JP7582273B2 - Battery diagnostic system, vehicle equipped with same, and battery diagnostic method - Google Patents

Description

The present disclosure relates to a battery diagnostic system, a vehicle equipped with the same, and a battery diagnostic method, and more specifically to technology for diagnosing secondary batteries.

In recent years, vehicles equipped with battery packs have become increasingly popular. There is a possibility that counterfeit battery packs manufactured by non-genuine manufacturers are being distributed. There is also a possibility that genuine battery packs may be illegally modified. Non-genuine products such as counterfeits and illegally modified products may contain inferior secondary batteries or have defects in the control circuit. For this reason, technology has been proposed to diagnose whether a battery pack is genuine or not.

For example, the battery identification device disclosed in JP 2012-174367 A (Patent Document 1) monitors whether a battery pack is genuine based on a first characteristic value and a second characteristic value. The first characteristic value is an output voltage value obtained from each of the multiple battery cells when driving of the vehicle ends or charging of the battery pack ends. The second characteristic value is an output voltage value obtained from each of the multiple battery cells when driving of the vehicle starts for the first time thereafter or charging of the battery pack starts.

JP 2012-174367 A JP 2012-174487 A

There is always a demand for technology that can diagnose with high accuracy whether a secondary battery is genuine. This disclosure has been made to solve the above problem, and one of the objectives of this disclosure is to diagnose with high accuracy whether a secondary battery is genuine.

(1) A battery diagnostic system according to one aspect of the present disclosure includes a sensor that measures the voltage of a secondary battery, and a processor that diagnoses whether the secondary battery is genuine based on a voltage curve that indicates the change over time in voltage measured by the sensor during a diagnostic period that includes both a charging/discharging period and a charging/discharging rest period.

(2) The processor diagnoses whether the secondary battery is genuine based on the results of comparing the voltage curve with a genuine curve that shows the time change in voltage of a genuine product during the period being diagnosed.

(3) The processor diagnoses that the secondary battery is genuine if the voltage on the voltage curve at a first timing during a charging/discharging period is within a first voltage range determined based on the normal curve, and the voltage on the voltage curve at a second timing during a charging/discharging pause period is within a second voltage range determined based on the normal curve.

(4) The processor diagnoses that the secondary battery is genuine if the rate of change of the voltage curve at a first timing during a charging/discharging period is within a first reference range determined based on the normal curve, and if the rate of change of the voltage curve at a second timing during a charging/discharging pause period is within a second reference range determined based on the normal curve.

(5) The processor diagnoses whether the secondary battery is genuine based on the results of comparing the voltage curve with a normal curve created by simulating noise interference.

(6) The processor diagnoses whether the secondary battery is genuine based on the results of multiple comparisons of the voltage curve with the normal curve during a charging/discharging period and the results of multiple comparisons of the voltage curve with the normal curve during a charging/discharging pause period.

(7) The battery diagnostic system further includes a warning device that issues a warning. The processor controls the warning device to issue a warning if the secondary battery is diagnosed as not being genuine.

(8) A vehicle according to another aspect of the present disclosure is equipped with the battery diagnostic system described above.

(9) A battery diagnostic method according to yet another aspect of the present disclosure includes a step in which a computer acquires a voltage curve indicating the change over time in voltage measured by a sensor during a diagnostic period that includes both a charging/discharging period and a charging/discharging rest period, and a step in which the computer diagnoses whether the secondary battery is genuine based on the voltage curve.

This disclosure makes it possible to diagnose with high accuracy whether a secondary battery is genuine.

1 is a diagram illustrating an overall configuration of a vehicle equipped with a battery diagnosis system according to a first embodiment; FIG. 2 is a perspective view showing a schematic structure of a battery. FIG. 2 is a transparent perspective view showing an example of a cell configuration. FIG. 11 is a diagram illustrating a first example of a diagnostic target period. FIG. 11 is a diagram illustrating a second example of a diagnostic target period. FIG. 13 is a diagram showing a voltage change curve of a genuine product and a voltage change curve of a non-genuine product. 4 is a diagram for explaining a method for diagnosing whether a battery is genuine in the first embodiment. FIG. FIG. 4 is a diagram for explaining an impedance component of the internal resistance of a battery. 4 is a flowchart showing a battery diagnosis process in the first embodiment. 13 is a diagram for explaining a method for diagnosing whether a battery is genuine in the second embodiment. FIG. 10 is a flowchart showing a battery diagnosis process in the second embodiment. FIG. 1 is a conceptual diagram for explaining noise. 11 is a diagram for explaining the influence of noise interference on a voltage change curve. FIG. FIG. 13 is a diagram showing a voltage change curve of a regular product and a voltage change curve of a non-regular product when noise interference occurs. 13 is a flowchart showing a battery diagnosis process in the third embodiment.

