Battery characteristic analysis device, battery characteristic measurement device, and battery analysis system

Abstract

To provide a battery characteristic analyzer capable of measuring battery characteristics with a simple method.SOLUTION: A battery characteristic analyzer 14 acquires a damped vibration data concerning the damped oscillating current of batteries Bj from a damped oscillation circuit 24 that dampens and oscillates the current flowing through the analysis target batteries Bj (j is an integer from 1 to n). The battery characteristic analyzer 14 obtains the impedance real part of the battery Bj based on the damped vibration data or the real part of the impedance and output voltage of the batteries Bj. The battery characteristic analyzer 14 obtains the degree of deterioration of the batteries Bj based on the real part of the impedance of the batteries Bj or the real part of impedance and output voltage.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a battery characteristic analysis device, a battery characteristic measurement device, and a battery analysis system, and more particularly to a device that analyzes battery characteristics based on a damped oscillatory current flowing through a battery. [Background technology]

[0002] Electric vehicles, such as hybrid vehicles and electric vehicles, which run on battery power, are widely used. For electric vehicles, charging devices connected to a power supply network provided by an electric power supplier or the like are installed at service stations, parking lots, etc. The batteries of the electric vehicles are charged by the charging devices.

[0003] Furthermore, battery-powered electric devices such as forklifts and transport vehicles are used in factories, offices, event venues, etc. To use multiple electric devices in various locations within the premises of a factory, office, etc., charging systems have been developed in which charging devices are connected to key points in a locally constructed power supply network.

[0004] Regarding electric vehicles and charging systems, a technology for controlling multiple charging devices connected to a power supply network is known. In this technology, a control device acquires information indicating the state of charge of the battery from each charging device, and the control device controls each charging device according to the state of charge of the battery in each charging device. Patent Document 1 describes a distributed power supply system using this technology. This distributed power supply system includes multiple power conversion units (charging devices) and a control unit (control device) that controls each power conversion unit. A battery is connected to each power conversion unit. The control unit acquires the battery's SOC (State of Charge) from each of the multiple power conversion units, and controls the charging and discharging of each power conversion unit according to the SOC. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Laid-Open No. 2016-116428 [Patent Document 2] Japanese Patent Application Publication No. 2018-179652 Summary of the Invention [Problem to be solved by the invention]

[0006] Generally, battery performance deteriorates with use. Therefore, a system is conceivable in which a charging device measures the degree of battery deterioration, and a control device collects information on the degree of battery deterioration measured by each charging device. For example, as described in Patent Document 2, one method for measuring the degree of battery deterioration is to measure the change in impedance relative to a change in frequency. However, this method requires sweeping the frequency of the signal voltage applied to the battery over a wide range, which can make the measurement difficult.

[0007] The present invention aims to measure the performance of a battery in a simple manner. [Means for solving the problem]

[0008] The present invention acquires damped oscillation data on the damped oscillatory current of a battery to be analyzed from a damped oscillation circuit that causes a current flowing through the battery to oscillate at a damped oscillation, acquires two or more peak values ​​for the magnitude of the time waveform of the damped oscillatory current indicated by the damped oscillation data, and calculates the real part of the impedance of the battery based on the ratio of one of the two peak values ​​to the other of the two or more peak values ​​and a plurality of first constants predetermined from the characteristics of the damped oscillation circuit. Mel and based on the real part of the impedance of the battery, one of the two or more peak values, and a plurality of second constants predetermined from the characteristics of the damped oscillation circuit. The battery It is characterized by determining the output voltage.

[0009] Preferably, the deterioration level of the battery is determined based on the impedance real part, or based on the impedance real part and the output voltage.

[0010] Furthermore, the present invention Related technologiesexecutes, for each of a plurality of batteries, a process of acquiring damped oscillation data on a damped oscillation current of the battery from a damped oscillation circuit that damps oscillation of a current flowing through the battery to be analyzed, calculates an output voltage for each of the plurality of batteries based on a time waveform of the damped oscillation current indicated by the damped oscillation data acquired for each of the plurality of batteries, obtains machine learning data, calculates an output voltage of a battery different from the plurality of batteries, and applies the output voltage of the battery different from the plurality of batteries to a machine learning model constructed using the machine learning data to calculate a degree of deterioration of the battery different from the plurality of batteries. do. Preferably, the machine learning data is obtained by calculating the impedance real part in addition to the output voltage for each of the plurality of batteries based on the damped oscillation current indicated by the damped oscillation data acquired for each of the plurality of batteries, calculating the impedance real part in addition to the output voltage of a battery different from the plurality of batteries, and fitting the impedance real part and output voltage of the battery different from the plurality of batteries to a machine learning model constructed using the machine learning data to determine the degree of deterioration of the battery different from the plurality of batteries. Preferably, the output voltage of each of the plurality of batteries is a voltage that changes based on changing the load current of each of the plurality of batteries, and the output voltage of the battery different from the plurality of batteries is a voltage that changes based on changing the load current of the battery different from the plurality of batteries.

[0011] Preferably, each of the plurality of batteries The output voltage and the output voltages of the plurality of cells different from said cells are relaxation voltages.

[0012] Furthermore, the present invention Related technologiesis a battery characteristic analysis device that acquires damped oscillation data on a damped oscillation current of a battery to be analyzed from a damped oscillation circuit that damps oscillation in a current flowing through the battery, and determines a real part of an impedance of the battery based on the damped oscillation data, or determines the real part of an impedance and an output voltage of the battery. The battery characteristic measurement device, together with the battery characteristic analysis device, constitutes a battery characteristic analysis system, and includes the damped oscillation circuit and a control unit that generates the damped oscillation data, and the control unit extracts values ​​corresponding to the damped oscillation current flowing through the battery at a plurality of different timings, and generates the damped oscillation data based on the values ​​corresponding to the damped oscillation current extracted at the plurality of different timings. do.

