JP6927003B2 - Battery deterioration estimation device - Google Patents

Description

The present disclosure relates to a battery deterioration estimation device, and more particularly to a battery deterioration estimation device suitable for estimating the deterioration amount of a battery mounted on a vehicle.

A vehicle equipped with an electronic control device (hereinafter referred to as "ECU (Electronic Control Unit)") that controls charging / discharging of the battery while monitoring the state of the battery (current, voltage, temperature, etc.) is known. During the period when neither the vehicle running control nor the battery charge / discharge control is performed (hereinafter, referred to as "leaving period"), the power of the ECU is turned off from the viewpoint of energy consumption reduction and the like, and the ECU is stopped. When the ECU is in the stopped state, the battery state is not detected by the ECU. The stopped state includes a power saving mode (sleep, etc.). Further, as an example of the neglected period, the ignition switch is turned off while the vehicle is stopped, and the battery mounted on the vehicle is charged by a power source outside the vehicle (hereinafter referred to as "external charging"). ) Is not performed.

Japanese Unexamined Patent Publication No. 2014-126612 (Patent Document 1) discloses a battery deterioration estimation device that detects the battery state by turning on the power of the ECU at a predetermined cycle during the neglected period. In this device, the state of the battery detected during the leaving period is used to improve the estimation accuracy of the amount of deterioration of the battery.

Japanese Unexamined Patent Publication No. 2014-126421

By turning on the power of the ECU during the neglected period, it becomes possible to detect the battery state. In order to improve the estimation accuracy of the deterioration amount of the battery, it is preferable to increase the frequency of detecting the battery state during the leaving period and increase the number of data of the battery state detected during the leaving period. However, it is not preferable from the viewpoint of reducing energy consumption to frequently turn on the power of the ECU to detect the battery state during the neglected period.

The present disclosure has been made to solve the above problems, and an object of the present disclosure is to estimate the amount of deterioration of a battery with high accuracy while reducing energy consumption.

The battery deterioration estimation device of the present disclosure is a battery deterioration estimation device that estimates the amount of deterioration of the battery, and includes an outside air temperature acquisition unit, a battery temperature measurement unit, an outside air temperature estimation unit, and an outside air temperature correction unit. It includes a battery temperature estimation unit, a battery temperature correction unit, and a deterioration amount estimation unit.

The above-mentioned outside air temperature acquisition unit is configured to acquire actual measurement data of the outside air temperature. The battery temperature measurement unit described above is configured to acquire actual measurement data of the battery temperature. The above-mentioned outside air temperature estimation unit is configured to estimate the transition of the outside air temperature. The above-mentioned outside air temperature correction unit is configured to correct the estimated transition of the outside air temperature by using the actual measurement data of the outside air temperature. The above-mentioned battery temperature estimation unit uses the battery temperature followability to the outside air temperature (hereinafter, may be referred to as “temperature followability”) obtained in advance, and uses the corrected change in the outside air temperature to obtain the battery temperature. It is configured to estimate the transition. The battery temperature correction unit is configured to correct the estimated transition of the battery temperature by using the measured data of the battery temperature. The deterioration amount estimation unit is configured to estimate the deterioration amount of the battery from the corrected transition of the battery temperature.

It is also possible to obtain the transition of the battery temperature by a method of directly obtaining the transition of the battery temperature from the measured data by linear interpolation or the like (hereinafter, referred to as “direct method”). However, the direct method requires a large amount of actual measurement data in order to obtain the transition of the battery temperature with sufficiently high accuracy. On the other hand, in the battery deterioration estimation device, the transition of the battery temperature is obtained by the procedure of estimating the transition of the battery temperature from the transition of the outside air temperature and correcting the transition of the estimated battery temperature by the actual measurement data. With such a method, the number of actually measured data required to estimate the transition of the battery temperature with sufficiently high accuracy is small.

Therefore, when the transition of the battery temperature is obtained from a small amount of actually measured data, the above-mentioned method using the battery deterioration estimation device is higher than the direct method (for example, the battery deterioration estimation method according to the comparative example described later). The transition of the battery temperature can be obtained with accuracy (see, for example, FIGS. 11 to 14 described later).

Further, in the above-mentioned battery deterioration estimation device, not only the transition of the battery temperature but also the transition of the outside air temperature is a procedure in which the transition of the outside air temperature is first estimated, and then the estimated transition of the outside air temperature is corrected by the actual measurement data. Is sought after. Therefore, it is possible to obtain the transition of the outside air temperature with high accuracy from a small amount of actual measurement data.

The battery deterioration estimation device can obtain the transition of the battery temperature with high accuracy from a small amount of actual measurement data. Further, the battery deterioration estimation device is configured to estimate the deterioration amount of the battery from the transition of the battery temperature thus obtained. That is, the battery deterioration estimation device can estimate the battery deterioration amount with high accuracy from the measured data of the small battery temperature. Such a battery deterioration estimation device can be used to estimate the amount of battery deterioration during the standing period of the vehicle.

From the viewpoint of reducing energy consumption, it is preferable that the power of the ECU is turned off during the period when the vehicle is left unattended. However, when the power of the ECU is turned off, the state of the battery cannot be detected. Then, if the deterioration amount of the battery is estimated without considering the state of the battery during the leaving period, the estimation accuracy of the deterioration amount of the battery is lowered. Therefore, in order to estimate the amount of deterioration of the battery with high accuracy, the actual measurement data required to estimate the amount of deterioration of the battery during the leaving period by turning on the power of the ECU at a certain frequency even during the leaving period. It is preferable to have the ECU execute the acquisition (detection of the battery temperature). On the other hand, from the viewpoint of reducing energy consumption, it is not preferable to frequently turn on the power of the ECU to detect the battery state during the neglected period.