The following describes in detail the embodiments of the present disclosure with reference to the drawings. Note that the same or corresponding parts in the drawings are given the same reference numerals and their description will not be repeated.

In the following embodiment, an example will be described in which the battery diagnostic system according to the present disclosure is mounted on a vehicle. However, the use of the battery diagnostic system according to the present disclosure is not limited to vehicle use, and may be, for example, stationary use.

[First embodiment]
<System Configuration>
1 is a diagram showing a schematic overall configuration of a vehicle equipped with a battery diagnosis system according to a first embodiment. In this embodiment, the vehicle 1 is a battery electric vehicle (BEV). However, the type of the vehicle 1 is not limited to this as long as it is a vehicle equipped with a battery pack. The vehicle 1 may be a hybrid electric vehicle (HEV), a plug-in hybrid electric vehicle (PHEV), or a fuel cell electric vehicle (FCEV).

The vehicle 1 includes an inlet 10, an AC/DC converter 20, a charge relay (CHR) 30, a battery pack 40, a power control unit (PCU) 51, a motor generator (MG) 52, a warning device 60, and an integrated electronic control unit (ECU) 70. The battery pack 40 includes a battery 41, a monitoring unit 42, and a battery ECU 43.

The inlet 10 is configured to allow insertion of a charging connector provided at the end of a charging cable 91. The vehicle 1 and a charging device 92 installed outside the vehicle 1 are electrically connected via the charging cable 91. This allows the battery 41 to be charged using power supplied from the charging device 92 (plug-in charging).

AC/DC converter 20 is electrically connected between inlet 10 and charging relay 30. AC/DC converter 20 converts AC power supplied from charging device 92 via inlet 10 into DC power, and outputs the DC power to charging relay 30. AC/DC converter 20 also converts DC power supplied from battery 41 (or PCU 51) via charging relay 30 into AC power, and outputs the AC power to inlet 10.
The charging relay 30 is electrically connected to a power line connecting the AC/DC converter 20 and the battery 41. The charging relay 30 is opened/closed in response to a control signal from the integrated ECU 70.

The battery 41 stores power for driving the motor generator 52 and supplies power to the motor generator 52 through the PCU 51. The battery 41 is also charged by power output from the AC/DC converter 20 during plug-in charging. Furthermore, the battery 41 is charged by receiving the generated power through the PCU 51 when the motor generator 52 is generating power (such as during regenerative power generation).

The monitoring unit 42 includes a voltage sensor 421, a current sensor 422, and a temperature sensor 423. The voltage sensor 421 detects the voltage V of the battery 41 (more specifically, each cell). The current sensor 422 detects the current I input to and output from the battery 41. The temperature sensor 423 detects the temperature T of the battery 41 (more specifically, a specific cell). Each sensor outputs a signal indicating the detection result to the battery ECU 43. The voltage sensor 421 corresponds to the "sensor" according to the present disclosure.

The battery ECU 43 includes a processor 431 such as a CPU (Central Processing Unit), a memory 432 such as a ROM (Read Only Memory) and a RAM (Random Access Memory), and an input/output port (not shown) for inputting and outputting various signals. The battery ECU 43 manages the battery 41 in cooperation with the integrated ECU 70 based on input of signals from each sensor of the monitoring unit 42 and maps and programs stored in the memory 432. In this embodiment, the main process executed by the battery ECU 43 is a "battery diagnosis process" that diagnoses whether the battery 41 is a genuine product. The battery diagnosis process by the battery ECU 43 will be described later.

The PCU 51 includes, for example, an inverter and a converter (neither shown). The PCU 51 performs bidirectional power conversion between the battery 41 and the motor generator 52 in accordance with a control signal from the integrated ECU 70.

The motor generator 52 is, for example, a three-phase AC rotating electric machine with a permanent magnet embedded in a rotor (not shown). The motor generator 52 rotates the drive shaft using power supplied from the battery 41. The motor generator 52 can also generate power through regenerative braking. The AC power generated by the motor generator 52 is converted to DC power by the PCU 51 and charged into the battery 41.

The warning device 60 is, for example, a warning light that is turned on in the instrument panel. The warning device 60 may be a display of a navigation system capable of displaying a warning message, or a speaker capable of emitting a warning sound.

