process proceeds to 23 (step S21: No). Here, when a predetermined period has elapsed since the last time the SOC correction / calculation process was executed, the SOC correction / calculation process is executed when the state of the secondary battery 14 changes after a certain period of time has elapsed. Therefore, in such a case, even if the condition of step S20 is not satisfied, the process of step S22 is executed.

  In step S22, the CPU 10a executes SOC correction / calculation processing. Details of this processing will be described later with reference to FIG.

  In step S23, the CPU 10a executes an SOC calculation process. Details of this processing will be described later with reference to FIG.

  According to the above process, the parameters of the equivalent circuit of the secondary battery 14 are learned and stored in the RAM 10c while the vehicle is stopped, and the voltage value and current value of the secondary battery 14 are acquired when the vehicle is in operation. At the same time, the variation-induced state quantity is acquired and stored in the RAM 10c. Then, when the vehicle is stopped, the SOC correction / calculation process is performed when the process is the first process, the current value is smaller than the previous current value, or a predetermined period has elapsed since the previous process. Execute.

  Next, details of the process shown in step S22 of FIG. 6 will be described with reference to FIG. When the process shown in FIG. 7 is started, the following steps are executed.

  In step S30, the CPU 10a acquires the parameter of the equivalent circuit stored in step S13 of FIG. 6 from the RAM 10c.

  In step S31, the CPU 10a acquires, from the RAM 10c, the one stored in the change-induced state quantity stored in step S17 in FIG. 6 before the vehicle stops (for example, immediately before the stop). The reason why the variation-induced state quantity stored before the vehicle stops is to use the latest fluctuation-induced state quantity. Of course, for the state-of-change state quantity with little change over time, information before the stop may be used instead of immediately before the stop.

  In step S32, the CPU 10a acquires, from the RAM 10c, the voltage value and current value stored in step S17 of FIG. 6 that are stored before the vehicle stops (for example, immediately before the stop). The reason why the voltage value and current value stored before the vehicle stops is to use the latest voltage value and current value.

  In step S33, the CPU 10a applies the obtained equivalent circuit parameter, fluctuation-induced state quantity, and voltage / current values to the above-described equations (1) and (2), thereby recharging the secondary battery 14 at that time. The SOC value is calculated. Expressions (1) and (2) are examples, and other expressions may be used. Alternatively, for example, a table may be used instead of the formula.

  In step S34, the CPU 10a acquires the open circuit voltage OCV. As a method for obtaining the open circuit voltage OCV, for example, when a predetermined time (for example, several hours) has elapsed since the vehicle stopped and the current flowing through the load 19 is smaller than a predetermined threshold value. In addition, the open circuit voltage OCV can be obtained by measuring the voltage of the secondary battery 14. Or you may make it estimate the open circuit voltage which is a stable voltage from the time-dependent change of the voltage of the secondary battery 14. FIG.

  In step S35, the CPU 10a executes processing for correcting the OCV-SOC correlation equation. More specifically, the CPU 10a obtains the SOC by applying the OCV acquired in step S34 to the OCV-SOC correlation equation, and obtains the obtained SOC and the SOC obtained from the above-described equations (1) and (2). If these values match, it is determined that the OCV-SOC correlation formula is correct. In other cases, the OCV-SOC correlation formula is corrected. As a correction method, for example, the OCV-SOC correlation equation is expressed by a linear function (for example, SOC = a · OCV + b). By correcting the value of b, which is an intercept of this linear function, the OCV-SOC correlation formula is corrected. The SOC obtained by applying the OCV to the SOC correlation equation is matched with the SOC obtained by the equations (1) and (2).

  In step S36, CPU10a calculates | requires SOC which is a charging rate by applying the open circuit voltage OCV calculated | required by step S34 with respect to OCV-SOC correlation type | formula.

  According to the above processing, the charge rate SOC is obtained by applying the equivalent circuit parameter, the state amount due to fluctuation before stopping, and the voltage value / current value before stopping to the equations (1) and (2). By comparing the SOC obtained from (1) and (2) with the SOC obtained from the OCV-SOC correlation equation, the OCV-SOC correlation equation can be corrected if they do not match.

  Next, the details of the process shown in step S23 of FIG. 6 will be described with reference to FIG. When the process shown in FIG. 8 is started, the following steps are executed.