In the above-mentioned battery deterioration estimation device, the number of actually measured data required to obtain the transition of the battery temperature (and by extension, the amount of deterioration of the battery) with sufficiently high accuracy is small. Therefore, necessary actual measurement data can be secured without frequently turning on the power of the ECU during the neglected period. Energy consumption can be reduced by reducing the number of times the ECU is turned on during the neglected period.

As described above, according to the battery deterioration estimation device of the present disclosure, it is possible to estimate the deterioration amount of the battery with high accuracy while reducing the energy consumption.

The outside air temperature acquisition unit may acquire the actual measurement data of the outside air temperature by communication, or may acquire the actual measurement data of the outside air temperature by the outside air temperature sensor. The actual measurement data of the outside air temperature is preferably a plurality of data at intervals of 10 minutes or less. The outside air temperature estimation unit can estimate the transition of the outside air temperature by using, for example, the weather prediction information and a predetermined estimation formula. The actual measurement data of the battery temperature is, for example, a detection value of a temperature sensor provided in the battery. The battery temperature estimation unit may estimate the transition of the battery temperature from the transition of the corrected outside air temperature by using the measured data of the solar radiation intensity in addition to the above-mentioned temperature followability. The measured data of the solar radiation intensity is preferably a plurality of data at intervals of 10 minutes or less.

According to the present disclosure, it is possible to estimate the amount of deterioration of a battery with high accuracy while reducing energy consumption.

It is a figure which shows schematic the whole structure of the vehicle to which the deterioration estimation device of the battery according to the embodiment of this disclosure is applied. It is a figure for demonstrating how to obtain the correction battery temperature transition. It is a flowchart which shows the processing procedure of the deterioration amount estimation of the cell which is executed by the ECU while the vehicle is running. It is a flowchart which shows the processing procedure of the deterioration amount estimation of the cell which is executed by the ECU during the leaving period of a vehicle. It is a figure which shows an example of the estimated outside temperature transition obtained by fitting by a sine function. It is a figure which shows an example of the corrected outside air temperature transition obtained by the correction using the actual measurement data of the outside air temperature. It is a figure which shows an example of the estimated battery temperature transition. It is a figure which shows an example of the correction battery temperature transition obtained by the correction using the actual measurement data of the battery temperature. It is a figure which shows the temperature frequency distribution created in an Example. It is a figure which shows an example of the T-β correspondence information. It is a figure which conceptually shows the transition of the battery temperature obtained by the deterioration estimation method of the battery according to an embodiment. It is a figure which conceptually shows the transition of the battery temperature obtained by the deterioration estimation method of the battery which concerns on a comparative example. It is a figure which shows the temperature frequency distribution created by the deterioration estimation method of the battery which concerns on a comparative example. It is a figure which shows the transition of the capacity maintenance rate of the target cell obtained by the deterioration estimation method of the battery which concerns on Example and comparative example.

Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. The same or corresponding parts in the drawings are designated by the same reference numerals, and the description thereof will not be repeated.

FIG. 1 is a diagram schematically showing a configuration of a vehicle 1 to which a battery deterioration estimation device according to an embodiment of the present disclosure is applied. In the following, as a typical example, an example in which the vehicle 1 is a hybrid vehicle and the battery mounted on the vehicle 1 is an assembled battery will be described.

With reference to FIG. 1, the vehicle 1 includes an assembled battery 10, a monitoring unit 20, a power control unit (hereinafter, referred to as “PCU (Power Control Unit)”) 30, and a motor generator (hereinafter, “MG (Motor)”. 41, 42), an engine 50, a power dividing device 60, a drive shaft 70, a drive wheel 80, an ECU 100, and a communication device 110.

The assembled battery 10 includes a plurality of secondary batteries connected in series, and stores electric power for driving the MGs 41 and 42. Hereinafter, the secondary battery constituting the assembled battery 10 may be referred to as a “cell”. The cell is, for example, a lithium ion battery. However, a secondary battery other than the lithium ion battery (for example, a nickel hydrogen battery) may be adopted as the cell. The assembled battery 10 is mounted in, for example, the luggage space of the vehicle 1. However, the mounting position of the assembled battery 10 can be arbitrarily changed. For example, the assembled battery 10 may be mounted under the seat. The assembled battery 10 can supply electric power to the MGs 41 and 42 through the PCU 30. Further, the assembled battery 10 is charged by receiving the generated power through the PCU 30 at the time of power generation of the MGs 41 and 42.

The monitoring unit 20 includes a voltage sensor 21, a current sensor 22, and a temperature sensor 23. As the temperature sensor 23, for example, a thermocouple or a thermistor can be adopted. The voltage sensor 21 detects the voltage Vx for each cell of the assembled battery 10. The current sensor 22 detects the charge / discharge current Ix of the assembled battery 10. The temperature sensor 23 detects the temperature Tx for each cell of the assembled battery 10. Then, each sensor outputs a signal indicating the detection result to the ECU 100.

The voltage sensor 21 and the temperature sensor 23 may detect the voltage and the temperature in a plurality of (for example, several) cells as monitoring units, respectively. In this case, with respect to the voltage, the voltage (average value) for each cell can be calculated by dividing the detected value for a plurality of cells by the number of cells.

The PCU 30 executes bidirectional power conversion between the assembled battery 10 and the MGs 41 and 42 according to the control signal from the ECU 100. The PCU 30 is configured so that the states of the MGs 41 and 42 can be controlled separately. For example, the MG42 can be put into a power running state while the MG41 is in a regenerative (power generation) state. The PCU 30 includes, for example, two inverters provided corresponding to the MGs 41 and 42, and a converter that boosts the DC voltage supplied to each inverter to a voltage higher than the output voltage of the assembled battery 10.