Like the battery ECU 43, the integrated ECU 70 includes a processor 701, a memory 702, and an input/output port (not shown). Based on the input of signals from the various sensors provided in the vehicle 1 and the maps and programs stored in the memory, the integrated ECU 70 controls the devices (AC/DC converter 20, charging relay 30, and PCU 51) so that the vehicle 1 is in a desired state. The integrated ECU 70 controls the charging and discharging of the battery 41, for example, by controlling the AC/DC converter 20 and/or the PCU 51.

The integrated ECU 70 may execute the battery diagnosis process instead of the battery ECU 43. Also, the battery ECU 43 may execute a part of the battery diagnosis process, and the integrated ECU 70 may execute the remaining part. Either or both of the processor 431 of the battery ECU 43 and the processor 701 of the integrated ECU 70 correspond to the "processor" according to the present disclosure.

<Battery configuration>
Fig. 2 is a perspective view that shows a schematic structure of the battery 41. The battery 41 is an assembled battery including a plurality of stacks 410 (also called modules or blocks). The plurality of stacks 410 may be connected in series or in parallel to each other. Fig. 1 shows one of the plurality of stacks 410 as a representative example.

The stack 410 includes a plurality of cells 81, a plurality of resin frames 82, a pair of end plates 83, and a pair of restraining bands 84. In the stack 410, a laminate is formed by stacking the plurality of cells 81 and the plurality of resin frames 82. Hereinafter, the height direction of the laminate is referred to as HG, the length direction (stacking direction) of the laminate is referred to as LN, and the width direction of the laminate is referred to as WD.

In this embodiment, each of the multiple cells 81 is a lithium ion battery. However, each cell 81 may be another secondary battery, such as a nickel-metal hydride battery. The number of cells included in the stack 410 is not particularly limited. Each cell 81 has a common configuration. The configuration of the cell 81 will be described with reference to FIG. 3.

Each of the multiple resin frames 82 is disposed between two adjacent cells 81 in the stacking direction. A pair of end plates 83 are disposed at one end and the other end of the stack in the stacking direction. In other words, the end plates 83 are disposed so as to sandwich the stack from both sides in the stacking direction. A pair of restraining bands 84 are disposed on the upper and lower surfaces of the resin frames 82. The restraining bands 84 restrain the pair of end plates 83 to each other while sandwiching the stack.

Figure 3 is a perspective view showing an example of the configuration of cell 81. As mentioned above, in this example, cell 81 is a lithium ion battery.

The cell 81 is a square cell having a substantially rectangular parallelepiped shape. The top surface of the case of the cell 81 is sealed by a lid 811. The lid 811 is provided with a positive electrode terminal 812 and a negative electrode terminal 813. One end of each of the positive electrode terminal 812 and the negative electrode terminal 813 protrudes from the lid 811 to the outside. The other end of each of the positive electrode terminal 812 and the negative electrode terminal 813 is electrically connected to an internal positive electrode terminal and an internal negative electrode terminal (neither shown) inside the case, respectively. Although not shown, two adjacent cells 81 are electrically connected to each other by a bus bar.

The case contains an electrode body 814. The electrode body 814 is formed, for example, by stacking a positive electrode 815 and a negative electrode 816 with a separator 817 between them, and then winding them into a cylindrical shape. The electrolyte is held in the positive electrode 815, the negative electrode 816, the separator 817, etc. Note that it is also possible to use a laminate instead of a wound body as the electrode body 814.

The positive electrode 815, the negative electrode 816, the separator 817, and the electrolyte may be made of a material and structure that is conventionally known as the positive electrode, the negative electrode, the separator, and the electrolyte of a lithium ion secondary battery. As an example, the positive electrode 815 includes NCM (LiNi _1/3 Co _1/3 Mn _1/3 O ₂ ) as a positive electrode mixture, and an aluminum (Al) foil as a positive electrode foil. The negative electrode 816 includes graphite (C) as a negative electrode mixture, and a copper (Cu) foil as a negative electrode foil. The separator may be made of polyolefin (e.g., polyethylene, polypropylene). The electrolyte contains an organic solvent (e.g., a mixed solvent of dimethyl carbonate (DMC), ethyl methyl carbonate (EMC), and ethylene carbonate (EC)), a lithium salt (e.g., LiPF ₆ ), and an additive (e.g., lithium bis(oxalate)borate (LiBOB) or Li[PF ₂ (C ₂ O ₄ ) ₂ ]).