[0013] Preferably, the damped oscillation circuit includes a primary inductor, a capacitive element, and a switching element, and the primary inductor, the capacitive element, and the switching element are provided in a path connecting the positive and negative electrodes of the battery, and the switching element conducts in a pulsed manner, causing the current flowing through the battery to undergo damped oscillation, and the control unit generates the damped oscillation data based on the voltage appearing in a secondary inductor coupled to the primary inductor.

[0014] Furthermore, the present invention Related technologies a battery characteristic analysis device that acquires damped oscillation data about a damped oscillatory current of a battery to be analyzed from a damped oscillation circuit that damps oscillation in a current flowing through the battery, and determines a real part of the impedance of the battery based on the damped oscillation data, or determines the real part of the impedance and an output voltage of the battery, and together with the battery characteristic analysis device, constitutes a battery characteristic analysis system, the battery characteristic measurement device comprising the damped oscillation circuit and a control unit that generates the damped oscillation data, wherein the control unit causes the damped oscillatory current to flow through the battery a plurality of times, measures time waveforms of the damped oscillatory current that flows a plurality of times, extracts values ​​corresponding to the damped oscillatory current at different timings for each measurement, and generates circuit analysis information for analyzing the characteristics of the damped oscillation circuit based on the values ​​extracted for each measurement. do.

[0015] Preferably, the damped oscillation circuit includes a primary inductor, a capacitive element, and a switching element, and the primary inductor, the capacitive element, and the switching element are provided in a path connecting the positive and negative electrodes of the battery, and when the switching element conducts in a pulsed manner, the current flowing through the battery undergoes damped oscillation, and the control unit extracts a value corresponding to the damped oscillation current from the voltage appearing in a secondary inductor coupled to the primary inductor.

[0016] Furthermore, the present invention Related technologies is a battery analysis system including a plurality of the battery characteristic measuring devices, wherein the damped oscillation circuit is connected to each of the plurality of batteries connected in series, and each of the damped oscillation circuits includes a resistive element connected in parallel to the capacitive element, and the battery analysis system controls the discharge state of the battery relative to the capacitive element to equalize the states of charge of the plurality of batteries. do. [Effects of the Invention]

[0017] According to the present invention, the performance of a battery can be measured in a simple manner. [Brief explanation of the drawings]

[0018] [Figure 1] FIG. 1 is a diagram illustrating a configuration of a battery analysis system. [Figure 2] FIG. 2 is a diagram showing the configuration of the measuring device together with a control unit. [Figure 3] 3A and 3B are diagrams showing the time waveforms of each signal, a damped oscillation current, and a damped oscillation voltage. [Figure 4] FIG. 2 is a diagram showing each measuring device provided corresponding to each battery together with a control unit. [Figure 5] FIG. 4 is a diagram showing a time waveform of a drive signal. [Figure 6] FIG. 10 is a diagram showing the configuration of a battery characteristics measuring device according to an application embodiment. [Figure 7] FIG. 10 is a diagram showing a state of the battery characteristic measuring device when measuring the resonance frequency of a damped oscillation circuit. [Figure 8]FIG. 10 shows the total extraction signal together with the damped oscillatory voltage. [Figure 9] FIG. 2 is a diagram illustrating the configuration of a battery degradation analyzer. [Figure 10] FIG. 1 is a diagram showing an example of relaxation voltage for a lead battery. [Figure 11] 1 is a graph showing the relationship between degradation parameters measured by a reference measuring device and the measured values ​​of the real part of the impedance of a lead-acid battery measured by a battery analysis system. [Figure 12] FIG. 2 is a diagram illustrating the configuration of a battery degradation analyzer. [Figure 13] FIG. 1 is a diagram showing machine learning data of a lithium-ion battery and a machine learning model of a lithium-ion battery. [Figure 14] 10 is a graph showing the change in the real part of the impedance in relation to the degree of deterioration of the battery capacity. [Figure 15] FIG. 2 is a diagram conceptually illustrating an example of operation timing of the battery analysis system. DETAILED DESCRIPTION OF THE INVENTION

[0019] Each embodiment of the present invention will be described with reference to the drawings. Identical components shown in multiple drawings will be assigned the same reference numerals to simplify their description. Terms indicating directions such as up, down, left, and right in this specification refer to directions in the drawings. These terms do not limit the orientation of each component when it is arranged.

[0020] 1 shows the configuration of a battery analysis system 100 according to an embodiment of the present invention. The battery analysis system 100 includes a battery characteristic measuring device 10, a storage computer 12, and a battery characteristic analyzing device 14. The battery characteristic measuring device 10, the storage computer 12, and the battery characteristic analyzing device 14 may each be configured as separate computers connected via a communication line. The battery analysis system 100 may also be configured as an integrated unit of hardware. Furthermore, two selected from the battery characteristic measuring device 10, the storage computer 12, and the battery characteristic analyzing device 14 may also be configured as an integrated unit of hardware.

[0021] A plurality of n batteries B1 to Bn to be analyzed are connected to a battery characteristic measuring device 10. In this embodiment, the batteries B1 to Bn are connected in series, and both ends of each battery are connected to the battery characteristic measuring device 10. In the battery analysis system 100, the battery characteristic measuring device 10 measures characteristic data required for analyzing the characteristics of each battery for each battery and transmits the data to a storage computer 12. The storage computer 12 stores the characteristic data. A battery characteristic analysis device 14 reads the characteristic data of each battery from the storage computer 12 and analyzes the characteristics of each battery.