The MGs 41 and 42 are AC rotating electric machines, for example, three-phase AC synchronous motors in which a permanent magnet is embedded in a rotor. The MG 41 is mainly used as a generator driven by the engine 50 via the power dividing device 60. The electric power generated by the MG 41 is supplied to the MG 42 or the assembled battery 10 via the PCU 30.

The MG 42 mainly operates as an electric motor and drives the drive wheels 80. The MG 42 is driven by receiving at least one of the electric power from the assembled battery 10 and the electric power generated by the MG 41, and the driving force of the MG 42 is transmitted to the drive shaft 70. On the other hand, when the vehicle is braking or the acceleration is reduced on a downhill slope, the MG 42 operates as a generator to generate regenerative power generation. The electric power generated by the MG 42 is supplied to the assembled battery 10 via the PCU 30.

The engine 50 is an internal combustion engine that outputs power by converting the combustion energy generated when the air-fuel mixture is burned into the kinetic energy of movers such as pistons and rotors. The power splitting device 60 includes, for example, a planetary gear mechanism having three rotation axes of a sun gear, a carrier, and a ring gear. The power dividing device 60 divides the power output from the engine 50 into a power for driving the MG 41 and a power for driving the drive wheels 80.

The ECU 100 includes a CPU (Central Processing Unit) 101, a memory 102, and an input / output port (not shown) for inputting / outputting various signals. The memory 102 includes a ROM (Read Only Memory), a RAM (Random Access Memory), and a rewritable non-volatile memory. Various controls are executed by the CPU 101 executing the program stored in the memory 102. The various controls performed by the ECU 100 are not limited to processing by software, but can also be processed by dedicated hardware (electronic circuits).

The ECU 100 controls the charging / discharging of the assembled battery 10 according to the used SOC range determined by the lower limit SOC and the upper limit SOC. SOC (State Of Charge) is defined as the ratio of the current charge capacity to the full charge capacity (eg, percentage). When the SOC of the assembled battery 10 approaches the upper limit SOC, the ECU 100 limits the power supplied to the assembled battery 10 (that is, the charging power of the assembled battery 10) so that the SOC of the assembled battery 10 does not exceed the upper limit SOC. To. Further, when the SOC of the assembled battery 10 approaches the lower limit SOC, the ECU 100 limits the power discharged from the assembled battery 10 (that is, the discharge power of the assembled battery 10), and the SOC of the assembled battery 10 falls below the lower limit SOC. Try not to. The lower limit SOC and the upper limit SOC are stored in, for example, the memory 102. Each value of the lower limit SOC and the upper limit SOC can be changed by the ECU 100. As a method for measuring SOC, various known methods such as a method based on current value integration (Coulomb count) or a method based on estimation of open circuit voltage (OCV) can be adopted.

The ECU 100 estimates the amount of deterioration of each cell constituting the assembled battery 10 by using the state (cell temperature, etc.) of the assembled battery 10 detected by the monitoring unit 20. As the amount of deterioration of the cell increases, the cell capacity (the amount of electric power that can be stored in the cell) decreases. A possible cause of cell deterioration is the precipitation of charge carriers on the surface of the cell's electrodes. For example, in a lithium ion battery, the deterioration of the battery progresses as lithium precipitates on the surface of the negative electrode.

The ECU 100 outputs information to be stored (calculation result, etc.) to a memory 102 (for example, a rewritable non-volatile memory) and stores the information in the memory 102. The memory 102 may store information used for detecting the battery state and controlling the vehicle 1 in advance. For example, the memory 102 may store the initial information of the assembled battery 10 (cell type, capacity, internal resistance, electrode thickness, basis weight, etc.) in advance.

The memory 102 may further store the corresponding information (for example, the estimation formula (1) described later) used for estimating the deterioration of the battery. Correspondence information is information indicating the relationship between a plurality of correlated parameters. The correspondence information may be a map, a table, a mathematical formula, or a model. Further, the correspondence information may be configured by combining a plurality of maps and the like.

The communication device 110 is configured to be able to access the network 200 by wireless communication. The communication device 110 can receive data from another device (for example, download) via the network 200, or transmit (for example, upload) data to another device via the network 200. Further, the ECU 100 and the communication device 110 are configured to be able to send and receive information (data, signals, etc.) to each other.

Examples of the network 200 include a local area network (LAN), a wide area network (WAN) (eg, the Internet), a public network, a private network, a virtual network, and a peer-to-peer network. The network 200 may be a DSRC (Dedicated Short Range Communications) network, an IEEE802.11p network, a 3G network, a 4G network, a 5G + network, or a WiFi (registered trademark) network. Further, the network 200 may be a vehicle-to-vehicle network or a vehicle-to-base / base-to-vehicle network.

While the vehicle 1 is running, the ECU 100 controls the PCU 30 (and MG 41, 42) and the engine 50 based on the signals received from each sensor and various programs and maps stored in the memory 102, thereby causing the vehicle 1 to travel. Performs running control. The ECU 100 controls the discharge of the assembled battery 10 by controlling the PCU 30. By controlling the discharge from the assembled battery 10 to the PCU 30, the ECU 100 can control the amount of power supplied to the MGs 41 and 42 (and thus the torque of the MGs 41 and 42). Further, when the assembled battery 10 is charged by the generated power of the MGs 41 and 42 while the vehicle 1 is traveling, the ECU 100 controls the charging power (and thus the SOC) of the assembled battery 10 by controlling the PCU 30.

Further, the ECU 100 detects the temperature of the cells constituting the assembled battery 10 at a predetermined cycle while the vehicle 1 is running, and calculates the amount of deterioration of the assembled battery 10 for each cell using the detected cell temperature. ..