<Voltage change curve>
In the vehicle 1 configured as described above, the battery 41 deteriorates with use or over time. When the battery 41 deteriorates considerably, it may be necessary to replace the battery 41 with a new battery (or a used battery in which deterioration has not progressed). In this case, the battery may be replaced with a non-genuine battery such as a counterfeit or illegally modified battery. If the battery is replaced with a non-genuine battery, various performance characteristics of the vehicle 1 may be degraded. Therefore, it is necessary to diagnose with high accuracy whether the battery 41 is genuine or not.

Therefore, in this embodiment, a "voltage change curve" measured during a specific period described below is used to diagnose whether the battery 41 is genuine. This period is referred to as the "diagnosis target period." As described above, the configurations of the multiple cells 81 are identical, so the voltage of any cell 81 may be measured to obtain the voltage change curve. For simplicity, the following will refer to the voltage change curve of the battery 41 without distinguishing between the cells.

<Diagnosis period>
Fig. 4 is a diagram showing a first example of a diagnostic target period. Fig. 5 is a diagram showing a second example of a diagnostic target period. In Figs. 4 and 5, the horizontal axis represents elapsed time. The vertical axis represents the voltage V measured by the voltage sensor 421. The same applies to Figs. 6, 7, 10, 13, and 14 described below.

As shown in FIG. 4, the diagnosis target period includes a discharge period during which the battery 41 is discharged and a pause period during which charging and discharging of the battery 41 is paused. The length of the discharge period may be several seconds to several tens of seconds. The length of the pause period may be several tens of seconds. For example, when the vehicle 1 is stopped for a certain period of time after traveling uphill and waiting for a traffic light, a voltage change curve L1 as shown in FIG. 4 is measured.

Alternatively, as shown in FIG. 5, the diagnosis target period may include a charging period during which the battery 41 is charged and a pause period during which charging and discharging of the battery 41 is paused. The length of the charging period may be several seconds to several tens of seconds. The length of the pause period may be several tens of seconds. For example, when the vehicle 1 travels downhill and then stops at a traffic light for a certain period of time, a voltage change curve L2 as shown in FIG. 5 is measured. A similar voltage change curve L2 can also be measured by pausing charging during plug-in charging of the vehicle 1.

The voltage change curve L1 or L2 measured during the diagnostic period is stored in the memory 432 of the battery ECU 43. Then, the voltage change curve L1 or L2 is compared with a voltage curve previously obtained from a genuine battery 41. Hereinafter, the voltage change curve of the genuine battery is also referred to as the "genuine curve."

Figure 6 is a diagram showing the voltage change curve of a genuine product and that of an ungenuine product. As shown in Figure 6, the shape of the voltage change curve differs between genuine and ungenuine batteries 41. Therefore, by comparing the voltage change curve L1 (or L2) with the genuine curve, it is possible to diagnose whether the battery 41 is genuine or ungenuine. In other words, if the voltage change curve L1 matches the genuine curve, the battery 41 can be diagnosed as genuine. On the other hand, if the voltage change curve L1 does not match the genuine curve, the battery 41 can be diagnosed as ungenuine.

It is desirable to prepare a normal curve for each combination of (SOC, current I). For example, a large number of normal curves are prepared by measuring voltage changes under conditions in which the SOC in the initial condition differs by a predetermined amount and the current I differs by a predetermined value. In this example, the large number of normal curves are stored in the memory 432 of the battery ECU 43. The battery ECU 43 selects the normal curve to be compared with the voltage change curve L1 according to the combination of (SOC, current I).

Figure 7 is a diagram for explaining a method for diagnosing whether the battery 41 is genuine in the first embodiment. In Figure 7, the voltage change curve L1 shown in Figure 4 is used as an example, but the same diagnosis can also be made using the voltage change curve L2 shown in Figure 5.

Even genuine products can have a certain degree of voltage variation. Therefore, a voltage range VR including the genuine curve is set in advance. The upper limit voltage of the voltage range VR is indicated by UL, and the lower limit voltage is indicated by LL. In the first embodiment, it is determined whether the voltage change curve L1 is within the voltage range VR. More specifically, at least one voltage during the discharge period and at least one voltage during the rest period are used.

In the example shown in FIG. 7, it is determined whether the voltage V(t11) at time t11 (corresponding to the "first timing" according to the present disclosure) during the discharge period is within a first voltage range between the upper limit voltage UL and the lower limit voltage LL, and it is determined whether the voltage V(t21) at time t21 (corresponding to the "second timing" according to the present disclosure) during the pause period is within a second voltage range between the upper limit voltage UL and the lower limit voltage LL.