[0022] 2 shows the configuration of a measuring device 20, which is a part of the configuration of battery characteristic measuring device 10 that acquires characteristic data of one battery Bj (j is an integer from 1 to n), together with a control unit 22. Measuring device 20 includes a damped oscillation circuit 24 and a drive unit 26. Damped oscillation circuit 24 includes a primary inductor 28, a capacitive element 30, a resistive element 32, and a switching element 34.

[0023] The primary inductor 28 may be formed of a winding. The primary inductor 28 is coupled to a secondary inductor 38 in the drive unit 26, and together with the secondary inductor 38, forms a transformer. The secondary inductor 38 may also be formed of a winding. The capacitive element 30 may be a capacitor, which is a passive element. The capacitive element 30 may also be an active capacitive element such as a varicap.

[0024] One end of the primary inductor 28 is connected to the positive electrode of the battery Bj, and the other end is connected to one end of the capacitive element 30. The other end of the capacitive element 30 is connected to one end of the switching element 34, and the other end of the switching element 34 is connected to the negative electrode of the battery Bj. A resistive element 32 is connected in parallel to the capacitive element 30. A damped oscillation circuit 24 is formed in the path between the positive and negative electrodes of the battery Bj by the primary inductor 28, the capacitive element 30, the resistive element 32, and the switching element 34. The damped oscillation circuit 24 includes a resonant circuit including a resistive component. If the battery Bj to be analyzed is a lead battery, the resonant frequency of the damped oscillation circuit 24 may be 2 kHz to 30 kHz. If the battery Bj to be analyzed is a lithium-ion battery, the resonant frequency of the damped oscillation circuit 24 may be 200 kHz to 30 MHz.

[0025] The drive unit 26 includes a drive amplifier 36, a secondary inductor 38, a detection amplifier 40, and peak hold circuits 42-1 to 42-3. The secondary inductor 38 is coupled to the primary inductor 28. One end of the secondary inductor 38 is grounded. The other end of the secondary inductor 38 is connected to the input terminal of the detection amplifier 40. The output terminal of the detection amplifier 40 is connected to the input terminals of the peak hold circuits 42-1 to 42-3, respectively.

[0026] The control unit 22 outputs a drive signal P0 to the drive amplifier 36, and the drive amplifier 36 outputs the drive signal P0 to the switching element 34. The drive signal P0 rises from low to high, remains high for a predetermined time, and then changes from high to low. When the drive signal P0 is high, the switching element 34 turns on. The switching element 34 conducts in a pulsed manner in accordance with the drive signal P0. Here, "conducting in a pulsed manner" refers to the switching element 34 changing from off to on, maintaining the on state for a predetermined time, and then changing from on to off.

[0027] When the switching element 34 is turned on in a pulsed manner, a pulse voltage based on the output voltage of the battery Bj is applied from the positive electrode of the battery Bj to the damped oscillation circuit 24, which is composed of the primary inductor 28, capacitive element 30, resistive element 32, and switching element 34. As a result, a damped oscillatory current that oscillates at the resonant frequency and damps flows through the damped oscillation circuit 24. The damping of the damped oscillatory current is due to the loss caused by the resistive element 32, the resistance component included in the primary inductor 28, and the like.

[0028] In response to the damped oscillatory current flowing through the primary inductor 28, an induced electromotive force having a damped oscillatory waveform is generated in the secondary inductor 38. Peak hold signals PH1 to PH3 are output from the control unit 22 to the peak hold circuits 42-1 to 42-3, respectively. When or after the drive signal P0 rises and the switching element 34 becomes conductive, the peak hold signals PH1 to PH3 rise in a step-like manner in the order of PH1, PH2, and PH3, and fall after a predetermined time has elapsed. The peak hold circuits 42-1 to 42-3 sequentially extract the value of the induced electromotive force generated in the secondary inductor 38 in response to the peak hold signals PH1 to PH3, and output extraction signals S1 to S3 to the control unit 22, respectively.

[0029] The control unit 22 acquires the battery temperature Tmp from the temperature sensor 50 attached to the battery Bj. The control unit 22 generates characteristic data (damped oscillation data) including information indicating the time waveforms of each of the extraction signals S1 to S3, the battery temperature Tmp, a battery ID (IDentification), and the time (timestamp) at which this information was acquired, and transmits this data to the storage computer 12 (FIG. 1). The characteristic data is damped oscillation data including information about the damped oscillation current. The storage computer 12 stores the characteristic data transmitted from the control unit 22. Note that the characteristic data may include maximum absolute values ​​Pm1 to Pm3 of each of the extraction signals S1 to S3 instead of or in addition to the information indicating the time waveforms of each of the extraction signals S1 to S3.

[0030] 3(a) to 3(h) show the time waveform of the damped oscillatory current Ia and the time waveforms of each signal used in the battery analysis system 100. FIG. 3(a) shows the drive signal P0. FIG. 3(b) shows the damped oscillatory current Ia. The drive signal P0 rises from low to high at time t0, remains high for a time Ton from time t0, and then falls from high to low at time t0+Ton. After time t0, the damped oscillatory current Ia oscillates sinusoidally while attenuating.

[0031] 3(c) shows the peak hold signal PH1 together with the damped oscillation voltage Ea, and FIG. 3(d) shows the extraction signal S1 together with the damped oscillation voltage Ea. Here, the damped oscillation voltage Ea is an induced electromotive force appearing in the secondary inductor 38 according to the damped oscillation current Ia. The damped oscillation voltage Ea has a value according to the damped oscillation current Ia and has a time waveform similar to that of the damped oscillation current Ia. The peak hold signal PH1 rises at time t0 and falls together with the drive signal P0 at time t0+Ton. While the peak hold signal PH1 remains high, the peak hold circuit 42-1 outputs to the control unit 22 an extraction signal S1 indicating the maximum value of the damped oscillation voltage Ea from the present time back to time t0, when the peak hold signal PH1 became high.

