JP2014013245A - Battery deterioration model generation and updating method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a battery deterioration model generation and updating method.SOLUTION: A battery deterioration model generation and updating method includes steps of: transmitting a deterioration parameter record data of a battery to a battery application management center; recording the deterioration parameter record data in a database and updating the deterioration model of bettery using the deterioration parameter record data by the battery application management center; and searching an item of deterioration model data corresponding to the battery from the database, and when any item of deterioration model data corresponding to the battery is not found, updating the battery deterioration model based on a battery deterioration relevant parameter and a newly calculated deterioration value, and generating a corresponding data item.

Description

  The present invention relates to a method and system for obtaining a degree of deterioration of a battery, and a secondary battery operating system based on the method and system. Specifically, the present invention relates to a method and a system for acquiring the degree of battery deterioration of an electric vehicle. Accurately acquiring the battery deterioration level, the remaining battery level can be conveniently and rationally measured, and the secondary usage related to various effective use and distribution of the battery based on the acquired remaining level information. A battery management system is realized.

  At present, energy conservation and environmental protection are already the focus issues that are generally attracting attention in each industry. As the automobile industry is actively developed, new energy vehicles are becoming an important new industry in many countries. New energy vehicles have advantages such as energy saving and environmental protection compared to conventional internal combustion engine vehicles. However, the current new energy vehicle cannot satisfy the needs of general users because it is difficult to develop industrial production and market on a large scale due to the problem of the battery itself. These challenges include the low energy density of the battery. For example, the current lithium ion battery has an energy density of about 150 wh / kg, but the energy density of gasoline is 10000 to 12000 wh / kg. In addition, since the battery has poor high-speed charging capability, the time for full charge is too long. Full charge will take approximately 3-5 hours using the current charge capability. The general consumer usually cannot accept such a charge rate except when charging at home. Even if a fast charging method of non-saturated charging is used, it usually takes about 30 minutes. In addition, the cost of the battery is high. For example, currently, a lithium-ion battery has a unit cell capacity of 3 to 5 RMB / wh, and one car has a battery cost of tens of thousands to hundreds of thousands of RMB. Yes. Also, battery safety may be required. Batteries have much higher energy storage than mobile terminal device built-in batteries, and are more likely to experience collisions, extrusions, and high temperatures under extreme conditions, which further increases safety requirements. This further increases the cost of the electric vehicle battery.

  The above-mentioned problems of the battery will eventually be solved by the advancement of the technology of the battery itself, but it is difficult to fundamentally solve the problems of high cost and slow charging speed within a short period of time. It is.

  In view of the long battery charging time and high cost, these problems have already been solved by adopting a new battery operation mode. One existing operation mode is a mode in which the battery is replaced instead of being charged. The battery replacement time can be shortened to 1 or 2 minutes compared to the battery charging time. Another method related to battery replacement is a method of battery rental. Since the owner of the electric vehicle only has to pay a battery rental fee instead of purchasing an expensive battery, the initial purchase cost of the electric vehicle can be greatly reduced. The other method is a method for indirectly reducing the cost at the stage of use as a car battery by effectively utilizing the battery until the end of its life. For example, a battery can be diverted as a storage battery in a home or commercial facility when the electrical capacity is reduced to a certain ratio (for example, 80%) of the rated capacity due to the degree of performance deterioration. Furthermore, when the battery capacity drops to a certain value, it can be recovered and used. Furthermore, as another method, since the battery of an electric vehicle can be distributed or exchanged between owners of the vehicle, the cost of the battery can be reduced.

  The battery may be designed as a standard battery pack having a relatively small capacity. In the electric vehicle, the number of standard battery packs can be freely set according to the use needs. The electric capacity of the standard battery pack may be determined by the battery capacity required for the daily travel distance during daily use. The current electric vehicle has only one battery pack (assembled battery), and the battery pack (assembled battery) is also exchanged for battery replacement.

  However, each of the above methods has a common technical problem. That is, a method for accurately knowing the degree of deterioration of a battery is required. In other words, it is necessary to accurately know the remaining life of the battery, and based on the residual use value of the battery, the value is determined as a value judgment standard such as rental or distribution.

  An existing method for acquiring the degree of deterioration of the battery and the remaining life of the battery is a method of acquiring the degree of deterioration of the battery by conducting a charge / discharge experiment of the battery. However, this method needs to fully charge the battery and perform high-speed discharge. It takes a very long time for measurement and damages the battery, so it is not applied for the purpose of battery operation.

  Moreover, the existing battery exchange system is mainly used for the mobile terminal device. In the rental usage process, the cost of the rental battery is determined by estimating the remaining value before and after rental using two parameters: the number of times the battery of the mobile terminal device has already been charged and the battery usage time. Is supposed to be done. Here, the usage environment of a mobile terminal device such as a mobile phone is relatively stable, and its usage method is also relatively fixed. For this reason, depending on the deterioration degree of the battery of the mobile terminal, the number of times of charging, and the usage time, the deterioration degree of the battery of the mobile terminal can be roughly reflected. However, for an electric vehicle, the power of the electric vehicle and the degree of deterioration of the battery vary depending on the road surface condition of the driving, the season, the climate environment, the driving habits of the driver, the difference between the in-vehicle electric device and the usage situation, etc. Presents.

  FIG. 4 shows a schematic diagram of a deterioration degree curve of a battery and a battery (EV) used in the mobile terminal device. As shown in FIG. 4, the horizontal axis indicates the ratio between the battery usage time and the number of times the battery is charged, and the vertical axis indicates the remaining battery level. It can be seen from the curve of the deterioration level of the battery used in the mobile terminal apparatus shown in FIG. 4 that the battery deterioration level curve of the mobile terminal device is linear. The number of times the battery is charged and the usage time can largely reflect the degree of deterioration of the battery. For electric vehicles, a non-linear relationship that cannot be determined between the battery deterioration level and the number of times of charging and usage time is used. It cannot be reflected.

  The method of estimating the battery degradation level of existing electric vehicles is based on different vehicle types (vehicle weights, specifications of electrical devices such as in-vehicle air conditioners), different road conditions in which the vehicle travels, and the external environment. Considering. In this method, a part of each deterioration factor or a value of the deterioration degree of a battery under a certain typical condition is acquired and stored by an actual test. Thereafter, in the actual battery deterioration degree calculation process, the current battery deterioration degree is determined by examining the entry most similar to each situation stored in the database. However, this method is a method of estimating the degree of deterioration of the battery under various actual situations by creating a battery deterioration degree database having a finite number, but in actual use of electric vehicles, Since the actual parameters of each factor that affects the battery degradation level are not completely the same as the corresponding parameters stored in the database, the actual degradation level of the battery is the degradation level that can be retrieved from the degradation database. Will cause an error. FIG. 5 shows the difference in the deterioration curve between different batteries. As shown in FIG. 5, the actual deterioration degree modes of different batteries are different, and there is a deviation from the reference model.

  Furthermore, under the operation mode of battery rental or battery replacement, batteries from different manufacturers may be used for different car models from different car companies. Due to the inherent characteristics of car batteries (for example, lithium ion batteries), even if batteries with the same model number are used, there are individual differences. Individual differences are more pronounced between batteries from different manufacturers. Therefore, the possible combinations of interactions between various factors that affect the degree of battery degradation are enormous. In the case of use in this way, such a battery deterioration degree measurement method cannot provide the measurement accuracy required for battery rental operation because the error is further expanded. Establishing a larger degradation database in advance can reduce the measurement error to some extent, but various factors such as battery type, car model number, road conditions, driving habits, and climatic conditions Considering the complexity of the effect on the degree of degradation of the database, it is very difficult to establish in advance a database that can satisfy the measurement accuracy requirements.

  An object of the present invention is to provide a method and a system for acquiring a battery deterioration degree that can accurately acquire the deterioration degree of the battery in view of the above-described problems in the prior art. According to the method and system of the present invention, a battery deterioration degree with high accuracy can be obtained by sequentially updating the deterioration degree model using the parameters related to the deterioration degree and performing calculation using the updated deterioration degree model. It is done.

  Another object of the present invention is to realize various methods necessary for battery rental, replacement, distribution, reuse, and the like based on the acquired information on the degree of battery deterioration.