  In step S50, the CPU 10a calculates the integrated SOC. More specifically, the integrated SOC is obtained by integrating the currents input to and output from the secondary battery 14 with the SOC at a certain time as a reference.

  In step S51, the CPU 10a acquires the open circuit voltage OCV. The method for obtaining the open circuit voltage OCV is the same as that in step S34 in FIG.

  In step S52, the CPU 10a applies the open circuit voltage OCV obtained in step S51 to the OCV-SOC correlation equation that has been subjected to the correction process in step S35 of FIG. 7 to obtain the charging rate SOC. Note that the SOC obtained in step S50 and the SOC obtained in step S52 are compared, and if these are more than a predetermined threshold, the process of step S35 in FIG. 7 may be executed.

  According to the above processing, the integrated SOC can be obtained and the SOC can be calculated using the OCV-SOC correlation equation that has been subjected to the correction processing in step S35 of FIG.

  As described above, according to the embodiment of the present invention, the SOC is calculated based on the above-described equations (1) and (2), and the OCV-SOC correlation equation is corrected based on the calculated SOC. As a result, the SOC can be accurately obtained even when the secondary battery 14 is not fully charged. Thus, by not waiting for a fully charged state, unnecessary charging can be reduced and fuel consumption can be improved.

  In the present embodiment, since the SOC is obtained based on the variation-induced state quantity and the OCV-SOC correlation equation is corrected based on the SOC, the SOC is determined regardless of the state or usage relationship of the secondary battery 14. Can be obtained with high accuracy. Further, a deterioration factor of the secondary battery 14 and a factor that varies depending on the type of the secondary battery 14 are acquired as a variation-caused state quantity, and the SOC is obtained based on the obtained fluctuation-caused state quantity. Even when the battery is replaced (when the battery is replaced with the same type of secondary battery 14 or when the battery is replaced with a different type of secondary battery 14), the SOC can be obtained with high accuracy.

(C) Description of Modified Embodiment It goes without saying that the above embodiment is merely an example, and the present invention is not limited to the case described above. For example, in each of the above embodiments, the temperature, stratification, polarization, deterioration state, battery capacity, and battery size are used as the variation-causing state quantities, but not all of these are used. A part may be used. In addition, it has been experimentally found that the influence in the order of temperature, stratification, and polarization is large, so that these may be used preferentially or a coefficient corresponding to the magnitude of the influence may be used. Good.

  In the above embodiment, the above-described formulas (1) and (2) are examples, and other formulas may be used. Alternatively, a table may be used instead of a mathematical expression.

  In the above embodiment, the values immediately before the stop are used as the variation-causing state quantity, the voltage value, and the current value, but values that are several minutes to several tens of minutes before are used instead of the previous values. You may do it. Moreover, you may make it change the timing to acquire according to driving | running time. For example, when operating for a long time, for example, the temperature stabilizes when operating to some extent, so the value after stabilization can be obtained, and when operating for a short time, it is stopped before stabilizing. Therefore, it is desirable to acquire the value immediately before stopping. Further, the acquisition timing may be set according to the type of the variation-induced state quantity. For example, the voltage value and the current value that change drastically are acquired immediately before the stop, and the deterioration state changes gradually, so that it can be acquired periodically (for example, every week). Instead of using a value obtained by one measurement, an average value of values obtained by a plurality of measurements may be obtained.

  In the above embodiment, as the equivalent circuit of the secondary battery 14, the equivalent circuit shown in FIG. 3 is used. However, other equivalent circuits may be used. For example, the number of reaction resistors and electric double layer capacitors connected in parallel may be one or three or more. Further, an equivalent circuit having only a resistor having no electric double capacitance may be used. In this case, the learning process can be executed by internal resistance = (charging voltage−open circuit voltage + St + P1) / charging current.

  In the above embodiment, the above-described linear expression is used as the OCV-SOC correlation expression. However, an expression other than the primary expression may be used, or a table may be used instead of the expression.

  In the process of FIG. 6, when the current value at this time is smaller than the previous current value at step S20, the process at step S22 is always executed. For example, the elapsed time from the previous process If is smaller than the predetermined threshold value, the process may proceed to step S20 without executing the process of step S22. Further, instead of making a determination by comparing the current value of the previous time and the current value, for example, when the current value of the current time is smaller than a predetermined threshold value, the process of step S22 may be executed. As the threshold value, for example, 10A can be used.