[0032] 3(e) and 3(g) show the peak hold signals PH2 and PH3, respectively, together with the damped oscillation voltage Ea, and FIG. 3(f) and 3(h) show the extraction signals S2 and S3, respectively, together with the damped oscillation voltage Ea. The peak hold signals PH2 and PH3 rise at times t2 and t3, respectively, which are times τ2 and τ3 after the rise of the drive signal P0, and fall together with the drive signal P0 at time t1+Ton.

[0033] While the peak hold signal PH2 is maintained high, the peak hold circuit 42-2 outputs an extraction signal S2 indicating the maximum value of the damped oscillation voltage Ea from the present time back to time t2 when the peak hold signal PH2 became high to the control unit 22. While the peak hold signal PH3 is maintained high, the peak hold circuit 42-3 outputs an extraction signal S3 indicating the maximum value of the damped oscillation voltage Ea from the present time back to time t3 when the peak hold signal PH3 became high to the control unit 22.

[0034] In this way, the control unit 22A extracts a value (value of the damped oscillation voltage Ea) corresponding to the damped oscillation current Ia flowing through the battery Bj at three (plural) different timings to obtain extraction signals S1 to S3, and generates characteristic data (damped oscillation data) based on the extraction signals S1 to S3. The extraction signals S1 to S3 are values ​​corresponding to the damped oscillation current Ia extracted at three (plural) different timings.

[0035] 1 reads the above characteristic data from the storage computer 12. The battery characteristic analyzer 14 calculates the output voltage Vb and the impedance real part Rhf of the battery Bj based on the characteristic data through the following process. Here, the impedance real part refers to the real part when the internal impedance of the battery at a certain frequency is expressed as a complex number.

[0036] The battery characteristic analyzer 14 calculates the real part of impedance Rhf according to Equation 1 based on the maximum value Pm3 of the absolute value of the extracted signal S3 and the maximum value Pm2 of the absolute value of the extracted signal S2.

[0037] (Equation 1) Rhf=ln(Pm2 / Pm3)·ar-br

[0038] Here, ln denotes the natural logarithm. The constants ar and br are predetermined based on the characteristics of the damped oscillation circuit 24. Equation 1 is derived from the fact that the time constants when the peaks of the damped oscillation current Ia and the damped oscillation voltage Ea decay over time are determined according to the real part of the impedance of the battery Bj.

[0039] The battery characteristic analyzer 14 obtains the output voltage Vb of the battery Bj according to (Equation 2).

[0040] (Math 2)Vb=(1 / √δ)·k·N·Pm1,δ=exp(-Rhf·tr / (2Lr))

[0041] Here, Pm1 is the maximum absolute value of the extracted signal S1, k is the gain of the detection amplifier 40, N is the turns ratio of the winding constituting the secondary inductor 38 to the winding constituting the primary inductor 28, tr is the time from time t0 until the absolute value of the extracted signal S1 reaches its maximum, and Lr is the self-inductance of the primary inductor.

[0042] The battery characteristic measuring device 10 sequentially acquires characteristic data over time and sequentially transmits the characteristic data to the storage computer 12 over time. The battery characteristic analyzing device 14 sequentially determines the impedance real part Rhf and output voltage Vb of the battery Bj over time based on the characteristic data stored in the storage computer 12. The battery characteristic analyzing device 14 may store the impedance real part Rhf and output voltage Vb of the battery Bj in association with time, or may cause the storage computer 12 to store the impedance real part Rhf and output voltage Vb of the battery Bj in association with time.

[0043] The battery characteristic analyzer 14 may determine the degree of deterioration of the battery Bj based on the impedance real part Rhf and the output voltage Vb, using processing that will be described later.

[0044] In the battery analysis system 100 according to this embodiment, if the output voltage Vb of each battery is stored in the storage computer 12, the control unit 22 of the battery characteristic measuring device 10 may execute a process for equalizing the output voltages Vb of the batteries B1 to Bn. This process controls the discharge state from the battery Bj to the capacitive element 30 for the battery Bj having the largest output voltage Vb among the batteries B1 to Bn, thereby equalizing the charge states of the batteries B1 to Bn. FIG. 4 shows measuring devices 20-1 to 20-n provided corresponding to the batteries B1 to Bn together with the control unit 22. Each of the measuring devices 20-1 to 20-n has a configuration similar to that of the measuring device 20 shown in FIG. 2.

[0045] Figure 5 shows the time waveform of the drive signal P0 output from the control unit 22 to each drive amplifier 36 of the measuring devices 20-1 to 20-n in a first mode of operation in which characteristic data for each of the batteries B1 to Bn is acquired, and in a second mode of operation in which the output voltages Vb for each of the batteries B1 to Bn are equalized.

[0046] In the first mode of operation, control unit 22 sequentially outputs three pulses of drive signal P0 to measuring devices 20-1 to 20-n, i.e., three pulses for acquiring extraction signals S1 to S3. Through the above operation, measuring devices 20-1 to 20-n each acquire characteristic data. Battery characteristic analysis device 14 calculates output voltage Vb of each of batteries B1 to Bn based on the characteristic data.

[0047] 5 shows an example in which the output voltage Vb of battery Bj connected to measuring device 20-j is larger than that of the other batteries. In operation in the second mode, control unit 22 sets drive signal P0, which is output to measuring device 20-j connected to battery Bj with the largest output voltage Vb among batteries B1 to Bn, to high. Control unit 22 also sets drive signal P0, which is output to measuring devices other than measuring device 20-j, to low. As a result, a damped oscillation current flows through battery Bj and damped oscillation circuit 24 of measuring device 20-j, and then battery Bj charges capacitive element 30, causing the output voltage Vb of battery Bj to decrease.