On the other hand, during the neglected period of the vehicle 1, neither the traveling control of the vehicle 1 nor the charge / discharge control of the assembled battery 10 is performed. The vehicle 1 may be a vehicle that can be charged externally or a vehicle that cannot be charged externally. In a vehicle that can be charged externally, a typical example of the neglected period is a period in which the ignition switch is turned off and the vehicle is not charged externally while the vehicle is stopped. In a vehicle that cannot be charged externally, a typical example of the neglected period is a period in which the ignition switch is turned off while the vehicle is stopped.

By the way, from the viewpoint of reducing energy consumption and the like, it is preferable that the power supply of the ECU 100 of the vehicle 1 is turned off during the neglected period. However, when the power of the ECU 100 is turned off, the state of the assembled battery 10 cannot be detected. If the amount of deterioration of the assembled battery 10 is estimated without considering the state of the assembled battery 10 during the neglected period, the accuracy of estimating the amount of deterioration of the assembled battery 10 will decrease. Therefore, in order to estimate the deterioration amount of the assembled battery 10 with high accuracy, the power of the ECU 100 is turned on at a certain frequency even during the leaving period, and the deterioration amount of the assembled battery 10 during the leaving period is estimated. It is preferable to have the ECU 100 acquire the necessary actual measurement data (detection of the battery temperature). On the other hand, from the viewpoint of reducing energy consumption, it is not preferable to frequently turn on the power of the ECU 100 to detect the battery state during the neglected period.

Therefore, in the battery deterioration estimation device according to this embodiment, the power of the ECU 100 is turned off during the leaving period of the vehicle 1 except for the start timing shown below. As a result, energy consumption can be reduced. Further, in the neglected period of the vehicle 1, when the periodic start timing (for example, the timing of every hour) is reached, the ECU 100 is started to actually measure the battery temperature (acquire the actual measurement data). Then, the ECU 100 estimates the transition of the battery temperature (cell temperature of the assembled battery 10) from the transition of the outside air temperature (the temperature outside the vehicle 1), and corrects the transition of the estimated battery temperature by the above-mentioned actual measurement data. According to such a method, it is possible to interpolate the battery temperature between the actually measured values with high accuracy even if only a small amount of actually measured data (for example, the measured value every hour) is obtained with respect to the battery temperature. Therefore, it is possible to obtain the transition of the battery temperature with high accuracy from a small amount of actually measured data.

Specifically, the ECU 100 (particularly, the portion that functions as the outside air temperature estimation unit) estimates the transition of the outside air temperature by using, for example, weather prediction information and a predetermined estimation formula (for example, a sin function described later). The weather forecast information can be obtained from a website (for example, a weather forecast site) through the network 200, for example. Hereinafter, the transition of the estimated outside air temperature may be referred to as an “estimated outside air temperature transition”.

The ECU 100 (particularly, a part that functions as an outside air temperature acquisition unit) cooperates with a communication device 110 or the like to acquire actual measurement data of the outside air temperature from a website (sites of various weather information services, etc.) through, for example, a network 200. Then, the ECU 100 (particularly, the portion that functions as the outside air temperature correction unit) corrects the above-mentioned estimated outside air temperature transition by using the actual measurement data of the outside air temperature. Hereinafter, the transition of the corrected outside air temperature may be referred to as a “corrected outside air temperature transition”.

The ECU 100 (particularly, the portion that functions as the battery temperature estimation unit) estimates the transition of the battery temperature (cell temperature of the assembled battery 10) from the transition of the corrected outside air temperature by using the temperature followability obtained in advance. The temperature followability is corresponding information indicating the relationship between the outside air temperature and the battery temperature, and is obtained in advance by an experiment or the like and stored in the memory 102, for example. The battery temperature tends to follow the change in the outside air temperature with a delay of a certain period of time. The degree of delay varies depending on the mounting position of the assembled battery 10 and the like. Further, when the mounting position of the assembled battery 10 is the luggage space of the vehicle 1, the transition of the battery temperature is easily affected by the radiant energy from the sun in addition to the influence of the outside air temperature. Therefore, in order to estimate the transition of the battery temperature with high accuracy, it is preferable to estimate the transition of the battery temperature by using the measured data of the solar radiation intensity in addition to the above-mentioned temperature followability. Hereinafter, the transition of the battery temperature estimated from the transition of the corrected outside air temperature may be referred to as "estimated battery temperature transition".

The ECU 100 (particularly, the portion that functions as the battery temperature measurement unit) acquires the battery temperature measurement data (detected value of the temperature sensor 23) from the monitoring unit 20. Then, the ECU 100 (particularly, the portion that functions as the battery temperature correction unit) corrects the estimated battery temperature transition by using the actual measurement data of the battery temperature. Hereinafter, the transition of the battery temperature after correction may be referred to as "corrected battery temperature transition".

FIG. 2 is a diagram for explaining how to obtain the temperature transition of the correction battery. With reference to FIG. 2, the ECU 100 estimates the transition of the battery temperature by using, for example, the transition of the corrected outside air temperature shown by the line k1, the measured data of the solar radiation intensity, and the temperature followability obtained in advance. As a result, an estimated battery temperature transition (not shown) can be obtained.

The shape of the estimated battery temperature transition (curve shape) generally matches the actual transition. However, the estimated battery temperature transition may deviate to the higher temperature side or the lower temperature side than the actual transition. Therefore, the ECU 100 uses the actually measured battery temperature data to correct the estimated battery temperature transition in the direction of eliminating the above deviation (low temperature side or high temperature side). For example, the ECU 100 makes a correction only for moving the estimated battery temperature transition to the low temperature side or the high temperature side without changing the shape of the estimated battery temperature transition. However, the present invention is not limited to this, and the ECU 100 may make a correction so as to change the shape of the estimated battery temperature transition according to the measured data of the battery temperature in accordance with a predetermined rule. In FIG. 2, points S1, S2, S3, and S4 show actual measurement data of the battery temperature acquired at the timings t1, t2, t3, and t4, respectively. Although the details will be described later, during the neglected period of the vehicle 1, the power of the ECU 100 is turned on at the timings t1, t2, t3, and t4 (for example, the start timing every hour), and the battery temperature is actually measured by the ECU 100. Then, by correcting the estimated battery temperature transition according to the actually measured data of the battery temperature indicated by the points S1, S2, S3, and S4, the corrected battery temperature transition indicated by the line k2 can be obtained.