For one voltage change curve L1A, the voltage V(t11) exceeds the upper limit voltage UL of the first voltage range, and the voltage V(t21) exceeds the upper limit voltage UL of the second voltage range. In this case, the voltage change curve L1A diagnoses that the battery 41 is non-genuine. In contrast, for another voltage change curve L1B, the voltage V(t11) is within the first voltage range, and the voltage V(t21) is within the second voltage range. In this case, the voltage change curve L1B diagnoses that the battery 41 is genuine.

For ease of understanding, an example has been described in which diagnosis is performed based on one voltage value during the discharge period and one voltage value during the pause period. However, diagnosis may also be performed based on multiple voltage values during the discharge period and multiple voltage values during the pause period. By performing diagnosis based on multiple voltage values, it is possible to improve the accuracy of diagnosis.

<Impedance component of internal resistance>
In the present embodiment, both the voltage value during the discharging period and the voltage value during the pause period are used, the reason for which will be explained below.

Fig. 8 is a diagram for explaining the impedance components of the internal resistance of the battery 41. Fig. 6 shows an example of an equivalent circuit diagram of the positive electrode, negative electrode, and separator of the battery 41 (each cell 81). The impedance components of the battery 41 can be classified into a direct current resistance _RDC , a reaction resistance Rc, and a diffusion resistance Rd.

The DC resistance R _DC is an impedance component related to the movement of lithium ions and electrons between the positive and negative electrodes. The DC resistance R _DC increases due to the bias of the salt concentration distribution of the electrolyte when a high load is applied to the battery 41 (when a high voltage is applied or a large current flows). In the equivalent circuit diagram, the DC resistance R _DC is represented as the positive electrode active material resistance Ra1, the negative electrode active material resistance Ra2, and the separator electrolyte resistance R3.

The reaction resistance Rc is an impedance component related to the exchange of electric charges (charge transfer) at the interface between the electrolyte and the active material interface (the surface of the positive and negative active materials). When the battery 41 in a high SOC state is in a high temperature environment, the reaction resistance Rc increases due to the growth of a film at the active material/electrolyte interface. In the equivalent circuit diagram, the reaction resistance Rc is represented as the positive electrode resistance component Rc1 and the negative electrode resistance component Rc2.

The diffusion resistance Rd is an impedance component related to the diffusion of salt in the electrolyte or charge transport material in the active material. The diffusion resistance Rd increases due to cracking of the active material when a high load is applied. The diffusion resistance Rd is determined by the equilibrium voltage Veq1 generated at the positive electrode, the equilibrium voltage Veq2 generated at the negative electrode, and the salt concentration overvoltage Vov3 generated in the cell (overvoltage caused by the salt concentration distribution of the active material in the separator).

The following relational equation (1) holds between the voltage V (CCV: Closed Circuit Voltage) measured by the voltage sensor 421, the OCV (Open Circuit Voltage), the current I, the impedance components R _DC , Rc, Rd, and the polarization voltage ΔVp.
V=OCV-I×(R _DC +Rc+Rd)-ΔVp...(1)

As mentioned above, the voltage change curve L1 and the normal curve are compared for combinations of (SOC, current I). In addition, there is a correspondence between SOC and OCV. Therefore, it can be approximated that the difference in OCV and current I in equation (1) between the voltage change curve L1 and the normal curve is sufficiently small.

The voltage V measured during the discharge period reflects the impedance components R _DC , Rc, and Rd and the polarization voltage ΔVp. During the discharge period, the voltage drop due to the impedance components R _DC , Rc, and Rd is significantly greater than the polarization voltage ΔVp. Therefore, comparing the voltage V(t11) measured during the discharge period with the corresponding voltage on the normal curve (first voltage range) is equivalent to comparing mainly the impedance components R _DC , Rc, and Rd between the battery 41 to be diagnosed and a normal product.

On the other hand, since I = 0 during the pause period, the voltage V measured during the pause period reflects the polarization voltage ΔVp. Therefore, comparing the voltage V (t21) measured during the pause period with the corresponding voltage on the normal curve (second voltage range) is equivalent to comparing the polarization voltage ΔVp between the battery 41 being diagnosed and a normal product.

Genuine and non-genuine products have different specifications, and the resistances R _DC , Rc, and Rd as well as the polarization voltage ΔVp are also different. Therefore, by comparing the voltage V on the voltage change curve measured during the discharge period with the corresponding voltage on the genuine curve, it is possible to diagnose whether the battery 41 is genuine or not. In particular, by comparing both the resistances R _DC , Rc, and Rd and the polarization voltage ΔVp, it is possible to diagnose with high accuracy whether the battery 41 to be diagnosed is genuine or not.