[0048] The first mode operation and the second mode operation are repeated in the battery analysis system 100. This causes the output voltages Vb of the batteries B1 to Bn to converge to the same value, preventing a particular battery from being subjected to a large electrical load.

[0049] 6 shows the configuration of a battery characteristic measuring device 10A according to an applied embodiment of the present invention. In the battery characteristic measuring device 10A, a control unit 22A executes a process of acquiring extraction signals S1 to S3 corresponding to one battery for each of batteries B1 to B3 in a time-division manner.

[0050] Battery characteristic measuring device 10A includes measuring devices 20A-1 to 20A-3 connected to three batteries B1 to B3, respectively. Measuring device 20A-1 is configured by removing peak hold circuits 42-2 and 43-3 from measuring device 20-1 shown in Fig. 2, and instead of grounding the bottom end of secondary inductor 38, connecting it to one end of secondary inductor 38 of measuring device 20A-2.

[0051] Measuring instrument 20A-2 is configured by removing detection amplifier 40 and peak hold circuits 42-1 to 42-3 from measuring instrument 20 shown in FIG. 2, and instead of connecting the upper end of secondary inductor 38 to the lower end of secondary inductor 38 of measuring instrument 20A-1 and grounding the lower end, connecting it to the upper end of secondary inductor 38 of measuring instrument 20A-3. Measuring instrument 20A-3 is configured by removing detection amplifier 40 and peak hold circuits 42-1 to 42-3 from measuring instrument 20 shown in FIG. 2, and connecting the upper end of secondary inductor 38 to the lower end of secondary inductor 38 of measuring instrument 20A-2. In this way, secondary inductors 38 of measuring instruments 20A-1 to 20A-3 are connected in series, the upper end of secondary inductor 38 of measuring instrument 20A-1 is connected to detection amplifier 40, and the lower end of secondary inductor 38 of measuring instrument 20A-3 is grounded.

[0052] Cascaded delay circuits 52-1 and 52-2 are inserted between the driver amplifier 36 and the control unit 22A of the measuring device 20A-3, and a delay circuit 52-1 is inserted between the driver amplifier 36 and the control unit 22A of the measuring device 20A-2.

[0053] Control unit 22A raises and lowers drive signal P0 three times at different time periods. Delay circuit 52-1 delays drive signal P0 by delay time D1 and outputs it to delay circuit 52-2 and drive amplifier 36 of measuring device 20A-2. Delay circuit 52-2 delays drive signal P0 output from delay circuit 52-1 by delay time D2 and outputs it to drive amplifier 36 of measuring device 20A-3. Delay times D1 and D2 are determined so that the time periods during which drive signal P0 input to the drive amplifiers 36 of measuring devices 20A-1 to 20A-3 are high do not overlap.

[0054] The control unit 22A outputs a pulse of a peak hold signal PH1 to the peak hold circuit 42-1 to acquire an extraction signal S1 when the drive signal P0 input to the drive amplifier 36 of the measuring device 20A-1 rises and falls for the first time. As a result, the peak hold circuit 42-1 outputs an extraction signal S1 for the battery B1 to the control unit 22A. The control unit 22A outputs a pulse of a peak hold signal PH2 to the peak hold circuit 42-1 to acquire an extraction signal S2 when the drive signal P0 input to the drive amplifier 36 of the measuring device 20A-1 rises and falls for the second time. As a result, the peak hold circuit 42-1 outputs an extraction signal S2 for the battery B1 to the control unit 22A. The control unit 22A outputs a pulse of a peak hold signal PH3 to the peak hold circuit 42-1 to acquire an extraction signal S3 when the drive signal P0 rises and falls for the third time. As a result, the peak hold circuit 42-1 outputs an extraction signal S3 for the battery B1 to the control unit 22A.

[0055] For measuring device 20A-2, control unit 22A causes peak hold circuit 42-1 to perform the same operation as for measuring device 20A-1, with a delay of delay D1 relative to measuring device 20A-1. As a result, peak hold circuit 42-1 outputs extraction signals S1 to S3 for battery B2 to control unit 22A. For measuring device 20A-3, control unit 22A performs the same operation as for measuring device 20A-1, with a delay of delay D1+D2 relative to measuring device 20A-1. As a result, peak hold circuit 42-1 outputs extraction signals S1 to S3 for battery B3 to control unit 22A.

[0056] The control unit 22A generates characteristic data for each of the batteries B1 to B3 and transmits the characteristic data acquired for each of the batteries B1 to B3 to the storage computer 12. The battery characteristic analysis device 14 determines the impedance real part Rhf and the output voltage Vb for each of the batteries B1 to B3 based on the characteristic data acquired for each of the batteries B1 to B3.

[0057] Here, a configuration for acquiring characteristic data for three batteries B1 to B3 has been described. Battery characteristic measuring device 10A can be modified to acquire characteristic data for two or four or more batteries. In this case, a measuring device similar to measuring device 20A-2 is provided for each battery, and a delay circuit that delays drive signal P0 is provided between the measuring device in the previous stage and the measuring device in the next stage.

[0058] FIG. 7 shows the state of the battery characteristic measuring device 10B when measuring the resonant frequency of the damped oscillation circuit 24 of the measuring device 20B. The measuring device 20B has a configuration similar to that of the measuring device 20A-1 shown in FIG. 6. A reference battery BS is connected to the battery characteristic measuring device 10B instead of the battery Bj. The reference battery BS illustrated in FIG. 7 includes a battery B0, a reference capacitor C0, a reference inductor L0, and a reference resistor R0. One end of the reference inductor L0 is connected to the positive terminal of the battery B0. The reference capacitor C0 and the reference resistor R0 are connected in series. One end of the reference capacitor C0 opposite the reference resistor R0 is connected to the other end of the reference inductor L0, and the terminal of the reference resistor R0 opposite the reference capacitor C0 is connected to the negative terminal of the battery B0. The element constants of the reference capacitor C0, the reference inductor L0, and the reference resistor R0 are known. The element constants of the reference capacitor C0, the reference inductor L0, and the reference resistor R0 may be stored in the storage computer 12, and the control unit 22B or the battery characteristic analyzer 14 may read these element constants.