  According to one aspect of the present invention, battery data and data relating to the degree of deterioration of the battery are collected, the collected battery data and data relating to the degree of deterioration of the battery are processed, and parameters relating to the degree of deterioration of the battery are acquired. A step of constructing a battery deterioration degree model using the acquired parameters relating to the battery deterioration degree, a step of updating the battery deterioration degree model using the parameter relating to the battery deterioration degree, the battery deterioration degree model, and the battery The method of acquiring the deterioration degree of a battery including the step which calculates the deterioration degree of a battery using the parameter regarding the deterioration degree of is provided.

  According to another aspect of the present invention, the battery data and the data relating to the degree of deterioration of the battery are collected, the collected battery data and the data relating to the degree of deterioration of the battery are processed, and the parameter relating to the degree of deterioration of the battery is obtained. In addition, a data collection device for sequentially storing the parameters in the deterioration parameter history table and a battery deterioration degree model are constructed using the acquired parameters relating to the battery deterioration degree, and the battery using the parameters relating to the battery deterioration degree. A deterioration degree model construction / update device for updating a deterioration degree model of the battery, and a deterioration degree calculating device for calculating the deterioration degree of the battery using parameters relating to the battery deterioration degree model and the battery deterioration degree. Provide a system to acquire.

  According to another aspect of the present invention, the step of transmitting the battery deterioration degree parameter history table data to the battery application management center, the battery application management center records the deterioration degree parameter history table data in the database, and the deterioration degree The step of updating the battery deterioration level model using the parameter history table data, and searching the database for the deterioration level model data item corresponding to the battery, and if there is no deterioration level model data item corresponding to the battery, the battery deterioration level A method for generating / updating a battery deterioration level model is provided that includes updating a battery deterioration level model based on related parameters and a newly calculated deterioration level value and generating a corresponding data item.

  In addition, the present invention has submitted a data application subsystem that utilizes the degradation degree related information. These data application subsystems may include battery application locations such as battery charging stations, battery exchange stations, home charging, various electric vehicles, and power storage systems. The data application subsystem uses the deterioration level data provided by the system and the relationship between the deterioration level data, battery-related data, and parameters related to the deterioration level, battery replacement, charging, management, vehicle operation, etc. Provide support to.

  According to the present invention, in the model update operation, it is necessary to estimate other parts of the model by adopting a certain mathematical expression based on the initial deterioration degree, so that a certain error may occur. The present invention has also submitted a method for calibrating the degree of deterioration model. Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings. As a result, the above-described object and other objects, features, and superior points of the present invention will become more apparent.

It is a block diagram which shows the basic composition of the system which acquires a battery degradation degree based on this invention. It is a block diagram which shows the system configuration | structure which added the calibration module of the deterioration degree model to the system shown in FIG. It is the block diagram which showed the system configuration which added the data analysis and application module to the system shown in FIG. It is a schematic diagram which shows the deterioration degree curve of the battery used for the mobile terminal device, and a battery (EV). It is a schematic diagram which shows the difference between the deterioration degree curves of different battery individuals. It is a block diagram which shows the preferable Example which combined the system which acquires the battery degradation degree based on this invention, and another system. FIG. 3 is a schematic diagram showing one embodiment of a parameter collection subsystem and a transmission network of a battery deterioration factor. It is a figure which shows the detailed structure of the information exchange adapter module shown by FIG. It is a figure which shows the Example of the data application subsystem in the system for measuring the deterioration degree of the battery which concerns on this invention. It is a schematic diagram which shows the Example of the production | generation / update process of the battery degradation degree model which concerns on this invention. It is a schematic diagram which shows the process in which a battery remaining charge value is calculated using a battery deterioration degree model. It is a schematic diagram which shows a battery residual value estimation module. It is a module schematic diagram of the management system which the system for acquiring the battery degradation degree which concerns on this invention manages. It is a figure which shows the workflow of a DCL module. It is a workflow of the deterioration degree calculation module according to the present invention.

  Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the drawings. In order to avoid confusion with the understanding of the present invention, in the description of the invention, descriptions of details and functions that are not necessary for the present invention are omitted.

The following describes a preferred embodiment of a system for obtaining the degree of battery degradation according to the present invention. The present invention is not limited to the specific embodiments shown here, and is applicable to a system for acquiring the degree of battery degradation of the present invention and its application according to a specific situation without departing from the gist of the present invention. It should be understood that various combinations can be made. In accordance with one preferred embodiment of the present invention, the system for obtaining the degree of battery degradation of the present invention includes several interacting subsystems: That is,
1) Battery degradation factor parameter collection subsystem;
2) Battery degradation model construction / update subsystem;
3) Battery degradation degree calculation subsystem;
4) DCL storage system for parameters related to battery degradation.
Moreover, the system for acquiring the battery deterioration level according to the present invention may further include the following subsystems. That is,
5) Degradation model calibration system;
6) Data application subsystem based on battery degradation data.

  FIG. 1 is a block diagram showing a basic configuration of a preferred embodiment of a system for acquiring a battery deterioration degree according to the present invention. According to this embodiment, the system for acquiring the battery deterioration degree includes a collection subsystem 11 connected to the battery system, a model construction / update subsystem 12, a deterioration degree calculation subsystem 13, and a deterioration degree parameter. And a history table (DCL: degradation state log) storage subsystem 14. The degradation level related parameter collection subsystem 11 is connected to the battery system, collects various types of battery data from the battery or its management system, and transmits information such as degradation level data to the battery system. The collection subsystem 11 processes various collected primitive data and other data of the collected battery to obtain a parameter relating to the degree of deterioration, and then transmits the data obtained by processing to the model construction / update subsystem 12. . The collection subsystem 11 also transmits various parameters of the collected battery and battery data obtained by processing to the DCL storage subsystem 14 for storage. The degradation level calculation subsystem 13 is connected to the DCL storage subsystem 12 and the model construction / update subsystem 12 respectively, and acquires parameters related to the degradation level and the updated degradation level model from these two subsystems. Then, the degree of deterioration of the battery is calculated. Thereafter, the calculated result is transmitted to the DCL storage subsystem for storage. The DCL storage subsystem stores various battery data and parameters as corresponding battery history data.

  FIG. 2 is a diagram showing a system structure in which the model calibration subsystem 15 is added to the system for obtaining the deterioration degree of the battery shown in FIG. In order to acquire the basic data of the battery, as one example, the deterioration model calibration subsystem 15 may acquire the battery data using a battery charge / discharge cycle test or other methods. The deterioration level model calibration subsystem 15 constructs or calibrates an initial deterioration degree model of the battery based on the numerical value of the battery deterioration degree actually measured and the parameters relating to the deterioration degree obtained by collecting. To update the battery deterioration model. Further, the deterioration level model calibration subsystem 15 applies, for example, a portion obtained by non-measurement such as mathematical calculation so as to bring the model closer to the actual situation based on the acquired battery data. Update and calibrate. Thereby, the deterioration degree data obtained by the model calculation becomes more accurate.

  FIG. 3 is a diagram showing a system structure in which the data analysis / application subsystem 16 is added to the system for obtaining the deterioration degree of the battery shown in FIG. The data analysis / application subsystem 16 analyzes data such as DCL data, degradation level related parameters, degradation level calculation results, and supplies the analysis results to an external system for use.

  FIG. 6 is a block diagram showing an embodiment of the entire structure in which a system for acquiring the degree of deterioration of a battery according to the present invention and a corresponding subsystem are combined. The embodiment shown in FIG. 6 shows a difference in the configuration of the subsystem as compared with the structure of the system for acquiring the degree of deterioration of the three batteries shown in FIGS. In the embodiment shown in FIG. 6, the application subsystem corresponding to the system for acquiring the deterioration level of the battery as a whole includes an information exchange adapter 61, a deterioration measuring device 62, a data analyzing device 63, A deterioration degree model construction / update device 64, a deterioration degree parameter history table (DCL) database 65, a battery application subsystem 66, and a data application subsystem 67 are included. As shown in FIG. 6, the information exchange adapter 61 is connected to the battery application subsystem 66, and collects and temporarily stores parameters related to the deterioration degree of the battery. Here, the battery application subsystem 66 includes cases where the battery can be applied, such as an electric vehicle, an electric motorcycle, an electric bicycle, and other battery application systems.

  In FIG. 6, the information exchange adapter 61 and the battery application subsystem 66 can constitute a parameter collection subsystem for a battery deterioration factor. The subsystem obtains battery DCL data from one or more battery modules or related battery DCL data from other related controllers and provides it to the degradation subsystem via the transmission network. In addition, this subsystem temporarily stores the calculation result obtained from the degradation degree subsystem for future use. For a detailed description, refer to “Battery Degradation Model Configuration Method and Degradation Parameter Collection Subsystem” described later.