<Battery diagnosis flow>
9 is a flowchart showing the battery diagnosis process in the first embodiment. This flowchart is called from the main routine (not shown) and executed when a predetermined condition is met (for example, when the battery pack 40 is replaced). Each step is realized by software processing by the battery ECU 43, but may also be realized by hardware (electrical circuitry) created within the battery ECU 43. Hereinafter, steps are abbreviated as S.

In this flowchart, one of the multiple stacks 410 included in the battery 41 is the target of diagnosis. By performing the same process on stacks 410 other than the target stack, it is possible to diagnose two or more stacks 410.

In S101, the battery ECU 43 determines whether the diagnostic period described in FIG. 4 or FIG. 5 (for example, a discharge period of several seconds to several tens of seconds followed by a rest period of several tens of seconds) has elapsed. The battery ECU 43 sequentially acquires the voltage V from the voltage sensor 421 and temporarily stores the acquired voltage V (i.e., time series data of the voltage V) in the memory 432. If the diagnostic period has not elapsed (NO in S101), the battery ECU 43 continues to temporarily store the voltage V. In this case, the old time series data of the voltage V that exceeds a predetermined storage capacity is erased from the memory 432. On the other hand, if the diagnostic period has elapsed (YES in S101), the battery ECU 43 retains the time series data of the voltage V during the diagnostic period without erasing it (S102).

In S103, the battery ECU 43 acquires the voltage V1 at a predetermined timing during the charge/discharge period (charging period or discharging period) from the time series data (voltage change curve) of the stored voltage V. In the example of FIG. 7, the voltage V (t11) at time t11 corresponds to the voltage V1. Note that the predetermined timing here can be determined based on the results of a previous experiment, for example, the time when X seconds have elapsed since the charge/discharge start time t10.

In S104, the battery ECU 43 acquires the voltage V2 at a predetermined timing during the pause period from the stored time series data of the voltage V. In the example of FIG. 7, the voltage V (t21) at time t21 corresponds to the voltage V2. The predetermined timing here can be determined, for example, as the time when Y seconds have elapsed from the pause start time (charging/discharging stop time) t20. Y may be the same as X, or may be different.

In S105, the battery ECU 43 determines whether the voltage V1 is within a first voltage range. In S106, the battery ECU 43 determines whether the voltage V2 is within a second voltage range. As described above, the normal curve is selected according to the combination of (SOC, current I). Therefore, both the first voltage range and the second voltage range can change according to the combination of (SOC, current I).

If voltage V1 is within the first voltage range and voltage V2 is within the second voltage range (YES in S105 and YES in S106), the battery ECU 43 diagnoses that the battery 41 is genuine (S107).

On the other hand, if the voltage V1 is not within the first voltage range (NO in S105) or if the voltage V2 is not within the second voltage range (NO in S106), the battery ECU 43 diagnoses that the battery 41 is a non-genuine product (S108). In this case, the battery ECU 43 cooperates with the integrated ECU 70 to control the warning device 60 so that a warning light is turned on, a warning message is displayed, or a warning sound is generated (S109). The battery ECU 43 may cooperate with the integrated ECU 70 to prohibit the vehicle 1 from traveling.

As described above, in the first embodiment, whether the battery 41 is genuine is diagnosed based on the voltage value of the voltage change curve (time series data of voltage V) measured by the voltage sensor 421 during the diagnosis period that includes both the charge/discharge period and the rest period. Since the diagnosis is performed based on the voltage during both the charge/discharge period and the rest period, differences in the specifications of the battery 41 can be accurately detected. Therefore, according to the first embodiment, it is possible to diagnose with high accuracy whether the battery 41 is genuine.

As in the explanation of FIG. 7, in the flowchart shown in FIG. 8, a genuine/non-genuine diagnosis may be performed based on the voltage V1 measured multiple times during the charging/discharging period and the voltage V2 measured multiple times during the pause period. In this case, the battery 41 may be diagnosed as genuine if the ratio of the voltages V1 and V2 that are within the voltage range (the first voltage range or the second voltage range) is equal to or greater than a predetermined value, and the battery 41 may be diagnosed as non-genuine if the ratio is less than the predetermined value. By performing a diagnosis based on the voltages V1 and V2 measured multiple times, the accuracy of the diagnosis can be further improved.

[Embodiment 2]
In the first embodiment, an example in which diagnosis is performed based on a voltage value on a voltage change curve is described. In the second embodiment, an example in which diagnosis is performed based on a rate of change of the voltage change curve (in other words, a slope of a tangent line drawn to the voltage change curve) is described. Note that the configuration of the vehicle in the second embodiment is the same as the configuration of vehicle 1 in the first embodiment (see FIGS. 1 to 3), and therefore description thereof will not be repeated.