[0059] The control unit 22B repeatedly outputs pulses of the drive signal P0 at predetermined time intervals to the drive amplifier 36. The control unit 22B repeatedly outputs pulses of the peak hold signal PH to the peak hold circuit 42-1 in synchronization with the drive signal P0.

[0060] The control unit 22B delays the rising edge of the pulse of the peak hold signal PH to be output to the peak hold circuit 42-1 depending on the number of times the pulse of the peak hold signal PH is output. That is, when the control unit 22B outputs the pth pulse of the peak hold signal PH to the peak hold circuit 42-1, the control unit 22B outputs to the peak hold circuit 42-1 a pulse of the peak hold signal PH whose rising edge is delayed by p·ΔT relative to the rising edge of the drive signal P0. The falling edge of the pulse of the peak hold signal PH may be simultaneous with the falling edge of the pulse of the drive signal P0 synchronized therewith. The peak hold circuit 42-1 sequentially outputs the extraction signal S to the control unit 22B in accordance with the pulse of the peak hold signal PH repeatedly output from the control unit 22B.

[0061] According to this processing, as pulses of the drive signal P0 are repeatedly output from the control unit 22B, the switching element 34 is repeatedly turned on in a pulsed manner, and a damped oscillation current Ia repeatedly flows through the damped oscillation circuit 24. The extraction signal S is acquired so that the timing at which the extraction signal S is acquired is delayed by a time ΔT each time a damped oscillation current flows through the damped oscillation circuit 24.

[0062] FIG. 8 shows the total extraction signal ΣS along with the damped oscillation voltage Ea. The total extraction signal ΣS is a series of extraction signals S repeatedly acquired while delaying the rising edge of the pulse of the peak hold signal PH by a time ΔT, and these signals are arranged on a time axis. The total extraction signal ΣS represents a time waveform that holds the peak value of the damped oscillation voltage Ea. The control unit 22B determines the frequency of the damped oscillation voltage Ea based on the total extraction signal ΣS. If the element constants of the reference battery BS and the capacitance of the capacitive element 30 included in the measuring device 20B are known, the control unit 22B may determine the inductance value of the primary inductor 28 based on the total extraction signal ΣS. Alternatively, the battery characteristic analyzer 14 may acquire the total extraction signal ΣS via the storage computer 12 and determine the frequency of the damped oscillation voltage Ea or the inductance value of the primary inductor 28. The values ​​obtained by measuring device 20B may be used as data for analyzing the degree of deterioration of battery Bj when the battery Bj to be analyzed is connected instead of reference battery BS. Furthermore, the inductance value of primary inductor 28 obtained by measuring device 20B may be used as Lr in Equation 2.

[0063] As described above, in the battery characteristic measuring device 10B shown in FIG. 7, the control unit 22B turns on the switching element 34 multiple times, and each time the switching element 34 turns on, an extraction signal S is acquired at a different position on the time axis for the damped oscillation current flowing through the damped oscillation circuit 24. That is, the control unit 22B turns on the switching element 34 multiple times, causing a damped oscillation current to flow through the reference battery BS (battery) multiple times. The control unit 22B measures the time waveforms of the damped oscillation current flowing multiple times and extracts, as the extraction signal S, a value corresponding to the damped oscillation current at a different timing for each measurement. The control unit 22B generates a total extraction signal ΣS based on the extraction signal S extracted for each measurement. The total extraction signal ΣS serves as circuit analysis information for analyzing the characteristics of the damped oscillation circuit 24.

[0064] The process of acquiring the total extracted signal ΣS and determining the frequency of the damped oscillatory current Ia or the inductance value of the primary inductor 28 may be performed by the battery characteristic measuring device 10A shown in Fig. 6. The control unit 22A repeatedly outputs pulses of the drive signal P0 at predetermined time intervals to the drive amplifier 36 of the measuring device 20A-1.

[0065] Delay circuits 52-1 and 52-2 delay the pulse of drive signal P0 so that the pulse of drive signal P0 is output in a time-division manner from control unit 22A to measuring units 20A-1, 20A-2, and 20A-3 in that order. Control unit 22A outputs a pulse of peak hold signal PH corresponding to measuring unit 22A-1 to peak hold circuit 42-1 in synchronization with the pulse of drive signal P0 input to drive amplifier 36 of measuring unit 20A-1. Control unit 22A also outputs a pulse of peak hold signal PH corresponding to measuring unit 22A-2 to peak hold circuit 42-1 in synchronization with the pulse of drive signal P0 input to drive amplifier 36 of measuring unit 20A-2. Control unit 22A also outputs a pulse of peak hold signal PH corresponding to measuring unit 22A-3 to peak hold circuit 42-1 in synchronization with the pulse of drive signal P0 input to drive amplifier 36 of measuring unit 20A-3.

[0066] Control unit 22A delays the rising edge of the pulse of peak hold signal PH output to peak hold circuit 42-1 for each of measuring units 20A-1 to 20A-3, depending on the number of times the pulse of peak hold signal PH has been output. Through this processing, the following operation is performed for each of measuring units 22A-1 to 22A-3. That is, as pulses of drive signal P0 are repeatedly output from control unit 22B, switching element 34 is repeatedly turned on in a pulsed manner, and a damped oscillation current repeatedly flows through damped oscillation circuit 24. Extraction signal S is acquired so that the timing at which extraction signal S is acquired is delayed by time ΔT each time a damped oscillation current flows through damped oscillation circuit 24.