  The transmission line between the battery degradation factor parameter collection subsystem and other devices may constitute a battery degradation factor parameter transmission network. The transmission network transmits battery DCL data, degradation-related parameters, and corresponding time parameters. The deterioration model building / updating means 64 and the DCL database 65 can constitute a battery deterioration model building / updating subsystem. The deterioration degree model construction / update means 64 constructs and updates the deterioration degree initial model. The deterioration degree initial model may be a deterioration degree calculation model formed using battery data obtained by means such as experiments. Furthermore, a deterioration degree update model may be automatically generated based on this initial model and actual battery DCL data. In the generation process of the deterioration level update model, the calculation accuracy of the deterioration level model improves as the amount of data of the battery DCL increases, and the calculated battery deterioration level data becomes more accurate, so-called update of the deterioration level model. is there. The detailed operation process relating to the deterioration model building / updating means 64 refers to a “battery deterioration model building / updating subsystem” described later.

  The deterioration degree measuring device 62 and the data analyzing device 63 can constitute a battery deterioration degree calculating subsystem. Here, the deterioration degree measuring device 62 is based on the deterioration degree model, the battery DCL data obtained from the DCL database, and the battery parameters obtained directly from the battery data collection subsystem. Calculation of degree data. After specific deterioration degree data is obtained, the deterioration degree measuring device 62 uses these data as parameters. The deterioration degree measuring device 62 calculates the deterioration degree data of the corresponding battery based on the updated deterioration degree model supplied by the deterioration degree model updating means 64, and supplies and stores it in the DCL database. For a detailed deterioration degree calculation method, refer to a “battery deterioration degree calculation subsystem” described later.

  The data analysis module 63 provides a service to the degradation degree data application subsystem described below. The data analysis module 63 uses the DCL data in the DCL database, the data relating to the battery deterioration degree, the parameter relating to the battery deterioration degree obtained by the processing, and the corresponding deterioration degree data, for example, the charging current of the battery It is possible to analyze certain parameters of the battery that are noted in the external data application subsystem, such as the relationship with the corresponding deterioration degree data, and supply these analysis results to the external deterioration degree data application system. In FIG. 6, the data application subsystem based on the degree of deterioration of the battery and the information exchange adapter 61 are connected via a transmission network. The data application subsystem receives and uses the data temporarily stored in the data temporary storage memory in the information exchange adapter 61. For example, the data application subsystem determines which method is best to operate based on the deterioration degree data stored in the temporary data storage memory, which method is best to charge the battery, etc. To do. For a detailed description, refer to “Data Application Subsystem Based on Battery Degradation” described later.

  In actual application, the degree of degradation of battery performance is the result of multiple factors resulting from a joint action. For example, the battery is deteriorated by charging / discharging or leaving the battery. Different types of batteries, such as lead-acid batteries, nickel metal hydride batteries, and lithium batteries, have different degradation characteristics. By studying and experimenting with various battery mechanisms, it is now possible to describe the degradation characteristics of various batteries using a basic degradation model. However, the initial deterioration model created for a certain type of battery can reflect only the average state of the deterioration characteristics of the battery. Regarding the actual deterioration degree characteristics of individual batteries, as shown in FIG. 5 above, there is a significant error between individuals.

  According to a preferred embodiment of the system for acquiring the battery degradation level of the present invention, the battery individual model is obtained by technical processing such as data prediction, update, and calibration using a battery initial degradation model of a known or existing battery. It is possible to automatically generate an updated deterioration degree model that can accurately reflect the deterioration degree characteristics of the.

  The present invention is composed of several parts such as construction of an initial deterioration degree model, generation of an update deterioration degree model, acquisition of deterioration degree, and use of deterioration degree. Each part includes a corresponding method and subsystem. According to one embodiment of the present invention, an in-vehicle battery deterioration measuring device may be employed. A single battery deterioration measuring device may be adopted. Moreover, a networked battery deterioration degree measurement system may be employed, or a measurement system in which a network and a measurement device are mixed may be employed.

  Each part according to the present invention may be formed by each corresponding subsystem. The collection subsystem collects battery data for various parameters related to battery degradation, performs various pre-processing on these data, and then transmits the data to the battery degradation via the transmission network. It is transmitted to the subsystem that performs the calculation. A battery deterioration degree is calculated based on a preset deterioration degree model. In addition, in order to obtain a highly accurate calculation result, expansion, update, and calibration processes were adopted for the deterioration model. Based on the battery deterioration level information obtained by the above calculation, the battery or the device using the battery is controlled by performing corresponding operation control or supplying the corresponding information. The request can be satisfied efficiently.

  In the present invention, the number of standard battery packs may be freely arranged, or some or all of the standard battery packs may be freely replaced. In the present invention, a battery pack having such characteristics is referred to as a free battery pack (FBP). By adopting the free battery pack, the initial purchase cost of the electric vehicle can be reduced more effectively, which helps to promote the spread of the electric vehicle. By combining the free battery pack and the battery rental operation mode, it is possible to further reduce the daily use cost of the electric vehicle.

  The usage pattern of the battery described in the present invention includes a plurality of usage patterns such as an electric vehicle, a hybrid vehicle, a plug-in hybrid vehicle, and a distance extension type electric vehicle. Moreover, this usage pattern may include a usage pattern of an electric bicycle or an electric motorcycle. Moreover, the battery described in the present invention includes different configurations. The configuration is, for example, freely expanding, replacing, using and controlling the battery pack in addition to having a fixed battery pack that cannot be partially replaced or expanded with respect to the battery pack (sometimes referred to as an assembled battery). A possible free battery pack FBP may be included. The battery according to the present invention may be a battery for non-driving applications. For example, it may be a storage battery for storing electric power.

  Hereinafter, a specific method for realizing a system for measuring the degree of deterioration of a battery according to the present invention and a configuration of a corresponding subsystem will be described.

1. Battery Degradation Model Configuration Method and Degradation Parameter Collection Subsystem The degree of battery degradation in electric vehicles is a result of the interaction of many factors. In order to accurately calculate the degree of deterioration of the battery, it is necessary to record parameters of each degree of deterioration factor. The deterioration degree of the battery is determined based on the values of these deterioration degree parameters. These parameters mainly include a battery attribute parameter fb, a battery charge / discharge related parameter fp, a battery usage environment parameter fe, and a vehicle parameter fv (for example, a car parameter, an electrical level, etc.).

  The reason for constructing the battery deterioration degree model is to establish the relationship between the battery deterioration degree and the respective deterioration degree parameters. This relationship can be expressed by a mathematical relational expression. It can also be shown in a table or database. The initial deterioration model and the update deterioration degree model of the battery can be expressed by the following equations. That is,

Battery-like degradation model Ds = Func (fb, fp, fe, fv) (1)

  In the battery deterioration model Ds described above, in addition to the battery attribute parameter fb and the battery charge / discharge related parameter fp, the battery use environment parameter fe and the vehicle parameter fv are also considered.

  The above model reflects the relationship between the battery deterioration degree and the battery deterioration degree parameter at a certain measurement time. Such a model based on the deterioration degree parameter at a certain time can better reflect the deterioration degree situation when a specified battery is used for a specific device. However, for usage patterns such as battery rental, such a model based on instantaneous parameters cannot constitute a complete deterioration model. In addition, the value of the actual deterioration degree of the battery cannot be calculated. Therefore, since the present invention not only collects the current deterioration level parameters but also holds the previous deterioration level parameters, a specific deterioration level parameter history table (DCL) for a certain battery is formed. DCL can be expressed by the following equation (2).

DCL_t
= DCL_t-1 + (fb_t, fp_t, fe_t, fv_t) (2)

  Therefore, in the present invention, the deterioration model is a function of the intrinsic DCL and can be expressed by the following equation (3).