Figure 10 is a diagram for explaining a method of diagnosing whether the battery 41 is genuine in the second embodiment. In the second embodiment, it is determined whether the rate of change (slope of the tangent) of the voltage change curve L1 at a predetermined timing is within a predetermined reference range based on the normal curve. More specifically, the slope of the tangent at least once during the discharging period and the slope of the tangent at least once during the resting period are used. In the example shown in Figure 10, it is determined whether the slope SL1 of the tangent T1 at time t31 during the discharging period is within a first reference range (not shown), and it is determined whether the slope SL2 of the tangent T2 at time t41 during the resting period (not shown) is within a second reference range.

Figure 11 is a flowchart showing the battery diagnosis process in embodiment 2. This flowchart is the same as the flowchart in embodiment 1 (see Figure 9) except that tangent slopes SL1 and SL2 are used instead of voltages V1 and V2. Therefore, detailed description will not be repeated.

As described above, in the second embodiment, whether the battery 41 is genuine is diagnosed based on the rate of change (slope of the tangent) of the voltage change curve (time series data of voltage V) measured by the voltage sensor 421 during a diagnosis period that includes both a charge/discharge period and a rest period. Since the diagnosis is performed based on the rate of change during both the charge/discharge period and the rest period, differences in the specifications of the battery 41 can be accurately detected, as in the first embodiment. Therefore, according to the second embodiment, it is possible to diagnose with high accuracy whether the battery 41 is genuine.

[Embodiment 3]
In the third embodiment, an example will be described in which diagnosis is performed taking into consideration noise generated by electronic devices around battery pack 40. Note that the configuration of the vehicle in the third embodiment is the same as the configuration of vehicle 1 in the first and second embodiments (see FIGS. 1 to 3), and therefore description thereof will not be repeated.

Figure 12 is a conceptual diagram for explaining noise. The horizontal axis represents time. The vertical axis represents current. Various electronic devices may be present around the battery pack 40. In the vehicle configuration of Figure 1, the PCU 51 (inverter and/or converter), charging device 92, etc. are present around the battery pack 40. Noise generated by these electronic devices (or their power sources) may be intermittently superimposed on the current (detection result of current sensor 422) as shown in Figure 12. Noise may also be superimposed on the voltage (detection result of voltage sensor 421). Hereinafter, this phenomenon will be referred to as "noise interference."

Figure 13 is a diagram for explaining the effect of noise interference on the voltage change curve. Figure 13 shows a comparison of a voltage change curve when noise interference occurs and a voltage change curve when noise interference does not occur. As is clear from Figure 13, the shape of the voltage change curve can change when noise interference occurs. Although not shown, the shape of the genuine curve can also change. This can result in a decrease in the accuracy of diagnosing whether the battery 41 is genuine.

Therefore, in this embodiment, a normal curve is prepared in advance assuming noise interference that may occur in the vehicle 1. That is, a variety of ripple currents simulating noise interference are generated in advance using a ripple current generating circuit (not shown) and applied to the normal product. By simulating noise interference under various conditions, including during charging/discharging and resting, a large number of normal curves are created. The created normal curves are stored in the memory 432 of the battery ECU 43.

Figure 14 shows the voltage change curve of a genuine product and a non-genuine product when noise interference occurs. As shown in Figure 14, even when noise interference occurs, the shape of the voltage change curve differs between genuine and non-genuine batteries 41. Therefore, by comparing the voltage change curve with the genuine curve, it is possible to diagnose whether the battery 41 is genuine or non-genuine.

Figure 15 is a flowchart showing the battery diagnosis process in embodiment 3. The processes in steps S301 to S304 are the same as the processes in steps S101 to S104 in embodiment 1 (see Figure 9).

In S305, the battery ECU 43 determines whether noise interference is occurring. The battery ECU 43 can determine whether noise interference is occurring based on, for example, whether noise is superimposed on the current V detected by the voltage sensor 421 or the current I detected by the current sensor 422 (whether the amplitude of the noise is greater than a predetermined amount, whether the duration of the noise superimposition is longer than a predetermined time, etc.).