The transition of the battery temperature tends to follow the transition of the outside air temperature with a certain time delay. It is considered that the reason for this is that it takes a certain amount of time for the battery temperature to change according to the change in the outside air temperature. Further, the peak temperature of the transition of the battery temperature tends to be higher than the peak temperature of the transition of the outside air temperature. It is considered that the reason for this is that the temperature of the battery rises due to the heat received from the sunlight. The correction battery temperature transition shown by the line k2 in FIG. 2 follows the correction outside air temperature transition with a delay time Δt10, and is higher than the temperature of the peak P1 of the correction outside air temperature transition by the temperature increase ΔT. It has a peak P2. By considering the temperature followability and the measured data of the solar radiation intensity when calculating the estimated battery temperature transition, the respective values of the delay time Δt10 and the temperature rise ΔT become appropriate magnitudes, and the correction is close to the actual transition. The battery temperature transition can be obtained.

The battery deterioration estimation device according to this embodiment can obtain the transition of the battery temperature with high accuracy from a small amount of actually measured data by obtaining the transition of the battery temperature (transition of the corrected battery temperature) by the method as described above. Then, the ECU 100 (particularly, the portion that functions as the deterioration amount estimation unit) estimates the deterioration amount of the battery from the transition of the battery temperature thus obtained. In the battery deterioration estimation device according to this embodiment, the number of actually measured data required to obtain the transition of the battery temperature (and by extension, the amount of deterioration of the battery) with sufficiently high accuracy is small. Therefore, necessary actual measurement data can be secured even if the power supply of the ECU 100 is not frequently turned on during the neglected period. Energy consumption can be reduced by reducing the number of times the power of the ECU 100 is turned on during the leaving period.

Hereinafter, the estimation of the deterioration amount of the battery performed by the ECU 100 will be described in detail with reference to FIGS. 3 to 14. The amount of deterioration is estimated for each cell (lithium ion battery) constituting the assembled battery 10 for the assembled battery 10 mounted in the luggage space of the vehicle 1. The cell that is the target of this estimation will be referred to as the "target cell" below.

FIG. 3 is a flowchart showing a processing procedure for estimating the amount of deterioration of the cell executed by the ECU 100 while the vehicle 1 is running. The process shown in this flowchart is called from the main routine at predetermined time intervals (for example, in a cycle of 5 minutes or less) and repeatedly executed.

With reference to FIG. 3, the ECU 100 acquires an actually measured value (temperature Tx) of the temperature of the target cell and stores it in the memory 102 (step S11). The signal (detected value) of the temperature sensor 23 of the monitoring unit 20 corresponds to the measured value of the temperature of the target cell.

The ECU 100 creates a temperature frequency distribution using the measured value of the temperature of the target cell and stores it in the memory 102 (step S12). If the temperature frequency distribution is already stored in the memory 102, the temperature frequency distribution may be updated. Next, the ECU 100 calculates the deterioration amount Dx using the temperature frequency distribution and the deterioration rate β, and stores it in the memory 102 (step S13). The deterioration amount Dx corresponds to the capacity reduction amount of the target cell. Then, the ECU 100 integrates the current deterioration amount Dx with the previous deterioration amount (deterioration amount ΣD stored in the memory 102), and adds the current deterioration amount ΣD (deterioration amount ΣD stored in the memory 102). The value of is updated (step S14). The processes of steps S12 to S14 are the same as those of steps S27 to S29 of FIG. 4, which will be described later. Details of the temperature frequency distribution and the deterioration rate β will be described later.

FIG. 4 is a flowchart showing a processing procedure for estimating the amount of deterioration of the cell executed by the ECU 100 during the neglected period of the vehicle 1. The process shown in this flowchart is called from the main routine at predetermined time intervals (for example, in a cycle of one hour or more) and repeatedly executed. The power of the ECU 100 is turned off during the neglected period of the vehicle 1, but the power of the ECU 100 is turned on at the execution timing of the process shown in FIG. 4 (starting timing of the ECU 100). Then, when all of the series of processes shown in FIG. 4 is executed by the ECU 100, the power of the ECU 100 is turned off again. In this embodiment, the execution cycle of the process shown in FIG. 4 is set to 1 hour.

With reference to FIG. 4, the ECU 100 acquires an actually measured value (temperature Tx) of the temperature of the target cell and stores it in the memory 102 (step S21). The signal (detected value) of the temperature sensor 23 of the monitoring unit 20 corresponds to the measured value of the temperature of the target cell.

Next, the ECU 100 acquires weather prediction information (various types of weather prediction data described later), actual measurement data of the outside air temperature, and actual measurement data of the solar radiation intensity by communication, for example (step S22). Specifically, the communication device 110 acquires the above-mentioned data corresponding to the position (region) of the vehicle 1 from a website on the network 200, for example, in response to a request from the ECU 100, and transmits the data to the ECU 100. Further, the communication device 110 may acquire the above data from another vehicle traveling near the vehicle 1 by vehicle-to-vehicle communication.

Each measured data of outside air temperature and solar radiation intensity includes, for example, measured values every 10 minutes in the last hour. That is, in addition to the current measured values, the measured data of the outside air temperature and the solar radiation intensity are measured 10 minutes ago, 20 minutes ago, 30 minutes ago, 40 minutes ago, and 50 minutes ago, going back from the present to the past. Includes a value.