Deterioration degree model = Func (DCL_t) (3)

  The battery correlation parameters can be divided into battery attributes, operation parameters, environmental parameters, vehicle parameters, operation modes, user information, and the like in detail. Here, the battery attributes are battery ID (ID for uniquely identifying the corresponding battery in the entire network), battery brand, battery model number, battery type, battery quality, battery shipping date, battery shipping price, battery It may include the rated full charge. The operation parameter may include the number of times of charging, battery scheduled collection data, battery triggered collection data, and past measurement data. The environmental parameters may include environmental temperature and environmental humidity. The vehicle parameters may include a vehicle manufacturer ID, a vehicle type ID, a vehicle weight, a vehicle ID, and a vehicle electrical level parameter (medium / high / low level). The operation mode may include examples of various road conditions (general urban areas, congested urban areas, smooth urban areas, highways, mountains, plains). The user information may include the user ID and the type of user driving style (slow driving, driving with rapid acceleration, driving with rapid deceleration / braking). Here, it should be noted that each parameter listed above is only an example, and the present invention is not limited thereto. The present invention may be employed, which may include other more parameters.

  The operation parameters may include battery scheduled collection data, battery triggered collection data, and past measurement data. Here, the battery scheduled collection data may include, for example, collection time, total voltage, total current, battery temperature, battery pack voltage, battery pack current, battery pack internal resistance, battery pack SOH (health state), The present invention is not limited to these. The battery-triggered collection data may include, for example, the collection time, the SOC before charging (charging state), the SOC after charging, the charging amount, the charging current, the SOC before discharging, the SOC after discharging, the discharging amount, and the discharging current. However, the present invention is not limited to these. The past measurement data may include, for example, a plurality of past deterioration levels and times corresponding to a plurality of past deterioration levels, but the present invention is not limited to these.

  These parameters are examples of the parameters fb, fp, fe, and fv that can be collected. In an example of a typical parameter collection system, the following parameters are parameters that need to be collected.

  FIG. 7 is a schematic diagram illustrating one embodiment of a parameter collection subsystem and a transmission network for a battery degradation factor. The battery system shown on the left side of FIG. 7 includes a battery management system (BMS) and a battery. The battery portion may include a plurality of battery modules. The central part of FIG. 7 is the internal structure of the information exchange adapter. The right part is a transmission network. In some cases, the left battery system may not include a BMS system.

  In FIG. 7, data that needs to be collected multiple times is acquired from the battery system periodically or inspired by a data collection module. Information on the battery itself may also be read once from the battery system. When a plurality of battery modules are included, the data collection and writing process is the same as that of the battery module 1.

  When the battery system includes BMS, each BMS is connected to a corresponding battery module. Alternatively, the entire BMS of the battery system is connected to a plurality of battery modules. The BMS collects battery data necessary for the information exchange adapter via a data bus. By deploying a BMS system under the conditions of different system needs, you can adjust which data needs to be collected, convert which data is collected or convert data that is not needed at one time Perform filtering and transmit to the information exchange adapter after completion.

  The information exchange adapter includes a data collection module, a data temporary storage device, and a data transmission module. The data collection module acquires data from the BMS or the battery module itself via a specific interface such as USB, RS232, serial port or other dedicated data interface and stores it in the data temporary storage device. In addition, other data acquired by the data communication network, for example, a deterioration degree calculation result received from the deterioration degree subsystem is also stored in the data temporary storage device. The data transmission module transmits the battery DCL data stored in the temporary data storage device to the deterioration degree subsystem via the data communication network. Further, the degradation analysis data stored in the temporary data storage device is also transmitted to the data application subsystem via the data transmission module.

  FIG. 8 shows a detailed structure of the information exchange adapter shown in FIG. As shown in FIG. 8, the information exchange adapter includes a DCL data collection interface 51, a DCL data temporary storage device 52, and a DCL data transmission interface 53 (a data transmission module is not shown for the sake of simplicity). Contains. The DCL data collection interface 51 receives other parameters that cannot be acquired from the battery system other than receiving parameters related to the battery system, such as parameters such as vehicle ID and vehicle body electrical level, and these data from other correlation control units. Can be obtained via the data bus. In addition, for a part of the local history data that needs to be stored, for example, past deterioration degree data and corresponding time, the DCL data collection interface 51 reads the corresponding data from the deterioration degree subsystem via the network. All the data acquired by the above process is written in the DCL data temporary storage device 52. The DCL data transmission interface 53 provides data obtained from the DCL data temporary storage device 52.

The DCL data temporary storage device 52 can be divided into two logical data blocks, a long-term storage area and a temporary storage area. The long-term storage area stores, for example, data necessary for long-term storage including mainly “battery attribute” parameters and “past measurement data” in “operation parameters”. Since “battery attribute” does not change within the life cycle of the battery, it is not necessary to change it after the first writing. On the other hand, for the “operation parameter”, for example, entries of the contents of past measurement data are accumulated a plurality of times and written in the storage area. This “operation parameter” is used later as an important deterioration degree measurement history. However, some of these data may be deleted due to storage capacity limitations. This is different from the former. Generally, such a situation occurs when a new past deterioration degree data entry is written. If the storage capacity is insufficient, a new entry needs to replace an old entry. The entries to be replaced include the following entries. That is:
1. The oldest degradation data entry of the oldest recording time in the area,
2. An entry of “the shortest interval time between two adjacent entries” in the area;
3. And “entry having the smallest deterioration degree difference between two adjacent entries” in the corresponding area.

  Each of the above three types of entries corresponds to three rules. Specifically, regarding which replacement rule to employ, one of the three may be selected, but two or three of the three may be employed.

  For DCL data collected by the system, the collection format at the time of battery discharge can be shown in Table 2 below.

  The battery charging time collection format can be shown in Table 3 below.

  The data format transmitted to the DCL module can be shown in Table 4 below.

  Battery parameter collection can be divided into one-time collection, scheduled collection, and inspired collection. The one-time collection target may be, for example, a battery attribute. Since the parameter included in the battery attribute does not change in the life cycle of each battery, the corresponding parameter is recorded inside the battery by one-time collection. The target of regular collection may be, for example, a part of operation parameters. During the entire life cycle of the battery, the battery undergoes uninterrupted charging and discharging processes. Since the battery discharges slowly even when not in use, it has a certain influence on the degree of deterioration of the battery. For this reason, in order for the battery to consider the state in the life cycle, it is necessary to collect certain parameters of the battery at a constant cycle. The collection period may be determined by the BMS. Moreover, you may newly set by another system. The subject of inspiration collection may be, for example, inspiration collection in a broad sense. Some of the operation parameters described above, for example, related parameters in the charging process may be included, and after the battery is distributed, the vehicle parameters and user information that need to be recorded may be included. In addition, each time the degree of deterioration of the battery is measured, data and time related to the obtained degree of deterioration should be recorded.

  Hereinafter, a method for collecting various parameters of the battery deterioration level will be described.

  Currently, many batteries have a battery management system BMS (Battery Management System) that manages charging / discharging of the battery and records and stores basic information of the battery. Therefore, necessary parameters may be collected using the BMS inside the battery. In general, in the case of a free battery pack (FBP), information may be acquired by an assembled battery management system that manages a plurality of FBP battery packs in addition to the BMS of a single battery pack. The parameters that cannot be collected by the BMS may be collected by an information collecting device added outside the battery pack. Also, other sensors may be mounted to acquire more information that cannot be provided by the BMS, or the BMS may be changed. Various sensors may be used to collect the corresponding parameters of the battery.

  The information that needs to be collected further includes parameters of the vehicle itself and electrical level parameters. These parameters cannot be obtained by BMS or battery internal sensors. A vehicle controller (for example, ECU) acquires parameters of the vehicle itself and electrical level parameters, and transmits them to a system of the present invention via a data bus (for example, LIN / CAN / FlexRay on the vehicle) for recording. Do. In addition, it has parameters that are difficult to obtain by the above method, for example, user-related information. The parameter collection method and apparatus of the present invention are not limited to this, and if necessary, other more effective parameter recording methods, for example, manual input with a dedicated terminal, external data with dedicated software, wired, A download method to the system of the present invention may be included in the wireless method. Of course, this method can be applied to all parameters.

  The collected primitive battery DCL data (for example, related parameters such as voltage, current, weight, etc.) cannot be used for the structure and update of the deterioration model as it is. Moreover, it cannot be used for calculation of the deterioration level as it is. In order to achieve the above object, we convert all DCL data of a battery into four parameters related to the degree of battery deterioration based on the four kinds of parameters described above. The four parameters are as follows.