DESCRIPTION OF SYMBOLS 1 Secondary battery state detection apparatus 10 Control part (Learning means, estimation means, calculation means, seeking means, correction means)
10a CPU
10b ROM
10c RAM
10d Display unit 10e I / F
11 Voltage sensor (measuring means)
12 Current sensor (measuring means)
13 Temperature sensor (measuring means)
14 Secondary battery 15 Discharge circuit (discharge means)
16 Alternator 17 Engine 18 Starter motor 19 Load

Claims (9)

In a secondary battery state detection device that detects the state of a secondary battery mounted on a vehicle,
Measuring means for measuring the voltage, current, and temperature of the secondary battery;
Discharging means for discharging the secondary battery;
Learning means for learning parameters of an electrical equivalent circuit of the secondary battery based on voltage and current values at the time of discharging by the discharging means;
Estimating means for estimating a variation-induced state quantity that affects the estimation of the charging rate of the secondary battery;
The voltage, current and temperature values of the secondary battery measured by the measuring means, the parameters of the equivalent circuit of the secondary battery obtained by learning by the learning means, and estimated by the estimating means Calculating means for calculating a charging rate of the secondary battery based on the variation-induced state quantity;
Obtaining means for obtaining a charging rate from the relationship between the open circuit voltage and the charging rate;
Correction means for correcting the obtaining means based on the charging rate calculated by the calculating means and the open circuit voltage of the secondary battery;
A secondary battery state detection device comprising:   The calculation means includes values of the voltage, current, and temperature of the secondary battery measured before the vehicle stops, the variation-induced state quantity estimated before stopping, and the equivalent obtained during the stop. The secondary battery state detection device according to claim 1, wherein a charge rate of the secondary battery is calculated based on a circuit parameter.   The correction means performs correction processing when the current value of the secondary battery measured before the vehicle stops is smaller than the current value at the time of the previous correction. Item 3. The secondary battery state detection device according to Item 1 or 2.   4. The correction unit according to claim 1, wherein the correction unit performs a correction process when a current value of the secondary battery measured before the vehicle stops is smaller than 10 A. 5. The secondary battery state detection device according to item. The learning means has an internal resistance as an equivalent circuit parameter,
5. The secondary battery state detection device according to claim 1, wherein the learning process is executed based on: internal resistance = (charging voltage−open circuit voltage) / charging current. 6. The discharging means discharges the secondary battery at a predetermined frequency and current value,
The learning means has solution resistance, reaction resistance, and electric double layer capacity as equivalent circuit parameters, and learning processing of the equivalent circuit parameters based on discharge at a predetermined frequency and current value by the discharge means The secondary battery state detection device according to any one of claims 1 to 4, wherein:   The variation amount state quantity includes at least one of a temperature, a stratification state, a polarization state, a deterioration state, a battery capacity, and a battery size of the secondary battery. The secondary battery state detection apparatus of Claim 1. The secondary battery state detection device according to claim 7, wherein the state of deterioration of the secondary battery is obtained based on changes over time in liquid resistance , reaction resistance, and electric double layer capacity. In a secondary battery state detection method for detecting a state of a secondary battery mounted on a vehicle,
A measurement step of measuring the voltage, current, and temperature of the secondary battery;
A discharging step of discharging the secondary battery;
A learning step of learning parameters of an electrical equivalent circuit of the secondary battery based on voltage and current values during discharging in the discharging step;
An estimation step for estimating a variation-induced state quantity that affects the estimation of the charging rate of the secondary battery;
The voltage, current, and temperature values of the secondary battery measured in the measurement step, the parameters of the equivalent circuit of the secondary battery obtained by learning in the learning step, and estimated in the estimation step A calculation step of calculating a charging rate of the secondary battery based on the variation-induced state quantity;
A requesting step for determining a charging rate from a relationship between an open circuit voltage and a charging rate;
A correcting step for correcting the obtaining step based on the charging rate calculated by the calculating step and the open circuit voltage of the secondary battery;
A secondary battery state detection method comprising:

Images