The weather forecast information includes, for example, the predicted minimum temperature of today's outside temperature, the predicted maximum temperature of today's outside temperature, today's "sunrise" predicted time, today's predicted south-central time, and today's "sunset". Includes the predicted time and the next day's "sunrise" predicted time.

The ECU 100 estimates the transition of the outside air temperature by using the weather prediction information acquired in step S22 and the estimation formula (1) shown below (step S23). The estimation formula (1) is an example of correspondence information showing the relationship between the weather prediction information and the transition of the outside air temperature, and is stored in the memory 102 in advance.

Outside air temperature = (T _max −T _min ) × sinωt + T _min … (1)
In the estimation formula (1), T _max represents the predicted maximum temperature _{of today's outside air temperature, and T min} represents the predicted minimum temperature of today's outside air temperature. Further, ωt corresponds to the phase (angle).

The ECU 100 can estimate the transition of the outside air temperature by performing the fitting according to the estimation formula (1) based on the above weather prediction data. FIG. 5 shows an example of the estimated outside temperature transition obtained by such fitting.

With reference to FIG. 5, today's "sunrise" predicted time is at phase 0 ° of estimation formula (1), and "today's predicted south-central time + 2 hours" is estimated at phase 90 ° of estimation formula (1). By fitting so that the predicted time of "sunrise" of the next day coincides with the phase of 180 ° of (1), the estimated outside temperature transition as shown by the line k11 can be obtained. The position of the peak P11 of the estimated outside temperature transition corresponds to "today's predicted south-central time + 2 hours".

As described above, the estimated outside temperature transition can be obtained. Then, the ECU 100 stores the estimated outside air temperature transition in the memory 102.

With reference to FIG. 4 again, the ECU 100 corrects the estimated outside air temperature transition using the actual measurement data of the outside air temperature acquired in step S22 (step S24). FIG. 6 is a diagram showing an example of the corrected outside air temperature transition obtained by such correction. In FIG. 6, the measured data S10 corresponds to the measured data of the outside air temperature acquired in step S22. Further, the period Δt1 is a period corresponding to the execution cycle of the process of FIG. 4 (the period from the previous execution to the current execution). In this embodiment, the period Δt1 is 1 hour. During the period Δt1, the temperature of the target cell is not detected (step S21).

With reference to FIG. 6, the estimated outside air temperature transition shown by the line k11 is shifted to the high temperature side with respect to the actually measured data S10. Therefore, the ECU 100 corrects the estimated outside air temperature transition to the low temperature side according to the actually measured data S10. By this correction, the corrected outside air temperature transition as shown by the line k12 can be obtained. The position of the peak P12 of the corrected outside temperature transition corresponds to "today's predicted south-central time + 2 hours" as in the above-mentioned estimated outside temperature transition.

As described above, the corrected outside temperature transition can be obtained. Then, the ECU 100 stores the corrected outside air temperature transition in the memory 102.

With reference to FIG. 4 again, using the corrected outside air temperature transition obtained in step S23, the measured data of the solar radiation intensity acquired in step S22, and the temperature followability obtained in advance and stored in the memory 102, The transition of the battery temperature is estimated (step S25). As a result, the estimated battery temperature transition can be obtained.

FIG. 7 is a diagram showing an example of the estimated battery temperature transition. With reference to FIG. 7, the estimated battery temperature transition as shown by the line k21 can be obtained from the corrected outside air temperature transition shown by the line k12. The estimated battery temperature transition follows the corrected outside air temperature transition with a delay time Δt2. That is, the estimated battery temperature transition has a peak P21 at a timing t21 later by a delay time Δt2 than “today's predicted south-central time + 2 hours”. The delay time Δt2 corresponds to the above-mentioned temperature followability. The temperature of the estimated battery temperature transition of the peak P21 is higher by sunlight temperature rise [Delta] T _A than the temperature correction ambient temperature changes in the peak P12. The amount of increase in the solar radiation temperature is the amount at which the peak temperature of the transition of the battery temperature rises due to the heat received from the solar radiation. ECU100 refers to the solar radiation temperature rise calculation information stored in advance in the memory 102, it is possible to obtain the solar radiation temperature rise [Delta] T _A from the measured data of solar irradiance above. Insolation temperature increase calculation information includes, for example, the measured value of the intensity of solar radiation, the measured timing of the irradiance (i.e., the phase of the estimation equation irradiance is measured (1)), the relationship between the solar radiation temperature rise [Delta] T _A It is the corresponding information indicating, and is obtained in advance by an experiment or the like and stored in the memory 102. In the embodiment, the delay time Δt2 is 4 hours, the solar radiation temperature rise [Delta] T _A was 6.5 ° C..

The estimated battery temperature transition can be obtained as described above. Then, the ECU 100 stores the estimated battery temperature transition in the memory 102.

With reference to FIG. 4 again, the ECU 100 corrects the estimated battery temperature transition using the measured data of the temperature of the target cell acquired in step S21 (step S26). FIG. 8 is a diagram showing an example of the temperature transition of the corrected battery obtained by such correction. In FIG. 8, the actual measurement data S20 corresponds to the actual measurement data of the temperature of the target cell acquired in step S21. Further, the period Δt1 in FIG. 8 indicates the same period as the period Δt1 in FIG.

With reference to FIG. 8, the estimated battery temperature transition shown by the line k21 is shifted to the higher temperature side with respect to the actually measured data S20. Therefore, the ECU 100 corrects the estimated battery temperature transition to the low temperature side according to the actually measured data S20. By this correction, the correction battery temperature transition as shown by the line k22 can be obtained. In the corrected battery temperature transition, the battery temperature of the period Δt1 during which the temperature of the target cell is not detected (step S21) is interpolated.