Parameter E = func (fe)
Parameter V = func (fv)
Parameter P = func (fp)
Parameter B = func (fb)

  As described above, a set of DCL data obtained by collecting each time is divided into four types and then converted, and four parameters: parameters that can indicate the corresponding set of DCL data abstractly: E, parameter V, parameter P, and parameter B can be acquired, and a four-dimensional parameter group (E, V, P, B) is configured. The four-dimensional parameter group (E, V, P, B) is, for example, battery ID, battery brand, battery model number, battery type, battery quality, battery shipping date, battery shipping price, rated full charge, discharge current, discharge voltage. It may include data such as battery internal resistance and environmental temperature, and may be converted from these data. This four-dimensional parameter group can be used as it is for the structure and update of the deterioration model.

  The parameter relating to the degree of battery deterioration obtained by collecting and converting may be temporarily or permanently stored in the built-in storage device of the information exchange adapter. Further, it may be stored in a dedicated storage device outside the information exchange adapter. The external data storage device may be connected to the information exchange adapter via a local common or dedicated interface. Moreover, you may connect to an information exchange adapter with the system of a communication network. The memory may store all the collected primitive data and the converted four-dimensional parameter group, but may store only the abstracted four-dimensional parameter group.

2. Battery Degradation Factor Parameter Transmission Network The parameter collection subsystem acquires various parameters related to the battery deterioration information, and these collected parameters are used to calculate the battery deterioration and transmit The data is transmitted to the data center of the degradation degree calculation subsystem via the network. The parameter transmission network includes wired transmission (twisted pair cable, coaxial cable, optical fiber, ADSL, FTTH, power line communication HD-PLC / PLC, etc.), wireless transmission (as shown in the intermediate transmission network in FIG. 2G / 3G / 4G, GSM (registered trademark) and other wide-area wireless communications, and WiFi, Bluetooth (registered trademark), UWB, RFID, and other short-range wireless transmission methods) The

Further, the connection form of parameter transmission may be a plurality of methods described below. For example, a method of directly transmitting from a battery pack (set) to a data center. The parameters stored in the battery are transmitted in a wireless manner via an external communication device of the battery pack.
Also, battery collection parameters and parameters stored in the battery may be transmitted to the data center through the battery charging / battery exchange device. In this case, when performing battery replacement or charging for the battery by the battery charging / battery exchange station, the parameters in the battery storage device are read through a dedicated matching interface between the battery charging / battery exchange device and the battery, These parameters are transmitted via a communication line between the battery charging / battery exchange device and the data center. In some cases, the battery charging / battery exchange device can also transmit data to the battery. For example, after acquiring related information, the battery exchange station can calculate battery deterioration degree information such as the proportion of deterioration degree and the remaining value. Thereafter, the deterioration level information and the time corresponding to the corresponding information are transmitted to the battery by the above-described three methods, that is, the dedicated device and interface, the wired network, and the wireless network.

  Further, the charging information of the battery may be transmitted to the battery by the above transmission method. The battery may directly exchange data with the data center. For example, the battery exchange station itself is a power center. Alternatively, all battery exchange stations in the entire network are data centers (cloud computing).

  The battery exchange station may not store only a small amount of data or may not store data due to limited conditions. In this case, after the battery exchange station acquires the DCL data of the battery, it needs to be transmitted to the data center. This data transmission method can use the wired network or the wireless network described above.

  As indicated above, in the special case where all battery switching stations have the power of a data center, i.e. the entire network has realized cloud computing, between the data center and the data center, as required Data exchange can be performed freely. Similarly, the data transmission method may use a wired network method or a wireless network method.

3. Battery Degradation Model Construction / Updating Subsystem The battery degradation level is a result of the joint action of multiple types of factors such as battery characteristics, usage status, and environmental conditions. A complex relationship with nonlinearity is exhibited. One possible method is to create a relationship between the degree of deterioration and each collected parameter by using a statistical or experimental method, and to determine the degree of deterioration of the battery using this relationship. However, the degradation level model created with finite experimental data accurately reflects only the degradation level of the battery under the condition of some parameters. For most other parameters, the estimated degradation level is actually An error will occur between the values.

  The battery deterioration degree model of the present invention is a basis for calculating the battery deterioration degree. The battery deterioration degree model uses not only the current deterioration degree information of the battery but also past history information related to the battery deterioration degree information. For this reason, the battery deterioration level model of the present invention is a function related to the battery deterioration level history DCL parameter. The deterioration model may be stored in the battery, in the assembled battery, in the battery exchange station, or in the data center.

  The battery degradation model in the present invention is constructed using the following method.

One of them. Construction of initial degradation model.
The initial deterioration model of the battery may be acquired by experiment or other methods. This model is a database of the correspondence relationship between the battery deterioration degree and various parameters related to the deterioration degree. As the value of each parameter relating to the collected deterioration degree, the closest deterioration degree value can be searched from the deterioration degree database. Regarding the battery of an electric vehicle, the deterioration degree parameter includes a battery parameter, a vehicle type and a parameter of an in-vehicle electric device, a road surface condition parameter of vehicle driving, an environmental parameter, and the like. According to the above description, all of these parameters related to the degree of deterioration are converted into a four-dimensional parameter group (E, V, P, B). For this reason, it can be considered that the initial deterioration degree model is a table composed of the deterioration degree D and these four-dimensional parameter groups (E, V, P, B). The number of each parameter can be determined by the range of possible values of each parameter in the four-dimensional parameter group and the accuracy of quantization. If the numbers of parameters (E, V, P, B) are m, n, k, and t, respectively, the number of rows N in this table is the product of m, n, k, and t. . At the same time, each row of the table is obtained by sequentially sorting the values of the parameters (E, V, P, B) in ascending or descending order of magnitude. Table 5 shows the configuration of the initial deterioration model when m, n, k, and t are numerical values of 1/2/2/2. The initial deterioration degree model is generated by a rapid charge / discharge cycle, other measurement data, and the like.

  There are many influence factors of the battery deterioration degree, and the result of the interaction between a plurality of types of factors causes an error between the value of the battery deterioration degree and the value of the deterioration degree of the initial model. In particular, in the case of the battery rental application method, there is a possibility that the error between the initial model and the actual deterioration degree value is further expanded. In order to reduce this error and delete it sequentially, the battery deterioration degree model of the present invention is expanded based on the initial deterioration degree model, thereby generating a new deterioration degree corresponding to a combination of different deterioration degree parameters. . This is a data generation method for generating a new deterioration degree value of the expansion deterioration degree model based on the deterioration degree value of the initial deterioration degree model. As a method of expanding the value of the degree of deterioration of the simplest model, a method using linear data interpolation is used. Here, the present invention is not limited to this, and a non-linear interpolation method or other methods may be adopted to generate the degradation value of the new expansion degradation model. The data generation method may be fixed or may be changed according to changes in conditions. The more data transmitted from the degradation parameter collection system, the larger the degradation database. In order to avoid that the database is too large, one quantization accuracy is set for all the deterioration degree parameters, and the scale of the extended deterioration degree database is determined. When creating the degradation model, a certain type of battery from a certain manufacturer may be targeted, but a single confirmed battery may be targeted. The deterioration level model created for one confirmed battery can effectively delete the deterioration level measurement error caused by the difference between individual batteries. Table 6 below shows new deterioration degree table items obtained by linear data insertion.

Second. Updating the Deterioration Model After describing the structure of the initial deterioration model, it is necessary to update the model based on the deterioration parameters obtained by actual collection and conversion. The four-dimensional parameter group of the new deterioration degree data is as follows:

(El_m_2, vl_i_2, pl_j_2, bl_k_2)

  In the present invention, since it can be observed directly, one parameter V can be expressed using v1_i_2 when positioned between V1 and V2. Here, i represents that the value is at a position between vl and v2 (for example, V1_25_2 represents that this value is at a position 25% greater than vl between vl and v2. The same applies to parameters in other columns. According to the current construction method of this table, before a new line data item is determined, it is necessary to determine two existing line data items related to it. The basis for determining these two related row data items must satisfy the condition that all the corresponding parameters of the existing data item and the new data item are equal or adjacent to each other. Next, it is necessary to search the corresponding 4D parameter group and the corresponding table item from the initial model. As shown in Table 6, according to the new parameter group, it can be clearly seen that the related table items in the initial model are (el, v1, p1, b1), (e2, v2, p2, b2). . In the initial table item, all combinations within the range of the values of all parameters are covered. Therefore, dx and dy values can be obtained. In Table 6, there are some number of table items between dx, dz, and dy. At this time, dz can be calculated by the following model update formula.