If noise interference is occurring (YES in S305), the battery ECU 43 reads from the memory 432 the first and second voltage ranges set from the normal curve in an environment simulating noise interference (S306). On the other hand, if noise interference is not occurring (NO in S305), the battery ECU 43 reads from the memory 432 the first and second voltage ranges set from the normal curve under normal conditions (the normal curve when noise interference is not occurring, which is the same as in embodiment 1) (S307). The processing from S308 onwards is similar to the processing from S105 onwards in embodiment 1, so the description will not be repeated.

Note that, here, an example has been described in which diagnosis is performed based on the voltage values on the voltage change curve, as in embodiment 1. However, diagnosis may also be performed based on the rate of change of the voltage change curve (the slope of the tangent line), as in embodiment 2.

As described above, according to the third embodiment, as in the first and second embodiments, the diagnosis is performed based on the voltage during both the charge/discharge period and the idle period, so that the difference in the specifications of the battery 41 can be accurately detected. Therefore, it is possible to diagnose with high accuracy whether the battery 41 is genuine. Furthermore, in the third embodiment, the voltage range (the first voltage range and the second voltage range in the processing of S308 and S309) used to diagnose whether the battery 41 is genuine is switched between when noise interference occurs and when it does not occur (normal). When noise interference occurs, a normal curve created under an environment simulating noise interference is used, so that it is possible to diagnose with high accuracy whether the battery 41 is genuine even when noise interference occurs.

The embodiments disclosed herein should be considered to be illustrative and not restrictive in all respects. The scope of the present disclosure is indicated by the claims rather than the description of the embodiments above, and is intended to include all modifications within the meaning and scope of the claims.

1 vehicle, 10 inlet, 20 converter, 30 charging relay, 40 battery pack, 41 battery, 410 stack, 42 monitoring unit, 421 voltage sensor, 422 current sensor, 423 temperature sensor, 43 battery ECU, 431 processor, 432 memory, 51 PCU, 52 motor generator, 60 warning device, 70 integrated ECU, 701 processor, 702 memory, 81 cell, 811 cover, 812 positive terminal, 813 negative terminal, 814 electrode body, 815 positive electrode, 816 negative electrode, 817 separator, 82 resin frame, 83 end plate, 84 restraining band, 91 charging cable, 92 charging device.

Claims (6)

A sensor for measuring the voltage of the secondary battery;
a processor for diagnosing whether the secondary battery is genuine based on a voltage curve showing a time change in voltage measured by the sensor during a diagnosis period including both a charge/discharge period and a charge/discharge rest period ;
The processor diagnoses the secondary battery to be genuine if the rate of change of the voltage curve at a first timing during the charging and discharging period is within a first reference range determined based on a normal curve that shows the time change in voltage of the genuine product during the period under diagnosis, and if the rate of change of the voltage curve at a second timing during the charging and discharging pause period is within a second reference range determined based on the normal curve . A sensor for measuring the voltage of the secondary battery;
a processor for diagnosing whether the secondary battery is genuine based on a voltage curve showing a time change in voltage measured by the sensor during a diagnosis period including both a charge/discharge period and a charge/discharge rest period;
The processor diagnoses whether the secondary battery is genuine based on the results of comparing the voltage curve with a genuine curve that shows the change in voltage of the genuine battery over time during the diagnosis period, the genuine curve being created by simulating noise interference. A sensor for measuring a voltage of the secondary battery;
a processor for diagnosing whether the secondary battery is genuine based on a voltage curve showing a time change in voltage measured by the sensor during a diagnosis period including both a charge/discharge period and a charge/discharge rest period;
The processor diagnoses whether the secondary battery is genuine based on the results of multiple comparisons of the voltage curve during the charging and discharging period with a genuine curve that shows the time change of the voltage of the genuine battery during the diagnosis period , and the results of multiple comparisons of the voltage curve with the genuine curve during the charging and discharging pause period. Further comprising a warning device for issuing a warning,
The battery diagnostic system according to claim 1 , wherein the processor controls the warning device to issue a warning when the secondary battery is diagnosed as not being a genuine product. A vehicle comprising the battery diagnostic system according to any one of claims 1 to 3 . A step in which a computer acquires a voltage curve indicating a time change in the voltage of the secondary battery measured by a sensor during a diagnosis target period including both a charge/discharge period and a charge/discharge rest period;
and diagnosing, by the computer, whether the secondary battery is a genuine product based on the voltage curve ;
The diagnosing step includes a step of diagnosing the secondary battery as genuine if a rate of change of the voltage curve at a first timing during the charging and discharging period is within a first reference range determined based on a normal curve that shows the time change in voltage of the genuine product during the period to be diagnosed, and if a rate of change of the voltage curve at a second timing during the charging and discharging pause period is within a second reference range determined based on the normal curve .

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