The correction battery temperature transition can be obtained as described above. Then, the ECU 100 stores the correction battery temperature transition in the memory 102.

With reference to FIG. 4 again, the ECU 100 creates a temperature frequency distribution in the period Δt1 (FIG. 8) using the correction battery temperature transition obtained in step S26, and stores it in the memory 102 (step S27). If the temperature frequency distribution is already stored in the memory 102, the temperature frequency distribution may be updated. The temperature frequency distribution is heat history information received by the battery, and more specifically, information indicating the frequency for each battery temperature.

FIG. 9 is a diagram showing a temperature frequency distribution created in the examples. The line k31 in FIG. 9 shows the temperature frequency distribution. In the embodiment, the ECU 100 repeatedly executes the process of FIG. 4 in a cycle of 1 hour to create a temperature frequency distribution as shown by the line k31.

With reference to FIG. 9, the horizontal axis represents the temperature of the target cell, and the vertical axis represents the frequency (that is, the number of integrations in which the temperature of the target cell was the temperature indicated by the horizontal axis). In the temperature frequency distribution shown by the line k31, a value close to the actual frequency was obtained even in the region R1 on the high temperature side, which is difficult to detect with high accuracy.

With reference to FIG. 4 again, the ECU 100 calculates the deterioration amount Dy using the temperature frequency distribution created in step S27 and the deterioration rate β acquired by the following method, and stores the deterioration amount Dy in the memory 102. (Step S28). The deterioration rate β is a coefficient corresponding to the rate of decrease in cell capacity. The deterioration amount Dy corresponds to the capacity reduction amount of the target cell. The ECU 100 can obtain the deterioration amount Dy by multiplying the frequency in the temperature frequency distribution by the deterioration rate β. However, the deterioration rate β changes depending on the temperature of the battery. Therefore, the ECU 100 obtains the deterioration rate β of each temperature by referring to the T-β correspondence information stored in the memory 102 in advance. The T-β correspondence information is correspondence information indicating the relationship between the battery temperature (cell temperature) and the deterioration rate β, and is obtained in advance by an experiment or the like and stored in the memory 102. FIG. 10 is a diagram showing an example of T-β correspondence information.

With reference to FIG. 10, the horizontal axis represents the reciprocal of the cell temperature (1 / T), and the vertical axis represents the natural logarithm (ln (β)) of the deterioration rate. The line k40 defines the relationship between the cell temperature (T) and the deterioration rate β. More specifically, the line k40 defines the relationship in which the deterioration rate β increases as the cell temperature (T) increases. The deterioration rate β of each temperature is obtained by the line k40. Due to the temperature dependence according to the Arrhenius equation, 1 / T and ln (β) tend to have a substantially proportional relationship, as shown by the line k40.

With reference to FIG. 4 again, the ECU 100 integrates the current deterioration amount Dy with the previous deterioration amount (deterioration amount ΣD stored in the memory 102) and stores the current deterioration amount ΣD (stored in the memory 102). The value of the deterioration amount ΣD) is updated (step S29). The amount of deterioration ΣD corresponds to the amount of decrease in capacity from the initial state of the target cell.

The ECU 100 may acquire the initial capacity of the target cell from the memory 102, and obtain the capacity retention rate from the initial capacity of the target cell and the current deterioration amount ΣD of the target cell. The capacity retention rate is the ratio of the current cell capacity to the initial cell capacity (eg, percentage). The larger the capacity retention rate (closer to 100%), the smaller the amount of deterioration of the cell.

Although the execution frequency of the process of FIG. 4 is low, the current deterioration amount ΣD of the target cell can be obtained with sufficiently high accuracy by repeating the series of processes shown in FIG. The ECU 100 compares the deterioration amount ΣD thus obtained with the threshold value stored in the memory 102 (hereinafter, referred to as “deterioration determination threshold value”), and the deterioration amount ΣD exceeds the deterioration determination threshold value. If so, a predetermined process (hereinafter, referred to as "deterioration process") may be performed. The deterioration determination threshold value may be a fixed value or may be variable depending on the situation of the vehicle 1 and the like. As an example of the processing at the time of deterioration, it is possible to narrow the usable SOC range of the assembled battery 10 and to strengthen the limitation of the input / output power of the assembled battery 10. However, the present invention is not limited to this, and the deterioration processing may be a processing for prohibiting the use of the cell or a processing for notifying the user that the cell has deteriorated. The notification process may prompt the user to exchange cells.

As described above, in the battery deterioration estimation device according to this embodiment, the ECU 100 is started at the start timing of every hour during the leaving period of the vehicle 1, and the battery temperature (temperature of the target cell) is determined from the transition of the outside air temperature. (Step S25), and the estimated battery temperature transition is corrected by the actual measurement data (step S26). Further, in the battery deterioration estimation device according to this embodiment, not only the transition of the battery temperature but also the transition of the outside air temperature first estimates the transition of the outside air temperature (step S23), and then the estimated transition of the outside air temperature. Is corrected by the measured data (step S24). According to such a method, it is possible to obtain the transition of the battery temperature with high accuracy from a small amount of actually measured data even when the vehicle 1 is left unattended. Then, by estimating the amount of deterioration of the battery from the transition of the battery temperature obtained with high accuracy (steps S27 to S29), the amount of deterioration of the battery can be estimated with high accuracy.

FIG. 11 is a diagram conceptually showing the transition of the battery temperature obtained by the battery deterioration estimation method according to this embodiment. With reference to FIG. 11, by executing the process of FIG. 4 during the neglected period of the vehicle 1, the power of the ECU 100 is turned on at the timings t1, t2, t3, and t4 (starting timing every hour), and the ECU 100 turns on the power of the ECU 100. The battery temperature is detected (step S21). By detecting the battery temperature, actual measurement data of the battery temperature as indicated by points S1, S2, S3, and S4 can be obtained. Further, by performing the processes of steps S22 to S26, the correction battery temperature transition as shown by the line k2 can be obtained. In this way, the battery temperature in each period of the timings t1 to t2, t2 to t3, and t3 to t4 can be interpolated.