  In the above formulas, W (e), W (b), W (v), and W (p) respectively indicate the weights when the four parameter strings in the model calculate the degree of deterioration. This can also be understood as the effect of four types of parameters on the degree of battery degradation. According to the above formula, the deterioration degree data dz corresponding to a new parameter group is obtained. Thereafter, a new table item is inserted into the data table according to the order before and after each column based on the sorting rule described above.

  In certain cases, the E and B columns are finite and have some range of values, in other words, the E and B column values are represented using discrete data. The V and P columns have some range of limits that are finite in the initial row data, but the actual data may be intermediate values located between two finite ranges. . That is, the values of the V column and the P column are expressed using continuous data.

  Hereinafter, the generation process for updating the table item will be described in detail.

  On the other hand, when searching for a specific table item, one approximation result can be provided. That is, when searching for the numerical value of the degree of deterioration corresponding to one specific parameter combination, the set of data that needs to be searched is compared with the parameters of the existing specific table items in the table to a certain degree of similarity. When it reaches, the unit time deterioration degree of this specific table item may be directly adopted. Otherwise, the above method is repeated and the calculation is performed with the initial table items.

  On the other hand, it can be considered that all the data items in the table are sorted according to the four parameter columns (E / V / P / B). That is, in Table 5, first, the table items having the same E column value are sorted according to the E column so that they are adjacent to each other. Next, the table items having the same E column value are sorted according to the V column. The P / B column is sorted by analogy sequentially. After each new deterioration degree table item is obtained, it is necessary to insert an appropriate row into the table according to the sort rule as described above. In a future calculation, the inserted row will have the same function as the initial initial degradation table item. Tables 7 and 8 below describe changes before and after the table item data is updated and inserted into the initial table item as an example.

  Temporarily, the deterioration degree table item that needs to be inserted is E1 / B2 / P1 — 23 — 2 / V2 — 43 — 3. The two row data items in Table 7 are table items related to the new table item. A partial table after insertion is shown in Table 8 below.

  From the above table, after a new table item has been inserted, a new table item has been inserted at the corresponding position in the table as reference data for future calculations according to the sorting rules described above. I understand.

  Further, in view of the current production status of lithium batteries, even if batteries are produced in similar manufacturers, similar types, or similar lots, there is a large difference between the individual batteries. Further processing may be performed on the row B indicating the battery type. For example, in the data collection process, a specific battery ID is collected and transmitted, and when the data is stored in the deterioration degree table, the battery ID is also written in the table. That is, in one similar table, there is actually one single table for each individual battery. Of course, the data may be stored separately as a single table, but the data corresponding to all the individual batteries may be continuously stored in one large table by the above method. In this case, when the table data is initialized, a new table item can still be inserted and the model can be calculated and updated by the above method. However, if the data amount increases gradually, the battery individual that needs to be searched may reduce the deterioration degree parameter in the table to three (E / P / V) when there is a sufficient data amount in the database. The processing method is the same as described above.

  After describing the insertion method of the new table item, the position, and the selection of the related table item, the calculation of Dz in Table 8 will be described below. The four parameters corresponding to Dz are El / B2 / Plj2 / V2k3, respectively. Each of j and k indicates the difference (in percentage) between the P parameter and the V parameter and the corresponding parameter in the adjacent row, and new based on the previously obtained deterioration degree data of the two related table items. D column is calculated. That is, the degree of deterioration in unit time corresponding to these four values is calculated. V1-V2 and P2-P3 assume that the influence on the D-column approximates a linear change. In this way, two weight values W (v) and W (p) can be determined for the V and P columns. In this way, the related value of the D column can be calculated by the following equation (4).

  By such calculation, the degree of deterioration in unit time is obtained from the initial table item and the measured characteristic parameter. Thus, the model is updated with the newly added table item.

  Hereinafter, calibration and update of the battery deterioration degree model will be described. In the process of updating to the deterioration model using the DCL data and the above argon rhythm, the newly added data item can be calculated based on one mathematical argon rhythm, resulting in an estimation error of the deterioration degree value. there is a possibility. Furthermore, there is a possibility that the error is further accumulated and transmitted, so that the error of the deterioration degree model is further expanded. In response to this problem, the present invention has proposed an error calibration and update method. According to the present invention, a certain battery is selected as a calibration sample according to a certain method, and an accurate deterioration degree of the battery can be obtained by a rapid charge / discharge test on the battery or other methods under a specific condition. After inputting the exact deterioration value of this battery and the corresponding deterioration degree history information into the deterioration degree model, it is necessary to calibrate against the deterioration degree in the model and all the deterioration degree values derived from it. Updates will be made to gradually improve the accuracy of the degradation model in the course of uninterrupted construction and use. Table 9 below shows the newly inserted data items.

  In Table 9, the dz value is calculated by the other table item D column values, and may have a certain error. When performing calibration, the battery is subjected to a rapid charge / discharge cycle test using measurement conditions consistent with e1_m_2, v1_i_2, p1_j_2, and bl_k_2 to obtain the true degradation degree data d of the battery. Is used to calibrate the dz value in the table. Here, different calibration methods may be employed. The first is to replace the dz value in Table 6 with the d value. Part 2: Adopting a certain value between dz and d. After this row is calibrated, the other rows that this row is based on may be calibrated. As the calibration method, the calculation may be repeatedly performed using the model update formula described above.

4). Battery Deterioration Calculation Subsystem The battery deterioration calculation subsystem will be described below. Usually, in order to accurately determine the cost associated with battery replacement, a battery deterioration degree calculation process is performed when the battery is in circulation. At this time, the deterioration model is first updated based on the battery DCL data. Thereafter, the battery deterioration degree data is calculated, and then the DCL data and the battery deterioration degree data are transmitted to the DCL database and transmitted to the information exchange adapter via the data analysis system. Degradation level data is also transmitted to the information exchange adapter. In some special cases, for example, when it is impossible to connect to the data center database for a certain reason, the degradation level data is used when calculating the battery degradation level. In addition, the data application subsystem needs to acquire related information from the information exchange adapter.

  Normally, if the battery exchange station cannot make a data connection with the data center, it first updates the degradation model, then calculates the degradation data and then all the data that should be transmitted to the data center. May be stored locally at the battery exchange station so that when the degradation data is transmitted to the battery and data can be connected in the future, the relevant data is uploaded to the data center. Also, if the battery exchange station cannot calculate and store data, it communicates with the information exchange adapter through one specific device, then acquires the data temporarily stored in it and calculates its degradation data You may do it. The particular device described here is a device that is temporarily employed when the battery exchange station cannot provide services to the user (eg, when the battery exchange station calculation / storage device is unavailable). This device may be a handheld device or a fixed device. This device acquires data by connecting to an information exchange adapter using an interface that can be used in combination with other devices, and calculates the basic deterioration level based on the acquired DCL data and the return deterioration data. Is called. It should be noted that this device can perform basic deterioration degree calculation only if it stores at least the initial model data.

In the above case, the DCL data and the deterioration degree data may be stored in a specific device. When the conditions of the battery exchange station are permitted, these data are uploaded to the battery exchange station and transmitted to the data center. In the above case, the DCL data and the deterioration degree data may be stored in the battery storage system. When permitting the condition of the battery exchange station, the above data is uploaded to the battery exchange station via a wired network, a wireless network, or directly through a specific interface.
The degree of deterioration can be conveniently calculated based on a database type deterioration degree calculation model. After processing based on the data collected by the DCL collection module, the following Table 10 is obtained. Table 10 shows the cumulative data of the degree of deterioration.

  Table 10 above shows various degradation parameter groups and their corresponding durations. By the following equation (5), the degree of deterioration after the previous deterioration degree measurement can be easily calculated.

Tl * D1 + T2 * D2 + ... + Tn * Dn (5)

  The current degree of deterioration of the battery is obtained by adding the degree of deterioration stored last time to the degree of deterioration calculated using Equation (5).

  FIG. 15 shows an operation flow of the deterioration degree calculation module according to the present invention. As shown in FIG. 15, first, DCL data is acquired, and the acquired DCL data is recorded and stored in a database. On the other hand, the battery deterioration model is updated based on the acquired DCL data. Thereafter, the deterioration level of the battery is estimated based on the DCL data stored in the DCL database and the updated deterioration level model.