[0067] Here, the process of acquiring the total extracted signal ΣS for each of the three measuring devices 20A-1 to 20A-3 and determining the frequency of the damped oscillatory current or the inductance value of the primary inductor 28 has been described. The number of measuring devices to be processed may be two, or may be four or more. The battery characteristic measuring device may be configured such that a delay circuit that delays the drive signal P0 is provided between the measuring device at the previous stage and the measuring device at the next stage.

[0068] FIG. 9 shows the configuration of a battery degradation analyzer 60 included in the battery characteristic analysis device 14. The battery degradation analyzer 60 is used to determine the degree of degradation of a lead-acid battery. The battery degradation analyzer 60 receives as input the impedance real part Rhf, the battery output voltage Vb, and the battery temperature Tmp, which are sequentially acquired over time. Here, the output voltage Vb is a relaxation voltage that increases over time when the battery changes from a state in which a load current is flowing through it (on state) to a state in which the load current is interrupted (off state). Alternatively, the battery degradation analyzer 60 receives as input the relaxation voltage that decreases over time when the battery changes from an off state to an on state.

[0069] The battery degradation analyzer 60 applies at least one of the impedance real part Rhf, the relaxation voltage of the battery output voltage Vb, and the battery temperature Tmp to a pre-constructed machine learning model to determine the degradation levels SOH_R and SOH_C. SOH_R is defined, for example, as a value indicating the rate (by what percentage) that the impedance real part Rhf has increased relative to a new battery. In this case, the larger the SOH_R, the greater the degradation level of the battery. SOH_C is defined, for example, as a value indicating the rate (by what percentage) that the discharge capacity (mAh) has decreased relative to a new battery. The larger the SOH_C, the greater the degradation level of the battery.

[0070] The machine learning model may be constructed, for example, by obtaining machine learning data for a plurality of batteries with different cumulative values ​​(usage amounts) of charge and discharge charges since the start of use. For example, the battery characteristic analysis device 14 acquires characteristic data for each of the plurality of batteries with different usage amounts. Furthermore, the SOH_R and SOH_C for each of the plurality of batteries with different usage amounts are actually measured by a device or the like separate from the battery analysis system 100. Then, the battery characteristic analysis device 14 associates the characteristic data with the actually measured SOH_R and SOH_C using a machine learning algorithm to obtain machine learning data. The machine learning data is stored in the storage computer 12 and is read from the storage computer 12 into the battery degradation analyzer 60.

[0071] The top row of Figure 10 shows an example of the relaxation voltage for a lead-acid battery. The horizontal axis represents time, and the vertical axis represents the battery's output voltage. Output voltage 62-1 represents the relaxation voltage for a new battery, and output voltage 62-2 represents the relaxation voltage for a degraded battery with non-zero usage. The battery changes from the off state to the on state at time 40 seconds, and its output voltage decreases. Also, the battery changes from the on state to the off state at time 240 seconds, and its output voltage increases.

[0072] The bottom part of Fig. 10 shows the measurement results of the impedance real part of a lead-acid battery measured by the battery analysis system 100 according to an embodiment of the present invention. The horizontal axis shows time, and the vertical axis shows the impedance real part. The impedance real part 64-1 shows the value of a new battery, and the impedance real part 64-2 shows the value of a deteriorated battery with a non-zero usage amount. The bottom part of Fig. 10 shows that the fluctuations in the impedance real part are small even when the output voltage fluctuates as shown in the top part of Fig. 10.

[0073] FIG. 11 shows a graph correlating degradation parameters measured by a general reference measurement device (reference measurement device) with the measured values ​​of the impedance real part of a lead-acid battery measured by the battery analysis system 100 according to this embodiment. The horizontal axis represents the degradation parameters measured by the reference measurement device. The smaller the degradation parameter value in FIG. 11, the greater the degree of degradation. The vertical axis represents the impedance real part measured by the battery analysis system 100. There is a tendency for the impedance real part to be larger as the degradation parameter measured by the reference measurement device is smaller, i.e., the greater the degree of degradation. A machine learning model for lead-acid batteries may utilize this tendency.

[0074] 12 shows the configuration of a battery degradation analyzer 70 configured in the battery characteristic analysis device 14. The battery degradation analyzer 70 is used to determine the degree of degradation of a lithium-ion battery. The battery degradation analyzer 70 receives as input the impedance real part Rhf, the battery output voltage Vb, and the battery temperature Tmp, which are sequentially acquired over time. The output voltage Vb, which is the relaxation voltage, is input to the battery degradation analyzer 70.

[0075] The battery degradation analyzer 70 applies at least one of the impedance real part Rhf, the relaxation voltage of the battery output voltage Vb, and the battery temperature Tmp to a pre-constructed machine learning model to determine the degradation levels SOH_R, SOH_C, and SOH_S. SOH_S indicates, for example, the amount of metal deposition in the active material of the battery. The greater the amount of metal deposition, the greater the degradation level of the battery. SOH_R is defined, for example, as a value indicating the rate (by what percentage) the impedance real part has decreased compared to a new battery. In this case, the greater the SOH_R, the greater the degradation level of the battery. SOH_C is defined, for example, as a value indicating the rate (by what percentage) the discharge capacity (mAh) has decreased compared to a new battery. The greater the SOH_C, the greater the degradation level of the battery.