FIG. 12 is a diagram conceptually showing the transition of the battery temperature obtained by the battery deterioration estimation method according to the comparative example. With reference to FIG. 12, in this comparative example, the battery temperature is detected at timings t1, t2, t3, and t4 (timing every hour) by executing the process of FIG. 3 in a cycle of 1 hour (step S11). ) Was performed, and actual measurement data of the battery temperature indicated by points S1, S2, S3, and S4 was obtained. Then, the battery temperatures in each of the timings t1 to t2, t2 to t3, and t3 to t4 were linearly interpolated to obtain the transition of the battery temperature as shown by the line k3.

FIG. 13 is a diagram showing a temperature frequency distribution created by the battery deterioration estimation method according to the comparative example. With reference to FIG. 13, in the temperature frequency distribution shown by the line k32, the frequency of the region R2 on the high temperature side was lower than the actual frequency.

FIG. 14 is a diagram showing a transition of the capacity retention rate of the target cell obtained by the battery deterioration estimation method according to the example and the comparative example. In FIG. 14, the line k51 shows the transition according to the embodiment, and the line k52 shows the transition according to the comparative example. Further, the timing t31 indicates the initial stage (at the start of use of the target cell), and the timing t32 indicates 10 years after the initial stage. In the transition according to the example, the capacity retention rate at timing t32 was 83.1%. In the transition according to the comparative example, the capacity retention rate at timing t32 was 86.2%.

With reference to FIG. 14, the transition according to the example shown by the line k51 was closer to the actual transition than the transition according to the comparative example shown by the line k52. That is, the capacity retention rate shown in the transition according to the comparative example was higher than the actual capacity retention rate. If on the basis of transition of the comparative example is performed processing upon the aforementioned degradation, actual degradation during processing even capacity retention rate is below the deterioration determination threshold value C _A of the object cell (power limit, etc.) is not performed, The target cell is likely to be overcharged. When the target cell is overcharged, lithium is likely to be deposited on the negative electrode surface of the target cell (lithium ion battery). On the other hand, when the above-mentioned deterioration treatment is performed based on the transition according to the embodiment obtained with high accuracy, the upper limit SOC of the SOC range used is lowered when the capacity retention rate of the target cell becomes low. Therefore, the limit of the input power (charging power) of the target cell can be strengthened. Due to such power limitation, precipitation of lithium on the negative electrode surface of the target cell (lithium ion battery) can be accurately suppressed.

In the above embodiment, the ECU 100 estimates the amount of deterioration for each cell constituting the assembled battery 10. However, the present invention is not limited to this, and the ECU 100 may estimate the deterioration amount of the entire assembled battery 10 by using the measured data indicating the overall temperature of the assembled battery 10.

The object to which the battery deterioration estimation device of the present disclosure is applied is not limited to the above-described embodiment. For example, instead of the hybrid vehicle, a vehicle other than the hybrid vehicle (electric vehicle, etc.) may be applied. Further, a cell battery may be applied instead of the assembled battery.

The embodiments disclosed this time should be considered to be exemplary in all respects and not restrictive. The scope of the present invention is shown by the scope of claims rather than the description of the embodiment described above, and is intended to include all modifications within the meaning and scope equivalent to the scope of claims.

1 vehicle, 10 sets of batteries, 20 monitoring units, 21 voltage sensors, 22 current sensors, 23 temperature sensors, 30 PCUs, 41, 42 MGs, 50 engines, 60 power dividers, 70 drive shafts, 80 drive wheels, 100 ECUs, 101 CPU, 102 memory, 110 communication device, 200 networks.

Claims (2)

It is a battery deterioration estimation device that estimates the amount of battery deterioration.
The outside air temperature acquisition unit that acquires the actual measurement data of the outside air temperature,
Battery temperature measurement unit that acquires actual battery temperature data,
An outside air temperature estimation unit that estimates changes in outside air temperature,
Using the actual measurement data of the outside air temperature, the outside air temperature correction unit that corrects the transition of the estimated outside air temperature, and the outside air temperature correction unit.
A battery temperature estimation unit that estimates the transition of the battery temperature from the corrected transition of the outside air temperature by using the battery temperature tracking property with respect to the outside air temperature obtained in advance.
Using the measured data of the battery temperature, the battery temperature correction unit that corrects the transition of the estimated battery temperature, and the battery temperature correction unit.
A deterioration amount estimation unit that estimates the deterioration amount of the battery from the corrected battery temperature transition,
Equipped with a,
The deterioration estimation device for the battery is activated at a periodic start timing in a predetermined period, acquires the actual measurement data of the battery temperature and the actual measurement data of the outside air temperature, and estimates and estimates the transition of the outside air temperature. The transition of the outside air temperature is corrected by the measured data of the outside air temperature, the transition of the battery temperature is estimated from the corrected transition of the outside air temperature, and the estimated transition of the battery temperature is corrected by the measured data of the battery temperature. Configured to
The battery deterioration estimation device is a battery deterioration estimation device in which the power is turned off during the predetermined period except for the start timing . Each of the battery and the deterioration estimation device for the battery is mounted on the vehicle.
The predetermined period is a neglected period of the vehicle in which neither the traveling control of the vehicle nor the charge / discharge control of the battery is performed.
The amount of deterioration of the battery during the leaving period of the vehicle is estimated from the transition of the corrected battery temperature.
The battery deterioration estimation device according to claim 1, wherein the amount of deterioration of the battery during the traveling period of the vehicle is estimated from the measured data of the battery temperature.

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