5. Data Application Subsystem Based on Battery Degradation In existing battery management application systems based on battery degradation, the accuracy of battery degradation measurement is not high. Limited to estimating remaining amount. In the system for measuring the degree of battery deterioration according to the present invention, since the history information DCL of the degree of battery deterioration is stored and the battery deterioration degree information with high accuracy can be acquired, the present invention further improves the battery usage efficiency. Can be provided as a method.

  FIG. 9 shows a schematic diagram of a data application subsystem of a system for measuring the deterioration degree of a battery according to the present invention. As shown in FIG. 9, the information exchange adapter 91 of FIG. 9 is connected to the battery deterioration degree system 93 via the transmission network 92.

  As shown in FIG. 9, the application system 94 for measuring the degree of battery deterioration according to the present invention includes various electric vehicles such as electric vehicles, hybrid vehicles, electric motorcycles, electric bicycles, and charging stations, battery exchange stations, home charging systems, and the like. It is applied to various deterioration degree measurement cases and other application cases. Under the above application environment, the DCL data collected by the present system and the calculated battery deterioration degree data can cause various new applications. For example, the remaining value of the battery can be accurately calculated based on the battery deterioration degree data calculated for the present system. The remaining value of the battery can be easily calculated by the following equation (6).

Battery remaining value = Battery shipping value * Battery deterioration level (6)

  According to the remaining value of the battery, the corresponding value at the time of various applications such as rental, transfer, and recovery of the battery can be determined. For example, when a battery rental transaction occurs, the user needs to pay a certain cost, for example, a deposit. The height of the deposit is determined by the remaining value of the battery that the user intends to rent. When battery replacement occurs, the user needs to pay the price difference between the two batteries. The expense to pay is shown by the following formula (7).

Payment cost = (replacement battery remaining value−replacement battery remaining value) + (replacement battery remaining electrical capacity * power value−replacement battery remaining electrical capacity * power value) (7)

  Here, it is calculated based on the battery deterioration degree together with the remaining value of the replacement battery and the remaining value of the replacement battery. Also, when the battery is collected, it is necessary to calculate the remaining value of the battery based on the degree of battery deterioration.

  The DCL data and the degree of deterioration calculated and collected by the method and system for measuring the degree of battery deterioration of the present invention can provide valuable information services to battery users. Based on the DCL data stored in the database and the corresponding deterioration level data, the relationship between one or several parameters in the DCL and the deterioration level can be determined. Thereby, the deterioration rate of the battery can be reduced by corresponding control or operation.

  For example, by using a wireless network or a wired network system, the result obtained above is transmitted to a data receiving system of an electric vehicle or a hybrid vehicle in a certain data format. Based on the DCL and the degree of deterioration of each battery, control including the charge / discharge control and the battery connection method is performed on each battery by an in-vehicle battery management system based on the DCL and the degree of deterioration of each battery so as to be in a good operating state.

  In addition, the method and system for measuring the degree of battery deterioration according to the present invention can be obtained by collecting and calculating a large amount of battery deterioration factor data, for example, battery deterioration degree and battery type in different environments (temperature, humidity). Relationships can be acquired. By analyzing these data, the mechanism of the degree of battery deterioration can be analyzed and understood further deeply.

  In addition, the data calculated and collected by the method and system for measuring the degree of battery degradation according to the present invention can provide reference information for the battery charging process (for example, charging station charging, home charging, etc.). Corresponding control can be performed. For example, the optimal charging process in a self-adaptive manner based on the target requirements of different charging methods, such as the shortest charging time, the lowest power consumption of charging, and the least amount of deterioration given to the battery Parameters, for example, a charging voltage, a charging current, a charging dynamic method, and a charging stop condition can be set. The optimum charging process parameters under various charging methods can be obtained by theoretical or experimental methods. For example, various different charging current conditions can calculate and analyze the effect on battery degradation so that the charging station selects the best charging conditions. In addition, the influence of the different SOC (State of Charge) state on the battery deterioration degree can be calculated and analyzed so that the charging station selects the best method.

  In the entire operation process of the system for measuring the degree of battery deterioration according to the present invention, data that can be acquired includes battery DCL data, parameters relating to the degree of deterioration, battery deterioration degree data, and unit time deterioration degree control. Based on these data, further data applications can be provided in various ways. These applications can include several specific scenes, as shown on the left side of FIG. However, the present invention is not limited to this.

  1) Charging: The relationship between the charging current, the charging market, the charging depth, and the battery deterioration rate can be obtained by analyzing the past DCL data. After the optimal charging scheme is obtained by analysis, this data is provided to the charging control system of the battery charging station. The charging station charges as much as possible with the best (or second best) charging method, and slows the rate of battery degradation to the maximum. In some cases, when a charging speed is required, it may be analyzed which charging method is relatively good on the assumption of rapid charging in the DCL history database. For example, the effect of the charging depth during rapid charging on the degree of battery deterioration is compared, and the result is similarly transmitted to the control system of the charging station.

2) Battery replacement: In one typical system, the battery degradation data calculated by the system of the present invention is used to calculate the remaining value of the battery.
When a battery rental transaction occurs, the user needs to pay a certain cost, for example, a deposit. The height of the deposit is determined by the remaining value of the battery that the user intends to rent.

When the battery exchange occurs, the price difference between the two battery blocks that the user needs to pay is expressed by the above equation (7). Here, the remaining value of the exchanged battery and the remaining value of the exchanged battery are obtained by calculating the battery deterioration degree. The above formula (6) represents a battery remaining value calculation formula.
When battery recycling occurs, it is necessary to calculate the remaining value of the battery based on the degree of battery deterioration.

  3) Vehicle control: As shown in FIG. 9, the result of analysis for DCL may be transmitted to a battery user, for example, an electric vehicle user, in a wireless, wired or specialized device communication system. From these data, the influence of different driving methods on the battery deterioration degree, for example, the specific influence on the battery deterioration degree by the state in the form of vehicle speed, acceleration, deceleration, etc. can be obtained relatively easily. Accordingly, it is possible to cause the vehicle user to drive the vehicle so that the battery is in an optimal state, and to significantly reduce the deterioration rate of the battery.

  In other cases, for example, it can be obtained by analyzing a person's driving style, such as the normal vehicle speed and the acceleration / deceleration height. At the same time, analysis of the DCL data can be used to search for which type of battery (for example, which manufacturer's battery) can obtain optimal performance or lowest wear under this operating mode. These data are very useful for battery exchange stations.

  FIG. 10 shows a schematic diagram of an embodiment of the process of generating and updating the battery deterioration model according to the present invention. As shown in FIG. 10, in one typical example, the user of the A battery transmits the DCL of the corresponding battery to the BSC (Battery Application Management Center). The BSC first records the DCL data of the corresponding battery in a database. At the same time, the battery initial deterioration model is updated using the DCL data. On the other hand, a specific deterioration degree model corresponding to the A battery is searched from the database. If there is a specific degradation level model corresponding to the A battery, the specific degradation level model is updated based on the new DCL data of the currently input A battery. Otherwise, a specific deterioration degree model is generated based on the updated initial deterioration degree model and the current new data.

  In the process of generating and updating the battery deterioration degree model, the battery deterioration degree parameter history table data is transmitted to the battery application management center. The battery application management center records the deterioration degree parameter history table data in the database, and updates the deterioration degree model of the battery using the deterioration degree parameter history table data. If the deterioration level model data item corresponding to the battery is searched from the database and there is no deterioration level model data item corresponding to the battery, based on the parameter related to the battery deterioration level and the newly calculated deterioration level value. The battery deterioration model is updated, and the corresponding data item is generated.

  When the difference between the deterioration level related parameter of the deterioration level model and the collected battery deterioration level related parameter is larger than a predetermined value, a new data item of the extended deterioration level model is generated. Note that the magnitude of the predetermined value may be set based on the accuracy requirement of the deterioration degree model.

  FIG. 11 shows a schematic diagram of a process of calculating the battery remaining amount value using the battery deterioration degree model. FIG. 12 is a schematic diagram of the battery remaining amount estimation module. As shown in FIG. 11, in the process of calculating the battery remaining value, first, the DCL data of the battery A is uploaded to the data center or the battery exchange station. The data center or the battery exchange station updates the deterioration level model of the A battery based on the acquired DCL data. Thereafter, the remaining amount value of the A battery is calculated using the updated battery deterioration model and DCL data.