[0076] The machine learning model may be constructed, for example, by obtaining machine learning data for multiple batteries with different usage amounts. For example, the battery characteristic analysis device 14 acquires characteristic data for each of the multiple batteries with different usage amounts. Furthermore, the SOH_R, SOH_C, and SOH_S for each of the multiple batteries with different usage amounts are actually measured by a device or the like separate from the battery analysis system 100. Then, the battery characteristic analysis device 14 associates the characteristic data with the actually measured SOH_R, SOH_C, and SOH_S using a machine learning algorithm to obtain machine learning data. The machine learning data is stored in the storage computer 12 and is read from the storage computer 12 into the battery degradation analyzer 60.

[0077] Figure 13 shows example machine learning data for lithium-ion batteries and results obtained from a machine learning model for lithium-ion batteries. The upper section of Figure 13 shows graphs illustrating the machine learning data. The graph on the left side of the upper section shows machine learning data that associates output voltage with discharge capacity for a new battery and three degraded batteries A to C with different amounts of usage. The horizontal axis shows discharge capacity, and the vertical axis shows output voltage. The graph on the right side of the upper section shows relaxation voltage as machine learning data for a new battery and three degraded batteries A to C with different amounts of usage. The horizontal axis shows time, and the vertical axis shows output voltage.

[0078] The lower part of FIG. 13 shows an example of results obtained by a machine learning model for a lithium-ion battery. The left side of the lower part of FIG. 13 shows a graph (based on a machine learning model) in which a predicted value of discharge capacity is obtained by providing an actual measured value of discharge capacity. The horizontal axis shows the actual measured value of discharge capacity, and the vertical axis shows the predicted value. The actual measured value and the predicted value are associated by a straight line on the graph. The right side of the lower part of FIG. 13 shows a graph (based on a machine learning model) in which a predicted value is obtained by providing an actual measured value of the impedance real part for a battery with a different usage amount from degraded batteries A to C. The horizontal axis shows the actual measured value of the impedance real part, and the vertical axis shows the predicted value. The actual measured value and the predicted value are associated by a straight line on the graph. The battery degradation analyzer 70 may calculate SOC_R and SOH_C based on the machine learning model shown in FIG. 13.

[0079] FIG. 14 shows a graph in which the change in the impedance real part corresponds to the degree of battery capacity degradation. The impedance real part was measured by the battery analysis system 100 according to an embodiment of the present invention. The batteries for which the impedance real part indicated by the open circles was measured have a larger amount of metal deposition compared to the batteries for which the impedance real part indicated by the filled circles was measured. As shown in FIG. 14, the decrease in the impedance real part relative to the decrease in battery capacity is larger in batteries with a larger amount of metal deposition. In other words, in lithium-ion batteries, the greater the degree of battery degradation, the stronger the tendency for the impedance real part to decrease. A machine learning model for lithium-ion batteries may utilize this tendency.

[0080] Fig. 15 conceptually shows an example of the operation timing of the battery analysis system 100. The upper part of Fig. 15 shows the load current of multiple batteries B1 to Bn connected in series. The horizontal axis represents time, and the vertical axis represents the load current. A positive load current indicates that power is being output from batteries B1 to Bn, and a negative load current indicates that power is being supplied to batteries B1 to Bn. The lower part of Fig. 15 shows the output voltages Vb of two of batteries B1 to Bn. The horizontal axis represents time, and the vertical axis represents the output voltage.

[0081] The battery analysis system 100 constantly calculates the real part of the impedance and the output voltage of each battery. The battery analysis system 100 also constantly executes a process to equalize the output voltages of multiple batteries. As shown in the bottom part of Figure 15, the output voltages of the two batteries converge to the same value over time.

[0082] 15, the load current changes from 0 to a positive value at time T1, and from a positive value to 0 at time T2. That is, each battery changes from an off state to an on state at time T1, and from an on state to an off state at time T2. Therefore, at time T1 and time T2, the relaxation voltage of each battery may be measured, and machine learning data may be stored in the storage computer 12.

[0083] According to the battery analysis system 100, a damped oscillatory current flows through each battery by turning on and off the switching element of the battery characteristic measuring device, and the performance of the battery is measured based on the damped oscillatory current. Therefore, there is no need to sweep the frequency of the measurement signal, and the performance of each battery can be measured in a simple manner. [Explanation of symbols]

[0084] 10 battery characteristic measuring device, 12 storage computer, 14 battery characteristic analyzing device, 20, 20-1 to 20-n, 20A-1 to 20A-3, 20B measuring instrument, 22, 22A, 22B control unit, 24 damped oscillation circuit, 26 drive unit, 28 primary inductor, 30 capacitive element, 32 resistive element, 34 switching element, 36 drive amplifier, 38 secondary inductor, 40 detection amplifier, 42-1 to 42-3 peak hold circuit, 50 temperature sensor, 52-1, 52-2 delay circuit, 60, 70 battery deterioration analyzer, 62-1, 62-2 output voltage, 64-1, 64-2 impedance real part, B1 to Bn battery, B0 reference battery, L0 reference inductor, C0 reference capacitor, R0 reference resistive element.

Claims

1. obtaining damped oscillation data on the damped oscillation current of the battery from a damped oscillation circuit that damps oscillation of the current flowing through the battery to be analyzed; a battery characteristic analysis device that acquires two or more peak values ​​for the magnitude of a time waveform of a damped oscillation current indicated by the damped oscillation data, calculates a real part of an impedance of the battery based on a ratio of one of the two or more peak values ​​to the other and a plurality of first constants that are predetermined based on characteristics of the damped oscillation circuit, and calculates an output voltage of the battery based on the real part of the impedance of the battery, one of the two or more peak values, and a plurality of second constants that are predetermined based on characteristics of the damped oscillation circuit.

2. The battery characteristic analyzer according to claim 1, A battery characteristic analysis device that determines a degree of deterioration of the battery based on the impedance real part, or based on the impedance real part and the output voltage.

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