  12 includes a deterioration level model update module 121, a DCL database 122, and a deterioration level calculation module 123. The battery remaining amount estimation module shown in FIG. 12 performs the remaining amount calculation process shown in FIG. First, the degradation level model update module 121 updates the degradation level model of the battery using the uploaded DCL data of the A battery, and records the DCL data in the DCL database 122. Thereafter, the deterioration degree calculation module 123 calculates the remaining amount value of the A battery using the updated battery deterioration degree model and DCL data.

  Hereinafter, an embodiment of a system operating system for acquiring a battery deterioration level according to the present invention will be described. The BSC performs storage, information processing, and information use for the battery DCL data. After paying a certain membership fee, the battery user obtained the right to rent the battery, replace the battery, and expand or reduce the battery from the BSC. In the process of battery rental, replacement, battery expansion or contraction, the cost paid by the user depends on the remaining value of the battery calculated by the BSC based on the deterioration level model and the deterioration level related parameters. At the first rental, the BSC records the remaining value of the battery. When the battery is replaced, the BSC calculates the remaining value and the remaining electric capacity of the two battery blocks, and calculates the cost that the user should pay based on a certain cost ratio.

  In this example, the residual value calculation may not be accurate in some cases. For example, the amount of data in the database is too small, or the amount of data corresponding to the corresponding battery in the database is too small. At this time, certain compensation measures should be taken. For example, one experience model has been proposed. This empirical model can represent the degree of deterioration of a battery when a certain parameter changes a certain amount (for example, after a certain time) under average conditions. Next, the difference between the measured degradation level and the previously measured degradation level is obtained. The cost is calculated by comparing the difference between the degree of average deterioration obtained before and the degree of deterioration after, and taking a weighted average value. This method gradually decreases its effect as the total data amount and the data amount corresponding to the corresponding battery increase, and is eventually abolished. In other words, this method may be a compensation method at the initial stage of data. Another compensation method is that after one battery has been exchanged a sufficient number of times, there will be more and more DCL records and degradation measurement records in the database for this battery. With further development, the degree of deterioration of the corresponding battery will become more accurate. Since BSC can back-estimate the past deterioration degree of the corresponding battery based on a large amount of accurate data, the result obtained by back-estimation is compared with the past deterioration degree obtained at that time. This comparison result is used as a basis for compensation for past users at that time. In this case, the user can conveniently check all the compensation records in the course of his / her battery usage, and record the compensation records by other means such as continually saving the relevant records or obtaining compensation values. You can also choose to delete it.

  In one implementation, the BSC may be a distributed system. Each station has different data and has the same calculation ability. In general, it is assumed that all stations are connected to the Internet. When calculating the degree of deterioration, the greater the amount of data, the higher the accuracy of the obtained result. However, if one station cannot connect to the Internet or cannot obtain data from other stations, the battery's local data is insufficient, so that relatively accurate data cannot be generated. At this time, the compensation measures described above may be adopted.

  In view of even more extreme cases, the present invention provides yet another embodiment. When the user is unable to access the battery deterioration level database for some reason or when the deterioration level calculation module cannot be calculated using the deterioration level calculation module at the BSC station in which the user is currently located, even the deterioration level calculation result without accuracy can be obtained. It is not possible to be in a state where it is impossible to perform activities such as battery replacement. As a result, the battery's BMS has the battery degradation level measurement results, the initial model, the updated model, and the DCL data uploaded for a finite number of times in the past (the collected battery data, the data regarding the battery degradation level, and the battery degradation level). One storage area for storing (including parameters) should be left in advance. The amount of data may be determined by the storage space. When the above situation occurs, the battery needs to obtain one rough result of deterioration as a basis for battery replacement based on the finite history data, the initial model, and the update model. The BSC should record this result and have this station record be introduced into the database when the system can operate normally. At the same time, since the measurement result of this time is not accurate, it is necessary to compensate by the compensation method described above.

  According to the provisions of the national standard, when the full charge ratio of the battery is reduced to 80%, it cannot be used continuously as a battery. The BSC collects batteries with a full charge ratio of 80% or less of the collected batteries every time the battery is replaced, and is used as an energy storage method for storage batteries, small electric vehicles (electric motorcycles, electric bicycles), etc. Can be treated. Similarly, for the energy storage battery, it is necessary to detect the state of each battery. The battery should be disposed of when its battery degradation reaches a certain value. Otherwise, the life of other energy storage batteries will be affected. Therefore, the degradation degree measuring method of the present invention can be applied to the state detection of the energy storage battery as well.

  FIG. 13: has shown the module schematic diagram of the management system which the system for acquiring the battery degradation degree which concerns on this invention manages. As shown in FIG. 13, the DCL module 131 collects parameters relating to the degree of battery deterioration from a battery usage location, for example, an electric vehicle, and stores the collected parameters in the battery information database 132. The remaining battery level estimation module 133 calculates the remaining battery level based on the battery deterioration model and the collected battery parameters, and provides the remaining level value to the information providing module 135. The information providing module 135 supplies information about the battery to the BMS of the electric vehicle, and the BMS controls and adjusts the driving of the vehicle and / or other operation / control methods based on the DCL information. On the other hand, the battery information user 134 can use the battery supplied from the information providing module 135 to determine the operation method for battery supply and battery reuse.

  In other embodiments, DCL information usage will be described. Based on a lot of DCL information and the battery deterioration degree index obtained by updating the deterioration degree model based on this information and the initial deterioration degree model, the battery deterioration rate, the battery manufacturer, the battery type, the driving style, the driving road surface The relationship with important parameters such as the situation, each charging time, and each charging average current can be obtained relatively easily. These data can be operated commercially as information having commercial value.

  In other embodiments, the DCL includes, for example, fixed one-time information such as a battery ID and a battery shipping date, and also includes data that has been collected and recorded multiple times or collected and recorded multiple times. Here, the data periodically collected a plurality of times includes collection time, total voltage, total current, battery temperature, battery pack voltage, battery pack current, battery pack internal resistance, and battery pack SOH. The data collected multiple times includes one or more sets of pre-charge SOH, post-charge SOH, charge charge, charge current, pre-discharge SOH, post-discharge SOH, discharge charge, and discharge current.

  FIG. 14 shows an operation flow of the DCL module. In step S141, the DCL collection device collects parameters relating to the degree of deterioration of the collection battery, and then records the collected parameters in step S142. In step S143, the DCL collection device stores the collected parameters in the temporary storage device of the parameter collection subsystem. Temporarily store. In step S144, the BSC determines whether it is connected to the data center. If the BSC is connected to the data center, the DCL data collected in step S145 is uploaded. If it is determined in step S144 that the BSC is not connected to the data center, the process returns to step S141 to continuously collect DCL data.

In the above data, the data of multiple times of periodic collection shows some battery parameters collected at regular intervals in the battery life cycle based on a preset cycle. These parameters are mainly used to evaluate the relationship between the degree of battery deterioration and the change with time.
The data collected by inspiration several times is data that is not set in advance and is collected by the action of collecting the inspiration when an event occurs (for example, charging). Data collected by this action is mainly used to evaluate the influence of specific events (for example, charge / discharge, fitback braking) on the degree of battery deterioration.

Although the foregoing has described the present invention in terms of battery degradation factor parameter collection subsystem, battery degradation model construction / update subsystem, battery degradation calculation subsystem, and parameter DCL storage subsystem for battery degradation. It should be understood that the present invention does not change substantially even when the corresponding subsystem is replaced and the similar apparatus is used.
Thus far, the present invention has been described in terms of preferred embodiments. It should be understood by those skilled in the art that various other changes, substitutions and additions can be made in the present invention without departing from the spirit and scope of the present invention. Accordingly, it should be understood that the scope of the invention is not limited to the specific embodiments described above, and should be limited to the appended claims.

Claims (2)

Transmitting the battery deterioration degree parameter history table data to the battery application management center;
The battery application management center records the deterioration level parameter history table data in a database, and updates the battery deterioration level model using the deterioration level parameter history table data.
Search the database for a deterioration level model data item corresponding to the battery, and if there is no deterioration level model data item corresponding to the battery, based on the battery deterioration level related parameter and the newly calculated deterioration level numerical value A method for generating and updating a battery deterioration level model, including the step of updating the battery deterioration level model and generating a corresponding data item.   When the difference between the deterioration level related parameter of the deterioration level model and the parameter related to the deterioration level of the battery obtained by collecting and processing is larger than a predetermined value determined based on the accuracy requirement of the deterioration level model The method according to claim 1, further comprising: generating a new data item that extends the deterioration level model.

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